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Article

Recent Advances in Stimulation Techniques for Unconventional Oil Reservoir and Simulation of Fluid Dynamics Using Predictive Model of Flow Production

by
Charbel Ramy
1,
Razvan George Ripeanu
1,
Salim Nassreddine
2,
Maria Tănase
1,*,
Elias Youssef Zouein
3,
Alin Diniță
1 and
Constantin Cristian Muresan
1
1
Mechanical Engineering Department, Petroleum-Gas University of Ploiești, 100680 Ploiesti, Romania
2
Department of Chemical Engineering, Lebanese University Faculty of Engineering, Beirut P.O. Box 6573/1, Lebanon
3
Faculty of Engineering, Conservatoire National des Arts et Métiers, 292 Rue Saint Martin, 75003 Paris, France
*
Author to whom correspondence should be addressed.
Processes 2025, 13(4), 1138; https://doi.org/10.3390/pr13041138
Submission received: 14 March 2025 / Revised: 4 April 2025 / Accepted: 7 April 2025 / Published: 10 April 2025
(This article belongs to the Special Issue Recent Advances in Heavy Oil Reservoir Simulation and Fluid Dynamics)

Abstract

:
This research makes a strong focus on improving fluid dynamics inside the reservoir after stimulation for enhancing oil and gas well performance, particularly in terms of increasing the Gas–oil ratio (GOR) and injectivity leading to a better productivity index (PI). Advanced stimulation operation using new formulated emulsified acid treatment greatly improves the reservoir permeability, allowing for better fluid movement and less formation damage. This, in turn, results in injectivity increases of at least 2.5 times and, in some situations, up to five times the original rate, which is critical for sustaining reservoir pressure and ensuring effective hydrocarbon recovery. The emulsified acid outperforms typical 15% HCl treatments in terms of dissolving and corrosion rates, as it is tuned for the reservoir’s pressure, temperature, permeability, and porosity. This dual-phase technology increases injectivity by five times while limiting the environmental and material consequences associated with spent and waste acid quantities. Field trials reveal significant improvements in injection pressure and a marked reduction in circulation pressure during stimulation, underscoring the treatment’s efficient penetration within the rock pores to enhance oil flow and sweep. This increase in performance is linked to the creation of the wormholing impact of the emulsified acid, resulting in improved fluid dynamics and optimized reservoir efficiency, as shown by the enhanced gas–oil ratio (GOR) in the four mentioned cases. A critical component of attaining such improvements is the capacity to effectively analyze and forecast reservoir behavior prior to executing the stimulation in real life. Engineers can accurately forecast injectivity gains and improve fluid injection tactics by constructing an advanced predictive model with low error margins, decreasing the need for time-consuming and costly trial-and-error approaches. Importantly, the research utilizes sophisticated neural network modeling to forecast stimulation results with minimal inaccuracies. This predictive ability not only diminishes the dependence on expensive and prolonged trial-and-error methods but also enables the proactive enhancement of treatment designs, thereby increasing efficiency and cost-effectiveness. This modeling approach based on several operational and reservoir factors, combines real-time field data, historical well performance records, and fluid flow simulations to verify that the expected results closely match the actual field outcomes. A well-calibrated prediction model not only reduces uncertainty but also improves decision making, allowing operators to create stimulation treatments based on unique reservoir features while minimizing unnecessary costs. Furthermore, enhancing fluid dynamics through precise modeling helps to improve GOR management by keeping gas output within appropriate limits while optimizing liquid hydrocarbon recovery. Finally, by employing data-driven modeling tools, oil and gas operators can considerably improve reservoir performance, streamline operational efficiency, and achieve long-term production growth through optimal resource usage. This paper highlights a new approach to optimizing reservoir productivity, aligning with global efforts to minimize environmental impacts in oil recovery processes. The use of real-time monitoring has boosted the study by enabling for exact measurement of post-injectivity performance and oil flow rates, hence proving the efficacy of these advanced stimulation approaches. The study offers unique insights into unconventional reservoir growth by combining numerical modeling, real-world data, and novel treatment methodologies. The aim is to investigate novel simulation methodology, advanced computational tools, and data-driven strategies for improving the predictability, reservoir performance, fluid behavior, and sustainability of heavy oil recovery operations.

1. Introduction

This study investigates novel and sustainable strategies for maximizing hydrocarbon recovery, especially in unconventional reservoirs where typical extraction techniques fall short. As global energy demand rises, the oil and gas industry has prioritized increasing oil production while maintaining cost-effective and environmentally sustainable procedures Emulsified acid emerges as a preferable option to traditional hydrochloric acid (HCl) treatments, with a controlled reaction rate that maximizes acid penetration while minimizing environmental damage. This results in considerable improvements in well injectivity, with gains ranging from 2.5 to 5 times the initial rates, as well as optimized gas–oil ratio (GOR) in both oil and gas wells, indicating improved reservoir performance and fluid dynamics. Incorporating a triazine-based H2S scavenger improves field operations by reducing dangers from H2S emissions [1,2].
Stimulation procedures such as acid fracturing, matrix acidization, reperforation, and recompletion have long been used to increase reservoir permeability and well productivity. However, traditional stimulation methods, particularly those employing simple hydrochloric acid (HCl), present considerable problems, including high corrosion rates, excessive chemical consumption, quick acid spending, and increased environmental pollution. To address these restrictions, novel and sustainable stimulation methods must be developed that strike a compromise between efficiency and environmental responsibility. Recent advances in acidizing technology have made emulsified acid a better option to traditional HCl-based therapies [3]. Unlike traditional acid systems, which react quickly with the formation and overmix with formation water, emulsified acid provides a regulated reaction rate, increasing acid penetration while limiting unproductive acid loss. The main advantage of emulsified acid is its dual-phase composition, organic (diesel) and inorganic (HCl), which results in a stable emulsion in water [2]. This special formulation prevents acid from diffusing uncontrollably into formation water, preserving acid strength, decreasing dilution, and assuring more effective reservoir stimulation. The current study analyzes the use of emulsified acid in matrix acidizing operations on four different types of wells in the Field. The major goal is to determine how effective this treatment is at improving well injectivity, well productivity, permeability, and overall reservoir performance, which reflect on fluid flow behavior. Compared to the standard 15% HCl treatments, emulsified acid has higher dissolution capabilities, resulting in the formation of deep wormholes that allow for continuous fluid circulation within the reservoirs. This gain is especially noteworthy in carbonate deposits, where deep acid penetration is critical for overcoming low permeability and increasing hydrocarbon flow. This work integrates emulsified acid treatment with a triazine-based hydrogen sulfide (H2S) scavenger to reduce the danger of H2S emission during acidizing activities [4]. The presence of H2S in reservoir fluids raises significant safety and environmental concerns, including increased toxicity and corrosion. This study uses a triazine-based scavenger to neutralize H2S emissions in the emulsified acid system, decreasing toxicity, limiting environmental effect, and ensuring safer field operations. Beyond chemical stimulation, an improved abrasive jetting approach was used to increase reservoir permeability. This method uses high-velocity jetting instruments to generate precise wormholes within the formation, dramatically increasing injectivity and oil mobility [4].
The paper proposes a complete method to reservoir performance optimization that combines chemical and mechanical stimulation strategies. The effectiveness of these approaches was validated using real-time monitoring and data gathering, which allowed for the exact evaluation of post-injectivity performance and oil flow rates. The combination of emulsified acid treatment and abrasive jetting resulted in significant improvements in injection pressure, lowered circulation pressure during stimulation, and overall reservoir permeability. The study also emphasizes the necessity of good predictive modeling, which enables the precise calculation of injectivity prior to stimulation, minimizing operational time and expenses. By integrating novel treatment approaches with modern computational tools, this study lays the path for a more sustainable and effective approach to maximize hydrocarbon recovery. A significant breakthrough in this research is the creation of a predictive model that employs advanced neural network modeling techniques. This model was created using real-field data and is intended to simulate stimulation results depending on several operational and reservoir parameters. The model replaces the traditional trial-and-error approach with machine learning algorithms, lowering operational costs, reducing downtime, and increasing treatment efficiency. The capacity to estimate post-stimulation production and flow data allows engineers to adjust acidizing treatments to individual reservoir conditions, assuring maximum recovery while minimizing environmental effect. Field trials in the Gulf region, revealed tangible proof of the efficacy of emulsified acid stimulation. Pre- and post-acidifying data were acquired from the data gathering system and compared, demonstrating considerable improvements in pumping rates and a significant drop in pressure at constant rate. These results highlight the effectiveness of emulsified acid in increasing reservoir permeability, minimizing skin damage, and boosting overall well performance. The lower spent acid volume and acid leak-off highlight the treatment’s environmental benefits over traditional acidizing procedures. Emulsified acid treatments help to reduce the environmental impact of oil recovery procedures while also increasing reservoir productivity. This strategy promotes sustainability by minimizing chemical use, controlling hazardous fluid dispersion, and introducing ecologically friendly additives such triazine-based H2S scavengers. Furthermore, the regulated reaction kinetics of emulsified acid lower corrosion rates, hence increasing the life of downhole equipment, coiled tubing strings, and production infrastructure.
Given the economic and environmental advantages of emulsified acid treatment, this study seeks to prove its viability as a long-term alternative to traditional HCl-based acidifying procedures. The study demonstrates how combining emulsified acid with modern jetting techniques and real-time monitoring systems can transform reservoir stimulation, providing a long-term and highly efficient approach for increasing oil recovery. This work makes a substantial addition to the evolving field of heavy oil recovery and unconventional reservoir stimulation by combining unique simulation methodology, modern computational tools, and data-driven approaches. Finally, this study emphasizes the significance of switching to more sustainable stimulation technology in the oil and gas business. As the demand for hydrocarbons rises, the necessity for environmentally appropriate extraction methods becomes more urgent. By pioneering the use of emulsified acid treatments, this study lays the way for future advances in well stimulation, guaranteeing that energy production is both efficient and environmentally friendly.
For determining the production rate (Q) and productivity index (PI), we can apply the empirical injection rate formula to a production scenario while keeping the governing reservoir and well parameters [1,5].
1.
Estimate the production rate (Q).
To estimate the production rate (Q) for a horizontal well, use Darcy’s radial flow equation:
Q = K h · H μ · β × Pr P w f F  
where:
  • Q represents production rate (STB/day);
  • Kh = horizontal permeability (mD);
  • H = reservoir thickness (ft);
  • μ represents fluid viscosity (cp);
  • β = formation volume factor (RB/STB), assumed at 1.0 for non-energized fluids;
  • Pr = average reservoir pressure (PSI);
  • Pwf = flowing bottom hole pressure (Psi).
The flow resistance factor (F) is obtained from the empirical injection equation.
The term F takes into consideration well geometry, wellbore skin, anisotropy effects, and pressure losses and is calculated following the value of damaged skin S, the wellbore radius rw, and the anisotropy factor of the permeabilities.
Additionally, for each well an estimated productivity index is defined as:
P I = Q 1 1 Pr P w f
where:
  • PI = productivity index (STB/day/Psi);
  • Q represents production rate (STB/day);
  • Pr = average reservoir pressure (PSI);
  • Pwf = bottom hole flowing pressure (PSI).
Therefore:
P I = K h   .   H μ   .   β   × Pr P w f F   Pr P w f
-
High value of PI demonstrates better productivity of the well;
-
Low value of PI shows reduction in production, formation damaged, and less profitability.
This study proposes a breakthrough, sustainable matrix acidizing strategy based on an emulsified acid system—a precisely constructed dual-phase mixture of acid and diesel designed to drastically improve oil reservoir performance. This technique improves well injectivity significantly by increasing permeability and producing deep, extensive wormholing inside carbonate formations. This improved injectivity, as evidenced by a five-fold improvement in the Field experiments, directly permits higher oil flow rates, which are a significant driver in increasing total well profitability. Unlike typical HCl treatments, which frequently result in quick acid spending and limited penetration, this emulsified acid formulation, created in the Superior Abu Dhabi company laboratory, has better high-temperature stability (275 °F) and a regulated reaction rate. This controlled reaction rate is critical for maximizing the emulsified acid’s effect on flow behavior, guaranteeing deeper, more uniform acid penetration, and reducing premature acid spending. This translates directly into increased fluid conductivity within the reservoir, which optimizes flow behavior.
The impact of the emulsified acid treatment on flow behavior was demonstrated in rigorous field studies conducted in the Gulf region Fields, as evidenced by the observed reduction in circulation pressure during stimulation, reduction in damaged skin and impressive high injection rate. The use of high-velocity jetting tools improved fluid distribution and reduced waste, which directly influenced oil flow efficiency. Furthermore, the creation and implementation of an advanced neural network model, which included 14 critical operational and reservoir factors, provided highly accurate prediction of stimulation outcomes, allowing treatment designs to be optimized to maximize oil flow and reservoir efficiency [6].
This research highlights the oil and gas sector’s dedication to sustainable methods by illustrating the effectiveness of a dual-phase emulsified acid system in enhancing reservoir stimulation. This novel method not only produces significant gains in injectivity, with real-time data collection improving well performance during and post-operations, but also enhances reservoir fluid dynamics, resulting in a better gas–oil ratio (GOR) in both oil and gas wells. By employing cutting-edge technologies such as neural network modeling and high-speed jetting, this approach enhances oil recovery rates while reducing environmental effects and promoting effective resource use. In the end, this results in improved well profitability by enhancing reservoir performance, optimizing injectivity, and ensuring sustainable oil flow, which aids in creating a more environmentally responsible and economically viable energy landscape.

2. Materials and Methods

2.1. Introduction of Emulsified Acid Treatment and Its Advantages

This study provides a paradigm change in matrix acidization by introducing a painstakingly engineered emulsified acid system that aims to revolutionize oil reservoir stimulation while prioritizing environmental aspect. The creation of this dual-phase acid–diesel emulsion, precisely produced in the Superior Abu Dhabi laboratory, marks a significant divergence from traditional acidizing procedures. Unlike typical hydrochloric acid (HCl) treatments, which frequently result in rapid acid spending and limited penetration, this emulsified acid system is designed to act as a highly efficient retarded acid, allowing for deeper and more uniform stimulation throughout the reservoir.
The main innovation is in the emulsion’s precise formulation, which includes patented emulsifiers that enable remarkable stability and regulated reaction kinetics under extreme reservoir conditions, specifically up to 275 °F. This high-temperature stability is critical in deep carbonate reservoirs, where rising temperatures can speed up the reaction rate of traditional acids, resulting in premature expenditure and ineffective stimulation. The regulated reaction rate, which is achieved by strategically selecting and concentrating emulsifiers, is responsible for the emulsified acid’s ability to permeate deeply into low-permeability oil pores. The delayed nature of this acid system enables it to overcome the limits of conventional HCl, which tends to react quickly with the formation matrix along the wellbore face, resulting in a localized stimulation effect. In contrast, the emulsified acid’s regulated reaction kinetics ensure that it remains active as it penetrates further into the reservoir, successfully dissolving calcium carbonate and forming conductive wormholes that avoid near-wellbore damage. This is especially important in heterogeneous carbonate deposits, where permeability variations can result in uneven stimulation and ineffective oil recovery.
The capacity of the emulsified acid to penetrate and stimulate oil pores in low-permeability zones is an important advantage, especially in mature reservoirs where permeability has been severely reduced due to pore blockage and mineral precipitation. The emulsified acid system improves overall reservoir connectivity by efficiently stimulating low-permeability zones, resulting in greater oil flow rates and well profitability.
Furthermore, the emulsified acid method has substantial sustainability advantages over traditional HCl treatments. By its stability and homogenous phase as demonstrated in Figure 1, it avoids premature acid spending, the method minimizes the overall volume of acid required for stimulation, lowering chemical consumption and the environmental impact of acidizing activities. Reduced wasted acid volumes lead to lower disposal costs and a lesser danger of environmental pollution.
Furthermore, the emulsified acid system’s regulated reaction kinetics reduce the likelihood of excessive corrosion, a major issue with traditional HCl treatments. By preventing corrosion, the emulsified acid system extends the life of well equipment and reduces the need for expensive repairs and replacement [7].
In essence, the developed emulsified acid system is a sustainable and highly effective method for matrix acidification in carbonate reservoirs. Its capacity to serve as a retarded acid, allowing for greater penetration and stimulation of low-permeability oil pores, combined with its environmental benefits, offers it an appealing alternative to traditional HCl treatments. This novel technique is consistent with the industry’s expanding emphasis on sustainable oil recovery practices, which ensure that hydrocarbon resources are produced efficiently and responsibly. Moreover, this treatment not only applicable for limestone but also applicable for sandstone and quartz rock where it creates its own pathway towards oil and improve acid diversion and operation objective [1,2].

2.2. Laboratory Steps and Mixture Formulation and Experiments

Prior to deploying the emulsified acid treatment in field applications, substantial laboratory testing was performed to guarantee the formulation’s stability, homogeneity, and effectiveness under simulated reservoir conditions. The primary goal of these tests was to ensure that the emulsified acid retains its two-phase stability, efficiently mixes the organic diesel phase (external) and inorganic acid phase (interior), and operates consistently under different temperature, pressure, and salt conditions.
Laboratory studies to create and sustain a consistent emulsion over 24 h at room temperature was a challenge. Trials were performed in the UAE in Superior Abu Dhabi company laboratory with the help of engineers that put effort to test many emulsifiers and be able to create the required one phase product, having organic external phase and inorganic internal phase.
The laboratory was equipped with the following equipment:
-
Corrosion tester machine;
-
Emulsion stabilizer;
-
High performance digital oven;
-
Testing bottles and tubes.
Step 1: Selecting the Right Emulsifying Additive:
1.
The first step is to select a specific emulsifying agent that ensures steady and homogeneous mixing of the two immiscible phases: organic diesel (external phase) and inorganic acid (interior phase).
A thorough series of tests was carried out to assure the creation of a stable emulsion between diesel and acid. These tests were necessary because emulsions including hydrocarbons and acids are intrinsically unstable, resulting in phase separation due to variations in polarity, density, and solubility. Achieving a steady emulsion necessitated the careful optimization of elements such as the diesel to acid ratio, the type and quantity of emulsifying agents, and the mechanical conditions under which emulsification occurred, including stirring speed and temperature. Various surfactants and stabilizing agents were tried to see how well they could induce a consistent and long-lasting dispersion of acid droplets in the diesel phase.
The stability of the generated emulsions was assessed over time using factors such as droplet size distribution, coalescence tendencies, and the possibility of phase inversion. Ensuring the emulsion’s stability was critical, since any phase separation may cause inefficiencies in following corrosion protection testing and jeopardize the formulation’s overall efficacy [7].
2.
This addition is essential for ensuring long-term stability and preventing phase separation, both of which are required for effective acid transport and penetration.
Once a stable and reproducible emulsion had been established, several attempts were undertaken to improve its corrosion resistance by introducing other families of corrosion inhibitors. These inhibitors were chosen due to their known chemical characteristics, methods of action, and compatibility with the diesel–acid system.
Step 2: Compatibility Testing:
  • The prepared emulsified acid is subjected to comprehensive compatibility testing to determine its effectiveness and stability under a variety of temperature and pressure conditions.
  • Tests are run at room temperature and elevated reservoir temperatures to confirm that the mixture is stable and does not separate prematurely.
  • Compatibility testing also evaluates how the emulsified acid interacts with formation minerals, wellbore fluids, and stimulation additives.
Step 3: Optimization of Chemical Dosage:
1.
The ideal acid-to-diesel ratios, emulsifier concentrations, and other additions are found via laboratory tests and field simulations.
Emulsified acid treatment is optimized using a systematic approach that includes laboratory testing and field simulations to establish the optimal acid-to-diesel ratios, emulsifier concentrations, and extra chemical additions. Extensive laboratory testing determined that a 70:30 acid-to-diesel ratio achieves the optimal blend of emulsion stability, controlled acid release, and deep formation penetration, ensuring excellent mineral dissolving while avoiding premature acid spending. The choice and concentration of emulsifiers were also important, with 3–5 wt% of nonionic and anionic surfactants being ideal for maintaining phase stability at high reservoir temperatures and pressures.
2.
This phase assures that the treatment increases reservoir stimulation efficiency while lowering operational costs and dangers.
3.
The proper dosage is required to achieve a regulated acid reaction rate, which reduces excessive acid spending and extends wormhole growth.
Step 4: Corrosion Testing for Different Well Conditions:
1.
To measure its impact on downhole metallurgy, the emulsified acid is tested under various well conditions with a variety of corrosion coupons.
Extensive studies were conducted to examine the stability of the emulsion and the performance of various corrosion inhibitors under both low and extremely high temperature circumstances in order to successfully stop the acidic emulsion treatment over a wide range of temperatures. Temperature is an important factor in determining emulsion stability and the efficiency of corrosion inhibitors since temperature changes can affect the system’s solubility, reaction kinetics, and phase behavior. At low temperatures, the fundamental problem was preventing phase separation and ensuring that the acid was evenly distributed throughout the fuel. This required the selection of surfactants and emulsifying agents that could perform efficiently at low kinetic energy levels, ensuring that the acid droplets remained finely dispersed without coagulating. Furthermore, corrosion inhibitors at lower temperatures had to be tested for adsorption efficacy on metal surfaces, as decreased molecular mobility could affect the creation of a protective inhibitor layer. In contrast, at extremely high temperatures, the problem switched to preventing thermal deterioration of the emulsion and inhibitors while maintaining corrosion protection. At high temperatures, increased molecular activity accelerates phase separation, weakening the emulsion and potentially exposing metal surfaces to acid attack. To address this, high-temperature-resistant emulsifiers were carefully chosen, and thermally stable corrosion inhibitors were added to ensure that the protective barrier remained effective even in harsh conditions.
2.
To verify that the treatment does not severely erode tubulars and well equipment, tests are carried out at various temperatures, pressures, and acid strengths.
The inhibitor families included film-forming inhibitors, passivating compounds, and adsorption-type inhibitors, each with a unique protective mechanism. Film-forming inhibitors were evaluated for their capacity to build a physical barrier on metal surfaces, preventing direct contact between corrosive acid and metal substrate. Passivating inhibitors were examined for their ability to modify the electrochemical behavior of the metal, hence reducing its susceptibility to oxidation. Adsorption inhibitors, on the other hand, were evaluated for their ability to bind to the metal surface and form a protective molecular layer, thereby reducing acid assault. The performance of each inhibitor family was rigorously assessed, taking into account variables such as inhibitor concentration, exposure time, temperature fluctuations, and the emulsion’s general chemical stability in the presence of these additives.
2.1. 
Standard Corrosion Testing Procedure
Gravimetry, the most commonly used method for corrosion measurement, was employed to quantify inhibitor performance by tracking material weight loss over time. Metal samples were subjected to a diesel–acid emulsion containing various inhibitors [7], then cleaned and weighed before and after the exposure. Unlike electrochemical approaches, which can add uncertainty owing to current variations, gravimetric analysis provides a precise, repeatable assessment of metal degradation, making it suitable for evaluating inhibitor efficiency and determining the most effective formulations.
Standardized gravimetric corrosion tests were carried out on L-80 (production tubing material), QT-800 (coiled tubing material), and Alloy-28 (offshore wells). Coupons were immersed in emulsions containing varied inhibitor concentrations, treated to regulated temperatures for 6 or 12 h, then cleaned, dried, and weighed to assess mass loss and corrosion rate.
Analyzing these results revealed the most effective inhibitor formulations—such as quaternary ammonium and quinoline chloride—for both low- and high-temperature applications, ensuring optimal corrosion protection while retaining emulsion stability.
3.
Results show that emulsified acid has much lower corrosion rates than standard HCl, making it a safer option for long-term use in high-temperature and deep reservoirs.
Steps 5: Validation of Unique Advantages.
  • The emulsified acid has a significant benefit over typical acid treatments: it is immiscible with water, limiting uncontrolled acid loss into the formation.
  • Unlike conventional acids, emulsified acid only reacts when in contact with oil, allowing for deep formation cleaning, extended wormhole propagation, and increased permeability.
  • This selective reaction improves reservoir fluid dynamics by increasing oil flow efficiency and reducing water breakthrough and formation damage.
  • Its gradual investment promotes deeper penetration into the formation, hence increasing stimulation efficiency in tight and ultra-low permeability reservoirs.
Step 6: Field trials and Performance Validation:
Advanced stimulation techniques are required to address the difficulty of low injection rates and reduced oil production in carbonate reservoirs, which is frequently caused by precipitates and deposits that generate detrimental skin and hinder fluid flow. Darcy’s Law describes the relationship between flow rate (Q), permeability (K), and pressure gradient (ΔP) in reservoirs. However, the presence of skin, a measure of near-wellbore damage, considerably modifies this relationship, resulting in decreased permeability (Ks) and a positive skin effect (s), which drastically affects injectivity and productivity.
1.
To test the efficacy of emulsified acid, field studies were undertaken versus traditional 15% HCl acid treatments in a variety of well types, including oil producers, gas producers, and water injectors.
Field trials using standard matrix acidification with conventional HCl was ineffective in addressing these concerns. HCl’s high reactivity resulted in limited penetration because the acid preferentially reacted with near-wellbore damage while leaving deeper formation pores untouched. This resulted in long-lasting favorable skin effects, which hampered injection and manufacturing. To address these constraints, a unique emulsified acid treatment was developed to function as a delayed acid system. The designed emulsified acid, a two-phase solution with HCl droplets dispersed in a continuous diesel phase, provided a regulated reaction rate, allowing for deeper acid penetration. This retardation effect was achieved by strategically using patented emulsifiers (SUP-AE-03), which retarded the interaction between HCl and carbonate production, allowing the acid to permeate deeper into the reservoir and stimulate low-permeability pores. This is in stark contrast to conventional HCl, which quickly depletes at the wellbore face.
The retardation mechanism is directly proportional to the volume percentage of the acid internal phase. A 70:30 acid-to-diesel ratio was chosen to balance viscosity and penetration depth. This formulation, which had the same raw acid dosage as a traditional 15% HCl treatment, provided optimum retardation and deep live acid penetration even at high bottomhole temperatures (275 °F).
2.
The results of the field trials demonstrated:
The effectiveness of stimulation techniques in oil and gas reservoirs is usually evaluated according to three main categories of criteria where geological and physical factors significantly influence their success. These elements include various reservoir attributes, such as the characteristics of reservoir fluids including:
-
viscosity;
-
density;
-
formation composition;
-
petrophysical data, such as permeability, porosity, thickness, and lithology;
-
bottom hole pressure;
-
bottom hole temperature.
Where these factors affect fluid mobility and the success of stimulation procedures. The depth and circumstances surrounding an oil-saturated reservoir also influence the choice of treatment fluids and methods, as deeper formations typically necessitate more resilient stimulation approaches due to increased pressures and temperatures. To address this challenge, emulsified acid, by its formulation, overcomes water’s diluting effects due to its combinations of the diesel phase’s outer shell, allowing the oily emulsion to have a deeper penetration towards the reservoir, seeking extensive wormholing to reach out to oil pores and clean damaged skin.
2.1.
Injectivity increased by 2.5 to 5 times compared to the initial well performance.
Additionally, the petrophysical characteristics of the reservoir, including porosity and permeability, are vital for comprehending how fluids will move through the formation and how efficiently stimulation can improve injectivity and productivity. The traits of an oil-bearing reservoir, such as its lithology, level of heterogeneity, and natural fracture systems, influence how stimulation fluids can penetrate and interact with the formation. Furthermore, the filling of the pore space with reservoir fluids—be it oil, water, or gas—determines the effectiveness of displacement and possible enhancements after stimulation.
2.2.
Superior wormhole propagation and acid penetration compared to standard HCl.
For gas-saturated reservoirs, utilizing emulsified acid treatment has demonstrated a marked increase in injectivity and productivity, with enhancements between 2.5 and 5 times the initial performance. This improvement is mainly due to the acid’s capacity to uniformly infiltrate the formation, dissolve blocking minerals, and establish highly conductive flow pathways, thus enhancing gas movement and reservoir connectivity. Consequently, the productivity index, reflecting the reservoir’s capacity to supply hydrocarbons to the wellbore, shows significant enhancements, guaranteeing a more effective and continuous production rate.
The heightened injectivity facilitates improved reservoir pressure upkeep and greater hydrocarbon extraction, resulting in optimized well efficiency and a more cost-effective operation. Through the meticulous assessment of these geological and physical factors, Superior Abu Dhabi engineers can customize stimulation treatments to suit particular reservoir conditions, guaranteeing optimal efficiency and sustainable production over long term.
The emulsified acid therapy effectively addressed the difficulties of limited injectivity while also providing favorable skin effects. By disintegrating damaged skin and forming conductive wormholes, it greatly enhanced permeability and reduced the skin effect, resulting in a dramatic rise in injectivity of five times, depending on well conditions. This large improvement in injectivity directly translated into increased oil production rates, as indicated by the significant pressure drop recorded during emulsified acid injection. The high-velocity jetting instrument, when combined with the emulsified acid, improved acid penetration and distribution, ensuring that the acid reached and stimulated all zones of interest. This combination efficiently creates conductives channels known as wormholes, which improved rock qualities like wettability, permeability, and differential pressure.
2.3
Significant reduction in post-stimulation skin factor, resulting in sustained high productivity gains.
3
Reduced corrosion influence on wellbore materials, resulting in longer operating life.
The comparison testing indicate that emulsified acid is not only a feasible alternative to HCl, but also a long-term option for improving well performance while decreasing environmental effect. Furthermore, the emulsified acid system provided considerable benefits in terms of decreased acid leakage and spent acid amounts. The regulated reaction rate reduced the quantity of acid necessary for effective stimulation, resulting in lower chemical consumption and environmental impact. The stability of the emulsified acid system was carefully examined, including corrosion tests and viscosity studies under reservoir conditions. The adoption of a tuned corrosion inhibitor guaranteed that the system remained stable and effective at high temperatures, which contributed to its overall success.
In summary, the developed emulsified acid treatment proved to be a highly successful and long-term solution for increasing oil production in oil-saturated reservoirs, gas-saturated and reservoir injectivity in the Fields. Its capacity to operate as a retarded acid, along with the use of high-velocity jetting instruments, resulted in a huge improvement in well performance, highlighting the significant benefits of this novel strategy over traditional acidizing approaches to improve deep clean into formation leading to better reservoir performance.
The experimental data in Table 1 offer a detailed overview of the important parameters controlling the performance of the emulsified acid system. The ideal acid-to-diesel ratio was determined to be 70:30, which ensures consistent emulsion formation while successfully limiting acid discharge for deep reservoir penetration. The emulsifier concentration, ranging from 3 to 5 wt%, was critical in maintaining the stability of the two-phase emulsion, especially under high-temperature conditions of up to 275 °F, which are typical of deep carbonate reservoirs. Reaction retardation was well controlled, allowing for longer acid–rock interaction, resulting in deeper wormhole propagation and increased acid penetration efficiency. The formulated system had a major advantage in that it greatly reduced corrosion rates when compared to standard hydrochloric acid (HCl) treatments, improving wellbore integrity and minimizing equipment degradation. Furthermore, the injectivity of treated wells increased by 2.5 to 5 times, demonstrating the better stimulating effectiveness of the emulsified acid treatment. These findings show that the improved formulation has the potential to increase well productivity while reducing operational constraints associated with conventional acidizing procedures.

3. Results

3.1. Laboratory Trials to Formulate Emulsified Acid for Field Trial

Extensive testing was performed to identify the best dosage of each chemical component in the designed emulsified acid treatment, ensuring both a homogeneous single-phase mixture and excellent corrosion prevention with a 12-h protection window and no pitting on metal surfaces. The initial phase of development aimed to create a stable emulsion that seamlessly blended the hydrocarbon and acid phases. This was accomplished by combining the Superior Abu Dhabi Acid Emulsifier, which was specifically developed to improve emulsion stability, with the corrosion inhibitor SUP-CI-68, which gave longer protection while preserving the emulsion’s integrity. These components worked together to create a robust and homogenous emulsified acid solution that could withstand over six hours of exposure to both ambient surface temperatures and harsh downhole reservoir conditions [8].
After achieving a consistent and stable emulsion (Figure 1 and Figure 2) for different recipes seeking different temperatures, a vital “snack test” was performed to determine the stability of the final combination when in contact with water. This test was critical in establishing that the emulsion would keep its integrity even in the presence of formation water, thus preventing premature phase separation, which could alter treatment efficiency.
Emulsions are classed as macro or micro based on droplet size and dispersion phase. There are four types: oil-in-water (O/W), water-in-oil (W/O), oil-in-water-in-oil (O/W/O), and water-in-oil-in-water (W/O/W). Emulsions appear white or hazy due to light scattering at phase boundaries, with uniform scattering resulting in a milky-white appearance. A stable emulsified acid treatment necessitates an optimal balance of oil, water, surfactants, and mechanical agitation. Surfactants minimize interfacial tension, resulting in stable, low-energy distributed droplets. Emulsion stability is crucial—poor formulation or inadequate mixing can lead to coalescence and separation, undermining treatment effectiveness. Research by Pandya, Wadekar, and Cassidy highlights that corrosion inhibitors can reduce emulsion stability by affecting interfacial film properties, but this study optimized the formulation to maintain stability while ensuring effective corrosion protection [8]. Mechanical energy is used to disrupt the oil–water immiscibility, and surfactants stabilize the droplets, preventing coalescence and ensuring long-term structural integrity.
The emulsions employed in this investigation were created with high-shear mixing equipment to assure consistency and repeatability, as manual mixing or insufficient stirring could result in discrepancies in droplet size and stability.

3.2. Corrosion Protection for Different Types of Metal

Corrosion prevention is an important feature of emulsified acid treatment during stimulation operations, as it ensures the integrity and lifetime of numerous metal components exposed to harsh acidic conditions. Unlike traditional hydrochloric acid (HCl) treatments, emulsified acid formulations are specifically designed to give improved protection to metal surfaces while being effective in matrix stimulation. During field operations, many types of metal—including carbon steel, stainless steel, and high-strength alloys—are exposed to acidic fluid at various stages of the process.
The corrosion protection technique for emulsified acid treatment was thoroughly developed and verified in extensive laboratory experiments to ensure safe field application with no corrosion-induced failures. These tests were conducted using OFITE corrosion tester machine in Figure 3, to determine the acid’s compatibility with coiled tubing strings, surface mixing equipment, downhole production tubing, and well liners, ensuring that all metal components remained structurally sound during the treatment process. To evaluate the effectiveness of corrosion inhibition in emulsified acid, laboratory tests were carried out utilizing gravimetric weight loss measurements and electrochemical testing under simulated field circumstances [7,8].
The studies were meant to imitate both surface and downhole settings, taking into account temperature, pressure, acid strength, and exposure time. Metal coupons of various compositions, including low-carbon steel, coiled tubing QT-800, and nickel-based alloy Alloy-28 (Figure 4), were immersed in an emulsified acid solution containing corrosion inhibitors for varying lengths of time at temperatures ranging from ambient to elevated downhole temperatures exceeding 300 °F (150 °C). The results showed that using a highly efficient corrosion inhibitor package, such as SUP-CI-68, considerably reduced metal weight loss while keeping corrosion rates far below industry-acceptable standards.
During laboratory testing, coiled tubing samples were continuously circulated with emulsified acid to imitate real-world pumping conditions, and post-exposure examination revealed no signs of thinning, pitting, or structural weakness. This demonstrated that the emulsified acid treatment may be safely administered via coiled tubing without the risk of early equipment failure. Downhole corrosion protection is also important, as production tubing and well liners are constantly exposed to acidic fluids during stimulation. Conventional acid treatments in high-temperature reservoirs frequently require large corrosion inhibitor loading to prevent an aggressive attack on metal surfaces; however, emulsified acid significantly reduces this demand because of its sluggish reaction rate. The regulated discharge of acid avoids excessive localized corrosion, allowing for more uniform acid exposure and minimum damage of the tubing
As shown in Figure 4, three metal coupons representing different critical components—surface equipment material, coiled tubing string, and downhole production tubing—were subjected to extensive corrosion testing to assess the compatibility and protective efficacy of the newly developed emulsified acid treatment. The corrosion resistance of these materials was a major worry, since any breakdown in surface mixing units, coiled tubing, or downhole tubulars might result in operating risks, equipment degradation, and costly maintenance. Each coupon was immersed in an emulsified acid solution that contained the advanced corrosion inhibitor SUP-CI-68, ensuring that the protective formulation could successfully prevent acid-induced metal loss while retaining the acid’s reactivity. These tests revealed passable corrosion rates, with all three coupons remaining structurally intact and free of significant weight loss, pitting, or localized damage. This proof of corrosion protection enables the safe deployment of the emulsified acid treatment in field applications without jeopardizing the well infrastructure.
The successful corrosion test results demonstrate that the formulated acid treatment can be utilized reliably in the field, allowing for more aggressive stimulation tactics without the risk of early equipment deterioration
As a result, using this emulsified acid significantly improves reservoir permeability, allowing oil to flow more freely across pay zones and, eventually, raising production rates. These data support emulsified acid as a superior option to standard acidizing procedures, offering both improved formation treatment and long-term well integrity.
Extensive corrosion testing was carried out to assess the efficacy of the corrosion inhibitors in the newly developed emulsified acid treatment, ensuring good protection for several types of metal alloys widely used in oilfield applications. The study focused on three different metal coupons: low-carbon steel L-80, QT-800, and Alloy-28, which are key materials utilized in a variety of well components such as surface equipment, coiled tubing strings, and downhole production tubing (Figure 4). Each coupon was immersed in an emulsified acid system containing a very effective corrosion inhibitor package, and testing was carried out in a controlled laboratory setting that simulated field conditions [8,9].
Because of its widespread use in production tubing and casing applications, low-carbon steel L-80’s corrosion resistance was a top priority. L-80, a ferritic steel of moderate strength, is known to be susceptible to strong acid exposure, particularly in hydrochloric acid-based stimulation treatments. The test findings showed that the emulsified acid, along with the corrosion inhibitor, successfully reduced weight loss and surface deterioration while maintaining corrosion rates well within industry standards. No visible pitting or localized attack was seen, indicating that the inhibitor effectively produced a protective coating on the metal surface, minimizing the acid’s direct interaction with the steel [9].
Similarly, QT-800, a quenched and tempered high-strength steel commonly used in coiled tubing applications, was evaluated for its resistance to acid-induced embrittlement and stress corrosion cracking. QT-800, due to its increased strength and microstructural characteristics, is particularly sensitive to corrosion in traditional acidizing treatments. However, the laboratory tests revealed that the emulsified acid treatment provided adequate protection, preserving the coupon’s structural integrity and preventing any symptoms of hydrogen embrittlement, a known failure mechanism in high-strength steels subjected to acid.
The investigation also included Alloy-28, a highly corrosion-resistant nickel-based alloy, to see if it was compatible with the emulsified acid system. This material is commonly employed in harsh downhole situations with high temperatures and strong acidic conditions. While Alloy-28 is naturally resistant to acid attack, the corrosion inhibitor package used in the emulsified acid treatment increased its stability, guaranteeing that no substantial degradation occurred even after prolonged exposure. The test findings showed that the inhibitor efficiently prevented both uniform and localized corrosion, allowing the alloy to retain its mechanical qualities and metallurgical stability. Overall, the laboratory studies showed that the developed corrosion inhibitor package effectively addressed corrosion problems across all tested metal types, demonstrating its ability to protect various materials throughout the stimulation process. These findings support the use of emulsified acid treatment as a safe and dependable alternative to traditional acidizing procedures, maintaining long-term well integrity while increasing reservoir permeability and oil production.
As shown in Table 2 and Table 3, the corrosion inhibitors used in the newly formulated emulsified acid treatment were carefully selected to provide superior protection for various types of metals commonly used in upstream operations, particularly during stimulation treatments where corrosion risks are significantly high. The optimization process centered on developing inhibitor compositions that effectively moderate acid-induced corrosion on a variety of metal surfaces, including low-carbon steels (such as L-80), high-strength quenched and tempered steels (such as QT-800), and corrosion-resistant alloys (such as Alloy-28).
The primary goal of increasing corrosion inhibition in emulsified acid treatment was not just to protect metal equipment, but also to increase reservoir permeability and hydrocarbon flow efficiency. This deep penetration capability enables the effective removal of formation damage, such as scale deposits, drilling mud residues, and other impediments that impede oil flow or water injectivity. The test findings in Table 3 provide additional support, demonstrating a significant improvement in permeability enhancement, which translates into enhanced oil production and injectivity following stimulation. Field trials have shown that the optimized emulsified acid treatment can increase injectivity by a factor of 6 to 14 times, depending on well conditions, demonstrating the efficacy of both the corrosion inhibitor package and the acid system in achieving long-term reservoir stimulation benefits. The findings underline the importance of corrosion inhibition. The findings emphasize the importance of corrosion inhibition in permitting successful emulsified acid treatments, which ensures operational safety and improved production performance. Figure 5 depicts a comparison of two chemical treatment series, with Series 1 representing the corrosion inhibitor dosage and Series 2 reflecting the corrosion inhibitor aid dosage. The primary goal of this review was to optimize chemical dosage while carefully balancing corrosion mitigation and operating efficiency.
The optimization procedure entailed establishing the optimal concentration of both the primary corrosion inhibitor and its assistance in order to produce a corrosion rate within acceptable limits while minimizing chemical consumption. The goal was to ensure that the applied treatment effectively reduced corrosion to a passable and optimal rate, hence prolonging equipment lifespan and maintaining well integrity without the overuse of costly chemical additives. The data trends revealed in Figure 4 gave vital insights into the interaction of the inhibitor. Figure 4 revealed crucial insights into the inhibitor-aid relationship, showing the most efficient combination that provided outstanding corrosion protection while minimizing expenses and any chemical-related adverse effects.

3.3. Field Description

The prospective wells chosen for this study came from three large fields in the Gulf region with limestone formations as the main geology. These formations support a wide variety of well types, including oil and gas producers, water injectors, and water-alternating-gas (WAG) injectors. The limestone reservoir showed moderate to high heterogeneity, which affected fluid flow dynamics and acid stimulation effectiveness. The major goal of the acid treatment was to increase injectivity by removing formation damage, expanding pore throats, and enhancing connectivity within the reservoir matrix. During the treatment, acid was injected deep into the formation, successfully dissolving carbonate minerals and reducing near-wellbore limitations, allowing for increased oil displacement and reservoir pressure support. The treated wells showed significant injectivity improvement, with injection rates rising from as low as 0.2 barrels per minute (bpm) to as high as 2.5 bpm. This significant increase in injectivity not only proved the acid stimulation technique’s effectiveness, but it also contributed to long-term hydrocarbon production by improving sweep efficiency and fluid motion within the reservoirs.
Eight wells have been tested using the same emulsified acid treatment in order to improve oil production and assess the hydrocarbon flow rate after operation.
In Table 4 are presented the four analyzed cases with the specification for each well.
The implementation of a novel acid treatment in the selected wells aims to improve permeability and hydrocarbon flow by efficiently removing formation damage and enhancing pore connectivity. The treatment consisted of injecting a customized acid system that was designed to penetrate deep into the carbonate formation and selectively dissolve fines, scale, and other permeability-reducing elements. The simulation of fluid dynamics was an important part of this procedure because it allowed us to precisely characterize acid–rock interactions and anticipate treatment efficacy. Advanced reservoir modeling methods were used to investigate fluid behavior in porous media, taking into account variables such as injection rates, reaction kinetics, wormhole propagation, and acid penetration depth. Engineers were able to maximize permeability increase by simulating these parameters, which included acid volume, injection pressure, and treatment sequencing.
Post-treatment studies revealed a considerable improvement in formation permeability, resulting in higher oil and gas flow rates. Real-time monitoring of pressure responses and output rates validated the acidizing process’s performance, confirming that the enhanced fluid design and treatment execution successfully reduced flow constraints. The use of fluid dynamics simulations gave crucial insights on the acid’s propagation paths, resulting in uniform stimulation coverage and long-term productivity gains.
Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12 and Figure 13 describe four field trials injection rate ahead and behind stimulation operation. Real data, extracted from CTES-NOV software Cerberus (V15), provide the acid penetration rate, with the permeability enhancement concluded from the improvement of injectivity. In Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12 and Figure 13, all operational factors were recorded to clearly demonstrate the effectiveness of acid penetration and relative injectivity. In case 1 of a gas producer well, Figure 6 and Figure 7 demonstrate the improvement in production rate after stimulation. In case 2 of an oil producer well, Figure 8 and Figure 9 demonstrate the improvement in production rate after stimulation. In case 3, the water-alternating-gas well, Figure 10 shows the initial rate, and Figure 11 shows the improved injection rate after acidizing. In case 4, related to water injector well, the initial injection is present in Figure 12, and good injection is demonstrated in Figure 13.
For case 1:
For case 2:
For case 3:
For case 4:
The performance of oil, gas, and injector wells before and after pumping emulsified acid revealed considerable improvements in permeability and fluid injection rates, demonstrating the treatment’s efficacy in increasing well productivity and injectivity. Prior to acidizing, the formation had restricted flow due to causes such as near-wellbore degradation, carbonate scale deposition, and fines migration, which slowed fluid movement and limited injection or production rates. However, the injection of emulsified acid increased the permeability of the formation, resulting in significant improvements in well performance [10].
In the case of the gas producer well (Case 1), the injection rate increased by fourfold, from a limited one barrel per minute (bpm) to an astounding four bpm post-treatment. This significant improvement suggests that the emulsified acid efficiently dissolved formation damage, expanded pore throats, and reduced resistance to gas flow, hence improving reservoir deliverability. Similarly, the oil producer well (Case 2) had a fivefold increase in injection capability, with the rate rising from 0.4 bpm to 2 bpm following treatment. This large increase in injectivity demonstrates the acid’s effectiveness in dissolving inorganic deposits and mineral scale and enhancing fluid routes within the reservoir matrix, resulting in higher oil recovery.
The water-alternating-gas (WAG) injector well (case 3) likewise showed a significant increase in injectivity, with the injection rate rising from 0.5 bpm to 2.7 bpm—a more than fivefold increase. This enhancement is critical to the performance of WAG operations because it enables uniform sweep efficiency and improved gas and water conformity control within the reservoirs. Similarly, the water injector well (case 4) experienced a significant increase in injection rate, rising from 0.8 bpm to 2.1 bpm following the emulsified acid treatment. The roughly threefold improvement suggests that the acid was effective in removing blocking materials, such as iron sulfides, carbonate scales, and residual hydrocarbons, allowing for a more efficient water injection and pressure maintenance.
Overall, the emulsified acid treatment was highly effective in all cases, with significant permeability and injectivity increases resulting in doubled, tripled, and even quadrupled injection rates. The treatment’s success in gas, oil, and injector wells demonstrates its promise as a powerful stimulation tool for improving well performance and increasing hydrocarbon recovery.
1.
Gas producer well-injection rate increased from 1 to 4 bpm.
The productivity index (PI) for gas wells is represented as follows:
J   g = q × g   Δ   P
where:
  • J = gas productivity index (Mscf/d/psi);
  • qg = gas production rate (Mscf/d);
  • ΔP = pressure drawdown (psi).
Darcy’s Law gives the gas flow rate as follows:
0.00708 × k × h μ g × Z × T × (   p   r   2 p   w   f   2   ) B   g
where:
  • k represents permeability (mD);
  • h represents formation thickness (ft);
  • μg = gas viscosity (cp);
  • Z = gas deviation factor;
  • T = temperature (°R);
  • pr, pw, f = the variables p, w, and f represent reservoir and bottom-hole pressures (psi);
  • Bg = gas formation volume factor (res ft3/scf).
A fourfold rise in injection rate suggests that permeability has increased dramatically, as gas flow is extremely sensitive to near-wellbore degradation. The acid treatment effectively removed carbonate scales and decreased skin, resulting in increased gas mobility [10,11].
2.
Oil producer well-injection rate increases from 0.4 to 2 bpm.
The productivity index for oil wells is calculated as follows:
J o = q o p r p w f
Additionally, Darcy’s equation for a radial flow oil well:
q = 0.00708 × k × h   μ × B   o × l n r   e r   w × ( p   r p   w )
where:
  • J is the oil productivity index (STB/d/psi);
  • qo = oil production rate (STB/d);
  • Μo = oil viscosity (CP);
  • Bo = oil formation volume factor (rb/STB);
  • re, rw = drainage and wellbore radius (ft).
A fivefold increase in injection shows significant permeability improvement, reducing the skin factor (S) from a damaged formation. This can be computed using the Hawkins equation.
S = K K s 1
The lower permeability prior to acidification is denoted by Ks. The acid effectively dissolved particle migration barriers and freed flow channels, allowing more oil entry [12].
3.
Water-alternating-gas (WAG) injector—Injection rate increased from 0.5 to 2.7 bpm.
The injectivity index (II) is applied to injectors.
I I = q P
As well as Darcy’s equation for injectivity, as follows:
q = 0.00708 × k × h   μ × B   × l n r   e r   w × ( p   r p   w )  
where:
  • II = injectivity index (bpm/psi);
  • pi = injection pressure (psi).
Since the injection rate increased by more than fivefold (0.5 bpm to 2.7 bpm), the acid treatment effectively increased permeability by dissolving carbonate scale and reducing near-wellbore constraints, making WAG injection more efficient. This is critical for enhanced oil recovery (EOR) operations because higher injectivity results in greater displacement efficiency and sweep coverage [13].
For case 4, water injector well—where injection rate increases from 0.8 bpm up to 2.1 bpm.
The improvement in permeability is assessed using the following equation:
q = 0.00708 × k × h   μ w × B w   × l n r   e r   w × ( p   i p   w f )  
where:
  • qw = water injection rate (STB/d);
  • Water viscosity (cp) is denoted by μ and w;
  • Bw = water formation volume factor (rb/STB).
An almost threefold increase in injection indicates a decrease in formation resistance, allowing for more water throughput and better pressure maintenance inside the reservoir. The acid effectively eliminated blocking elements like iron sulfides, carbonate scales, and residual hydrocarbons, resulting in a more efficient injection procedure [14].
The emulsified acid treatment efficiently removed near-wellbore damage, reduced skin, and increased permeability, resulting in injection and production rates that doubled, tripled, or even quadrupled. Productivity and injectivity indicators improved dramatically, indicating a higher reservoir flow efficiency. Skin removal calculations (Hawkins equation) confirm increased permeability, which is consistent with reported well performance improvements. The treatment’s effectiveness demonstrates its potential for stimulating tight reservoirs, enhancing EOR (enhanced oil recovery), and optimizing gas and water injection tactics.
In conclusion, the formulated emulsified acid treatment has demonstrated itself to be an extremely efficient and durable approach for boosting oil output, increasing injectivity, and maximizing reservoir functionality in oil-saturated and gas-saturated formations, along with injection wells. This sophisticated acid system is essential for changing the characteristics of unconventional and tight formations by altering rock–fluid interactions, enhancing matrix permeability, and establishing highly conductive pathways that aid in the transport of hydrocarbons and injected fluids. In contrast to traditional acid treatments that can cause quick acid depletion and irregular dissolution patterns, the emulsified acid functions as a delayed system, enabling deeper infiltration into the formation before completely reacting. This regulated reactivity guarantees that the acid efficiently eliminates formation damage, clears pore-blocking minerals, and improves the connectivity of the pore network, thus greatly enhancing both injectivity and productivity [1,12,13,14].
In reservoirs saturated with gas, this treatment technique enhances gas mobility by removing obstructions and boosting effective permeability, resulting in a significant increase in production rates. In injection wells, the improved injectivity obtained via emulsified acid stimulation guarantees more effective water or gas injection, which is vital for preserving reservoir pressure and enhancing secondary recovery methods. The capacity of emulsified acid to evenly infiltrate the formation and produce enduring stimulation effects highlights its advantages over conventional acidizing methods, which frequently face challenges with shallow penetration and inconsistent acid spread. Emulsified acid treatment represents a groundbreaking technology that fundamentally transforms formation characteristics and enhances fluid–rock interaction, enabling the complete potential of complex reservoirs to be accessed, promoting sustainable hydrocarbon extraction, and greatly increasing the economic feasibility of well interventions.

3.4. Simulation Run and Data Gathering

StimVision and CTES-NOV are two examples of advanced software for simulation and modeling of well intervention. They use sophisticated geomechanical, petrophysical, and fluid flow models as part of a treatment permeability enhancement, well injectivity, and production post-treatment analysis. Before performing any stimulation jobs, StimVision and StimPro obtain real-time field data, historical well data, and formation information to simulate various acidizing scenarios. Once these parameters are set, engineers can expect permeability enhancement and fluid movement changes under different operational conditions [15]. These software programs also incorporate reservoir porosity, permeability anisotropy, pressure depletion, and rock–fluid interaction. Based on these parameters, they develop detailed acid penetration profiles, skin factor reduction, and fracture conductivity enhancement predictions so that acid volumes, pumping rates, and treatment duration can be optimally set.
Once the emulsified acid gets injected, StimVision and CTES confirm their predictions by meshing the post-treatment pressure transient analysis (PTA) and the well test results, so that the actual injectivity increases can be compared with the modeled ones. For example, with the gas producer well, the software would have anticipated formation damage reduction, improved near wellbore permeability, enhanced gas mobility, and would also have been positive by the post-operational results. Additionally, with the oil producer well, as the injectivity increased from 0.4 bpm to 2 bpm, the software would have predicted capillary barriers being lifted due to organic scale dissolution, matrix acidizing, and then being able to ensure an adequate oil recovery from the well [16].
Furthermore, in water-alternating-gas (WAG) injectors and water injector wells, where injection rates have dramatically increased following stimulation, StimVision and StimPro are critical in anticipating the influence on reservoir pressure support, sweep efficiency, and breakthrough dynamics. The capacity of these tools to mimic water and gas conformance, fluid distribution, and pressure propagation inside the reservoir is extremely useful for reservoir engineers when making real-time choices about injection strategy changes. By executing various acidizing scenarios, the software generates an optimum plan that combines formation damage removal with controlled acid reaction kinetics, resulting in uniform permeability enhancement throughout the stimulated zone.
Furthermore, machine learning algorithms and predictive analytics included into these software tools assist engineers in anticipating long-term well performance trends, allowing for proactive intervention planning in the future [17]. StimVision and StimPro’s post-stimulation analysis enables operators to measure skin factor decrease, compare pre- and post-treatment productivity indices, and produce well inflow performance relationships (IPR) for production forecasts. Their role goes beyond initial evaluation; they are constantly employed to monitor pressure drawdown behavior, detect potential formation re-damage over time, and change stimulation tactics for future acid treatments.
Finally, integrating StimVision and StimPro into stimulation operations improves decision making by giving data-driven insights regarding acid treatment effectiveness, maximizing hydrocarbon recovery, and extending well life. These software solutions are critical tools for assessing formation response to stimulation, predicting reservoir behavior after treatment, and optimizing well performance in both production and injection scenarios. Reservoir data, such as formation petrophysical data and relative pumped fluid mentioned in Table 4 and Table 5, are essential in order to simulate the exact case and provide accurate simulation results.
Well data are shown in Table 5.
In order to estimate the fluid progression and invasion into the formation and through the damaged skin, some fluid characteristics were used as an input into the simulation run considering the acid concentration, density, diffusivity, friction factor, and retardation factor, as well as the initial K factor, as demonstrated in the Table 6 [18].

4. Discussion

StimVision’s advanced simulation is tailored to model the complex behavior of acid treatments within reservoir formations. In StimVision, the penetration depth is analyzed by calculating skin factor reduction and quantifying the formation conductivity improvement. The diffusion mechanism analysis is incorporated, allowing StimVision and StimPro to predict not only the acid depth penetration, but its effect to the damage formation reduction. The advanced simulation software predicts the fluid flow dynamics along with the reaction kinetics and the effects of acid–rock interaction to increase the permeability to a level of formation. The software can define the differential pressure profile across the damage zone and how the acid treatment affects the pressure dissipation along the length of the reservoir. This yields accurate information pertaining to post-stimulation well performance [19].
StimVision and StimPro conduct these simulations using extensive reservoir data inputs such as formation porosity, permeability, mineralogy, fluid composition, pressure gradients, and well geometry, ensuring a highly accurate approximation of in situ conditions. The software then creates predictive models that estimate final rock properties after stimulation, permeability improvements, and injectivity index changes, allowing engineers to forecast how the well would perform under changing flow conditions. In addition, it replicates the emulsified acid injection process, optimizing the treatment design by modifying acid injection rates, reaction time, and fluid loss control mechanisms to improve stimulation efficiency, as shown in Figure 14 below.
The simulation run not only gives a thorough evaluation of each influencing factor’s overall performance following the stimulation procedure (Figure 14), but it also provides a complete depiction of the invasion dynamics occurring within the reservoir. Using well-specific data, the simulation effectively mimics acid’s deep penetration into the formation (Figure 15), providing vital insights into the extent and efficacy of the acidizing treatment. Furthermore, as shown in Figure 16, the simulation results show a significant improvement in the well’s wormholing capacity, which can be directly attributable to the increased acid penetration seen in Figure 15. This deeper acid infiltration is critical for dissolving formation damage, lowering the damaged skin impact and improving overall reservoir performance. The simulation results are an important tool for evaluating the effects of acid stimulation on well productivity, ensuring that the treatment is properly structured to maximize hydrocarbon flow while minimizing formation resistance.
Table 7 displays the fluid injection rate and injectivity index under a low skin factor condition (S = 0.01), indicating negligible reservoir flow disruption. The tubing head pressure (THP) is 3997.3 psi, and the bottomhole pressure (BHP) is 4000 psi, both critical for determining the well’s ability to take injected fluids. The surface water injection rate is 3760.35 STB/day, whereas the downhole injection rate is somewhat lower (3735 STB/day), implying minor frictional and formation entry losses.
The well injectivity index (4.42252 STB/day/psi) measures a well’s ability to take injected fluid per pressure unit. A higher value indicates a more permeable, less damaged formation. With a skin factor around zero, the formation is extremely responsive to fluid injection. This data demonstrates that the well efficiently delivers fluid to the reservoir with minimum loss, making it excellent for waterflooding, EOR, or disposal activities because it can withstand high injection rates without exerting undue pressure. Figure 17 shows the fluid behavior along the open hole length contributing to well conditions present in Table 6 covering reservoir conditions and parameters.
The cumulative injection rate stock tank rate is presented in the Figure 18, showing a decrease of cumulative injection rate over time.
After inserting all the data, the simulation run resulted in a better enhancement of permeability, a reduction in damaged skin, and a better injection rate along the open hole section, which led to an improved injectivity index.
The below results demonstrated an impressive oil and gas flow rate due to damaged skin removal using new formulated emulsified acid treatment.
Improving reservoir permeability through emulsified acid stimulation treatments has significant benefits for optimizing fluid flow and, ultimately, maximizing hydrocarbon recovery.
By effectively reducing damaged skin as demonstrated in Figure 19 and Figure 20, which is frequently caused by drilling mud invasion or fines migration, these treatments restore and even amplify the natural flow paths in reservoir rock. This permeability gain correlates to a large boost in the productivity index, a critical parameter representing the well’s ability to produce fluids. In a two-phase reservoir, where both oil and gas coexist, this permeability enhancement permits a more efficient and balanced flow of both phases. The reduced flow resistance, combined with improved relative permeability, enables increased oil mobility and gas production [20].
This results in higher production rates, enhanced recovery factors, and ultimately, increased economic returns. Furthermore, the improved permeability may result in a more consistent sweep efficiency, guaranteeing a more thorough and equitable drainage of the reservoir. This not only optimizes resource usage but also aids the field’s longevity by reducing the chances of early water breakthrough or gas coning. Ultimately, improving reservoir permeability is fundamental to efficient reservoir management, especially in two-phase systems, where optimized fluid flow behaviors are essential for maximizing production capabilities and ensuring lasting sustainability [21,22].
Table 8 shows the fluid injection rate and injectivity index for a well following stimulation, with a post-stimulation skin factor of −2.35. The negative skin value implies better formation permeability, which makes the well more fluid-receptive. The tubing head pressure (THP) stays at 3997.3 psi, while the bottomhole pressure (BHP) is steady at 4000 psi. However, fluid injection rates have risen dramatically. The surface water injection rate climbed to 4434.29 STB/day, while the downhole injection rate increased to 4523 STB/day, demonstrating the stimulation’s efficacy.
The well injectivity index increased to 5.21499 STB/day/psi, demonstrating improved fluid absorption per pressure unit and lower formation resistance. The negative skin factor indicates that stimulation, most likely acidic or hydraulic fracturing, increased permeability and extended flow channels. This innovation allows for larger injection rates with less energy input, which benefits waterflooding, EOR, and disposal operations while also ensuring superior reservoir pressure maintenance and long-term production performance.
In summary, Table 8 shows that the stimulation treatment was effective in optimizing well injectivity, confirming its favorable effects on fluid flow and long-term reservoir efficiency.
Figure 15, Figure 16, Figure 17, Figure 18, Figure 19 and Figure 20 and Table 7 and Table 8 provide a comprehensive and detailed assessment of the improvement in simulated reservoir fluid performance (oil and gas) following the removal of damaged skin via stimulation treatments, highlighting both theoretical predictions and actual field results. Prior to stimulation, the simulation results showed considerable formation damage, including high skin values, reduced permeability, and limited fluid mobility, all of which had a detrimental influence on both oil production and gas injectivity. However, post-stimulation study revealed significant permeability enhancement and substantial improvement in injectivity, with the injectivity index (II) rising from 4.4 to 5.2, demonstrating the acid treatment’s efficiency in recovering well performance [23].
Furthermore, a rigorous comparison of simulated forecasts and real post-stimulation field data was performed to evaluate the reservoir’s oil and gas flow dynamics and behavior. The actual results obtained following stimulation demonstrated a significant correlation with the simulation forecasts, demonstrating the accuracy of the numerical models employed to estimate well performance increases. The field-measured production rates, injection pressures, and fluid mobility values closely matched the post-stimulation simulated trends, indicating that the acidizing treatment effectively removed the near-wellbore restrictions and significantly reduced the pressure drop required for hydrocarbon flow. Furthermore, the figures show changes in reservoir pressure distribution, wellbore pressure response, and flow rate variations that correspond to anticipated reservoir fluid behavior improvement.
By comparing pre- and post-stimulation actual well test results to expected simulation outputs, it was proven that oil dynamics, reservoir pressure response, and fluid behavior improved significantly following the successful elimination of skin damage. The results show that restoring near-wellbore permeability boosted oil mobility, resulting in more uniform pressure dissipation and an overall improvement in hydrocarbon flow characteristics. The decrease in skin factor and reported rise in injectivity index support the acidizing technique, assuring that similar treatments can be optimized for future reservoir development and enhanced oil recovery (EOR). This comparison of simulated and actual outcomes gives crucial insights for fine-tuning stimulation procedures, optimizing production strategies, and increasing long-term reservoir performance for sustained hydrocarbon recovery [23].
The four simulated cases demonstrated significant injectivity improvement (Figure 12, Figure 13, Figure 14, Figure 15, Figure 16, Figure 17 and Figure 18).
The injectivity test was conducted both before and after acid stimulation, and the injectivity index remained steady for long period after stimulation operation.
-
For the first scenario, injectivity was approximately 1 bpm at 1100 Psi and climbed to 4 bpm at 150 Psi.
-
In the second occurrence, injectivity increased from roughly 0.4 to 2 bpm at a drop of 100 Psi.
-
In the third situation, injectivity was approximately 0.5 bpm at 1100 Psi and climbed to 2.7 bpm at 250 Psi.
-
In the fourth case, injectivity increased from 0.8 to 2.1 bpm at 1100 Psi (Figure 21).
As anticipated and modeled, the injectivity of the treated wells markedly enhanced, with a minimum rise of 2.5 times and reaching as high as five times, influenced by reservoir type, downhole conditions, and petrophysical traits. The differences in injectivity improvement among various well types can be linked to aspects like formation permeability, initial skin factor, mineral makeup, and fluid–rock interactions, all of which were meticulously considered in the numerical simulations [25]. The simulation modeling took into account the diverse characteristics of the reservoir, such as differences in porosity, anisotropic permeability, and capillary pressure influences, guaranteeing that the anticipated enhancements matched the real fluid flow behavior seen in the field. The rise in injectivity observed in the simulation was corroborated by field tests, where real-time observation of injection rates, wellhead pressure responses, and pressure transient analysis (PTA) verified that the well performance after stimulation aligned closely with the expected injectivity patterns [26,27].
Additionally, a comparison of simulated and real results showed that the field trial results differed by around 10% from the expected values, a variation mostly due to the application of an abrasive jetting nozzle in the field to improve emulsified acid diversion. The addition of abrasive jetting technology facilitated localized erosion and enhanced acid penetration, resulting in increased permeability surpassing initial simulations, which somewhat impacted the precision of direct numerical forecasts. Even with a 10% variation, the general trend stayed steady, indicating that the modeling method successfully reflected the well’s reaction to acid stimulation, increased permeability, and improved fluid mobility. The analysis following treatment of pressure distribution, flow rate increase, and decrease in skin factor further validated that the acid treatment, in combination with the optimized abrasive jetting method, resulted in a notable decrease in near-wellbore damage, thus guaranteeing prolonged high injectivity and enhanced long-term well performance. These results underscore the strength and dependability of the simulation method in forecasting actual stimulation results, while also stressing the significance of field-adaptive strategies like jetting to enhance acid placement and improve reservoir stimulation effectiveness [28].
Table 9 compares the performance of a conventional acid system with an emulsified acid system in terms of injectivity improvement, circulation pressure, and wellhead pressure (WHP) in two different scenarios. These metrics are crucial for determining the efficacy of each acid system in improving well performance following stimulation.
-
Injectivity and Flow Rate Comparison:
The injectivity flow rate (bpm) is the fluid volume that the well can accept per minute before and after acid treatment. In the conventional acid system, injectivity increased from 1.2 to 1.9 bpm in case 1 and 0.3 to 0.85 bpm in case 2, showing a moderate improvement. In contrast, the emulsified acid system demonstrated a substantially better improvement, with injectivity increasing from 1 bpm to 4 bpm in case 1 and from 0.4 bpm to 2 bpm in case 2. This shows that the emulsified acid system is more successful at increasing well permeability, most likely due to its regulated acid release mechanism, which extends acid–rock interaction, resulting in deeper penetration and greater formation dissolution.
-
Circulation Pressure in Coiled Tubing:
The circulating pressure (Psi) in the coiled tubing represents the pressure needed to push acid through the tube and into the well. A large reduction in circulation pressure following stimulation shows that formation damage has been successfully removed, allowing the injected fluids to flow more easily. In the conventional acid system, the circulation pressure decreased from 1300 to 1100 psi in Case 1 and from 4000 to 1250 psi in case 2, indicating some improvement. However, the emulsified acid system showed a substantially greater decline, with circulating pressure falling from 1100 psi to 150 psi in case 1 and from 1200 psi to 900 psi in case 2. This significant decrease in pressure demonstrates that the emulsified acid system was more efficient in reducing formation resistance, adding to its greater effectiveness.
-
Wellhead Pressure (WHP) Comparison:
Wellhead pressure (WHP) (Psi) is another important indication of well performance after stimulation. A drop in WHP following acid injection suggests that the well is absorbing fluids more effectively. For the conventional acid system, WHP fell from 1100 psi to 1050 psi in case 1 and from 1000 psi to 900 psi in case 2, with only minor improvements. In contrast, for the emulsified acid system, WHP decreased dramatically from 1200 psi to 700 psi in case 1 and from 1200 psi to 600 psi in case 2, indicating a far more effective increase in well injectivity. This demonstrates the emulsified acid system’s excellent effectiveness in increasing wellbore permeability and decreasing formation resistance.

5. Simulation Modeling and Output Prediction

A set of comprehensive predictive modeling experiments was carried out to create a highly accurate reservoir simulation model that can predict nearly real-time values of well injectivity and production performance. The goal was to develop a strong model that combines various operational, reservoir, and injection factors to reliably forecast well performance post-stimulation, attaining an error margin of under 2% relative to real field data [29]. This method necessitated a multi-variable data-focused strategy that included historical field data, ongoing well performance tracking, and numerical simulations to enhance prediction precision. The experiments aimed to measure important reservoir characteristics like permeability, porosity, relative permeability curves, formation variability, and pressure gradients, in addition to operational factors such as wellbore shape, acid injection rates, temperature influences, and formation–fluid interactions [30].
A core element of the predictive modeling method involved utilizing machine learning algorithms and sophisticated computational techniques to examine extensive datasets and pinpoint significant trends in fluid flow patterns prior to and following stimulation. To improve the model’s accuracy, a set of iterative sensitivity analyses was conducted, altering parameters like acid concentration, injection pressure, and reaction kinetics to assess their effects on post-stimulation injectivity and the reduction of the skin factor. Furthermore, the model included injectivity index computations, well testing information, and pressure transient analysis (PTA) findings to create precise correlations between the well performance before and after stimulation.
The tests included a comparative examination of forecasted versus actual field results, involving the validation of the simulated injectivity index, flow rates, and skin values against real-time field data collected from several injection and production wells. The ultimate model effectively reached an accuracy rate surpassing 98%, with a highest deviation of under 2%, showcasing its dependability in predicting post-stimulation well performance [31]. The decrease in error was linked to improved input parameter calibrations, real-time adjustments of pressure and temperature, and dynamic updating of reservoir conditions derived from field-acquired data. Additionally, validation methods like history matching and statistical regression analysis guaranteed that the model was consistently refined for different well conditions. The achievements of these trials highlight the significance of predictive modeling as an effective method in enhancing stimulation treatments, allowing engineers to forecast reservoir behavior with almost flawless precision, reduce operational uncertainties, and boost hydrocarbon extraction [31].

5.1. Process of Standarization

Prior to starting the modeling process, all input data was standardized to guarantee that the dataset had a mean of zero and a variance of one, an essential step for enhancing the efficacy of predictive algorithms. This method, often called z-score normalization, is a statistical transformation that adjusts dataset attributes to ensure their mean (μ) is exactly zero and their standard deviation (σ) is equal to one, effectively removing possible biases resulting from varying scales among variables. The conversion adheres to the typical equation:
z = x μ σ
To efficiently execute this standardization, Scikit-learn’s preprocessing module was employed, particularly the “StandardScaler” function, which automates the procedure by calculating and applying scaling factors to the data. The scaler is first adjusted to the training dataset, where it computes the mean and standard deviation for every feature. These calculated statistical parameters are subsequently applied consistently to both the training and testing datasets, guaranteeing that the testing phase stays impartial by avoiding any information leakage from the test set into the training process [32].
The significance of sustaining standardized data goes beyond merely enhancing model performance; it is also crucial for accurately interpreting model coefficients and predictions. When predictions must be reverted to the original feature space, the captured means and standard deviations enable a smooth transition, guaranteeing that the output stays contextually relevant and aligned with actual data. This phase is especially vital in situations where model interpretations influence operational decision making, as incorrect scaling may result in deceptive conclusions. Standardizing the dataset prior to modeling guarantees strong, impartial, and scalable predictive analytics, improving the reliability and precision of the final model.

5.2. Configuration of Predictive Analytics Based on Three Different Models

To create a strong predictive framework, three distinct machine learning models were utilized: support vector regression (SVR), gradient boosting regressor (GBR), and ridge regression. All of these models were set up with particular hyperparameters to enhance performance and guarantee precise predictions of injectivity rates and reservoir dynamics.

5.2.1. Support Vector Regression (SVR)

Support vector regression (SVR) utilizes the core concepts of support vector machines (SVM) for regression purposes by aiming to fit data within a specified tolerance margin while ensuring resilience against outliers. Rather than focusing on minimizing residual errors in the conventional way, SVR emphasizes lowering significant deviations by refining a loss function that keeps errors below an acceptable limit, which makes it especially efficient for intricate datasets with noise.
In the adopted method, the SVR model was trained with hyperparameters that specify the tolerance margin (C) and the type of kernel, which defines how the input data are modified for regression purposes. In order to enhance model performance, GridSearchCV, a hyperparameter tuning method based on cross-validation, was utilized. This approach systematically examines a specified search space of hyperparameter values, assessing various configurations via cross-validation to identify the most effective combination for reducing predictive error [33].

5.2.2. Gradient Boosting Regression Model (GBR)

The gradient boosting regressor (GBR) functions as an ensemble learning approach, involving the sequential construction of various weak prediction models—usually decision trees—to fix the errors of the prior models. This iterative method reduces a specified loss function, making sure that later trees concentrate more on the regions where the model struggles, resulting in a general enhancement of predictive accuracy.
In this implementation, the GBR model was set up with a standard configuration, yet essential hyperparameters like the number of estimators (trees), learning rate, and maximum tree depth can be adjusted to enhance predictive performance. Furthermore, to guarantee consistent results, a constant random state parameter was employed, ensuring uniformity throughout various runs of the model. This setup enables the GBR model to efficiently grasp non-linear connections within the dataset, rendering it especially beneficial for predicting intricate reservoir behavior.

5.2.3. Ridge Regression

Ridge regression builds upon ordinary least squares (OLS) regression by adding a regularization component (α), which aids in avoiding overfitting by restricting the size of the model coefficients. This is especially beneficial when working with multi-collinear datasets, where closely related features could otherwise result in unreliable predictions.
In this instance, the ridge regression model was set up with a regularization parameter (α = 5), establishing the intensity of the penalty imposed on significant coefficients. An increased of α value applies firmer regularization, leading to reduced coefficient sizes, which aids in minimizing overfitting but could cause underfitting if set excessively high. The equilibrium between bias and variance was meticulously adjusted to guarantee maximum predictive accuracy [32,33].

5.3. Utilization of Ridge Coefficients for Creating Predictive Equations

Following training, ridge regression yielded a collection of coefficients (weights) for every feature, indicating the modified relationship between each independent variable and the target injectivity rate while considering the impacts of standardization. The typical expression of the predictive equation obtained from ridge regression is represented as:
y = β0 + β1 × 1 + β2x2 + βnxn
where:
  • y represents the projected injectivity rate;
  • β0 is the intercept of the model, β1, β2, ..., βn;
  • β1, β2,..., βn are the feature coefficients;
  • x1, x2, ..., xn are the input features utilized in the prediction.
Nevertheless, because the model was trained on standardized data, the coefficients relate to the altered feature space instead of the original dataset scale. To make certain that the predictions are understandable within the original operational and reservoir parameter ranges, a re-scaling transformation was implemented, returning the coefficients to their actual real-world values. This is achieved by utilizing the original means and standard deviations of the features in the following manner:
  • Initial coefficient;
  • Normalized coefficient x;
  • Characteristic standard deviation.
Therefore:
Original Coefficient = Standardized Coefficient × Standard Deviation of Feature
Moreover, the intercept is modified to correspond with the initial feature values, making certain that the model’s forecasts can be directly utilized for actual injectivity and permeability assessments:
  • Original intercept;
  • Ridge intercept;
  • Initial coefficients;
  • Characteristic/features averages.
Original Intercept = Ridge Intercept − Σ(Original Coefficients × Feature Averages)
This re-scaling process is essential for properly understanding the influence of each feature on injectivity rates and guarantees that the created model can be effectively utilized for practical reservoir management and well performance enhancement. By combining fourteen essential reservoir and operational parameters, the predictive model offers insights into the changes in injectivity rates after stimulation, serving as an important resource for creating future stimulation treatments, enhancing acid injection methods, and boosting overall reservoir efficiency as demonstrated in Table 10.
Table 11 compares anticipated injectivity rates (measured in barrels per minute, bpm) to actual results for four different situations. Furthermore, the error % for each case is given, which quantifies the difference between the anticipated and actual values. The quality of these forecasts is critical for determining the trustworthiness of the injectivity model used to estimate well performance.
Predictive Injectivity Analysis
The projected injectivity rates vary amongst the four scenarios, reflecting differing formation conditions, fluid characteristics, and wellbore restrictions.
Case 1 had the highest anticipated injectivity of 3.9 bpm, indicating either a reasonably permeable formation or an efficiently stimulated well. Case 2 has a much lower anticipated injectivity of 1.92 bpm, indicating a formation with moderate resistance to fluid injection, either due to greater skin values or decreased permeability. Case 3 has an intermediate expected value of 2.65 bpm, which falls between the injectivity performances of cases 1 and 2, indicating that the well may have suffered partial damage or improved moderately after stimulation. Case 4 has the lowest anticipated injectivity of 2.11 bpm, which, while on the low side, could nonetheless imply a well with adequate injectivity given certain operating limitations.
The variance in injectivity rates highlights the impact of formation heterogeneity, well conditions, and fluid injection efficiency, highlighting the importance of precise modeling for optimal reservoir management.
Error Analysis and Model Accuracy:
The error percentage is the difference between the expected and actual injectivity values. A lower absolute error indicates a more accurate and dependable prediction model. Examining the errors for each case:
Case 1 has an error of 0.025 (2.5%), suggesting a highly accurate forecast with small departure from the actual outcomes. Case 2 has a little higher error of 0.04 (4%), which is still within acceptable limits but indicates modest differences between projected and actual performance. This could be attributed to unaccounted formation variability or operating uncertainty. Case 3 has the lowest error at 0.018 (1.8%), indicating an extraordinarily precise forecast and validating the model’s robustness for this particular circumstance. Case 4 indicates a negative error of −0.004 (−0.4%), indicating that the projected injectivity was somewhat lower than the actual value, but the difference is insignificant, demonstrating good model reliability.
The consistently low error percentages across all four examples show that the predictive model is extremely dependable for determining injectivity rates. However, case 2’s comparatively higher inaccuracy indicates that certain well variables, such as formation damage, permeability changes, or fluid properties, may not have been properly represented in the forecast procedure.
The study carefully examines the parameters that influence well injectivity after emulsified acid therapy, using a sophisticated ridge regression model to predict and optimize treatment outcomes. The model’s inner workings are disclosed by its coefficients, which are presented in both scaled and descaled forms, giving a more nuanced understanding of how each factor contributes to the anticipated injectivity. These coefficients, generated from a careful analysis of the study’s data, quantify the relationship between various well features and treatment parameters, as well as the consequent injectivity, allowing for a more precise forecast of treatment efficiency.
The model’s predictive power is further confirmed by comparing its performance metrics to those of other machine learning models, including support vector machine (SVM) and gradient boosting regression. Metrics such as MAPE, RMSE, and R2 evaluate model accuracy and reliability. The ridge model performs exceptionally well, with a low MAPE of 2.1%, an RMSE of 0.13, and a R2 of 0.95, suggesting its ability to properly forecast injectivity with minimum error and effectively capture variability in data as shown in Table 12.
This thorough examination of the ridge model’s coefficients and performance measures provides useful information for optimizing emulsified acid treatments in oil reservoirs. Understanding the impact of each element on injectivity allows operators to customize treatments to individual well circumstances, increasing their effectiveness and overall reservoir performance. The study’s findings make a substantial contribution to the practical use of novel acid treatments, which aligns with the overall goal of improving reservoir injectivity and optimizing oil recovery. The rigorous methodology and extensive analysis give a solid foundation for future operations decision making, allowing for more informed choices that lead to better well performance and resource management.

6. Conclusions

This study clearly shows the revolutionary potential of emulsified acid as a novel stimulation treatment in the oil and gas industry [34]. The data demonstrate that emulsified acid improves well performance by decreasing acid reaction rates, facilitating deep fluid diversion, and maximizing wormhole formation, resulting in significant permeability improvement and higher injectivity or productivity index.
The article highlights the following:
  • Improved Permeability and Well Performance
    1.a
    Emulsified acid permits extensive wormholing and deep acid penetration, resulting in improved reservoir stimulation.
    1.b
    Case studies show that injectivity and production rates improve across a variety of well types, including gas and oil producers, water-alternating-gas (WAG) injectors, and dedicated water injectors.
    1.c
    The treatment enhances permeability by up to five times compared to unstimulated reservoirs, resulting in increased output and injection rates [35].
  • Impact on Flow Dynamics and Hydrocarbon Recovery.
    2.a
    Increased permeability improves hydrocarbon flow paths, allowing reservoirs to maintain higher production rates.
    2.b
    The treatment enhances the gas–oil ratio (GOR) by increasing gas mobility, which improves oil recovery.
    2.c
    Injected fluids (water/gas) travel deeper into the reservoir, making secondary and enhanced recovery procedures more efficient.
    2.d
    Higher permeability lowers pressure losses and improves reservoir efficiency, which correlates directly with increased injectivity and productivity.
  • Predictive Modeling for Treatment Optimization
    3.a
    A comprehensive ridge regression model was created to predict accurate injectivity related to emulsified acid treatments.
    3.b
    By including essential reservoir features and treatment variables, the model gives very precise injectivity estimates, decreasing uncertainty in treatment results.
    3.c
    This predictive capability allows operators to enhance treatment designs, tailor methods to specific wells, and improve decision making for future interventions.
  • Advanced Fluid Dynamics Modeling
    4.a
    A neural network model with 14 operational and reservoir parameters accurately replicates fluid behavior in emulsified acid treatments.
    4.b
    This model provides crucial insights into reservoir flow behavior, enabling treatment optimization and informed decision making.
    4.c
    The observed reductions in circulation pressure during stimulation and considerable pressure falls after injection corroborate the model’s ability to accurately capture fluid flow responses.
  • Economic and Sustainability Advantage
    5.a
    The novel acid treatment is economically viable, as improved injectivity and productivity result in better oil production rates and well profitability.
    5.b
    The study lays the framework for future advances in stimulation techniques, boosting the use of sustainable and data-driven solutions in the oil and gas sector.
    5.c
    Emulsified acid treatment, when paired with predictive modeling, enables optimal output, reduced environmental impact, and effective resource utilization, especially in unconventional reservoirs.
  • Scientific Contributions and Future Implications
    6.a
    This study improves our understanding of how emulsified acid interacts with reservoir rock, offering important insights into fluid dynamics and reaction mechanisms.
    6.b
    The use of advanced predictive modeling supports the case for emulsified acid as a scientifically verified, data-driven stimulating method.
    6.c
    Future applications could include improving treatment processes, moving into additional reservoir environments, and creating novel acid compositions adapted to specific geological conditions.
The consequences of this research go beyond immediate performance benefits. This study advances our understanding of how this innovative treatment interacts with reservoir rock by explaining the fluid dynamics and response mechanisms of emulsified acids. This information base is critical for improving treatment operation, creating new applications, and tackling the issues that come with various reservoir environments. The use of advanced predictive modeling enhances the value proposition of emulsified acid by providing a comprehensive approach to stimulation that combines scientific understanding with data-driven optimization.
Finally, emulsified acid appears as a game-changing stimulation technique capable of improving well performance and unlocking enormous production potential. Its unique features, combined with the predictive potential of machine learning algorithms, pave the way for a new age of enhanced oil recovery characterized by increased efficiency, lower environmental impact, and optimal resource utilization.

Author Contributions

Conceptualization, R.G.R. and C.R.; methodology, R.G.R., C.R., A.D., C.C.M., E.Y.Z., S.N. and M.T.; validation, R.G.R.; formal analysis, R.G.R., C.R., A.D., C.C.M., E.Y.Z., S.N. and M.T., investigation, R.G.R., C.R., A.D., C.C.M., E.Y.Z., S.N. and M.T.; resources, C.R.; writing—original draft preparation R.G.R., C.R., A.D., C.C.M., E.Y.Z., S.N. and M.T.; writing—review and editing R.G.R., C.R., A.D., C.C.M., E.Y.Z., S.N. and M.T.; visualization R.G.R.; supervision R.G.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

All relevant data are available in Superior Abu Dhabi laboratory and can be shared at charbelramy@superior.ae.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Describing emulsified acid stable mixture in water simulating real pumping stage into the formation: (a) emulsified acid in water; (b) emulsified acid stable emulsion.
Figure 1. Describing emulsified acid stable mixture in water simulating real pumping stage into the formation: (a) emulsified acid in water; (b) emulsified acid stable emulsion.
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Figure 2. Emulsion performance: (a) emulsified acid recipe stable emulsion in water; (b) drop test using emulsified acid to simulate its performance during operation.
Figure 2. Emulsion performance: (a) emulsified acid recipe stable emulsion in water; (b) drop test using emulsified acid to simulate its performance during operation.
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Figure 3. Corrosion test under pressure: (a) corrosion tester machine display; (b) corrosion tester machine specimen location and valves; (c) display of pressure gauge at 3000 Psi to simulate reservoir pressure.
Figure 3. Corrosion test under pressure: (a) corrosion tester machine display; (b) corrosion tester machine specimen location and valves; (c) display of pressure gauge at 3000 Psi to simulate reservoir pressure.
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Figure 4. Coupons status after corrosion testing: (a) low carbon steel L-80; (b) coiled tubing coupons QT-800; (c) Alloy-28 coupons.
Figure 4. Coupons status after corrosion testing: (a) low carbon steel L-80; (b) coiled tubing coupons QT-800; (c) Alloy-28 coupons.
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Figure 5. Optimizing chemical dosage for better corrosion rate.
Figure 5. Optimizing chemical dosage for better corrosion rate.
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Figure 6. Injection rate and well performance ahead being stimulated reaching an injection rate of 1 bpm.
Figure 6. Injection rate and well performance ahead being stimulated reaching an injection rate of 1 bpm.
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Figure 7. Injection rate and well performance after being stimulated reaching an injection rate of 4 bpm.
Figure 7. Injection rate and well performance after being stimulated reaching an injection rate of 4 bpm.
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Figure 8. Injection rate and well performance ahead being stimulated reaching an injection rate of 0.4 bpm.
Figure 8. Injection rate and well performance ahead being stimulated reaching an injection rate of 0.4 bpm.
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Figure 9. Injection rate and well performance after being stimulated reaching an injection rate of 2 bpm.
Figure 9. Injection rate and well performance after being stimulated reaching an injection rate of 2 bpm.
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Figure 10. Injection rate and well performance ahead being stimulated reaching an injection rate of 0.5 bpm.
Figure 10. Injection rate and well performance ahead being stimulated reaching an injection rate of 0.5 bpm.
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Figure 11. Injection rate and well performance after being stimulated reaching an injection rate of 2.7 bpm.
Figure 11. Injection rate and well performance after being stimulated reaching an injection rate of 2.7 bpm.
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Figure 12. Injection rate and well performance ahead being stimulated reaching an injection rate of 0.8 bpm.
Figure 12. Injection rate and well performance ahead being stimulated reaching an injection rate of 0.8 bpm.
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Figure 13. Injection rate and well performance after being stimulated reaching an injection rate of 2.1 bpm.
Figure 13. Injection rate and well performance after being stimulated reaching an injection rate of 2.1 bpm.
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Figure 14. Simulated reservoir parameters after being stimulated.
Figure 14. Simulated reservoir parameters after being stimulated.
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Figure 15. Simulated fluid invasion into the reservoir.
Figure 15. Simulated fluid invasion into the reservoir.
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Figure 16. Simulation results obtained in terms of average skin damage and average wormhole length for acid penetration.
Figure 16. Simulation results obtained in terms of average skin damage and average wormhole length for acid penetration.
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Figure 17. Fluid behavior along open hole length and reservoir thickness.
Figure 17. Fluid behavior along open hole length and reservoir thickness.
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Figure 18. Cumulative stock tank rate at the condition of skin damaged S = “0.01”.
Figure 18. Cumulative stock tank rate at the condition of skin damaged S = “0.01”.
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Figure 19. Fluid invasion and behavior after being stimulated along reservoir length and thickness.
Figure 19. Fluid invasion and behavior after being stimulated along reservoir length and thickness.
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Figure 20. Cumulative stock tank rate at the condition of skin damaged S = “−2.35” after stimulation using emulsified acid.
Figure 20. Cumulative stock tank rate at the condition of skin damaged S = “−2.35” after stimulation using emulsified acid.
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Figure 21. The pre- and post-injectivity results for four different cases evaluated in the field: (1) post-injectivity result by four times improvement; (2) post-injectivity result by four times improvement; (3) post-injectivity result by five times improvement; (4) post-injectivity result by 2.5 times improvement [24].
Figure 21. The pre- and post-injectivity results for four different cases evaluated in the field: (1) post-injectivity result by four times improvement; (2) post-injectivity result by four times improvement; (3) post-injectivity result by five times improvement; (4) post-injectivity result by 2.5 times improvement [24].
Processes 13 01138 g021
Table 1. Summary of experimental tests of emulsified acid treatment.
Table 1. Summary of experimental tests of emulsified acid treatment.
ParameterValue/RangeUnitsDescription
Acid-to-Diesel Ratio70:30:00RatioOptimal blend for achieving emulsion stability, controlled acid release, and deep formation penetration.
Emulsifier Concentration3–5 wt%wt%Ideal concentration to maintain a homogeneous two-phase emulsion under high reservoir temperatures and pressures.
Maximum Operating TemperatureUp to 275 °F°FDemonstrates high-temperature stability critical for deep carbonate reservoirs.
Reaction RetardationRegulatedQualitativeControlled reaction kinetics allow for extended wormhole propagation and uniform acid penetration.
Corrosion Rate ReductionSignificantly lower than HCl% reductionImproved performance in corrosion tests, leading to extended equipment life and reduced maintenance costs.
Injectivity Improvement2.5 to 5 times increaseRatioEnhanced reservoir stimulation leading to significant gains in well productivity.
Table 2. Corrosion tests on low carbon steel L-80 coupons using different corrosion inhibitors families at 200 °F.
Table 2. Corrosion tests on low carbon steel L-80 coupons using different corrosion inhibitors families at 200 °F.
Chemical CodeWater SUP-CISUP-IS-90LSUP-FA-01HCL Acid Diesel SUP-AE-03Low Carbon Steel L-80Corrosion Rate (g/m3)Pitting Index
Corrosion Inh. Quad Base
127083241728020QS850188.3NO PITS
226893341728020QS851181.56NO PITS
3266103441728020QS852171.98NO PITS
Corrosion Inh. Phosphonate Base
4263123541728020QS853145.22NO PITS
5261133641728020QS854120.87NO PITS
6260143641728020QS855111.753NO PITS
Corrosion Inh. Quinoline Base
7258153741728020QS85672.7NO PITS
8256163841728020QS85766.23NO PITS
9255173841728020QS85852.8NO PITS
Table 3. Corrosion test using QT-800 coupons for different inhibitors families for 12 h.
Table 3. Corrosion test using QT-800 coupons for different inhibitors families for 12 h.
Chemical CodeWaterSUP-ICI-72HSUP-CI-68SUP-IS-90LSUP-IS-91PSUP-FA-01SUP-SC-95HCL AcidSUP-ICI-32LDieselSUP-AE-03QT-800 CouponsCorrosion Rate (g/m2)Pitting Index
Corrosion Inh. Quad
195065330556011228020U7862180NO PITS
246070330556011228020U7863171NO PITS
307074330556011228020U7864162NO PITS
Corrosion Inh. Phosphonate
495065330556011528020U7865465NO PITS
546070330556011828020U7866386NO PITS
607074330556011828020U7867288NO PITS
Corrosion Inh. Quinoline
795065330556012028020M2113198NO PITS
846070330556012228020M2114160NO PITS
907074330556012528020M211590NO PITS
Table 4. Well petrophysical data.
Table 4. Well petrophysical data.
Well NumberCase 1Case 2 Case 3Case 4
Depth13,869 ft11,885 ft10,327 ft13,600 ft
Pay zone length3000 ft2885 ft4050 ft5014 ft
Pay zone diameter6″6″6″6″
Slotted liner 4.5″N/A
Completion size3 ½″3 ½″3 ½″3 ½″
Formation typeCaCO3CaCO3CaCO3CaCO3
Well typeGas producerOil producerInjectionInjection
Well profileHorizontalHorizontalHorizontalHorizontal
Table 5. Reservoir and well data 1.
Table 5. Reservoir and well data 1.
FactorsUOMQuantity
Reservoir TemperatureF200
Pore Fluid Permeability mD3 × 10−1
Reservoir Viscosity (Pa·s)cP0.5
TVD to Top of Open Section (m)ft5788
Acidizing TypeCarbonate
Avg. Surface Pressure Psi200
Initial SkinN/A5.08
Avg. Reservoir PressurePsi2722
Porosity %18.1
Frac Pressure Psi3650
TVD to Bot of Open Sectionft5774
Acid Volumebbls1190
Max. Surface Pressure17241724
Final SkinN/A−3
Table 6. Reservoir and well data 2.
Table 6. Reservoir and well data 2.
FactorsUOMQuantity
Reservoir TemperatureF200
Pore Fluid Permeability mD5.00 × 10−1
Reservoir Viscosity (Pa·s)cP0.52
TVD to Top of Open Section (m)ft5265
Acidizing TypeCarbonate
Avg. Surface Pressure Psi301
Initial SkinN/A0.01
Avg. Reservoir PressurePsi3151
Porosity %21
Frac Pressure Psi3850
TVD to Bot of Open Sectionft5625
Acid Volumebbls1200
Max. Surface Pressure15001500
Final SkinN/A−2.34
Table 7. Fluid injection rate and injectivity index calculation for conditions S = “0.01”.
Table 7. Fluid injection rate and injectivity index calculation for conditions S = “0.01”.
Tubing HeadBottomhole WaterDownholeWell Injectivity Index
Pressure (Psi)Pressure (Psi)Rate (STB/day)Rate (STB/day)Rate (STB/day/Psi)
3.997.340003760.3537354.42252
Table 8. Fluid injection rate and injectivity index calculation for conditions S = “−2.35”after stimulation.
Table 8. Fluid injection rate and injectivity index calculation for conditions S = “−2.35”after stimulation.
Tubing HeadBottomhole WaterDownholeWell Injectivity Index
Parameters Pressure (Psi)Pressure (Psi)Rate (STB/Day)Rate (STB/Day)Rate (STB/Day/Psi)
Values3997.340004434.2945235.21499
Table 9. Comparison in injection and reservoir fluid performance while using conventional HCl system and emulsified acid system.
Table 9. Comparison in injection and reservoir fluid performance while using conventional HCl system and emulsified acid system.
Conventional Acid System Emulsified Acid System
Case 1 Case 2 Case 1 Case 2
Factors for ModelPre-InjectivityPost-Injectivity Pre-InjectivityPost-Injectivity Factors for ModelPre-InjectivityPost-Injectivity Pre-InjectivityPost-Injectivity
Injectivity Flow Rate bpm 1.21.90.30.85Injectivity Flow Rate bpm 140.42
Circulating Pressure in Coiled Tubing Psi1300110040001250Circulating Pressure in Coiled Tubing Psi11001501200900
WHP Psi110010501000900WHP Psi12007001200600
Table 10. Data analysis and predicted values.
Table 10. Data analysis and predicted values.
DescriptionPredicted Values
Ridge Scaled coefficients−0.10.03−0.030.07−0.110.070.080.10.1
Ridge Scaled intercept6.23
Standard Scaler st_dev0.121.77.8600.91195.160.62362.86449.69
Standard Scaler means0.732370.13−0.124.812545.331.17950766.67
Descaled coefs−0.810.02014.11−0.1200.1300
Table 11. Predictive injection rates along with its error versus actual results.
Table 11. Predictive injection rates along with its error versus actual results.
ResultsCase 1 Case 2 Case 3 Case 4
Predicted Injectivity (bpm)3.91.922.652.11
Error (%)0.0250.040.018−0.004
Table 12. statistical data related to different model prediction results.
Table 12. statistical data related to different model prediction results.
Models ErrorsMAPERMSER2
SVM1.20.080.98
Gradient boosting regression1.80.20.85
Ridge2.10.130.95
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Ramy, C.; Ripeanu, R.G.; Nassreddine, S.; Tănase, M.; Zouein, E.Y.; Diniță, A.; Muresan, C.C. Recent Advances in Stimulation Techniques for Unconventional Oil Reservoir and Simulation of Fluid Dynamics Using Predictive Model of Flow Production. Processes 2025, 13, 1138. https://doi.org/10.3390/pr13041138

AMA Style

Ramy C, Ripeanu RG, Nassreddine S, Tănase M, Zouein EY, Diniță A, Muresan CC. Recent Advances in Stimulation Techniques for Unconventional Oil Reservoir and Simulation of Fluid Dynamics Using Predictive Model of Flow Production. Processes. 2025; 13(4):1138. https://doi.org/10.3390/pr13041138

Chicago/Turabian Style

Ramy, Charbel, Razvan George Ripeanu, Salim Nassreddine, Maria Tănase, Elias Youssef Zouein, Alin Diniță, and Constantin Cristian Muresan. 2025. "Recent Advances in Stimulation Techniques for Unconventional Oil Reservoir and Simulation of Fluid Dynamics Using Predictive Model of Flow Production" Processes 13, no. 4: 1138. https://doi.org/10.3390/pr13041138

APA Style

Ramy, C., Ripeanu, R. G., Nassreddine, S., Tănase, M., Zouein, E. Y., Diniță, A., & Muresan, C. C. (2025). Recent Advances in Stimulation Techniques for Unconventional Oil Reservoir and Simulation of Fluid Dynamics Using Predictive Model of Flow Production. Processes, 13(4), 1138. https://doi.org/10.3390/pr13041138

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