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Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery...
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Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 1 November 2024 | Viewed by 7029

Special Issue Editor

Dr. Syed Muhammad Shakil Hussain

E-Mail Website
Guest Editor
Center for Integrative Petroleum Research, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Interests: enhanced oil recovery; new material; drilling

Special Issue Information

Dear Colleagues,

The topic “Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes” covers a set of equations, assumptions, descriptions, fluid dynamics, and active processes in the reservoir using computer models. For this Special Issue, a collection of original articles and review articles covering the topic are invited. Advanced studies help us understand the nature of the analyzed method and its potential application in the real world. The topic of this Special Issue covers a large range of research, and we ask you to publish articles showing the proficiency, efficiency, and effectiveness of numerical methods to address scientific and engineering problems. We also invite articles highlighting in-depth calculations of reservoirs using advanced simulation software. The calculations include reservoir porosity, permeability, and reservoir engineering using computer models to identify flow fluids through porous media.

Dr. Syed Muhammad Shakil Hussain
Guest Editor

Manuscript Submission Information

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Keywords

  • reservoir engineering
  • computer models
  • fluid flow
  • porosity
  • permeability
  • fluid dynamics
  • thermal behavior
  • enhanced oil recovery
  • reservoir management
  • real-time data

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Published Papers (7 papers)

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Research

22 pages, 9588 KiB  
Article
On the Feasibility of Deep Geothermal Wells Using Numerical Reservoir Simulation
by Ali Nassereddine and Luis E. Zerpa
Processes 2024, 12(7), 1369; https://doi.org/10.3390/pr12071369 - 30 Jun 2024
Viewed by 759
Abstract
This study examines the geothermal energy extraction potential from the basement rock within the Denver–Julesburg Basin, focusing on the flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-shaped, V-shaped, inclined V-shaped, and pipe-in-pipe configurations against enhanced geothermal [...] Read more.
This study examines the geothermal energy extraction potential from the basement rock within the Denver–Julesburg Basin, focusing on the flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-shaped, V-shaped, inclined V-shaped, and pipe-in-pipe configurations against enhanced geothermal system setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. The results suggest that while closed-loop systems offer moderate temperature increases, Enhanced geothermal system configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations. Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
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37 pages, 43915 KiB  
Article
Microfluidic Insights into the Effects of Reservoir and Operational Parameters on Foamy Oil Flow Dynamics during Cyclic Solvent Injection: Reservoir-on-the-Chip Aided Experimental and Numerical Studies
by Ali Cheperli, Farshid Torabi and Morteza Sabeti
Processes 2024, 12(7), 1305; https://doi.org/10.3390/pr12071305 - 24 Jun 2024
Viewed by 689
Abstract
This study examines the microfluidic characterization of foamy oil flow dynamics in heterogeneous porous media. A total of 12 microfluidic CSI experiments were conducted using reservoir-on-the-chip platforms. In addition, detailed PVT analysis was performed to characterise the heavy oil/solvent systems. Moreover, a numerical [...] Read more.
This study examines the microfluidic characterization of foamy oil flow dynamics in heterogeneous porous media. A total of 12 microfluidic CSI experiments were conducted using reservoir-on-the-chip platforms. In addition, detailed PVT analysis was performed to characterise the heavy oil/solvent systems. Moreover, a numerical model constructed with CMG software package (2021.10) has been validated against the experimental findings in this study. A clear-cut visualization study provided by microfluidic systems revealed that factors including solvent type, pressure depletion rate, and reservoir parameters have a significant impact on foamy oil flow extension. It was found that a solvent containing a higher CO2 content demonstrated more effective performance compared with other solvent compositions, owing to its capability to reduce viscosity, enhance swelling, and offer more gas molecules due to its superior solubility. Additionally, a high pressure-depletion rate amplifies the driving force for bubble nucleation, as well as reducing the amount of time available for bubble coalescence. In addition, lower reservoir porosity impedes bubble movement and delays coalescence, thus extending the foamy oil flow. Furthermore, with the aid of a robust image analysis technique, it was discovered that utilizing 100% CO2 as a solvent resulted in a 17% increase in oil recovery over using 50% CO2 and 50% CH4. Furthermore, a 6% increase in oil recovery was achieved by applying a fast pressure depletion rate as opposed to a slow pressure depletion rate. Moreover, the numerical model constructed was found to be accurate in adjusting heavy oil recovery with an average relative error of 7.7%. Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
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15 pages, 4554 KiB  
Article
Multilayer Commingled Production Effects in Hydrate Reservoirs with Underlying Gas
by Shu Jia, Jin Yang, Ting Sun, Ali Reza Edrisi, Yuan Chen, Kejin Chen and Zhiliang Wen
Processes 2024, 12(6), 1225; https://doi.org/10.3390/pr12061225 - 14 Jun 2024
Viewed by 831
Abstract
Multilayer commingled production is a widely used development method to improve the production capacity of gas reservoirs. However, there is currently limited research on the gas production characteristics of multilayer commingled production in hydrate reservoirs with underlying gas. The objective of this study [...] Read more.
Multilayer commingled production is a widely used development method to improve the production capacity of gas reservoirs. However, there is currently limited research on the gas production characteristics of multilayer commingled production in hydrate reservoirs with underlying gas. The objective of this study was to analyze the characteristics of multilayer commingled production in order to determine suitable hydrate reservoirs for such a development method. Firstly, we employed analytical solutions to the equations of fluid flow in porous media to determine the factors affecting the production capacity. Then, by employing numerical simulation and depressurization methods, the rates of gas production and gas release from hydrate dissociation in a single production well were estimated. Additionally, the production capacity ratio of multilayer commingled production and separated-layer production was proposed. The influence of different reservoir characteristics on multilayer commingled production yield was determined and plotted. When there is an interlayer between hydrates and the underlying gas, the formation pressure ratio is the decisive factor affecting the multilayer commingled production yield. When there is no interlayer, the multilayer commingled production rate will increase with an increase in the permeability ratio, hydrate saturation, and underlying gas saturation. This study provides a theoretical foundation for predicting the production capacity of hydrate reservoirs, as well as assistance in selecting the hydrate reservoirs most suitable for multilayer commingled production. Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
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26 pages, 4321 KiB  
Article
Leveraging Designed Simulations and Machine Learning to Develop a Surrogate Model for Optimizing the Gas–Downhole Water Sink–Assisted Gravity Drainage (GDWS-AGD) Process to Improve Clean Oil Production
by Watheq J. Al-Mudhafar, Dandina N. Rao and Andrew K. Wojtanowicz
Processes 2024, 12(6), 1174; https://doi.org/10.3390/pr12061174 - 7 Jun 2024
Viewed by 818
Abstract
The Gas and Downhole Water Sink–Assisted Gravity Drainage (GDWS-AGD) process addresses gas flooding limitations in reservoirs surrounded by infinite-acting aquifers, particularly water coning. The GDWS-AGD technique reduces water cut in oil production wells, improves gas injectivity, and optimizes oil recovery, especially in reservoirs [...] Read more.
The Gas and Downhole Water Sink–Assisted Gravity Drainage (GDWS-AGD) process addresses gas flooding limitations in reservoirs surrounded by infinite-acting aquifers, particularly water coning. The GDWS-AGD technique reduces water cut in oil production wells, improves gas injectivity, and optimizes oil recovery, especially in reservoirs with high water coning. The GDWS-AGD process installs two 7-inch production casings bilaterally. Then, two 2-3/8-inch horizontal tubings are completed. One tubing produces oil above the oil–water contact (OWC) area, while the other drains water below it. A hydraulic packer in the casing separates the two completions. The water sink completion uses a submersible pump to prevent water from traversing the oil column and entering the horizontal oil-producing perforations. To improve oil recovery in the heterogeneous upper sandstone pay zone of the South Rumaila oil field, which has a strong aquifer and a large edge water drive, the GDWS-AGD process evaluation was performed using a compositional reservoir flow model in a 10-year prediction period in comparison to the GAGD process. The results show that the GDWS-AGD method surpasses the GAGD by 275 million STB in cumulative oil production and 4.7% in recovery factor. Based on a 10-year projection, the GDWS-AGD process could produce the same amount of oil in 1.5 years. In addition, the net present value (NPV) given various oil prices (USD 10–USD 100 per STB) was calculated through the GAGD and GDWS-AGD processes. The GDWS-AGD approach outperforms GAGD in terms of NPV across the entire range of oil prices. The GAGD technique became uneconomical when oil prices dropped below USD 10 per STB. Design of Experiments–Latin Hypercube Sampling (DoE-LHS) and radial basis function neural networks (RBF-NNs) were used to determine the optimum operational decision variables that influence the GDWS-AGD process’s performance and build the proxy metamodel. Decision variables include well constraints that control injection and production. The optimum approach increased the recovery factor by 1.7525% over the GDWS-AGD process Base Case. With GDWS-AGD, water cut and coning tendency were significantly reduced, along with reservoir pressure, which all led to increasing gas injectivity and oil recovery. The GDWS-AGD technique increases the production of oil and NPV more than the GAGD process. Finally, the GDWS-AGD technique offers significant improvements in oil recovery and income compared to GAGD, especially in reservoirs with strong water aquifers. Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
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15 pages, 6030 KiB  
Article
Surfactant–Polymer Flooding: Chemical Formula Design and Evaluation for High-Temperature and High-Salinity Qinghai Gasi Reservoir
by Jinlong Sun, Yifeng Liu, Xiuyu Zhu, Futang Hu, Yuanyuan Wang, Xiaoling Yi, Zhuoyan Zhu, Weidong Liu, Youyi Zhu and Qingfeng Hou
Processes 2024, 12(6), 1082; https://doi.org/10.3390/pr12061082 - 24 May 2024
Viewed by 952
Abstract
The Gasi reservoir in the Qinghai oilfield is a typical high-temperature and high-salinity reservoir, with an average temperature and average salinity of 70.0 °C and 152,144 mg/L, respectively. For over 30 years since 1990, water flooding has been the primary method for enhancing [...] Read more.
The Gasi reservoir in the Qinghai oilfield is a typical high-temperature and high-salinity reservoir, with an average temperature and average salinity of 70.0 °C and 152,144 mg/L, respectively. For over 30 years since 1990, water flooding has been the primary method for enhancing oil recovery. Recently, the Gasi reservoir has turned into a mature oilfield. It possesses a high water cut of 76% and a high total recovery rate of 47%. However, the main developing enhanced oil recovery (EOR) technology for the development of the Gasi reservoir in the next stage is yet to be determined. Surfactant–polymer (SP) flooding, which can reduce the oil–water interfacial tension and increase the viscosity of the water phase, has been widely applied to low-temperature and low-salinity reservoirs across China in the past few decades, but it has rarely been applied to high-temperature and high-salinity reservoirs such as the Gasi reservoir. In this study, the feasibility of SP flooding for high-temperature and high-salinity reservoirs was established. Thanks to the novel surfactant and polymer products, an SP flooding formula with surfactants ZC-2/B2 and polymer BRH-325 was proposed for Gasi. The formula showed a low interfacial tension of 10−2 mN/m and a high viscosity of 18 MPa·s in simulated reservoir conditions. The oil displacement experiment demonstrated that this formula can enhance the oil recovery rate by 26.95% upon water flooding at 64.64%. This study provides a feasible EOR candidate technology for high-temperature and high-salinity reservoirs, as exemplified by the Qinghai Gasi reservoir. Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
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13 pages, 844 KiB  
Article
Production Prediction Model of Tight Gas Well Based on Neural Network Driven by Decline Curve and Data
by Minjing Chen, Zhan Qu, Wei Liu, Shanjie Tang, Zhengkai Shang, Yanfei Ren and Jinliang Han
Processes 2024, 12(5), 932; https://doi.org/10.3390/pr12050932 - 3 May 2024
Cited by 1 | Viewed by 1049
Abstract
The accurate prediction of gas well production is one of the key factors affecting the economical and efficient development of tight gas wells. The traditional oil and gas well production prediction method assumes strict conditions and has a low prediction accuracy in actual [...] Read more.
The accurate prediction of gas well production is one of the key factors affecting the economical and efficient development of tight gas wells. The traditional oil and gas well production prediction method assumes strict conditions and has a low prediction accuracy in actual field applications. At present, intelligent algorithms based on big data have been applied in oil and gas well production prediction, but there are still some limitations. Only learning from data leads to the poor generalization ability and anti-interference ability of prediction models. To solve this problem, a production prediction method of tight gas wells based on the decline curve and data-driven neural network is established in this paper. Based on the actual production data of fractured horizontal wells in three tight gas reservoirs in the Ordos Basin, the prediction effect of the Arps decline curve model, the SPED decline curve model, the MFF decline curve model, and the combination of the decline curve and data-driven neural network model is compared and analyzed. The results of the case analysis show that the MFF model and the combined data-driven model have the highest accuracy, the average absolute percentage error is 14.11%, and the root-mean-square error is 1.491, which provides a new method for the production prediction of tight gas wells in the Ordos Basin. Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
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20 pages, 7834 KiB  
Article
A Comprehensive Investigation of the Relationship between Fractures and Oil Production in a Giant Fractured Carbonate Field
by Riyaz Kharrat, Ali Kadkhodaie, Siroos Azizmohammadi, David Misch, Jamshid Moghadasi, Hashem Fardin, Ghasem Saedi, Esmaeil Rokni and Holger Ott
Processes 2024, 12(4), 631; https://doi.org/10.3390/pr12040631 - 22 Mar 2024
Viewed by 1263
Abstract
This study examines the connections between various fracture indicators and production data with an example from one of the giant fields in the Middle East producing complex fractured carbonate lithologies. The field under study hosts two reservoirs with a long development and production [...] Read more.
This study examines the connections between various fracture indicators and production data with an example from one of the giant fields in the Middle East producing complex fractured carbonate lithologies. The field under study hosts two reservoirs with a long development and production history, including carbonates from the Asmari and Bangestan Formations. A fracture intensity map was generated based on the interpretation of image logs from 28 wells drilled within the field. Mud loss data were collected and mapped based on the geostatistical Gaussian Random Function Simulation (GRFS) algorithm. Maximum curvature maps were generated based on Asmari structural surface maps. Comparing the results shows a good agreement between the curvature map, fault distribution model, mud loss map, fracture intensity map, and productivity index. The results of image log interpretations led to the identification of four classes of open fractures, including major open fractures, medium open fractures, minor open fractures, and hairline fractures. Using the azimuth and dip data of the four fracture sets mentioned above, the fracture intensity log was generated as a continuous log for each well with available image log data. For this purpose, the fracture intensity log and a continuous fracture network (CFN) model were generated. The continuous fracture network model was used to generate a 3D discrete fracture network (DFN) for the Asmari Formation. Finally, a 3D upscaled model of fracture dip and azimuth, fracture porosity, fracture permeability, fracture length, fracture aperture, and the sigma parameter (the connectivity index between matrix and fracture) were obtained. The results of this study can illuminate the modeling of intricate reservoirs and the associated production challenges, providing insights not only during the initial production phase but also in the application of advanced oil recovery methods, such as thermal recovery. Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
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