Overview of the Progress in Practice and Experimental Research in Petroleum and Natural Gas Engineering

1. Introduction

The global energy system is undergoing unprecedented changes. Despite the urgent need for the development of existing renewable energy systems, the promotion of carbon neutrality goals, and enhanced energy security, oil and natural gas—traditional fossil fuels—continue to provide most of humanity’s primary energy needs [1,2,3]. Our reserves of oil are substantial; however, complex geological and geographical environments, which are the result of different mechanisms behind the formation of oil in terrestrial and marine settings, pose significant challenges to their efficient extraction. Simultaneously, there are considerable shale gas reserves within the ground [4,5,6], and other natural gases, such as tight sandstone gas and coalbed methane, are not only abundant but also widely distributed. The geological conditions under which these resources are found are similarly complex [7,8,9,10], characterized by high ground stress, fault structures, low porosity, and fractures in gas reservoirs. These factors complicate the efficient extraction of natural gas. However, the efficient extraction of oil and natural gas is crucial to minimizing resource waste. For instance, in regions where extraction is challenging, abandonment can lead to the permanent loss of unexploited resources due to geological disturbances, complicating future extraction efforts. On the other hand, efficient mining introduces new challenges related to mining equipment, processes, and technological advancements, necessitating the development of advanced methodologies and predictive techniques.

Efficient oil and gas recovery methods, enhanced oil recovery, fracture propagation prediction, and reservoir management continue to pose significant challenges in the field of oil and gas extraction. The development of unconventional resources, such as shale oil and gas, tight gas, and natural gas hydrates, is reshaping the global energy supply landscape. Meanwhile, the advancement of conventional oil and gas resources is undergoing profound transformation through the integration of digital technology. The real-time data analysis of intelligent drilling systems, completion systems, and nanoscale fracturing fluid technology exemplifies this change [11,12,13]. Intelligent drilling systems enhance drilling efficiency and mitigate the risks associated with mountain springs during construction by enabling real-time data analysis. The use of nanoparticle fracturing fluid technology in unconventional oil and gas development increases the efficiency of shale gas recovery. The integration of new composite-material pipelines into smart pipeline monitoring systems, which utilize IoT technology, significantly advances the storage, transportation, and extraction of oil and gas. Methane capture technology effectively reduces carbon emissions. Photothermal-driven geological storage systems facilitate negative carbon cycling in the CO₂-enhanced oil recovery (EOR) process. Hybrid power supply systems that combine offshore wind power, photovoltaic power generation, and oil and gas platforms play a crucial role in reducing carbon emissions. Digital models of deep-sea oil fields substantially improve the accuracy of development plans. Artificial intelligence algorithms are vital for predicting oil and gas reservoirs, enhancing prediction accuracy. Moreover, the wear resistance of graphene-reinforced drill bits has been significantly improved. Some of the innovations in oil and gas storage and transportation technologies are also noteworthy. In response to carbon neutrality targets, the oil and gas industry is establishing a new environmental technology framework. Digital twin technology is redefining the oil and gas development model, while the application of artificial intelligence, big data, and Internet of Things (IoT) technology is accelerating the digital transformation of the industry. Over the next decade, several changes are expected, including the upgrade of carbon management technology from auxiliary processes to core business units, the promotion of intelligent transitions across the entire industry chain through digital twin systems, and the collaborative design of engineering systems that include wind, solar, and hydrogen technologies. These changes not only extend the economic lifecycle of fossil fuels but also strive to create a strategic buffer period during which new energy systems can mature.

This Special Issue aims to highlight recent developments and innovations in oil and gas engineering, with a particular emphasis on hydraulic fracturing and enhanced oil recovery (EOR) technologies, as well as the application of advanced artificial intelligence in oil and gas extraction practices and experimental research. These methods are essential to optimizing extraction processes and enhancing production efficiency. We also seek to address advancements in drilling technology, which play a critical role in the exploration and extraction of oil and gas resources. Research topics of interest included innovations in hydraulic fracturing fluids and proppants, the modeling and simulation of fracture propagation, environmental impacts and mitigation strategies related to hydraulic fracturing, real-time monitoring and adaptive fracturing techniques, chemical and thermal EOR methods, successful case studies of EOR implementations, the integration of EOR with reservoir management, advances in drilling technology and equipment, intelligent construction in oil and gas extraction, drilling optimization and cost reduction strategies, wellbore stability and control, and new materials and technologies for drilling in challenging environments. This collective effort aims to further our understanding of oil and gas engineering. A total of 11 high-quality papers have been published in this Special Issue, all of which have undergone rigorous review and screening.

2. Recent Developments in Petroleum and Natural Gas Engineering

Scholars have conducted extensive research on topics related to petroleum and natural gas engineering. The papers published in our Special Issue cover key aspects of this engineering, and we have elaborated on them below.

Li et al. utilized artificial intelligence and GRN-VSN neural networks to predict oilfield indicators. First, they input highly relevant parameters into that serve as predictors of the key indicators driven by artificial intelligence into their model. Subsequently, the Shapley Additive Explanation (SHAP) was employed to interpret the artificial model and evaluate its predicted results. Additionally, its performance was compared to that of the ResNet-50 neural network, long short-term memory (LSTM) neural network, and backpropagation (BP) neural network in terms of oil extraction efficiency. Among these networks, LSTM excels in continuous sequence prediction and demonstrates a superior performance. Artificial intelligence algorithms have significantly enhanced the prediction accuracy of key production indicators in offshore oil fields, achieving an accuracy rate of at least 92%.

Aiming at improving the extraction efficiency of petroleum and natural gas, Chen et al. investigated the characteristics of a reservoir within a specific block of the Ordos Basin, analyzing the flow lines and horizontal principal stresses present to identify the conditions necessary for the formation of waterflood-induced fractures (WIFs). Subsequently, they constructed a permeability evolution equation for the fractured reservoir and cap rock areas between oil wells. Finally, numerical simulation methods were employed to examine the characteristics of WIFs in horizontal and vertical well networks by applying different injection modes. Notably, the study revealed that WIFs formed at locations where the maximum principal stress and flow were aligned, influencing the distribution of permeability. To effectively adjust the extension range of WIFs, the authors recommended controlling the injection rate of the vertical well along the flow line and at the maximum principal stress point, thereby cyclically optimizing oil production. Additionally, Wei et al. provided a comprehensive introduction to the principles of and technology behind oxygen-reducing agent-assisted gravity drainage (OAGD). They conducted a detailed analysis of the factors affecting oil displacement, which primarily include the reservoir dip angle, layer characteristics, injection rate, and low-temperature oxidation reactions. Low-temperature oxidation significantly enhances oil recovery (EOR) due to the dynamic balance between fuel deposition and light hydrocarbon volatilization, as well as the synergistic optimization of the concentration, temperature, and pressure of oxygen. To expand the sweeping volume and delay gas breakthroughs, the injection rate can be appropriately controlled to stabilize the oil–gas interface. The enhanced gravity separation effect results in highly efficient oil displacement in steeply dipping reservoirs.

The following studies focus on fracture networks in petroleum and natural gas reservoirs. Shale oil reservoirs are characterized by low permeability and porosity, necessitating the use of horizontal wells with multiple fractures for their extraction. Multiphase flow characteristics complicate fluid movement during shale oil extraction. Liu et al. propose a productivity model for multi-fractured horizontal wells in shale oil reservoirs, which they establish using the principles of pressure superposition, conformal transformation, and fractal theory, which are solved simultaneously. The effectiveness of this model has been validated using on-site experimental data. Another group of authors conducted an analysis of various complex factors affecting the productivity of shale oil wells. Their research findings indicate that phase transition behavior significantly reduces oil production, while fluid desorption markedly increases production. Gu et al. employed a Pearson correlation analysis to investigate the relationships between natural fractures, mineral composition and content, horizontal stress differences, and yield parameters, aiming to evaluate the impact of fracture network complexity on yield. Furthermore, they proposed the fracture network index (FNI) model, which is based on the support vector machine (SVM) algorithm and an improved particle swarm optimization (IPSO) algorithm, to assess the complexity of fracture networks. Finally, the correlation between the fracture network index and gas produced from various hydraulic fracturing operations was analyzed and quantified. Their research findings indicate that the Pearson correlation coefficient is 0.39, revealing that natural fracture density has a dominant controlling effect on gas production, while other factors exert relatively minor effects. The coefficient of determination (R²) for the IPSO-SVM-FNI model, when deployed on the training set, was better than that of traditional models, demonstrating its superior data fitting. The IPSO-SVM-FNI model also exhibits high prediction accuracy. The fracture network index (FNI) predominantly falls within the range of [0.2, 0.8]. For hydraulic fracturing operations with a high fracture network index (FNI), oil and gas production is comparatively high, indicating a positive correlation between reservoir fracture complexity and shale gas production.

The following studies focus on oil and gas extraction. Chen et al. utilized a surfactant polymer (SP) system combined with a viscosity reducer to enhance oil recovery efficiency. The combination of OAB (a beta surfactant) and LPS-3 (an anionic surfactant) significantly reduced interfacial tension and enhanced lotion stability, with optimal results achieved when their ratio was 1:9. Their research indicates that the BRH-325 polymer possesses multiple desirable characteristics, including enhanced viscosity, resistance to high temperatures, and long-term stability. The viscosity reducer contains graphene nanowedges, which can decrease the viscosity of heavy oil by approximately 97%. Indoor core flooding simulation experiments were conducted to verify the effectiveness of this method, resulting in an increase in the recovery rate of about 33%. Microbial-enhanced oil recovery remains a compelling area of research. Zhao et al. collected outcrop rock samples and conducted simulation experiments on microbial-enhanced oil recovery. Concurrently, they studied the changes in biochemical parameters, including Bacillus subtilis concentration, nutrient concentration, displacement pressure, and surface tension, seen throughout the process. Their research findings indicate that after injecting microorganisms into reservoirs, cells and nutrients tend to be distributed along the primary pathways of the injection wells and fluid flow. Bacteria exhibit adsorption and retention abilities which are greater than those of nutrients. The combined effects of microbial reproduction and metabolic products increase the pressure within the model. However, from the injection well to the production well, pressure gradually decreases, with high-pressure areas primarily concentrated near the injection well. The fermentation mixture of Bacillus subtilis can enhance oil recovery by 6.5%.

Regarding other research areas, two-dimensional nuclear magnetic resonance (NMR) provides rapid measurements in petroleum and natural gas engineering. Zhang et al. conducted research on high-porosity and high-permeability heavy-oil loose-sandstone reservoirs using two-dimensional NMR testing technology. They obtained the distribution patterns of crude oils with varying viscosities from the NMR spectra. Additionally, a model relating NMR parameters to oil viscosity was established using T1 and T2 spectra, thereby creating a novel method for estimating oil viscosity. This technology has been applied in practical engineering, and results indicate that the error between the actual viscosity and the theoretically calculated viscosity of the oil is 15%. The reliability of the method was further validated by analyzing the consistency between the oil discrimination chart and the oil type. This research meets the accuracy requirements of well logging interpretation. Zhang et al. employed the pressure transient analysis (PTA) method to examine the shut-in pressure data of shale gas wells following fracturing. The results indicated that the pressure derivative gradually dispersed after one day of shut-in. Two wells exhibited zero-slope pressure derivatives over one week of fluid immersion, suggesting that the duration of fluid immersion was appropriate. In contrast, the other four wells demonstrated an increase in their pressure derivative after one week of fluid immersion, indicating that a longer immersion period is necessary to fully achieve the desired effect. Xu et al. established a heat transfer model for a composite insulation structure featuring multi-layer insulation and liquid nitrogen screen (LNCS) insulation, as well as a numerical model. They investigated the changes in the natural convection characteristics, thermal stratification, pressure distribution, and self-pressurization characteristics of LHe-4 storage tanks. Additionally, a self-pressurization thermodynamic model for LHe-4 storage tanks was developed. Their research findings indicate that the mLee model significantly improves the prediction of self-enhancement characteristics compared to the Lee model. An increase in operational time is associated with a rise in the thermal stratification degree (TSD) of the storage tank, and gradual increases in operational duration increase the self-pressurization of the tank. The graph of the interface mass transfer rate reveals a pattern of low values in the middle and high values at both ends, which is attributed to the strong evaporation point on the wall in contact with the phase interface. Yang et al. investigated the fixed tooth strength of roller drill bits, testing the maximum fastening force of the fixed teeth under various conditions and analyzing the change in this force. Their research findings indicate that high temperatures can weaken the strength of the fixed teeth. The maximum fastening force decreases with increasing temperature, becoming approximately 49–65% lower than that in a normal-temperature environment. Under consistent temperature conditions, the maximum fastening force occurs at a perforation distance of 10 mm. An increase in tooth diameter is associated with a rise in the maximum fastening force, indicating an improvement in the fixing effect. The relationship between maximum fastening force and interference fit is non-linear, with the maximum tightening force occurring at an interference fit of 0.095 mm.

Despite the significant achievements of this Special Issue, oil and gas engineering continues to face numerous challenges. For instance, technological bottlenecks in deepwater oil and gas development and ultra-deep resource exploration urgently need to be addressed. Cross-disciplinary technologies, such as hydrogen energy coupling and carbon capture, utilization, and storage (CCUS), require enhanced system integration. Additionally, the use of artificial intelligence in oil and gas extraction engineering needs to be further developed, and innovations in high-temperature drill bit design and production processes for deep oil and gas extraction are required. The advancement of efficiency and environmental adaptability in oil and gas extraction will inevitably lead to the establishment of a diversified, intelligent, and sustainable new energy system.

3. Closing Remarks

The papers published in this Special Issue addresses various aspects of oil and gas extraction, including improvements in extraction methods, reservoir modifications, and fracture network prediction. Although petroleum and natural gas engineering is a broad field, the findings presented in this Special Issue will stimulate and enhance research in the industry. Understanding these topics is crucial for recognizing the latest advancements in oil and gas engineering. We would like to express our gratitude to all the authors who contributed to this Special Issue. Given the broad scope of oil and gas engineering, we will continue to explore new research directions with these scholars and engage in in-depth investigations.