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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 7506

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Special Issue Editors

Dr. Jiaxue Li

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Guest Editor

Engineering Institute, China University of Petroleum (Beijing), Beijing 102249, China
Interests: oil and gas engineering; oilfield surface engineering chemistry; natural gas transportation; harmless treatment technology for oil and gas field waste; drilling fluid and completion fluid

Dr. Pengfei Zhao

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Guest Editor

School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
Interests: petroleum engineering; reservoir physics; rock mechanics

Special Issue Information

Dear Colleagues,

This Special Issue aims to highlight recent advancements and innovations in the field of petroleum and natural gas engineering, with a particular focus on hydraulic fracturing and enhanced oil recovery (EOR) techniques. These methods are crucial for optimizing extraction processes and improving overall production efficiency. We also seek to address the latest developments in drilling technologies, which play a supporting role in the exploration and extraction of petroleum and natural gas resources.

Topics of interest include, but are not limited to, the following:

Innovations in hydraulic fracturing fluids and proppants;
Modeling and simulation of fracture propagation;
Environmental impacts and mitigation strategies of hydraulic fracturing;
Real-time monitoring and adaptive fracturing techniques;
Chemical, thermal, and gas injection EOR methods;
Case studies of successful EOR implementations;
Integration of EOR with reservoir management;
Advances in drilling technologies and equipment;
Drilling optimization and cost reduction strategies;
Wellbore stability and control;
New materials and techniques for drilling in challenging environments.

We welcome submissions of original research papers, review articles, and case studies that contribute to the understanding and advancement of these critical areas within petroleum and natural gas engineering. This Special Issue aims to compile a comprehensive collection of cutting-edge research that will serve as a valuable resource for researchers, engineers, and practitioners in the field.

Dr. Jiaxue Li
Dr. Pengfei Zhao
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

hydraulic fracturing
enhanced oil recovery (EOR)
drilling technologies
reservoir management
environmental impact

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Published Papers (10 papers)

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Research

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16 pages, 3653 KiB

Open AccessArticle

Two-Dimensional Physical Simulation of the Seepage Law of Microbial Flooding

by Yongheng Zhao, Jianlong Xiu, Lixin Huang, Lina Yi and Yuandong Ma

Energies 2025, 18(5), 1246; https://doi.org/10.3390/en18051246 - 4 Mar 2025

Viewed by 449

Abstract

The study of seepage laws during microbial enhanced oil recovery helps to elucidate the mechanisms behind microbial flooding, and the use of large-scale physical simulation experimental devices can more objectively and accurately investigate the seepage laws of microbes in porous media, and evaluate the oil displacement efficiency of microbial systems. In this study, physical simulation experiments of microbial flooding were conducted via a slab outcrop core, and the biochemical parameters such as the concentration of Bacillus subtilis, nutrient concentration, surface tension, and displacement pressure data were tracked and evaluated. The analysis revealed that the characteristics of the pressure field change during microbial flooding and elucidates the migration rules of microbes and nutrients, as well as the change rule of surface tension. The results show that after the microbial system is injected, cells and nutrients are preferentially distributed near the injection well and along the main flow paths, with the bacterial adsorption and retention capacity being greater than those of the nutrient agents. Owing to the action of microorganisms and their metabolites, the overall pressure within the model increased, From the injection well to the production well, the pressure in the model decreases stepwise, and the high-pressure gradient zone is mainly concentrated near the injection well. The fermentation mixture of Bacillus subtilis increased the injection pressure by 0.73 MPa, reduced the surface tension by up to 49.8%, and increased the oil recovery rate by 6.5%. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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19 pages, 4331 KiB

Open AccessArticle

Experimental Study on Surfactant–Polymer Flooding After Viscosity Reduction for Heavy Oil in Matured Reservoir

by Xiaoran Chen, Qingfeng Hou, Yifeng Liu, Gaohua Liu, Hao Zhang, Haojie Sun, Zhuoyan Zhu and Weidong Liu

Energies 2025, 18(3), 756; https://doi.org/10.3390/en18030756 - 6 Feb 2025

Cited by 1 | Viewed by 718

Abstract

An advanced enhanced oil recovery (EOR) method was investigated, employing a surfactant–polymer (SP) system in combination with a viscosity reducer for application in a heavy oil reservoir within the Haiwaihe Block, Liaohe Oilfield, in China. Significant advantages were observed through the combination of LPS-3 (an anionic surfactant) and OAB (a betaine surfactant) in reducing interfacial tension and enhancing emulsion stability, with the optimal results achieved at the ratio of 9:1. The BRH-325 polymer was found to exhibit superior viscosity enhancement, temperature resistance, and long-term stability. Graphene nanowedges were utilized as a viscosity reducer, leading to a viscosity reduction in heavy oil of 97.43%, while stability was maintained over a two-hour period. The efficacy of the combined system was validated through core flooding experiments, resulting in a recovery efficiency improvement of up to 32.7%. It is suggested that the integration of viscosity reduction and SP flooding could serve as a promising approach for improving recovery in mature heavy oil reservoirs, supporting a transition toward environmentally sustainable, non-thermal recovery methods. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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12 pages, 2678 KiB

Open AccessArticle

Use of Pressure Transient Analysis Method to Assess Fluid Soaking in Multi-Fractured Shale Gas Wells

by Jun Zhang, Boyun Guo and Majid Hussain

Energies 2025, 18(3), 549; https://doi.org/10.3390/en18030549 - 24 Jan 2025

Viewed by 582

Abstract

Multi-stage hydraulic fracturing is a key technology adopted in the energy industry to make shale gas and shale oil fields profitable. Post-frac fluid soaking before putting wells into production has been found essential for enhancing well productivity. Finding the optimum time to terminate the fluid-soaking process is an open problem to solve. Post-frac shut-in pressure data from six wells in two shale gas fields were investigated in this study based on pressure transient analysis (PTA) to reveal fluid-soaking performance. It was found that pressure-derivative data become scattering after 1 day of well shut in. The overall trend of pressure-derivative data after the first day of well shut in should reflect the effectiveness of fluid soaking. Two wells exhibited flat (zero-slope) pressure derivatives within one week of fluid soaking, indicating adequate time of fluid soaking. Four wells exhibited increasing pressure derivatives within one week of fluid soaking, indicating inadequate time of fluid soaking. This observation is consistent with the reported well’s Estimated Ultimate Recovery (EUR). This study presents a new approach to the assessment of post-frac fluid-soaking performance with real-time shut-in pressure data. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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29 pages, 11718 KiB

Open AccessArticle

Numerical Study on Heat Leakage, Thermal Stratification, and Self-Pressurization Characteristics in Liquid Helium Storage Tanks

by Jing Xu, Fa’an Liu, Jianguo Zhang, Chao Li, Qinghua Liu, Changjun Li, Wenlong Jia, Shixiong Fu and Longjiang Li

Energies 2024, 17(24), 6254; https://doi.org/10.3390/en17246254 - 11 Dec 2024

Viewed by 681

Abstract

During the operation of liquid-phase He-4 (LHe-4) storage tanks, heat leakage changes the thermophysical parameters and phase properties of the LHe-4 in the tanks, resulting in the thermal layering phenomenon. This phenomenon is characterized by the LHe-4 temperature gradient and pressure increase (self-pressurization) phenomena in the tanks. Based on the Layer-by-Layer model, a heat transfer model of a composite adiabatic structure with multilayer insulation and liquid nitrogen screen (LNCS) insulation was established, and the Neumann boundary heat flux of the thermal response model was determined. A numerical simulation model of the thermal response of a liquid helium storage tank was established. The spatial and temporal evolutions of the pressure distribution, natural convection characteristics, thermal stratification characteristics, and self-pressurization characteristics of the LHe-4 tank were investigated. Finally, the self-pressurization thermodynamic model of the LHe-4 storage tank was built based on the isothermal saturation and homogeneous model. It is shown that the predictive performance of the mLee model for the self-boosting characteristics (relative deviation of 14.32%) was significantly improved compared with that of the Lee model (relative deviation of 39.64%). The thermal stratification degree (TSD) of the tank increased with the operation time, with TSDs of 1.023, 1.028, and 1.036 at 1 h, 2 h, and 3 h, which exacerbated the self-pressurization of the tank. The wall surface in contact with the phase interface is a strong evaporation point, so the interfacial mass transfer rate maps show a pattern of high at both ends and low in the middle. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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15 pages, 1103 KiB

Open AccessArticle

Analysis on Correlation Model Between Fracture Network Complexity and Gas-Well Production: A Case in the Y214 Block of Changning, China

by Zhibin Gu, Bingxiao Liu, Wang Liu, Lei Liu, Haiyu Wei, Bo Yu, Lifei Dong, Pinzhi Zhong and Hun Lin

Energies 2024, 17(23), 6026; https://doi.org/10.3390/en17236026 - 29 Nov 2024

Viewed by 645

Abstract

The fracture network of the Y214 block in the Changning area of China is complex, and there are significant differences in the productivity of different shale gas wells. However, traditional machine learning models have problems such as missing key parameters, poor fitting effects and low prediction accuracy, which make it difficult to effectively evaluate the impact of crack network complexity on productivity. Therefore, the Pearson correlation coefficient was used to analyze the correlation between evaluation parameters, such as mineral content, horizontal stress difference, natural fractures and gas production. Combined with the improved particle swarm optimization (IPSO) algorithm and support vector machine (SVM) algorithm, a fracture network index (FNI) model was proposed to effectively evaluate the complexity of fracture networks, and the model was verified by comparing it with the performance evaluation results from the other two traditional models. Finally, the correlation between the fracture network index and the actual average daily gas production of different fracturing sections was calculated and analyzed. The results showed that the density of natural fractures was the key factor in controlling gas production (the Pearson correlation coefficient was 0.39), and the correlation between other factors was weak. In the process of fitting the actual data, the coefficient of determination, R², of the IPSO-SVM-FNI model training set increased by 8% and 24% compared with the two traditional models, and the fitting effect was greatly improved. In the prediction process based on actual data, the R² of the IPSO-SVM-FNI model test set was improved by 22% and 20% compared with the two traditional models, and the prediction accuracy was also significantly improved. The fracture index was concentrated, and its main distribution range was in the range of [0.2, 0.8]. The fracturing section with a higher FNI showed higher average daily gas production, and there was a significant positive correlation between fracture network complexity and gas production. Indeed, the research results provide some ideas and references for the evaluation of fracturing effects in shale reservoirs. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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25 pages, 7398 KiB

Open AccessArticle

Productivity Model for Multi-Fractured Horizontal Wells with Complex Fracture Networks in Shale Oil Reservoirs Considering Fluid Desorption and Two-Phase Behavior

by Xin Liu, Ping Guo, Junjie Ren, Zhouhua Wang and Hanmin Tu

Energies 2024, 17(23), 6012; https://doi.org/10.3390/en17236012 - 29 Nov 2024

Viewed by 710

Abstract

Shale oil reservoirs are characterized by extremely low porosity and permeability, necessitating the utilization of multi-fractured horizontal wells (MFHWs) for their development. Additionally, the complex phase behavior and desorption effect of two-phase fluids make the fluid flow characteristics of shale oil reservoirs exceptionally intricate. However, there are no productivity models for MFHWs in shale oil reservoirs that incorporate the complex hydraulically fractured networks, the oil–gas desorption effect, and the phase change of oil and gas. In this study, we propose a novel productivity model for MFHWs in shale oil reservoirs that incorporates these complex factors. The conformal transformation, fractal theory, and pressure superposition principle are used to establish and solve the proposed model. The proposed model has been validated by comparing its predicted results with the field data and numerical simulation results. A detailed analysis is conducted on the factors that influence the productivity of shale oil wells. It is found that the phase behavior results in a significant 33% reduction in well productivity, while the fluid desorption leads to a significant 75% increase in well productivity. In summary, the proposed model has demonstrated promising practical applicability in predicting the productivity of MFHWs in shale oil reservoirs. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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16 pages, 5909 KiB

Open AccessArticle

Application of Two-Dimensional NMR for Quantitative Analysis of Viscosity in Medium–High-Porosity-and-Permeability Sandstones in North China Oilfields

by Wei Zhang, Si Li, Shaoqing Wang, Jianmeng Sun, Wenyuan Cai, Weigao Yu, Hongxia Dai and Wenkai Yang

Energies 2024, 17(21), 5257; https://doi.org/10.3390/en17215257 - 22 Oct 2024

Viewed by 734

Abstract

The viscosity of crude oil plays a pivotal role in the exploration and development of oil fields. The predominant reliance on laboratory measurements, which are constrained by manual expertise, represents a significant limitation in terms of efficiency. Two-dimensional nuclear magnetic resonance (NMR) logging offers a number of advantages over traditional methods. It is capable of providing faster measurement rates, as well as insights into fluid properties, which can facilitate timely adjustments in oil and gas development strategies. This study focuses on the loose sandstone reservoirs with high porosity and permeability containing heavy oil in the Huabei oilfield. Two-dimensional nuclear magnetic resonance (NMR) measurements and analyses were conducted on saturated rocks with different-viscosity crude oils and varying oil saturation levels, in both natural and artificial rock samples. This study elucidates the distribution patterns of different-viscosity crude oils within the two-dimensional NMR spectra. Furthermore, the T₁ and T₂ peak values of the extracted oil signals were employed to establish a model correlating oil viscosity with NMR parameters. Consequently, a criterion for determining oil viscosity based on two-dimensional NMR was formulated, providing a novel approach for estimating oil viscosity. The application of this technique in the BQ well group of the Huabei oilfield region yielded an average relative error of 15% between the actual oil viscosity and the computed results. Furthermore, the consistency between the oil types and the oil discrimination chart confirms the reliability of the method. The final outcomes meet the precision requirements for practical log interpretation and demonstrate the excellent performance of two-dimensional nuclear magnetic resonance (NMR) logging in calculating oil viscosity. The findings of this study have significant implications for subsequent exploration and development endeavors in the research area’s oilfields. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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14 pages, 4648 KiB

Open AccessArticle

Asynchronous Injection–Production Method in the High Water Cut Stage of Tight Oil Reservoirs

by Jianwen Chen, Dingning Cai, Tao Zhang, Linjun Yu, Dalin Zhou and Shiqing Cheng

Energies 2024, 17(19), 4838; https://doi.org/10.3390/en17194838 - 26 Sep 2024

Viewed by 932

Abstract

Asynchronous injection–production cycle (AIPC) in a horizontal–vertical well pattern is an efficient strategy for enhancing water injection in tight reservoirs. However, current studies lack consideration of waterflood-induced fractures (WIFs) caused by long-term water injection. This paper takes block Z in the Ordos Basin, China, as the research object and first clarifies the formation conditions of WIFs considering the horizontal principal stress and flow line. Then, the pressure-sensitive permeability equations for the induce-fracture region between wells are derived. Finally, the WIFs characteristics in a horizontal–vertical well network with different injection modes are discussed by numerical simulation. The results show that WIFs preferentially form where flow aligns with the maximum principal stress, influencing permeability distribution. Controlling the injection rate of vertical wells on the maximum principal stress and flow line and cyclically adjusting the production rate of horizontal wells can regulate the appropriate propagation of WIFs and expand the swept areas. The parallel injection mode (PIM) and the half-production injection mode are superior to the full-production injection mode. This study can provide theoretical support for the effective development of tight oil reservoirs. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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22 pages, 6614 KiB

Open AccessArticle

Prediction of Key Development Indicators for Offshore Oilfields Based on Artificial Intelligence

by Ke Li, Kai Wang, Chenyang Tang, Yue Pan, Yufei He, Shaobin Cai, Suidong Chen and Yuhui Zhou

Energies 2024, 17(18), 4594; https://doi.org/10.3390/en17184594 - 13 Sep 2024

Cited by 1 | Viewed by 852

Abstract

As terrestrial oilfields continue to be explored, the difficulty of exploring new oilfields is constantly increasing. The ocean, which contains abundant oil and gas resources, has become a new field for oil and gas resource development. It is estimated that the total amount of oil resources contained in ocean areas accounts for 33% of the global total, while the corresponding natural gas resources account for 32% of the world’s resources. Current prediction methods, tailored to land oilfields, struggle with offshore differences, hindering accurate forecasts. With oilfield advancements, a vast amount of rapidly generated, complex, and valuable data has piled up. This paper uses AI and GRN-VSN NN to predict offshore oilfield indicators, focusing on model-based formula fitting. It selects highly correlated input indicators for AI-driven prediction of key development metrics. Afterwards, the Shapley additive explanations (SHAP) method was introduced to explain the artificial intelligence model and achieve a reasonable explanation of the measurement’s results. In terms of crude-oil extraction degree, the performance levels of the Long Short-Term Memory (LSTM) neural network, BP neural network, and ResNet-50 neural network are compared. LSTM excels in crude-oil extraction prediction due to its monotonicity, enabling continuous time-series forecasting. Artificial intelligence algorithms have good prediction effects on key development indicators of offshore oilfields, and the prediction accuracy exceeds 92%. The SHAP algorithm offers a rationale for AI model parameters, quantifying input indicators’ contributions to outputs. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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Review

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18 pages, 4820 KiB

Open AccessReview

Research and Application of Oxygen-Reduced-Air-Assisted Gravity Drainage for Enhanced Oil Recovery

by Jiangfei Wei, Hongwei Yu, Ming Gao, Peifeng Yan, Kesheng Tan, Yutong Yan, Keqiang Wei, Mingyan Sun, Xianglong Yu, Zhihua Chen and Qiang Chen

Energies 2025, 18(3), 557; https://doi.org/10.3390/en18030557 - 24 Jan 2025

Viewed by 674

Abstract

This paper summarizes the research progress and applications of oxygen-reduced-air-assisted gravity drainage (OAGD) in enhanced oil recovery (EOR). The fundamental principles and key technologies of OAGD are introduced, along with a review of domestic and international field trials. Factors influencing displacement performance, including low-temperature oxidation reactions, injection rates, and reservoir dip angles, are discussed in detail. The findings reveal that low-temperature oxidation significantly improves the recovery efficiency through the dynamic balance of light hydrocarbon volatilization and fuel deposition, coupled with the synergistic optimization of the reservoir temperature, pressure, and oxygen concentration. Proper control of the injection rate stabilizes the oil–gas interface, expands the swept volume, and delays gas channeling. High-dip reservoirs, benefiting from enhanced gravity segregation, demonstrate superior displacement efficiency. Finally, the paper highlights future directions, including the optimization of injection parameters, deepening studies on reservoir chemical reaction mechanisms, and integrating intelligent gas injection technologies to enhance the effectiveness and economic viability of OAGD in complex reservoirs. Full article

(This article belongs to the Special Issue Petroleum and Natural Gas Engineering)

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