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Processes
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Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources
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Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources

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

Deadline for manuscript submissions: closed (15 April 2025) | Viewed by 8071

Special Issue Editors

Dr. Zhixue Sun

E-Mail Website
Guest Editor
School of Petroleum Engineering, China University of Petroleum, Qingdao 266580, China
Interests: quantitative characterization and geological modeling of complex oil and gas reservoirs; theory and methods of numerical simulation of complex oil and gas reservoirs; theory and simulation of EGS development
Prof. Dr. Xiaoguang Wang

E-Mail Website
Guest Editor
College of Energy, Chengdu University of Technology, Chengdu 610059, China
Interests: THMC-coupled processes; inverse modeling; geothermal energy development; carbon storage

Special Issue Information

Dear Colleagues,

With the increasing demand for quantitative evaluation, efficient development, and accurate simulation of geo-energy resources, the field of geoscience and energy engineering has been witnessing significant advancements. This Special Issue aims to explore the latest developments and applications in the evaluation of geo-energy resources, effective methods for promoting their extraction, and the simulation of reservoir flow in geological formations.

The topics covered in this Special Issue include, but are not limited to:

  • Quantitative evaluation of geo-energy resources, including methods for assessing the potential and feasibility of various forms of geothermal, oil, gas, and other underground resources.
  • Efficient development of geo-energy resources, focusing on innovative techniques and technologies for enhancing extraction efficiency, reducing environmental impact, and optimizing the overall performance of energy extraction processes.
  • Seepage and simulation of geological resources, encompassing advanced modeling and simulation techniques for understanding the flow behavior of fluids, gases, and other substances within subsurface reservoirs and the impact on resource extraction.

Contributions from researchers, practitioners, and experts in the field are welcome to share their latest findings, methodologies, and case studies. We encourage interdisciplinary approaches that combine geoscience, engineering, and computational modeling to address the challenges and opportunities in harnessing geo-energy resources.

Dr. Zhixue Sun
Prof. Dr. Xiaoguang Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • geo-energy resources
  • quantitative evaluation
  • efficient development
  • geothermal exploitation
  • unconventional oil and gas
  • complex reservoir
  • seepage
  • flow simulation

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Published Papers (8 papers)

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Research

12 pages, 3976 KiB  
Article
An Improved Nishihara Model Considering the Influence of Moisture Content on the Whole Shear Creep Process of Shale
by Liyao Ma, Mingfeng Lei, Lichuan Wang, Bin Hu, Yaqian Zhao and Jingjing Zhang
Processes 2025, 13(3), 783; https://doi.org/10.3390/pr13030783 - 7 Mar 2025
Viewed by 506
Abstract
The moisture content is closely related to the shear creep deformation behavior of soft rock, and the linear creep deformation behavior of soft rock can be described by the classical Nishihara model. However, its accuracy in describing accelerated nonlinear creep characteristics and the [...] Read more.
The moisture content is closely related to the shear creep deformation behavior of soft rock, and the linear creep deformation behavior of soft rock can be described by the classical Nishihara model. However, its accuracy in describing accelerated nonlinear creep characteristics and the effects of moisture content still needs to be improved. The innovation of this paper is to propose an improved Nishihara model that can describe the whole creep process of shale with different moisture content. The model uses a strain-triggered nonlinear sticky pot to describe the process of accelerated creep of rock, and proposes a damage factor to reflect the effect of moisture content on the creep characteristics of rock. The relationship between the moisture content and damage factor is an exponential function, and the damage factor and related model parameters are determined by the shear creep test results under moisture conditions (0%, 0.46%, 0.87%, 1.24%). The shear creep tests were carried out by a self-developed rock shear apparatus. The experimental results show that the shear creep rate decreases first and then increases. The higher the moisture content of shale, the greater the initial shear displacement and stable creep displacement, and the longer it takes to enter the stable creep stage. The improved Nishihara model proposed in this paper can accurately fit the shear creep curves of four groups of shale samples with different moisture contents, and the correlation coefficients all reach 0.99. The fitting effect is better than that of the traditional model, which has good accuracy and practicability. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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15 pages, 2956 KiB  
Article
Molecular Dynamics Study on the Nature of near Miscibility and the Role of Minimum Miscibility Pressure Reducer
by Feng Liu, Shengbing Zhang, Jiale Zhang, Zhaolong Liu, Yonghui Chen and Shixun Bai
Processes 2025, 13(2), 535; https://doi.org/10.3390/pr13020535 - 14 Feb 2025
Viewed by 390
Abstract
Gas miscible flooding, especially CO2 miscible flooding, is a key method for enhanced oil recovery. However, the high Minimum Miscibility Pressure (MMP) often makes true-miscible flooding impractical. A number of studies confirm the existence of a near-miscible region that also ensures high [...] Read more.
Gas miscible flooding, especially CO2 miscible flooding, is a key method for enhanced oil recovery. However, the high Minimum Miscibility Pressure (MMP) often makes true-miscible flooding impractical. A number of studies confirm the existence of a near-miscible region that also ensures high recovery. However, the exact boundary for near miscibility remains unclear, with various speculative definitions based on experimental data or by experience. In this work, a molecular-level understanding of miscibility and near miscibility and the role of the MMP reducer are achieved using the molecular dynamics method. It is found that the traditional criterion of interfacial tension being zero is not valid for the molecular dynamics method, and that the interaction energy between oil molecules suggests distinct boundary between near-miscibility and miscibility regimes. MMP reducers were found to bring the two regions closer in terms of energy, rather than actually reducing the MMP. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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22 pages, 12736 KiB  
Article
Automatic History Matching Method and Application of Artificial Intelligence for Fractured-Porous Carbonate Reservoirs
by Kaijun Tong, Wentong Song, Han Chen, Sheng Guo, Xueyuan Li and Zhixue Sun
Processes 2024, 12(12), 2634; https://doi.org/10.3390/pr12122634 - 22 Nov 2024
Viewed by 799
Abstract
Fractured-porous carbonate reservoirs, mainly composed of dolomites and crystalline rocks with various rock types and extremely poor initial porosity and permeability, are dominated by tectonic fractures and exhibit extreme heterogeneity. The fracture system plays a predominant role in hydrocarbon fluid transport. Compared with [...] Read more.
Fractured-porous carbonate reservoirs, mainly composed of dolomites and crystalline rocks with various rock types and extremely poor initial porosity and permeability, are dominated by tectonic fractures and exhibit extreme heterogeneity. The fracture system plays a predominant role in hydrocarbon fluid transport. Compared with conventional sandstone reservoirs, fracture geometry and topological structure parameters are key factors for the accuracy and computational efficiency of numerical simulation history matching in fractured reservoirs. To address the matching issue, this paper introduces an artificial intelligence history matching method combining the Monte Carlo experimental planning method with an artificial neural network and a particle swarm optimization algorithm. Taking reservoir geological parameters and phase infiltration properties as the objective function, this method performs reservoir production history matching to correct the geological model. Through case studies, it is verified that this method can accurately correct the geological model of fractured-porous reservoirs and match the observed production data. This research represents a collaborative effort among multiple disciplines, integrating advanced algorithms and geological knowledge with the expertise of computer scientists, geologists, and engineers. Currently the world’s major oilfields history fitting is mainly based on reservoir engineers’ experience to fit; the method is applicable to major oilfields, but the fitting accuracy and fitting efficiency is severely limited, the fitting accuracy is less than 75%, while the artificial intelligence history fitting method shows a stronger applicability; intelligent history fitting is mainly based on the integrity of the field data, and as far as the theory is concerned, the accuracy of the intelligent history fitting can be up to 100%. Therefore, AI history fitting can provide a significant foundation for mine field research. Future research could further explore interdisciplinary collaboration to address other challenges in reservoir characterization and management. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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16 pages, 10553 KiB  
Article
Evaluation of the Compatibility Between Formation and Injection Water in Ultra-Low Permeability Reservoirs
by Zhaobo Gong, Leilei Zhang, Tingting Zhang, Zhong Yan, Shuping Cong, Zhenyu Zhou and Debin Kong
Processes 2024, 12(11), 2475; https://doi.org/10.3390/pr12112475 - 7 Nov 2024
Viewed by 1106
Abstract
This study focuses on the reservoir scaling and the under-injection issues of the water injection well during the water injection development of an ultra-low permeability reservoir in Xinjiang due to the complex composition of injected water. Microfluidic experiments were applied to visualize the [...] Read more.
This study focuses on the reservoir scaling and the under-injection issues of the water injection well during the water injection development of an ultra-low permeability reservoir in Xinjiang due to the complex composition of injected water. Microfluidic experiments were applied to visualize the flow channel changes during water flooding, indoor core flooding experiments were employed to analyze the permeability and ion concentration, and nuclear magnetic resonance (NMR) was used to evaluate the pore structure damage. Together, these experiments were used to clarify the scaling and precipitation characteristics as the injected water met the formation water in porous media and the effects on reservoir damage. The research results showed that the poor compatibility of the injected water with the formation water could easily produce calcium carbonate scaling. The scaling products exhibited a unique network structure of blocks and a radial distribution, mainly composed of calcium carbonate and aluminosilicate. The scaling in the porous media exhibited the characteristics of unstable crystal precipitation, migration, and repeated scaling following water mixing, while the scale crystal growth occurred in the pores and the throats. According to the scaling characteristics, the damage to the reservoir permeability by scaling can be divided into the induction, damage, and stabilization stages. The filling and clogging of the scale crystals enhanced the pore structure heterogeneity, with the median pore radius reduced by 21.61% and the permeability reduced by 50%. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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16 pages, 5525 KiB  
Article
Analysis of Fault Influence on Geostress Perturbation Based on Fault Model Test
by Shuang Tian, Yan Qiao, Yang Zhang, Dawei Hu, Hui Zhou and Sayed Muhammad Iqbal
Processes 2024, 12(6), 1240; https://doi.org/10.3390/pr12061240 - 17 Jun 2024
Viewed by 898
Abstract
The distribution of the geostress field in reservoirs holds significant implications for the precise exploration and efficient development and utilization of oil and gas resources, especially in deep strata regions where faults are prevalent. Geological structural movements in these deep strata regions exacerbate [...] Read more.
The distribution of the geostress field in reservoirs holds significant implications for the precise exploration and efficient development and utilization of oil and gas resources, especially in deep strata regions where faults are prevalent. Geological structural movements in these deep strata regions exacerbate the complexity of geostress field distributions. To elucidate the perturbation of the geostress field in deep reservoirs caused by faults, this study initially conducted a series of physical model tests on single fault dislocation, employing digital image correlation techniques to capture the displacement fields of various types of fault dislocations. Subsequently, a numerical model of the fault interface element was established, and fault element parameters were determined through sensitivity analysis and trial calculation. This study further analyzed the perturbation of the geostress field using this numerical model. Finally, a multi-fault numerical simulation model was constructed to clarify the perturbations in the regional geostress field under the influence of multiple faults. The results indicate that the geostress perturbation range under the action of multiple faults spans from 183.06 to 310.06 m. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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13 pages, 4148 KiB  
Article
Prediction Technology of a Reservoir Development Model While Drilling Based on Machine Learning and Its Application
by Xin Wang, Min Mao, Yi Yang, Shengbin Yuan, Mingyu Guo, Hongru Li, Leli Cheng, Heng Wang and Xiaobin Ye
Processes 2024, 12(5), 975; https://doi.org/10.3390/pr12050975 - 10 May 2024
Cited by 1 | Viewed by 1148
Abstract
In order to further understand the complex spatial distribution caused by the extremely strong heterogeneity of buried hill reservoirs, this paper proposes a new method for predicting the development pattern of buried hill reservoirs based on the traditional pre-drilling prediction and post-drilling evaluation [...] Read more.
In order to further understand the complex spatial distribution caused by the extremely strong heterogeneity of buried hill reservoirs, this paper proposes a new method for predicting the development pattern of buried hill reservoirs based on the traditional pre-drilling prediction and post-drilling evaluation methods that mainly rely on seismic, logging, and core data, which are difficult to meet the timeliness and accuracy of drilling operations. Firstly, the box method and normalization formula are used to process and normalize the abnormal data of element logging and engineering logging, and then the stepwise regression analysis method is used to optimize the sensitive parameters of element logging and engineering logging. The Light Gradient Boosting Machine (LightGBM) algorithm, deep neural network (DNN), and support vector machine (SVM) are used to establish a new method for predicting the development pattern of buried hill reservoirs. Lastly, a comprehensive evaluation index F1 score for the model is established to evaluate the prediction model for the development pattern of buried hill reservoirs. The F1 score value obtained from this model’s comprehensive evaluation index indicates that the LightGBM model achieves the highest accuracy, with 96.7% accuracy in identifying weathered zones and 95.8% accuracy in identifying interior zones. The practical application demonstrates that this method can rapidly and accurately predict the development mode of buried hill reservoirs while providing a new approach for efficient on-site exploration and decision-making in oil and gas field developments. Consequently, it effectively promotes exploration activities as well as enhances the overall process of oil and gas reservoir exploration. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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12 pages, 847 KiB  
Article
Well Selection for CO2 Huff-n-Puff in Unconventional Oil Reservoirs Based on Improved Fuzzy Method
by Yunfeng Liu, Yangwen Zhu, Haiying Liao, Hongmin Yu, Xin Fang and Yao Zhang
Processes 2024, 12(5), 958; https://doi.org/10.3390/pr12050958 - 9 May 2024
Viewed by 1095
Abstract
The implementation of CO2 huff-n-puff in unconventional oil reservoirs represents a green development technology that integrates oil recovery and carbon storage, emphasizing both efficiency and environmental protection. A rational well selection method is crucial for the success of CO2 huff-n-puff development. [...] Read more.
The implementation of CO2 huff-n-puff in unconventional oil reservoirs represents a green development technology that integrates oil recovery and carbon storage, emphasizing both efficiency and environmental protection. A rational well selection method is crucial for the success of CO2 huff-n-puff development. This paper initially identifies eight parameters that influence the effectiveness of CO2 huff-n-puff development and conducts a systematic analysis of the impact of each factor on development effectiveness. A set of factors for well selection decisions is established with seven successful CO2 huff-n-puff cases. Subsequently, the influencing factors are classified into positive, inverse, and moderate indicators. By using an exponential formulation, a method for calculating membership degrees is calculated to accurately represent the nonlinearity of each parameter’s influence on development, resulting in a dimensionless fuzzy matrix. Furthermore, with the oil exchange ratio serving as a pivotal parameter reflecting development effectiveness, recalibration of weighting factors is performed in conjunction with the dimensionless fuzzy matrix. The hierarchical order of weighting factors, from primary to secondary, is as follows: porosity, reservoir temperature, water saturation, formation pressure, reservoir thickness, crude oil density, crude oil viscosity, and permeability. The comprehensive decision factor and oil exchange ratio exhibit a positive correlation, affirming the reliability of the weighting factors. Finally, utilizing parameters of the Ordos Basin as a case study, the comprehensive decision factor is calculated, with a value of 0.617, and the oil exchange ratio is predicted as 0.354 t/t, which falls between the Chattanooga and Eagle Ford reservoirs. This approach, which incorporates exponential membership degrees and recalibrated weighting factors derived from actual cases, breaks the limitations of linear membership calculation methods and human factors in expert scoring methods utilized in existing decision-making methodologies. It furnishes oilfield decision-makers with a swifter and more precise well selection method. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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20 pages, 10450 KiB  
Article
Understanding Plugging Agent Emplacement Depth with Polymer Shear Thinning: Insights from Experiments and Numerical Modeling
by Shanbin He, Chunqi Xue, Chang Du, Yahui Mao, Shengnan Li, Jianhua Zhong, Liwen Guo and Shuoliang Wang
Processes 2024, 12(5), 893; https://doi.org/10.3390/pr12050893 - 28 Apr 2024
Viewed by 1185
Abstract
Polymer-plugging agents are widely employed in profile control and water-plugging measures, serving as a crucial component for efficient reservoir development. However, quantitatively monitoring the emplacement depth of polymer-plugging agents in low-permeability and high-permeability layers remains a challenging bottleneck. Presently, insufficient attention on shear [...] Read more.
Polymer-plugging agents are widely employed in profile control and water-plugging measures, serving as a crucial component for efficient reservoir development. However, quantitatively monitoring the emplacement depth of polymer-plugging agents in low-permeability and high-permeability layers remains a challenging bottleneck. Presently, insufficient attention on shear thinning, a critical rheological property for water shut-off and profile control, has limited our understanding of polymer distribution laws. In this study, polymer shear-thinning experiments are firstly conducted to explore polymer variations with flow rate. The novelty of the research is that varying polymer viscosity is implemented instead of the fixed-fluid viscosity that is conventionally used. The fitted correlation is then integrated into the 2D and 3D heterogeneous numerical models for simulations, and a multivariate nonlinear regression analysis is performed based on the simulation results. The results show that lower polymer emplacement depth ratios corresponded to higher viscosity loss rates under the same flow rate. An increase in the initial permeability ratio corresponds to a decrease in the emplacement ratio, along with a reduction in the fraction of the plugging agent penetrating the low permeability formations. The model was applied to the Kunan Oilfield and demonstrated a polymer reduction of approximately 3000 tons compared to traditional methods. Despite the slightly complex nature of the multivariate nonlinear mathematical model, it presents clear advantages in controlling plugging agent distribution and estimating dosage, laying good theoretical ground for the effective and efficient recovery of subsurface resources. Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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