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Recent Advances in Geothermal Energy Systems and Reservoir Engineering
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Recent Advances in Geothermal Energy Systems and Reservoir Engineering

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H2: Geothermal".

Deadline for manuscript submissions: 20 March 2026 | Viewed by 3056

Special Issue Editors

Dr. Yuxiang Cheng

E-Mail Website
Guest Editor
1. College of New Energy and Environment, Jilin University, Changchun 130026, China
2. Key Lab of Groundwater Resource and Environment, Ministry of Education, Jilin University, Changchun 130026, China
Interests: geothermal energy development and utilization; exploration and development of hot dry rock (HDR) resources; microscale rock mechanics; hydraulic fracturing; induced seismicity prediction and analysis; THCM-coupled numerical simulations; CO2 geological storage; deep engineering safety and risk control
Dr. Yibin Huang

E-Mail Website
Guest Editor
College of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
Interests: development and utilization of geothermal energy; energy geotechnical engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Xuefeng Gao

E-Mail Website
Guest Editor
School of Mines, China University of Mining and Technology, Xuzhou 221116, China
Interests: deep geothermal resources development; geothermal reservoir construction; reservoir fracture characterization and energy transport quantification; efficient heat recovery methods; reservoir safety management

Special Issue Information

Dear Colleagues,

As the world shifts toward sustainable energy solutions, geothermal energy stands out as a reliable, low-carbon resource capable of providing baseload power and direct heat applications. This Special Issue aims to spotlight recent breakthroughs and foster interdisciplinary dialogue on innovations in geothermal energy systems and reservoir engineering. By addressing technological, environmental, and economic challenges, we seek to advance the deployment of geothermal technologies and expand their role in the global energy transition.

This Special Issue seeks to bridge gaps between geoscience, engineering, data science, and policy, providing a platform for sharing transformative research that addresses critical challenges such as reservoir heterogeneity, energy efficiency, and system scalability. Contributions may include theoretical, experimental, or computational studies, as well as real-world case studies demonstrating successful geothermal projects.

The scope of this Special Issue encompasses a broad range of topics, including (but not limited to) the following:

  • Reservoir Characterization and Engineering: Advances in geophysical exploration, machine learning-driven reservoir modeling, fracture network optimization, and long-term reservoir management strategies.
  • Next-Generation Geothermal Technologies: Enhanced geothermal systems (EGSs), closed-loop systems, hybrid configurations (e.g., geothermal/solar/wind integration), and low-enthalpy applications for district heating or industrial use.
  • Drilling and Materials Innovation: The development of cost-effective drilling technologies, corrosion-resistant materials for high-temperature environments, and solutions to enhance wellbore integrity and longevity.
  • Environmental and Socioeconomic Considerations: The mitigation of induced seismicity, lifecycle analysis, groundwater protection, policy frameworks, and strategies to improve public engagement and investment viability.
  • Cross-Disciplinary Approaches: The integration of geothermal systems with energy storage (e.g., thermal batteries), AI/ML applications for predictive modeling, and techno-economic analyses for scalable deployment.

Dr. Yuxiang Cheng
Dr. Yibin Huang
Dr. Xuefeng Gao
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. Energies is an international peer-reviewed open access semimonthly 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 2600 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

  • geothermal reservoirs
  • enhanced geothermal systems (EGSs)
  • subsurface modeling
  • sustainable drilling
  • hybrid energy systems
  • geothermal policy
  • machine learning in geothermal systems

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Published Papers (5 papers)

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24 pages, 5379 KB  
Article
Multiscale Fracture Roughness Effects on Coupled Nonlinear Seepage and Heat Transfer in an EGS Fracture
by Ziqian Yan, Jian Zhou, Xiao Peng and Tingfa Dong
Energies 2025, 18(20), 5391; https://doi.org/10.3390/en18205391 - 13 Oct 2025
Viewed by 170
Abstract
The seepage characteristics and heat transfer efficiency in rough fractures are indispensable for assessing the lifetime and production performance of geothermal reservoirs. In this study, a two-dimensional rough rock fracture model with different secondary roughness is developed using the wavelet analysis method to [...] Read more.
The seepage characteristics and heat transfer efficiency in rough fractures are indispensable for assessing the lifetime and production performance of geothermal reservoirs. In this study, a two-dimensional rough rock fracture model with different secondary roughness is developed using the wavelet analysis method to simulate the coupled flow and heat transfer process under multiscale roughness based on two theories: local thermal equilibrium (LTE) and local thermal nonequilibrium (LTNE). The simulation results show that the primary roughness controls the flow behavior in the main flow zone in the fracture, which determines the overall temperature distribution and large-scale heat transfer trend. Meanwhile, the nonlinear flow behaviors induced by the secondary roughness significantly influence heat transfer performance: the secondary roughness usually leads to the formation of more small-scale eddies near the fracture walls, increasing flow instability, and these changes profoundly affect the local water temperature distribution and heat transfer coefficient in the fracture–matrix system. The eddy aperture and eddy area fraction are proposed for analyzing the effect of nonlinear flow behavior on heat transfer. The eddy area fraction significantly and positively correlates with the overall heat transfer coefficient. Meanwhile, the overall heat transfer coefficient increases by about 3% to 10% for eddy area fractions of 0.3% to 3%. As the eddy aperture increases, fluid mixing is enhanced, leading to a rise in the magnitude of the local heat transfer coefficient. Finally, the roughness characterization was decomposed into primary roughness root mean square and secondary roughness standard deviation, and for the first time, an empirical correlation was established between multiscale roughness, flow velocity, and the overall heat transfer coefficient. Full article
(This article belongs to the Special Issue Recent Advances in Geothermal Energy Systems and Reservoir Engineering)
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24 pages, 6123 KB  
Article
Multifactor Coupling Effects on Permeability Evolution During Reinjection in Sandstone Geothermal Reservoirs: Insights from Dynamic Core Flow Experiments
by Miaoqing Li, Sen Zhang, Yanting Zhao, Yun Cai, Ming Zhang, Zheng Liu, Pengtao Li, Bing Wang, Bowen Xu, Jian Shen and Bo Feng
Energies 2025, 18(17), 4770; https://doi.org/10.3390/en18174770 - 8 Sep 2025
Viewed by 612
Abstract
Efficient reinjection is critical for maintaining reservoir pressure and ensuring the sustainable development of sandstone geothermal systems. However, complex thermal–hydraulic–chemical (THC) interactions often lead to progressive permeability reduction, significantly impairing injection performance. This study systematically investigates the coupled effects of injection flow rate, [...] Read more.
Efficient reinjection is critical for maintaining reservoir pressure and ensuring the sustainable development of sandstone geothermal systems. However, complex thermal–hydraulic–chemical (THC) interactions often lead to progressive permeability reduction, significantly impairing injection performance. This study systematically investigates the coupled effects of injection flow rate, temperature, and suspended particle size on permeability evolution during geothermal reinjection. Laboratory-scale core flow-through experiments were conducted using sandstone samples from the Guantao Formation in the Huanghua Depression, Bohai Bay Basin. The experimental schemes included graded flow rate tests, temperature-stepped injections, particle size control, long-term seepage, and reverse-flow backflushing operations. The results reveal that permeability is highly sensitive to injection parameters. Flow rates exceeding 6 mL/min induce irreversible clogging and pore structure damage, while lower rates yield more stable injection behavior. Injection at approximately 35 °C resulted in a permeability increase of 15.7%, attributed to reduced fluid viscosity and moderate clay swelling and secondary precipitation. Particles larger than 3 μm were prone to bridging and persistent clogging, whereas smaller particles exhibited more reversible behavior. During long-term seepage, reverse injection implemented upon permeability decline restored up to 98% of the initial permeability, confirming its effectiveness in alleviating pore throat blockage. Based on these findings, a combined reinjection strategy is recommended, featuring low flow rate (≤5 mL/min), moderate injection temperature (~35 °C), and fine filtration (≤3 μm). In addition, periodic backflushing should be considered when permeability loss exceeds 30% or a sustained injection pressure rise is observed. This study provides robust experimental evidence and practical guidance for optimizing geothermal reinjection operations. Full article
(This article belongs to the Special Issue Recent Advances in Geothermal Energy Systems and Reservoir Engineering)
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17 pages, 6663 KB  
Article
Study on Thermal Conductivity Prediction of Granites Using Data Augmentation and Machine Learning
by Yongjie Ma, Lin Tian, Fuhang Hu, Jingyong Wang, Echuan Yan and Yanjun Zhang
Energies 2025, 18(15), 4175; https://doi.org/10.3390/en18154175 - 6 Aug 2025
Viewed by 524
Abstract
With the global low-carbon energy transition, accurate prediction of thermal and physical parameters of deep rock masses is critical for geothermal resource development. To address the insufficient generalization ability of machine learning models caused by scarce measured data on granite thermal conductivity, this [...] Read more.
With the global low-carbon energy transition, accurate prediction of thermal and physical parameters of deep rock masses is critical for geothermal resource development. To address the insufficient generalization ability of machine learning models caused by scarce measured data on granite thermal conductivity, this study focused on granites from the Gonghe Basin and Songliao Basin in Qinghai Province. A data augmentation strategy combining cubic spline interpolation and Gaussian noise injection (with noise intensity set to 10% of the original data feature range) was proposed, expanding the original 47 samples to 150. Thermal conductivity prediction models were constructed using Support Vector Machine (SVM), Random Forest (RF), and Backpropagation Neural Network(BPNN). Results showed that data augmentation significantly improved model performance: the RF model exhibited the best improvement, with its coefficient of determination R2 increasing from 0.7489 to 0.9765, Root Mean Square Error (RMSE) decreasing from 0.1870 to 0.1271, and Mean Absolute Error (MAE) reducing from 0.1453 to 0.0993. The BPNN and SVM models also improved, with R2 reaching 0.9365 and 0.8743, respectively, on the enhanced dataset. Feature importance analysis revealed porosity (with a coefficient of variation of 0.88, much higher than the longitudinal wave velocity’s 0.27) and density as key factors, with significantly higher contributions than longitudinal wave velocity. This study provides quantitative evidence for data augmentation and machine learning in predicting rock thermophysical parameters, promoting intelligent geothermal resource development. Full article
(This article belongs to the Special Issue Recent Advances in Geothermal Energy Systems and Reservoir Engineering)
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21 pages, 5215 KB  
Article
Evaluation of Seismicity Induced by Geothermal Development Based on Artificial Neural Network
by Kun Shan, Yanhao Zheng, Wanqiang Cheng, Zhigang Shan and Yanjun Zhang
Energies 2025, 18(15), 4004; https://doi.org/10.3390/en18154004 - 28 Jul 2025
Viewed by 714
Abstract
The process of geothermal energy development may cause induced seismic activities, posing a potential threat to the sustainable utilization and safety of geothermal energy. To effectively evaluate the danger of induced seismic activities, this paper establishes an artificial neural network model and selects [...] Read more.
The process of geothermal energy development may cause induced seismic activities, posing a potential threat to the sustainable utilization and safety of geothermal energy. To effectively evaluate the danger of induced seismic activities, this paper establishes an artificial neural network model and selects nine influencing factors as the input parameters of the neurons. Based on the results of induced seismic activity under different parameter conditions, a sensitivity analysis is conducted for each parameter, and the influence degree of each parameter on the magnitude of induced seismic activity is ranked from largest to smallest as follows: in situ stress state, fault presence or absence, depth, degree of fracture aggregation, maximum in situ stress, distance to fault, injection volume, fracture dip angle, angle between fracture, and fault. Then, the weights of each parameter in the model are modified to improve the accuracy of the model. Finally, through data collection and the literature review, the Pohang EGS project in South Korea is analyzed, and the induced seismic activity influencing factors of the Pohang EGS site are analyzed and evaluated using the induced seismic activity evaluation model. The results show that the induced seismicity are all located below 3.7 km (drilling depth). As the depth increases, the seismicity magnitude also shows a gradually increasing trend. An increase in injection volume and a shortening of the distance from faults will also lead to an increase in the seismicity magnitude. When the injection volume approaches 10,000 cubic meters, the intensity of the seismic activity sharply increases, and the maximum magnitude reaches 5.34, which is consistent with the actual situation. This model can be used for the induced seismic evaluation of future EGS projects and provide a reference for project site selection and induced seismic risk warning. Full article
(This article belongs to the Special Issue Recent Advances in Geothermal Energy Systems and Reservoir Engineering)
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21 pages, 4324 KB  
Article
Dilemma of Spent Geothermal Water Injection into Rock Masses for Geothermal Potential Development
by Agnieszka Operacz, Bogusław Bielec, Tomasz Operacz, Agnieszka Zachora-Buławska and Karolina Migdał
Energies 2025, 18(15), 3922; https://doi.org/10.3390/en18153922 - 23 Jul 2025
Viewed by 566
Abstract
The global shift towards the use of renewable energy is essential to ensure sustainable development, and geothermal energy stands out as a suitable option that can support various cascading projects. Spent geothermal water (SGW) requires proper treatment to ensure that it does not [...] Read more.
The global shift towards the use of renewable energy is essential to ensure sustainable development, and geothermal energy stands out as a suitable option that can support various cascading projects. Spent geothermal water (SGW) requires proper treatment to ensure that it does not become an environmental burden. Typically, companies often face the dilemma of choosing between discharging spent geothermal water (SGW) into surface waters or injecting it into rock masses, and the economic and environmental impacts of the decision made determines the feasibility of geothermal plant development. In this study, we aimed to comprehensively assess the technical, economic, and environmental feasibility of SGW injection into rock masses. To this end, we employed a comprehensive analytical approach using the Chochołów GT-1 geothermal injection borehole in Poland as a reference case. We also performed drilling and hydrogeological testing, characterized rock samples in the laboratory, and corrected hydrodynamic parameters for thermal lift effects to ensure accurate aquifer characterization. The results obtained highlight the importance of correcting hydrogeological parameters for thermal effects, which if neglected can lead to a significant overestimation of the calculated hydrogeological parameters. Based on our analysis, we developed a framework for assessing SGW injection feasibility that integrates detailed hydrogeological and geotechnical analyses with environmental risk assessment to ensure sustainable geothermal resource exploitation. This framework should be mandatory for planning new geothermal power plants or complexes worldwide. Our results also emphasize the need for adequate SGW management so as to ensure that the benefits of using a renewable and zero-emission resource, such as geothermal energy, are not compromised by the low absorption capacity of rock masses or adverse environmental effects. Full article
(This article belongs to the Special Issue Recent Advances in Geothermal Energy Systems and Reservoir Engineering)
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