Geoenergy Science and Engineering最新文献

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Real-time lithology identification based on dynamic felling strategy and differential evolutionary random forest algorithm 基于动态采伐策略和差分进化随机森林算法的实时岩性识别
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-26 DOI: 10.1016/j.geoen.2025.214172
Junqing Bai, Weinan Chen, Xiaoran Yu
{"title":"Real-time lithology identification based on dynamic felling strategy and differential evolutionary random forest algorithm","authors":"Junqing Bai,&nbsp;Weinan Chen,&nbsp;Xiaoran Yu","doi":"10.1016/j.geoen.2025.214172","DOIUrl":"10.1016/j.geoen.2025.214172","url":null,"abstract":"<div><div>Lithology identification holds a pivotal role in geological exploration and reservoir characterization, as it directly affects the efficient development and accurate localization of oil and gas resources. However, traditional machine learning approaches often face limitations such as insufficient accuracy and weak generalization when dealing with complex geological conditions. To address these challenges, this study proposes an intelligent lithology identification method that integrates a Differential Evolution (DE) algorithm with a Dynamic Purity Pruning strategy, referred to as DRF-DE. Specifically, the DE algorithm is employed to globally optimize the hyperparameter boundaries of the Random Forest model, enhancing its adaptability to complex data distributions. Subsequently, a dynamic purity pruning mechanism is introduced to eliminate redundant classifiers based on variations in node purity during training, thereby refining the model structure and improving both stability and interpretability. Experimental results on a well-logging dataset from the North Sea oilfield demonstrate that the proposed DRF-DE model achieves an overall classification accuracy of 98.1 % on the test set, while the out-of-bag (OOB) evaluation yields an accuracy of 97.9 %. Compared with conventional machine learning methods, the DRF-DE model shows significant improvements in recognition accuracy and model robustness. Furthermore, the model maintains high performance across various complex geological formations, indicating strong generalization capability and practical applicability. This research not only advances the intelligence of lithology identification but also provides a novel approach and technical support for the automated interpretation of geological data and the efficient development of oil and gas resources.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214172"},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144912386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Preparation of HPMA stabilized CaCO3 nanofluid and its EOR potential applied in low permeability reservoirs HPMA稳定CaCO3纳米流体的制备及其在低渗透油藏中的提高采收率潜力
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-26 DOI: 10.1016/j.geoen.2025.214171
Zhixue Huang , Yefei Wang , Jing Wang , Mingchen Ding , Wuhua Chen , Shizhang Cui , Xiaorong Yu
{"title":"Preparation of HPMA stabilized CaCO3 nanofluid and its EOR potential applied in low permeability reservoirs","authors":"Zhixue Huang ,&nbsp;Yefei Wang ,&nbsp;Jing Wang ,&nbsp;Mingchen Ding ,&nbsp;Wuhua Chen ,&nbsp;Shizhang Cui ,&nbsp;Xiaorong Yu","doi":"10.1016/j.geoen.2025.214171","DOIUrl":"10.1016/j.geoen.2025.214171","url":null,"abstract":"<div><div>Nanofluid EOR applications face key challenges including poor stability and clogging in subsurface formations. This study developed a relatively stable CaCO<sub>3</sub>-HPMA nanofluid through hydrolyzed polymaleic anhydride (HPMA) modification method using a one-pot method. The CaCO<sub>3</sub>-HPMA nanofluid was characterized by FT-IR, TG, particle size analysis, SEM, zeta potential revealing spherical calcite and aragonite phase particles with an average diameter of 164 nm. CaCO<sub>3</sub>-HPMA (1000 mg/L) exhibited excellent stability, sustaining a zeta potential exceeding 30 mV after 10 d. The initial median particle size was 164.0 nm, which gradually increased to 201.2 nm after 10 d and reached 314.1 nm after 30 d CaCO<sub>3</sub>-HPMA (1000 mg/L) effectively altered the wettability of oil wet core slices to water wet, reducing the contact angle from 103.1° to 77.9°, lowered oil water interfacial tension to 14 mN/m, and achieved a 20 % emulsification index after 240 h at 60 °C. CaCO<sub>3</sub>-HPMA (1000 mg/L) nanofluid flooding and the secondary water flooding enhanced oil recovery 18.0 % compared to the primary water flooding in low permeability reservoirs. Notably, when formation clogging occurred, CaCO<sub>3</sub>-HPMA nanoparticles were effectively dissolved through acidification, providing a practical and versatile solution for field operations.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214171"},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Handling narrow margin and drilling problems in deepwater using geomechanics, well design, and process management 利用地质力学、井设计和过程管理来处理深水的窄余量和钻井问题
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-26 DOI: 10.1016/j.geoen.2025.214173
Roland I. Nwonodi , Emmanuel E. Okoro , Adewale Dosunmu
{"title":"Handling narrow margin and drilling problems in deepwater using geomechanics, well design, and process management","authors":"Roland I. Nwonodi ,&nbsp;Emmanuel E. Okoro ,&nbsp;Adewale Dosunmu","doi":"10.1016/j.geoen.2025.214173","DOIUrl":"10.1016/j.geoen.2025.214173","url":null,"abstract":"<div><div>This study presents an approach for managing narrow drilling margins (NDM) and associated challenges in deepwater environment, addressing gaps in unifying geomechanics, casing-seat design, and pressure management simultaneously. It predicts fracture pressure using geomechanical modeling and the Mogi-Coulomb criterion, reformulates pore pressure using a casing-seat equation, and estimates NM from fracture and pore pressures. Torque and buckling analyses are derived from tank agitation concept. The method was applied to ROSE 1-1 well in Kansas and validated with field data from Gulf Coast's deepwater project. At 4847 ft, the fracture gradient was 0.9010 psi/ft, approximating Excel Solver's result (0.903 psi/ft). Fracture gradient decreased with increasing inclination but increased with cohesion in both tensile and shear-based failure, and NM significantly reduced with greater water depth. Validation result showed an Annular Friction Pressure of 298.23 psi at 16,000 ft-subsea, aligning excellently with field value (300 psi). The predicted critical buckling forces for vertical (6297 lbf) and horizontal (117171.4 lbf) sections approximated Lubinski (6550 lbf) and Dawson and Paslay (116577.5 lbf) models, respectively, and the rotary torque (22623.6 lb-ft) matched industry model. Sensitivity analysis showed closure stress (82.1 %), maximum horizontal stress (6 %), and pore pressure (0.9 %) had the most effect on DM. Narrower margins—more stable with their casing shoe closer to vertical depth—were linked to higher tectonic stress, temperature, and horizontal well, while cohesive rocks yielded wider margins than rigid ones. Numerical results showed that underbalanced drilling poses higher risks of casing-string displacement than overbalanced drilling, which are preventable using the study insights.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214173"},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Hydraulic fracturing of naturally fractured hot dry rock based on a coupled thermo-hydro-mechanical model 基于热-水-力耦合模型的自然破裂干热岩水力压裂
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-25 DOI: 10.1016/j.geoen.2025.214163
Tengda Long, Zixiao Xie, Zhongwei Huang, Gensheng Li, Xianzhi Song, Xiaoguang Wu, Jingbin Li, Rui Yang, Wenchao Zou, Zhaowei Sun
{"title":"Hydraulic fracturing of naturally fractured hot dry rock based on a coupled thermo-hydro-mechanical model","authors":"Tengda Long,&nbsp;Zixiao Xie,&nbsp;Zhongwei Huang,&nbsp;Gensheng Li,&nbsp;Xianzhi Song,&nbsp;Xiaoguang Wu,&nbsp;Jingbin Li,&nbsp;Rui Yang,&nbsp;Wenchao Zou,&nbsp;Zhaowei Sun","doi":"10.1016/j.geoen.2025.214163","DOIUrl":"10.1016/j.geoen.2025.214163","url":null,"abstract":"<div><div>The successful implementation of enhanced geothermal systems (EGS) depends on the complexity and transmissivity of the fracture networks induced by hydraulic stimulation. The reactivation of pre-existing natural fractures by hydraulic fractures plays a pivotal role in forming complex fracture networks in hot dry rock (HDR). Thermo-hydro-mechanical coupled models, employing the combined finite-discrete element method, are proposed herein to elucidate the interaction mechanism between hydraulic fractures and pre-existing natural fractures in HDR. Three representative types of natural fractures were incorporated into the model, which was validated through hydraulic fracturing experiments. The impact of geological and engineering factors on fracture interaction modes was systematically investigated, with an emphasis on the geometry of fracture networks. The results demonstrated that increased initial rock temperatures would induce greater thermal stress, which favors the opening of the pre-existing fracture, facilitating the hydraulic fracture to deflect into the natural fracture. Correlation analysis demonstrated that the horizontal stress contrast is the dominant factor affecting the complexity of fracture networks, and the HDR reservoirs characterized by weakly sealed natural fractures exhibited greater sensitivity compared to those with strongly sealed natural fractures when the horizontal stress contrast is less than 8 MPa. Additionally, the impact of reservoir temperature diminished with increasing bonding strength of natural fractures, and its effect on the fracture geometry became negligible when rock temperature was below 200 °C. Moreover, the impact of flow rate on the morphology of fracture networks was more pronounced than that of fluid viscosity. As a result, prioritizing the adjustment of injection flow rate over fracturing fluid viscosity is recommended for optimizing the stimulation of HDR. The key findings are expected to offer in-depth guidance for EGS stimulation treatment.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"257 ","pages":"Article 214163"},"PeriodicalIF":4.6,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Unsupervised learning-driven insights into shale gas Reservoirs: Production prediction and strategic applications 无监督学习驱动的页岩气藏洞察:产量预测和战略应用
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-22 DOI: 10.1016/j.geoen.2025.214170
Wente Niu , Yuping Sun , Mingshan Zhang , Hang Yuan , Pinghua Ma , Wenli Song , Lizhong Song
{"title":"Unsupervised learning-driven insights into shale gas Reservoirs: Production prediction and strategic applications","authors":"Wente Niu ,&nbsp;Yuping Sun ,&nbsp;Mingshan Zhang ,&nbsp;Hang Yuan ,&nbsp;Pinghua Ma ,&nbsp;Wenli Song ,&nbsp;Lizhong Song","doi":"10.1016/j.geoen.2025.214170","DOIUrl":"10.1016/j.geoen.2025.214170","url":null,"abstract":"<div><div>Accurate and effective production prediction of oil and gas wells is of great significance for formulating reasonable and effective development strategies in the future. However, traditional empirical, physical and machine learning methods often require the use of labeled samples to predict production, which limits the performance of the model. Meanwhile, the oil and gas extraction industry remains in a state of sustained prosperity, with a significant number of as-yet-undrilled oil and gas wells (i.e., unlabeled samples) present in numerous fields. Therefore, this paper proposes an innovative framework based on unsupervised learning algorithms, called Unsupervised Production Prediction Framework (UPPF), aiming to use unlabeled well data for production prediction. In this study, the framework is applied to production example wells in the Sichuan Basin, using geological and engineering parameters of 240 wells for production prediction. A comparison of the prediction results between the UPPF framework and classic unsupervised learning methods demonstrates that the proposed UPPF framework can capture potential production patterns and features from unlabeled data, and performs well in predicting cumulative production of oil and gas wells. This innovative framework provides an advanced and feasible method for production prediction in oil and gas wells, providing strong support for decision-making and optimization in the field of oil and gas engineering. The results of this study are of great significance for promoting the development of production prediction methods and can be applied in similar fields.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214170"},"PeriodicalIF":4.6,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Study on two-phase displacement behavior and carbon storage in low-permeability sandstone based on NMR and MRI 基于核磁共振和核磁共振的低渗透砂岩两相驱替行为及碳储量研究
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-19 DOI: 10.1016/j.geoen.2025.214165
Liu Yang , Mingxiu Ji , Yan Zhao , Siyuan Li , Zhenkun Geng , Ruipeng Dong , Qian Zhang , Yinyu Wen
{"title":"Study on two-phase displacement behavior and carbon storage in low-permeability sandstone based on NMR and MRI","authors":"Liu Yang ,&nbsp;Mingxiu Ji ,&nbsp;Yan Zhao ,&nbsp;Siyuan Li ,&nbsp;Zhenkun Geng ,&nbsp;Ruipeng Dong ,&nbsp;Qian Zhang ,&nbsp;Yinyu Wen","doi":"10.1016/j.geoen.2025.214165","DOIUrl":"10.1016/j.geoen.2025.214165","url":null,"abstract":"<div><div>Deep saline aquifers possess significant potential for carbon storage, and investigating two-phase displacement mechanisms in natural rocks is crucial for achieving efficient and secure CO<sub>2</sub> sequestration. In this study, combined drainage-imbibition displacement experiments were conducted on low-permeability sandstone cores. The two-phase displacement processes were visualized using nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) techniques. A systematic analysis was performed to investigate the influence of heterogeneity and pore structure on displacement patterns. Furthermore, the intrinsic relationships among displacement patterns, displacement efficiency, storage efficiency, and storage security were elucidated. The results showed that the pore structure of the cores significantly affects two-phase displacement behavior and CO<sub>2</sub> storage efficiency. During the displacement process, mesopores and macropores showed higher displacement efficiency and more stable displacement patterns. In contrast, micropores, due to the difficulty of displacing the water and supercritical CO<sub>2</sub> (scCO<sub>2</sub>) phases, showed less stable displacement patterns but higher carbon storage efficiency. Cores with better permeability and more uniform pore size distribution tended to exhibit more stable displacement modes, while the scCO<sub>2</sub> phase was more susceptible to the influence of core heterogeneity, leading to less stable displacement compared to the water phase. A higher proportion of macropores in the core led to higher displacement efficiency at the end of the drainage experiments but resulted in the lowest storage efficiency after imbibition. Conversely, cores with higher micropore proportions and less stable displacement during imbibition demonstrated higher final storage efficiency and better storage security. This study provides theoretical guidance for achieving efficient and secure CO<sub>2</sub> storage in deep saline aquifers.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214165"},"PeriodicalIF":4.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Control mechanism of regional structure on geothermal water chemistry, geothermal field and thermal hazard in a coal mine 区域构造对某煤矿地热水化学、地热场及热危害的控制机理
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-19 DOI: 10.1016/j.geoen.2025.214164
Zhehan Sun , Kun Yu , Zheng Zhen , Ali Raza , Jiakun Lv
{"title":"Control mechanism of regional structure on geothermal water chemistry, geothermal field and thermal hazard in a coal mine","authors":"Zhehan Sun ,&nbsp;Kun Yu ,&nbsp;Zheng Zhen ,&nbsp;Ali Raza ,&nbsp;Jiakun Lv","doi":"10.1016/j.geoen.2025.214164","DOIUrl":"10.1016/j.geoen.2025.214164","url":null,"abstract":"<div><div>The coalfields of eastern China possess a great potential for hydrothermal geothermal resources. Rapid exploration and development of these geothermal resources are vital for achieving carbon emission reductions and promoting the green transformation of the mining sector. In this work, we analyze the chemistry of geothermal water and borehole temperature data from the Ordovician limestone thermal reservoir in the Xinhu coal mine, Huaibei Coalfield. The results indicate that the deep geothermal water is predominantly characterized by a Na·Ca-HCO<sub>3</sub>·SO<sub>4</sub> composition, representing a mixture of shallow and deep groundwater. The horizontal average temperature of the thermal reservoir in the Ordovician limestone of this region is 50.5 °C, with the average circulation depth of geothermal water in the Ordovician limestone being 1267 m. The Xinhu coal mine has an average geothermal heat flow value of 61.93 mW/m<sup>2</sup> and an average geothermal gradient of 26.2 °C/km, and the geothermal gradient is controlled by faults and syncline structures. The drilling temperature curve indicates that the geothermal gradient in the study area is stable, with heat transfer primarily occurring through heat conduction. The dual tectonic heat accumulation model consisting of the Xinhu syncline and the deep large-scale faults determines the occurrence environment of the hydrothermal system of the Xinhu coal mine. Consequently, the combined influence of the F<sub>1</sub>, F<sub>2</sub> and F<sub>9</sub> fault systems, and geothermal water migration formed the second-level thermal hazard in the coal mine.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214164"},"PeriodicalIF":4.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting geomechanical properties of heterogeneous shale using ensemble learning methods 应用集合学习方法预测非均质页岩地质力学性质
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-19 DOI: 10.1016/j.geoen.2025.214148
Yang Chen , Shuheng Tang , Zhaodong Xi , Shasha Sun , Jingyu Wang , Donglin Lin , Ke Zhang , Xiaofan Mei
{"title":"Predicting geomechanical properties of heterogeneous shale using ensemble learning methods","authors":"Yang Chen ,&nbsp;Shuheng Tang ,&nbsp;Zhaodong Xi ,&nbsp;Shasha Sun ,&nbsp;Jingyu Wang ,&nbsp;Donglin Lin ,&nbsp;Ke Zhang ,&nbsp;Xiaofan Mei","doi":"10.1016/j.geoen.2025.214148","DOIUrl":"10.1016/j.geoen.2025.214148","url":null,"abstract":"<div><div>Accurate characterizing shale mechanical properties is crucial in oil and gas exploration and development. However, acquiring rock mechanical data remains challenging. This study investigates machine learning algorithms for predicting shale geomechanical properties using readily available data. A comprehensive dataset was collected, including confining pressure (CP), sampling orientation, Young's modulus (<span><math><mrow><mi>E</mi></mrow></math></span>) and Poisson's ratio (<span><math><mrow><mi>ν</mi></mrow></math></span>) from triaxial compression tests, as well as core analysis and conventional logging data. Three ensemble learning models were constructed following two strategies to predict <span><math><mrow><mi>E</mi></mrow></math></span> and <span><math><mrow><mi>ν</mi></mrow></math></span>, with inputs from core analysis and logging parameters. The results indicate that the Random Forest, eXtreme Gradient Boosting and Light Gradient Boosting Machine (LightGBM) outperformed neural networks and other classical models. The LightGBM model exhibited the highest accuracy, with determination coefficient (R<sup>2</sup>) and mean relative error (MRE) being 0.82–0.85 and 6.70 %–8.36 % on test dataset. Density and orientation were the primary factors influencing shale mechanical properties, with relative importance being 0.285–0.301 and 0.178–0.230, respectively, while the CP, mineralogical composition and porosity are secondary controlling factors. Based on different core or logging parameter combinations, model performance was categorized into four levels: “optimal,” “suboptimal”, “poor” and “very poor”, ensuring adaptability to varying data conditions for mechanical property prediction. The LightGBM model was successfully applied in predicting Wufeng-Longmaxi shale mechanical properties, outperforming empirical formulas and demonstrating the advantages of ensemble learning. This study provides a practical tool for the rapid estimation of shale mechanical parameters, facilitating oil and gas development while improving economic efficiency.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214148"},"PeriodicalIF":4.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Assessment of geothermal energy resources in the Marcellus shale 马塞勒斯页岩地热能资源评价
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-19 DOI: 10.1016/j.geoen.2025.214166
Levent Taylan Ozgur Yildirim , Jon Benesch , John Wang
{"title":"Assessment of geothermal energy resources in the Marcellus shale","authors":"Levent Taylan Ozgur Yildirim ,&nbsp;Jon Benesch ,&nbsp;John Wang","doi":"10.1016/j.geoen.2025.214166","DOIUrl":"10.1016/j.geoen.2025.214166","url":null,"abstract":"<div><div>This paper presents a basin-scale model and assessment of geothermal energy resources in the Marcellus shale in the Appalachian Basin, integrating the most recent data. This research was conducted through the following tasks: (1) review heat transfer mechanisms, (2) collect and analyze the most recent geological, reservoir, and thermal data related to the Marcellus shale and the basin, (3) computations of thermal resource characteristics, (4) develop and validate a thermal model by integrating all available data, and (5) perform a systematic and comprehensive modeling to assess thermal energy stored in the Marcellus shale through Monte Carlo simulations. The results show that the total thermal energy stored in the Marcellus shale is 4.44 × 10<sup>14</sup> Megajoules (MJ). Pennsylvania constitutes approximately 56% of the resources with a most likely value of 2.50 × 10<sup>14</sup> MJ. Temperature ranges from 14 to 96 °C, which is classified as low-temperature resources suitable for geothermal heating system. The greatest stored thermal energy is located in northeastern Pennsylvania, especially in Sullivan, Columbia, Luzerne, and Wyoming counties. This method and its application to the Marcellus shale enhance the understanding of geothermal resources in the Appalachian Basin.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"257 ","pages":"Article 214166"},"PeriodicalIF":4.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Impact of high-cycle huff and puff on residual oil distribution in heavy oil reservoirs 高旋回吞吐对稠油油藏剩余油分布的影响
IF 4.6
Geoenergy Science and Engineering Pub Date : 2025-08-19 DOI: 10.1016/j.geoen.2025.214168
Guangdong Zhang , Chaoping Mo , Yong Tang , Difeng Zeng
{"title":"Impact of high-cycle huff and puff on residual oil distribution in heavy oil reservoirs","authors":"Guangdong Zhang ,&nbsp;Chaoping Mo ,&nbsp;Yong Tang ,&nbsp;Difeng Zeng","doi":"10.1016/j.geoen.2025.214168","DOIUrl":"10.1016/j.geoen.2025.214168","url":null,"abstract":"<div><div>Steam huff and puff plays a crucial role in exploiting deep heavy oil reservoirs, where effectiveness and recovery rates decrease with increasing cycles. Understanding the pore-level distribution of residual oil post high-cycle is essential. This study investigates the impact of repeated huff and puff cycles on oil recovery in porous media. Experiments mimicked field conditions with hot water huff and puff, substituting for steam, which remains liquid due to significant heat loss. CT scans of rock samples assessed residual oil distribution, and digital rock core data were calibrated with mercury intrusion porosimetry to improve accuracy, achieving 87 % precision. Results showed the high-cycle huff and puff process occurs in two phases: initially, oil in larger pores (radii &gt;150 μm) is preferentially removed, with minimal mobilization in smaller pores (radii 0–50 μm). In subsequent phases, oil from medium and small pores gradually migrates to and replenishes the previously depleted larger pores. As cycles increase, oil migrates from smaller to larger pores, decreasing overall core saturation. Smaller pores thus require more cycles for effective oil mobilization. Although relative permeability of oil in cores initially drops sharply, it stabilizes after several cycles. This study advances understanding of pore-level oil distribution dynamics, providing important insights into oil recovery behavior in deep heavy oil reservoirs.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214168"},"PeriodicalIF":4.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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