Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.08.010
Ya Meng , Bin Zhang , Feng-Peng Lai
The methane adsorption capacity, gas content, and carbon isotope characteristics of coal are crucial parameters that determine the productivity of coalbed methane (CBM) wells and their development potential. In this paper, test analyses of methane adsorption, gas content and carbon isotope of methane were carried out using 89 samples from the No.3 coal seam in the southwestern part of the Qinshui Basin. Their characteristics and correlations were analyzed. A relationship model between methane adsorption, gas content, carbon isotopes, coal metamorphism and material composition were established, and its controlling mechanism was investigated. The results indicate that the distribution patterns of Langmuir volume and Langmuir pressure in No.3 coal seam are mainly determined by the material composition and the thermal evolution level. The methane gas content in coal is mainly affected by the burial depth, microcosmic composition, mineral content, moisture content and ash yield, adsorption capacity and metamorphism of the coal. The methane carbon isotope (δ13C1) values in the natural desorbed gas from No.3 coal seam range from −26.95% to −57.80‰, with a mean value of −34.53‰. δ13C1 in coal shows a two-stage variation pattern with increasing in vitrinite reflectance (). When is blow 3.0%, δ13C1 values of methane in coal become progressively heavier with increasing . When reaches or exceeds 3.0%, δ13C1 values exhibit a lightning trend with further increases in , which is primarily controlled by the carbon isotope fractionation effects during thermal evolution.
{"title":"Analysis on adsorption capacity of coal, gas content and methane carbon isotope characteristics in coal: A case study from Southwestern Qinshui Basin, China","authors":"Ya Meng , Bin Zhang , Feng-Peng Lai","doi":"10.1016/j.petsci.2025.08.010","DOIUrl":"10.1016/j.petsci.2025.08.010","url":null,"abstract":"<div><div>The methane adsorption capacity, gas content, and carbon isotope characteristics of coal are crucial parameters that determine the productivity of coalbed methane (CBM) wells and their development potential. In this paper, test analyses of methane adsorption, gas content and carbon isotope of methane were carried out using 89 samples from the No.3 coal seam in the southwestern part of the Qinshui Basin. Their characteristics and correlations were analyzed. A relationship model between methane adsorption, gas content, carbon isotopes, coal metamorphism and material composition were established, and its controlling mechanism was investigated. The results indicate that the distribution patterns of Langmuir volume and Langmuir pressure in No.3 coal seam are mainly determined by the material composition and the thermal evolution level. The methane gas content in coal is mainly affected by the burial depth, microcosmic composition, mineral content, moisture content and ash yield, adsorption capacity and metamorphism of the coal. The methane carbon isotope (<em>δ</em><sup>13</sup>C<sub>1</sub>) values in the natural desorbed gas from No.3 coal seam range from −26.95% to −57.80‰, with a mean value of −34.53‰. <em>δ</em><sup>13</sup>C<sub>1</sub> in coal shows a two-stage variation pattern with increasing in vitrinite reflectance (<span><math><msubsup><mi>R</mi><mi>max</mi><mi>o</mi></msubsup></math></span>). When <span><math><msubsup><mi>R</mi><mi>max</mi><mi>o</mi></msubsup></math></span> is blow 3.0%, <em>δ</em><sup>13</sup>C<sub>1</sub> values of methane in coal become progressively heavier with increasing <span><math><msubsup><mi>R</mi><mi>max</mi><mi>o</mi></msubsup></math></span>. When <span><math><msubsup><mi>R</mi><mi>max</mi><mi>o</mi></msubsup></math></span> reaches or exceeds 3.0%, <em>δ</em><sup>13</sup>C<sub>1</sub> values exhibit a lightning trend with further increases in <span><math><msubsup><mi>R</mi><mi>max</mi><mi>o</mi></msubsup></math></span>, which is primarily controlled by the carbon isotope fractionation effects during thermal evolution.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4381-4393"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.08.001
Wei Si , Du-Jie Hou , Xiong Cheng
In the Pearl River Mouth Basin of the northern South China Sea, extensive commercial shallow gas reservoirs have recently been discovered. However, their formation mechanisms remain poorly constrained. This study employs integrated petroleum geological and geochemical datasets to elucidate shallow gas systems' genesis and geochemical signatures. Key findings demonstrate that shallow gas reservoirs exhibit distinct geochemical differentiation from deep thermogenic counterparts, characterized by elevated dryness coefficients (>0.9), depleted methane δ13C values (−52‰ to −34.4‰), and 13C-enriched ethane and propane isotopes resulting from migration fractionation. The anaerobic environment minimizes microbial alteration, while the complex marine geology challenges conventional interpretations of isotopic source indicators. Light hydrocarbon analysis identifies type II2-III kerogen as the primary thermogenic gas source, with southern reservoirs showing sapropelic organic matter signatures consistent with oil-cracking origins. Notably, mixed-source reservoirs display an inverse δ13C relationship between carbon dioxide and methane, contrasting with positive correlations typically observed in biogenic gas from carbon dioxide reduction. Quantitative end-member modeling constrains biogenic contributions to ≤30%, confirming thermogenic dominance despite active methanogenesis. Shallow gas accumulation is a dynamic process involving simultaneous charge and diffusion. Synthesizing these insights with prior research, we propose a genetic model for shallow gas reservoirs, highlighting significant differences in source rock maturity, kerogen types, enrichment layers, migration channels, and water depths relative to deep-water counterparts.
{"title":"Geochemistry and genesis of marine shallow gas in the Pearl River Mouth Basin (PRMB), South China Sea","authors":"Wei Si , Du-Jie Hou , Xiong Cheng","doi":"10.1016/j.petsci.2025.08.001","DOIUrl":"10.1016/j.petsci.2025.08.001","url":null,"abstract":"<div><div>In the Pearl River Mouth Basin of the northern South China Sea, extensive commercial shallow gas reservoirs have recently been discovered. However, their formation mechanisms remain poorly constrained. This study employs integrated petroleum geological and geochemical datasets to elucidate shallow gas systems' genesis and geochemical signatures. Key findings demonstrate that shallow gas reservoirs exhibit distinct geochemical differentiation from deep thermogenic counterparts, characterized by elevated dryness coefficients (>0.9), depleted methane <em>δ</em><sup>13</sup>C values (−52‰ to −34.4‰), and <sup>13</sup>C-enriched ethane and propane isotopes resulting from migration fractionation. The anaerobic environment minimizes microbial alteration, while the complex marine geology challenges conventional interpretations of isotopic source indicators. Light hydrocarbon analysis identifies type II<sub>2</sub>-III kerogen as the primary thermogenic gas source, with southern reservoirs showing sapropelic organic matter signatures consistent with oil-cracking origins. Notably, mixed-source reservoirs display an inverse <em>δ</em><sup>13</sup>C relationship between carbon dioxide and methane, contrasting with positive correlations typically observed in biogenic gas from carbon dioxide reduction. Quantitative end-member modeling constrains biogenic contributions to ≤30%, confirming thermogenic dominance despite active methanogenesis. Shallow gas accumulation is a dynamic process involving simultaneous charge and diffusion. Synthesizing these insights with prior research, we propose a genetic model for shallow gas reservoirs, highlighting significant differences in source rock maturity, kerogen types, enrichment layers, migration channels, and water depths relative to deep-water counterparts.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4329-4340"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.08.032
Peng Zhu , Tong Ma , Lu Yin , Dan Xie , Cai-Hua Xu , Qin Xu , Tian-Yu Liu
Accurately characterizing the storage space of fractured-vuggy carbonate reservoirs is a major technical challenge in the efficient exploration and development of the petroleum industry. Electrical image logs are an effective technique for identifying and evaluating dissolution vugs in carbonate reservoirs. However, due to limitations in the wellbore structure and the design of instruments, the images of electrical image logs often contain numerous blank strips, which affects the accuracy of subsequent vug processing and interpretation. To finely evaluate the pore structure of karst reservoirs and quantitatively characterize reservoir parameters, this study proposes an automatic identification method for dissolution vugs in electrical image logs, integrating image inpainting and regional segmentation based on an improved deep image prior (IDIP) framework. Firstly, the IDIP neural network model, leveraging its structural characteristics, uses a random mask and image data as input to iteratively learn low-level features at known pixel points and extend these features to blank areas of the image. This approach allows clear capture of the structure and texture information of vugs in blank strips, even in the absence of sufficient training samples. Subsequently, based on the inpainted images, the Otsu algorithm is used to determine the optimal global threshold, and then the watershed algorithm is applied to segment and label the vug targets, which addresses the problem of over-segmentation when separating the vug information from the stratigraphic background. Finally, the Freeman chain code is used to store and calculate vug parameters, converting the picked vug area into areal porosity to quantitatively assess the development degree of fractures and vugs in the reservoir. The results show a good correlation with core porosity and are superior to calculations without image inpainting. This study presents a method based on image processing for vug identification and evaluation of karst reservoirs, demonstrating high consistency with actual field data and providing theoretical support and methodological reference for the classification and evaluation of similar reservoirs.
{"title":"Intelligent identification method for dissolution vugs in karst reservoirs of carbonate rocks using electrical image logs: The Dengying Formation reservoir in the Gaoshiti-Moxi block, Sichuan Basin","authors":"Peng Zhu , Tong Ma , Lu Yin , Dan Xie , Cai-Hua Xu , Qin Xu , Tian-Yu Liu","doi":"10.1016/j.petsci.2025.08.032","DOIUrl":"10.1016/j.petsci.2025.08.032","url":null,"abstract":"<div><div>Accurately characterizing the storage space of fractured-vuggy carbonate reservoirs is a major technical challenge in the efficient exploration and development of the petroleum industry. Electrical image logs are an effective technique for identifying and evaluating dissolution vugs in carbonate reservoirs. However, due to limitations in the wellbore structure and the design of instruments, the images of electrical image logs often contain numerous blank strips, which affects the accuracy of subsequent vug processing and interpretation. To finely evaluate the pore structure of karst reservoirs and quantitatively characterize reservoir parameters, this study proposes an automatic identification method for dissolution vugs in electrical image logs, integrating image inpainting and regional segmentation based on an improved deep image prior (IDIP) framework. Firstly, the IDIP neural network model, leveraging its structural characteristics, uses a random mask and image data as input to iteratively learn low-level features at known pixel points and extend these features to blank areas of the image. This approach allows clear capture of the structure and texture information of vugs in blank strips, even in the absence of sufficient training samples. Subsequently, based on the inpainted images, the Otsu algorithm is used to determine the optimal global threshold, and then the watershed algorithm is applied to segment and label the vug targets, which addresses the problem of over-segmentation when separating the vug information from the stratigraphic background. Finally, the Freeman chain code is used to store and calculate vug parameters, converting the picked vug area into areal porosity to quantitatively assess the development degree of fractures and vugs in the reservoir. The results show a good correlation with core porosity and are superior to calculations without image inpainting. This study presents a method based on image processing for vug identification and evaluation of karst reservoirs, demonstrating high consistency with actual field data and providing theoretical support and methodological reference for the classification and evaluation of similar reservoirs.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4446-4461"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.08.025
Hong-Wei Yang , Jun Li , Zhen-Yu Long , Xiu-Ling Zhang , Geng Zhang , Hui Zhang , Re-Yu Gao
Ultra-deep and complex formations are characterized by narrow safety density windows and challenging well control. The combined use of multiple well-killing methods or temporary adjustments to well-killing strategies is becoming common. However, conventional well-killing models often struggle to calculate the parameters required for these special cases. In this paper, a boundary matrix for well-killing fluid density and volume is proposed to unify the driller’s method, the engineer’s method, and the weight-while-circulating method. Furthermore, a dynamic unified well-killing model is developed to enable the synergistic regulation of multiple well-killing methods. The model also can be applied with or without accounting for gas dissolution. Using this model, it is able to dynamically track key parameters during well killing and shut in the well at any time to determine the standpipe and casing pressures. The results indicate that the casing pressure drops to zero before the well-killing fluid returns to the annulus wellhead, and continued injection of the fluid leads to a gradual increase in standpipe pressure, a phenomenon not previously accounted for. The discrepancy between the actual and calculated standpipe/casing pressures after shut-in can be utilized to assess whether the downhole gas kick is effectively controlled. Through real-time adjustments to the boundary matrix, updated well-killing parameters can be derived for conventional method, multi-method combination, temporary strategy modification, and other well-killing scenarios. The model was applied to two field wells under water- and oil-based drilling fluids. No secondary downhole complications occurred during well killing, and the calculated pressure curves closely matched the measured construction pressure curves, confirming the model’s reliability and applicability. This study provides valuable theoretical guidance for enhancing well control safety in ultra-deep and complex formations.
{"title":"A dynamic unified well-killing model for synergistic regulation of multiple well-killing methods","authors":"Hong-Wei Yang , Jun Li , Zhen-Yu Long , Xiu-Ling Zhang , Geng Zhang , Hui Zhang , Re-Yu Gao","doi":"10.1016/j.petsci.2025.08.025","DOIUrl":"10.1016/j.petsci.2025.08.025","url":null,"abstract":"<div><div>Ultra-deep and complex formations are characterized by narrow safety density windows and challenging well control. The combined use of multiple well-killing methods or temporary adjustments to well-killing strategies is becoming common. However, conventional well-killing models often struggle to calculate the parameters required for these special cases. In this paper, a boundary matrix for well-killing fluid density and volume is proposed to unify the driller’s method, the engineer’s method, and the weight-while-circulating method. Furthermore, a dynamic unified well-killing model is developed to enable the synergistic regulation of multiple well-killing methods. The model also can be applied with or without accounting for gas dissolution. Using this model, it is able to dynamically track key parameters during well killing and shut in the well at any time to determine the standpipe and casing pressures. The results indicate that the casing pressure drops to zero before the well-killing fluid returns to the annulus wellhead, and continued injection of the fluid leads to a gradual increase in standpipe pressure, a phenomenon not previously accounted for. The discrepancy between the actual and calculated standpipe/casing pressures after shut-in can be utilized to assess whether the downhole gas kick is effectively controlled. Through real-time adjustments to the boundary matrix, updated well-killing parameters can be derived for conventional method, multi-method combination, temporary strategy modification, and other well-killing scenarios. The model was applied to two field wells under water- and oil-based drilling fluids. No secondary downhole complications occurred during well killing, and the calculated pressure curves closely matched the measured construction pressure curves, confirming the model’s reliability and applicability. This study provides valuable theoretical guidance for enhancing well control safety in ultra-deep and complex formations.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4603-4623"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.09.034
Pei Du , Xuan-Kai Zhang , Jun-Tao Du , Jian-Zhou Wang
The significance of accurately forecasting natural gas prices is far-reaching and significant, not only for the stable operation of the energy market, but also as a key element in promoting sustainable development and addressing environmental challenges. However, natural gas prices are affected by multiple source factors, presenting complex, unstable nonlinear characteristics hindering the improvement of the prediction accuracy of existing models. To address this issue, this study proposes an innovative multivariate combined forecasting model for natural gas prices. Initially, the study meticulously identifies and introduces 16 variables impacting natural gas prices across five crucial dimensions: the production, marketing, commodities, political and economic indicators of the United States and temperature. Subsequently, this study employs the least absolute shrinkage and selection operator, grey relation analysis, and random forest for dimensionality reduction, effectively screening out the most influential key variables to serve as input features for the subsequent learning model. Building upon this foundation, a suite of machine learning models is constructed to ensure precise natural gas price prediction. To further elevate the predictive performance, an intelligent algorithm for parameter optimization is incorporated, addressing potential limitations of individual models. To thoroughly assess the prediction accuracy of the proposed model, this study conducts three experiments using monthly natural gas trading prices. These experiments incorporate 19 benchmark models for comparative analysis, utilizing five evaluation metrics to quantify forecasting effectiveness. Furthermore, this study conducts in-depth validation of the proposed modelʼs effectiveness through hypothesis testing, discussions on the improvement ratio of forecasting performance, and case studies on other energy prices. The empirical results demonstrate that the multivariate combined forecasting method developed in this study surpasses other comparative models in forecasting accuracy. It offers new perspectives and methodologies for natural gas price forecasting while also providing valuable insights for other energy price forecasting studies.
{"title":"Multivariate natural gas price forecasting model with feature selection, machine learning and chernobyl disaster optimizer","authors":"Pei Du , Xuan-Kai Zhang , Jun-Tao Du , Jian-Zhou Wang","doi":"10.1016/j.petsci.2025.09.034","DOIUrl":"10.1016/j.petsci.2025.09.034","url":null,"abstract":"<div><div>The significance of accurately forecasting natural gas prices is far-reaching and significant, not only for the stable operation of the energy market, but also as a key element in promoting sustainable development and addressing environmental challenges. However, natural gas prices are affected by multiple source factors, presenting complex, unstable nonlinear characteristics hindering the improvement of the prediction accuracy of existing models. To address this issue, this study proposes an innovative multivariate combined forecasting model for natural gas prices. Initially, the study meticulously identifies and introduces 16 variables impacting natural gas prices across five crucial dimensions: the production, marketing, commodities, political and economic indicators of the United States and temperature. Subsequently, this study employs the least absolute shrinkage and selection operator, grey relation analysis, and random forest for dimensionality reduction, effectively screening out the most influential key variables to serve as input features for the subsequent learning model. Building upon this foundation, a suite of machine learning models is constructed to ensure precise natural gas price prediction. To further elevate the predictive performance, an intelligent algorithm for parameter optimization is incorporated, addressing potential limitations of individual models. To thoroughly assess the prediction accuracy of the proposed model, this study conducts three experiments using monthly natural gas trading prices. These experiments incorporate 19 benchmark models for comparative analysis, utilizing five evaluation metrics to quantify forecasting effectiveness. Furthermore, this study conducts in-depth validation of the proposed modelʼs effectiveness through hypothesis testing, discussions on the improvement ratio of forecasting performance, and case studies on other energy prices. The empirical results demonstrate that the multivariate combined forecasting method developed in this study surpasses other comparative models in forecasting accuracy. It offers new perspectives and methodologies for natural gas price forecasting while also providing valuable insights for other energy price forecasting studies.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4823-4837"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.07.026
Jian-Yong Xie , Yan-Ping Fang , Chun-Wei Wu , She-Bao Jiao , Jing-Xiao Wang , Ji-Xin Deng , Xing-Jian Wang
Brittleness is pivotal in predicting shale reservoir quality and designing hydraulic fracturing strategies. However, intricate diagenetic environment of shale, characterized by distinct bedding structures, challenges the isotropic-based brittleness assessment methods. This study introduces a new quantitative approach to assess shale brittleness anisotropy, integrating anisotropic elastic responses and tensile fracturing mechanisms. The proposed model effectively reduces uncertainty in the causal relationship between Young's modulus and brittle failure. Comprehensive experimental validation encompassed 18 samples from six groups of Chang 7 terrestrial shale in Ordos Basin. The optimal anisotropic tensile strength criterion (N-Z criterion, error < 5%) was identified, enhancing the theoretical accuracy of the proposed model. Comparative experimental results demonstrate that the model adeptly predicts brittleness strength and directional variation characteristics across variations in mineral type, content and microstructure, underscoring its effectiveness. Additionally, theoretical predictions on shale samples with different organic matter reveal that brittleness strength and its anisotropy across varying OM are not monotonously decreasing. The research highlights that brittleness characteristics are influenced by both mineral type/content and microstructural distribution. Notably, the prevalence of isotropic brittle minerals is the primary determinant of brittleness strength, positively correlated. Conversely, ductile mineral content (striped skeletal support-type OM and clay) negatively correlates with brittleness strength, acting as secondary controlling factors. The impact of pore-filled OM on brittleness appears negligible. Rock physical modeling based on equivalent media theory for shale with pore-filled and/or striped OM further elucidates the mechanisms driving these variations. These findings attach great importance in assessment of terrestrial shale geological and engineering “sweet-spots".
{"title":"Quantitative evaluation of brittleness anisotropy and its influencing factors in terrestrial shale","authors":"Jian-Yong Xie , Yan-Ping Fang , Chun-Wei Wu , She-Bao Jiao , Jing-Xiao Wang , Ji-Xin Deng , Xing-Jian Wang","doi":"10.1016/j.petsci.2025.07.026","DOIUrl":"10.1016/j.petsci.2025.07.026","url":null,"abstract":"<div><div>Brittleness is pivotal in predicting shale reservoir quality and designing hydraulic fracturing strategies. However, intricate diagenetic environment of shale, characterized by distinct bedding structures, challenges the isotropic-based brittleness assessment methods. This study introduces a new quantitative approach to assess shale brittleness anisotropy, integrating anisotropic elastic responses and tensile fracturing mechanisms. The proposed model effectively reduces uncertainty in the causal relationship between Young's modulus and brittle failure. Comprehensive experimental validation encompassed 18 samples from six groups of Chang 7 terrestrial shale in Ordos Basin. The optimal anisotropic tensile strength criterion (N-Z criterion, error < 5%) was identified, enhancing the theoretical accuracy of the proposed model. Comparative experimental results demonstrate that the model adeptly predicts brittleness strength and directional variation characteristics across variations in mineral type, content and microstructure, underscoring its effectiveness. Additionally, theoretical predictions on shale samples with different organic matter reveal that brittleness strength and its anisotropy across varying OM are not monotonously decreasing. The research highlights that brittleness characteristics are influenced by both mineral type/content and microstructural distribution. Notably, the prevalence of isotropic brittle minerals is the primary determinant of brittleness strength, positively correlated. Conversely, ductile mineral content (striped skeletal support-type OM and clay) negatively correlates with brittleness strength, acting as secondary controlling factors. The impact of pore-filled OM on brittleness appears negligible. Rock physical modeling based on equivalent media theory for shale with pore-filled and/or striped OM further elucidates the mechanisms driving these variations. These findings attach great importance in assessment of terrestrial shale geological and engineering “sweet-spots\".</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4555-4572"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.09.033
Hai-Feng Zhao , Jie-Lun Luo , Xue-Jiao Li , Wen-Jie Yao , Liang Ji , Huai-Bin Zhen
The effectiveness of horizontal well multi-stage and multi-cluster fracturing in the fractured soft coal seam roof for coalbed methane (CBM) extraction has been demonstrated. This study focuses on the geological characteristics of the No. 5 and No. 11 coal seams in the Hancheng Block, Ordos Basin, China. A multi-functional, variable-size rock sample mold capable of securing the wellbore was developed to simulate layered formations comprising strata of varying lithology and thicknesses. A novel segmented fracturing simulation method based on an expandable pipe plugging technique is proposed. Large-scale true triaxial experiments were conducted to investigate the effects of horizontal wellbore location, perforation strategy, roof lithology, and vertical stress difference on fracture propagation, hydraulic energy variation, and the stimulated reservoir volume in horizontal wells targeting the soft coal seam roof. The results indicate that bilateral downward perforation with a phase angle of 120° optimizes hydraulic energy conservation, reduces operational costs, enhances fracture formation, and prevents fracturing failure caused by coal powder generation and migration. This perforation mode is thus considered optimal for coal seam roof fracturing. When the roof consists of sandstone, each perforation cluster tends to initiate a single dominant fracture with a regular geometry. In contrast, hydraulic fractures formed in mudstone roofs display diverse morphology. Due to its high strength, the sandstone roof requires significantly higher pressure for crack initiation and propagation, whereas the mudstone roof, with its strong water sensitivity, exhibits lower fracturing pressures. To mitigate inter-cluster interference, cluster spacing in mudstone roofs should be greater than that in sandstone roofs. Horizontal wellbore placement critically influences fracturing effectiveness. For indirect fracturing in sandstone roofs, an optimal position is 25 mm away from the lithological interface. In contrast, the optimal location for indirect fracturing in mudstone roofs is directly at the lithological interface with the coal seam. Higher vertical stress coefficients lead to increased fracturing pressures and promote vertical, layer-penetrating fractures. A coefficient of 0.5 is identified as optimal for achieving effective indirect fracturing. This study provides valuable insights for the design and optimization of staged fracturing in horizontal wells targeting crushed soft coal seam roofs.
{"title":"Experimental investigation into the fracture propagation behavior of horizontal well multi-stage and multi-cluster fracturing within the roof of crushed soft coal seams","authors":"Hai-Feng Zhao , Jie-Lun Luo , Xue-Jiao Li , Wen-Jie Yao , Liang Ji , Huai-Bin Zhen","doi":"10.1016/j.petsci.2025.09.033","DOIUrl":"10.1016/j.petsci.2025.09.033","url":null,"abstract":"<div><div>The effectiveness of horizontal well multi-stage and multi-cluster fracturing in the fractured soft coal seam roof for coalbed methane (CBM) extraction has been demonstrated. This study focuses on the geological characteristics of the No. 5 and No. 11 coal seams in the Hancheng Block, Ordos Basin, China. A multi-functional, variable-size rock sample mold capable of securing the wellbore was developed to simulate layered formations comprising strata of varying lithology and thicknesses. A novel segmented fracturing simulation method based on an expandable pipe plugging technique is proposed. Large-scale true triaxial experiments were conducted to investigate the effects of horizontal wellbore location, perforation strategy, roof lithology, and vertical stress difference on fracture propagation, hydraulic energy variation, and the stimulated reservoir volume in horizontal wells targeting the soft coal seam roof. The results indicate that bilateral downward perforation with a phase angle of 120° optimizes hydraulic energy conservation, reduces operational costs, enhances fracture formation, and prevents fracturing failure caused by coal powder generation and migration. This perforation mode is thus considered optimal for coal seam roof fracturing. When the roof consists of sandstone, each perforation cluster tends to initiate a single dominant fracture with a regular geometry. In contrast, hydraulic fractures formed in mudstone roofs display diverse morphology. Due to its high strength, the sandstone roof requires significantly higher pressure for crack initiation and propagation, whereas the mudstone roof, with its strong water sensitivity, exhibits lower fracturing pressures. To mitigate inter-cluster interference, cluster spacing in mudstone roofs should be greater than that in sandstone roofs. Horizontal wellbore placement critically influences fracturing effectiveness. For indirect fracturing in sandstone roofs, an optimal position is 25 mm away from the lithological interface. In contrast, the optimal location for indirect fracturing in mudstone roofs is directly at the lithological interface with the coal seam. Higher vertical stress coefficients lead to increased fracturing pressures and promote vertical, layer-penetrating fractures. A coefficient of 0.5 is identified as optimal for achieving effective indirect fracturing. This study provides valuable insights for the design and optimization of staged fracturing in horizontal wells targeting crushed soft coal seam roofs.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4682-4713"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.08.002
Yun-Zhao Zhang , Quan-Qi Dai , Lian-Bo Zeng , Rui-Qi Li , Rong-Jun Zhang , Le Qu , Yang-Wen Zhu , Hai-Ying Liao , Hao Wu
During the CO2 injection and geological storage process, the integrity of the cap rock significantly influences the long-term safety of CO2 storage. Natural fractures within the cap rock serve as potential pathways for CO2 migration, thereby increasing the risk of CO2 leakage. In this study, we determined the types, developmental characteristics, permeability changes, and CO2-H2O-Rock reactions of natural fractures in the mudstone cap rocks of the Sanduo Formation (E3s) and Dainan Formation (E2d) in the Gaoyou Sag of the Subei Basin using core observations, thin-section analysis, rock mechanics experiments, and paleomagnetic directional analysis. We identified four tectonic fracture sets (NNW, NWW, EW, and NE); high-angle shear fractures, ranging from 60° to 90° (average 82°) and typically measuring 4–12 cm (average 7.5 cm), dominate the assemblage, while slip fractures, ranging from 32° to 50° (average 36°) and measuring 3–6 cm (average 3.9 cm), are also present. At the microscale, shear fractures average 160 μm, and bedding fractures average 82 μm. Notably, 85.78% of shear fractures are unfilled, with calcite filling observed in 14.22%, while other fracture types show no filling. Permeability tests on samples without fractures reveal that permeability declines rapidly below 9 MPa, especially in shallower samples, followed by a slower reduction between 9 and 13 MPa, and ultimately stabilizes at approximately 0.00003 mD. In contrast, samples with fractures exhibit permeability that is 3–4 orders of magnitude higher; their fracture permeability decays according to a power law with pressure yet remains above 10 mD even at 46 MPa. Fractures with larger dip angles and those aligned with the maximum principal stress demonstrate the highest permeability. While silicate-filled fractures exhibit negligible changes in permeability, carbonate-filled fractures experience a temporary enhancement due to dissolution; however, subsequent permeability remains controlled by factors such as effective stress and fracture orientation.
{"title":"Effects of natural fractures in cap rock on CO2 geological storage: Sanduo Formation and Dainan Formation of the early Eocene epoch in the Gaoyou Sag of the Subei Basin","authors":"Yun-Zhao Zhang , Quan-Qi Dai , Lian-Bo Zeng , Rui-Qi Li , Rong-Jun Zhang , Le Qu , Yang-Wen Zhu , Hai-Ying Liao , Hao Wu","doi":"10.1016/j.petsci.2025.08.002","DOIUrl":"10.1016/j.petsci.2025.08.002","url":null,"abstract":"<div><div>During the CO<sub>2</sub> injection and geological storage process, the integrity of the cap rock significantly influences the long-term safety of CO<sub>2</sub> storage. Natural fractures within the cap rock serve as potential pathways for CO<sub>2</sub> migration, thereby increasing the risk of CO<sub>2</sub> leakage. In this study, we determined the types, developmental characteristics, permeability changes, and CO<sub>2</sub>-H<sub>2</sub>O-Rock reactions of natural fractures in the mudstone cap rocks of the Sanduo Formation (E<sub>3</sub>s) and Dainan Formation (E<sub>2</sub>d) in the Gaoyou Sag of the Subei Basin using core observations, thin-section analysis, rock mechanics experiments, and paleomagnetic directional analysis. We identified four tectonic fracture sets (NNW, NWW, EW, and NE); high-angle shear fractures, ranging from 60° to 90° (average 82°) and typically measuring 4–12 cm (average 7.5 cm), dominate the assemblage, while slip fractures, ranging from 32° to 50° (average 36°) and measuring 3–6 cm (average 3.9 cm), are also present. At the microscale, shear fractures average 160 μm, and bedding fractures average 82 μm. Notably, 85.78% of shear fractures are unfilled, with calcite filling observed in 14.22%, while other fracture types show no filling. Permeability tests on samples without fractures reveal that permeability declines rapidly below 9 MPa, especially in shallower samples, followed by a slower reduction between 9 and 13 MPa, and ultimately stabilizes at approximately 0.00003 mD. In contrast, samples with fractures exhibit permeability that is 3–4 orders of magnitude higher; their fracture permeability decays according to a power law with pressure yet remains above 10 mD even at 46 MPa. Fractures with larger dip angles and those aligned with the maximum principal stress demonstrate the highest permeability. While silicate-filled fractures exhibit negligible changes in permeability, carbonate-filled fractures experience a temporary enhancement due to dissolution; however, subsequent permeability remains controlled by factors such as effective stress and fracture orientation.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4341-4356"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.10.012
Xin Zhao , Ying-Bo Wang , Fu-Hua Cao , Cao-Yuan Niu , Zi-Qing Liu , Lei Wang
In Dagang Oilfield in China, the utilization of the KCl polymer water-based drilling fluid (WBDF) in mid-deep exploration/appraisal wells presents a challenge in simultaneously optimizing resistivity logging accuracy and wellbore stability. To address this, it is necessary to conduct geology-engineering integration studies. Based on the formation resistivity, an analytical model was developed to assess the impact of KCl concentration in the WBDF on array induction logging response accuracy. The maximum permissible KCl concentration for the target formations was determined, and technical strategies were proposed to maintain wellbore stability at a reduced KCl concentration. After that, considering the inhibitory, encapsulating, and plugging effects, a low-KCl-concentration WBDF was optimized and applied. Model calculations demonstrate that increasing KCl concentration in the WBDF decreases resistivity, thereby reducing logging accuracy. To maintain a logging accuracy of ≥80%, the upper limits for KCl concentration in the WBDF are 4.8%, 4.2%, and 3.6% for the 3rd Member of the Dongying Formation, the 1st and 2nd members of the Shahejie Formation, respectively. Cuttings recovery experiments revealed that a minimum KCl concentration of 3% is required to ensure basic shale inhibition. A combination of 3% KCl with 1% polyamine inhibitor yielded cuttings recovery and shale stability index comparable to those achieved with 7% KCl alone, and the shale inhibition performance was further enhanced with the addition of an encapsulator. The optimized WBDF has been successfully deployed in exploration/appraisal wells across multiple blocks within Dagang Oilfield, resulting in superior wellbore stability during operations. Furthermore, the electric logging interpretation coincidence rate improved from 68.1% to 89.9%, providing robust technical support for high-quality drilling and accurate reservoir evaluation in exploration/appraisal wells.
{"title":"Optimization and application of KCl polymer drilling fluid balancing wellbore stability and logging response accuracy","authors":"Xin Zhao , Ying-Bo Wang , Fu-Hua Cao , Cao-Yuan Niu , Zi-Qing Liu , Lei Wang","doi":"10.1016/j.petsci.2025.10.012","DOIUrl":"10.1016/j.petsci.2025.10.012","url":null,"abstract":"<div><div>In Dagang Oilfield in China, the utilization of the KCl polymer water-based drilling fluid (WBDF) in mid-deep exploration/appraisal wells presents a challenge in simultaneously optimizing resistivity logging accuracy and wellbore stability. To address this, it is necessary to conduct geology-engineering integration studies. Based on the formation resistivity, an analytical model was developed to assess the impact of KCl concentration in the WBDF on array induction logging response accuracy. The maximum permissible KCl concentration for the target formations was determined, and technical strategies were proposed to maintain wellbore stability at a reduced KCl concentration. After that, considering the inhibitory, encapsulating, and plugging effects, a low-KCl-concentration WBDF was optimized and applied. Model calculations demonstrate that increasing KCl concentration in the WBDF decreases resistivity, thereby reducing logging accuracy. To maintain a logging accuracy of ≥80%, the upper limits for KCl concentration in the WBDF are 4.8%, 4.2%, and 3.6% for the 3rd Member of the Dongying Formation, the 1st and 2nd members of the Shahejie Formation, respectively. Cuttings recovery experiments revealed that a minimum KCl concentration of 3% is required to ensure basic shale inhibition. A combination of 3% KCl with 1% polyamine inhibitor yielded cuttings recovery and shale stability index comparable to those achieved with 7% KCl alone, and the shale inhibition performance was further enhanced with the addition of an encapsulator. The optimized WBDF has been successfully deployed in exploration/appraisal wells across multiple blocks within Dagang Oilfield, resulting in superior wellbore stability during operations. Furthermore, the electric logging interpretation coincidence rate improved from 68.1% to 89.9%, providing robust technical support for high-quality drilling and accurate reservoir evaluation in exploration/appraisal wells.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4645-4655"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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