Zheng Zhao , Dameng Liu , Yidong Cai , Fengrui Sun , Yingfang Zhou
{"title":"地球物理技术在煤层气储层多面表征中的应用途径与挑战","authors":"Zheng Zhao , Dameng Liu , Yidong Cai , Fengrui Sun , Yingfang Zhou","doi":"10.1016/j.gr.2025.05.017","DOIUrl":null,"url":null,"abstract":"<div><div>Revealing the distribution patterns of coal reservoir parameters is essential for evaluating the resource potential and guiding the production activities of coalbed methane (CBM). Although direct methods such as sample testing, coal core observation, and well testing measurement are effective, they are time-consuming, costly, and limited by the sampling locations and data volume. Consequently, the precision of regional-scale reservoir characterization based solely on these methods is often insufficient. Therefore, predictive methods based on geophysical technologies have been developed by establishing correlations between reservoir parameters and geophysical data, using direct measurements as labels. These methods offer significant advantages in terms of efficiency and cost-effectiveness, making them highly promising and practically valuable in the CBM field. This study presents a critical review of these advancements. First, the fundamental principles of seismic and geophysical logging are systematically introduced, along with methods for data preprocessing and analysis. Second, based on the differences in response mechanisms of various geophysical datasets to different reservoir parameters, the application advances of these techniques in assessing coal properties, coal structures, permeability, and fluid characteristics are emphasized. These advancements have contributed significantly to reducing exploration costs and improving development efficiency. However, the highly complex and heterogeneous nature of coal reservoirs weakens the correlation between geophysical data and individual reservoir parameters, and the generalizability of existing predictive models remains limited. To overcome these challenges, this paper proposes several key directions for the future development of geophysical technologies in CBM research, including: (1) the development of reservoir evaluation models that integrate geological constraints with algorithmic prediction; (2) the advancement of geophysical theory and the improvement of model generalizability; (3) the establishment of models focused on the spatial distribution characteristics of coal measure reservoir parameters; and (4) the construction of a comprehensive evaluation system that integrates geology, reservoir, and development for CBM.</div></div>","PeriodicalId":12761,"journal":{"name":"Gondwana Research","volume":"147 ","pages":"Pages 164-183"},"PeriodicalIF":7.2000,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pathways and challenges of the application of geophysical techniques to multifaceted coalbed methane reservoir characterization\",\"authors\":\"Zheng Zhao , Dameng Liu , Yidong Cai , Fengrui Sun , Yingfang Zhou\",\"doi\":\"10.1016/j.gr.2025.05.017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Revealing the distribution patterns of coal reservoir parameters is essential for evaluating the resource potential and guiding the production activities of coalbed methane (CBM). Although direct methods such as sample testing, coal core observation, and well testing measurement are effective, they are time-consuming, costly, and limited by the sampling locations and data volume. Consequently, the precision of regional-scale reservoir characterization based solely on these methods is often insufficient. Therefore, predictive methods based on geophysical technologies have been developed by establishing correlations between reservoir parameters and geophysical data, using direct measurements as labels. These methods offer significant advantages in terms of efficiency and cost-effectiveness, making them highly promising and practically valuable in the CBM field. This study presents a critical review of these advancements. First, the fundamental principles of seismic and geophysical logging are systematically introduced, along with methods for data preprocessing and analysis. Second, based on the differences in response mechanisms of various geophysical datasets to different reservoir parameters, the application advances of these techniques in assessing coal properties, coal structures, permeability, and fluid characteristics are emphasized. These advancements have contributed significantly to reducing exploration costs and improving development efficiency. However, the highly complex and heterogeneous nature of coal reservoirs weakens the correlation between geophysical data and individual reservoir parameters, and the generalizability of existing predictive models remains limited. To overcome these challenges, this paper proposes several key directions for the future development of geophysical technologies in CBM research, including: (1) the development of reservoir evaluation models that integrate geological constraints with algorithmic prediction; (2) the advancement of geophysical theory and the improvement of model generalizability; (3) the establishment of models focused on the spatial distribution characteristics of coal measure reservoir parameters; and (4) the construction of a comprehensive evaluation system that integrates geology, reservoir, and development for CBM.</div></div>\",\"PeriodicalId\":12761,\"journal\":{\"name\":\"Gondwana Research\",\"volume\":\"147 \",\"pages\":\"Pages 164-183\"},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2025-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gondwana Research\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1342937X25001674\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gondwana Research","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1342937X25001674","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Pathways and challenges of the application of geophysical techniques to multifaceted coalbed methane reservoir characterization
Revealing the distribution patterns of coal reservoir parameters is essential for evaluating the resource potential and guiding the production activities of coalbed methane (CBM). Although direct methods such as sample testing, coal core observation, and well testing measurement are effective, they are time-consuming, costly, and limited by the sampling locations and data volume. Consequently, the precision of regional-scale reservoir characterization based solely on these methods is often insufficient. Therefore, predictive methods based on geophysical technologies have been developed by establishing correlations between reservoir parameters and geophysical data, using direct measurements as labels. These methods offer significant advantages in terms of efficiency and cost-effectiveness, making them highly promising and practically valuable in the CBM field. This study presents a critical review of these advancements. First, the fundamental principles of seismic and geophysical logging are systematically introduced, along with methods for data preprocessing and analysis. Second, based on the differences in response mechanisms of various geophysical datasets to different reservoir parameters, the application advances of these techniques in assessing coal properties, coal structures, permeability, and fluid characteristics are emphasized. These advancements have contributed significantly to reducing exploration costs and improving development efficiency. However, the highly complex and heterogeneous nature of coal reservoirs weakens the correlation between geophysical data and individual reservoir parameters, and the generalizability of existing predictive models remains limited. To overcome these challenges, this paper proposes several key directions for the future development of geophysical technologies in CBM research, including: (1) the development of reservoir evaluation models that integrate geological constraints with algorithmic prediction; (2) the advancement of geophysical theory and the improvement of model generalizability; (3) the establishment of models focused on the spatial distribution characteristics of coal measure reservoir parameters; and (4) the construction of a comprehensive evaluation system that integrates geology, reservoir, and development for CBM.
期刊介绍:
Gondwana Research (GR) is an International Journal aimed to promote high quality research publications on all topics related to solid Earth, particularly with reference to the origin and evolution of continents, continental assemblies and their resources. GR is an "all earth science" journal with no restrictions on geological time, terrane or theme and covers a wide spectrum of topics in geosciences such as geology, geomorphology, palaeontology, structure, petrology, geochemistry, stable isotopes, geochronology, economic geology, exploration geology, engineering geology, geophysics, and environmental geology among other themes, and provides an appropriate forum to integrate studies from different disciplines and different terrains. In addition to regular articles and thematic issues, the journal invites high profile state-of-the-art reviews on thrust area topics for its column, ''GR FOCUS''. Focus articles include short biographies and photographs of the authors. Short articles (within ten printed pages) for rapid publication reporting important discoveries or innovative models of global interest will be considered under the category ''GR LETTERS''.