Total organic carbon(TOC)content is a crucial evaluation parameter in the process of shale gas exploration and development.Marine-continental transitional shale is characterized by strong heterogeneity and thin single...Total organic carbon(TOC)content is a crucial evaluation parameter in the process of shale gas exploration and development.Marine-continental transitional shale is characterized by strong heterogeneity and thin single-layer thickness.The discrete TOC data measured by experimental methods are unable to accurately reflect the reservoir characteristics of marine-continental transitional shale.In this paper,a multivariate nonlinear regression prediction model(R-MNR)was established,and the model was applied to predict the TOC content of shale for the first time.TheΔlgR model,multiple linear regression model(MLR),BP neural network model(BP model),and R-MNR model were built to predict the TOC of shale in Benxi Formation.The coefficient of determination(R2),mean-absolute-percentage-error(MAPE),root-mean-square-error(RMSE),and the number of input layer parameters(NILP)were employed to assess the efficacy of the model through the analytic hierarchy process(AHP)method.The total weight of R-MNR is 0.361,and that of BP model is 0.336.The weights of the two traditional models are 0.104 and 0.199,respectively.The results indicate that the R-MNR is comparable to the BP model in terms of prediction accuracy,and both models are significantly more accurate than the traditional prediction model.The R-MNR is capable of obtaining a clear TOC prediction formula,which is convenient for verification and promotion.During the training process of the R-MNR,the influence of each parameter and coupling relationship on the prediction results is elucidated,which enables researchers to gain a deeper understanding of the geophysical significance and geological process of the model.The result of this study suggests that the R-MNR can be employed to predict the TOC content of marine-continental transitional shale effectively in the future.展开更多
Commercial exploration and development of deep buried coalbed methane (CBM) in Daning-Jixian Block, eastern margin of Ordos Basin, have rapidly increased in recent decades. Gas content, saturation and well productivit...Commercial exploration and development of deep buried coalbed methane (CBM) in Daning-Jixian Block, eastern margin of Ordos Basin, have rapidly increased in recent decades. Gas content, saturation and well productivity show significant heterogeneity in this area. To better understand the geological controlling mechanism on gas distribution heterogeneity, the burial history, hydrocarbon generation history and tectonic evolution history were studied by numerical simulation and experimental simulation, which could provide guidance for further development of CBM in this area. The burial history of coal reservoir can be classified into six stages, i.e., shallowly buried stage, deeply burial stage, uplifting stage, short-term tectonic subsidence stage, large-scale uplifting stage, sustaining uplifting and structural inversion stage. The organic matter in coal reservoir experienced twice hydrocarbon generation. Primary and secondary hydrocarbon generation processes were formed by the Early and Middle Triassic plutonic metamorphism and Early Cretaceous regional magmatic thermal metamorphism, respectively. Five critical tectonic events of the Indosinian, Yanshanian and Himalayan orogenies affect different stages of the CBM reservoir accumulation process. The Indosinian orogeny mainly controls the primary CBM generation. The Yanshanian Orogeny dominates the second gas generation and migration processes. The Himalayan orogeny mainly affects the gas dissipation process and current CBM distribution heterogeneity.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.42372194)the Natural Science Foundation of Shanxi Province,China(No.20210302123165),the Chinese Postdoctoral Science Foundation(No.2024T170634)the Open Fund Project of Provincial Center of Technology Innovation for Coal Measure Gas Co-production(ZZGSSASMCYJ2024-0306).
文摘Total organic carbon(TOC)content is a crucial evaluation parameter in the process of shale gas exploration and development.Marine-continental transitional shale is characterized by strong heterogeneity and thin single-layer thickness.The discrete TOC data measured by experimental methods are unable to accurately reflect the reservoir characteristics of marine-continental transitional shale.In this paper,a multivariate nonlinear regression prediction model(R-MNR)was established,and the model was applied to predict the TOC content of shale for the first time.TheΔlgR model,multiple linear regression model(MLR),BP neural network model(BP model),and R-MNR model were built to predict the TOC of shale in Benxi Formation.The coefficient of determination(R2),mean-absolute-percentage-error(MAPE),root-mean-square-error(RMSE),and the number of input layer parameters(NILP)were employed to assess the efficacy of the model through the analytic hierarchy process(AHP)method.The total weight of R-MNR is 0.361,and that of BP model is 0.336.The weights of the two traditional models are 0.104 and 0.199,respectively.The results indicate that the R-MNR is comparable to the BP model in terms of prediction accuracy,and both models are significantly more accurate than the traditional prediction model.The R-MNR is capable of obtaining a clear TOC prediction formula,which is convenient for verification and promotion.During the training process of the R-MNR,the influence of each parameter and coupling relationship on the prediction results is elucidated,which enables researchers to gain a deeper understanding of the geophysical significance and geological process of the model.The result of this study suggests that the R-MNR can be employed to predict the TOC content of marine-continental transitional shale effectively in the future.
基金This research was funded by the National Natural Science Foundation of China (Grant No. 41902178)National Science and Technology Major Project (Oil & Gas) (No. 2016ZX05065)+1 种基金Natural Science Foundation of Shanxi Province, China (No. 20210302123165)Open Fund of Beijing Key Laboratory of Unconventional Natural Gas Geological Evaluation and Development Engineering, China University of Geosciences (Beijing) (No. 2019BJ02001).
文摘Commercial exploration and development of deep buried coalbed methane (CBM) in Daning-Jixian Block, eastern margin of Ordos Basin, have rapidly increased in recent decades. Gas content, saturation and well productivity show significant heterogeneity in this area. To better understand the geological controlling mechanism on gas distribution heterogeneity, the burial history, hydrocarbon generation history and tectonic evolution history were studied by numerical simulation and experimental simulation, which could provide guidance for further development of CBM in this area. The burial history of coal reservoir can be classified into six stages, i.e., shallowly buried stage, deeply burial stage, uplifting stage, short-term tectonic subsidence stage, large-scale uplifting stage, sustaining uplifting and structural inversion stage. The organic matter in coal reservoir experienced twice hydrocarbon generation. Primary and secondary hydrocarbon generation processes were formed by the Early and Middle Triassic plutonic metamorphism and Early Cretaceous regional magmatic thermal metamorphism, respectively. Five critical tectonic events of the Indosinian, Yanshanian and Himalayan orogenies affect different stages of the CBM reservoir accumulation process. The Indosinian orogeny mainly controls the primary CBM generation. The Yanshanian Orogeny dominates the second gas generation and migration processes. The Himalayan orogeny mainly affects the gas dissipation process and current CBM distribution heterogeneity.
