Prediction of coalbed methane content based on seismic identification of key geological parameters: a case in a study area, Southern Qinshui Basin

• Autorzy: Liu Jing , Chang Suoliang , Zhang Sheng , Li Yanrong , Hao Yaju , He Guoxian , He You , Liu Bo

Identyfikatory

DOI

10.1007/s11600-023-01037-0

• Języki publikacji: EN

Abstrakty

EN

The coalbed methane content (CMC) is an important parameter to evaluate the degree of coalbed methane enrichment, and also an important reservoir parameter to calculate coalbed methane resources, productivity prediction and reservoir simulation. Accurately identifying the distribution of CMC is crucial to the exploration of CBM. In this study, we developed a prediction method for the CMC distribution via seismic techniques identification of key geological parameters such as structure, coal thickness and sedimentation. Firstly, the geological factors that control the generation and preservation of CBM in the study area are quantitatively characterized by using five parameters: surface (X₁), residual (X₂), dip (X₃), coal thickness (X₄) and the ratio of sand to mud (X₅). Secondly, the geological parameters are extracted by seismic structure interpretation and inversion prediction technology. Thirdly, the key geological parameters of CMC are screened out by grey correlation analysis. Finally, the functional relationship of CMC and the key geological parameters is established to predict the CMC distribution. The method is applied to the CMC distribution prediction of two coal seams of a study area in the southern Qinshui Basin, China. Results show that different coal seams differ in key geological parameters of CMC, resulting in various CMC distribution laws. The CMC prediction method based on the key geological factors can effectively delineate the CBM enrichment area in the study area, providing important reference for the CBM exploration and development.

Słowa kluczowe

EN

coalbed methane content; structure; coal thickness; sedimentation; seismic identification; key geological parameters; quantitative prediction

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2023
• Tom: Vol. 71, no. 6
• Strony: 2645--2662
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Liu Jing

• Department of Earth Science & Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

autor

Chang Suoliang

• Department of Earth Science & Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

autor

Zhang Sheng

• Department of Earth Science & Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

autor

Li Yanrong

• Department of Earth Science & Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

autor

Hao Yaju

• School of Earth Science, East China University of Technology, Nanchang, 330013, China

autor

He Guoxian

• Asian American Gas, Inc., Beijing, 100024, China

autor

He You

• Asian American Gas, Inc., Beijing, 100024, China

autor

Liu Bo

• Department of Earth Science & Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).