LAPSE:2023.14755
Published Article
LAPSE:2023.14755
Application of Far-Gather Seismic Attributes in Suppressing the Interference of Coal Beds in Reservoir Prediction
Yunxin Mao, Chunjing Yan, Ruoyu Zhang, Yangsen Li, Min Lou, Luxing Dou, Xinrui Zhou, Xixin Wang
March 1, 2023
Abstract
The sandstone reservoir of the Pinghu Formation in the Xihu Depression, East China Sea is characterized by great depth, small thickness, radical facies change and a widespread coal bed. It is difficult to describe the reservoir accurately using conventional reservoir prediction methods. In order to analyze the influence of coal-bearing strata on the prediction of the mid-low thickness sandstone reservoir, the seismic response of different sandstone−coal stratigraphic assemblages was simulated by seismic forward modeling. The modeling result indicates that the post-stack seismic response is dominated by coal bed, whereas the response of sandstone can hardly be recognized. In contrast, the difference between the pre-stack AVO (amplitude versus offset) response characteristics of coal seams and gas-bearing sandstones has been clarified based on the statistics pertaining to AVO characteristics of drilled wells. Therefore, we propose a method to reduce the interference of coal beds in sandstone reservoir prediction using far-gather seismic information. This method has significantly improved the accuracy of reservoir prediction and sand description in sand−coal coupled environments and has been applied successfully in the exploration of coal-rich strata in the Pingbei slope belt, Xihu Depression.
Keywords
coal strata, dominant far-offset, pre-stack AVO forward, reservoir prediction, seismic response
Suggested Citation
Mao Y, Yan C, Zhang R, Li Y, Lou M, Dou L, Zhou X, Wang X. Application of Far-Gather Seismic Attributes in Suppressing the Interference of Coal Beds in Reservoir Prediction. (2023). LAPSE:2023.14755
Author Affiliations
Mao Y: Shanghai Branch of CNOOC China Limited, Changning District, Shanghai 200050, China
Yan C: School of Geosciences, Yangtze University, Wuhan 430100, China
Zhang R: Shanghai Branch of CNOOC China Limited, Changning District, Shanghai 200050, China [ORCID]
Li Y: Shanghai Branch of CNOOC China Limited, Changning District, Shanghai 200050, China
Lou M: Shanghai Branch of CNOOC China Limited, Changning District, Shanghai 200050, China
Dou L: School of Geosciences, Yangtze University, Wuhan 430100, China
Zhou X: School of Geosciences, Yangtze University, Wuhan 430100, China
Wang X: School of Geosciences, Yangtze University, Wuhan 430100, China [ORCID]
Journal Name
Energies
Volume
15
Issue
6
First Page
2206
Year
2022
Publication Date
2022-03-17
ISSN
1996-1073
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PII: en15062206, Publication Type: Journal Article
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LAPSE:2023.14755
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https://doi.org/10.3390/en15062206
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