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Application of scattering image wavelet transform in cave recognition: A case study on a bedrock buried hill reservoir in Bongor Basin, Chad

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Abstract

Caves located in the buried hill reservoir of granite bedrock in Bongor Basin, Chad, are excessively small and cannot be identified in conventional reflection wave imaging profiles because their reflection characteristics are suppressed by the strong reflection of the weathering crust at the top of the buried hill. In contrast to reflection wave imaging, which reflects the reflection characteristics of continuous interfaces, scattered wave imaging reflects the reflection characteristics of discontinuous geological bodies. Scattering waves can be produced in the presence of discontinuous points, such as karst caves, fractures, and stratum vanishing points. Scattering imaging can accurately provide the location of discontinuous abnormal bodies, highlight the seismic reflection characteristics of caves with weak reflections, and eliminate continuous strong reflections to strengthen the ability of seismic data to distinguish discontinuous geological bodies and solve the inability of seismic data from conventional poststack reflection wave imaging to identify small caves in buried hills. Three-parameter wavelet spectral decomposition technology is used to depict the boundary of caves accurately in accordance with the strong energy spectral characteristics of caves in the section of the scattering imaging seismic data of the granite bedrock buried hill reservoir. Compared with the attributes extracted from conventional reflection wave poststack seismic data, those acquired from scattering imaging bodies are more reliable and consistent with the actual location of caves on boreholes and have higher resolution. For connected wells, the attributes extracted from the conventional poststack seismic data can only predict whether caves are developed, whereas those calculated from scattering imaging can not only predict whether caves are present but also reflects the degree of cave development. On the plane, the attributes obtained from scattering imaging calculation are more consistent with the geological law of cave development. On the basis of this finding and in accordance with the results of the three-parameter wavelet spectral decomposition of scattering imaging seismic data, the degree of cave development is classified, and the favorable location for reservoir development in the study area is identified. This solution provides an effective way to improve the exploration accuracy of cave-type granite buried hill reservoirs..

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Correspondence to Yu-Jiang Xiao.

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The research was funded by the PetroChina.

XiaoYu-Jiang received a doctor’s degree in earth exploration and information technology from China Petroleum Exploration and Development Research Institute in 2021. Now he works at China Petroleum Exploration and Development Research Institute and is engaged in petroleum geophysical exploration interpretation and reservoir prediction.

Co-author: Tao Song, Research Institute of Petroleum Exploration& Development, Beijing, China (Email: st0601@petrochina.com.cn

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Xiao, YJ., Song, T., Gan, LD. et al. Application of scattering image wavelet transform in cave recognition: A case study on a bedrock buried hill reservoir in Bongor Basin, Chad. Appl. Geophys. (2023). https://doi.org/10.1007/s11770-023-1008-0

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  • DOI: https://doi.org/10.1007/s11770-023-1008-0

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