Abstract
To fully extract and mine the multi-scale features of reservoirs and geologic structures in time/depth and space dimensions, a new 3D multi-scale volumetric curvature (MSVC) methodology is presented in this paper. We also propose a fast algorithm for computing 3D volumetric curvature. In comparison to conventional volumetric curvature attributes, its main improvements and key algorithms introduce multi-frequency components expansion in time-frequency domain and the corresponding multi-scale adaptive differential operator in the wavenumber domain, into the volumetric curvature calculation. This methodology can simultaneously depict seismic multi-scale features in both time and space. Additionally, we use data fusion of volumetric curvatures at various scales to take full advantage of the geologic features and anomalies extracted by curvature measurements at different scales. The 3D MSVC can highlight geologic anomalies and reduce noise at the same time. Thus, it improves the interpretation efficiency of curvature attributes analysis. The 3D MSVC is applied to both land and marine 3D seismic data. The results demonstrate that it can indicate the spatial distribution of reservoirs, detect faults and fracture zones, and identify their multi-scale properties.
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This work was supported by the National Natural Science Foundation of China (No. 41004054), the Research Fund for the Doctoral Program of Higher Education of China (No. 20105122120002), and Natural Science Key Project, Sichuan Provincial Department of Education (No. 092A011).
Chen Xue-Hua, Associate professor, received his BS from Huazhong University of Science and Technology in 2002 and MS and PhD Chengdu University of Technology in 2006 and 2009. His research interests include seismic signal processing, seismic reservoir characterization and hydrocarbon exploration.
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Chen, XH., Yang, W., He, ZH. et al. The algorithm of 3D multi-scale volumetric curvature and its application. Appl. Geophys. 9, 65–72 (2012). https://doi.org/10.1007/s11770-012-0315-7
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DOI: https://doi.org/10.1007/s11770-012-0315-7