Abstract
In view of the technical difficulties of the fine identification of micro-fractures and the prediction of sweet spot in coalbed methane (CBM) reservoirs in unconventional oil and gas reservoir exploration, this paper carries out the extraction and comparison of fractures on the basis of the gradient structure tensor (GST) method, combining with the real geological conditions of the Yanchuannan (YCN) work area. Based on the above, the Euler curvature at different angles is further extracted. Meanwhile, according to the data of five gas production wells in this work area, fracture networks at the top of the M2 target layer are displayed in 3D space. The frequency responses of the fracture networks are characterized by threshold filter histogram and fracture stress rose diagrams are also analyzed. The results show that the NE-trending micro-fractures are well developed and the interlaced fracture networks are dense in the study area, which is an ideal sweet spot for CBM. Therefore, this study verifies the efficiency and practicability of the GST detection method, and provides an innovative way for identifying CBM fracture networks and predicting sweet spot.
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The authors would like to extend the thankfulness to the editors and the anonymous reviewers for their careful review of this paper.
Funding
The authors received financial support provided from the National Science and Technology Major Project of China (grant no. 2016ZX05026001-004), 2018 Sichuan Science and Technology Innovation Seedling Project Funding Project (no: 2018133), and 2018 National Students’ project for innovation and entrepreneurship training program (no.: 201810616045X).
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Zhao, C., Zhou, Y., Li, Y. et al. Application of gradient structure tensor method in CBM fracture identification and sweet spot prediction. Arab J Geosci 12, 641 (2019). https://doi.org/10.1007/s12517-019-4831-0
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DOI: https://doi.org/10.1007/s12517-019-4831-0