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ORIGINAL RESEARCH article
Front. Earth Sci.
Sec. Georeservoirs
Volume 13 - 2025 | doi: 10.3389/feart.2025.1538756
This article is part of the Research Topic Advances and New Methods in Reservoirs Quantitative Characterization Using Seismic Data View all 14 articles
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Accurate estimation of brittleness index, characterizing the brittleness level of rocks, and reservoir fluid identification are crucial for the characterization and development of shale gas reservoirs. However, conventional seismic methods for the sweet spot parameters failed to realize the simultaneous inversion of fluid indicator and brittleness index, challenging exploration of the favorable fracturing areas for shale gas production. For this issue, we concentrate on the simultaneous seismic inversion method of fluid indicator and brittleness index. First, we have derived a novel PP-wave reflection coefficient equation incorporating the above sweet spot parameters, allowing the direct estimation of reservoir brittleness and fluid properties.Two groups of classical layered medium models are introduced to justify the high accuracy of the novel equation within the incidence angle of 40 degrees. Then, to effectively decouple these parameters from the pre-stack seismic data, anisotropic total variation based on LP norm sparse constraint (ATpV) seismic inversion method is introduced to obtain accurate inversion results, extracting sparser priori information through the strong sparsity of the LP norm. Numerical model examples demonstrate the high stability and robustness of the proposed simultaneous inversion method. Ultimately, we applied it to field seismic data from a gas-bearing shale reservoir in the Sichuan Basin, China. A comprehensive analysis of the threedimensional (3D) inversion results with logging, geological structure, and micro-seismic events detected from horizontal fracturing wells has validated the rationality of the method.
Keywords: shale gas, fluid indicator, brittleness, Sparse constraint, simultaneous seismic inversion
Received: 03 Dec 2024; Accepted: 19 Mar 2025.
Copyright: © 2025 Li, Wen, Zhao, Li and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiaotao Wen, Chengdu University of Technology, Chengdu, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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