Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle Reservoirs

Accurate characterization of subsurface geological structures, particularly those obscured by strong coal-seam reflections, is essential for hydrocarbon exploration in subtle reservoirs. Enhancing seismic resolution remains a pivotal technical challenge in addressing this demand. Here, we present a...

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Main Authors: Shuai Chen, Yanwu Xu, Yue Yu, Jianxiang Feng, Sanyi Yuan
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/9/5125
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author Shuai Chen
Yanwu Xu
Yue Yu
Jianxiang Feng
Sanyi Yuan
author_facet Shuai Chen
Yanwu Xu
Yue Yu
Jianxiang Feng
Sanyi Yuan
author_sort Shuai Chen
collection DOAJ
description Accurate characterization of subsurface geological structures, particularly those obscured by strong coal-seam reflections, is essential for hydrocarbon exploration in subtle reservoirs. Enhancing seismic resolution remains a pivotal technical challenge in addressing this demand. Here, we present a multitrace reflectivity inversion method guided by geological sparsity principles. This method establishes quantitative relationships between sparse inversion operators and the spatial positions of stratigraphic boundaries. Specifically, by integrating prior geological knowledge, such as stratigraphic boundaries and stable sedimentary structures, as constraint operators within the sparsity matrix, this method results in a geologically interpretable and robust inversion framework. Subsequently, we validated this method through synthetic data and field applications in a carbonate fracture–cavity reservoir in the Ordos Basin of western China. The enhanced seismic resolution demonstrates that our method effectively restores shielded reservoir reflections beneath coal seams. Clearer than conventional sparse inversion techniques, the coherence attribute of the enhanced seismic resolution reveals distinct fracture–cavity geometries. Moreover, integrated analyses of well logs, fracture–cavity characterization, and drilling production data further confirm the accuracy and reliability of the inversion results. In conclusion, this method effectively leverages accurate geological structural information to enhance localized seismic resolution, thereby providing robust support for the exploration of subtle hydrocarbon reservoirs.
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spelling doaj-art-68bc73fb972a4f428af1184d38dba9aa2025-08-20T03:49:22ZengMDPI AGApplied Sciences2076-34172025-05-01159512510.3390/app15095125Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle ReservoirsShuai Chen0Yanwu Xu1Yue Yu2Jianxiang Feng3Sanyi Yuan4State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum, Beijing 102249, ChinaState Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum, Beijing 102249, ChinaState Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum, Beijing 102249, ChinaState Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum, Beijing 102249, ChinaState Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum, Beijing 102249, ChinaAccurate characterization of subsurface geological structures, particularly those obscured by strong coal-seam reflections, is essential for hydrocarbon exploration in subtle reservoirs. Enhancing seismic resolution remains a pivotal technical challenge in addressing this demand. Here, we present a multitrace reflectivity inversion method guided by geological sparsity principles. This method establishes quantitative relationships between sparse inversion operators and the spatial positions of stratigraphic boundaries. Specifically, by integrating prior geological knowledge, such as stratigraphic boundaries and stable sedimentary structures, as constraint operators within the sparsity matrix, this method results in a geologically interpretable and robust inversion framework. Subsequently, we validated this method through synthetic data and field applications in a carbonate fracture–cavity reservoir in the Ordos Basin of western China. The enhanced seismic resolution demonstrates that our method effectively restores shielded reservoir reflections beneath coal seams. Clearer than conventional sparse inversion techniques, the coherence attribute of the enhanced seismic resolution reveals distinct fracture–cavity geometries. Moreover, integrated analyses of well logs, fracture–cavity characterization, and drilling production data further confirm the accuracy and reliability of the inversion results. In conclusion, this method effectively leverages accurate geological structural information to enhance localized seismic resolution, thereby providing robust support for the exploration of subtle hydrocarbon reservoirs.https://www.mdpi.com/2076-3417/15/9/5125multitrace reflectivity inversionsparsitygeological-guidedhigh-resolution processingcoal-covered reservoirs
spellingShingle Shuai Chen
Yanwu Xu
Yue Yu
Jianxiang Feng
Sanyi Yuan
Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle Reservoirs
Applied Sciences
multitrace reflectivity inversion
sparsity
geological-guided
high-resolution processing
coal-covered reservoirs
title Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle Reservoirs
title_full Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle Reservoirs
title_fullStr Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle Reservoirs
title_full_unstemmed Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle Reservoirs
title_short Geologically Guided Sparse Multitrace Reflectivity Inversion for High-Resolution Characterization of Subtle Reservoirs
title_sort geologically guided sparse multitrace reflectivity inversion for high resolution characterization of subtle reservoirs
topic multitrace reflectivity inversion
sparsity
geological-guided
high-resolution processing
coal-covered reservoirs
url https://www.mdpi.com/2076-3417/15/9/5125
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AT yueyu geologicallyguidedsparsemultitracereflectivityinversionforhighresolutioncharacterizationofsubtlereservoirs
AT jianxiangfeng geologicallyguidedsparsemultitracereflectivityinversionforhighresolutioncharacterizationofsubtlereservoirs
AT sanyiyuan geologicallyguidedsparsemultitracereflectivityinversionforhighresolutioncharacterizationofsubtlereservoirs