A method for tight sand sweet spot reservoir prediction based on seismic sedimentology

By using a seismic sedimentology-based approach, combined with well logging curve processing and seismic data analysis, a geological model was established, solving the problems of high accuracy and low cost in predicting tight sandstone reservoirs and achieving efficient prediction of sweet spots in tight sandstone.

CN122172310APending Publication Date: 2026-06-09CHINA PETROLEUM & CHEMICAL CORP +1
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Patent Information

Application Number
CN202411787293.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-06
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

Existing technologies struggle to predict tight sandstone reservoirs with high accuracy and low cost, especially tight sandstone sweet spots. Seismic analysis suffers from multiple solutions, and acquiring and processing detailed seismic data is costly.

Method used

A geological model was established using a seismic sedimentology-based approach, combined with well logging curve processing, well-seismic calibration, seismic data resolution enhancement, and elastic and physical property parameter inversion, to predict reservoir formation.

Benefits of technology

It improves the accuracy and precision of predicting sweet spot reservoirs in tight sandstone, and enhances the efficiency and economic benefits of data processing and exploration and development.

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Abstract

The application discloses a tight sandstone dessert reservoir prediction method based on seismic sedimentology, and relates to the technical field of reservoir prediction in oil exploration. The tight sandstone dessert reservoir prediction method based on seismic sedimentology comprises the following steps: pre-processing well logging data; drawing a seismic-geological interpretation profile graph; obtaining a structure graph; obtaining a fine layer velocity model; performing well logging curve standardization processing; performing forward simulation; performing reservoir inversion; extracting attributes; and comprehensively performing reservoir prediction according to the attributes and the inversion. The method improves the accuracy and precision of reservoir prediction, and improves the efficiency and economic benefits of data processing and exploration and development.
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Citation Information

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