Porous rock physical modeling method and system for tight sandstone

By constructing matrix, skeleton and fluid models, combining multiple mathematical models and algorithms, the lack of consideration of mineral composition and pore types in dense sandstone rock physical modeling is solved, and higher precision reservoir prediction and favorable region identification are achieved.

CN119578205APending Publication Date: 2025-03-07CHINA RAILWAY FIRST SURVEY & DESIGN INST GRP
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Patent Information

Application Number
CN202411498211.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-25
Publication Date
2025-03-07

AI Technical Summary

Technical Problem

The prior art lacks considerations for mineral composition and pore types in the physical modeling of dense sandstone rocks, resulting in errors in parameter calculations and affecting the accuracy of the prediction results.

Method used

By constructing matrix, skeleton and fluid models, combining Gassmann equations, Voigt-Reuss model, simulated annealing algorithm and Batzle-Wang equations, the matrix, skeleton and fluid modulus of rocks are accurately calculated, and a petrophysical model of dense sandstone is constructed based on these moduluses.

Benefits of technology

It improves the accuracy of physical modeling of tight sandstone rocks, can more accurately predict the transverse wave velocity and fluid distribution of the reservoir, and improves the accuracy of identification of favorable reservoir areas.

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Abstract

The invention discloses a porous rock physical modeling method and a porous rock physical modeling system for tight sandstone, which realize accurate calculation of matrix, skeleton and fluid modulus in tight sandstone by combining an equivalent thought and applying a machine learning related algorithm, rock slice experimental analysis, pore simulation and other technologies so as to predict and verify a transverse wave curve. And determining the sensitive parameters of the reservoir fluid through the forms of rendezvous analysis and the like, predicting the distribution condition of the tight sandstone reservoir fluid, and realizing the identification of the favorable region of the reservoir.
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