Analysis of the Main Controlling Factors of Differential Enrichment in Terrestrial Strongly Heterogeneous Reservoirs

By analyzing the TOC, clay, silicate, and carbonate mineral content of core samples from terrestrial strongly heterogeneous reservoirs, and performing clustering and lithofacies classification, the accuracy problem of reservoir enrichment control factor analysis was solved, and a more accurate evaluation of control factors was achieved.

CN120910457BActive Publication Date: 2026-07-17DAQING OILFIELD CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
DAQING OILFIELD CO LTD
Filing Date
2025-07-31
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies have poor accuracy in analyzing the main controlling factors of reservoir enrichment in terrestrial strongly heterogeneous reservoirs. Manual analysis methods are affected by subjective human factors, resulting in insufficient objectivity in the evaluation.

Method used

By obtaining the TOC content, clay content, silicate mineral content, and carbonate mineral content of core samples, a target vector is constructed. Clustering and lithofacies classification are then performed. Combined with carbon grade markers and depth values, the differences in the main controlling factors inside and outside the lithofacies are analyzed, and the main controlling factors are screened out.

Benefits of technology

It improves the accuracy of reservoir enrichment control factor analysis, realizes systematic and full-scale characterization of lithofacies characteristics, comprehensively considers multiple influencing factors, and quantifies the evaluation of control factors.

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Abstract

This invention relates to the field of factor analysis technology, specifically to a method for analyzing the main controlling factors of differential enrichment in continental strongly heterogeneous reservoirs. The method includes: acquiring the TOC content, clay content, silicate mineral content, and carbonate mineral content of core samples at different depths within the area to be tested, constructing a target vector for each core sample; clustering, sorting, and labeling the target vectors with carbon levels; classifying the target clusters into lithofacies; acquiring the data values ​​of the core samples corresponding to each target vector under each preset influencing factor, and analyzing the possible main controlling factors within and between lithofacies for each target cluster under each preset influencing factor; and selecting the target main controlling factors corresponding to each lithofacies category based on the main control evaluation values ​​of each lithofacies category for all preset influencing factors. This invention realizes the analysis of main controlling factors of reservoir enrichment and improves the accuracy of such analysis.
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