A method for predicting reservoir probability based on oil and gas migration system evaluation

By comprehensively evaluating multiple parameters of the oil and gas transport system, the problem of low accuracy in predicting the probability of oil and gas accumulation in existing technologies has been solved, achieving more efficient prediction of accumulation probability and risk assessment, and ensuring the effectiveness of investment.

CN115907537BActive Publication Date: 2026-06-19CHINA PETROLEUM & CHEMICAL CORP +2
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINA PETROLEUM & CHEMICAL CORP
Filing Date
2022-11-22
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

Existing technologies lack quantitative or semi-quantitative evaluation methods for oil and gas transport systems that integrate multiple factors, resulting in low accuracy in predicting the probability of oil and gas accumulation and failing to reliably guarantee the effectiveness of investment.

Method used

By classifying and evaluating the intensity of fault activity and lateral migration capacity, and combining a comprehensive assessment of vertical and lateral migration efficiency, a method for predicting the probability of hydrocarbon accumulation in hydrocarbon transport systems is established. Multi-parameter comprehensive evaluation and Monte Carlo algorithm are used to predict the probability of hydrocarbon accumulation.

Benefits of technology

This improved the accuracy of hydrocarbon accumulation probability prediction, enhanced the reliability of pre-drilling risk prediction, and ensured the effectiveness of investment.

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Abstract

This invention provides a method for predicting hydrocarbon accumulation probability based on the evaluation of an oil and gas transport system, comprising the following steps: 1) classifying and evaluating the vertical migration capacity within the transport system; 2) classifying and evaluating the lateral migration capacity within the transport system; 3) comprehensively evaluating the oil and gas transport efficiency based on the evaluation of vertical and lateral migration capacity; and 4) predicting the hydrocarbon accumulation probability (Pg). This application establishes a hydrocarbon accumulation probability prediction model after a comprehensive normalized classification and semi-quantitative evaluation of transport parameters. It integrates data from different dimensions, conducts multi-parameter comprehensive evaluation, optimizes the controlling factors through multivariate clustering and factor analysis to reduce dimensionality, and scores the relevant conditions of the target area after determining the dominant conditions. Furthermore, it visualizes the hydrocarbon accumulation probability prediction results through gridding. This application can significantly improve the reliability of the evaluation results, which is beneficial for early risk prediction and thus ensures the effectiveness of investment.
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