Quantitative characterization method for pore structure of low-permeability reservoir based on multi-peak fitting of nuclear magnetic resonance T2 spectrum

The pore structure of low-permeability reservoirs is quantitatively characterized by the multi-peak fitting method of nuclear magnetic resonance T2 spectra, which solves the problems of unstable qualitative division and limited applicability of parameter methods in existing technologies, and realizes accurate analysis of pore structure and efficient prediction of permeability.

CN120629237AActive Publication Date: 2025-09-12CHINA UNIV OF PETROLEUM (EAST CHINA)
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Patent Information

Application Number
CN202510762089.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-09
Publication Date
2025-09-12
Estimated Expiration
2045-06-09

AI Technical Summary

Technical Problem

The existing technology for characterizing the pore structure of low permeability reservoirs has problems such as unstable reliance on empirical qualitative division, limited applicability of parameter methods, lack of physical interpretation of multi-peak fitting, and insufficient connection with permeability prediction.

Method used

The multi-peak fitting method based on the nuclear magnetic resonance T2 spectrum was used to preprocess the nuclear magnetic resonance T2 spectrum, and then decomposed by Gaussian multi-peak fitting and quantitatively characterized in combination with sub-peak parameters to correct the permeability prediction model.

Benefits of technology

It achieves accurate quantitative analysis of complex reservoir pore structures, improves the ability to distinguish pore types, enhances the interpretability of results, and improves the accuracy of permeability prediction.

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Abstract

The invention discloses a quantitative characterization method for a low-permeability reservoir pore structure based on nuclear magnetic resonance T2 spectrum multi-peak fitting, and relates to the technical field of reservoir pore structure characterization, the nuclear magnetic resonance T2 spectrum is preprocessed, and Gaussian multi-peak fitting decomposition is performed on the preprocessed data; according to the peak area, the peak center and the peak width of each sub-peak, carrying out quantitative characterization on the porosity contribution and the aperture range of the corresponding micropores, mesopores and macropores; the sub-peak parameters obtained through multi-peak fitting are introduced into the permeability prediction model, the model for predicting the permeability based on the NMR T2 relaxation data is corrected based on the multi-peak fitting result, the permeability model is constructed, the permeability is predicted more accurately, and the method has great significance in promoting reservoir prediction.
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