Inversion representation method of fracturing fracture network

Abstract

The invention relates to an inversion technology of fracture network, in particular to an inversion representation method for fracture network calibration and attribute after staged fracturing or volume fracturing. The inversion representation method includes the steps of 1), reading and entering main data and auxiliary data: (1), reading fracturing monitoring micro-seismic signals; (2), reading oil well yield data, fracturing construction parameters and reservoir information; 2), based on a fractal geometry system and combining with an integer programming method, generating fractal fracture network capable of satisfactorily matching with the micro-seismic signals in geometrical morphology; 3), performing quality check on the generated fractal fracture network on the basis of engineering parameters and construction parameters or a normal analysis method and adjusting fractal parameters controlling the geometrical morphology of fractures; 4), performing history matching on the basis of the yield data and combining a modified genetic algorithm and calibrating attributes of the fracture network by degrees. The inversion representation method is widely applicable to fracture network representation after hydraulic fracturing of oil wells.

Description

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AI Technical Summary

Benefits of technology

This technology allows for accurate prediction of faulty cables during hydrofractures without relying solely upon previous models or assumptions about them. It uses multiple levels of complexity that are determined from data collected over time. By combining these techniques together it provides more precise results than existing approaches alone.

Problems solved by technology

This patented technical problem addressed by this patents relates to evaluating the structure or characteristics (fissured networks) within an underground hydrocarbon reservoir caused by hydrauled drilling techniques that are being developed today. Current methods have limitations with regard to accurately representing these structures due to their complexity and lack of ability to provide detailed analysis on them.

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