Numerical Simulation Based on Microseismic Discrete Fractures and Automatic History Matching

doi:10.3969/j.issn.1006-6535.2021.03.009

Abstract

Abstract: In view of the detailed description of complex fracture network, complex characterization, cumbersome history matching of numerical simulation, and strong uncertainty, which make it difficult to achieve accurate numerical simulation of unconventional reservoirs, a comprehensive numerical simulation technology was developed by three means: microseismic complex seam network inversion, detailed description of discrete fracture network and ensemble Kalman filter (EnKF) to realize accurate numerical simulation of unconventional reservoirs under complex fracture network conditions. The results showed that the difference between the results respectively obtained by the complex fracture network inversion method in the paper and the direct interpretation was small, with an error of 2% to 6%, but the method presented in this paper could directly reflect the distribution and propagation of underground artificial fractures; the unstructured network based on artificial fracture network could be used to characterize the flow in fractures in detail; the automatic history matching technology based on EnKF could reduce artificial matching errors and improve matching efficiency. Field tests show that the average matching rate between the matched daily oil production and the actual production of 28 single wells in the study area was as high as 91%, realizing accurate simulation of the complex seepage field in oil and gas reservoirs. This study can provide a reference for the production prediction of complex fracture network of unconventional reservoir.

Key words: numerical simulation, microseismic, fracture network, discrete fracture, large-scale hydraulic fracturing, automatic history matching

CLC Number:

TE357

Qu Xuefeng, Xie Qichao, Lan Zhengkai, Zhao Guoxi. Numerical Simulation Based on Microseismic Discrete Fractures and Automatic History Matching[J]. Special Oil & Gas Reservoirs, 2021, 28(3): 62-68.

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