Petroleum Research (Feb 2022)

A new-generation Embedded Discrete Fracture Model calibration workflow applied to the characterization of complex naturally fracture reservoir

  • Hongbing Xie,
  • Mauricio Fiallos Torres,
  • Penyu Cheng,
  • Wei Yu,
  • Yuzhong Xin,
  • Jijun Miao,
  • Muwei Cheng

Journal volume & issue
Vol. 7, no. 1
pp. 1 – 12

Abstract

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Characterizing natural fractures has a decisive effect on production forecasts in fractured oil and gas reservoirs. Discrete Fracture Networks (DFN) constitutes the main modeling framework for fractured geosystems. However, myriads of uncertainties are enclosed prior modeling representative stochastic or deterministic DFN ensembles. This paper presents a novel methodology for DFN calibration and an efficacious field application, which incorporates Well-testing interpretation, Embedded Discrete Fracture Model (EDFM) framework, and numerical reservoir simulation. The proposed workflow starts with the DFN generation from seismic data, imaging logging data and core data. After multiple DFNs are modeled, well-test analysis is employed to calibrate the intrinsic properties of fractures at different locations. Then, these fracture networks are characterized dynamically by EDFM, which promotes capturing the optimal fracture model quickly screened. Finally, pressure and production history match are reached for the DFN realization that honors the optimal fracture model.

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