摘要
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 incorporatesWell-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.
基金
This researchwas funded by“CNPC Science and technology project:Fine evaluation and prediction technology for complex reservoirs in overseas natural gas reservoirs,grant number 2018D-4305”.
