Probabilistic history matching of multi-scale fractured reservoirs: Integration of a novel localization scheme based on rate transient analysis

Abstract

In this paper, a new assisted history-matching workflow is presented, where rate transient analysis (RTA) results are used to constrain not only the initial discrete fracture network (DFN) models, the interpreted flow regimes are also used to formulate a localization scheme for more efficient updating of the pertinent DFN model parameters. The outcome is an ensemble of DFN realizations that are calibrated to both geologic and dynamic production data.RTA interpretations and other pertinent geological data are used to infer the prior probability distributions of the unknown fracture parameters, from which an ensemble of initial DFN models is sampled. The DFN models are subjected to numerical multiphase flow simulation. The fracture parameters are adjusted following an indicator-based probability perturbation method, which is capable of minimizing the objective function and reducing the uncertainties in the unknown fracture parameters simultaneously. A key feature is that the flow regimes identified from RTA are used to formulate a localization strategy, where individual segments of the production data are used to tune only a specified subset of the unknown model parameters.In a case study, the method is applied to characterize the probability distributions of four parameters in a multifractured shale gas well: primary fracture transmissivity, aperture of the secondary fracture, transmissivity of the secondary induced fracture, and global fracture intensity. Their probability distributions are updated following the proposed approach to match the production history. Multiple realizations of the DFN model are sampled.A key novelty is that the proposed probabilistic approach facilitates the representation of uncertainties in fracture parameters via multiple equally-probable DFN models and their corresponding upscaled flow-simulation models. A more comprehensive and robust approach is presented for integrating specific RTA interpretations and estimations into various steps of the history-matching process.