Abstract
In this study, we established a more efficient approach for fractured shale reservoir modeling with an emphasis on simplifying and automating the workflow for assisted history matching and uncertainty quantification. The improvement is especially notable for the process of history matching since the fracture geometry and properties can be directly set as parameters to be history matched. The resultant approach not only shows a significant reduction in the computational time while maintaining model accuracy, but also provides an automatic method for modifying the fracture related parameters - a laborious process in the traditional workflow.
In the forward reservoir model, we implemented and extended the Embedded Discrete Fracture Model (Embedded DFM) approach for fractures with arbitrary strike and dip angle to a multiple porosity/permeability setting. The fractures are naturally discretized by the boundary of parent matrix grid blocks. Control volumes of fracture segments are generated according to the specific geometry of each of the segments. Three types of non-neighbor connections are then generated, namely the connection between the fracture segment and its parent matrix grid blocks, the connection between two intersecting fracture segments from different fractures, and the connection between two neighbor fracture segments from the same fracture. For each of the non-neighbor connections, transmissibility can be calculated honoring the physics of the flow.
In our approach with Embedded Discrete Fracture Multiple-Porosity Model, the matrix is sub-divided into three porosity types, namely organic matrix (kerogen), inorganic matrix and natural fractures, with the necessary physics included for each of the porosity types. The macro fractures are explicitly represented with Embedded DFM. The proposed model provides a coherent method for characterizing the organic matrix, inorganic matrix, micro fractures as well as the hydraulic fractures of shale reservoirs. It offers a computationally efficient approach for modeling the severe heterogeneity due to hydraulic and natural fractures. Compared with traditional discrete fracture models, fewer grid blocks and lower levels of refinement are required. Compared with multiple porosity method, the proposed model has desirable accuracy for the simulation of reservoirs with large scale fractures.
In the history matching and uncertainty quantification stage, due to the low efficiency of traditional Markov Chain Monte Carlo (MCMC) method when applied to reservoir history matching, a more advanced algorithm of two-stage MCMC is employed to evaluate the uncertainty for all the parameters. Since no upscaling of the fracture related parameters is required, the reservoir model can be generated by a pre-processor based on the proposed parameter, which maintains the adequacy of a Gaussian distribution assumption. Therefore, the workflow can be completely automated. By incorporating Embedded DFM and multiple porosity/permeability approaches, the improved model facilitates the history matching of fractured shale reservoirs by cutting the total amount of grid blocks, reducing the complexity of the gridding process, as well as improving the accuracy of fluid transportation within and among different porosity types.