Multi-Level and High-Resolution Fracture Modeling, Simulation and History Matching in Field-scale Reservoir Study

Carbonate formations are usually highly fractured. The fractures exist at all length scales ranging from microscopic fissures to kilometer-size structures. Consequently, it is vitally important to rigorously characterize the multi-scale fracture system and to accurately model the fluid flow in such highly fractured porous media. In this paper, we will present an integrated workflow for characterization of natural fracture system and accurate numerical modeling of fluid flow in fractured rocks. The fracture characterization usually involves the integration of multiple data sources including core analysis, image logs and seismic interpretations etc., at different scales. The fracture mappings are thus required to perform at different length scales and resolutions. In this study, we present a systematic approach that characterizes the actual fracture distribution with seismic and log interpretations. Firstly, the small-scale fractures are interpreted using image logs and seismic anisotropy analysis with a co-Kriging and stochastic modeling approach. The small-scale fractures are initially constructed in an explicit fashion, and are then incorporated in the matrix medium using a flow-based upscaling procedure. Secondly, the large-scale fractures are mapped out from post-stack seismic data with ant-tracking and maximum curvature analysis. The reservoir is then gridded into unstructured tetrahedral or prism meshes to fully resolve these large fractures. This discrete fracture model (DFM) is employed in a reservoir simulation study based on such grid system. We applied the procedure for simulation study and history match on a portion of a carbonate gas reservoir in Longwangmiao formation in Southwest China. Currently, there are 7 horizontal and 2 vertical wells in operation. Due to the connection of some large-scale fractures to edge water, early water breakthrough and drastic water invasion were observed. We partitioned the reservoir block into 0.6 million cells, in which 153 large-scale and thousands of small-scale fractures are fully resolved. The simulation study was performed and automated history match was successfully achieved using our extended Ensemble Karman Filter algorithm based on a parameterized description of the fractures that are explicitly represented in DFM. This proposed overall procedure is able to efficiently capture such extreme flow dynamics and achieve significantly better history match results.