Abstract

Fracture networks are critical in controlling subsurface fluid flow, significantly influencing hydrocarbon recovery, groundwater movement, and geothermal energy extraction. Understanding and accurate fracture network modeling is crucial for predicting subsurface fluid behavior. Multiple-Point Geostatistics (MPS) effectively captures complex spatial patterns from outcrop data and serves as a more accurate alternative to traditional methods that oversimplify fracture connectivity. This study uses the CCSIM algorithm to generate stochastic fracture network realizations from outcrop-based training images. Two different strategies are proposed for finding the method that best captures the heterogeneity of the pattern studied. Realizations generated using both strategies are further evaluated using response curves and MDS plots.