State Key Lab of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, China
School of Oil & Natural Gas Engineering, Southwest Petroleum University, Chengdu, China
A simplified pore network model divided pore structure into cube lattices was developed base on the digital core extracted from micro computerized tomography (μ-CT) in this study. It rolled the complex topology and connectivity of pore structure into adjacent cubes. The static property of each cube was determined by the statistic CT data. The connectivity of adjacent cubes and flow regime were determined by the capillary pressure difference which is a function of tunnel size, interfacial tension, wet contact angle, and external pressure gradient. In this simplified pore network model, the flow capacity properties are determined by number and size distribution, mobile tunnels, and fluid viscosity. The flow velocity and sweep efficiency are non liner as mobile tunnels increase nonlinearly with increasing driving force before all tunnels start flowing. The critical pressure gradient that changes the non liner flow to liner flow was performed as the threshold pressure gradient. The dynamic mobile performance of oil in place (OIP) is determined by the number of mobile tunnels and their diameter distribution for different pressure gradient. The relationship of microscopic sweep efficiency, water cut and pressure gradient to oil recovery can be quantified by flow simulation in this pore network model.