Pressure Transient Analysis in Fractured Horizontal Wells with Fracture Networks

Abstract

Drilling fractured horizontal well is now a common practice to improve the productivity of unconventional wells. With the reactivated natural fractures, the technique of fractured horizontal wells can generate a large amount of complex fracture networks of hydraulic fractures (HF) and micro fractures (MF) in unconventional reservoirs. In this paper, an efficient semi-analytical model is developed for pressure transient analysis in horizontal wells by considering hydraulic fracture networks as well as natural fracture networks. During the model development, we develop the diffusivity equation for fluid flow in formation matrix using line source function. With the nodal analysis technique, the flow interplay at fracture intersections is eliminated and the diffusivity equations for fluid flow in hydraulic fractures are built. The pressure transient solution of these diffusivity equations is obtained by using Laplace transforms and Stehfest numerical inversion (Stehfest, 1970). The results show that different from a single "dip"––the classical dual-porosity feature of naturally fractured reservoirs ––in the pressure derivative, the reservoir system exhibits many other different pressure behaviors like "fluid feed", "pseudo-boundary dominated flow", etc. All these pressure behaviors are associated with the properties and geometries of natural/hydraulic fractures. What's more, the pressure response for fracture network horizontal wells with natural fracture networks can be divided into some flow regimes, which include: (1) the first bilinear flow, (2) "MF-HF" support, (3) the second bilinear flow, (4) formation linear flow, (5) cross flow, and (6) pseudo-radial flow. Model reliability is demonstrated by a numerical verification. The efficient semi-analytical model in this work can substantially reduce the computational burdens of numerical simulators for transient pressure analysis in shale reservoirs with hydraulic and/or natural fracture networks.