Modeling Well Performance in Shale-Gas Reservoirs

Abstract The paper focuses on modeling well performance in shale-gas reservoirs using numerical simulation. Stimulation treatments in many shale-gas reservoirs create very complex fracture networks. These fracture networks are required to achieve economic production rates from rock with a matrix permeability of 1e-4 to 1e-5 md. The primary issues with modeling production from shale-gas reservoirs are accurately describing gas flow from the tight shale matrix into the fracture network, properly characterizing the matrix block size (or fracture density) and the conductivity of the network fractures, and evaluating the impacts of stress sensitive network fracture conductivity and gas desorption. This paper contrasts numerical reservoir simulation approaches using discrete modeling of the tight matrix and fracture network to that of dual porosity models. The paper illustrates that discretely gridding the network fractures is required to accurately model fluid flow in shale-gas reservoirs (with complex fracture networks) and show that dual porosity solutions do not adequately capture the transient flow in the very low permeability matrix blocks. The paper also illustrates the impact of gas desorption on the production profile and ultimate gas recovery in various shale reservoirs, showing that in some shale-gas reservoirs desorption may be a minor component of gas recovery. In addition, the paper details the impact of stress sensitive network fracture conductivity on well productivity. The reservoir simulations show that as closure stress increases in the fracture network, significant reductions in network fracture conductivity are likely, decreasing ultimate gas recovery. However, the effects of stress sensitive network fracture conductivity may not be evident in the initial well performance (1-2 years) and could lead to optimistic gas recovery forecasts. The paper presents selected examples from Barnett shale horizontal wells that incorporate microseismic fracture mapping and production data to illustrate the application of the production modeling to evaluate well performance in unconventional gas reservoirs.