SPE 144355 Numerical Simulation of Shale-Gas Production: from Pore-Scale Modeling of Slip-Flow, Knudsen Diffusion, and Langmuir Desorption to Reservoir Modeling of Compressible Fluid

We combine a new pore-scale model with a reservoir simulation algorithm to predict gas production in gas-bearing shales. It includes an iterative verification method of surface mass balance to ensure real-time desorption-adsorption equilibrium with gas production. The pore-scale model quantifies macroscopic petrophysical properties of formations using an algorithm of gas transport in porous media that simultaneously considers the effects of no-slip and slip flow, Knudsen diffusion, and Langmuir desorption. Subsequently, the reservoir model populates petrophysical properties derived from the pore-scale analysis at every numerical grid and at each time-step to calculate the production history and pressure distribution in the reservoir. This approach examines the contribution of different transport processes (i.e. advective flow, Knudsen diffusion, and desorption) to quantify their corresponding contributions to overall flow. Previously, we showed that slip flow and Knudsen diffusion play a significant role in explaining the higher-than-expected permeability observed in shale-gas formations with pore-throat sizes in the range of nanometers. It is shown that Langmuir desorption from organic-matter surfaces is important in the calculation of stored gas in gas-bearing shales. Modeling results show that gas desorption maintains the reservoir pressure via the supply of gas. In comparison to conventional reservoir descriptions, the contributions of slip flow and Knudsen diffusion increase the apparent permeability of the reservoir while gas production takes place. The effects of both mechanisms explain the higher-than-expected gas production rates commonly observed in these formations. Introduction Fossil fuels are perhaps the most significant sources of fossil fuel currently available. Despite increasing environmental consciousness that aims to diversify energy sources to mitigate global climate change, fossil fuels will continue to supply the majority of energy consumption throughout this century. Natural gas is the cleanest fossil fuel, but as a finite source, more challenging reservoirs must be explored to meet the growing world demand (Ground Water Protection Council and ALL Consulting 2009). In this situation, gas-bearing shale strata are important energy resources in North America and they will become increasingly important all over the world. Nevertheless, gas production in these formations has remained mostly unpredictable, which has caused their categorization as unconventional gas reserves (Passey et al. 2010). Determining the petrophysical characteristics of a reservoir (e.g. permeability) and predicting production of gas-bearing shales is essential for economical assessments prior to field development. However, there is no standard model available to predict gas production from shale strata. Existing empirical and simplified models do not predict gas production accurately even though the production is usually higher than predictions made with conventional models (i.e. Darcy’s equation) (Lu et al. 1995; Javadpour et al. 2007; Gault and Stotts 2007; Javadpour 2009; Sondergeld, et al. 2010; Ambrose et al. 2010; Kale et al. 2010; Sondergeld, et al. 2010; Freeman et al. 2010; Shabro et al. 2011). Recently, pore-scale characterization of shale formations using Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM) and Atomic Force Microscopy (AFM) methods has advanced our understanding of shale morphologies and physical mechanisms behind gas production in these formations (Ambrose et al. 2010; Sondergeld et al. 2010; Javadpour 2009). At the same time, we have developed a pore-scale method to (1) analyze the imaged pore space; (2) characterize slip and no-slip flows, Knudsen diffusion and Langmuir desorption-adsorption; and (3) calculate apparent petrophysical properties (Shabro et al. 2009; Shabro et al. 2011). Apparent permeability depends on the smoothness of mineral grain surfaces, pressure, temperature, and gas molar mass as well as on pore-scale morphology. Gas and surface types, pressure, and temperature also control Langmuir desorption.