Simulation of Linear Displacement Experiments on Massively Parallel Computers

Abstract

TX 75083-3836, U.S.A. fax 01-214-952-9435. AbstractWe have developed a throat-bulb network model to simulate multiphase flow experiments. The model has been efficiently implemented on massively parallel computers (MasPar and eM5). This model has allowed us to study the dynamics of displacement processes. Using grids of size 64 x 64 x 128 (half a million cells), we are able to incorporate random variations in the throat and pore size distributions and observe flow patterns such as viscous fingering, stable front displacement, and invasion percolation. Furthermore, we are able to discern certain scaling rules in terms of macroscale variables.Displacement processes in a network model with random distribution of throat and pore size can be characterized by three parameters: M (viscosity ratio), Ca (capillary number), and Cg (the ratio of capillary number and Bond number). Macroscale variables, f{ rand Sor, are strongly dependent on flow patterns, whereas the dynamic capillary pressure, Pc, is independent of flow patterns.Analysis oflaboratory measurements of these macroscopic variables is generally based on steady state approximations and moreover, it offers no clue as to how one might extrapolate the results to the reservoir scale. Using the pore network simulator, we can model dynamic flow behavior and understand the scaling rules for experimental measurements. The simulator will eventually become a practical tool to investigate multi-phase flow in various flow conditions. Furthermore, a better understanding of experimental measurements will help us construct effective grid-block properties for reservoir simulation.

A dual-tube model for gas dynamics in fractured nanoporous shale formations

“…Pore networks of different complexity (figure 3) have been extensively and successfully used to model fluid flow in porous media (Fatt 1956;Koplik 1982;Blunt & King 1990;Lee, Padmanabhan & Al-Sunaidi 1996). The simplest model comprises a bundle of tubes (figure 3) and despite its simplicity has proven able to predict macroscopic parameters (Fatt 1956).…”

“…Throat-bulb models (figure 3b) represent an evolution of the bundle-of-tubes model (BTM) and have been employed to analyse multiphase flow in porous media (e.g. Lee et al 1996).…”

A Statistical Dual-Tube Model to Analyze Gas Production from Shale Formations

“…However, gas transport in the undisturbed shale matrix can be modeled by means of pore networks, which can be constructed from geometrical information about the pore-scale structure (as it can be obtained, for instance, from X-ray Computed Tomography (e.g., Walls and Sinclair 2011)). Pore networks of different complexity have been extensively and successfully employed to model fluid flow in porous media (Blunt and King 1990;Blunt et al 2012;Fatt 1956;Koplik 1982;Lee et al 1996). Ultimately, the level of complexity of the network model to be employed depends on the complexity of the physical phenomena to be analyzed.…”

Uncertainty Assessment of Production Performance for Shale-Gas Reservoirs

“…Pore network models are used to model fluid flow in porous media (Fatt, 1956;Koplik, 1982;Blunt and King, 1990;Lee et al, 1996). With different pore length scales; these approaches can be directly applied to model flow in micro-/nano-pores in shale formations.…”

“…Even with this simplest pore geometry, the model could predict macroscopic parameters (Fatt, 1956). Later the Throat-Bulb model was employed to analyze multi-phase flow in porous media (Lee et al, 1996), and more recently a complex randomly connected network is widely used in the literature (Blunt et al, 2012 andDong, 2007). As the model complexity increases, the computational cost increases.…”