High Fidelity Simulation of Recovery Mechanisms in Complex Natural Fracture Systems

Abstract

Due to numerical difficulties in conducting high fidelity simulation of recovery mechanisms in complex natural fracture systems, there are no published studies that address the impact of preserving details of the fracture networks. We used highly refined grids to conduct fine scale simulations of various recovery mechanisms in different complex fracture settings and compared the results to those obtained on simplified dual porosity dual permeability (DPDK) representations created by applying a consistent upscaling procedure. Our study considers densely connected, sparsely connected, and isolated fracture networks that are extracted from a field-scale fractured carbonate reservoir model. Discrete fracture-matrix (DFM) models were constructed using an unstructured grid with refinement of the matrix rock near fractures. High-resolution simulations of spontaneous imbibition, gravity drainage, and viscous displacement recovery mechanisms were conducted on these DFM models. We also built equivalent DPDK models by using single phase flow-based upscaling and actual fracture geometry and distribution. The recovery mechanisms were simulated on these DPDK models and compared to high-resolution DFM models. The fine scale simulations revealed that lateral viscous displacement recovery depends on the details of the fracture networks and can be significantly higher than those predicted from equivalent DPDK models. The DPDK models all predict the same recovery. For spontaneous imbibition, both fine scale and equivalent DPDK models show dependence on fracture geometry, but the DPDK models predict much higher rates. Fine scale and equivalent DPDK models agree reasonably for gravity drainage. These findings are explained by analyzing the matrix-fracture flows, and implications on efforts to improve shape factors in DPDK models and upscaling efforts in DFM models are discussed.

Embedded Discrete Fracture Models

“…The first and third fractures are vertical, whereas the second fracture is inclined. Once the setup in Listing 9.1 has been executed, the following code produces the plot in Figure 9.1a: plotfracongrid(G,fracplanes); view (30,45); axis equal tight Now that the matrix grid and fracture database have been created, the fracture grid can be constructed. This is usually done by passing these two objects to the EDFMgrid function:…”

“…The green fracture is inclined relative to the vertical axis and, as a result, has an unstructured grid pattern. The figure can be generated as follows: colors = ['r','g','y']; for i = 1:3 plotGrid(Fgrid(i).grid,'FaceColor',colors(i)); end axis equal tight; view (30,45); xlim([0 physdim(1)]); ylim([0 physdim(2)]); Figure 9.1c shows the intersected matrix grids and can be generated as follows:…”

“…%% PLOT DFN colourchoice=['r','g','y']; figure; hold on; plotGrid(cartGrid([1 1 1],physdim),'facealpha',0); axis equal tight view (45,30); for i=1:3 index = find(vertcat(fracplanes.SetID)==i); C = colourchoice(i); for j=index' X = fracplanes(j).points(:,1); Y = fracplanes(j).points(:,2); Z = fracplanes(j).points(:,3); fill3(X,Y,Z,C); end xlabel('x','Interpreter','latex') ylabel('y','Interpreter','latex') zlabel('z','Interpreter','latex') end…”

“…Hardebol et al [17] used DFM simulations to study the impact of fracture network characterization on fluid flow. Vo et al [45] compared DFM and dual-permeability models and identified a range of deficiencies in terms of the dual-permeability method's ability to account for viscous displacement and spontaneous imbibition. Hui et al [18] used a DFM method to simulate waterflooding in a full-field model in which the fracture network is simplified via a method known as edge collapse.…”

Effect of Cross-Well Natural Fractures and Fracture Network on Production History Match and Well Location Optimization in an Ultra-Deep Gas Reservoir

“…The traditional dual porosity dual permeability (DPDK) method, despite its widespread application for reservoir simulation and history matching [11][12][13], struggles with explicit single fracture modeling and tends to overestimate natural fracture connectivity [14][15][16][17][18]. Such methods inaccurately assume disconnected fractures to be connected networks [5,19].…”