Abstract

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 190113, “Advanced Analysis of Cleanup and Productivity From Perforated Rocks Using Computational Fluid Dynamics,” by Rajani Satti, SPE, Stephen N. Zuklic, and Derek Bale, SPE, Baker Hughes, a GE company, and Nils Koliha, Andrew Fager, SPE, Gana Balasubramanian, Bernd Crouse, SPE, and David Freed, SPE, EXA, prepared for the 2018 SPE Western Regional Meeting, Garden Grove, California, USA, 22–27 April. The paper has not been peer reviewed. Because of inherent complexities, understanding the characteristics of perforations in downhole environments is a significant challenge. Perforation-flow laboratories have been used to provide insight into cleanup and productivity mechanisms around perforation tunnels. In contrast to previous studies, the model presented in this work uses the perforation-flow laboratory, micro-computed-tomography (CT) and conventional CT imaging, and, most importantly, an advanced simulation approach to provide an accurate assessment of cleanup techniques and productivity. This full-scale 3D flow model accounts for realistic aspects of tunnel geometry, perforation damage, and blockages that impede flow. Introduction In recent years, numerical tools increasingly have been used in conjunction with experiments to provide better insight into the flow characteristics of perforated cores and perforated well-scale formations. Several numerical studies on perforation fluid flow have been conducted for core scale. However, comprehensive details relating to the modeling of perforation-zone damage and thickness, flow directionality, debris mechanisms, and implications for cleanup have not been studied in detail. In addition, most computational fluid dynamics (CFD) studies have used traditional Navier-Stokes-based solvers. In this study, the authors have used a commercially available flow-simulation software based on the lattice Boltzmann method (LBM) to calculate the complex flow and cleanup mechanisms around the perforation tunnel. Lattice-based methods, an alternative to traditional CFD methods, track the advection and collisions of fluid particles on a computational grid. Because the average number of particles per grid cell far exceeds the computing power required to track them individually, the particles are grouped into an integer number of discrete velocities. LBM has been well validated and is in common use for many flow applications. The flow solver used here includes a turbulence model that is similar conceptually to the large-eddy simulation approach. The flow solver also includes a porous-media model that is used, in this study, to model the rock. The porous-media model invokes a Darcy-type pressure loss by applying a flow resistance determined from the known permeability of the rock. The resistance can include a viscous (linear) and an inertial (quadratic) term with respect to local velocity and can be made to vary spatially to model rock heterogeneity.

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