Permeability up-scaling using Haar wavelets

TL;DR

This paper introduces a Haar wavelet-based block renormalization algorithm for permeability up-scaling in porous media flow, preserving heterogeneities while reducing computational costs in reservoir simulations.

Contribution

It presents a novel up-scaling method using Haar wavelets that maintains physical principles and provides accurate coarse-scale permeability estimates.

Findings

The method accurately approximates fine-scale pressure profiles.

It preserves heterogeneities across scales.

The approach simplifies permeability up-scaling in reservoir models.

Abstract

In the context of flow in porous media, up-scaling is the coarsening of a geological model and it is at the core of water resources research and reservoir simulation. An ideal up-scaling procedure preserves heterogeneities at different length-scales but reduces the computational costs required by dynamic simulations. A number of up-scaling procedures have been proposed. We present a block renormalization algorithm using Haar wavelets which provide a representation of data based on averages and fluctuations. In this work, absolute permeability will be discussed for single-phase incompressible creeping flow in the Darcy regime, leading to a finite difference diffusion type equation for pressure. By transforming the terms in the flow equation, given by Darcy's law, and assuming that the change in scale does not imply a change in governing physical principles, a new equation is obtained, identical in form to the original. Haar wavelets allow us to relate the pressures to their averages and apply the transformation to the entire equation, exploiting their orthonormal property, thus providing values for the coarse permeabilities. Focusing on the mean-field approximation leads to an up-scaling where the solution to the coarse scale problem well approximates the averaged fine scale pressure profile.