Permeability up-scaling using Haar wavelets
V. Pancaldi, K. Christensen, P. R. King
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.
Create a lesson
Related papers
Long-time Dynamics of Many-body Open Quantum Systems using Quantum Generating Functions
Katha Ganguly, Dario Poletti, Bijay Kumar Agarwalla
Localization Delocalization Transition in Diffusion with Adaptive Resetting
Tommer D. Keidar, Shlomi Reuveni
Quenched activity induces nonuniversal scaling in nonreciprocal XY Models and surfaces
Sudip Mukherjee, Abhik Basu
Brownian yet non-Gaussian diffusion through equilibrium nonlinear friction
Jakob Mihatsch, Andreas M. Menzel
When dissipative steady states admit thermodynamic occupation laws
Tetsu Ichitsubo
Fluctuation--response relations from an emergent Z2 symmetry in the rotating stochastic Landau model
Dhruv Kush, Nicki Mullins, Mauricio Hippert et al.