A Sparse Bayesian Estimation Framework for Conditioning Prior Geologic Models to Nonlinear Flow Measurements.

Mon, 11/30/2009 - 16:01 — SomNambul

Authors: Lianlin Li, Behnam Jafarpour
Subjects: Numerical Analysis

link: http://arxiv.org/abs/0911.4961
Abstract

We present a Bayesian framework for reconstruction of subsurface hydraulic
properties from nonlinear dynamic flow data by imposing sparsity on the
distribution of the solution coefficients in a compression transform domain.

Primary-links

A Sparse Bayesian Estimation Framework for Conditioning Prior Geologic Models to Nonlinear Flow Measurements.

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