Iglesias, Marco and Dawson, Clint (2009) An iterative representer-based scheme for data inversion in reservoir modeling. Inverse Problems, Vol.25 (No.3). Article no. 035006. doi:10.1088/0266-5611/25/3/035006

Research output not available from this repository, contact author.

Request Changes to record.

Abstract

In this paper, we develop a mathematical framework for data inversion in reservoir models. A general formulation is presented for the identification of uncertain parameters in an abstract reservoir model described by a set of nonlinear equations. Given a finite number of measurements of the state and prior knowledge of the uncertain parameters, an iterative representer-based scheme (IRBS) is proposed to find improved parameters. In this approach, the representer method is used to solve a linear data assimilation problem at each iteration of the algorithm. We apply the theory of iterative regularization to establish conditions for which the IRBS will converge to a stable approximation of a solution to the parameter identification problem. These theoretical results are applied to the identification of the second-order coefficient of a forward model described by a parabolic boundary value problem. Numerical results are presented to show the capabilities of the IRBS for the reconstruction of hydraulic conductivity from the steady-state of groundwater flow, as well as the absolute permeability in the single-phase Darcy flow through porous media.

Item Type:	Journal Article
Divisions:	Faculty of Science > Mathematics
Journal or Publication Title:	Inverse Problems
Publisher:	Institute of Physics Publishing Ltd.
ISSN:	0266-5611
Official Date:	2009
Dates:	Date Event 2009 Published
Volume:	Vol.25
Number:	No.3
Page Range:	Article no. 035006
DOI:	10.1088/0266-5611/25/3/035006
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access

Request changes or add full text files to a record

Repository staff actions (login required)

View Item