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Journal of Inverse and Ill-posed Problems

Editor-in-Chief: Kabanikhin, Sergey I.

6 Issues per year


Increased IMPACT FACTOR 2013: 0.593
Rank 143 out of 299 in category Mathematics in the 2013 Thomson Reuters Journal Citation Report/Science Edition

SCImago Journal Rank (SJR): 0.466
Source Normalized Impact per Paper (SNIP): 1.251

Mathematical Citation Quotient 2013: 0.51

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Imaging low sensitivity regions in petroleum reservoirs using topological perturbations and level sets

R. Villegas1 / O. Dorn2 / M. Kindelan3 / M. Moscoso4

11. Grupo de Modelización y Simulación Numérica, Universidad Carlos III de Madrid, Avenida de la Universidad 30, Leganes 28911, Spain.

2Email:

32. Grupo de Modelización y Simulación Numérica, Universidad Carlos III de Madrid, Avenida de la Universidad 30, Leganes 28911, Spain.

43. Grupo de Modelización y Simulación Numérica, Universidad Carlos III de Madrid, Avenida de la Universidad 30, Leganes 28911, Spain.

54. Grupo de Modelización y Simulación Numérica, Universidad Carlos III de Madrid, Avenida de la Universidad 30, Leganes 28911, Spain.

Citation Information: Journal of Inverse and Ill-posed Problems jiip. Volume 15, Issue 2, Pages 199–223, ISSN (Online) 1569-3953, ISSN (Print) 0928-0219, DOI: 10.1515/JIIP.2007.011, May 2007

Publication History

Published Online:
2007-05-25

We present a novel mathematical algorithm for the characterization of non-conventional reservoirs which contain regions of low sensitivity. Our algorithm uses a level set representation of shapes describing different lithofacies in the reservoir. These shapes need to be reconstructed from the production data using a two-phase flow model. In order to deal with regions of low sensitivity, topological perturbations are applied successively during the reconstruction in these low sensitivity regions, and the level set technique will evolve the so created shapes following a gradient direction that minimizes the mismatch between the computed and the production data. New shapes created at wrong locations tend to disappear gradually, whereas those created at locations where a lithofacie is present tend to grow until they approximately match the correct boundaries. We will discuss different strategies and present numerical results which demonstrate and compare their performances for two realistic 2D test cases.

Key Words: Image processing,; sensitivity regions,; topological perturbations,; level sets.

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