New formulation of the objective function for better incorporation of 4D seismic data into reservoir : Models and image registration based on nonlinear elasticity
type: Dataset
contact point: Organization
  fn: CCSD
keyword: augmented-lagrangian-method
keyword: ciarlet-geymonat-materials
keyword: saint-venant-kirchoff-materials
keyword: theses
keyword: elasticite-non-lineaire
keyword: infoeu-reposemanticsdoctoralthesis
keyword: non-linear-elasticity
keyword: materiau-de-type-saint-venant-kirchoff
keyword: calculus-of-variation
keyword: materiau-de-type-ciarlet-geymonat
keyword: methode-du-lagrangien-augmente
keyword: calcul-de-variations
keyword: infoinfo-ticomputer-science-csimage-processing-eessiv
landing page: https://theses.hal.science/tel-00924825
description: In a first part, we propose an innovative methodology for image matching in the context of reservoir simulation. In order to build a model consistent with data collected on the field, we need to evaluate the error between seismic cubes obtained by simulation and seismic cubes acquired in the oil field. Using image processing tools, we develop a new formulation of the error. The application of this new formulation on synthetic reservoir cases demonstrates its efficiency. In a second part, we address the issue of designing two theoretically well-motivated registration models capable of handling large deformations since they are based on nonlinear elasticity. The shape to be matched are viewed as Ciarlet-Geymonat materials for the first model and as Saint-Venant Kirchhoff materials for the second one. We investigate the efficiency of the proposed matching model for the registration of mouse brain gene expression data to a neuroanatomical mouse atlas.
identifier: NNT: 2013ISAM0024
issued: 2026-05-07T15:07:09.563145
language: fr
modified: 2026-05-07T15:07:09.563149

test_moissonnage_selune
type: Agent

New formulation of the objective function for better incorporation of 4D seismic data into reservoir : Models and image registration based on nonlinear elasticity
type: Distribution
access URL: https://theses.hal.science/tel-00924825
format: HTML
issued: 2026-05-07T15:07:09.564838
modified: 2026-05-07T15:07:09.547742