History Matching with Geostatistical Prior: A Smooth Formulation

Yulia Melnikova, Katrine Lange, Andrea Zunino, Knud Skou Cordua, Klaus Mosegaard

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

We present a new method for solving the history matching problem by gradient-based optimization within a probabilistic framework. The focus is on minimizing the number of forward simulations and conserving geological realism of the solutions. Geological a priori information is taken into account by means of multipoint statistics borrowed from training images. Then production data and prior information are integrated into a single differentiable objective function, minimizer of which has a high posterior value. Solving the proposed optimization problem for an ensemble of different starting models, we obtain a set of solutions honouring both data and prior information.
Original languageEnglish
Title of host publicationMathematics of Planet Earth
PublisherSpringer
Publication date2014
Pages703-707
ISBN (Print)978-3-642-32407-9
ISBN (Electronic)978-3-642-32408-6
DOIs
Publication statusPublished - 2014
Event15th Annual Conference of the International Association for Mathematical Geosciences: Frontiers of Mathematical Geosciences: New approaches to understand the natural World - Faculty of Mathematics of the Complutense University of Madrid, Madrid, Spain
Duration: 2 Sep 20136 Sep 2013
Conference number: 15
http://www.igme.es/internet/iamg2013/

Conference

Conference15th Annual Conference of the International Association for Mathematical Geosciences
Number15
LocationFaculty of Mathematics of the Complutense University of Madrid
Country/TerritorySpain
CityMadrid
Period02/09/201306/09/2013
Internet address
SeriesLecture Notes in Earth Sciences
ISSN0930-0317

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