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An Implementation of the Frequency Matching Method

  • Katrine Lange
  • , Jan Frydendall
  • , Thomas Mejer Hansen
  • , Andrea Zunino
  • , Klaus Mosegaard

Research output: Book/ReportReportResearch

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Abstract

During the last decade multiple-point statistics has become in-creasingly popular as a tool for incorporating complex prior infor-mation when solving inverse problems in geosciences. A variety of methods have been proposed but often the implementation of these is not straightforward. One of these methods is the recently proposed Frequency Matching method to compute the maximum a posteriori model of an inverse problem where multiple-point statistics, learned from a training image, is used to formulate a closed form expression for an a priori probability density function. This paper discusses aspects of the implementation of the Fre-quency Matching method and the techniques adopted to make it com-putationally feasible also for large-scale inverse problems. The source code is publicly available at GitHub and this paper also provides an example of how to apply the Frequency Matching method to a linear inverse problem.
Original languageEnglish
Place of PublicationKgs. Lyngby
PublisherTechnical University of Denmark
Number of pages45
Publication statusPublished - 2013
SeriesDTU Compute Technical Report-2013
Number09
ISSN1601-2321

Keywords

  • Multiple-points statistics
  • Training image
  • A priori in- formation
  • Maximum a posteriori model

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