Monte Carlo methods in geophysical inverse problems

dc.contributor.authorSambridge, Malcolm
dc.contributor.authorMosegaard, Klaus
dc.date.accessioned2015-12-13T22:19:34Z
dc.date.available2015-12-13T22:19:34Z
dc.date.issued2002
dc.date.updated2015-12-11T07:48:48Z
dc.description.abstractMonte Carlo inversion techniques were first used by Earth scientists more than 30 years ago. Since that time they have been applied to a wide range of problems, from the inversion of free oscillation data for whole Earth seismic structure to studies at the meter-scale lengths encountered in exploration seismology. This paper traces the development and application of Monte Carlo methods for inverse problems in the Earth sciences and in particular geophysics. The major developments in theory and application are traced from the earliest work of the Russian school and the pioneering studies in the west by Press [1968] to modern importance sampling and ensemble inference methods. The paper is divided into two parts. The first is a literature review, and the second is a summary of Monte Carlo techniques that are currently popular in geophysics. These include simulated annealing, genetic algorithms, and other importance sampling approaches. The objective is to act as both an introduction for newcomers to the field and a comprehensive reference source for researchers already familiar with Monte Carlo inversion. It is our hope that the paper will serve as a timely summary of an expanding and versatile methodology and also encourage applications to new areas of the Earth sciences.
dc.identifier.issn8755-1209
dc.identifier.urihttp://hdl.handle.net/1885/71882
dc.publisherAmerican Geophysical Union
dc.sourceReviews of Geophysics
dc.subjectKeywords: algorithm; geophysics; inverse problem; Monte Carlo analysis; simulated annealing Monte Carlo nonlinear inversion numerical techniques
dc.titleMonte Carlo methods in geophysical inverse problems
dc.typeJournal article
local.bibliographicCitation.issue3
local.bibliographicCitation.startpagedoi:10.1029/2000RG000089
local.contributor.affiliationSambridge, Malcolm, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationMosegaard, Klaus, University of Copenhagen
local.contributor.authoremailu8414462@anu.edu.au
local.contributor.authoruidSambridge, Malcolm, u8414462
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor040499 - Geophysics not elsewhere classified
local.identifier.absfor010401 - Applied Statistics
local.identifier.ariespublicationMigratedxPub2931
local.identifier.citationvolume40
local.identifier.scopusID2-s2.0-0036765114
local.identifier.uidSubmittedByMigrated
local.type.statusPublished Version

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