A Monte Carlo method to quantify uncertainty in the inversion of zero‐offset VSP data

Abstract

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2000A Monte Carlo method to quantify uncertainty in the inversion of zero‐offset VSP dataAuthors: Alberto MalinvernoScott LeaneyAlberto MalinvernoSchlumberger‐Doll Research, Ridgefield, CT and Scott LeaneySchlumberger House, Gatwick, UKhttps://doi.org/10.1190/1.1815943 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1815943FiguresReferencesRelatedDetailsCited ByTrans-dimensional gravity and magnetic joint inversion for 3-D earth models25 February 2022 | Geophysical Journal International, Vol. 230, No. 1Transdimensional simultaneous inversion of velocity structure and event locations in downhole microseismic monitoringXingda Jiang, Wei Zhang, Hui Yang, Chaofeng Zhao, and Zixuan Wang18 November 2021 | GEOPHYSICS, Vol. 87, No. 1Bayesian Geophysical Inversion Using Invertible Neural Networks10 July 2021 | Journal of Geophysical Research: Solid Earth, Vol. 126, No. 7An introduction to variational inference in geophysical inverse problemsImaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion9 May 2020 | Geophysical Journal International, Vol. 222, No. 3Seismic Tomography Using Variational Inference Methods7 April 2020 | Journal of Geophysical Research: Solid Earth, Vol. 125, No. 41‐D, 2‐D, and 3‐D Monte Carlo Ambient Noise Tomography Using a Dense Passive Seismic Array Installed on the North Sea Seabed15 February 2020 | Journal of Geophysical Research: Solid Earth, Vol. 125, No. 2Bayesian transdimensional seismic full-waveform inversion with a dipping layer parameterizationGerhard Visser, Peng Guo, and Erdinc Saygin9 October 2019 | GEOPHYSICS, Vol. 84, No. 63-D Monte Carlo surface wave tomography4 September 2018 | Geophysical Journal International, Vol. 215, No. 3Seismic inversion and uncertainty quantification using transdimensional Markov chain Monte Carlo methodDehan Zhu and Richard Gibson13 June 2018 | GEOPHYSICS, Vol. 83, No. 4Transdimensional seismic inversion using the reversible jump Hamiltonian Monte Carlo algorithmMrinal K. Sen and Reetam Biswas6 March 2017 | GEOPHYSICS, Vol. 82, No. 3Frequency domain full waveform elastic inversion of marine seismic data from the Alba field using a Bayesian trans-dimensional algorithm10 February 2016 | Geophysical Journal International, Vol. 205, No. 2Uncertainty Analysis for Seismic Inverse Problems: Two Practical Examples12 October 2010Stochastic inversion of pressure and saturation changes from time-lapse multi component dataGeophysical Prospecting, Vol. 55, No. 6Trans-dimensional inverse problems, model comparison and the evidence1 November 2006 | Geophysical Journal International, Vol. 167, No. 2Stochastic inversion of pressure and saturation changes from time-lapse AVO dataHelene Hafslund Veire, Hilde Grude Borgos, and Martin Landrø11 September 2006 | GEOPHYSICS, Vol. 71, No. 5Monte-Carlo Bayesian look-ahead inversion of walkaway vertical seismic profilesGeophysical Prospecting, Vol. 53, No. 5Expanded uncertainty quantification in inverse problems: Hierarchical Bayes and empirical BayesAlberto Malinverno and Victoria A. Briggs28 July 2004 | GEOPHYSICS, Vol. 69, No. 4Parsimonious Bayesian Markov chain Monte Carlo inversion in a nonlinear geophysical problem1 December 2002 | Geophysical Journal International, Vol. 151, No. 3 SEG Technical Program Expanded Abstracts 2000ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2000 Pages: 2484 publication data© 2000 Copyright © 2000 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 04 Jan 2005 CITATION INFORMATION Alberto Malinverno and Scott Leaney, (2000), "A Monte Carlo method to quantify uncertainty in the inversion of zero‐offset VSP data," SEG Technical Program Expanded Abstracts : 2393-2396. https://doi.org/10.1190/1.1815943 Plain-Language Summary PDF DownloadLoading ...