Statistical modeling for facies-dependent seismic inversion

Iris Fernandes*, Klaus Mosegaard, Andrea Zunino

*Corresponding author for this work

Abstract

To improve seismic inversion, we propose to use prior information from empirical estimates of spatial rock property distributions obtained from outcrop training images. Using photographic images of chalk outcrops, we derive empirical distributions of spatial rock property gradients and estimates of spatial correlations. We use this information as a priori information in probabilistic, seismic inversion. Our results are realistic, high-resolution posterior samples of subsurface models, whose variability can be used as an estimate of model uncertainties.

Original languageEnglish
Publication date27 Aug 2018
Number of pages5
DOIs
Publication statusPublished - 27 Aug 2018
Event88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018 - Anaheim, United States
Duration: 14 Oct 201819 Oct 2018

Conference

Conference88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018
Country/TerritoryUnited States
CityAnaheim
Period14/10/201819/10/2018
SponsorBGP, Chevron, et al., Kuwait Petroleum Corporation and Subsidiaries, Saudi Aramco, Royal Dutch Shell PLC

Fingerprint

Dive into the research topics of 'Statistical modeling for facies-dependent seismic inversion'. Together they form a unique fingerprint.

Cite this