Improving 4D Seismic Data Interpretation using Geostatistical Filtering

Abstract

PreviousNext No Access9th International Congress of the Brazilian Geophysical Society & EXPOGEF, Salvador, Bahia, Brazil, 11-14 September 2005Improving 4D Seismic Data Interpretation using Geostatistical FilteringAuthors: Carlos Eduardo AbreuNathalie LucetPhilippe NivletJean-Jacques RoyerCarlos Eduardo AbreuInstitut Français du PétroleSearch for more papers by this author, Nathalie LucetInstitut Français du PétroleSearch for more papers by this author, Philippe NivletInstitut Français du PétroleSearch for more papers by this author, and Jean-Jacques RoyerCNRS-CRPGSearch for more papers by this authorhttps://doi.org/10.1190/sbgf2005-248 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract 4D Seismic is becoming a conventional tool for hydrocarbon reservoirs monitoring and management, especially for heavy oil bearing fields (Calvert, 2005). In this case, 4D, or time-lapse seismic, can be used to detect important reservoir properties variations imposed by thermal enhanced oil recovery processes. This work aims at identifying remaining noise, invariant common features and time-dependent variations in oil reservoirs from post-stack amplitude time-lapse data. It involves a geostatistical multivariate technique called factorial co-kriging, an extension of the factorial kriging (FK) technique proposed by Matheron (1982). It is based on the decomposition of spatial correlations to identify redundant structures at various scales. Three seismic surveys, with different acquisition parameters, were acquired at the same site in different calendar times to monitor the progress of injected steam fronts into a heavy-oil reservoir. These seismic volumes were then carefully processed to minimize their discrepancies. Factorial co-kriging revealed possible common geological structures, 4D effects and remaining noise, and it seems to be an efficient method for extracting common regional trends from several repeated seismic datasets. Keywords: 4D, seismic, time-lapse, interpretationPermalink: https://doi.org/10.1190/sbgf2005-248FiguresReferencesRelatedDetailsCited BySeismic data assimilation with an imperfect model10 July 2019 | Computational Geosciences, Vol. 24, No. 2M-Factorial Kriging for Seismic Data Noise AttenuationCédric Magneron, Matthieu Bourges, and Nicolas Jeannee28 April 2014Characterization of the Measurement Error in Time-Lapse Seismic Data and Production Data with an EM Algorithm14 June 2007 | Oil & Gas Science and Technology - Revue de l'IFP, Vol. 62, No. 2 9th International Congress of the Brazilian Geophysical Society & EXPOGEF, Salvador, Bahia, Brazil, 11-14 September 2005ISSN (online):2159-6832Copyright: 2005 Pages: 2274 publication data© 2005 Published in electronic format with permission by the Brazilian Geophysical SocietyPublisher:Society of Exploration Geophysicists HistoryPublished: 14 Sep 2005 CITATION INFORMATION Carlos Eduardo Abreu, Nathalie Lucet, Philippe Nivlet, and Jean-Jacques Royer, (2005), "Improving 4D Seismic Data Interpretation using Geostatistical Filtering," SEG Global Meeting Abstracts : 1249-1251. https://doi.org/10.1190/sbgf2005-248 Plain-Language Summary Keywords4Dseismictime-lapseinterpretationPDF DownloadLoading ...