Accounting for processing errors in AVO/AVA data

R. B. Madsen, E. Nørmark, T. Mejer Hansen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingspeer-review

2 Citations (Scopus)

Abstract

Processing of raw seismic data into AVO/AVA data serves many purposes, but also induces some unwanted features (errors) in the resulting data set. Here we study the effect of such processing in an idealized case with a synthetic raw data set. The behavior of the processing errors are estimated using a statistical Gaussian model. The 1D marginal distribution of this model show a good match with observed errors. The subsequent linearized inversion reveals that the processing errors can only be safely ignored for a signal-to-noise ratio (S/N) of 0,4 or below when using an uncorrelated noise model. Such inversion results will have poor posterior resolution. Uncorrelated models with a higher S/N will be biased. Using the estimated Gaussian model to describe the noise in the data eliminates this bias and increases resolution in linear inversion. In a real-world case we expect the threshold of 0.4 to be even lower.

Original languageEnglish
Title of host publication80th EAGE Conference and Exhibition 2018
Subtitle of host publicationOpportunities Presented by the Energy Transition
PublisherEuropean Association of Geoscientists and Engineers, EAGE
ISBN (Electronic)9789462822542
Publication statusPublished - 2018
Event80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition - Copenhagen, Denmark
Duration: 11 Jun 201814 Jun 2018

Publication series

Name80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition

Conference

Conference80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition
Country/TerritoryDenmark
CityCopenhagen
Period11/06/1814/06/18

Programme Area

  • Programme Area 3: Energy Resources

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