Back to Search Start Over

Appraising structural interpretations using seismic data—theoretical elements

Authors :
Paul Cupillard
Paul Sava
Guillaume Caumon
Modeste Irakarama
Jonathan Edwards
GeoRessources
Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre de recherches sur la géologie des matières premières minérales et énergétiques (CREGU)-Institut national des sciences de l'Univers (INSU - CNRS)
Institut de Physique du Globe de Paris (IPGP)
Institut national des sciences de l'Univers (INSU - CNRS)-IPG PARIS-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS)
Ecole Nationale Supérieure de Géologie (ENSG)
Université de Lorraine (UL)
Colorado School of Mines
RING-GOCAD Consortium
RING
Institut national des sciences de l'Univers (INSU - CNRS)-Centre de recherches sur la géologie des matières premières minérales et énergétiques (CREGU)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
Centre National de la Recherche Scientifique (CNRS)-Université de La Réunion (UR)-Université Paris Diderot - Paris 7 (UPD7)-IPG PARIS-Institut national des sciences de l'Univers (INSU - CNRS)
Source :
Geophysics, Geophysics, Society of Exploration Geophysicists, 2019, 84 (2), pp.N29-N40. ⟨10.1190/geo2018-0128.1⟩
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

International audience; Structural interpretation of seismic images can be highly subjective, especially in complex geological settings. A single seismic image will often support multiple geologically valid interpretations. However, it is usually difficult to determine which of those interpretations are more likely than others. We refer to this problem as structural model appraisal herein. We propose the use of misfit functions to rank and appraise multiple interpretations of a given seismic image. Given a set of possible interpretations, we compute synthetic data for each structural interpretation, then compare these synthetic data against observed seismic data; this allows us to assign a data-misfit value to each structural interpretation. Our aim is to find data-misfit functions which enable a ranking of interpretations. To do so, we formalize the problem of appraising structural interpretations using seismic data and derive a set of conditions to be satisfied by the data-misfit function for a successful appraisal. We investigate both vertical seismic profiling and surface seismic configurations. An application of the proposed method to a realistic synthetic model shows promising results for appraising structural interpretations using vertical seismic profiling data, provided the target region is well illuminated. However, we find appraising structural interpretations using surface seismic data to be more challenging, mainly due to the difficulty of computing phase-shift data-misfits.

Details

Language :
English
ISSN :
00168033
Database :
OpenAIRE
Journal :
Geophysics, Geophysics, Society of Exploration Geophysicists, 2019, 84 (2), pp.N29-N40. ⟨10.1190/geo2018-0128.1⟩
Accession number :
edsair.doi.dedup.....72f0ec61fa9ce2a674d53acc102cfdd2
Full Text :
https://doi.org/10.1190/geo2018-0128.1⟩