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Titre3D stochastic inversion of gravity data using cokriging and cosimulation
AuteurShamsipour, P; Marcotte, D; Chouteau, M; Keating, P
SourceGeophysics vol. 75, no. 1, 2010 p. I1-I10, https://doi.org/10.1190/1.3295745
Année2010
Séries alt.Secteur des sciences de la Terre, Contribution externe 20080670
ÉditeurSociety of Exploration Geophysicists
Documentpublication en série
Lang.anglais
DOIhttps://doi.org/10.1190/1.3295745
Mediapapier; en ligne; numérique
Référence reliéeCette publication est reliée Shamsipour, P; Chouteau, M; Keating, P; Marcotte, D; (2010). Three-dimensional stochastic inversion of gravity data: application to gravity data from the Matagami region, Quebec, Commission géologique du Canada, Recherches en cours (En ligne) no. 2010-12
Formatspdf
Sujetsgéostatistiques; simulations par ordinateur; interprétations de la pesanteur; anomalies gravimétriques; modèles de la pesanteur; modèles; modèles de la pesanteur; établissement de modèles; géophysique; géomathématique
Illustrationsprofiles; diagrams; plots
ProgrammeInitiative géoscientifique ciblée (IGC-3), 2005-2010
Résumé(disponible en anglais seulement)
Anew application has been developed, based on geostatistical techniques of cokriging and conditional simulation, for the 3D inversion of gravity data including geologic constraints. The necessary gravity, density, and gravity-density covariance matrices are estimated using the observed gravity data. Then the densities are cokriged or simulated using the gravity data as the secondary variable. The model allows noise to be included in the observations. The method is applied to two synthetic models: a short dipping dike and a stochastic distribution of densities. Then some geologic information is added as constraints to the cokriging system. The results show the ability of the method to integrate complex a priori information. The survey data of the Matagami mining camp are considered as a case study. The inversion method based on cokriging is applied to the residual anomaly to map the geology through the estimation of the density distribution in this region. The results of the inversion and simulation methods are in good agreement with the surface geology of
the survey region.
GEOSCAN ID226445