Joint inversion of gravity and magnetic data in 3D using Monte Carlo methods

Miguel Bosch and Ronny Meza and Carlos Hönig and Jhonny Merchan. ( 2007 )
in: 27th gOcad Meeting, ASGA

Abstract

Inference of earth medium structure and properties is based on multidisciplinary data and information. Commonly, geophysics, petrophysics and geology need to be integrated to produce a realistic description of earth structures, basins and reservoirs. To achieve a quantitative combination of such different types of information we use a statistical approach that begins with defining a common model jointly describing structural, petrophysical and physical properties of the medium. By inverting the geophysical data onto the common model, we further constraint the model to jointly explain the geophysical observations and comply with the petrophysical and geological information. The related calculations are developed using sampling (Monte Carlo) techniques. We followed this approach for the joint inversion of gravity and magnetic data to infer the 3D structure and properties in a region of northern Venezuela, modeling the major lithotype regions, the medium mass density and magnetic susceptibility fields. These model properties are linked by conditioning the physical property statistics to the lithotype using petrophysical and geostatistical information. We generate a large number of model realizations that jointly honor the prior structural and geostatistical information, and the likelihoods with the gravity and magnetic observations, calculating final estimates and probabilities of the medium model parameters. This method combines the gravity and magnetic data with prior information on the mass density, and magnetic susceptibility statistics obtained from measurements on rock samples, and statistical constraints on interface positions obtained from interpreted seismic sections. The resulting models jointly comply with the gravity and magnetic observations and the prior information.

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    BibTeX Reference

    @inproceedings{BoschRM2007,
     abstract = { Inference of earth medium structure and properties is based on multidisciplinary data and information. Commonly, geophysics, petrophysics and geology need to be integrated to produce a realistic description of earth structures, basins and reservoirs. To achieve a quantitative combination of such different types of information we use a statistical approach that begins with defining a common model jointly describing structural, petrophysical and physical properties of the medium. By inverting the geophysical data onto the common model, we further constraint the model to jointly explain the geophysical observations and comply with the petrophysical and geological information. The related calculations are developed using sampling (Monte Carlo) techniques. We followed this approach for the joint inversion of gravity and magnetic data to infer the 3D structure and properties in a region of northern Venezuela, modeling the major lithotype regions, the medium mass density and magnetic susceptibility fields. These model properties are linked by conditioning the physical property statistics to the lithotype using petrophysical and geostatistical information. We generate a large number of model realizations that jointly honor the prior structural and geostatistical information, and the likelihoods with the gravity and magnetic observations, calculating final estimates and probabilities of the medium model parameters. This method combines the gravity and magnetic data with prior information on the mass density, and magnetic susceptibility statistics obtained from measurements on rock samples, and statistical constraints on interface positions obtained from interpreted seismic sections. The resulting models jointly comply with the gravity and magnetic observations and the prior information. },
     author = { Bosch, Miguel AND Meza, Ronny AND Hönig, Carlos AND Merchan, Jhonny },
     booktitle = { 27th gOcad Meeting },
     month = { "may" },
     publisher = { ASGA },
     title = { Joint inversion of gravity and magnetic data in 3D using Monte Carlo methods },
     year = { 2007 }
    }