2007
DOI: 10.1111/j.1365-246x.2007.03440.x
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Lithology-derived structure classification from the joint interpretation of magnetotelluric and seismic models

Abstract: S U M M A R YMagnetotelluric and seismic methods provide complementary information about the resistivity and velocity structure of the subsurface on similar scales and resolutions. No global relation, however, exists between these parameters, and correlations are often valid for only a limited target area. Independently derived inverse models from these methods can be combined using a classification approach to map geologic structure. The method employed is based solely on the statistical correlation of physic… Show more

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Cited by 77 publications
(74 citation statements)
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“…Put differently, the velocity model we are trying to produce is dependent on our first guess at it. To minimize the importance of the accuracy of this first guess, an iterative approach varying cell sizes has been developed (also discussed in Ryberg et al, 2007). In this approach, the initial cell size is made vary large, for example the cross-section is divided into six cells along its length, and four along depth, and a fairly straightforward initial model is provided.…”
Section: Data Processing and Tomographymentioning
confidence: 99%
“…Put differently, the velocity model we are trying to produce is dependent on our first guess at it. To minimize the importance of the accuracy of this first guess, an iterative approach varying cell sizes has been developed (also discussed in Ryberg et al, 2007). In this approach, the initial cell size is made vary large, for example the cross-section is divided into six cells along its length, and four along depth, and a fairly straightforward initial model is provided.…”
Section: Data Processing and Tomographymentioning
confidence: 99%
“…Examples of well-known geostatistical methods that may have value in cooperative inversion include basic methods such as kriging or co-kriging and clustering techniques such as k-means, Fuzzy logic, principal component analysis (PCA) and neural networking (Bedrosian et al 2007;De Benedetto et al 2012;Di Giuseppe et al 2014;Dubrule 2003;Kieu and Kepic 2015;Klose 2006;Roden et al 2015;Ward et al 2014).…”
Section: Geostatistical Methods In Cooperative Inversionmentioning
confidence: 99%
“…Bedrosian et al (2007) use kriging to interpolate inverted MT-derived electrical resistivity values onto a finer mesh corresponding to that used for seismic velocity, to perform lithological classification. Bourges et al (2012) demonstrate the benefits of co-kriging on the two dataset's porosity and acoustic impedance.…”
Section: Geostatistical Methods In Cooperative Inversionmentioning
confidence: 99%
“…The methodology used in the present paper was described by Bedrosian et al (2007) and is based on a probabilistic approach developed by Bosch (1999), in a sense that diverse geophysical parameters are represented as a probability density function (pdf) in the joint parameter space. The coincident velocity and resistivity models are first interpolated onto a common grid.…”
Section: Methodology Descriptionmentioning
confidence: 99%
“…However, with a statistical analysis of the distributions of both resistivity and velocity, we can find certain areas of the models space where a particular relation between the physical parameters holds locally, thus allowing us to characterize this region as a particular lithology. In the present work, we use a statistical analysis, as described by Bedrosian et al (2007) in order to correlate two independently obtained models of the Groß Schönebeck geothermal test site in the Northeast German Basin.…”
Section: Introductionmentioning
confidence: 99%