3D stochastic inversion of gravity data using cokriging and cosimulation

Abstract

A new 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.

GRAVILOG: An update on the development and use of Borehole Gravity for Mining Exploration

“…Forward modeling (Giroux et al, 2006) and stochastic 3D inversion (Shamsipour et al, 2010) of the multi-hole borehole gravity data (Figure 7) match and potentially extend the Coulon Lens 44 deposit published on Virginia Mines' website, http://minesvirginia.com. This example shows a situation commonly encountered where a borehole has not been extended far enough past the deposit to completely resolve the gravity anomaly (Figure 8).…”

3D stochastic joint inversion of gravity and magnetic data

“…Using Eq. (1) in Shamsipour et al (2010) and Eq. (3) in Shamsipour et al (2011), the response at the observation point (x 0 , y 0 , z 0 ) of all the prisms included within the subsurface model is the sum of the contribution of each prism:…”

“…The multivariate v-v plot is the extended version of the v-v plot method (Asli et al, 2000;Gloaguen et al, 2005;Shamsipour et al, 2010Shamsipour et al, , 2011. Here, the B k matrices of coefficients and elementary structures parameters C k (h) are optimized iteratively such that the theoretical covariances C g,g , C T,T and C g,T computed from the LCM (Eqs.…”

“…Chasseriau and Chouteau (2003) advocate 3D inversion of gravity data using an a priori model of covariance. Shamsipour et al (2010Shamsipour et al ( , 2011 proposed geostatistical techniques of cokriging and conditional simulation for the separate three-dimensional inversion of gravity and magnetic data respectively, including geological constraints.…”

“…The method is a useful extension of Shamsipour et al (2010Shamsipour et al ( , 2011. After the description of the method, it is tested on two synthetic models: a model consisting of two prisms buried in a homogeneous background and a model with stochastic distribution of parameters.…”