Joint stochastic constraint of a large dataset from a salt-dome

Understanding the uncertainty associated with large joint geophysical surveys, such as 3D seismic, gravity and magneto-telluric studies, is a challenge, both conceptually and practically. By demonstrating the use of emulators, we adopt a Monte Carlo forward screening scheme to globally test a prior model space for plausibility. This methodology means that the incorporation of all types of uncertainty is made conceptually straightforward, by designing an appropriate prior model space, upon which the results are dependent, from which to draw candidate models. We test the approach on a salt-dome target, over which three datasets have been obtained; wide-angle seismic refraction, magneto-telluric and gravity data. We consider the datasets together using an empirically measured uncertain physical relationship connecting the three different model parameters; seismic velocity, density and resistivity, and show the value of a joint approach, rather than considering individual pa- rameter models. The results are probability density functions over the model parameters, together with a halite probability map. The emulators are shown to give considerable speed advantage over running the full simulator codes, and we consider their use to have much potential in the development of geophysical statistical constraint methods.