Joint inversion of seismic traveltimes and gravity data using petrophysical constraints with application to lithology differentiation

Abstract

Multiple geophysical data collected over the same area but based on fundamentally different physics usually contain complementary information about the subsurface. Joint inversion combines the complementary information by integrating all the geophysical data into a single inversion scheme. Thus, models resulting from joint inversion are more likely to represent the subsurface better than models derived from a single type of data. In this study, we consider joint inversion of seismic traveltimes and gravity data, and present a new joint inversion algorithm that uses petrophysical information as constraints. Using a synthetic example, we show that this new method can effectively build the available petrophysical information into inversion and improve the definition of both structure and physical properties. We also show that this method can deal with the situation where only partial petrophysical information about the subsurface is available. An important component of our method is applying fuzzy c-means (FCM) clustering algorithm to the recovered physical property distribution to generate a lithology map that is consistent with both the observed geophysical data and the a priori petrophysical information.