Incorporating Probabilistic Petrophysical Information into Elastic Full Waveform Inversion

Elastic full waveform inversion (EFWI) augmented with petrophysical information defines a high standard for velocity model building, as it delivers high-resolution, accurate and lithologically feasible subsurface models. The technique enhances the benefits of using an elastic wave equation over the acoustic implementation while constraining the inverted models to geologically plausible solutions. We derive elastic models of subsurface properties using EFWI and explicitly incorporate petrophysical penalties to guide models toward realistic lithology, i.e., to models consistent with the seismic data as well as with the petrophysical context in the area of study. This methodology mitigates several issues related to EFWI, as it reduces the high non-linearity of the inverse problem, mitigates the artifacts created by interparameter crosstalk, and prevents geologically implausible earth models. We define this penalty using multiple probability density functions (PDFs) derived from petrophysical information, such as well logs, where each PDF represents a different lithology. We demonstrate that the combined FWI objective function establishes a more robust foundation for EFWI by explicitly guiding models toward plausible solutions in the specific geological context of the exploration problem, while at the same time reducing the misfit between the observed and modelled data.