A Field Data Application of RockAVO: Data-driven, Direct Petrophysical Inversion of Pre-stack Seismic Data

Seismic Reservoir Characterization (SRC) is a pillar for the success of any hydrocarbon exploration and CO₂ storage project. One of the main goals of SRC is the inversion of seismic pre-stack data for petrophysical properties, such as porosity, shale content, and water saturation. However, the non-linear relationship between petrophysical properties and seismic amplitudes, and the noisy nature of seismic data make this a challenging task. The recently introduced RockAVO methodology offers a new solution to such a problem by enabling the direct inversion of petrophysical properties from pre-stack seismic data, whilst leveraging the information provided by a limited number of available training wells. Provided the availability of both petrophysical and elastic well logs, this method bypasses the need for creating a rock physics model and instead learns directly from the data. In this work, we present our first successful field application of RockAVO, conducted on the openly accessible Volve dataset. We delve into the necessary pre-processing steps, elaborating on how to transform the pre-stack seismic data from offset to angle domain and establish trustworthy petrophysical background models for the last step of inversion. Additionally, we discuss the challenges encountered throughout the process, particularly in dealing with high levels of noise present in the Volve pre-stack gathers. Our initial findings underline the efficacy and promise of RockAVO in petrophysical inversion, setting the stage for further enhancements and applications.