Bayesian rock physics inversion using a localized ensemble-based approach - with an application to the Alvheim field

Abstract

We describe, implement and show results of a localized ensemble-based approach for seismic AVO inversion with uncertainty quantification. Ensembles are simulated from continuous prior probability distributions for fluid saturations and clay content. Starting with continuous saturations and clay content variables, we use depth-varying models for cementation and grain contact theory, Gassmann fluid substitution with mixed saturations, and approximations to the Zoeppritz equations for the AVO attributes at the top-reservoir. The local conditioning to seismic AVO observations relies on i) the misfit between ensemble simulated seismic AVO data and the field observations in a local partition of the grid - local patch, of inlines/crosslines around the locations where we aim to predict, ii) correlations between the simulated reservoir properties and the data in local patches, iii) local assessment to avoid unrealistic updates based on spurious correlations in the ensembles. Data from the Alvheim field in the North Sea are used to demonstrate the approach. The influence of the prior information from the well logs in combination with the seismic reflection data indicates presence of higher oil and gas saturation in the lobe structures of the field and increased clay content at their edges.

Bayesian rock physics inversion using a localized ensemble-based approach - with an application to the Alvheim field