We show the importance and propose a way of including consistent geological prior and rock physics knowledge when estimating reservoir properties, such as lithology and fluids, from inverted seismic data. As it is common in exploration settings, information from a single well (well logs and petrological analysis) was used to define a set of initial facies that combine lithology and fluids in a single reservoir property. Based on our understanding of the depositional environment, we added expected litho-fluid facies and associated elastic properties, which were not sampled by the well. Given a geologically-consistent, spatially-variant, prior probability of facies occurrence, Bayesian estimation of facies probability was computed at every sample of the seismic data. Deterministic seismic inversion was used to produce the input data for our analysis, which is customary in similar field studies. Accounting for the augmented geological prior we were able to generate a scenario consistent with all available data, which supports further field development. In contrast, the purely data-driven Bayesian classification would lead to downgrading the field’s prospectivity. Based on our findings, we argue that lack of data in Quantitative Interpretation needs to be counterweighted by robust geological prior information to risk geological scenarios without bias.


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