We implement an AVA-petrophysical inversion that uses an anisotropic Markov random field to model the lateral variability of petrophysical properties. A Bayesian framework is adopted for transforming pre-stack data to the maximum-a-posteriori solution of reservoir properties. The lateral heterogeneity of the investigated reservoir is reasonably modeled by the Huber energy function. For computational feasibility reasons, we limit our attention to a target-oriented inversion that uses the amplitude versus angle (AVA) responses extracted along a time slice representing the top reflection of the investigated reservoir, to infer the petrophysical properties of interest for the reservoir layer. The implemented AVA-petrophysical inversion uses a previously defined linear rock-physics model to rewrite the linear Aki and Richards AVA equation for P-P waves in terms of contrasts in the petrophysical properties at the reflecting interface. This reformulation allows us to directly derive the petrophysical properties around the target zone from AVA data. We applied this method to 3D onshore seismic data for the characterization of a clastic, gas-saturated, reservoir. A comparison with the outcomes of a more standard laterally unconstrained AVA-petrophysical inversion is used to demonstrate the antinoise and the imaging ability of the implemented approach.


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