Seismic reservoir characterisation is a natural pathway to combine engineering, geological, and geophysical data, which is crucial for making good exploration and operational decisions. Basin simulation gives the geoscientist the opportunity to incorporate sophisticated and calibrated models into predictions of subsurface properties. Reservoir characterisation work often produces multiple interpretations using incompatible techniques. The technological challenge of using basin simulation output with traditional seismic inversion methods is that the exact location of facies is not accurate. When the simulation output is transformed to produce elastic properties, the properties are inevitably inaccurate. Consequently, an inversion approach that statically uses basin model-derived low frequency models produces impedance models with unphysical artifacts caused by inconsistencies with the seismic input.

To overcome these challenges, we utilise a Bayesian seismic inversion framework that produces facies and impedances using prior estimates of elastic facies uncertainty and distribution. In this application, the per-facies priors are constructed using specific porosity compaction models, cement profiles based on temperature and timing and pore pressures, transformed with rock physics models to elastic properties. The resulting inversion properties are thus a sensible integration of a complex basin simulation model with a deterministic seismic inversion.

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