Detailed seismic lithofluid distribution using Bayesian stochastic inversion for a thinly bedded reservoir: A case study over Huntington UK Central North Sea

Abstract

A geostatistical inversion scheme was designed and performed for reservoir characterization of the UK Central North Sea (CNS) Huntington Oil field, with the goal of increasing the resolution of the seismic inversion and derived attributes, and to provide statistical measures of the uncertainties involved in the seismic facies prediction. The aim of the study was to fully understand lithology and pore-fluid rock properties in the Forties sandstone reservoir, Late Paleocene Sele Formation fan system of the UK CNS. In the Forties, multiple sand beds are separated by thin layers of silt and shale. Reprocessed prestack seismic volumes and considerable well-log data were input to an advanced stochastic simultaneous inversion method. This method combines the strengths of geostatistical inversion with sequential Gaussian simulation and Bayesian inversion. The approach allowed the inversion to be built on a fine-scale stratigraphic grid at a reservoir scale rather than at a seismic scale, and it enabled a detailed description of facies distribution and associated uncertainty. A sufficiently large number of stochastic solutions (100 realizations) enabled probabilistic models of lithofluid distribution to be generated. Facies geobody connectivity can also be derived, but this was not part of this work. As a consequence of our study, a sidetrack water injector well location was evaluated, and a potential undrilled hydrocarbon accumulation was identified, which could extend the field life of the Huntington asset.