Controlling the sedimentological realism of deltaic reservoir models by the use of intelligent sedimentological prior information

The generation of multiple reservoir models that match production data is one of the advantages of automatic history matching. Including facies geometry varia­tions within the AHM process without the modeller control could result in the selection of reservoir models that match production data but lack of sedimentological realism (facies geometry that mimic the geometry observed in nature). These unrealistic models will cause problems in production forecasting and reserves estimation. In this article, a technique is proposed to guarantee sedimentological realism within the AHM process. Building realistic prior models that describe the non-linear dependencies between sedimentological parameters of deltaic systems can prevent the development of geologically unrealistic reservoir models. Multi-dimensional realistic priors were generated using One-Class Support Vector Machine. This technique captures hidden relations of deltaic param­eters: Delta Plane Width, Length and Thickness; Distributary Channel Width and Thickness, Meander Amplitude, and Wavelength and Mouth bar dimensions. Variables are sampled from the realistic priors in order to assure facies realism. A Multiple Point Statistics (MPS) algo­rithm is used to model facies in a deltaic reservoir. Variability of facies geometry is produced by changing the MPS geometri­cal parameter, different training images and regions. History-matched models produced under geological realis­tic constraints reduce uncertainty of the production prediction, ensures the realism of the selected reservoir and also helps in the identification of the reservoir geometry.