Pressure and saturation change inversion using 4D seismic: Application to a chalk reservoir in North Sea

A comparative study is carried out between a deterministic and a stochastic approach via Bayesian McMC to obtain estimates of changes in pressure and saturation. The aim is to provide insights into well performance and pressure distribution within a geo-mechanically active chalk reservoir (Ekofisk). Uncertainty of such predictions is usually high; henceforth the solution of such an inverse problem is not limited to a single set of predicted parameters but represented by a probability density function on the model space. Both inversion approaches are similarly constrained by reservoir engineering concepts and predictions. We show that the Bayesian framework provides a suitable platform to incorporate data uncertainties and prior information. Quantitative interpretation on this field using the inversion results shows good agreement with well production data and helps to explain strong localized anomalies in both the Ekofisk and Tor formations.