Analysis of Time-Lapse Seismic and Production Data for Systematic Reservoir Model Classification and Assessment

Abstract

The heterogeneous distribution of reservoir properties is one of the most important uncertainties in static and dynamic reservoir modelling. Petrophysical properties are usually interpolated within reservoir models from sparse well-log data, which can lead to highly uncertain estimates at inter-well locations that directly affect the reliability of fluid-flow model predictions of reservoir behavior. To address this issue, we build an ensemble of equiprobable models that combine different geostatistical realizations of reservoir properties to span the range of potential outcomes. While this process captures the impact of reservoir property distributions on the model response, a major challenge is classifying the subset of models in the ensemble best representing reservoir fluid-flow behavior. Thus, we introduce a methodology combining 4D seismic amplitude attributes and reservoir production data to classify fluid-flow models. This classification is based on applying thresholds for independent seismic and production objective functions. We test our methodology on the benchmark case UNISIM-I developed from observations from the Namorado Field, Campos Basin, Brazil. By comparing injection and production rates in relation to 4D seismic amplitude trends, we identify nine models out of an ensemble of 100 that judged optimal via the required seismic and production objective function thresholds and obtain an improved quantitative evaluation of the impact of reservoir production on the 4D seismic signal. Ultimately, combining seismic and production data offers interpretation scenarios that automatically identify realistic fluid-flow models that can assist the update of permeability and porosity distributions within the reservoir.