Scaling Issues through Quantitative Analysis between Reservoir Simulation

Abstract

Abstract Time-lapse seismic has been providing valuable information on identifying fluid movements, to locate bypassed oil and well placement optimization to reduce uncertainties in reservoir development and production management. Nevertheless, most of these are made through a qualitative approach, which limits seismic data integration in reservoir simulation studies due to different scales. In order to overcome this and develop new data integration techniques, many studies involving these processes have the assumption that both frameworks are in the same scale. Nonetheless, the quantification of the lost information in the scaling procedures needs to be evaluated and quantitative seismic data integration into the simulator should improve the mitigation of these problems improving the knowledge about the representativeness of the scaled data. In this context, it is presented a technique regarding to scale issues relating time-lapse seismic data, geological and simulation models aiming to quantify the information lost due to the scaling problems. This paper describes a methodology involving seismic attributes and reservoir simulation. Saturation and pressure trends derived from acoustic impedance behavior, which were obtained from seismic data. The lost information due to scaling procedures is evaluated through comparison between flux model properties and seismic attributes, at each respective framework, for estimating the best step to do it. This technique allowed the reliability improvement of the reservoir parameters from seismic attributes regarding to the lost information due to scaling procedures. It has been shown that it is possible to improve the model and results reliability through a quantitative analysis involving scaling procedures between 4D seismic data and reservoir simulation integrated studies. As main contributions of this technique are the integration procedures regarding to scaling issues between reservoir simulation models and time-lapse seismic information.