Advances in Generating and Ranking Integrated Geological Models for Fluvial Reservoir

Abstract

Abstract Development plans for Oil and gas reservoirs require huge investments. The decision for making these investments is based on many factors among them the reservoir performance predictions. To get reliable reservoir performance predictions, a reliable geological model is need. However, there are a lot of challenges encountered in the process of building a reliable geological. An important challenge is the limited amount of information available to geologists. Another challenge is the non-uniqueness problem, in other words several models can fit the same data and give different future forecasts. Moreover, stochastic modeling methods alone cannot predict accurately lithological distribution. New advances have been made in building and ranking geological models to over come all of these problems. This paper reviews the current status of integrated reservoir modeling in general and present advances in integrated geological modeling for fluvial reservoir. It covers advances in three important areas: reservoir characterisation of fluvial reservoirs, stochastic modeling and geological models ranking. These new advances have made it possible to generate the best possible geological model to be used in reservoir simulation. The first part focuses on advance in building a fully integrated reservoir characterisation study and exploring the different possible reservoir depositional settings for fluvial settings. In the second part covers advance in the utilization of stochastic modeling such as the use of object oriented algorithms to generate multi realizations that match modern analogs. The third part covers ranking geological models by static and dynamic methods. Static methods include the match of input and output statistics, while the dynamic methods include streamline simulation methods.