Integrated Workflow Applied to the Characterization of a Carbonate Fractured Reservoir: Qarn Alam Field

Abstract

Abstract This paper presents an innovative integrated workflow applied to the characterization of a carbonate fractured reservoir in order to generate an effective 3D Matrix Block Size (MBS) distribution based on all available data: geological, geophysical and dynamic production data. The MBS is a key factor determining heating and thereby recovery efficiency during steam flooding in a fractured reservoir. The MBS model allows simulating the complex flow and establishing reservoir management strategies that will optimize oil recovery and facility sizing. The major difficulty in developing a 3D MBS model is the ability to account for the all the information pertinent to natural fractures in the field and develop an understanding of what geological characteristics are linked to the occurrence of fractures. Until recently most fractured reservoir modeling tools were limited to simple discrete statistical models. A new approach in fractured reservoir characterization, using primarily artificial intelligence tools, is presented in this paper. The methodology is based on the assumption that there is a complex relationship between a large number of potential geologic drivers (structure, faults, matrix characteristics etc.) and fractures. The combination of both the continuum fracture modeling (CFM) and discrete fracture network (DFN) modeling provides a quantitative framework for MBS distribution estimation, geological concepts and data integration. The application of this integrated workflow to the Qarn Alam field is presented in this paper.