The Inverse Modeling and Geostatistics Project
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Integrated Modelling of Oil Reservoirs

This project is funded from 1. September 2009 by The Danish Council for Independent Research - Technology and Production Sciences (DKK 5.38 mill. or $1.1 mill.) and by DONG Energy (DKK 970.000 or $190.000). The project will in the next 3 years focus on the integration of history matching with geostatistical reservoir models and seismic data.

Significant improvement of oil recovery depends on two, very computer-intensive numerical processes: seismic inversion and history matching. Seismic inversion exploits reflected seismic waves from the subsurface to calculate physical/geological structure of the reservoir. History matching computes physical properties of the reservoir that explain the time evolution of pressure and oil/gas/water production in production wells.
If seismic inversion and history matching could be integrated in an efficient way, significantly improved images of the reservoir structure could be obtained. New production wells could be located optimally, and production planning could be optimized.

This goal is now within reach due to the discovery of an interesting property of seismic data. Recent work by the project group has demonstrated that most information about structure and porosity of a reservoir is encapsulated in a limited set of characteristics derived from the seismic data. This enables fast and accurate calculation of reservoir properties, and opens new perspectives for integration of seismic analysis and history matching technology. The aim of the project is to seize this opportunity to develop the first efficient and accurate reservoir modelling method.

(Collaborators: Prof. Ph.D. Erling H. Stenby, IVC-SEP, DTU Chemical Engineering, Technical University of Denmark; Ph.D. Morten G. Stage, R&D Manager, DONG Energy AS, Denmark; Prof. dr. Albert Tarantola, IPGP, University of Paris, France; Prof. dr. Jef Caers, Energy Resources Engineering Department, Stanford University, USA; Dr. Peter Gerstoft, Scripps Institute of Oceanography, University of California, San Diego, USA.)