1 Center for Energy Resources Engineering, Center, Technical University of Denmark2 National Space Institute, Technical University of Denmark3 Mathematical and Computational Geoscience, National Space Institute, Technical University of Denmark4 Department of Applied Mathematics and Computer Science, Technical University of Denmark5 CERE – Center for Energy Ressources Engineering, Department of Chemical and Biochemical Engineering, Technical University of Denmark6 Department of Informatics and Mathematical Modeling, Technical University of Denmark
We present a new method for solving the history matching problem by gradient-based optimization within a probabilistic framework. The focus is on minimizing the number of forward simulations and conserving geological realism of the solutions. Geological a priori information is taken into account by means of multipoint statistics borrowed from training images. Then production data and prior information are integrated into a single differentiable objective function, minimizer of which has a high posterior value. Solving the proposed optimization problem for an ensemble of different starting models, we obtain a set of solutions honouring both data and prior information.
Lecture Notes in Earth Sciences, 2014, p. 703-707
Main Research Area:
Lecture Notes in Earth Sciences
15th Annual Conference of the International Association for Mathematical Geosciences, 2014