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 Department of Informatics and Mathematical Modeling, Technical University of Denmark
We present a study on the inversion of seismic reflection data generated from a synthetic reservoir model. Our aim is to invert directly for rock facies and porosity of the target reservoir zone. We solve this inverse problem using a Markov chain Monte Carlo (McMC) method to handle the nonlinear, multi-step forward model (rock physics and seismology) and to provide realistic estimates of uncertainties. To generate realistic models which represent samples of the prior distribution, and to overcome the high computational demand, we reduce the search space utilizing an algorithm drawn from geostatistics. The geostatistical algorithm learns the multiple-point statistics from prototype models, then generates proposal models which are tested by a Metropolis sampler. The solution of the inverse problem is finally represented by a collection of reservoir models in terms of facies and porosity, which constitute samples of the posterior distribution.
Lecture Notes in Earth Sciences: Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, 2014, p. 683-687
Main Research Area:
Lecture Notes in Earth Sciences
15th Annual Conference of the International Association for Mathematical Geosciences, 2014