Abstract
The frequency matching method defines a closed form expression for a complex prior that quantifies the higher order statistics of a proposed solution model to an inverse problem. While existing solution methods to inverse problems are capable of sampling the solution space while taking into account arbitrarily complex a priori information defined by sample algorithms, it is not possible to directly compute the maximum a posteriori model, as the prior probability of a solution model cannot be expressed. We demonstrate how the frequency matching method enables us to compute the maximum a posteriori solution model to an inverse problem by using a priori information based on multiple point statistics learned from training images. We demonstrate the applicability of the suggested method on a synthetic tomographic crosshole inverse problem.
Original language | English |
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Journal | Mathematical Geosciences |
Volume | 44 |
Issue number | 7 |
Pages (from-to) | 783-803 |
ISSN | 1874-8961 |
DOIs | |
Publication status | Published - 2012 |
Keywords
- Geostatistics
- Multiple point statistics
- Training image
- Maximum a posteriori solution