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Uncertainty estimation by probabilistic first arrival time tomography using Markov Chain Monte Carlo sampling
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 79th EAGE Conference and Exhibition 2017 - Workshops, Jun 2017, cp-519-00044
- ISBN: 978-94-6282-219-1
Abstract
We present several applications of probabilistic first arrival time tomography by Markov Chain Monte Carlo sampling dedicated to uncertainty estimation. In the first part, we introduce a new velocity model parameterization based on Johnson-Mehl tessellation that allows applying probabilistic approach to typical seismic refraction data. We also present results of the tomography to a real data set recorded in the context of hydraulic fracturing and illustrate how the velocity model uncertainties can be properly taken into account when locating seismic events.