A Bayesian Approach for Seismic Inversion at Roncott Research Area

DOI

10.2991/mmsa-18.2018.90How to use a DOI?

Keywords

genetic algorithm; simulated annealing; optimal regulation; bayes theory; seismic inversion

Abstract

In this paper, we embedded the genetic algorithm (GA) into the inner loop of the simulated annealing (SA) with a special design. The new method will boost the tunability of the searching process by providing two scales of regulation in seismic inversion problem. Moreover, a quantified uncertainty of the inversion result can be obtained when we put this strategy under Bayesian framework. Real data tests are conducted to support the theoretical calculation. Based on the conventional sparse spike inversion results, as a part of the prior information, our proposed method presents a superior quality and convincible uncertainty description.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yaoting Lin
AU  - Wei Zhou
AU  - Wenyuan Liao
PY  - 2018/03
DA  - 2018/03
TI  - A Bayesian Approach for Seismic Inversion at Roncott Research Area
BT  - Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)
PB  - Atlantis Press
SP  - 404
EP  - 407
SN  - 1951-6851
UR  - https://doi.org/10.2991/mmsa-18.2018.90
DO  - 10.2991/mmsa-18.2018.90
ID  - Lin2018/03
ER  -