Stochastic Inversion of 2D Magnetotelluric Data

Software · Thu Jul 01 04:00:00 EDT 2010

OSTI ID:1231818

Chen, Jinsong

The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function is explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, it provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows

• Short Name / Acronym: STINV-2DMT; 003067MLTPL00
• Site Accession Number: CR-2907
• Version: 00
• Programming Language(s): Medium: X; OS: Linux/Unix, or Windos; Compatibility: Multiplatform
• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1231818
• Country of Origin: United States