Pemodelan Inversi Non-Linier dalam Geofisika Menggunakan Algoritma Rantai Markov

Hendra Grandis (Program Studi Geofisika, Departemen Geofisika dan Meteorologi Fakultas Ilmu Kebumian dan Teknologi Mineral – ITB Jl. Ganesha 10 Bandung 40132)

Indonesian Journal of Physics (IJP)
Vol 13 No 2 (2002): Vol. 13 No.2, April 2002

In the frame of Bayesian inference, the inverse problem solution is described by posterior probability density function (PDF) in the model space. Estimation of PDF in a multidimensional space is based on a Markov chain having invariant probability identical to the posterior PDF of the model. Extensive exploration of the model space using a stochastic technique is expected to circumvent local minima. The Markov chain algorithm has been applied to non-linear inversion of magnetotelluric (MT) data using 1-D and 2-D models with satisfactory results, i.e. synthetic models have been recovered.