2022-07-292022-07-292019-12-12MADEIRA, Roberto Livy da Costa. Inversão bayesiana 1D de dados geofísicos de dipolo magnético vertical. 2019. Trabalho de Curso (Licenciatura em Matemática) – Faculdade de Matemática, Campus Universitário de Castanhal, Universidade Federal do Pará, Castanhal, 2019. Disponível em: https://bdm.ufpa.br:8443/jspui/handle/prefix/4278. Acesso em:.https://bdm.ufpa.br/handle/prefix/4278Various geophysical methods are used to estimate subsurface geolectric properties, such as the resistivity of subsurface layers of the earth and their geometric properties. Bayesian methods were used in this study to estimate resistivity and thickness of subsurface horizons. Specifically, Monte Carlo Methods based in Markov Chains (MCMC) were proposed, which are the most common bayesian methods used in parameter inversions. First, MCMC Metropolis-Hastings (MH) were used to fix different thickness to each layer and then estimated the resistivity of each. Then, Reversible Jump MCMC (RJ-MCMC) was applied using the modelgenerated thicknesses and number of layers as variables. The MH model returned acceptable resistivity values of the shallow layers, generating imprecision in the intermediate and deep layers. The RJ-MCMC model was better suited for self-parameterizing and for faster computing time, generating uncertainty in the deeper layers. Our results show that for studies of shallow layers RJ-MCMC correctly adjusted the three-layer model with low deviation of real values as related to correlations between the pair of properties.Acesso AbertoInversão (Geofísica)Métodos BayesianosResistividadeInversion (Geophysics)Bayesian methodsResistivityCNPQ::CIENCIAS EXATAS E DA TERRATrabalho de Curso - Graduação - Monografia