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Comparative study of local versus global methods for 1D joint inversion of direct current resistivity and time‐domain electromagnetic data
Author(s) -
Santos Monteiro Fernando A.,
ElKaliouby Hesham M.
Publication year - 2010
Publication title -
near surface geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.639
H-Index - 39
eISSN - 1873-0604
pISSN - 1569-4445
DOI - 10.3997/1873-0604.2009056
Subject(s) - particle swarm optimization , simulated annealing , inversion (geology) , global optimization , electrical resistivity and conductivity , synthetic data , algorithm , direct current , mathematical optimization , geology , computer science , mathematics , engineering , paleontology , structural basin , electrical engineering , voltage
Direct current resistivity and time‐domain electromagnetic (TDEM) surveys are often used in environmental, hydrological and mining evaluation. The interpretation of the data acquired with each of these geophysical methods, assuming one‐dimensional models, frequently produces ambiguous results. The joint inversion of TDEM and direct current resistivity data is considered by several authors as an efficient method to reduce the ambiguity inherent to each of these methods. This paper presents the results of a comparative study on the use of a local optimization method, iteratively reweighted least squares and global optimization methods of simulated annealing and particle swarm optimization in the joint inversion of TDEM and direct current resistivity data. The models obtained from joint inversion of synthetic data (H‐ and K‐type) and of experimental data using the three methods yield similar results. The iteratively reweighted least squares method is the fastest while the simulated annealing is the most time‐consuming. Simulated annealing and particle swarm optimization are the most efficient methods when studying equivalence problems.