In the paper two global optimization methods called FGA (Float-Encoded Genetic Algorithm) and Very Fast Simulated Annealing (VFSA) are presented in solving the nonlinear geophysical well logging inverse problem. Applying global optimization for the interpretation of well logging data has got a strong advantage against conventional linear inversion methods. Furthermore, they can even improve the performance of modern inversion methods like the so-called interval inversion method developed by us, which estimates petrophysical parameters more accurately and more reliable than point by point inversion techniques owing to an effective joint inversion procedure. Moreover, it gives an estimate for the layer-thicknesses that can not be treated as unknowns in the conventional point by point well logging inversion. In the paper, we make a comparison between global interval inversion techniques using synthetic and measured well logging data.


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