Using the memetic algorithm to determine the depths of sedimentary basins by 2-D gravity modeling - L.P. Toan; D.V. Liet (International Association of Lowland Technology, 2015)
In this article, the memetic algorithm using gravity data is applied to determine the thickness of a 2-D sedimentary basin whose density contrast varies with depth as a parabolic function. This memetic algorithm is a combination of the genetic algorithm and the Nelder-Mead Simplex local search to find optimal global solutions based on the minimum of the objective function, which is the total of data misfit  d and the ‘norm’ model  m and the second term is multiplied by the weight parameter namely a Tikhonov regularization. The program is written in Matlab. Firstly, it was tested on a synthetic model and the interpretable results are coincident with the model. Then, it was applied on An Giang and Dong Thap gravity anomalies in the Mekong Delta, Southwest of Vietnam, where the density contrast’s function of sediment layers was found from the density contrasts of each layer of CL-1 well’s stratigraphic column. The results showed that for both An Giang and Dong Thap anomalies, the observed and calculated gravity anomalies were fitted well, but the difference between the calculated depths using the memetic algorithm and the forward modeling method is slight because the approach to the solution of each method is different.