Modified Symbiotic Organism Search (mSOS) for Inversion Time-Domain Electromagnetic Data

Abstract

Abstract One of the most common ways to model central-loop configuration Time-Domain Electromagnetic (TDEM) data is using 1D inversion model. The Born Approximation method used for this study to accommodate problem in calculations and speed of convergence when calculated the TDEM response, meanwhile for inversion modelling of TDEM observation data modified Symbiotic Organism Search (mSOS) was chose, which is one of the global optimization algorithms to accommodate multi-minimum problem ​​in non-linear objective functions, so the optimal global solution is obtained. Inversion modeling was carried out on synthetic and field data to test accuracy in inversion, the accuracy of synthetic data tested based on the capability of the algorithm to retrieve value of synthetic data indicated by small relative error value between synthetic model parameters and calculated model, while for modeling of field data, the accuracy of modeling was depending on consistency when the data was modeling with different number of layer, in addition time to perform inversion are considered evaluate inversion performance. In synthetic data case, the algorithm produced a relatively good model based on the accuracy of the model in terms of misfit values which has a misfit value round about 0%, relative error values, while for field data case the inversion model attain consistency and experienced lessen misfit value when the data was modeled using different number of layer specifically 8.72% for 2-layers model, 3.92% for 3-layers model, and 2.61% for 4- and 5- layers model. According to both data required under 19 minutes for 10.000 iterations.