Forward modeling of seabed logging with controlled source electromagnetic method using multilayer perceptron

Forward modeling is an important step in processing data of seabed logging (SBL) with controlled source electromagnetic (CSEM) method to determine the location of a hydrocarbon layer under the seafloor. In this research, forward modeling was conducted using a multi layer perceptron (MLP), which is an important type of artificial neural networks. To train this MLP, a data set was generated using simulation software: COMSOL Multiphysics. The MLP designed has 3 layers with 3 neurons in input layer and 1 neuron in output layer. The single hidden layer contained neurons whose number had been varied between 3 until 15 neurons. The performance comparison showed that the MLP with 10 neurons in its hidden layer was the best to model SBL with CSEM method.