Forward modeling is an important step in processing data of seabed logging (SBL) with controlled source electromagnetic (CSEM) method to determine the location and dimension of a hydrocarbon layer under the seafloor. In this research, forward modeling was conducted using a radial basis function (RBF) network, which is an important type of artificial neural networks. To train this RBF network, a data set was generated using a simulation software: COMSOL Multiphysics. The network designed has 3 layers with 3 neurons in the input layer and 1 neuron in the output layer. The single hidden layer contained neurons whose number had been varied between 1 and 20 neurons. The performance comparison showed that the RBF network with 10 neurons in its hidden layer was the best to model SBL with CSEM method. © 2011 IEEE.