%0 Conference Paper
%A Arif, A.
%A Asirvadam, V.S.
%A Karsiti, M.N.
%D 2011
%F scholars:1673
%K Controlled source; Data sets; Electromagnetic methods; Forward modeling; Hidden layers; Hydrocarbon layers; Input layers; Multi-physics; multilayer perceptron; Output layer; Performance comparison; Radial basis functions; RBF Network; Sea floor; Simulation software, Computer software; Data handling; Electromagnetism; Hydrocarbon refining; Hydrocarbons; Neural networks; Radial basis function networks; Sustainable development, Electromagnetic logging
%R 10.1109/NatPC.2011.6136385
%T Forward modeling of seabed logging with controlled source electromagnetic method using radial basis function networks
%U https://khub.utp.edu.my/scholars/1673/
%X 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.
%Z cited By 1; Conference of 3rd National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011 ; Conference Date: 19 September 2011 Through 20 September 2011; Conference Code:88531