Modeling Marine Electromagnetic Survey with Radial Basis Function Networks

Journal of ICT Research and Applications

Arif Sasongko¹  Sarwono Sutikno¹  Hidayat¹  Yusuf Kurniawan¹ 

关键词: controlled source electromagnetic method;    forward modeling;    multilayer perceptron;    radial basis function;   

DOI  :  10.5614/itbj.ict.2011.5.2.5

学科分类：电子、光学、磁材料

来源: Institute for Research and Community Services ITB

【 摘 要 】

A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF) network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP) network. By comparing their validation and training performances (mean-squared errors and correlation coefficients), it is concluded that, in this case, the MLP network is comparatively better than the RBF network.

【 授权许可】

Unknown