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Marine controlled source electromagnetic (CSEM) sensing method used for thedetection of hydrocarbons based reservoirs in seabed logging application doesnot perform well due to the presence of the airwaves (or sea-surface). Theseairwaves interfere with the signal that comes from the subsurface seafloor andalso tend to dominate in the receiver response at larger offsets. The task isto identify these air waves and the way they interact, and to filter them out.In this paper, a popular method for counteracting with the above stated problemscenario is Independent Component Analysis (ICA). Independent componentanalysis (ICA) is a statistical method for transforming an observedmultidimensional or multivariate dataset into its constituent components(sources) that are statistically as independent from each other as possible.ICA-type de-convolution algorithm that is FASTICA is considered for mixedsignals de-convolution and considered convenient depending upon the nature ofthe source and noise model. The results from the FASTICA algorithm are shownand evaluated. In this paper, we present the FASTICA algorithm for the seabedlogging application.

Independent Component Analysis for Filtering Airwaves in Seabed Logging Application