  Marine controlled source electromagnetic (CSEM) sensing method used for the
detection of hydrocarbons based reservoirs in seabed logging application does
not perform well due to the presence of the airwaves (or sea-surface). These
airwaves interfere with the signal that comes from the subsurface seafloor and
also tend to dominate in the receiver response at larger offsets. The task is
to 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 problem
scenario is Independent Component Analysis (ICA). Independent component
analysis (ICA) is a statistical method for transforming an observed
multidimensional 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 mixed
signals de-convolution and considered convenient depending upon the nature of
the source and noise model. The results from the FASTICA algorithm are shown
and evaluated. In this paper, we present the FASTICA algorithm for the seabed
logging application.
