Effect of Frequency Variation to Sea Bed Logging using SPLINE Interpolation Technique

This paper discusses on the use of Cubic Spline Interpolation with Mean Square Error (MSE) as tools to process data acquired from in house built simulator and from scaled down experiments that replicate sea bed logging environment. Sea bed logging (SBL) is a new technique that uses marine controlled source electromagnetic (CSEM) sounding technique and is proven to be successful in detecting and characterizing hydrocarbon bearing reservoirs in deep water area. This technique uses resistivity contrast as hydrocarbon reservoirs are known to have resistivity value of 30 – 500 Ωm in contrast to sea water of 0.5 – 2 Ωm and sediments of 1 -2 Ωm. Data collected from this technique is enormous; therefore good processing tools are required. To acquire real data is very costly therefore in house built simulator and scaled experiments are used as source of data. In this work we focus only on frequency variations and how it may affect the electromagnetic wave’s amplitude. Data collected are processed using cubic spline interpolation technique (degree of three) and mean square error (MSE) are calculated between original data and interpolated data. Comparisons are made by studying the MSE trend for data that has no hydrocarbon and with hydrocarbon in the set up. It is found that as the frequency increases, the EM waves amplitude is reduced. It is also found that MSE is higher for data that have hydrocarbon in the set up.