A Scaled Experiment 2 for Verification of SPLINE Interpolation Technique for Sea Bed Logging Method
This paper discusses series of experiments conducted in a scaled model tank that replicates sea bed logging (SBL) environment with various parameter settings which includes present and absent of hydrocarbon for data acquisition purposes. A scaled tank with a scale factor of 2000 was built to replica...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/7838/1/4524_001.pdf http://www.scopus.com http://eprints.utp.edu.my/7838/ |
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| Summary: | This paper discusses series of experiments conducted in a scaled model tank that replicates sea bed logging (SBL) environment with various parameter settings which includes present and absent of hydrocarbon for data acquisition purposes. A scaled tank with a scale factor of 2000 was built to replicate the SBL environment and water resistivity, frequency, and amplitude of transmitted electromagnetic (EM) waves were varied. Aluminum rod was used as transmitter and was connected to a function generator that transmitted square waves. Magnetic field generated by EM source was detected by fluxgate magnetic field sensor and sent to data acquisition station. Data acquired from series of experiments were processed using Spline Interpolation Technique (degree of three) and Mean Square Error (MSE) were calculated between original data and interpolated data. The MSE calculated were used to distinguish the set up that contained hydrocarbon than the one without hydrocarbon. It is known that existence of hydrocarbon shall increase magnitude of received EM wave due to contribution from refracted transmission of electromagnetic signals via high resistivity hydrocarbon reservoir. Comparisons were made by studying the trends and relationship between this data. It is found that the MSE is on increasing trends in the experiments that involved the presence of hydrocarbon in the setting than the one without. This shall give indication that combination of spline interpolation and mean square error can be used as new techniques in processing CSEM data. |
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