Visualization Of Sediment Thickness Variation For Sea Bed Logging Using Spline Interpolation

This paper discusses on the use of Spline Interpolation and Mean Square Error (MSE) as tools to process data acquired from the developed simulator that shall replicate sea bed logging environment. Sea bed logging (SBL) is a new technique that uses marine controlled source electromagnetic (CSEM) soun...

Full description

Bibliographic Details
Main Authors: Daud, Hanita, Noorhana Yahya, Vijanth Sagayan, Muizuddin Talib
Format: Text
Language:English
Published: Zenodo 2012
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.1075089
https://zenodo.org/record/1075089
Description
Summary:This paper discusses on the use of Spline Interpolation and Mean Square Error (MSE) as tools to process data acquired from the developed simulator that shall 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 very successful in detecting and characterizing hydrocarbon reservoirs in deep water area by using resistivity contrasts. It uses very low frequency of 0.1Hz to 10 Hz to obtain greater wavelength. In this work the in house built simulator was used and was provided with predefined parameters and the transmitted frequency was varied for sediment thickness of 1000m to 4000m for environment with and without hydrocarbon. From series of simulations, synthetics data were generated. These data were interpolated using Spline interpolation technique (degree of three) and mean square error (MSE) were calculated between original data and interpolated data. Comparisons were made by studying the trends and relationship between frequency and sediment thickness based on the MSE calculated. It was found that the MSE was on increasing trends in the set up that has the presence of hydrocarbon in the setting than the one without. The MSE was also on decreasing trends as sediment thickness was increased and with higher transmitted frequency. : {"references": ["E. N. Kong, H. Westerdhal. Seabed Logging: A possible direct hydrocarbon\nfor deepsea prospects using EM energy. Oslo :Oil Gas Journal,\n2002. - May 13, 2002 edition.", "T. Eidesmo, et al. Sea Bed Logging (SBL), A New Method for Remote\nand Direct Identification of Hydrocarbon Filled Layers in Deepwater\nAreas using Controlled Source Electromagnetic Sounding, Technical\nArticle, First Break Volume 20, 2002, p. 144-152.", "S. Constable,, L.J.Srnka,An Introduction to Marine Controlled Source\nElectromagnetic Methods for Hydrocarbon Exploration, Geophysics 72,\nno 2, 2007,WA3-WA12", "Dirk Smit, Pal R. Wood, Experience is crucial to expanding CSEM use,\nWorld Oil, September 2006, pg 37-43.", "S. Ellingsrud, T. Eidesmo, M. C. Sinha, L.M. MacGregor, S. C. Constable.\nRemote Sensing of Hydrocarbon Layers by Sea Bed Logging (SBL):\nResults from a Cruise Offshore Angola, Leading Edge 20(10), 2002, pp\n972-982.", "Anwar Bhuiyan, Tor wicklund, Stale Johansen, High Resistivity Anomalies\nat Modgunn Arch in the Norwegian Sea, Technical Article, first break\nvolume 24, January 2006", "N.O. Sadiku, \"Numerical methods in Electromagnetics\", second edition,\nMathew, Boca Raton London New York Washington, D.C. (2001).", "Cox, C.S. Constable, S.C., Chave, A.D, Webb S.C.Controlled-source\nElectromagnetic Sounding of the oceanic Lithosphere, Nature Magazine,\n1986, 320, pp 52-54.", "Evan S Um, David L Alumbaugh, Marine CSEM Methods on the Physics\nof the Marine CSEM Method, Geophys. Res. Vol.72, No. 2, pp. 13 - 18,\n2007.\n[10] N Nasir, A Shafie, H Daud, H M Zaid, N Yahya, M N Akhtar, M Khasif,\nMagnitude Versus Offset (MVO) Study with EM Transmitter in Different\nResistive Medium, Journal of Applied Sciences 11 (7), pp. 1309-1314,\n2011\n[11] Ulaby Fawwaz T. Electromagnetics for Engineers. New Jersey : Pearson\nEducation, 2005.\n[12] L.M.MacGregor, M.Tompkins, Imaging Hyrocarbon Reservoirs using\nMarine Controlled-Source Electromagnetic Sounding, in Offshore Technology\nConference, 2-5May 2005, paper OTC 17163.\n[13] Daud, H., Yahya, N., Asirvadam, V. Development of EM simulator for\nsea bed logging applications using MATLAB Indian Journal of Marine\nSciences 40 (2), pp. 267-274, 2011\n[14] Sky McKinley, Megan Levine, Cubic\nSpline Interpolation, available online at\nhttp://online.redwoods.cc.ca.us/instruct/darnold/laproj/Fall98/SkyMeg/Proj.\nPDF (Accessed on 30/08/2010)\n[15] C. de Boor, A Practical Guide to Splines, 1978, Springer-verlag, New\nYork.\n[16] JM. Unser, Splines: A Perfect Fit for Signal and Image Processing, 1999,\nIEEE Signal Processing Magazine, Vol 16, pp 22-38\n[17] Panayiotis Foteinopoulos, Cubic spline interpolation to develop contours\nof large reservoirs and evaluate area and volume, 2009, Journal of\nAdvances in Engineering Software 40, pp 23-29.\n[18] M Sarfaz, Malik Zawwar Hussain, Data visualization using rational\nspline interpolation, Journal of Computational and Applied Mathematics\n189 (2006) pgp 513-525.\n[19] JM. Unser, Splines and Wavelets: New Perspectives for Pattern Recognition,\n2003, pp 244-248, Springer-Verlag Berlin Heidelberg.\n[20] E.L. Lehmann; Casella, George (1998). Theory of Point Estimation (2nd\ned.). New York: Springer"]}