A Deterministic Approach to Measurement of Noise Attenuation in Oil-Rig Drill Ship Positioning Systems
Automation, Control and Intelligent Systems
Volume 4, Issue 3, June 2016, Pages: 59-65
Received: May 30, 2016; Accepted: Jun. 12, 2016; Published: Jun. 29, 2016
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Authors
E. C. Obinabo, Department of Electrical and Electronic Engineering, Ambrose Alli University, Ekpoma, Edo State, Nigeria
T. C. Nwaoha, Department of Marine Engineering, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria
F. I. Ashiedu, Department of Mechanical Engineering, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria
C. O. Izelu, Department of Mechanical Engineering, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria
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Abstract
This paper presents a qualitative evaluation of wave-induced motions in an oil-rig drill ship positioning system which incorporates a priori knowledge of noise contamination in the measured data. The noise contamination β defined in the function of the known form (P (X, β )) and X takes the specific values z, which from Cramer-Rao bound, gives the smallest possible variance with which the estimate of β can be determined. A conceptual model of the problem based on the maximum likelihood techniques in terms of joint probability distribution functions enhanced convergence of the iteration process. A filter was postulated to define the error covariance matrix which yielded unbiased estimates of the measured data.
Keywords
Wave-Induced Motions, Oil-Rig Drill Ship, Maximum Likelihood, Error Covariance Matrix, Noise Attenuation, Filter, Minimum Variance Estimate, Error Covariance Matrix, Iteration Process
To cite this article
E. C. Obinabo, T. C. Nwaoha, F. I. Ashiedu, C. O. Izelu, A Deterministic Approach to Measurement of Noise Attenuation in Oil-Rig Drill Ship Positioning Systems, Automation, Control and Intelligent Systems. Vol. 4, No. 3, 2016, pp. 59-65. doi: 10.11648/j.acis.20160403.12
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Grimble M. J. (1981). Adaptive Kalman Filter for Control Systems with Unknown Disturbance IEE Proc. 128, pt. D, 6, 263–267.
[2]
Kalman, R. E. (1960). A new approach to linear filtering and prediction problems, Trans. ASME J. Basic Eng., 82, 35–45.
[3]
Ekejiuba, A. O. M. (1986). Locating By-passed Hydrocarbon Accumulation in Old Reservoirs, Nigerian Association of Petroleum Explorationists, Fourth Annual Conference.
[4]
Ahonsi, B. and Gdula, J. (1993). A Case History of By-passed Oil in the Niger Delta, Society of Petroleum Engineers, Nigeria Council, 35–46.
[5]
Weber, K. J. (1971). Sedimentological Aspects of Oil Fields in the Niger Delta, Goelogie en Mijnbouw Sc., 559–576.
[6]
Dalley, R. M., Gevers, E. C. A. Stamfli, G. M. Davies, D. J. Gastaldi, C. N. Ruijtenberg, P. R. and Vermeer, G. I. O. (1989). DAZIL (Dip Azimuth, Illumination), First Break, 7 (3), 86–100.
[7]
Esho, K. M. (1993). Prediction of Remaining Oil in the Imo River D2.0 Sand Using 3D Seismic Data, Society of Petroleum Engineers, Nigeria Council, 23–28.
[8]
Van Wagoner, J. C., Mitchum, R. M. K. Campion, M. and Rahmanian, V. D. (1990). Siliciclastic Sequence Stratigraphy in Well Logs, Core and Outcrops: Concept for High-Resolution Correlation of Time and Facies, AAPC Methods in Exploration Series, No. 7.
[9]
Weber, K. J. (1986). Hydrocarbon Distribution Patterns in Nigeria Growth Fault Structures Controlled by Structural Style and Stratigraphy, Journal of Petroleum Science and Engineering, 1, 91–104.
[10]
Benato, G., D’Andrea, V., Cattadori, C., and Riboldi, S. (2015). Improvement of the GERDA Ge detectors energy resolution by an optimized digital signal processing, Physics Procedia, 61, 673-682.
[11]
Lépy, M. C., Cissé, O. I., and Pierre, S. (2014). Comparison of digital signal processing modules in gamma-ray spectrometry” Applied Radiation and Isotopes, 87, 402-406.
[12]
Seyfried, D., Brueckner, S., and Schoebel, J. (2014). Comparison of antenna dispersion and digital signal processing effects in ultrawideband ground penetrating radar systems, Journal of Applied Geophysics, 101, 20-26.
[13]
Hsiao C. H. and Wang, W. J. (2000). State Analysis and Parameter Estimation of Bilinear Systems Via Haar Wavelets, IEEE Trans. on Circuits and Systems 1: Fundamental Theory and Applications, 47 (2), 246–250.
[14]
Hong, L., Girsang, I. P., Dhupia, J. S. (2016). Identification and control of stick–slip vibrations using Kalman estimator in oil-well drill strings, Journal of Petroleum Science and Engineering, 140, 119-127.
[15]
Tan, C., Dai, W., Yeung, H., and Dong, F. (2015). A Kalman estimation based oil–water two-phase flow measurement with CRCC, International Journal of Multiphase Flow, 72, 306-317.
[16]
Liu, M., Lai, J., Li, Z., and Liu, J. (2016). An adaptive cubature Kalman filter algorithm for inertial and land-based navigation system, Aerospace Science and Technology, 51, 52-60.
[17]
Athans, M. (1971). The role and use of the stochastic linear quadratic Gaussian problem in control system design, IEEE Trans. Automatic Control AC-16, 529–552.
[18]
Foster, M. R. and Saffman, P. G. (1970). The Drag of a Body Moving Transversely in a Confined Stratified Fluid, Journal of Fluid Mech., 43 (2), 407 – 418.
[19]
Obinabo, E. C. and Ojieabu, C. E. (2010). Measurement Noise Filtration and State Estimation of a Discrete-time Stochastic Process, International Journal of Soft Computing, 5 (2), .
[20]
Bacher, R. A., Gray, W. and Murray–Smith, D. J. (1981). Time Domain System Identification Applied to Non – invasive Estimation Cardiopulmonary Quantities ibid, 128 (2), 56–64.
[21]
Ho Y. C. (1962). On the Stochastic approximation method and optimal filtration theory. Journal Math anal Applications, 6, 152–154.
[22]
Sage A. P. (1967). Least Squares Curve Fitting and Discrete Optimum Fitting, IEEE Trans. EDUC. E-10, 1, 29–38.
[23]
Obinabo, E. C. (2015). The Development of Oil-rig Drill Ship Positioning Systems, Bowens Nigeria Limited, Warri, Nigeria, 425.
[24]
Ljung I. (1979). Asymptotic behaviour of the extended Kalman filter as a parameter Estimation for linear Systems, IEEE Trans, ac-24, 36-50.
[25]
Kochhar, A. K. (1978). Comparison of Stochastic Identification Techniques for Dynamic Modelling of Plastic Extrusion Processes, Proc. Instn. Mech. Engrs., 192 (28), 299–309.
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