ESTIMATION OF OIL SPILLAGE AND SALVAGE REVENUE IN KOKORI OIL FIELD USING NUMERICAL METHODS AND PYTHON ALGORITHM
machine Learning
Abstract
The study aimed to estimate oil spillage in the Kokori Oil Field, discovered in 1958, using a linear model. The field has 23 oil wells and produced 383 million barrels of oil. A linear model was developed using Python programming, comparing it with the trapezoidal method and salvage revenue. Results showed a linear relationship between oil spill quantity, duration, and mitigation measures. This study provides a valuable model for estimating oil spillage in the Kokori oil field, emphasizing the importance of accurate estimation for environmental and economic purposes. The study presents a comprehensive model for estimating oil spillage in the Kokori oil field, emphasizing the significance of accurate estimation for environmental and economic purposes. The correlation coefficient value supports the model's sufficiency, and the calculated salvage revenue indicates a commendable projected value for the Kokori oil field at its end of use. Salvage revenue is the estimated value of an asset at the end of its useful life, which is crucial in determining the cost of goods sold and depreciation charge. It lowers the asset's cost, influences its usable life, resale value, and replacement cost. Salvage revenue is calculated by subtracting revenue generated without mitigation measures from revenue realized with mitigation measures.
References
Abdulmumini A. K., Obunadike G., & Jiya E. (2022). Predictive Model for Child Delivery. FUDMA Journal of Sciences, 6(1), 141 - 145. https://doi.org/10.33003/fjs-2022-0601-885 DOI: https://doi.org/10.33003/fjs-2022-0601-885
Adamu J., Momoh O. M., Tor N. E. T., Ukwu H. O., Aliyu J., Saleh B., & Ahemen T. (2023). The Haematological Parameters of Donkeys in Sahel Agro-Ecological Zone of Nigeria based on Sex and Breeds. FUDMA Journal of Sciences, 7(6), 8 - 11. https://doi.org/10.33003/fjs-2023-0706-2094 DOI: https://doi.org/10.33003/fjs-2023-0706-2094
Agboola S.O., Adebiyi O.O., & Obaromi D. A. (2023). Application of Single Step Euler and Trapezoidal Methods of Solving Transient Distribution in Markov Chain in Curve. Nigerian Journal of Pure and Applied Science. Vol.38 (2).
https://doi.org/10.48198/NJPAS/23.A08 DOI: https://doi.org/10.48198/NJPAS/23.A08
Atajeromavwo E. J., Yoro R. E., Ofuyekpone O. D., Ukpenusiowho D., & Ugbosu C. (2024). Python-Based Population Forecasting for Delta State: Trapezoidal and Integration Method. FUDMA Journal of Sciences, 8(3), 112 - 118. https://doi.org/10.33003/fjs-2024-0803-2372
Atajeromavwo E.J., Nwabudike. A.A., Eti. F., & Onavwie E.C. (2015). An Approach for Population Forecasting: A case Study of Nigeria Population Census. Journal of the Nigerian Association of Mathematical Physics Vol.32
Atajeromavwo E.J., Nwabudike A.A., Osazuwa L.0., & AKazue E.C. (2021). A comparative Analysis of Population Model Using Discrete and Natural Model: Case Study of Delta State Polytechnic, Ogwashi –Uku. Journal of the Nigerian Association of Mathematical Physics Vol.61 (July-September 2021 Issue), pp23-30
Gupta, S. (2010). Comparison of Numerical Methods for Area curve. Journal of Mathematics Modellings and Algorithms.
Maikano F. A. (2024). Machine Learning Approaches For Cyber Bullying Detection In Hausa Language Social Media: A Comprehensive Review And Analysis. FUDMA Journal of Sciences, 8(3), 344 - 348. Retrieved from
https://fjs.fudutsinma.edu.ng/index.php/fjs/article/view/2517
Mba I. C., Mba E. I., Ogbuabor J. E. & Arazu O. (2019). Causes and Terrain of Oil Spillage in Niger Delta Region of Nigeria: The Analysis of Variance Approach. International Journal of Energy Economics and Policy. https://doi.org/10.32479/ijeep.7352.
Miller. G. (2023). Numerical Analysis for Engineers and Scientists. Cambridge University Press https://www.cambrige.org.>books
National Oil Spillage Detection and Response Agency (NOSDRA) (2021). A Government Agency for Oil Spillage Monitoring and Detection. https://www/premium
NnajiJ. C., OmotugbaS. K., AmpitanA. T., BabatundeK. O., & OluwoleE. A. (2023). Review of Nanomaterials for Remediation of Petroleum Impacted Soil and Water. FUDMA Journal of Sciences, 3(4), 276 - 284. Retrieved from https://fjs.fudutsinma.edu.ng/index.php/fjs/article/view/1648
Olofintuyi S. S. (2023). Breast Cancer Detection with Machine Learning Approach. FUDMA Journal of Sciences, 7(2), 216 - 222. https://doi.org/10.33003/fjs-2023-0702-1392 DOI: https://doi.org/10.33003/fjs-2023-0702-1392
Olujobi, O, J., Oyewunmi O, A., Oyewunmi A, E. (2018). Oil Spillage in Nigeria Upstream Petroleum Sector: Beyond the Legal frameworks. International Journal of Energy Economics and Policy, Vol. (8(1). 220-226. https://doi.org/10.32479/ijeep.7352.
Rufai M. A., Abdullahi M. B., Abisoye O. A., & Ojerinde O. A. (2024). Utilizing a Fusion of Machine Learning Techniques for Diabetes Mellitus Subtypes Classification and Identification. FUDMA Journal of Sciences, 8(3), 331 - 343. https://doi.org/10.33003/fjs-2024-0803-2510
Singh, R. (2010). Efficiency of Trapezoid for Area under curve. Journal of Applied Mathematics and Computation, 217 (2), 655-665.
Vanguard Newspaper, July 20th, 2020. Oil spillage in Niger Delta
Wang Y. (2015). Limitations of Trapezoid Method for Area under Curve. Journal of Numerical Analysis and Applications, 18 (2), 155- 165.
Wang Z, Fingas. M. & Sigoin (2001). Characteristics and identification of “Mystery of Oil Spill” from Quebec (199). Journal of Chromatography 909: 155-169. DOI: https://doi.org/10.1016/S0021-9673(00)01084-0
Copyright (c) 2024 FUDMA JOURNAL OF SCIENCES
This work is licensed under a Creative Commons Attribution 4.0 International License.
FUDMA Journal of Sciences
