Time Series Analysis on Crude Oil Production(a Case Study of Nnpc, 2006-2023)
Student: Aliyu Goni Abubakar (Project, 2025)
Department of Computer Science and Mathematics
Kashim Ibrahim University
Abstract
This study examines the descriptive statistics and time series analysis of crude oil production data, focusing on identifying an appropriate forecasting model. The production data ranged from 0.94MMbpd to 2.88MMbpd with a mean of 1.9764MMbpd and displayed negative skewness(-0.8338) and leptokurtic characteristics (-1.1772). I itial analysis revealed non-stationary, confirmed by KPSS and ADF tests, necessitating first differencing for stationarity. The Autocorrelation and Partial Autocorrelation Function (ACF and PACF) of the differenced series suggested an ARIMA(0,1,2) model as the best fit based on AIC, BIC and HQC criteria. Residual analysis confirmed the adequacy of the model, indicating random residuals. Forecasting results showed a declining trend in production. This study underscores the importance of rigorous statistical metheds for reliable forecasting in crude oil production.
Keywords
For the full publication, please contact the author directly at: aliyuaag2003@gmail.com
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- Hassan Usman Katsina Polytechnic, Katsina, Katsina State 5
- Heritage Polytechnic, Ikot Udota, Akwa Ibom State 46
- Hussaini Adamu Federal Polytechnic, Kazaure, Jigawa State 8
- Ibrahim Badamasi Babangida University, Lapai, Niger State 24
- Igbinedion University, Okada, Benin City, Edo State 2
- Ignatius Ajuru University of Education, Port Harcourt, Rivers State 8
- Imo State Polytechnic, Umuagwo, Owerri, Imo State 3
- Imo State University, Owerri, Imo State 46
- Institute of Management and Technology, Enugu, Enugu State 11
- Isa Mustapha Agwai I Polytechnic, Lafia, Nasarawa State 2