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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- School of Health Information Mgt (Uch, Ibadan), Oyo State 5
- School of Health Information Mgt, Oau Teaching Hospital, Ile-Ife, Osun State 30
- Skyline University Nigeria, Kano, Kano State 2
- Sokoto State University, Sokoto, Sokoto State 43
- St. Albert The Great Major Seminary, Abeokuta. (affl. To University of Benin) 1
- Sule Lamido University, Kafin Hausa, Jigawa State 4
- Tai Solarin University of Education, Ijagun, Ogun State 18
- Tansian University, Oba, Anambra State 1
- Taraba State University, Jalingo, Taraba State 32
- Temple-Gate Polytechnic, Osisioma, Abia State 1