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
Crude oil production Nigeria time series analysis ARIMA forecasting oil prices political instability infrastructure OPEC economic impact production votality Niger Delta CBN data energy policy
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