Time Series Analysis Model for Production and Utilization of Gas (A Case Study of Nigeria National Petroleum Corporation “Nnpc”)
H. R. Bakari
Abstract
Open-access reader
H. R. Bakari
Abstract
Open-access reader
Time series analysis and forecasting has become a major tool in different applications for the private sector.Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average).In this study we used Box-Jenkins methodology to build ARIMA model for annual production and utilization of gas from Nigeria National Petroleum Company (N.N. P. C.) for the period from 1970-2004.After the model specification; the best model for production was ARIMA (1, 1, 1) and for utilization was ARIMA (0, 1, 1).These models were used to forecasting the production and utilization of gas for the upcoming 4 years to help decision makers establish priorities in terms of gas demand management.An intervention time series analysis could be used to forecast the peak values of production and utilization data.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Time series analysis and forecasting has become a major tool in different applications for the private sector.Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average).In this study we used Box-Jenkins methodology to build ARIMA model for annual production and utilization of gas from Nigeria National Petroleum Company (N.N. P. C.) for the period from 1970-2004.After the model specification; the best model for production was ARIMA (1, 1, 1) and for utilization was ARIMA (0, 1, 1).These models were used to forecasting the production and utilization of gas for the upcoming 4 years to help decision makers establish priorities in terms of gas demand management.An intervention time series analysis could be used to forecast the peak values of production and utilization data.
Key concepts: Corporation, Production (economics), Series (stratigraphy), Mathematics, Petroleum, Petroleum engineering, Engineering, Business