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Prediction of Oil Depletion in Ghana Based on Hubbert's Model

Author

Listed:
  • Dennis Nchor

    (Department of Statistics and Operations Analysis, Mendel University in Brno, Zemědělská1, 613 00 Brno, Czech Republic)

  • Václav Klepáč

    (Department of Statistics and Operations Analysis, Mendel University in Brno, Zemědělská1, 613 00 Brno, Czech Republic)

Abstract

This study seeks to fulfil four specific tasks: to predict the year of peak oil production in Ghana, to estimate the quantity that will be produced at this peak point, to investigate the year of total oil depletion and last but not the least is to assess the total recoverable oil resources at the point of depletion. The study applied Hubbert's model of oil production and depletion. There was however modification to the approach in that Nonlinear Least Squares were used to estimate the logistic growth parameter instead of linear regression techniques. The modification was due to the fact that the historical data of oil production in Ghana did not follow a linear trend. The study acknowledges the influence of technology, economic, and political factors in the shorter time scales but hypothesizes that the amount of recoverable oil resources dominates all other factors in the long run. Hence the focus was placed on physical or geological constraints. The study results show that peak production in Ghana will occur in 2022. A maximum of about 100 million barrels will be produced per year though currently the annual production is about 40 million barrels. The predicted logistic curve also shows that total oil will be depleted by 2060. Ghana has total recoverable oil resources of about 1.8 billion. The data for the study was obtained from the U.S Energy Information Administration covers the period of production from 1992 to 2014.

Suggested Citation

  • Dennis Nchor & Václav Klepáč, 2016. "Prediction of Oil Depletion in Ghana Based on Hubbert's Model," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 64(1), pages 325-331.
    • Handle: RePEc:mup:actaun:actaun_2016064010325
    DOI: 10.11118/actaun201664010325
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    References listed on IDEAS

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