Author(s)

Jaesung Choi¹, David C. Roberts^2*, EunSu Lee³

¹Transportation and Logistics Program, North Dakota State University, Fargo, USA.
²Department of Agribusiness & Applied Economics, North Dakota State University, Fargo, USA.
³Upper Great Plains Transportation Institute, North Dakota State University, Fargo, USA.

North Dakota’s oil production has been rapidly increasing during the past several years. The state’s oil production in March 2013 even increased to more than twice the quantity produced in March 2011, and the estimated Bakken Formation reserves were reported very large compared with those of the United Arab Emirates. It eventually makes a question to us of how much oil will be able to be actually extracted with currently available technologies. To answer this question, this paper forecasts future oil development trend in North Dakota using the Seasonal Autoregressive Integrated Moving Average (S-ARIMA) model. Nonstationarity derived from a stochastic trend and the abrupt structural change of oil industry was a big potential problem, but through the Quandt Likelihood Ratio test, we found break points, which allowed us to select a model fitting period suitable for the S-ARIMA method to provide accurate statistical inference for the historical period. The seven major oil producing counties were investigated to determine whether the current oil boom was consistent across all oil fields in North Dakota. Empirical estimates show that North Dakota’s oil production will be more than double in the next five years. What we can predict with great certainty is that North Dakota’s influence over domestic and global oil supply systems will increase in the near future, especially over the next five to six years. This is good news for those who are concerned about domestic energy security in the USA.

Bakken Formation, Forecasting, North Dakota, Oil, S-ARIMA

Choi, J. , Roberts, D. and Lee, E. (2015) Forecasting Oil Production in North Dakota Using the Seasonal Autoregressive Integrated Moving Average (S-ARIMA). Natural Resources, 6, 16-26. doi: 10.4236/nr.2015.61003.