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Title:Spatio-Temporal Estimates of Long-Term Oil Drilling Locations
Authors:EunSu Lee, Nimish Dharmadhikari, and Alan Dybing
Publication Date:Oct 2014
Report #:DP-275
TRID #:01544662
Keywords:estimating, forecasting, logistic regression analysis, oil well drilling, spatial analysis, transportation planning, trucking
Type:Research Report – Department Publications



Estimating drilling locations plays an important role in forecasting truck trips derived by hydraulic fracturing oil development for long-range transportation planning. Predicting drilling locations among more than 7,000 oil drilling lands shows a random pattern with uncertainty. Twenty-year multi-period forecasting architecture is proposed in this study using maximum likelihood estimation to fit in the logistic regression. Probability of drilling on each leased space for drilling was predicted in order to forecast truck movements with respect to frequency and paths for a 20-year period. The maximum likelihood estimates of the parameters of a logistic model provide future locations for drilling considering well aging, the number of wells on a leased land space, closeness to the current wells, and oil density in an oil development zone. While, in the short term, the drilling locations were concentrated in the middle of the space, the probability of the drilling was marginally distributed throughout the region in the long run.

How to Cite

Lee, EunSu, Nimish Dharmadhikari, and Alan Dybing. Spatio-Temporal Estimates of Long-Term Oil Drilling Locations, DP-275. North Dakota State University, Fargo: Upper Great Plains Transportation Institute, 2014.

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