Withers, B.E., 1983, A simulation model of oil and gas development on the North Slope of Alaska: University of Colorado, Boulder, Ph.D. dissertation, 191 p., charts, maps.
The development of oil and gas resources in the Alaskan Arctic has created demands for several other natural resources which are scarce and environmentally sensitive. State policy-makers, faced with the responsibility for managing all of Alaska's resources, needed information and analytical tools for assessing these hydrocarbon related resource demands and for developing appropriate oil and gas leasing policies. This study develops a tool to forecast water and gravel requirements, two critical resources, associated with proposed hydrocarbon leases. Since water and gravel requirements are partly a function of workforce, forecasts of manpower requirements are also generated. A computer model was developed to simulate the hydrocarbon development system on the North Slope of Alaska. The model, based on technical relationships and assumptions developed from the available Arctic experience to date, evaluates annual manpower, water, and gravel requirements by phase of oil development activity. Parameter values for potential reservoir sizes were developed for this study using inputs from industry 'experts.' The purpose of the model is to analyze the Arctic oil development system. To achieve this purpose, four experiments were conducted on the model: a 'no discovery' scenario, a 'most likely' discovery scenario, and two sensitivity analyses on critical parameters. Output from these experiments provided detailed manpower, water, and gravel requirements and oil production for each proposed lease location. In addition, a summary oil production schedule for all lease locations within a scenario was produced. Output indicated the 'no discovery' scenario results were a function of whether the location is onshore or offshore and Native or non-Native owned. Output from the 'most likely' discovery scenario reported requirements associated with the various combinations of parameter values for the twelve locations. The sensitivity analysis revealed that the output variables are insensitive to changes in field depth. Changes in field sizes, however, resulted in reasonable changes in the output variables, suggesting there may be some economies of scale associated with increasing field sizes.
Theses and Dissertations
