M.Com. (Business Management) / Exploration, by its very natura, is a risky business; yet, because of the big rewards, it is a business in which huge amounts of money are invested world wide in spite of the risks involved. Success in exploration today, with fluctuating, unpredictable commodity markets, belongs to those operators who can assess the risks involved best, not only the geological, but also economic and financial risk elements. Risk stems from uncertainty, and it is in the recognition and description of uncertainty that the exploration .management can quantify those risks involved in their area of operation, and so minimise their exposure to risk. Because of incomplete knowledge, risk can never be eliminated, but by understanding the extent of uncertainty, Qecision ma~ing in the presence of risk can be optimised. A very important tool in the descriptidn of uncertainty is statistics. The first chapter of this dissertation is therefore spent on a summary of the most important statistical principles used in the description of populations of data. Since the method of analysis suggested in this study is illustrated as applied to hydrocarbon exploration, the next chapter is devoted to a brief description of the calculation of hydrocarbon reserves. Starting with the assumption of complete knowledge, the following geological factors important in the calculation of recoverable hydrocarbon reserves, are introduced: hydrocarbon source rock, reservoir rock, hydrocarbon trap (or structure), seal or caprock, and migration path. The terms porosity, permeability and nett reservoir to gross rock volume are also defined. A method of dealing with risk in each of these factors is demonstrated, by starting with the assumption of complete knowledge, and then gradually introducing uncertainty in the calculation of reserves. The method finally consists of estimating a minimum possible value for each geological factor, a most likely value and a maximum possible value, using statistics, or subjective judgement (depending on the extent of available data). The triangular factor distributions so formed are then combined by way of simulation into a distribution for·recoverable reserves...
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:3732 |
| Date | 10 February 2014 |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Johannesburg |
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