In today's volatile economic climate, comprehensive evaluation of the technical and financial uncertainties associated with all phases of tertiary or Enhanced Oil Recovery (EOR) projects is essential. In the portfolio approach used by major and independent oil producers, various EOR methods are in competition with exploration, drilling and continued secondary operations for limited funds.

A micro-computer-based, Chemical EOR Economics Simulator, (CEES) Model was developed to aid in the evaluations of various chemicals either used individually, or in combination for chemical EOR flooding. Chemicals such as alkalis, polymers, surfactants, sacrificial agents, etc., can be utilized in different chemical slug compositions. The model uses an oil recovery simulator with the option of utilizing a unique Monte Carlo technique to financially quantify the uncertainties associated with various chemical EOR alternatives. Parameters such as:

  1. Oil pricing

  2. Capital and expense escalation

  3. Oil production and decline curves

  4. Total incremental oil production

are allowed to vary in the model. A user, by choice, can select a standard deviation for chosen parameters and allow them to vary randomly along a standard normal distribution. By varying any of these parameters, a project's sensitivity to that key factor can be determined. A cash flow analysis for each year is completed over the duration of the project and is used to produce an internal rate of return. In addition, an incremental internal rate of return is determined when the revenues and expenses attributable to the continued water flood are subtracted from the tertiary project. A single case can be completed or, through the use of multiple runs (1,000+), confidence bands can be established to determine the impact of each key uncertainty factor on the profitability of a proposed chemical flood.

Examples are given to demonstrate the advantages provided by using this tool for initial screening of proposed projects and in evaluating the financial and technical risks associated with close alternatives.

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