Quick Look Methods of Economic Exploration Portfolio Evaluations and its Exemplary Application on the Prospect Inventory

Thilo Theloy

Research output: ThesisDiploma Thesis

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Abstract

Every year oil companies have to invest larger sums for exploration projects as the remaining petroleum reserves are more and more located in environmentally difficult areas. Therefore it is essential for these companies to make the right investment decisions in order to enhance the wealth of the company. This leads to an increasing need of valuation methods to help in sorting out the most promising projects. These methods range from simple discounted cash flow analysis to more sophisticated methods which incorporate the individual risk of each project as well as simulation tools which help to get insight into the true up- and downsides of a venture. Finally the interrelationship between projects within a portfolio can be analyzed to optimize the selection process. This thesis is based on the need of finding an appropriate method to determine an indicative value of each project, especially at an early stage of exploration where the uncertainties of the geological and geophysical input parameters are very high. Another aspect is to develop approaches to determine the attractiveness of a project within a short timeframe. In the course of these objectives, this work compares different evaluation methods on their accuracy as well as the influence of the oil price on the value of different projects. In addition two evaluation methods used by oil companies are presented. Finally several proposals are made for quick look evaluation tools and portfolio ranking factors.
Translated title of the contributionSchnellbestimmungsmethoden zur wirtschaftlichen Bewertung von Explorationsprojekten und ihre beispielhafte Anwendung
Original languageEnglish
QualificationDipl.-Ing.
Supervisors/Advisors
  • Staber, Stephan, Supervisor (internal)
Award date30 Mar 2007
Publication statusPublished - 2007

Bibliographical note

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Keywords

  • Prospect Exploration Production Forecasting Portfolio Ranking Evaluation Monte Carlo

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