Quantitative tools integration in the portfolio selection of petroleum production projects

Author(s)

Rafael Costa Galeno

• Document type: Master's Dissertation
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Mecânica
• Defense date: 2008-07-30

Examining board members

Saul Barisnik Suslick; Denis José Schiozer; Francisco Nepomuceno

• Advisor: Saul Barisnik Suslick

Abstract

One of the main impacts of the new technological progress in the petroleum companies is the increasing number of projects in E&P portfolios competing in a company's budget constraint. Despite of the increase of oil prices, several types of restrictions (workforce, rigs, materials, etc.) occurs in the project management, making the decision process of projects selection a complex task. In this dissertation was developed an integrated solution for analysis of E&P portfolios projects, considering an exponential model of risk aversion (preference theory) and the characteristics of risk and return, and incorporating new types of metric for projects selection. The methodology used to achieve the portfolio optimization was based on risk minimization for a certain return. The quantitative tool for portfolio optimization was the genetic algorithms. The portfolio selection was build upon different scenarios. Undeveloped oil reserves in deep-waters was used as a casestudy because they present different types of constraints and geological and technological uncertainties in the feasibility analysis. The results of this research allowed the selection of an optimal portfolio using not only the financial restrictions, but also incorporating various types of geological, operational, and technological variables, among others. (AU)

• FAPESP's process: 07/02260-9 - Selection and optimization of oil exploration and production project portfolios using risk aversion models
• Grantee: Rafael Costa Galeno
• Support Opportunities: Scholarships in Brazil - Master