doctoralThesis
Método Fuzzy Payoff modificado para valoração de opções reais com aplicação em abandono de campos de petróleo
Fecha
2019-02-04Registro en:
BORGES, Roberto Evelim Penha. Método Fuzzy Payoff modificado para valoração de opções reais com aplicação em abandono de campos de petróleo. 2019. 57f. Tese (Doutorado em Ciência e Engenharia de Petróleo) - Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, 2019.
Autor
Borges, Roberto Evelim Penha
Resumen
The decision whether or not to abandon an oil-producing field is complex. The
uncertainty inherent to the estimates used as premises makes that only the passage of time points
out whether the decision made was correct. However, companies need to make this decision
continuously, based on the information and techniques available at the time of evaluation. The
valuation of a petroleum field considering the abandonment real option is a modern way of
supporting such a decision. Unlike traditional techniques, such as discounted cash flow, which
only consider average values in valuation, the analysis of real options contemplates the possible
values that the estimated variables can assume. The Fuzzy Payoff Method (FPOM) is a
technique that simplifies complex traditional solutions for valuation of real options, since it is
based on scenarios and fuzzy logic. During this work, an inconsistency was identified in the
original FPOM: in some cases, it results in a value of the project with real options smaller than
the value of the same project without real option. In order to overcome this issue, the Center of
Gravity Fuzzy Payoff Method (CoG-FPOM) was developed and presented, which has been
shown to be consistent for any problem and type of fuzzy number. Hence, the model intended
to support the oilfield abandonment decision proposed here has the CoG-FPOM in its core. The
results obtained with the application of the model show the expected conceptual advantage and
the value added by the analysis of real options in the abandonment decision. By using scenarios
and fuzzy logic, the model achieves simplicity and ease of implementation, allowing the
industry's interest.