This work presents the conception, modeling and development of an E&P projects economical analysis system under uncertainty that integrates the following modules:
an optimization hybrid system for oilfields development based in evolutionary algorithms with distributed evaluation, proxies and use of quality maps to optimize the place and quantity of wells in a delimited petroleum field to maximizing the NPV of the alternative. Also, this system considers some technical constrains as the minimum wells distance and maximum wells trajectory.
a model based on Genetic Algorithms and Monte Carlo simulation designed to find an optimal decision rule for some oil field development alternatives obtained from previous module, considering market uncertainty (oil price), that may help decision-making with regard to: developing a field immediately or waiting until more favorable market conditions.
In the economic analysis also is considered, for each alternative under evaluating, the option of investment in information taking in account interactions of different uncertainties types. This analysis considers the option of future production expansion by installing an additional well under reserve volume uncertainties in the in the area to be drained by the additional well.
Some computational intelligence techniques were applied in this system as: evolutionary algorithms, neural networks and fuzzy numbers; also, the system uses other techniques as Real Options and Monte Carlo Simulation to treat uncertainties.
The obtained outcomes show the benefits to have an integrated decision support system to the decision-making in the economic analysis of oilfields development.
To analyze the option to develop some previously delimited petroleum field request investments which dimensions and benefits depend on the alternative being chosen. Some alternatives have different quantity and of the wells. The wells are vertical, horizontal or multilateral with several costs and benefits. The combination with other aspects as: platform type, recuperation method, production system, drills system, lifting, etc. becomes this problem more complex to optimize. Moreover, the alternatives of invest in information or just waiting for better market conditions will be considered. Also, it is necessary to consider the flexibility in the oilfield development, in order to incorporate a production increment (expansion option) by optional wells, depending on the market conditions and the reservoir behavior in the early months or years of production.
This is a typical complex and combinatorial optimization problem to need attend some constrains. Evolutionary optimization methods  are promissory in this kind of problem.
This problem searchs the alternative that maximizes the Net Present Value under uncertainties, this alternative must attend the technical constrains and consider technical and market uncertainties.