Entity

Time filter

Source Type


Bassi H.V.,Federal University of Rio de Janeiro | Ferreira Filho V.J.M.,Federal University of Rio de Janeiro | Ferreira Filho V.J.M.,Cirrelt Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise | Bahiense L.,Federal University of Rio de Janeiro
Computers and Industrial Engineering | Year: 2012

Some of the most important and expensive activities in the oil field development and production phases relate to using rigs. These can be used for drilling wells, or for maintenance activities. As rigs are usually scarce compared to the number of wells requiring service, a schedule of wells to be drilled or repaired must be devised. The objective is to minimize opportunity costs within certain operating constraints. This paper present the first stochastic approach to deals with the problem of planning and scheduling a fleet of offshore oil rigs, where the service time is assumed being uncertain. A simulation-optimization method is used to generate "expected solutions" and performance measures for rigs, as well as statistics about well allocation to rigs. The methodology can be used in two different ways - to schedule an existing fleet of rigs or to scale the size of the fleet - both contemplating the uncertain nature of the problem. The method's expected results include performance measures for each rig, expected delay for a well to be served, the expected schedule of rigs, and a distribution of the well servicing order. The experiments based on real situations demonstrate the effectiveness of the simulation-optimization approach. © 2012 Elsevier Ltd. All rights reserved.

Discover hidden collaborations