Monte Carlo simulation applied to 5-year recertification projects in surface equipment for drilling offshore oil wells
Several project management tools may be applied in oil and gas industry. The PERT tool, also known as estimate of three points, uses specialists’ info to calculate the duration of project schedule tasks, taking into consideration optimistic, most likely, and pessimistic scenarios, all of them relate...
| Authors: | , |
|---|---|
| Format: | article |
| Status: | Published version |
| Publication Date: | 2023 |
| Country: | Brasil |
| Institution: | Universidade Nove de Julho (UNINOVE) |
| Repository: | Revista Gestão e Projetos (GeP) |
| Language: | Portuguese |
| OAI Identifier: | oai:ojs.periodicos.uninove.br:article/23452 |
| Online Access: | https://periodicos.uninove.br/gep/article/view/23452 |
| Access Level: | Open access |
| Keyword: | Oil and gas Drilling Project management Risks Schedule Critical path PERT Simulation Monte Carlo Petróleo e gás Perfuração Gerenciamentos de projetos Riscos Cronograma Caminho crítico Simulação |
| Summary: | Several project management tools may be applied in oil and gas industry. The PERT tool, also known as estimate of three points, uses specialists’ info to calculate the duration of project schedule tasks, taking into consideration optimistic, most likely, and pessimistic scenarios, all of them related to project’s risks and uncertainty. Monte Carlo Simulation tool proposes a random numbers sampling process, applied throughout project critical path, to predict finishing probabilities within specific dates. This article aims to employ the Monte Carlo simulation as a tool for schedule management, based on risk analysis, applied to five-year recertification projects in surface equipment for drilling offshore oil wells. Therefore, using a combination of PERT and Monte Carlo Simulation tools, combine to other project management concepts, it was possible to perform a probability analysis and obtain a prediction of the project finish scenario, based on its risks and uncertainty analyzed. The results have shown the project original schedule had low chances of finishing within time stablished and so, the simulation performed contributes for the initial schedule revision and improvement. |
|---|