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Development of a Methodology for Toxic and Flammable Gases Sensors Positioning in Oil Platforms

Giordhanne Bruno Carpaneda Gimenes1, Patrícia Carneiro dos Santos1, Valter César de Souza1, Aristeu Da Silveira Neto2, and Solidônio R. de Carvalho2. (1) Chemtech - A Siemens Company, Rio de Janeiro, Brazil, (2) Universidade Federal de Uberlândia (UFU), Uberlândia/MG, Brazil

Computational fluid dynamics (CFD) and mechanical systems optimization concepts are currently quite important tools for engineering problems analysis. A typical application of such tools is gas dispersion studies, a theme of great importance for the oil and gas industry. An important safety item for oil and gas production installations (especially oil rigs) is the use of flammable and/or toxic gas sensors to detect gas leaks capable of starting fires, explosions and causing toxic exposure. Importance of these sensor rules may be evaluated if one considers all potential costs of compensations, environmental impacts, life loss and profit loss.

This work presents the development of a computational tool that supplies optimum position and number for gas detectors in an oil platform. Associating CFD simulation results with coherent mathematical treatment, this methodology presents improvements in relation to other studies of gas dispersion and sensor positioning. This mathematical treatment supported by this computational tool is responsible for all calculation methods and for the display of graphical results of the locations to place detectors both for toxic (hydrogen sulfide, for instance) and flammable (like methane) gases.

Gas detection projects are usually based on standards and technical notes that do not supply all necessary information for proper sensor positioning. In the same way, although qualitative methodologies are used intensively and are quite accepted, they are not so accurate because, in most cases, final decision is based on personal analysis and previous experience. Although experience will always remain an important asset in this kind of service, development of such a computational tool as the one described in this paper will reduce project schedules, besides providing more accurate and less intuitive results.