Drag Reducer Selection for Oil Pipeline Based Laboratory Experiment
- Leksono Mucharam
- Silvya Rahmawati
- Rizki Ramadhani
Oil and gas industry is one of the most capital-intensive industry in the world. Each step of oil and gas processing starting from exploration, exploitation, up to abandonment of the field, consumes large amount of capital. Optimization in each step of process is essential to reduce expenditure. In this paper, optimization of fluid flow in pipeline during oil transportation will be observed and studied in order to increase pipeline flow performance.
This paper concentrates on chemical application into pipeline therefore the chemical can increase overall pipeline throughput or decrease energy requirement for oil transportation. These chemicals are called drag reducing agent, which consist of various chemicals such as surfactants, polymers, nanofluids, fibers, etc. During the application of chemical into pipeline flow system, these chemicals are already proven to decrease pump work for constant flow rate or allow pipeline to transport more oil for same amount of pump work. The first application of drag reducer in large scale oil transportation was in Trans Alaskan Pipeline System which cancel the need to build several pump stations because of the successful application. Since then, more company worldwide started to apply drag reducer to their pipeline system.
Several tedious testings on laboratory should be done to examine the effect of drag reducer to crude oil that will be the subject of application. In this paper, one of the testing method is studied and experimented to select the most effective DRA from several proposed additives. For given pipeline system and crude oil type, the most optimum DRA is DRA A for pipeline section S-R and for section R-P is DRA B. Different type of oil and pipeline geometry will require different chemical drag reducer.
(The data was calculated based on Google Scholar Citations)
Google-based Impact Factor (2018): 6.49
h-index (January 2018): 30
i10-index (January 2018): 163
h5-index (January 2018): 19
h5-median(January 2018): 25
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