Tagging and tracking oil-gas mixtures in multiphase pipelines

نویسندگان

چکیده

Pipeline transportation of multiphase products, such as gas and oil mixtures, exhibits complex varying flow regimes: a result, analytical approaches or conventional methods cannot accurately describe the composition propagation characteristics fluid mix inside system itself. We address an issue by presenting methodology, driven data applied to real case history, where basic pressure transients are used tag track, along pipeline, different batches medium. Several statistical indicators, computed from on window lengths, employed train machine learning model, which learns distinguish characteristic behavior two oil-gas slugs: in practice, each combination phases (in terms gas/oil ratio given batch product) sequence slugs variability between successive batches) behaves like coded linked flowing fluid. The key innovation consists possibility tracking flowline at monitoring station: this allows one determine real-time entering/exiting line, its position, movement pipe. As such, we obtain also virtual metering system, able provide estimates rate ratio. Moreover, having several recording stations synchronized, can leverage transmission multichannel processing data, enabling opportunity for online applications. results test cases accuracy scores obtained metrics considered validate tagging approach. • Pressure be track oil/gas slugs. pipeline virtually monitored. position traced real-time.

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ژورنال

عنوان ژورنال: Journal of Petroleum Science and Engineering

سال: 2022

ISSN: ['0920-4105', '1873-4715']

DOI: https://doi.org/10.1016/j.petrol.2022.110982