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Yohana Dewi Lulu Widyasari
Department of Information Technology, Politeknik Caltex Riau, Pekanbaru 28265, Indonesia
Computer Science & IT Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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Integrated production facilities clustering and time-series forecasting derived from large dataset of multiple hydrocarbon flow measurement Adityapati Rangga; Yohana Dewi Lulu Widyasari; Dadang Syarif Sihabudin Sahid
Science, Technology, and Communication Journal Vol. 2 No. 2 (2022): SINTECHCOM Journal (February 2022)
Publisher : Lembaga Studi Pendidikan dan Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v2i2.207

Abstract

In the complex, mature, and large oilfields, there is a need for Integrated solution in order to have a helicopter view of entire facilities throughput. The real time metering information provides an on-demand daily data and trend. However, it is rarely being connected to analytics solution for business intelligence such as, prediction, optimization, decision support and forecast. This paper cover about exploratory data analysis of large dataset of multiple hydrocarbon facilities metering within integrated network, performing multi-feature data clustering and making a time-series forecasting techniques. K-means and PCA are combined to make cluster of production facilities which resulted with gas processing cluster, high oil producer, high water processing station, and the lowest performer in term in hydrocarbon processing. Furthermore, VAR and LSTM are compared as forecasting tools for day-to-day fluid prediction, to maintain normal operational scenario.
Co-Authors Adityapati Rangga Dadang Syarif Sihabudin Sahid