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All Journal Aptekmas : Jurnal Pengabdian Kepada Masyarakat Scientific Contributions Oil and Gas
Suranto
Universitas Pembangunan Nasional “Veteran” Yogyakarta
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SOSIALISASI PENGOLAHAN AIR DENGAN “WATER MEMBRANE FILTRATION” DARI MATA AIR POLAMAN KEBUMEN Heri Septya Kusuma; Bambang Sugiarto; Suranto; Retno Dwi Nyamiati
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 6 No 2 (2023): Aptekmas Volume 6 Nomor 2 2023
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36257/apts.v6i2.6814

Abstract

This community service aims to socialize water treatment technology from the Polaman spring in Polaman, Kebakalan Village, Karanggayam, Kebumen, Central Java, and further enhance the capabilities of UKM partners in processing water into packaged drinking water products and increasing the market value of the water. The Polaman spring is the main water source for the community in that area, but its water quality does not yet meet the safe standards for human consumption. This community service involves the implementation of water treatment technology in several stages. Firstly, an initial survey is conducted to understand the condition of the water source and the needs of the local community. Then, the appropriate water treatment method is chosen based on those conditions and needs. The applied method is filtration technology using microfiltration, ultrafiltration, nanofiltration, and reverse osmosis, complemented with UV radiation. Subsequently, water treatment is socialized by utilizing the filtration technology. Through this water treatment socialization, it is expected that the water quality from the Polaman spring can be improved and deemed safe for local consumption. Additionally, it is also expected to raise public awareness regarding the importance of safe water treatment and responsible water usage.
Development of Machine Learning for Lost Production Opportunity Prediction and Production Optimization Through Workover Scheduling in Pertamina Hulu Sanga Sanga Field, Sanga-Sanga Block of East Kalimantan, Indonesia Adinsya Yudha; Suranto; Frans Richard Kodong; Muhammad Rahmanaji Soeparmono
Scientific Contributions Oil and Gas Vol 49 No 3 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i3.2150

Abstract

Lost Production Opportunity (LPO) measures production that cannot be realized because a well or facility is constrained. In many field-planning workflows, LPO and workover schedules are still estimated from historical averages and a fixed production uplift for each job. Although practical, these assumptions do not represent the nonlinear interaction among production behavior, equipment failures, downtime, and intervention timing. This work examines whether those interactions can be learned from field data and used to improve the monthly scheduling of rigless workover jobs.Historical production, Planned Downtime (PDT), Unplanned Downtime (UPDT), and operational event records from Field ‘X’ were compiled at monthly resolution. XGBoost regression models were trained using a chronological data split and evaluated with MAE, RMSE, sMAPE, and actual-versus-predicted plots. The resulting LPO forecasts and feature-importance rankings were then incorporated into a Decision Support System (DSS). Together with workover capacity, expected uplift, job cost, commodity price, and operational constraints, the DSS assigns a monthly risk level and recommends whether workover activity should be increased, selected cautiously, or reduced.The gas and oil models produced sMAPE values of 16.79% and 19.06%, respectively. In the 2026 simulation, DSS-based scheduling increased gas production from 83.43 to 84.56 MMscfd and oil production from 9,650 to 9,805 BOPD relative to the conventional schedule. These results suggest that field data can be used not only to estimate LPO, but also to place rigless workover jobs in months where their production benefit is less exposed to operational disruption.
Co-Authors Adinsya Yudha Bambang Sugiarto Frans Richard Kodong Heri Septya Kusuma Muhammad Rahmanaji Soeparmono Nyamiati, Retno Dwi