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Anggara, Fajar
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Multiclass gas pipeline leak detection using multi-domain signals and genetic algorithm-optimized classification models Suprihatiningsih, Wiwit; Romahadi, Dedik; Pranoto, Hadi; Youlia, Rikko Putra; Anggara, Fajar; Rahmatullah, Rizky
Teknomekanik Vol. 9 No. 1 (2026): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/teknomekanik.v9i1.38372

Abstract

Pipeline networks are critical infrastructure for oil and gas transport because the occurrence of leaks can rapidly escalate into safety, economic, and environmental crises. Operators are practically required to identify the presence and type of leaks; however, applying multiclass recognition is challenging when labeled data and computing power are limited. Therefore, this study proposes a three-stage pipeline which consists of: (1) adopting the GPLA-12 dataset of acoustic or vibration signals spanning 12 leak types; (2) extracting multi-domain features by combining time-domain descriptors with Power Spectral Density (PSD)-based spectral features; and (3) applying a genetic algorithm (GA) as a wrapper for feature selection to enhance discriminability and reduce dimensionality, which was followed by benchmarking seven conventional classifiers and GA-based refinement of the top model with a focus on the feature subset and hyperparameters. A maximum accuracy of 96.35% was achieved on the GPLA-12 dataset with low computation time and a simple model architecture. The proposed pipeline also attained similar or better accuracy at substantially lower complexity and data requirements compared with prior deep CNN approaches. These results support timely multiclass decision-making in resource-constrained industrial settings. A key observation was that the focus was on supervised leak-type classification from acoustic or vibration signals, while localization, severity estimation, and multi-sensor fusion were beyond the scope of this study.
Evaluation of ESP Pump Size-up on Marley Field Production Tanpasya, Alexander; Arizona, Rafil; Elfiano, Eddy; Anggara, Fajar
Journal of Renewable Energy and Mechanics Vol. 5 No. 02 (2022): REM VOL 5 NO 02 2022
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/rem.2022.9894

Abstract

Field or Field Marley is one of the fields in the work area of ​​PT. Pertamina Hulu Rokan, which is located in Riau Province, has entered the brownfield phase and has a high water cut rate. This condition made the company start a new step by making a size-up on the pump in the Marley well. However, after the Size-Up program was carried out there were several wells that failed, therefore in this study, the researcher will do a re-calculation to find out how far the success of the Size-Up program has been. After the Size-Up program was carried out at the Asmud well in the Marley field, the results obtained as much as 68% success, which is below the minimum target which should be above 100%. It is known that the pump installed in the Asmud well is a Centrilift 400P10 pump with a pump range of 650-1400 bfpd specifications, motor power 42 HP, electric current 53 A, voltage 475 V, and efficiency of 88.4%. Well data can be in the form of a 93% water cut, with an sfl value of 184 ft and a wfl of 307 ft, a pwf of 383.33 psi, and an API value of 34. Based on these parameters, the Inflow Performance Relationship (IPR) curve can be analyzed. it is analyzed that the Asmud well is in a down thrust condition where the pump is in the minimum range. Therefore, the researcher suggests that a Size-Down pump be carried out using a Centrilift 400P8 60 Hz pump with a specification range of 550-1200 bfpd which is in accordance with the production capacity of the Asmud well.
Co-Authors Andi Firdaus Sudarma Anugrah, Rinasa Agistya Arizona, Rafil Dafit Feriyanto Dedik Romahadi Eddy Elfiano Hadi Pranoto Henry Carles Muhammad Nadjib, Muhammad Nur Indah, Nur Oktaviani, Vira Pathur Razi Ansyah Rahmatullah, Rizky Rikko Putra Youlia Sari, Andarany Kartka Subekti Subekti Suhanan Suhanan, Suhanan Swandya Eka Pratiwi Tanpasya, Alexander Ujang Sumarwan Wahyudi, Haris Wang Dong Wijaya, Fathoni Putra Wisnujati, Andika Wiwit Suprihatiningsih Xiong, Hui