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All Journal Formosa Journal of Science and Technology (FJST) Enrichment: Journal of Multidisciplinary Research and Development JURNAL REKAYASA KIMIA & LINGKUNGAN
Sommeng, Andy Noorsaman
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Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Education Energy Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences

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The Effect of Heat Tracing Installation for Wax Prevention on Onshore Buried Swampy Pipelines Santoso, Samuel Bagas Wahyu; Sommeng, Andy Noorsaman; Dianita, Cindy
Jurnal Rekayasa Kimia & Lingkungan Vol 19, No 1 (2024): Jurnal Rekayasa Kimia & Lingkungan (June 2024 )
Publisher : Chemical Engineering Department, Syiah Kuala University, Banda Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23955/rkl.v19i1.37754

Abstract

Transporting crude oil using pipelines is a widely adopted method globally. In one segment owned by PT. XYZ, especially in swampy areas, the fluid temperature tends to drop below the wax appearance temperature (WAT) during oil transportation. This is due to the relatively low temperature in swamp areas caused by heat loss to the environment. The solubility of paraffin in crude oil drastically decreases as fluid temperature drops, causing wax molecules to precipitate and deposit on the cold pipe walls. PT. XYZ employs chemical treatment by adding a pour point depressant (PPD) to lower the pour point temperature (PPT). However, PPD is effective only at certain temperatures, necessitating a study for alternative treatments. Another method involves installing heaters on the pipeline to reduce the viscosity of transported crude oil and enhance its flowability, either through direct heating or heat tracing using insulation with low thermal conductivity. Therefore, in PT. XYZ's case, an analysis is required to identify locations where fluid temperature decreases occur to ensure precise heater installation. Various software tools, including OLGA, have been developed to predict and describe wax deposition phenomena and temperature decreases along the pipeline. OLGA software can simulate locations of fluid temperature decreases in the pipeline, estimate heat loss along the pipeline, and simulate heat tracing technologies to prevent wax deposition. Simulation results indicate that wax deposition can be prevented by installing skin effect heat tracing with a heating power of 15 W/m and insulated with 2-inch aerogel, maintaining the oil temperature downstream at 157.34F, well above the desired 115F threshold.
Techno-Economic Risk Analysis Study of Co2 and Hydrogen Utilization From Refinery as Raw Material for Production of Dimethyl Ether Suriperdana, Puan Chairunnisa; Sommeng, Andy Noorsaman; Nengkoda, Ardian
Enrichment: Journal of Multidisciplinary Research and Development Vol. 3 No. 4 (2025): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v3i4.409

Abstract

The existence of carbon footprint trade regulations and advances in carbon capture, utilization, and storage (CCUS) technology have led to the urgency of CCUS installations at all refineries globally. Captured CO2 can be used as a new economic opportunity by being reprocessed as a raw material for the production process. CO2 can be processed into DME through dry methane reforming, methanol synthesis, and methanol dehydration processes. The Indonesian government plans to replace LPG with DME. Thus, a process simulation using Aspen Plus was carried out to see the effectiveness of production along with an investment feasibility analysis in terms of NPV, IRR, PBP, and PI values and a probability review using Monte Carlo simulation. From the simulation on Aspen Plus, DME was produced as much as 868.04 tons/day. Furthermore, the economic parameters were calculated with a DME selling price of USD 1,300/ton and obtained an NPV value of USD 1,783,715,566.19, IRR 58.44%, PBP 2.041 years, and PI 3.675 so that the plant can be said to be feasible. From 1000 iterations carried out in the simulation, the four economic parameters show positive values so that the financial risk of the plant is relatively safe.
Model of Machine Learning for Prediction and Optimization of Oil and Gas Operating Costs in Indonesia Bagaskoro, Adhanto; Nengkoda, Ardian; Sommeng, Andy Noorsaman
Formosa Journal of Science and Technology Vol. 3 No. 6 (2024): June 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v3i6.9687

Abstract

This study leverages machine learning techniques to predict and optimize operational expenditures (OPEX) in Indonesia's oil and gas industry. By analyzing historical data from Work Plan and Budget (WP&B) reports from 2017, the research identifies key factors influencing OPEX, such as production location, oil characteristics, and development stages. The Random Forest model demonstrated the highest predictive accuracy with an R-squared value of 0.92 and Mean Squared Error (MSE) of 4.5. The findings highlight significant cost-saving opportunities, particularly in Kalimantan and Papua. These insights support strategic planning and decision-making, emphasizing the transformative potential of machine learning in enhancing operational efficiency and sustainability in the oil and gas sector.
Co-Authors Bagaskoro, Adhanto Cindy Dianita, Cindy Nengkoda, Ardian Santoso, Samuel Bagas Wahyu Suriperdana, Puan Chairunnisa