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INDONESIA
Scientific Contributions Oil and Gas
Published by LEMIGAS
ISSN : 20893361     EISSN : 25410520     DOI : -
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Energy
The Scientific Contributions for Oil and Gas is the official journal of the Testing Center for Oil and Gas LEMIGAS for the dissemination of information on research activities, technology engineering development and laboratory testing in the oil and gas field. Manuscripts in English are accepted from all in any institutions, college and industry oil and gas throughout the country and overseas.
Arjuna Subject : Energi (semua kategori) - Teknologi Bahan Bakar
Articles 683 Documents
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Potential Use of Kepok Banana Peel Waste as Raw Material for Carboxymethyl Cellulose for Oil and Gas Drilling Fluid Applications Apriandi Rizkina Rangga Wastu; Asep Kurnia Permadi; Deana Wahyuningrum; Asri Nugrahanti
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.2070

Abstract

This research aims to evaluate the potential of kepok banana peel as a raw material for carboxymethyl cellulose synthesis and to assess its effects on the rheological properties and filtration of bentonite-based drilling mud. CMC is synthesized through a process of delignification, bleaching, alkalization, and carboxymethylation. CMC characterization includes alpha cellulose content, degree of substitution, purity, pH, FTIR, SEM, and EDS. The obtained CMC was added in drilling mud at concentrations of 3 g, 6 g, and 9 g, and the resulting mud was tested for mud rheology and filtrate volume. The results showed that the alpha-cellulose content was 91.60%, the degree of substitution was 1.0, and the purity was 88.17%, meeting the SNI CMC grade II standard. The application of CMC increased plastic viscosity (12–14 cP), yield point (19–21 lb/100 ft²), and gel strength (8–13 lb/100 ft² for 10 seconds; 12–17 lb/100 ft² for 10 minutes) as the concentration increased. The filtrate volume decreased from 15 ml to 13 ml/30 minutes, and the mud cake thickness decreased from 0.5 mm to 0.3 mm. The pH value was stable in the range of 9. It was concluded that CMC derived from kepok banana peel has the potential to serve as an environmentally friendly drilling mud additive.
The Next Generation of Safety: Artificial Intelligence and Machine Learning Strategies for a Safer Oil and Gas Industry Shahabodin Taheri; Yousef Azimi
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.1786

Abstract

This study explores the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) in revolutionizing safety practices within the oil and gas industry. Through a systematic literature review and conceptual analysis of peer-reviewed publications, industry reports, and regulatory frameworks, this research synthesizes current knowledge on AI applications in safety management. The study critically examines the ethical implications and potential drawbacks of AI-driven safety systems, such as data privacy concerns, algorithmic bias, and the evolving dynamics of human-machine interaction in high-risk environments. The regulatory landscape is scrutinized, highlighting the need for adaptive policies that can accommodate rapidly evolving technologies while maintaining robust safety standards. Furthermore, the paper explores emerging trends, including the convergence of AI with the Internet of Things (IoT) and 5G technologies, the development of explainable AI for safety-critical applications, and the increasing role of autonomous systems in hazardous operations. Based on the synthesis of empirical evidence and theoretical frameworks, the findings reveal that while AI and ML offer unprecedented opportunities in the oil and gas sector, their efficacy is contingent upon overcoming significant technical, organizational, and ethical challenges. The study proposes a holistic framework for AI implementation that emphasizes phased adoption, stakeholder engagement, and continuous evaluation of safety metrics. This work contributes to the growing body of knowledge on digital transformation in high-risk industries and provides actionable insights for policymakers and safety professionals seeking to leverage AI for improved safety performance in the oil and gas sector.
Development of A Risk-Based Pre-Tender Assessment Tool for Oil and Gas Construction Projects Using Analytical Hierarchy Process Sudirman; Rosmariani Arifuddin; M Asad Abdurrahman
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.1962

Abstract

The pre-tender stage is a critical decision point in oil and gas construction projects, particularly in capital-intensive, technically complex environments, where inappropriate project selection may increase financial, technical, operational, and regulatory risks. In practice, contractors often rely on subjective judgment in early project evaluation due to the limited availability of structured, quantitative decision-support tools. This study aims to develop a risk-based pre-tender assessment tool to support project selection decisions in oil and gas construction projects in Indonesia. The study integrates a literature review with a questionnaire-based survey involving 90 experienced construction practitioners occupying supervisory and managerial positions. Data were analyzed using descriptive statistics and the Analytical Hierarchy Process (AHP) to determine the relative priority weights of evaluation criteria and sub-criteria.The results indicate that all major criteria contribute significantly to pre-tender decision-making, with financial aspects obtaining the highest priority weight (22.9%), followed by commercial (20.1%), technical (19.4%), legal and social (19.3%), and marketing aspects (18.3%). At the sub-criteria level, expected profit margin, implementation risk, and project owner legality emerged as dominant evaluation factors. A case study application further demonstrates the practical applicability of the proposed framework, with the pipeline installation project achieving a higher feasibility score (7.48) than the oil storage terminal project (6.32). Sensitivity analysis also confirms that the ranking results remain stable under alternative weighting scenarios.The findings demonstrate that the proposed framework provides a structured, transparent, and risk-informed approach for evaluating project feasibility during the pre-tender stage. The study contributes by developing an integrated weighting-based decision-support framework specifically tailored to the characteristics and risk exposure of oil and gas construction projects, thereby supporting more objective and consistent contractor decision-making.
Optimization of Chemicaly Activated Candlenut and Walnut Shell Biosorbents for Produced Water Purification Within an Iot-Based Monitoring System Muhammad Khairul Afdhol; Rika Lala Saputri; Mursyidah; Fiki Hidayat; Tomi Erfando; Ari Prasetyo; Adiella Zakky Juneid
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.1972

Abstract

Produced water from petroleum operations contains high levels of hydrocarbons, suspended solids, and dissolved contaminants that must be treated before discharge or reuse. This study aims to optimize biosorbents derived from candlenut and walnut shells through chemical activation using potassium hydroxide (KOH) for the purification of produced water. In addition, an Internet of Things (IoT)-based monitoring system was integrated to enable real-time assessment of water quality parameters. The biosorbents were characterized using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM) to identify surface functional groups and morphological modifications. Experimental evaluations of turbidity, bulk density, and total dissolved solids (TDS) were conducted under various operating conditions. The activated biosorbents exhibited enhanced hydroxyl and carboxyl functional groups, as confirmed by FTIR, with an optimal bulk density of 0.76 g/cm³. Under optimum conditions (pH 7, contact time 90 min, adsorbent dosage 15 g/L), turbidity and TDS removals reached 80% and 75%, respectively. The IoT system successfully enabled real-time data acquisition and process monitoring, ensuring operational reliability. The maximum adsorption capacity based on the Langmuir model reached 33.8 mg/g for KOH-activated walnut and 31.2 mg/g for candlenut biosorbent. Overall, the chemically activated candlenut and walnut biosorbents demonstrated excellent adsorption capacity and potential for sustainable produced water treatment. This approach offers an environmentally friendly and cost-effective solution by utilizing local biomass waste integrated with modern IoT-based control technologies. Adsorption behavior was further evaluated using Langmuir/Freundlich isotherm and kinetic models.
Failure Mechanisms and Risk-Based Mitigation of Hydrocarbon Pipeline Blockages: A Comprehensive Review Hamdani Wahab; Asral; Awaludin Martin
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.2011

Abstract

Hydrocarbon pipelines play a vital role in ensuring the continuous transportation of oil and gas. However, pipeline blockages remain a major operational challenge because of their significant impacts on safety, environmental protection, and production reliability. This study presents a literature review aimed at identifying and classifying the hazards and risks associated with hydrocarbon pipeline blockages using a 5×5 risk matrix based on the MIL-STD-882B military safety standard. Historical incident data from 1970–2024 were collected from the Pipeline and Hazardous Materials Safety Administration of the US Department of Transportation to support the risk assessment process. The analysis indicates that environmental damage is the most significant consequence of pipeline blockage incidents (28%), followed by fire and explosion (22%), toxic gas exposure (17%), overpressure (13%), economic losses (11%), and production losses (9%). Furthermore, environmental recovery costs account for approximately 88.6% of the total financial impact, while the probability of severe incidents reaches 80%, with estimated economic losses up to USD 20 million or production disruptions of 25%. The findings highlight the urgent need for effective mitigation and prevention strategies to improve pipeline integrity, operational safety, and sustainability within the oil and gas industry.
A System Dynamics Approach to Analyze Biodiesel Production and Oil Import Dependency in Indonesia Andry Prima; Bayu Satiyawira; Havidh Pramadika; Daud Asrun Nauw; Lisa Samura; Mustamina Maulani; Cahaya Rosyidan; Maman Djumantara; Djunaedi Agus Wibowo; Wiwik Dahani; Osama Jawaid Butt
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.2019

Abstract

Indonesia’s persistent dependence on imported diesel fuel poses significant challenges to national energy security, fiscal stability, and exposure to global market volatility. In response, the government plans to implement a mandatory B50 biodiesel blending policy starting in 2026 to reduce diesel imports by leveraging domestic bioenergy resources. While higher blending mandates are often assumed to directly lower imports, existing studies largely rely on static or deterministic approaches that inadequately capture feedback dynamics and long-term uncertainty. This study addresses this gap by integrating system dynamics modelling with Monte Carlo simulation to analyze the impact of biodiesel blending policies on diesel import dependency under structural and parametric uncertainty. The model incorporates biodiesel production growth, domestic allocation after exports, diesel demand growth, and blending effectiveness within a feedback-based framework calibrated using historical data from 2013 to 2024. Simulation results indicate that the B50 policy consistently reduces diesel import requirements relative to the baseline; however, absolute imports may continue to rise without sufficient domestic supply expansion. Cumulative results show that by 2035, the B50 policy achieves import reductions of approximately 55–58 million kiloliters, increasing to around 60 million kiloliters when combined with accelerated biodiesel production growth. Monte Carlo analysis reveals robust medium-term outcomes by 2030 but increasing uncertainty by 2035. The findings highlight that blending mandates must be accompanied by sustained supply-side development to ensure long-term effectiveness and resilience.
Edge Computing–Enabled Real-Time CO₂ Emissions Monitoring: A Low-Latency and Bandwidth-Efficient Architecture for Oil and Gas Sector Suka Handaja; Bambang Yudho Suranta
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.2020

Abstract

The oil and gas industry is facing increasing pressure to reduce carbon dioxide (CO₂) emissions while maintaining operational efficiency and regulatory compliance. However, conventional cloud-based emissions monitoring systems often suffer from latency, bandwidth limitations, and reduced reliability in remote operational environments. This study aims to explore the role and implementation of edge computing as an enabling technology for real-time CO₂ emissions monitoring in oil and gas facilities. The architecture of the proposed system integrates the Internet of Things (IoT) gas sensors, local data processing units, and cloud platforms for long-term analytics and reporting. The system is designed to process the emissions data closer to the source with the aim of significantly reducing latency, improving measurement reliability, and enhancing responsiveness to abnormal emissions events. The performance was subsequently evaluated through a distributed monitoring test scenario that simulated multiple emissions monitoring points under intermittent network connectivity conditions often experienced in remote oil and gas operations. The focus was on key performance indicators including data latency, bandwidth utilization, and system availability. The results showed that the edge-enabled architecture reduced average data latency from approximately 3.8 s to 0.9 s and data transmission volume by an estimated 79% through local preprocessing while maintaining monitoring availability above 96% during network disruptions. The trend reflected the ability of edge computing to provide a scalable and robust solution for continuous CO₂ emissions monitoring, particularly in geographically distributed and harsh operational environments often associated with oil and gas operations.
Structural Integrity Assessment of A Low Temperature Separation Unit (LTSU) Strainer Handle-Plate in Oil and Gas Operations: Coupled CFD and FEA Analysis of Fluid-Induced Loads Mohd Azni Md Kasim; Mohd Azahari Razali; Norfakhira Mohd Nor; Iman Fitri Ismail; Masataro Suzuki; Amnur Akhyan
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.2033

Abstract

Structural strainers play a vital role in oil and gas processing facilities by removing solid contaminants from process fluids and protecting downstream equipment. In a Low Temperature Separation Unit (LTSU), a premature failure occurred at the handle punching plate connection of a strainer after approximately five years of continuous operation. This study aims to identify the root cause of the failure and to evaluate improved design configurations capable of withstanding operational loads. A coupled Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) methodology was employed. CFD simulations were conducted to determine internal flow characteristics, pressure distribution, and pressure drop under both normal and contingency operating conditions. The resulting fluid-induced pressure loads were transferred to structural models for FEA to evaluate von Mises stress, displacement, strain, and unity check (UC) values for three designs with different punching plate thicknesses. The original design (Geometry A) exhibited high stress concentration at the handle–plate interface and UC values exceeding allowable limits, explaining the observed field failure. Geometry B showed improved performance under normal conditions but approached critical limits during contingency operation. Geometry C demonstrated the best structural integrity, maintaining UC values within acceptable limits in all cases while reducing peak stresses and deformation. The results confirm that insufficient plate thickness was the primary cause of failure and that increasing thickness significantly enhances structural reliability. The study demonstrates that the coupled CFD–FEA approach is an effective tool for failure diagnosis and design optimisation of process equipment subjected to fluid-induced loading in oil and gas operations.
Permeability and Hydraulic Flow Units Prediction Using Neural Network Technique of The Clastic Mamuniyat Reservoir (Upper Ordovician), Murzuq Basin-Libya Bahia M. Ben Ghawar; Fathi M. Salloum; Mahmud A. Al Tarhouni; Mousa G. El Shamli
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.2035

Abstract

Delineation of the hydraulic flow unit (HFU) and a petrofacies parameter (R35) are essential reservoir characteristics, which are functions of the routine core analysis (CCA) and well log data. Thus, this work has been carried out with the Neural Network (NN) application to predict the HFU, pore size radius (R35), and permeability (KHFU) in uncored well 3 within an average thickness of 133 feet of the clastic Mamuniyat reservoir Murzuq basin (Libya). This prediction is based on data of two wells (1 and 2) producing from the same reservoir. Hence, log analysis demonstrates about 12% effective porosity (Øe) and not exceeding 14% of the shale content (Vsh). Also, 11% and 96 mD are averages of core porosity (Øcore) and permeability (Kcore), respectively. Whereas micropores, mesopores, and macropores are three pore throat radius (R35) classifications recognized in the reservoir and six HFUs in well 1 and five in well 2. Furthermore, gamma ray (GR) logs correlate among three wells and reveal a similarity between wells 1 and 3 that sustain the HFUs of well 3 by using the NN model. Whereas, the comparison between the predicted KHFU and two approved empirical permeability equations manifests furnishing high agreement results with some exceptions. However, the NN provides predictions supported by data of Mamuniyat reservoir quality (HFU, R35, and K) within the uncored reservoir section from the nearby wells that reveal consistent and reliable results.
A Techno-Economic Study on The Impact of Carbon Tax on Production Rate and Production Duration in An Oil Field Adithya Aladar; Silvya Dewi Rahmawati; Ardhi Hakim Lumban Gaol
Scientific Contributions Oil and Gas Vol 49 No 2 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i2.2049

Abstract

This study investigates the economic implications of carbon taxation on upstream oil and gas operations by integrating emission quantification with techno-economic evaluation in a mature offshore oil field. Greenhouse gas emissions were calculated from major upstream sources, including fuel combustion, flaring, venting, and fugitive emissions, using activity-based approaches aligned with IPCC methodologies. Emissions were monetized using Norwegian carbon tax rates, reaching approximately USD 87 per ton CO₂ by 2025, and integrated into project cash flow analysis. The quantified carbon costs were incorporated as additional operating expenditures to evaluate their impact on Net Present Value (NPV) and Internal Rate of Return (IRR). The quantified emissions were monetized using the Norwegian carbon tax framework and incorporated into project cash flow analysis as additional operating costs. Government allowance and subsidy mechanisms were also considered to partially offset the carbon burden. Net Present Value (NPV) and Internal Rate of Return (IRR) were evaluated for baseline conditions and nine production optimization scenarios combining production rate reductions of 10%, 20%, and 30% with production duration extensions of one to three years. The baseline case shows a reduction in NPV of approximately 19% after incorporating carbon costs. Fugitive emissions represent more than 60% of cumulative upstream emissions and dominate total carbon expenditures. Scenario analysis indicates that higher production rate reductions progressively reduce economic losses caused by carbon taxation, although at the expense of lower revenue generation. The results demonstrate that operational optimization can partially mitigate carbon tax impacts in mature oil fields but must be complemented by targeted emission mitigation strategies for long-term sustainability.

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