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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 648 Documents
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Caprock Integrity Assessment from Core-Based Formation Analysis and Laboratory Workflow: A Case Study of The Asri Basin Caprock Buntoro, Aris; Putra, Teddy Eka; Kristanto, Dedi; Swadesi, Boni; Amir, Zulhemi; Lukmana, Allen Haryanto; Wicaksono, Dimas Suryo; Nurcholis, Muhammad
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2021

Abstract

Caprock integrity is a critical factor in ensuring the long-term safety of CO₂ geological storage, enhanced oil recovery (EOR), and wellbore stability. This study investigates the sealing performance of shale- and carbonate-rich caprock intervals from the Asri Basin, with specific focus on the Baturaja and Gita Formations. This study introduces a CT-guided integrated laboratory workflow for caprock integrity assessment, which simultaneously links petrophysical sealing capacity, mineralogical controls, and geomechanical strength within a unified experimental framework, a workflow rarely applied in Southeast Asian basins. Whole-core sections from Well ASR-1 were screened using computed tomography (CT) imaging to identify fractures and heterogeneity prior to plug extraction. Laboratory methods included porosity and permeability determination under variable confining stresses, mercury injection capillary pressure (MICP) analysis to evaluate sealing capacity, mineralogical characterization by X-ray diffraction (XRD), scanning electron microscopy (SEM–EDS), petrography, and mechanical testing (UCS, triaxial, and Brazilian tensile tests). The results demonstrate significant depth-dependent variability: The Baturaja Formation exhibited heterogeneous sealing capacity, with entry pressures ranging from 217 to 1,197 psi, while the Gita Formation consistently displayed strong sealing, with maximum Pc_entry of 2,844 psi and pore systems dominated by <0.1 µm throats. Mechanical tests confirmed adequate strength and the preservation of low permeability under confining stress, with clay content and carbonate cementation identified as primary controls on integrity. The integrated workflow enables a process-based interpretation of lithology-controlled sealing mechanisms, improving the robustness of site selection and risk assessment for CO₂ storage in the Asri Basin and similar carbonate and mudstone systems.
Machine Learning for Reservoir Characterization: Lithology Prediction Using Support Vector Machine (SVM) in The "VISA" Field, East Kalimantan Muhammad Faiz Nugraha; Eki Komara; Abdul Latiff, Abdul Halim; Wien Lestari; Edy Wijanarko
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2032

Abstract

This research was conducted in the "VISA" field of the Balikpapan Formation, located in the Kutai Basin, one of Indonesia's largest hydrocarbon basins. The lithology of this formation is primarily Sandstone and shale, which are significant for hydrocarbon exploration and production. Determining the initial lithology is an essential step for understanding the characteristics of the well data during processing. Consequently, the Support Vector Machine (SVM) algorithm was implemented in this study to predict lithology using well data. This investigation employs data from four wells: VISA-9, VISA-13, VISA-36, and VISA-39. The prediction results are subsequently visualized as well as logs and lithology distribution histograms to make the results easier to interpret based on three interpreted lithology categories: Sandstone, shale, and Coal. Performance evaluations indicate that limitations remain in the SVM classification. The error range obtained in Experiments 1 and 2 was 11–22% compared to the actual lithology. However, Experiment 3 demonstrated substantial improvement by utilizing three training datasets, which reduced the error rate to 5% (a 7% improvement from previous experiments). Overall, the SVM method can effectively classify rock lithology; however, the model still requires optimization to minimize residual errors during the prediction process. Ultimately, this investigation demonstrates that SVM can be successfully applied to predict lithology using well log parameters.
Risk-Informed Strategic Governance in Precast Concrete Production as A High-Risk Industry: Cross-Sector Evidence from The Construction and Oil & Gas Industries Asyik, Noor; Latief , Rusdi Usman; Burhanuddin, Syarif
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.1956

Abstract

High-risk industrial production systems, particularly in the oil and gas sector, are characterized by capital-intensive operations, strict regulatory requirements, and extremely low tolerance for technical failure. In such environments, misalignment between technical risk exposure and strategic decision-making may escalate into significant operational, financial, and safety consequences. However, empirical examination of risk-informed strategic governance in oil and gas production systems remains limited due to data accessibility and confidentiality constraints. To address this gap, this study proposes an integrated risk-informed strategic governance framework using precast concrete manufacturing in Indonesia as a representative high-risk industrial production system with structural characteristics analogous to oil and gas fabrication and EPC-based operations. This study integrates the Risk Breakdown Structure (RBS) and Risk Priority Number (RPN) methods with the Quantitative Strategic Planning Matrix (QSPM) to explicitly link quantified technical risk exposure with strategic governance priorities. A descriptive–quantitative approach was employed, involving leading precast concrete companies in Indonesia to capture actual industrial production conditions. The research was conducted through three main stages: (1) systematic identification and hierarchical classification of technical risks using the RBS method; (2) quantitative assessment and prioritization of risks using the RPN method based on severity, occurrence, and detection parameters; and (3) formulation and prioritization of strategic governance responses using the QSPM approach. The results indicate that the most critical technical risks are design drawing errors, lack of supervision over the implementation of production standards, and product non-compliance with quality requirements, as reflected by the highest RPN values. Integration of RPN outputs into the QSPM analysis identifies three governance priorities with the highest Total Attractiveness Score (TAS): implementation of effective management systems, conducting operational risk management, and reducing product deviations. These priorities demonstrate the strongest quantitative alignment between dominant technical risks and strategic governance responses. Overall, the proposed RBS–RPN–QSPM integration framework strengthens the linkage between technical risk assessment and strategic governance by explicitly transforming quantified operational risk into strategic decision variables. In practice, the framework provides a structured decision-support approach that can assist oil and gas fabrication managers in prioritizing governance interventions—such as strengthening design verification, improving production supervision, and enhancing quality compliance—based on quantified technical risk exposure. Although empirically grounded in precast concrete manufacturing, the governance logic and decision-support architecture are therefore transferable to oil and gas fabrication yards, modular construction facilities, and EPC-based production systems, where strategic choices must be explicitly aligned with technical risk exposure to enhance operational robustness, regulatory compliance, and long-term sustainability.
Application of Computational Fluid Dynamics Simulation in The Case of Upward Vertical Core Annular Flow of Oil-Water System Dianita, Cindy; Nur Fatimah, Rana; Wahid, Abdul
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.1971

Abstract

The energy required to transport heavy oil through pipelines can be significantly lowered by applying the core-annular flow (CAF) technique, in which a layer of water surrounds the oil as it moves through the pipe. This research investigates the behavior of upward oil–water flow in vertical pipelines using three-dimensional computational fluid dynamics (CFD) simulations. The numerical analysis is conducted based on previously published experimental studies. Validation has been completed to ensure the visual and numerical consistency of the observed interfacial wave geometry. This CFD work captures the wavy bamboo CAF pattern, illustrating the effect of buoyancy and pressure gradient in upward vertical flow, as demonstrated by experimental results. The present CFD simulation results indicate a relatively stable velocity distribution, where the central region of the pipe contains the highest concentration of oil. In addition, the absolute pressure gradually decreases along the length of the pipe, while the wall shear stress remains relatively low. The influence of gravity affecting the flow is investigated, showing a higher pressure drop compared to gravity-free flow. Compared with single-phase heavy oil transport, the CAF technique demonstrates significantly higher efficiency, achieving energy savings exceeding 90%. Furthermore, the three-dimensional simulation developed in this study provides more detailed flow pattern representation and more reliable hydrodynamic predictions than those obtained from earlier two-dimensional analyses.
Multilinear Regression–Based Rock Physics Template Modeling for Sandstone Reservoir Characterization Fahrizi, Muhammad Alif; Winardhi, Ignatius
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2014

Abstract

Rock Physics Templates (RPT) are widely used to link petrophysical parameters with elastic properties for fluid identification in reservoir characterization. Previous studies have demonstrated the potential of RPT for fluid detection method; however, well-defined procedures for determining rock matrix parameters and P-wave velocity (Vp) as the basis for RPT construction remain limited. This study develops a systematic workflow for RPT construction based on volumetric and rock physics approached, where rock matrix properties are estimated directly from wireline logs when core data is unavailable. The performance of the proposed RPT approach is evaluated through comparing with conventional elastic attribute methods, namely Curved Pseudo Elastic Impedance (CPEI) and Lambda–Rho analysis. The results indicate that the RPT workflow provides improved fluid discrimination than the conventional methods, highlithing its effectiveness as a reliable rock-physics-based tool for fluid identification in sandstone reservoirs.
Improving Safety Awareness in the Workforce through Education and Programs: A Scoping Review Nurdiansyah, Warid; Lestari, Fatma
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2044

Abstract

Approximately two million people die annually from occupational diseases and workplace accidents. Despite extensive preventive measures, accident and fatality rates remain high, with recurring incidents and persistent root causes. These patterns highlight the urgent need for effective programs and educational models to enhance workers’ safety awareness, a critical factor in preventing occupational accidents. This study conducted a scoping review to map existing evidence, conceptual frameworks, and research gaps concerning safety awareness programs and educational interventions for workers. Following the PRISMA-ScR framework, three databases: Medline (PubMed), APA PsycArticles® (ProQuest), and Scopus, were systematically searched for English-language studies published in the past five years. Ten studies met the inclusion criteria. Although research in this area remains limited, evidence suggests that well-designed programs and educational approaches, particularly those integrating technology-based learning and participatory methods, can effectively improve workers’ safety awareness. Further empirical studies are needed to develop comprehensive, evidence-based educational models applicable across diverse occupational settings.
Evaluation of Chemical Acidizing Performance Using 15% Hydrochloric Acid (HCl) on Eight Production Wells in Field X Arjuna; Hardi, Maulana; Kuswardani, Tyas; Wardani, Oktaviani Kusuma
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2050

Abstract

This study evaluates the performance of matrix acidizing, a stimulation process conducted below fracturing pressure using 15% hydrochloric acid (HCl) on eight production wells in Field X, a carbonate reservoir. The assessment compares pre‑ and post‑treatment production performance over a defined 30‑day monitoring period. Acid selection was supported by laboratory dissolution analysis using β₁₀₀ and dissolution rate indicators, demonstrating that 15% HCl provided the strongest dissolving power against carbonate minerals compared with formic and acetic acids. The distinction between chemical acidizing (acid-based mineral dissolution) and matrix acidizing (operational mode focused on restoring near‑wellbore permeability without inducing fractures) is clarified to align with standard acidizing terminology. Field results show a 90% overall success rate, with average production gains of +778.76 BFPD (fluid) and +49.54 BOPD (oil). One well exhibited an anomalous response, characterized by an increased fluid rate but a reduced oil rate, indicating the potential activation of water-conductive pathways. These findings highlight that, although acid strength is an important factor, treatment success also depends on reservoir heterogeneity, scale distribution, and the effectiveness of acid placement. The integrated workflow combining Scale Index (SI) evaluation with dissolving‑power‑based acid screening provides a structured approach for designing matrix acidizing in mature carbonate fields.
Grey Wolf Optimization-Based Global MPPT for Solar-Assisted Hybrid Energy Systems in Oil and Gas Production Facilities Zulfadli, Teuku; Muliadi; Yassir; Zamzami; Salahuddin
Scientific Contributions Oil and Gas Vol 49 No 1 (2026)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v49i1.2056

Abstract

Partial shading in photovoltaic (PV) modules produces multiple power peaks that reduce system efficiency if the global maximum power point is not properly tracked. This condition commonly occurs in oil and gas production facilities due to shadows from industrial structures, requiring MPPT methods with reliable global tracking capability. This study evaluates the Grey Wolf Optimization (GWO) algorithm for global MPPT under eight partial shading scenarios (12.5%–100%) using MATLAB/Simulink simulation. The results show that GWO successfully tracks the global maximum power point under single-, double-, and triple-peak conditions. Under 12.5% shading, the system produces 277.0 W with an efficiency of 99.78%; under 25% shading, it produces 266.7 W with an efficiency of 99.85%; and under 37.5% shading, it produces 204.2 W with an efficiency of 99.90%. Across all scenarios, the algorithm achieves efficiencies above 99% with an average efficiency of 99.61%, which is higher than the 97.20% reported in previous studies. This efficiency improvement of approximately 2–4% increases the contribution of solar energy in PV–diesel hybrid systems and potentially reduces fuel consumption while improving power supply reliability for critical loads in oil and gas production facilities. Unlike conventional metaheuristic approaches such as PSO-MPPT, Flower Pollination Algorithm (FPA), and Differential Evolution (DE), which are sensitive to parameter tuning or prone to premature convergence, the proposed GWO implementation employs a hierarchical three-agent update mechanism (α, β, δ) that enhances global exploration capability across complex multi-peak P–V characteristics. This distinguishes the present study from prior GWO-based MPPT work that relied solely on the alpha agent for position update.

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