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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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1D Basin Modeling and Geochemical Analysis of Source Rock The Arafura Basin Mamengko, David Victor; Mamengko, Michael Davidjoy Hamonangan; Setyowati , Tri Peni; Tandirerung, Restu
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.v49i1.1967

Abstract

The Arafura Basin is a frontier basin with significant hydrocarbon potential that remains poorly understood, particularly regarding source rock effectiveness across different structural settings. This study evaluates source rock potential, geochemical characteristics, and thermal maturity history using geochemical data and 1D basin modeling from five exploration wells (ABDX-1, BRX-1, KBX-1, KLX-1, and BBX-1). The analysis identifies several potential source rock intervals ranging from Permian, Jurassic, Cretaceous, to Tertiary ages. Geochemical evaluation reveals a stark contrast between depocenters and structural highs. Wells in the northern and southern depocenters (ABDX-1 and KLX-1) contain source rocks of fair to excellent quality that have reached optimal thermal maturity phases, ranging from peak to late mature. Conversely, wells in the structural high areas (BRX-1, KBX-1, and BBX-1) are to be non-generative as all source rock intervals remain immature due to insufficient burial history. Thermal history reconstruction indicates that the main phase of hydrocarbon generation occurred in the Neogene, triggered by a surge in sedimentation rates in response to the Melanesian Orogeny. This study concludes that exploration in the structural highs of the Arafura Basin carries high source rock risk, and successful hydrocarbon accumulation in these areas relies heavily on lateral migration from active hydrocarbon kitchens developing in the northern and southern depocenters.  
Machine Learning-Based Prediction of Formation, Facies, Porosity, and Permeability in a Carbonate Reservoir of the "GTR" Field Mahfudhoh, Sayyidah Adilia; Welayaturromadhona
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.v49i1.1969

Abstract

Reservoir characterization is essential for understanding rock and fluid behavior in hydrocarbon field development. In the Baturaja Formation, Sunda Basin, this process i s challenging due to heterogeneity resulting from depositional and diagenetic variations. Limited core data and the high cost of conventional analysis encourage the use of machine learning (ML). This study aims to predict formation, facies, porosity, and permeability using ML algorithms and to assess the impact of feature augmentation. The dataset includes well log and core data from 13 wells. The workflow consists of preprocessing, feature selection, feature engineering, and supervised learning using Decision Tree, Random Forest, XGBoost, and KNN. Performance is evaluated using the F1-score for classification and MAE/RMSE for regression, followed by blind testing on wells HARLEY and XSR. Random Forest achieves the best formation prediction (F1-score 0.9890; blind test 0.9975) because the well data fall within the range of the training data distribution, although accuracy decreases in XSR due to differences in data distribution. XGBoost is the most accurate for facies prediction, improving from an F1-score of 0.9648 to 0.9741 after feature augmentation. For porosity and permeability, Random Forest produces the lowest errors, although permeability remains challenging in heterogeneous carbonates. Overall, ML provides an efficient and accurate approach, with Random Forest and XGBoost performing best, and feature augmentation consistently enhancing model generalization.
Enhancing Subsurface Geological Model Resolution in Challenging Seismic Conditions by Using Model-Based Deterministic Inversion Mawalid, Abi; Haris, Abdul; Wijanarko, Edy
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.v49i1.1976

Abstract

The limited resolution of 2D seismic data often limits the accuracy of subsurface interpretation. This study explores how deterministic inversion enhances the elastic representation of low-resolution intervals in Field X and contributes to more precise reservoir interpretation. By applying deterministic inversion, this study aims to improve the mapping of lithological variations throughout the interval. Petrophysical data show that the target zone contains porosity values of 11–22%, Gamma Ray readings of 10–120 API, and P-impedance values of 11022–15343. These parameters support well–seismic tying and model calibration. The inversion generates an acoustic impedance model that closely aligns with the log trends and shows a coherence error of only 6.23% within the target interval. Domains with increased permeability and reduced GR readings appear as subtle impedance irregularities, whereas more consolidated phases show higher impedance. The resulting impedance response captures geologically meaningful mid-range lithological variations, although limitations in seismic resolution still reduce the precision of stratigraphic delineation. Overall, the findings demonstrate that careful calibration with petrophysical datasets provides a consistent and quantifiable impedance framework, even in areas with limited seismic fidelity, thereby supporting more reliable reservoir interpretation.
Reservoir Characterization of the Terumbu and Arang Formations Using Model-Based Seismic Inversion in the East Natuna Basin Adham Syahputra, Guntur; Haris, Abdul; Wibowo, Ricky Adi; Wijanarko, Edy
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.v49i1.1979

Abstract

The Miocene carbonate buildup and fine-grained clastic sequence constitute the main reservoir and sealing intervals in the East Natuna Basin. This study characterizes the reservoirs of the Terumbu and Arang Formations using an integrated workflow that includes petrophysical analysis, sensitivity analysis, depth structure mapping, and model-based seismic inversion. Well-log interpretation shows clear lithological contrasts between the two formations. The Terumbu carbonates exhibit very low gamma-ray values (18 to 24 API) and high porosity, ranging from 28 to 37%, with neutron–density crossovers indicating gas-bearing intervals, particularly in the GADO-3 well, where resistivity values range from 852 to 1958 Ω·m. In contrast, the Arang Formation is characterized by high gamma-ray values (102 to 148 API), higher clay volume (30 to 44%), and low porosity (<10%). P-impedance–density cross-plots distinguish carbonate rocks (4,500 to 10,000 g/cc·m/s; 1.7 to 2.35 g/cc) from shale and shaly sand with higher impedance and density. Depth structure mapping reveals a central–northern structural high that is favorable for reef development and fault-related trapping. Model-based seismic inversion further reveals low-to-moderate impedance (4,100 to 6,156 g/cc·m/s), low density, and high inverted porosity within the Top Terumbu interval, indicating excellent reservoir quality. Overall, the results indicate that the Terumbu Formation forms the primary carbonate reservoir, while the Arang Formation mainly acts as an effective regional seal in the petroleum system of the East Natuna Basin
Depositional Facies Influence on Reservoir Heterogeneity in The Balikpapan Formation, Lower Kutai Basin: Insights Well Log Analysis Wahid, Abd.; Sultan; Meutia Farida; Jamaluddin; Ryka, Hamriani
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.v49i1.1985

Abstract

This The Balikpapan Formation in the Lower Kutai Basin hosts a complex assemblage of fluvial-to-deltaic reservoir facies whose heterogeneity significantly influences reservoir quality and connectivity. This study integrates well-log interpretation, electrofacies classification, and quantitative petrophysical evaluation from six wells to assess the stratigraphic controls governing reservoir distribution. Three main facies associations are identified: channelised sandstones, mouth-bar to delta-front, and prodelta. Proximal channel sands exhibit the highest porosity (18–30%) and permeability (5–40 mD), but their limited lateral continuity results in poor interwell connectivity. Mouth-bar and delta-front sands display moderate porosity (12–25%) and permeability (<1–30 mD) and form laterally extensive, sheet-like bodies that enhance reservoir connectivity under increasing tidal influence. Thick prodelta mudstones act as regionally extensive vertical seals. The stratigraphic framework is characterised by repeated upward- coarsening parasequences bounded by marine flooding surfaces, reflecting alternating phases of delta progradation and transgression. These results demonstrate that depositional processes and stratigraphic architecture are the primary controls on reservoir heterogeneity in the Lower Kutai Basin.
Determining The Dynamics of The Petroleum Buffer Reserve of Indonesia Prima, Andry; Moengin, Parwadi; Astuti, Pudji; Sari, Emelia; Nugrahanti, Asri; Jawaid Butt, Osama
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.v49i1.1987

Abstract

This study develops an integrated system dynamics and probabilistic Monte Carlo simulation framework to evaluate Indonesia’s Petroleum Buffer Reserve (PBR) strategy in alignment with Perpres 96/2024 and the nation’s broader energy security agenda. Monte Carlo simulation results reveal that only the scenario characterized by full import availability is capable of achieving the mandated 10.17-million-barrel reserve target, while all other scenarios consistently fail to accumulate sufficient stock under uncertainty. The probabilistic analysis further shows that this scenario yields a probability exceeding 98% of meeting or surpassing the target, in contrast to the near-zero success rates observed under restricted import conditions. Days-of-cover optimization highlights an additional strategic vulnerability: the current PBR target corresponds to only about 12 days of crude import protection. Building on the system’s dynamic behavior, this study recommends a minimum reserve target of 30 days as an immediately achievable benchmark. A 60-day reserve is identified as a feasible medium-term objective, provided that replenishment rates and storage capacity are enhanced. Achieving a 90-day reserve, consistent with international strategic stockpiling standards, would require substantial investment and diversification of supply sources. These findings underscore Indonesia’s structural dependence on imported crude oil and emphasize the need for assertive replenishment policies to strengthen national energy resilience
Prediction of S-Wave Using Conventional Method and Machine Learning Dayyan Dhaifullah; Winardhi, Sonny; Dinanto, Ekkal
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.v49i1.1988

Abstract

Shear-wave velocity (Vs) is an essential metric for subsurface characterization and CO₂ storage evaluation. However, Vs measurements are frequently unavailable in mature fields due to limited data acquisition. This research employs a machine-learning approach utilizing a Fully Connected Neural Network (FCNN) to predict Vs and Vp/Vs logs at a potential CO₂ injection site within a heterogeneous carbonate reservoir. Seismic elastic properties, particularly Acoustic Impedance (AI) and Vp/Vs, play a crucial role in assessing reservoir capacity by linking elastic responses to petrophysical properties such as porosity and water saturation. Conventional approaches, including the Castagna empirical relationship and Multiple Linear Regression (MLR), are commonly used for Vs estimation. Nevertheless, these methods often inadequately account for fluid-related effects. To address this limitation, this study examines two predictive approaches: (1) indirect Vp/Vs derived from predicted Vs, and (2) direct prediction of Vp/Vs prediction using a FCNN model. The findings indicate that direct Vp/Vs prediction demonstrate stronger correlation with observed data (R = 0.8023) and improved sensitivity to lithological and fluid variations compared to traditional methods. These findings underscore the advantage of directly predicting fluid-sensitive elastic properties through machine learning, providing a more reliable framework for reservoir characterization and CO₂ storage assessment in data-constrained carbonate formations.
The Study of Residual Chemical Carryover in Gas Well Production Facilities: A Case Problem Purnomosidi; Indriani, Erdila; S. Putri, Lathifah; Rahalintar, Pradini; Harnada R., Restu
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.v49i1.1996

Abstract

The PT JM Field is capable of producing approximately 133 MMSCFD of gas and 5,600 BCPD of condensate with fluid behavior characterized by retrograde condensation such as mercury-bearing gas systems. These conditions show the importance of filtration in ensuring safe and reliable downstream operations. However, an operational issue was identified in 2024 in the form of an unusually high differential pressure which reached 30 psid across the Condensate Mercury Pre-Filter. The condition was a reflection of partial blockage at the filter outlet and led to a reduction in the system performance. Therefore, this study aimed to identify the root cause through the laboratory analysis of sludge collected during pipeline pigging between the PG and the KCR Gas Plants. The results showed that the GEOPIC sample consisted of 12.03 wt.% solid and 21.52 wt.% liquid fractions while the BIDI2 had 5.70 wt.% and 42.86 wt.% respectively. Elemental analysis also confirmed the presence of C, H, N, S, and Na while FTIR spectroscopy showed characteristic C=N, N–H, and S=O functional groups which were the reflection of a strong similarity to imidazolinamide-based corrosion inhibitors. Ionic analysis further detected Cl⁻, PO₄³⁻, and NH₄⁺ ions in the pigging fluid which were commonly associated with the corrosion inhibitors applied in the system. The results led to the implementation of several mitigation measures such as filter replacement, pipeline pigging optimization, and equipment inspection during the Turnaround (TAR). These actions successfully mitigated sludge accumulation and restored normal filtration performance.
Probabilistic Thin-Bed Sandstone Reservoirs Delineation in The Montara Formation, Browse Basin, Using Stochastic Inversion and AVF-A (Intercept) Analysis Arhab, Fadhil; Winardhie, Ignatius Sonny
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.v49i1.1997

Abstract

In the pursuit of net zero-emission targets, restrictions on new oil and gas field discoveries have intensifies the need for enhanced reservoir characterization of secondary resources in mature fields, such as thin-bed reservoirs. However, imaging thin-bed remains challenging due to the limited vertical resolution of conventional seismic data. Advanced methodologies are therefore required to accurately delineate thin-bed sandstone reservoirs and improve reservoir prediction reliability. This study integrates seismic frequency attributes and stochastic seismic inversion to enhance vertical resolution and characterize thin-bed reservoirs within the Montara Formation, Browse Basin. The workflow begins with tuning thickness analysis to identify thin-bed responses, followed by the construction of reflectivity volumes for intercept-based amplitude variation with frequency (AVF-A) analysis and seismic inversion. The results indicate that thin-bed sandstone reservoirs were predominantly deposited during the syn-rift phase and exhibit a Northeast (NE)–Southwest (SW) orientation. These reservoirs are distributed in the eastern well area of the SW region and the western well area of the NE region, with thicknesses of up to 140 m. Probabilistic inversion results indicate reservoir probabilities exceeding 50% within the target zones. These findings demonstrate that integrating seismic frequency attributes with stochastic seismic inversion provides a robust framework for thin-bed bed delineation and reservoir prediction under sub-tuning conditions.
Evaluating Petrographic and Mechanical Property Correlations in Sihapas Formation for High-Pressure Hydraulic Fracturing Using Pearson and Spearman Methods Prayitno, Budi; Akhillah, Daffa; Novrianti; Fitiransyah, Dike; Panuh, Dedikarni
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.v49i1.1999

Abstract

This study aimed to evaluate the suitability of natural frac sand (SiO₂) from the Sihapas Formation as a proppant for hydraulic fracturing in unconventional oil and gas reservoirs in Riau Province, Indonesia. Quantitative–qualitative evaluation in hydraulic fracturing systems is conducted to assess the performance of quartz grains (SiO₂) in enhancing and maintaining fluid flow conductivity under the influence of stress, formation blockage, and chemical interactions. Sieve distribution analysis was performed to determine particle size distribution, crush resistance testing was conducted to evaluate mechanical strength, and X-Ray Diffraction (XRD) was used to characterize mineral composition. The correlative relationships among parameters were further analyzed using Pearson and Spearman statistical methods, with API RP 56 (frac sand) and API 19C (proppant) standards serving as benchmarks. The results showed that the 40/70 mesh fraction dominates across samples, though roundness values fall below specification thresholds while sphericity remains within acceptable ranges. Grain hardness testing at 5000 psi showed relatively high destruction rates, while mineralogical analysis confirmed a consistently high SiO₂ composition (≥98%) with secondary clay minerals. Elevated turbidity and alkaline pH values were also observed. Statistical analysis showed strong correlations among parameters, reflecting the influence of geological transport processes on grain morphology and mineral decomposition due to diagenetic processes. In general, these findings showed that natural frac sand samples do not fully meet API standards, highlighting the need for innovation and direct well testing to enhance material quality for hydraulic fracturing applications.

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