International Journal of Oil, Gas and Coal Technology (42 papers in press)

Regular Issues

• Open Access

  Integration of computational algorithms in enhancing geological modelling and drilling efficiency in coal mine exploration ( Free Full-text Access )

  by Xingen Ma, Yubo Song, Qinghai Zou, Ying He, Bo Pan, Sixuan Ye, Biwen Li, Guang Yang, Fuhong Li, Kamel Bou-Hamdan 
  Abstract: Coal calorific value calculation is crucial for power planning and mine exploration. Traditional lab techniques and empirical calculations often fail with high variability or limited data. We developed a machine learning framework for small-sample scenarios, combining compositional characteristics, data augmentation, and Bayesian hyperparameter adjustment to improve prediction accuracy. Four regression models (ANN, SVR, decision tree, and LightGBM) were trained on proximate, ultimate, and petrographic features to predict coal calorific value. Among these, the LightGBM model achieved the highest predictive performance with a test (R2 approximately 0.93) and the lowest error (RMSE approximately 0.19), outperforming the ANN (R2 approximately 0.91) and other models. Fixed carbon (FC) and volatile matter (VM) were the key predictors of calorific value, aligning with domain knowledge and model interpretability. The improved data-driven approach reliably estimates coal energy content from small samples, enabling evidence-based geological modelling and better drilling decisions for increased exploration efficiency. [Received: January 16, 2026; Accepted: May 8, 2026]
  Keywords: calorific value prediction; light gradient boosting machine; LightGBM; artificial neural network; ANN; feature engineering; data augmentation; hyperparameter optimisation; coal characterisation; coal quality prediction.
  DOI: 10.1504/IJOGCT.2026.10079168
   
  
• Numerical simulation of hydraulic fracture propagation in hot dry rock reservoirs integrating wellbore-reservoir-fracture  
  by Dagang Ji, Jingen Deng, Yongcun Feng, Xiaorong Li, Shuai Zhang 
  Abstract: Hot dry rock (HDR) represents a typical high-temperature, ultra -low permeability reservoir, where hydraulic fractures must be created to provide efficient heat-exchange pathways for geothermal energy extraction. In this paper, a fully thermal-hydro-mechanical (THM) coupled numerical model for HDR reservoirs’ hydraulic fracturing was established to study the hydraulic fracture propagation mechanism and reservoir mechanical response characteristics under low-temperature shock. The half-fracture length calculated by the KGD model was compared with the simulation results to verify the model's accuracy. The results show that the tensile stress and temperature gradient at the low-temperature shock boundary are relatively high. After the rock fractures, the temperature and tensile stress values inside the rock decrease but their range expands. The hydraulic fracture morphology is more sensitive to reservoir temperature than to the thermal expansion coefficient. Furthermore, the temperature hysteresis effect produced by the increase in injection displacement reduces the thermal stress at the fracture tip. [Received: September 6, 2024; Accepted: August 11, 2025]
  Keywords: rock mechanics; hot dry rock reservoirs; fracture propagation; thermal-hydro-mechanical coupled.
  DOI: 10.1504/IJOGCT.2025.10073280
   
  
• Geopolitical dynamics and the sustainable future of global energy supply chains  
  by Saurav Negi, Shantanu Trivedi 
  Abstract: The ongoing geopolitical crisis in Europe has had a global impact on the energy sector, underscoring the pivotal role that geopolitics plays in stabilising or destabilising energy supply chains. Beyond the immediate disruption, this crisis imparts valuable lessons for future resilience in global energy management. Amid an environment shaped by energy market volatility, resource scarcity, and climate concerns, this study examines the current state of the energy supply chain and the profound influence of geopolitical factors on its security and sustainability. Using a narrative literature review approach, this paper examines how geopolitical factors, including the RussiaUkraine conflict and Middle East tensions, influence energy security and accelerate the transition toward renewable and low-carbon energy solutions. The findings reveal critical insights into the operational state of the energy supply chain, illustrating how geopolitics is influencing energy security and sustainability efforts. The study also outlines a pathway forward, encouraging stakeholders to adopt a holistic perspective that includes all significant influences on the energy ecosystem. This paper offers comprehensive recommendations for sustainability strategies and policies that integrate considerations for energy security, environmental sustainability, and geopolitical risk. [Received: December 14, 2024; Accepted: August 20, 2025]
  Keywords: energy supply chain; energy security; sustainability; geopolitical crisis; supply chain resilience.
  DOI: 10.1504/IJOGCT.2025.10073511
   
  
• Multi-dimensional integrated monitoring 3D model and high-precision real-time analyzing method of multipoint microleakage field in the well site of underground gas storage  
  by Xianjian Zou, Weimin Han, Feng Chen, Huan Song 
  Abstract: This study addresses significant challenges including low detection accuracy, multiple placement points, diverse influencing factors, and unstable performance of microleakage detection sensors at underground gas storage well sites. It proposes a point-line-surface multidimensional integrated monitoring 3D model for well site layout and a cost-effective, high-precision real-time analysis method for multipoint microleakage fields. Two or three point-type natural gas sensors and one linear-type laser methane detector were amalgamated to monitor potential gas leakages at key points on the well site in real time. To achieve high-precision real-time monitoring and early warning of natural gas leakages across the entire well site, a point-line-surface multidimensional integrated monitoring 3D model was developed. This model was used to simulate the multipoint microleakage patterns of the well site, followed by an analysis of the microleakage field using a cost-effective, real-time analysis method, reducing the false alarm rate of safety monitoring and early warning systems. [Received: March 20, 2025; Accepted: June 19, 2025]
  Keywords: underground gas storage; microleakage model; safety monitoring; multi-dimensional integration; laser sensor.
  DOI: 10.1504/IJOGCT.2025.10073659
   
  
• Contemporaneous and lagged transmission mechanism among geopolitical risks, uncertainty and energy prices: a spatial heterogeneity perspective  
  by Shuiyang Chen, Bin Meng, Wenyu Xu 
  Abstract: Due to market spatial differentials, geopolitical risks and uncertainty from various sources exhibit diverse transmission mechanisms, both contemporaneous and lagged, in the globalised energy market. We employ geopolitical risk indices for six major global regions and utilise a novel connectedness approach to analyse the heterogeneous impacts of various sources of geopolitical risks and uncertainty on the energy market. Our findings indicate that geopolitical risks in Europe (North and East) and North America wield the greatest influence. Asia and Oceania, along with South America, significantly impact the energy market. The US economic policy uncertainty demonstrates a stronger explanatory power for energy prices. The total connectedness is 92.61%, with 56.18% caused by contemporaneous dynamics while 36.43% the lagged. Lagged dependencies elucidate a substantial portion of the market risk dynamics. Major geopolitical conflicts result in reduced contemporaneous shocks and heightened lagged shocks. Our conclusions underscore the need for policymakers and traders to discern the heterogeneous impacts and lagged effects of diverse geopolitical risks and uncertainty on the energy market, ensuring comprehensive risk management and robust trading decisions. [Received: November 15, 2024; Accepted: July 23, 2025]
  Keywords: geopolitical risk; uncertainty; energy market; connectedness; spatial heterogeneity.
  DOI: 10.1504/IJOGCT.2025.10073681
   
  
• Different treatment techniques of oilfield produced water - a review  
  by Aarzoo Mayur Jobanputra, Balasubramanian Ragunathan, Swastik Mazumder, Aastha Maurya, Arth Padaria 
  Abstract: Oilfield produced water (OPW) is an inextricably linked component in crude oil recovery processes. It is the most significant type of waste generated during hydrocarbon production. It contains high concentrations of organic and inorganic salts, heavy metals and sand particles. Exploration and production operations also generate large volumes of brine water. Due to the complex and hazardous composition of OPW, it cannot be discarded into the environment. With respect to the global rise in industrial activities, crude oil production has increased considerably, subsequently, the generation of OPW. This makes it necessary to manage OPW in a sustainable and eco-friendly manner. Currently, the focus is on treating OPW to make it suitable for reuse. Various physicochemical and biological methods are used for its treatment. This article discusses the reuse of OPW and different treatment methods. The regulation of different parameters such as oil-in-water in OPW, as employed by the industry are reviewed. [Received: March 30, 2024; Accepted: February 21, 2025]
  Keywords: exploration; petroleum; produced water; treatment methods.
  DOI: 10.1504/IJOGCT.2025.10074387
   
  
• Condensation pattern of moist blast furnace gas in pipelines  
  by Yuwen Liu, Xinmin Liu, Dawei Zhang, Wenqiang Sun 
  Abstract: During pipeline transport, acidic condensate containing chloride ions precipitates from dry-dedusted blast furnace gas (BFG) as its temperature decreases. To investigate the mechanisms of this phenomenon, this study analyses heat transfer processes in BFG condensation within pipelines and proposes a computational model to predict condensate formation. Using this model, the study determines the amount and location of condensate precipitation under different ambient temperatures, and variations in BFG temperature, pressure, pH, and chloride ion concentration along the pipeline. Computational results indicate that at 20 C ambient temperature, condensate starts precipitating at 1,100 m from the pipeline inlet. When ambient temperature decreases to -10 C, the precipitation point shifts to 2,200 m from the inlet. Lower ambient temperatures result in condensate forming farther from the pipeline inlet. [Received: March 26, 2025; Accepted: July 14, 2025]
  Keywords: blast furnace gas; BFG; condensate; chloride ion; pipeline transport; computational modelling.
  DOI: 10.1504/IJOGCT.2025.10074502
   
  
• Risk analysis and safety enhancement for tank inspection and maintenance using track cross theory and vortex tube technology  
  by Xing Chen, Peng Wang, Dongxu Gao, Rui Huang, Li Liang 
  Abstract: The inspection and maintenance of storage tanks are essential daily tasks in the production and operation of oil and gas fields. Based on on-site production analysis, the primary issues include a poor working environment (characterised by high temperatures and low oxygen levels) and operation process risk (such as unclear worker status and improper procedures). This study utilised on-site production practices to explore and implement two technologies namely, the risk control system and vortex tube technology in the inspection and maintenance of storage tanks. The research yielded remarkable results. Test results indicate that: 1) the risk control system effectively strengthens supervision during operations, monitors risk points with the assistance of mechanical devices, and mitigates the impact of personnels inadequate safety awareness and technical skills; 2) the application of vortex tube technology significantly improves working conditions within confined spaces by regulating temperature and continuously supplying air, thereby ensuring the physical well-being of personnel. [Received: July 28, 2025; Accepted: September 24, 2025]
  Keywords: risk control system; vortex tube; storage tank; confined space; occupational safety.
  DOI: 10.1504/IJOGCT.2025.10074754
   
  
• Predicting model of natural gas price based on a multi-strategy GWO-LSTM algorithm  
  by Hanyu Xie, Changjun Li, Wenlong Jia, Jie He 
  Abstract: The price of natural gas fluctuates in the stock market, thus an accurate price prediction is a key indicator for the development of medium and long-term planning in the industry. Here, the daily price fluctuation of natural gas is treated as a nonlinear and non-stationary time series prediction. The LSTM model and the LSTM combined with the grey wolf algorithm were adopted for training and testing. A multi-strategy GWO-LSTM model is proposed, which improves the global search ability and convergence speed by using chaotic variable search to replace random search, adding adaptive weight coefficient, and modifying control parameters. The prediction of the improved model compared with other methods is carried out using Henry Hub gas price data, which has been logarithmically processed to improve the distribution characteristics and remove the outliers. The improved algorithm has better performance in the convergence speed, prediction error, and stronger adjustment of trend fluctuation. [Received: July 12, 2024; Accepted: January 9, 2025]
  Keywords: natural gas price; neural network; long short-term memory; LSTM; prediction algorithm.
  DOI: 10.1504/IJOGCT.2026.10075629
   
  
• Mechanical properties and acoustic-emission energy-frequency characteristics of gas-bearing coal under different stress paths  
  by Erhui Zhang, Baokun Zhou, Changfeng Li, Chaoyang Zhu, Liang Sun 
  Abstract: Gas-bearing coal-rock dynamic hazards threaten mining safety, but their mechanisms under complex stress paths are unclear. This study examined the mechanical properties and acoustic emission (AE) energy-frequency characteristics of gas-bearing coal under three stress paths: meso-shear, confining pressure unloading, and triaxial compression. Key findings include: 1) different paths caused significant variations in the size and location of Mohr stress circles due to changes in effective stress and stress differences; 2) The AE energy-frequency fractal characteristics showed a consistent damage evolution pattern across all paths initial fluctuation, followed by a steady decrease, and a final drop to a minimum at rupture though specific values and evolution rates differed; 3) the average fractal dimension increased with gas pressure and was highest under meso-shear, followed by confining pressure unloading and triaxial compression. These results offer insights for early warning of coal-gas disasters and improved coalbed methane extraction. [Received: September 11, 2024; Accepted: September 21, 2025]
  Keywords: gas-bearing coal; different stress paths; acoustic emission energy frequency; strength properties; fractal dimension.
  DOI: 10.1504/IJOGCT.2026.10075630
   
  
• Research on the prediction method of rock uniaxial compressive strength using digital drilling technology  
  by Zhaoyu Wen, Mingming He, Mingchen Ding, Haoteng Wang, Qin Zhao 
  Abstract: The uniaxial compressive strength (UCS) of rock is one of the key indicators for evaluating its mechanical properties. This study employed self-developed equipment to conduct drilling experiments on sandstone and limestone. The segmented drilling method enhanced data continuity, accuracy, and controllability. Results showed that the uniaxial compressive strength (UCS) obtained by this method had lower variability, with the average value in the second stage being 4.42 MPa higher than in the first stage. The friction coefficient, derived from the relationship between drilling parameters and cutting force, combined with rock type, was used to establish a UCS prediction model. The discrepancy between model-predicted UCS values and those from uniaxial compression tests was only 4.44%, verifying the method s reliability. This study provides an efficient in-situ assessment method for rock mechanical properties. [Received: October 31, 2024; Accepted: December 6, 2024]
  Keywords: digital drilling; uniaxial compressive strength; segmented drilling method; model prediction.
  DOI: 10.1504/IJOGCT.2026.10075851
   
  
• Study on flow-induced variations in permeability characteristics of silty clay sediments from the perspective of fine migration and channelisation  
  by Man Huang, Dongchao Su, Zhirui Zhao, Yuzhe Cheng, Yiheng Ma, Yajie Mao, Zhun Zhang, Fulong Ning 
  Abstract: The well productivity is closely related to the permeability of sediments left by the decomposition of natural gas hydrate (NGH). To investigate the permeability evolution of silty clay sediments under fluid flow, column flow experiments were conducted with reconstituted sediment samples from core data in the Shenhu Sea Area. The results indicate that fluid flow can remarkably change the permeability of clay silty sediments. Even a small flow rate can reduce sediment permeability. There exists a critical flow rate that can improve sediment permeability. At a certain flow rate, the permeability fluctuates irregularly rather than monotonic variation. As the flow rate increases, the sediment average permeability first decreases then increases and finally decreases. The large porosity, increased fine sand content, and high clay content aggravate the flow-induced permeability damage. The work provides a reference for stimulation and protection of NGH reservoirs. [Received: December 12, 2024; Accepted: March 27, 2025]
  Keywords: natural gas hydrate; NGH; clay silty sediments; flow-induced permeability variations; fine migration; channelisation.
  DOI: 10.1504/IJOGCT.2026.10076051
   
  
• FAME analysis and chromatographic studies of sunflower oil biodiesel  
  by Vishal Kumar, Debasish Das 
  Abstract: This article explains about the base-catalysed transesterification process that was used to extract sunflower biodiesel from the sunflower seeds of Indian origin. The experiment was conducted at optimum conditions of 60 C reaction temperature, with a 9:1 (methanol/oil) molar ratio, 0.45% w/w KOH catalyst and 350 rpm stirring speed for 60 minutes. The base catalysed transesterification technique is used to produce biodiesel with an optimal yield (89%). GC-MS is currently being utilised to investigate the methyl esters of biodiesel generated from sunflower oil. The efficacy of gas chromatography-mass spectrometry (GC-MS; Shimadzu, Japan) was tested in the analysis and detection of FAME-fatty acid methyl ester content in sunflower biodiesel. Using FAME analysis, the fuel characteristics of sunflower oil biodiesel were also calculated and discussed in relation to ASTM D6751 standards for biodiesel. [Received: April 14, 2023; Accepted: April 18, 2025]
  Keywords: sunflower biodiesel; transesterification; methyl esters; characteristics; FAME analysis.
  DOI: 10.1504/IJOGCT.2026.10076175
   
  
• Machine learning-based prediction strategy for sustainable diesel engine operation using a tri-fuel blend  
  by Naseem Khayum, Jakeer Hussain Shaik, Krishna Kumar Pandey, Y. Nandakishora 
  Abstract: The investigation involves the introduction of acetylene at different flow rates to evaluate its effects on critical performance and emission parameters of a low heat rejection (LHR) diesel engine run on ternary blend. Advanced machine learning methodologies, especially random forest regression (RFR) and polynomial regression (PR), are utilised to forecast the engine’s performance and emissions. The findings demonstrate that the LHR engine, powered by the ternary blend and augmented with acetylene induction, exhibits a large improvement in brake thermal efficiency (BTE) and substantial decreases in hydrocarbon (HC) and carbon monoxide (CO) emissions and nevertheless, there is a simultaneous increase in NOx emissions. RFR demonstrates more accuracy in predicting performance and emission characteristics than PR among the utilised predictive models. Furthermore, the utilisation of machine learning models demonstrates significant efficacy in precisely forecasting engine performance and emission metrics, providing a dependable approach for enhancing engine operations. [Received: January 24, 2025; Accepted: July 3, 2025]
  Keywords: acetylene; ternary blend; low heat rejection diesel engine; machine learning.
  DOI: 10.1504/IJOGCT.2026.10076374
   
  
• Leakage detection method of acoustic emission pipeline based on deep convolutional neural network transfer learning  
  by Xinying Wang, Haojie Tian, Honglei Che, Haiqun Chen 
  Abstract: In this study, we propose a transfer learning method based on a deep convolutional neural network (DCNN-TL), where a gas pipeline system simulates various degrees of pipeline leakage with valve openings, generating original acoustic emission (AE) signal data under different conditions. We convert the AE signals into three-channel images, denoise them using Gaussian-non-local mean (G-NLM) joint filtering, and use these as input for a convolutional neural network (CNN). Six pre-trained CNN models undergo iterative training. The results show that the average accuracy of the pre-trained CNN model on the AE image dataset improves by 3.35%, 9.02%, 5.35%, 6.74%, 10.09%, and 4.80%, respectively. This method avoids reliance on expertise and complex signal processing, is computationally efficient, and enables precise pipeline leak detection in various operational scenarios. [Received: February 18, 2025; Accepted: July 3, 2025]
  Keywords: convolutional neural network; CNN; transfer learning; acoustic emissions; pipeline leak detection.
  DOI: 10.1504/IJOGCT.2026.10076495
   
  
• Data-driven analysis and predictive modelling of PDC and tricone bit performance in field drilling operations  
  by Azirulkheen Song Bin Muhamad Azlan, Bashir Suleman Busahmin, Amer Dermirovic 
  Abstract: Bit type and controllable drilling parameters strongly influence rate of penetration (ROP), torque/drag, and non-productive time (NPT). This study compares field performance of polycrystalline diamond compact (PDC) and tricone bits and develops predictive models for ROP and bit wear using multi-well metadata and surface drilling measurements. After quality control and data imputation, key features including mechanical specific energy (MSE), depth-normalised weight on bit (WOB), and torque were engineered. Gradient boosting, XGBoost, and elastic net models were evaluated for ROP prediction, while logistic regression, random forest, and XGBoost were applied for wear classification using grouped cross-validation. Results show that PDC bits achieve higher ROP at comparable WOB but are more sensitive in interbedded formations, whereas tricone bits require higher torque yet maintain steadier MSE in abrasive intervals. The proposed workflow supports data-driven bit selection and parameter optimisation to reduce bit-related NPT while balancing ROP and cost per meter. [Received: 18 August 2025; Accepted: 16 October 2025]
  Keywords: PDC bit; tricone bit; bit wear prediction; rate of penetration; ROP; stick-slip; non-productive time; NPT.
  DOI: 10.1504/IJOGCT.2026.10076496
   
  
• The formation mechanism of laumontite and its effect on reservoir quality in Upper Triassic Chang-63 tight oil sandstones, Ordos Basin  
  by Guichao Du, Qianshan Zhou, Ruiliang Guo, Yuanhao Li, Mingxian Wang, Ying Wang, Xingyu Huang 
  Abstract: Based on porosity-permeability measurements, thin-section petrography, SEM observations, and XRD analyses, the diagenetic features of sandstones from the Chang 63 reservoir were investigated. The results indicate that three distinct stages of laumontite cementation developed during burial. Laumontite initially precipitated as pore-filling cement during the syngenetic to early diagenetic stages, controlled by sedimentary environment, provenance, and feldspar albitisation. During mesodiagenesis, laumontite re-precipitated from alkaline pore fluids, with Ca2+, Na+, and SiO2 derived from dissolution of earlier cements and detrital minerals. Early laumontite cement inhibited compaction and helped preserve primary porosity, whereas its subsequent dissolution significantly enlarged pore spaces and improved pore-throat connectivity. The overall impact of laumontite on reservoir quality is therefore dual and strongly dependent on the intensity of dissolution processes. [Received: September 6, 2023; Accepted: December 1, 2024].
  Keywords: laumontite; diagenesis; reservoir quality; Yanchang Formation; Ordos Basin.
  DOI: 10.1504/IJOGCT.2026.10076677
   
  
• Experimental study on combustion, exergy and emission analyses in a dual-fuel compression ignition engine using hydrogen and biodiesel  
  by Krishnamani Selvaraj, Rajamohan Ganesan, M. Yogeshkumar, M. Harikishore 
  Abstract: Hydrogen is a promising energy source for internal combustion engines because of its reliability, production from renewable energy sources, and clean combustion products. Hydrogen could be used in the diesel engine in dual-fuel mode with significant engine modifications. In this research work, combustion and exergy analyses were carried out to investigate the performance of the dual-fuel engine employing diesel and frying oil methyl ester (biodiesel) as a pilot fuel. In the compression ignition engine, the hydrogen is fumigated with the intake air stream at different volume flow rates of 3, 6, and 9 litres per minute, biodiesel as a pilot fuel. A diesel engine is modified and operated as a dual-fuel engine with biodiesel as a pilot fuel. The maximum brake thermal efficiency of the dual-fuel engine with biodiesel (B100) is 34.10%, 32.04%, 30.79%, and 29.82% corresponding to different hydrogen energy shares of 9.89%, 6.19%, 2.97%, and 0% is observed at the rated load condition. The maximum exergy efficiency of 46.34% is achieved with dual fuel engine using hydrogen fumigation at the engine rated load. The unburnt HC, CO, and smoke emissions are observed to be decreased with an increase in the hydrogen flow rate. [Received: May 21, 2025; Accepted: October 6, 2025]
  Keywords: dual fuel engine; biodiesel; hydrogen fumigation; exergy analysis; combustion characteristics; emissions.
  DOI: 10.1504/IJOGCT.2026.10076731
   
  
• Graphene and graphene nanoribbons: insights into structure, properties, production, and applications in the oil and gas industry - a comprehensive review  
  by Wael A. Farag, Ahmad B. A. Alazmi, Muhammad Nadeem 
  Abstract: This paper provides a comprehensive overview of graphite, graphene, and graphene nanoribbons (GNRs), highlighting their evolution and significance in mechanical and electrical applications. It explores the transformation of graphite into graphene and further into GNRs, which exhibit exceptional physical, electronic, and electrical properties compared to other members of the graphene family. Particular attention is given to the edge structures of GNRs, which play a crucial role in determining their metallic or semiconducting behaviour based on the configuration. The paper also investigates various synthesis methods for GNR production and examines the impact of integrating GNRs into polymer matrices, which significantly enhances their properties and expands their applicability. The primary focus is on leveraging these advancements for innovative applications in the oil and gas industry, demonstrating GNRs’ potential to revolutionise this sector. This review aims to broaden the understanding of GNR properties and inspire further research into their diverse applications, with a special emphasis on their transformative potential in the petroleum industry. [Received: July 4, 2023; Accepted: December 2, 2024]
  Keywords: carbon; graphene; graphite; graphene nanoribbons; GNRs; polymer nanocomposites; oil & gas; petroleum.
  DOI: 10.1504/IJOGCT.2026.10076780
   
  
• Study on wax deposition and its influence during shutdown and restart process of high waxy crude oil pipeline  
  by Wu Liu, Yupeng Guo, Bin Zheng, Liyuan Guo, Qihang Xue 
  Abstract: The Bozi crude oil pipeline transports waxy crude oil, and there is a risk of difficulty in restarting the pipeline due to wax gelation during shutdown in cold environments. In this study, a three-field coupling model - encompassing heat transfer, fluid flow, and wax deposition was developed to simulate the shutdown and restart processes of the entire Bozi crude oil pipeline. The results indicate that, within the maximum safe shutdown duration of the Bozi pipeline, the wax deposition rate during the restart phase increased significantly compared to that during shutdown. Additionally, the required restart pressure was found to be closely related to the crude oil temperature at the time of shutdown. Wax deposition also accelerated the reconstruction of the temperature field during restart. Notably, the peak wax deposition consistently occurred in the transitional zone between hot and cold oil, diminishing progressively as the restart advanced. [Received: August 11, 2025; Accepted: November 25, 2025]
  Keywords: high wax content crude oil; shutdown temperature drop; restart pressure; wax deposition.
  DOI: 10.1504/IJOGCT.2026.10076781
   
  
• Influence of natural fracture occurrence on hydraulic fracturing construction pressure  
  by Lihua Fan, Yucai Yang, Hailong Zhang, Yanzhen Chen, Xu Liu 
  Abstract: Natural fracture occurrence exerts a significant influence on hydraulic fracturing operation pressure in fractured reservoirs. Based on in-situ stress and fracture mechanics theories, mechanical analysis models and operation pressure calculation models incorporating fracture dip and azimuth angles were established, validated with field case studies, and applied to systematically investigate the distribution laws of fracture stress and operation pressure under normal, reverse, and strike-slip fault structures. Results indicate distinct patterns: in normal faults, normal stress, shear stress (30 ~60 dip, 90 /270 azimuth), and operation pressure all increase with dip, peaking at 90 /270 azimuth; reverse faults show azimuth-dependent normal stress trends, with larger shear stress at 40 ~50 dip and oblique azimuths, and operation pressure following normal stress; strike-slip faults exhibit increasing stress and pressure with dip, peaking at 0 /180 azimuth. This model provides valuable theoretical support for optimising fracturing operation parameters. [Received: February 24, 2025; Accepted: October 18, 2025]
  Keywords: fracture occurrence; normal stress; shear stress; fracture pressure; construction pressure.
  DOI: 10.1504/IJOGCT.2026.10077402
   
  
• Study on the morphology of the initial fracture surface of carbonate rocks based on mineral content analysis  
  by Xu Liu, Qin Li, Jianwei Zhang, Wenling Chen, Na Li 
  Abstract: Fracture surface roughness is a key factor influencing carbonate rock fracturing stimulation effectiveness, yet the quantitative impact of mineral content differences on fracture morphology and corresponding prediction methods remain unclear. This study focuses on carbonate rocks, exploring the relationship between fracture surface morphological characteristics and mineral composition heterogeneity via fractal theory combined with mineral content analysis. 3D laser scanning acquires fracture surface point cloud data, with multi-dimensional roughness parameters (per ISO 25178) and box-counting method-calculated fractal dimension as characterisation indices. A mineral heterogeneity index is introduced for quantification, and results show its highest fitting degree (88.41%) with fractal dimension, outperforming other parameters. A prediction model based on this index is established using the diamond-square algorithm, exemplified by Well A in Fuxian area. This study provides a new method for quantitative characterisation and prediction of carbonate rock fracture morphology, guiding oil and gas field fracturing design. [Received: May 16, 2025; Accepted: August 23, 2025]
  Keywords: fractal theory; mineral content heterogeneity index; fracture morphology; diamond-square algorithm; morphology prediction.
  DOI: 10.1504/IJOGCT.2026.10077403
   
  
• Predicting well cement integrity using open-hole logging and borehole survey data: a novel machine learning approach  
  by Amal Nabillah Abdul Aziz, Stefan Godeke, Mohamad Azwan Yakup, Pg Emeroylariffion Abas 
  Abstract: Cement integrity is crucial for the long-term stability of wells. Traditional assessments using cement bond logs (CBL) are often costly and susceptible to data gaps. This study introduces a novel predictive modelling approach to classify cement integrity along the well depth using machine learning algorithms. Artificial neural network (ANN), K-nearest neighbours (KNN), and support vector machine (SVM) were trained on eleven input parameters from open-hole and borehole surveying logs. Comparative analysis showed that the KNN model excelled, achieving an accuracy of 80.0%, precision of 76.4%, recall of 74%, and an F1-score of 75.0%. Further optimisation using the Youden J index to adjust thresholds based on receiver operating characteristic curve analysis enhanced the KNN models performance to an accuracy of 80.5%, maintaining precision at 76.4%, and F1-score at 75.0%. This methodology offers a cost-effective and reliable alternative for assessing cement integrity in oil and gas wells. [Received: November 10, 2024; Accepted May 12, 2025]
  Keywords: well cement integrity; cement bond log; CBL; cement evaluation; missing well log; artificial neural network; ANN; K-nearest neighbours; KNN; support vector machine; SVM; optimal threshold.
  DOI: 10.1504/IJOGCT.2026.10077489
   
  
• Dynamic permeability model based on Klinkenberg effect: numerical simulation on CBM migration around boreholes and methane extraction practice  
  by Teng Teng, Guoliang Gao, Yanan Gao, Zhenping Sun 
  Abstract: Effective extraction of coalbed methane (CBM) can enhance energy utilisation and mitigate the risks of gas outburst disasters. To investigate the migration characteristics of CBM around boreholes and to determine the optimal borehole spacing for methane extraction, a gas-solid coupling model was established, incorporating the dynamic Klinkenberg effects on permeability in dual-porous coal. This model was implemented in a numerical simulation of methane extraction from the No. 8 coal seam at Dayun Coal Mine, utilising a COMSOL Multiphysics. The results indicate that the seepage velocity of methane can be classified into three distinct stages: a rapid rising stage, a slow rising stage and a stable stage. The optimal borehole spacing is approximately 3.5 m. After 30 days of extraction, the methane content in the coal seam was found to decrease by more than 40%, with maximum residual methane pressure and content recorded at 0.29 MPa and 5.7 m3/t, respectively. [Received: February 20, 2025; Accepted: December 17, 2025]
  Keywords: methane extraction; gas-solid coupling model; effective extraction radius; dynamic permeability model; Klinkenberg effect.
  DOI: 10.1504/IJOGCT.2026.10077549
   
  
• Bias mitigation and model selection in stochastic decline curve analysis  
  by Minhai Luo, Tao Yin, Jianyi Liu 
  Abstract: Decline curve analysis (DCA) estimates oil and gas well productivity but traditional methods lack statistical frameworks for evaluation. This paper introduces a statistical framework by adding error terms to decline curve models, addressing bias in log-transformed data used in traditional DCA. We provide a bias correction method applying adjustment factors before estimation, unlike existing methods that adjust after estimation. Our approach enables direct use of goodness-of-fit measures like Akaike information criterion (AIC) for model selection. Using shale gas production data from Southwestern China, we demonstrate that non-bias corrected DCA significantly underestimates production levels and that AIC effectively guides model selection. [Received: August 29, 2025; Accepted: November 15, 2025]
  Keywords: DCA models; bias mitigation; model selection; Akaike information criterion; AIC.
  DOI: 10.1504/IJOGCT.2026.10077550
   
  
• Study on the self-priming law of heterogeneity in fractured tight reservoirs  
  by Yang Zeng, Chengyong Li, Danni Tang, Xintong Wang, Yu Cheng 
  Abstract: Spontaneous imbibition notably enhances oil recovery in tight reservoirs during hydraulic fracturing and is influenced by factors such as fracture opening width and non-uniform wettability distribution. Understanding how geological heterogeneity affects spontaneous imbibition at the pore scale in fractured reservoirs is challenging owing to limitations in observational scale. This study employs a two-dimensional non-uniform porous medium from core casting sheets as the research model. Using COMSOL multi-physics, we introduce artificial fractures into the porous medium and solve the coupled NavierStokes and CahnHilliard equations for multi-phase flow with a stable finite element solver. Results indicate that spontaneous imbibition is most effective when fracture openings align with the pore aperture size, achieving 27% matrix oil recovery. Recovery is further enhanced when the rock displays hydrophilic wettability, especially with an increased hydrophilic proportion in large matrix particles. The model provides valuable insights for optimising post-fracturing recovery and offers strategies for enhanced oil recovery in fractured tight reservoirs. [Received for review: December 23 2024; Accepted: January 28 2026]
  Keywords: phase-field method; imbibition; fractured tight reservoir; numerical simulation; wettability; heterogeneity.
  DOI: 10.1504/IJOGCT.2026.10077601
   
  
• Multi-scale pore structure and methane adsorption of deep lower Jurassic coals from the Badaowan formation in the Junggar Basin  
  by Xu Ou, Zhonghong Chen, Weijiang Yao, Xin Hu, Xiaojie Jin, Kegong Dong 
  Abstract: This study characterises the pore structure and gas adsorption of low-rank bituminous coals from the Badaowan Formation (Lower Jurassic, Junggar Basin, western China). Integrated analysis employing high-pressure mercury intrusion, low-temperature N2 and CO2 adsorption reveals a multi-scale pore network that exhibits significant heterogeneity. Pore volume shows a U-shaped distribution, dominated by micropores (62.97%, avg. 0.0214 cm3/g, 0.31.5 nm) and macropores (33.18%, avg. 0.0102 cm3/g), with mesopores minor (3.85%). Specific surface area (SSA) exhibits an L-shaped pattern, mainly from micropores (99%, avg. 81.1 m2/g). Vitrinite (ave. 87.63%) and inertinite (ave. 5.75%) show a good positive correlation with micropore and macropore volumes, respectively, thus having a reducing and increasing effect on the permeability of coal rock. The experimental Langmuir volumes and field-desorbed gas content range in 10.6811.57 m3/t and 3.283.87 m3/t, respectively, which is controlled by micropore SSA and volume. Results highlight dual roles of micropores (adsorption) and macropores (transport), and clarify key factors for predicting gas storage and production. [Received: October 14, 2025; Accepted: January 11, 2026]
  Keywords: deep coalbed methane; full-scale pore characterisation; gas-bearing property; adsorbability; Junggar Basin.
  DOI: 10.1504/IJOGCT.2026.10077910
   
  
• Optimisation of novel Salvia hispanica L. biodiesel using sodium methoxide base catalyst  
  by K.M. Manjunatha Swamy, H. Manjunath 
  Abstract: The preparation of biodiesel from chia (Salvia hispanica L.) seed oil through process optimisation is examined in this work. After titration, the beginning acid value of Salvia hispanica L. oil was found to be 1.68 mg KOH/g. The biodiesel synthesis process consists of a single-step alkaline transesterification. The transesterification process parameters optimised to get the peak chia seed oil ester yield were catalyst amount, methanol-to-chia seed oil molar ratio, reaction temperature, and time. This process gives yields of about 96.58%. Chia seed oil methyl ester met IS 15607 and ASTM D6751 biodiesel standards for flash point (142 C), viscosity (3.98 mm2/s), density (882 kg/m3), calorific value (38,900 kJ/kg), and acid value (0.22 mg KOH/g). Based on a comparison of fuel characteristics chia seed oil has been identified as a possible biodiesel feedstock. Chia seed oils can be turned into biodiesel, providing energy while reducing environmental pollutants. Further research shows that biodiesel blend B20 might be a viable alternative fuel for diesel engines. [Received: November 17, 2025; Accepted: February 24, 2026]
  Keywords: chia seed oil; CSO; acid value; sodium methoxide; transesterification; viscosity; biodiesel.
  DOI: 10.1504/IJOGCT.2026.10077911
   
  
• Numerical simulation study on evolution characteristics and difference of CO2 injection pressure transfer between multi-branch pinnate borehole and single borehole  
  by Qi Zhang, Jinlong Jia, Linjie Hu, Zhengyuan Qin, Debin Xia, Weizhong Zhang 
  Abstract: Deep unmineable coal seams are ideal for CO2 storage, but the traditional single borehole injection method has limitations. Pinnate borehole injection adopts multi-branch cooperative injection, which improves injection efficiency. A novel approach utilises underground mine roadways to inject CO2 into deep unmineable coal seams via directional long boreholes. The mathematical model for CO2 injection considers gas adsorption, permeation, diffusion, and coal seam deformation. The right-angle chamfering method solves the problem of non-convergence in calculations. Results show that pressure transmission is notably superior; at 50 days, near-well pressure in the pinnate borehole exceeds 4 MPa (1.6 times that of the single borehole), and the effective pressure range extends to the far-well zone. After 250 days, the cumulative CO2 storage amount is far greater than that of the single borehole. This method significantly enhances CO2 injection capacity and serves as an effective solution for deep coal seam sequestration. [Received: November 18, 2025; Accepted: February 15, 2026]
  Keywords: multi-branch pinnate borehole; single borehole; CO2 storage; numerical simulation; CO2 pressure migration.
  DOI: 10.1504/IJOGCT.2026.10077977
   
  
• Evolving energy use diversity in South Asia: implications for energy security, economic resilience and environmental sustainability  
  by Princy Jain, Mahima Mahima, Vandana Yadav 
  Abstract: This paper examines the impact of energy-mix concentration on energy security, economic resilience and environmental sustainability in South Asia. The energy mix concentration index is declining for all countries during 1990-2018. Besides, high initial fossil fuel dependence of Nepal on biomass, Bangladesh, Pakistan and Sri Lanka on oil and natural gas, and India on coal is observed in Ternary plot. Further, energy diversification is observed in favour of non-renewable sources oil and natural gas for Bangladesh, Nepal, Pakistan, Sri Lanka, and Coal for India. Analysis of linkages between energy mix concentration and macroeconomic indicators using Vector error-correction model reveal long-term association of energy diversification with worsening current account balance and exaggerating economic damages of CO2 emissions. These linkages are partly explained by rising energy import and fossil fuel dependence in the region. South Asian region should harness its underutilised domestic energy reserves while addressing the challenges hindering green transition. [Received: May 29, 2025; Accepted: February 8, 2026]
  Keywords: energy diversity; South Asia; energy mix concentration; renewable energy; energy security; environmental sustainability.
  DOI: 10.1504/IJOGCT.2026.10078068
   
  
• Failure analysis of a heat exchanger in petroleum refining industry  
  by Medhat M. Sorour, Yehia M.S. ElShazly, Mohamed Nabil Afifi, Mohamed Alnakeeb 
  Abstract: Failure of heat exchanger tubes in petroleum refineries poses serious operational and safety risks, requiring accurate root cause analysis. This study investigates a failed carbon steel tube using field inspection, non-destructive testing, and 3D finite element analysis in ANSYS. The model simulated actual operating conditions for both original and corroded wall thicknesses under combined internal and external pressures. Design calculations required minimum wall thicknesses of 0.64 mm and 1.34 mm, while inspection revealed only 0.27 mm in the corroded region. Finite element results showed that intact tubes maintained safe stress distributions, whereas the corroded tube exhibited localised deformation, stress concentration, and buckling, matching observed damage. The findings confirm corrosion-induced wall thinning as the primary failure cause. This integrated experimental and numerical approach provides insight into the failure mechanism and supports integrity assessment, inspection planning, and design validation of refinery heat exchanger tubes. [Received: September 18, 2025; Accepted: January 14, 2026]
  Keywords: heat exchanger; failure analysis; corrosion; finite element analysis; FEA; petroleum processing; buckling.
  DOI: 10.1504/IJOGCT.2026.10078069
   
  
• Impact of saturation temperature on coal mechanical property deterioration during supercritical CO2 adsorption  
  by Minmin Li, Mengfei Xu, Gaowei Yue, Weimin Liang 
  Abstract: CO2 injected under high pressure into deep coal seams usually exists in a supercritical state, and the interaction between supercritical CO2 (ScCO2) and coal leads to significant changes in the physical and chemical properties of coal. Before and after ScCO2 erosion adsorption process, the microcrystalline structure and pore structure of coal were tested and analysed by X-ray diffractometer and low-field nuclear magnetic resonance method. Meanwhile, the mechanical properties of coal were tested and analysed by mechanical tests. During the ScCO2 adsorption process, saturated erosion of ScCO2 alters the crystal structure and pore structure of coal, as the adsorption time and temperature increases, both the compressive strength and elastic modulus of coal gradually decrease. Obviously, the deterioration of coal’s mechanical properties lies in the alteration of its crystal structure and pore structure. The above research results are conducive to promoting the progress and development of ScCO2-enhanced coalbed methane technology. [Received: May 20, 2025; Accepted: September 21, 2025].
  Keywords: supercritical CO2; erosion; mechanical properties; microcrystalline structure; pore structure.
  DOI: 10.1504/IJOGCT.2026.10078165
   
  
• Machine learning modelling and prediction of crude oil nanoemulsion viscosity under various conditions  
  by Andaç Batur Çolak, Sagheer A. Onaizi 
  Abstract: Predicting the viscosity of nanoemulsions under varying conditions without extensive experimental procedures offers significant operational advantages. In this study, machine learning models were developed to predict the viscosity of crude oil-in-water nanoemulsions at different surfactant concentrations, oil-to-water ratios, and salinity levels. Multilayer perceptron-based neural network architectures were constructed and trained using a dataset split into 70% for training, 15% for validation, and 15% for testing. To the best of our knowledge, this study presents the first application of artificial neural networks specifically designed to model the viscosity of crude oil-in-water nanoemulsions as a function of combined formulation variables, namely surfactant concentration, oil-to-water ratio, and salinity. High accuracy was observed in the models, with the average deviation between predicted and experimental viscosity values being less than 0.24%. Comparative analysis demonstrated strong agreement between predicted and measured values, confirming the reliability of the utilised approach. Performance metrics further supported the predictive strength of the developed models. [Received: May 9, 2025; Accepted: November 8, 2025]
  Keywords: crude oil nanoemulsions; artificial neural network; ANN; rheology; viscosity; machine learning modelling.
  DOI: 10.1504/IJOGCT.2026.10078203
   
  
• A comprehensive GIS-LCA approach to carbon footprint in LNG terminals  
  by Lilin Zhan, Zhen Pan, Lifan Zhang 
  Abstract: Liquefied natural gas (LNG) receiving terminals serve as critical nodes in the energy supply chain. This study innovatively employs the geographic information system life cycle assessment (GIS-LCA) methodology, adhering to China’s first national standard for product carbon footprints. It constructs a comprehensive carbon footprint evaluation model for the entire operational lifecycle of LNG receiving terminals, applying this framework to a large-scale LNG receiving terminal along China’s southeastern coast as a case study. The results show that pressurisation by high-pressure pumps is the main carbon emission stage. Electricity emission factors exhibit significant spatial heterogeneity, and the use of provincial-level factors can substantially enhance the accuracy of calculations. Based on this, targeted emission reduction pathways are proposed, and the emission reduction potential of LNG cold energy power generation is analysed, providing scientific basis for low-carbon planning and precise emission reduction at LNG receiving terminals. [Received: October 15, 2025; Accepted: February 19, 2026]
  Keywords: GIS-LCA; liquefied natural gas; LNG terminals; carbon footprint; optimisation path; low-carbon development.
  DOI: 10.1504/IJOGCT.2026.10078204
   
  
• Research on the natural gas dissolution law and gas invasion annular flow pattern distribution of high temperature and high pressure oil-based drilling fluid  
  by Hu Yang, Qiao Liu, Yuhe Shi, Xinyu Tang, Jinde Li, Fei Peng, Fei Gao, Junqing Wu, Xiangguo Liu 
  Abstract: The solubility of natural gas in oil-based drilling fluids under high-temperature high-pressure (HTHP) conditions is a critical factor for well control safety. However, research on its dissolution behaviour and predictive model in multicomponent oil-based drilling fluids remains limited. To address this, the study systematically measured the solubilities of methane and commercial natural gas in two base oils and an emulsifier via HTHP experiments (40150 C; 0120 MPa). Based on experiment results, a solubility prediction model that accounts for the volume fractions of drilling fluid components was established, which achieved excellent agreement with experimental data (the relative error is less than 4.1%). Finally, the model was applied to the GT-1 well in the Junggar Basin, simulating the dissolution-precipitation process in the annulus and flow pattern evolution under different gas invasion rates. Results indicated that natural gas tends to precipitate extensively in the upper low-temperature, low-pressure section of the wellbore, accelerating slippage and forming slug flow/annular mist flow, significantly increasing the risk of well surges. This study provides a critical theoretical foundation and model support for wellbore pressure control and early gas invasion monitoring in HTHP drilling operations. [Received: December 13, 2024; Accepted: December 3, 2025]
  Keywords: high temperature deep well; oil-based drilling fluid; natural gas; solubility; annular flow pattern; well control safety.
  DOI: 10.1504/IJOGCT.2026.10078277
   
  
• Tail gas treatment in triethylene glycol dehydration processes of natural gas industries: a new operating strategy  
  by Wei Qin, Xiaobo Feng, Daifu Gan, Lu Yu, Liang Zhang, Peng Feng, Changkun He, Jiyu Zheng 
  Abstract: To address issues such as emission pollution and resource wastage in the treatment of triethylene glycol dehydration tail gas, a novel tail gas processing technology is proposed. The sulphur-containing tail gas, following gas-liquid separation, undergoes further treatment after being injected into the main pipeline network via an ejector. Utilising HYSYS software, models for the ejector and the overall process were established to validate feasibility. This study quantitatively analyses the impact of key process parameters on water dew point, carbon emissions, and energy consumption. Results demonstrate that this process achieves resource recovery from tail gas with zero emissions. HYSYS simulation outcomes align with actual conditions, with errors within acceptable limits. Optimising reboiler temperature to 205
  Keywords: triglyceride glycol; tail gas treatment; operating strategy; gas recycle.
  DOI: 10.1504/IJOGCT.2026.10078278
   
  
• Prediction of pressure drop in gas-water-foam three-phase flow using a data-driven approach: foam multiphase flow experimental analysis  
  by Shuqiang Shi, Yaning Wang, Huaan Zheng, Qixin Liu, Runyu Wang, Mei Xu, Dan Qi, Xin Wang, Yongcai Zhang, Qingyin Yu, Shaokang Lin, Danlin Chen 
  Abstract: Foam lift mitigates liquid loading in gas wells, but accurate wellbore pressure prediction remains challenging. Foaming agent injection complicates pressure dynamics, while traditional empirical models are parameter-heavy and computationally intensive. This study developed an innovative BKA-BP model to predict pressure drops in gas-water-foam three-phase flow. Trained on 6,678 experimental data (varying gas/liquid flow rates, foaming agent concentrations, pipe inclinations, liquid holdup) and validated with 450 published data, the model showed high accuracy (R2: 0.837~0.905; RMSE: 0.00632~0.0075), capturing complex nonlinear pressure variations - pressure reduction at moderate gas rates (550 m3/h) and increase at high rates (80150 m3/h, due to higher foam viscosity and interfacial friction). Inspired by black kite hunting, BKA integrates global search and local optimisation for rapid convergence. It outperformed standard ML models (BP, CNN, ELM, LSTM, RBF, RF, and SVM) in accuracy, robustness, and efficiency, providing a reliable data-driven solution to optimise gas well production and extend operational lifespans. [Received: February 21, 2025; Accepted: July 14, 2025]
  Keywords: foam multiphase flow experiment; gas-water-foam three-phase; data driven; pressure prediction; BKA-BP model.
  DOI: 10.1504/IJOGCT.2026.10078387
   
  
• Comparative numerical analysis of different pre-CO2 injection patterns for CO2 hybrid fracturing in shale oil reservoirs  
  by Yuxi Zang, Fengxia Li, Haizhu Wang, Zhiwen Huang, Tong Zhou, Jia Cui, Ning Li, Shouceng Tian 
  Abstract: CO2 hybrid fracturing enhances shale oil recovery by integrating CO2 injection with hydraulic fracturing, primarily through two patterns: pre-pad CO2 energisation and pre-pad CO2 assisted fracturing. To elucidate their distinct mechanisms and optimise performance, this study develops and validates a novel fully coupled thermo-hydro-mechanical-damage (THMD) model tailored for the complex conditions of shale oil reservoirs. Results show that both methods reduce breakdown pressure and increase fracture complexity compared to conventional fracturing. Importantly, assisted fracturing performs significantly better, lowering breakdown pressure by 32.7% and increasing cumulative damage by 59.3% compared to conventional fracturing, while promoting more complex multi-directional fracture networks. The model reveals that this enhanced complexity arises from strong thermo-poro-elastic coupling and damage-driven permeability evolution, even in a homogeneous medium. These findings provide novel mechanistic insights and guidance for optimising CO2 hybrid fracturing to improve recovery and carbon sequestration. [Received: January 7, 2026; Accepted: February 1, 2026]
  Keywords: CO2 hybrid fracturing; fracture propagation; fracture morphology; numerical simulation.
  DOI: 10.1504/IJOGCT.2026.10078412
   
  
• Design and analysis of a large-range torque calibration device for iron roughnecks in petroleum drilling  
  by Jun Shao, Jiawei Wang, Tao Jiang, Heng Wu, Jie Yang 
  Abstract: This paper presents a structurally optimised large-range torque calibration device for iron roughnecks, featuring octagonal-profile connection technology for high-precision torque transmission. The compact system integrates a torque transfer unit (with female interface, force disk, sensor) and rigidly constrained base, enabling dynamic measurement through direct coupling with the output shaft. Finite element-optimised octagonal profiles reduce maximum shear stress by 32% compared to conventional designs, effectively mitigating stress concentration. The system demonstrates excellent linearity within 100200 kN m range with < 10% measurement error, particularly suitable for spatially constrained drilling environments. Field tests verify its capability to suppress reactive torque interference while maintaining high accuracy through structural topology optimisation, providing critical technical support for iron roughneck performance enhancement. [Received: June 17, 2025; Accepted: January 4, 2026]
  Keywords: iron roughneck; torque measurement; calibration; mechanical analysis.
  DOI: 10.1504/IJOGCT.2026.10078521
   
  
• Study on the influence law of sandstones mesostructure with different cementation types on drillability  
  by Shuai Chen, Xiangchao Shi 
  Abstract: Accurate evaluation of formation drillability can provide a critical foundation for optimising drilling technologies and tool selection. Therefore, it is of vital importance to obtain drillability accurately. This study investigates the influence of meso-structure, mineral composition, and cementation degree on sandstone drillability. A dataset comprising 68 sandstone core samples was analysed through measurements of drillability indices, preparations of thin sections, and capturing of single/orthogonal polarisation images. Mineral particle contours were extracted using image processing software based on optical properties, and meso-structural parameters were quantified via digitisation. Our analysis demonstrates significant correlations between drillability and Dmc. Cementation-type-specific relationships were identified. Dmc-drillability correlation coefficients for base, contact, mosaic, crystal, grain-coating, and overgrowth-edge cementation types were 0.75, 0.85, 0.70, 0.89, 0.88 and 0.98, respectively. The method enables rapid, cost-effective, and precise evaluation, particularly advantageous for high-coring-difficulty formations. This approach offers actionable insights for real-time drilling strategy adjustments. [Received for review: November 11, 2025; Accepted: March 15, 2026]
  Keywords: sandstone; meso-structure; cement; thin sections; mineral composition; drillability.
  DOI: 10.1504/IJOGCT.2026.10078564
   
  
• Maximising oil production through gas lift allocation optimisation: a genetic algorithm approach in gas-constrained environments  
  by Pham Huu Tai 
  Abstract: Gas lift is an essential artificial lift technique in oil production, used to enhance recovery by reducing bottom hole pressure. However, optimising gas allocation is critical due to limited gas resources. This study focuses on optimising gas lift allocation for five wells to maximise oil production within a gas supply constraint of 10 MMscf/day. A genetic algorithm (GA) model was developed, considering well depths (3,380 m-4,380 m), oil gravity (0.72), and gas-oil ratios (200300 scf/stb). The GA approach outperformed traditional methods, achieving 8,994 stb/d, compared to 8,792 stb/d with equal slope and 7,517 stb/d with Alarcon. The results demonstrate that genetic algorithms can effectively optimise gas lift operations, providing a more efficient solution than conventional techniques. This research offers valuable insights into improving reservoir management and optimising hydrocarbon recovery under constrained gas conditions. [Received: December 4, 2024; Accepted: September 11, 2025]
  Keywords: gas lift optimisation; genetic algorithm; oil production; gas-constrained environments; well cluster.
  DOI: 10.1504/IJOGCT.2026.10078943
   
  
• A liquid chromatography method for simultaneous separation and detection of two polymer flooding agents in oilfield produced fluid  
  by Zuming Jiang, Fuqing Yuan, Xiaoyan Chen, Lan Yan, Yu Liu, Xiaojing Liang 
  Abstract: In an effort to improve oil recovery following polymer flooding, the Shengli Oilfield, guided by additive efficiency theory, optimised a heterogeneous phase combination flooding system. This system includes branched preformed particle gel (B-PPG), partially hydrolysed polyacrylamide (HPAM), and surfactant, and has demonstrated significant application results. To evaluate the impact of this heterogeneous phase combination flooding on field applications, it is crucial to monitor the concentrations of B-PPG and HPAM in the produced fluid from oil wells. To address this, we utilised the unique adsorption capacities of commercial C18 chromatography columns for linear and cross-linked polymers under different mobile phase conditions. By adjusting the gradient elution ratio of acetonitrile/250 mM NaH2PO4 in the mobile phase, we successfully achieved chromatographic separation of B-PPG and HPAM for the first time. The method proved to be fast, simple, and exhibited a strong linear relationship, a broad linear range (5~1,000 mg L1), sensitive detection (LOQ is 5 mg L1, LOD is 3 mg L1), and high accuracy (>91%). [Received: April 3, 2025; Accepted: February 12, 2026]
  Keywords: branched preformed particle gel; B-PPG; hydrolysed polyacrylamide; HPAM; heterogeneous composite flooding; liquid chromatography.
  DOI: 10.1504/IJOGCT.2026.10078944