International Journal of Oil, Gas and Coal Technology (45 papers in press)

Regular Issues

• 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
   
  
• 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
   
  
• 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
   
  
• 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
   
  
• Study on prediction model of coal spontaneous combustion temperature based on CLCM model: Interpretability analysis using Shapley additive explanations  
  by Peizhe Zou, Rongshan Nie, Chao Han, Xiaoyu Liang 
  Abstract: Coal spontaneous combustion (CSC) threatens mining safety, yet traditional temperature prediction models lack precision and gas-temperature coupling quantification in the models. This study developed a hybrid model (CLCM) integrating a convolutional neural network (CNN) for spatial gas correlation extraction, a long short-term memory network (LSTM) for temporal pattern mining, and a multilayer perceptron for prediction. Shapley additive explanations (SHAP) analysis interpreted the model. CLCM shows high accuracy, mean absolute errors for lignite, long-flame, gas, and anthracite are 2.23, 8.93, 4.85, and 5.16, respectively, with coefficient of determination are 0.99, 0.90, 0.97, and 0.96, outperforming standard CNN, LSTM, and other models. SHAP analysis revealed distinct key gas metrics across coal types, C2H4 and C2H6 for lignite, C2H4 and CO for long flame coal, O2 and C2H4 for gas coal, and O2 and CO for anthracite. This study enhances CSC temperature prediction precision and interpretability, providing a reliable basis for coal safety strategies. [Received: July 15, 2025; Accepted: April 18, 2026]
  Keywords: coal; machine learning; coal spontaneous combustion; CSC; temperature; prediction model.
  DOI: 10.1504/IJOGCT.2026.10079354
   
  
• Development and optimisation of predictive models for annular surface pressure using drillers and engineers methods with multi-objective genetic algorithm  
  by Chukwudi Michael Ohaegbulam, Kevin Chinwuba Igwilo, Ifeanyichukwu Onyejekwe, Anthony Ogbaegba Chikwe 
  Abstract: This study focuses on optimising predictive models for annular surface pressure during well control operations, using the driller’s and engineer’s methods, with multi-objective genetic algorithm (MOGA) for optimisation. Mathematical models based on pressure and material balance principles were developed, and natural gas composition from eight samples in the XYZ Niger Delta field was analysed. The rheological properties of water-based drilling mud were estimated using the Herschel-Buckley model. optimisation aimed to minimise wellbore pressure at specific depths, with kick volume and intensity as key parameters. Results showed that the driller’s method led to higher surface pressure than the engineer’s method, influencing casing depth optimisation. Simulations demonstrated that increasing kick volume and intensity raised surface pressure, risking formation fracturing. The study emphasises the need for early kick detection, optimal standpipe pressure, and effective pressure management to prevent well control failures. The developed models provide a foundation to mitigate well control risk. [Received: April 4, 2025; Accepted: January 4, 2026].
  Keywords: well control; well control models; annular surface pressure; drilling efficiency; mathematical modelling; optimisation; simulation.
  DOI: 10.1504/IJOGCT.2026.10079454
   
  
• Characteristics of the products generated from the large-scale and small-scale pyrolysis experiment on bitumen: significance for the in-situ upgrading process of shale oil  
  by Wenxue Han, Xia Luo, Shizhen Tao, Senhu Lin 
  Abstract: Pyrolysis experiment has smaller sample size and shorter heating time compared with the actual geological conditions. A large-scale pyrolysis experiment on bitumen (LPEB) was conducted and a parallel small-scale pyrolysis experiment (SPEB) was done at the same time. The heating rate was 2.5 C/day with the pressure of 100 psi. The pyrolysis experiment started at around 290 C and completed at approximately 400 C. More than 50% of bitumen converted to oil and about 10% to gas. The final products of the experiments have an obvious upgrade of the raw bitumen. The result of the LPEB is consistent with the SPEB, which confirms the accuracy of the experiment. However, the LPEB consumed more time and energy compared with the SPEB. This study confirms that the SPEB can well simulate the in-situ upgrading process of shale oil and the SPEB can also achieve this goal well with less time and energy cost [Received: May 9, 2025; Accepted: December 18, 2025]
  Keywords: pyrolysis experiment; in-situ upgrading process; bitumen; product analysis; geochemical characteristics.
  DOI: 10.1504/IJOGCT.2026.10079710
   
  
• Influence of bedding plane angle on shale/CO2/brine contact angle of Longmaxi outcrop  
  by Keming Gu 
  Abstract: As caprock or storage media, shale wettability is crucial to CO2 storage, the current research firstly uncovers the influential pattern of bedding plane angle. SEM-EDS and AFM are also adopted to analyse the in-situ micro chemical components and surface roughness pre and post CO2 contact. Shale brine contact angle is measured under different temperature and pressure in CO2. The influence of contact angle is addressed by relative permeability curves, mineral component changes are explained by reactions between CO2, brine and minerals, surface roughness changes are connected with wettability alteration. In order to analyse the comprehensive trend, estimated storage height of different bedding plane angles with rising CO2 density is computed, with contact angle hysteresis as support. The relationship between contact angle and temperature or pressure is interrupted by enhanced shale heterogeneity, cracks or pore tubes along 45 bedding plane angle are the best for storage. [Received: September 30, 2025; Accepted: January 05, 2026]
  Keywords: bedding plane angle; carbon dioxide; shale; contact angle; storage capability.
  DOI: 10.1504/IJOGCT.2026.10079986
   
  
• Deep driven approach-based time series prediction of ethanol requirement in India based on blending rate  
  by Kalyan Kumar Jena, Sourav Kumar Bhoi, Tushar Kanta Mallik 
  Abstract: India?s growing population and rising fuel use have increased petrol consumption, leading to higher costs and environmental issues. Ethanol is a renewable biofuel which can be mixed with petrol to reduce the use of fossil fuels. To overcome this issue, this work uses a deep driven based time series method to forecast India?s future ethanol requirement by considering projected petrol sales and blending rates. The deep learning (DL) models such as long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (Bi-LSTM), convolutional neural network (CNN) and multilayer perceptron (MLP) are used for the prediction. The estimated ethanol demand is then used to calculate how much sugarcane and molasses would be needed for its production. Among these models, the MLP achieves better performance with a mean squared error (MSE) of 0.98, a root mean squared error (RMSE) of 0.9604, and minimal loss. The proposed work offers valuable insights for policymakers and supports sustainable biofuel planning in India?s energy sector. This work is implemented in Python environment. [Received: 10 October 2023; Accepted: 09 November 2025]
  Keywords: deep learning; time series prediction; ethanol requirement; blending rate; mean squared error; MSE; root mean squared error; RMSE; loss.
  DOI: 10.1504/IJOGCT.2026.10080260
   
  
• Innovative co-solvent systems: utilising deep eutectic solvents for efficient biodiesel production and purity enhancement  
  by Santosh A. Kadapure, Umesh B. Deshannavar, Prasad G. Hegde, Laxmikant R. Patil, Sunita S. Patil, Saee H. Thakur, Poonam S. Kadapure 
  Abstract: There is growing awareness of the need for sustainable development, with a focus on cleaner, eco-friendly fuel production technologies. Deep eutectic solvents (DES), similar to ionic liquids, are gaining importance in this area. Our research explores using DES as co-solvents in biodiesel production and separation. Low levels of soap and methanol in fatty acid methyl esters (FAME) can clog fuel filters, making pure biodiesel crucial for engine efficiency. We investigated the effects of molar ratio, stirring speed, and contact time on FAME yield from waste cooking oil using DES. Response surface methodology optimised conditions, achieving a 92% yield with a 7.5:1 methanol-to-oil ratio, 1% catalyst load, and 2% DES concentration. Gas chromatography-mass spectrometry confirmed biodiesel purity, highlighting DESs potential for industrial-scale research. [Received: November 17, 2024; Accepted: December 31, 2025]
  Keywords: biodiesel; deep eutectic solvent; DES; environmental technology; response surface methodology; RSM; sustainable development.
  DOI: 10.1504/IJOGCT.2026.10080569
   
  
• Experimental study on petrophysical and rock mechanical properties of Changcheng Formation in Ordos Basin  
  by Xiaoping Zhang, Wei Liu, Wenjing Yang, Jun Jia, Lulu Wang, Lei Cheng, Xuelin Liang, Yanfang Gao 
  Abstract: The Mesoproterozoic Changcheng Formation in the Ordos Basin exhibits favourable conditions for hydrocarbon accumulation and demonstrates significant large-scale resource potential. This study systematically investigated the rock physical and mechanical properties of the Changcheng Formation through advanced techniques such as multiscale experimental analysis, X-ray diffraction (XRD), scanning electron microscopy (SEM), computed tomography (CT) scanning, combined with uniaxial and triaxial compression tests and Brazilian splitting tests. The results indicate that carbonate minerals constitute the main component of the rock samples in the study area, while dolomite and calcite form the principal mineral phases. Samples from the three studied wells exhibit minor development of irregular pores with poor connectivity. The uniaxial compressive strength ranges from 1.48 x 102 to 1.06 x 101 GPa, while the triaxial compressive strength increases with confining pressure, with an average tensile strength of 8.81 x 103 GPa. These findings provide key insights for predicting fracture networks and optimising production measures for deep carbonate reservoirs. [Received: September 28, 2025; Accepted: May 27, 2026]
  Keywords: The Ordos Basin; The Changcheng Formation; rock mechanical properties; mineral composition; CT; SEM; X-ray diffraction; XRD; compressive strength; tensile strength; elastic modulus.
  DOI: 10.1504/IJOGCT.2026.10080744
   
  
• Energy-efficient optimisation of LPG recovery in a natural gas fractionation unit: simulation and economic assessment using a Steady_State process simulator  
  by Fadi Khaddour, Bashar Al-shamàa 
  Abstract: Improving liquefied petroleum gas (LPG) recovery in natural gas processing plants is economically significant due to the high market value of propane and butane. This study presents a simulation and operational optimisation of the LPG fractionation section using a Steady_State process simulator. The deethaniser and debutaniser columns were modelled under actual plant operating conditions and validated against field data, showing a deviation below 2%, confirming the reliability of the model. A parametric analysis was conducted to evaluate the influence of debutaniser reboiler temperature and feed tray location on LPG recovery and energy consumption. The optimal operating temperature was identified as 148.8?C, achieving an LPG production rate of 3,429 kg/h with a minimised energy demand. In addition, relocating the feed from tray 16 to tray 10 reduced the reboiler duty by 34.5% while maintaining nearly identical LPG production rates, indicating a significant improvement in thermal efficiency and overall process performance. [Received for review: August 16, 2025; Accepted: June 25, 2026]
  Keywords: liquefied petroleum gas; LPG; natural gas processing; fractionation columns; energy optimisation; simulation.
  DOI: 10.1504/IJOGCT.2026.10080787
   
  
• Experimental study on the formation regularities of natural gas hydrates in a wax crystal precipitation system  
  by Haitaio Li, Jiang Wu, Na Wei, Lin Jiang, Shouwei Zhou, Liehui Zhang, Bjørn Kvamme 
  Abstract: Wax crystals and gas hydrates are common flow-assurance obstacles in oil and gas pipelines, and their coupled formation can reduce throughput, cause plugging, and generate substantial economic losses. Differential scanning calorimetry was used to determine the wax appearance temperature and wax precipitation characteristics of model crude oils containing 1%, 5%, 10%, and 15% wax. Hydrate formation experiments were then conducted to evaluate the effect of wax precipitation. Results show that increasing wax content shortens hydrate induction time and increases gas consumption under identical temperature and pressure conditions overall. At 10 MPa and 15% wax, gas consumption increased by 107% and induction time decreased by 68.07% compared with the wax-free system. The promoting effect became more pronounced with increasing wax content. At the same wax content, higher initial pressure increased gas consumption and further promoted hydrate formation. Wax precipitation affects hydrate formation mainly through changes in pipe-wall surface conditions and heat-and-mass-transfer characteristics. [Received: March 23, 2026; Accepted: July 6, 2026]
  Keywords: wax crystallisation; wax content; wax appearance temperature; phase equilibrium; hydrate generation process; gas consumption; interaction mechanism.
  DOI: 10.1504/IJOGCT.2026.10080852
   
  
• Distinguishing the roles of oil components and temperature on minimum miscibility pressure of the CO2/oil systems with the machine learning techniques  
  by Zongjin Li, Zeguang Dong, Dong Wang, Dongxing Du 
  Abstract: Present machine learning works on prediction of minimum miscibility pressure (MMP) of the CO2/oil systems usually lump medium and heavy oil components in one group, which is insufficient to reveal the oil composition effect on the system MMPs. In this study, the multicomponent oils are lumped into seven groups covering C5C45 at various concentrations, and the MMPs of the CO2/oil systems under different temperatures are determined through the thermodynamic phase equilibrium calculations. Machine learning studies, with help of Artificial neural networks (ANN), gradient boosting trees (XGBoost) and light gradient boosting machine (LGBM), are carried out to explore the roles of temperature and oil composition on MMPs of the CO2/oil systems. Results show ANN outperforms XGBoost and LGBM. Feature correlation analysis reveal temperature is the dominant factor, the heavy alkane content positively correlates with MMP, while the light hydrocarbons (particularly C9C11) help reduce the system MMPs. [Received: March 21, 2026; Accepted: June 18, 2026]
  Keywords: minimum miscibility pressure; CO2/multicomponent oil systems; machine learning; oil composition effect; temperature effect.
  DOI: 10.1504/IJOGCT.2026.10080894
   
  
• Micro-nano scale characterisation of mechanical properties in coal-gangue interbedded sediments  
  by Peng Wu, Bo Chen, Haoran Tang, Bo Li, Jianfei Yu, Yanghui Li 
  Abstract: Understanding the microstructure and mechanical properties of gangue coal is essential for borehole stability and efficient deep coalbed methane extraction. This study conducted a multi-scale mechanical characterisation of Gangue Coal No. 8 from the Daning-Jixian Block using micro-focus CT and nanoindentation. The results show that gangue coal exhibits a highly non-uniform spatial distribution and a multi-scale, complex morphology. Under load, weak interfaces (such as the gangue-coal interface and primary fracture zones) within the coal body preferentially initiate fractures, which propagate along bedding planes or interfaces, leading to full penetration. Digital volume correlation (DVC) was used to calculate strain components in the coal sample, revealing that strain primarily concentrated at the interface between gangue and coal strata. Furthermore, significant differences in mechanical properties were observed between gangue and coal strata, with the transition zone exhibiting intermediate mechanical properties. During deformation, energy in the transition zone dissipated through microcrack propagation and plastic flow. [Received: January 2, 2026; Accepted: June 9, 2026]
  Keywords: coalbed methane; nanoindentation; X-ray CT; digital volume correlation; DVC.
  DOI: 10.1504/IJOGCT.2026.10081074
   
  
• Reservoir prediction of saline lacustrine mixed sedimentation rock based on pore structure characteristics  
  by Qiang Zhang, Ping Zhang, Xiang Li, Xianglong Ni 
  Abstract: To tackle the challenge of predicting reservoirs in saline lacustrine hybrid sedimentary rock, this paper initially conducted petrophysical experiments Comprehensive analyses were performed on cores of hybrid sedimentary rocks from the Neogene Upper Ganchaigou Formation to Lower Youshashan Formation (N?N21) in the FX area of the Qaidam Basin using multiple techniques, including thin-section analysis, scanning electron microscopy (SEM), and computed tomography (CT) scanning. These analyses enabled detailed characterisation of the pore structures within the cores. Building upon the findings of the petrophysics experiments, inversion of the rock pore structure was carried out to quantify the content of different pore types. Subsequently, a multi-frequency heterogeneous rock physics model was constructed, and shear wave prediction was implemented. Guided by the distribution ranges of rock physics-sensitive parameters for mixed sedimentation rock reservoirs, high-resolution pre-stack inversion was performed, achieving quantitative prediction of the development extent of such reservoirs. [Received: October 20, 2025; Accepted: July 3, 2026]
  Keywords: mixed sedimentation rock; pore structure; high-resolution pre-stack inversion.
  DOI: 10.1504/IJOGCT.2026.10081086
   
  
• Research on the properties of coal dust explosion and residue in a gasification environment  
  by Guangqian Liang, Peikai Luo, Siyuan Zhang, Zili Zeng 
  Abstract: The explosion temperature, flame propagation, pressure and residue properties of coal dust in coal gasification environment were studied thorough a vertical pipe and 20 L spherical explosive device. The findings indicated that the flame emits a brilliant white light and spreads in a regular shape with the peak temperature reached at 705 . The (dP/dt)max reached 38.482 MPa/s during the explosion, while the explosion reached a peak pressure of 0.808 MPa. SEM, XPS and FTIR techniques were employed to characterize the residue before and after coal dust explosions. Compared to the raw samplethe holes and cracks in the solid residue increased significantly. Notably, C-C bonds at 285.5 eV experienced prominent consumption with up to a reduction of 33.25% after reaction within the vertical pipe. Meanwhile, the content of -OH functional group near 3450 cm-1 was significantly lower than that of the original sample. [Received: April 15, 2024; Accepted: October 23, 2024]
  Keywords: coal gasification; coal dust; explosion properties; residue analysis.
  DOI: 10.1504/IJOGCT.2026.10081128
   
  
• Investigating the flow characteristics of cavitation water jets impacting curved surfaces based on the Zwart-Gerber-Belamri cavitation model  
  by Wei Wu, Yan Xu, Hang Cui, Yuejuan Yan, Sen Li, Jinglong Zhang, Zunce Wang 
  Abstract: Cavitation water jets are extensively used in petroleum operations and coal exploration, such as pipeline descaling, near-well unblocking, hydraulic rock breaking, and hydraulic reaming. Therefore, it is critically important to simulate the cavitation flow field accurately under submerged conditions. This paper presented a numerical simulation study of the cavitation water jet field using the Zwart-Gerber- Belamri (ZGB) cavitation model and explored the effects of the model's evaporation coefficients (Fvap) and the model's condensation coefficients (Fcond) on the dynamic processes of cavitation cloud development. The optimal Fvap and Fcond were determined by comparing the evolutionary morphology of the cavitation cloud captured by the visualisation experiment. The modified model was used to examine cavitation water jet flow characteristics under curved surface constraints. This study provides new perspectives for precisely modelling the flow field of cavitation water jet operations under submerged conditions in different engineering fields. [Received: March 7, 2025; Accepted: June 18, 2026]
  Keywords: cavitation water jet; visualisation study; modified ZGB model; surface-constrained impact experiment.
  DOI: 10.1504/IJOGCT.2026.10081129
   
  
• Numerical simulation study of CO₂ migration and fault shear slip during CO₂-EGR process  
  by Jingwen Xiao, Dong Lin, Yang He, Tianshu He, Xiao Wu, Xinwei Hu, Nanlin Zhang 
  Abstract: CO₂-enhanced gas recovery (CO₂-EGR) is a promising CCUS technology offering both carbon reduction and enhanced gas production. However, CO₂ migration within the reservoir may cause abnormal pore pressure, inducing fault shear slip and resulting in leakage risks, which seriously impact engineering safety and storage stability. To address these issues, this study develops a multiphysics mathematical model that couples multiphase seepage, rock deformation, fault friction slip, and dynamic permeability evolution. Laboratory experiments and field-scale validations are conducted to systematically analyse the influence mechanisms of fault characteristics, matrix permeability, and other parameters on CO₂ migration and fault response. This study investigates the CO₂ migration and fault shear slip mechanisms under multi-physical field coupling, the results provide valuable theoretical insights for understanding CO₂ migration paths, optimising injection layout, and assessing geological storage safety, which are essential for the overall success of CO₂-EGR projects. [Received: June 15, 2025; Accepted: September 25, 2025]
  Keywords: CO₂-EGR; multiphase seepage; shear slip; multiphysics coupling; numerical simulation.
  DOI: 10.1504/IJOGCT.2026.10080786
   
  
• 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
   
  
• 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 and gas; petroleum.
  DOI: 10.1504/IJOGCT.2026.10076780
   
  
• 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
   
  
• 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