International Journal of Oil, Gas and Coal Technology (34 papers in press)

Regular Issues

• Biodiesel production from third-generation feedstock: process parameter modelling and optimisation using RSM-ANN approach  
  by Aqeel Ahmad, Ashok Kumar Yadav, Shifa Hasan 
  Abstract: This study employed response surface methodology (RSM) coupled with a central composite design (CCD) approach to ascertain the optimal conditions for biodiesel production from Neochloris oleoabundans microalgae oil. Four key process variables, including the methanol-to-oil molar ratio, catalyst concentration, reaction time, and temperature, were investigated across five levels to develop an L30 orthogonal array for experimentation. An artificial neural network (ANN)-based prediction model was developed using the experimentally obtained data, yielding high accuracy with mean square error (MSE) values of 0.019, 2.4327, and 0.8269 and coefficient of determination (R2 ) values of 0.9996, 0.9796, and 0.9890 for training, validation, and testing sets, respectively, indicating robust predictive capability. The optimisation analysis reveals a biodiesel yield of 94.94% under optimised conditions: 6.92:1 molar ratio, 1.22% catalyst concentration, 64.36 min reaction time, and 56.46 C temperature. Experimental validation confirmed the reliability of the optimisation results, demonstrating a marginal error of 2%. [Received: November 25, 2022; Accepted: April 30, 2024]
  Keywords: biodiesel production; Neochloris oleoabundans; response surface methodology; RSM; artificial neural network; ANN; sustainable fuel; central composite design; CCD; mean square error; MSE.
  
  
• Application of pigging track approach in gas-exhausting for gas-liquid two-phase flow in undulating pipelines  
  by Sihang Chen, Gong Jing, Yang Qi 
  Abstract: During the gas-liquid replacement process of the oil undulating pipeline, there are liquid single-phase parts, gas single-phase parts and liquid gas two phase parts appearing alternately, which pose challenges to the pig tracking and gas-exhaust simulation. In this paper, a novel approach to exhaust the gas from the pipe applying the pigging tech is proposed, and the complicated motion of pig in the undulating pipeline is described by the self adapting momentum equations based on the hydraulic analysis during operation process. The analysis focus on the changeable pressure and force condition happen to the pig with its moving along the pipeline, and switch the describe-equation to the pigs automatically. The model validation by the field data of a real pipeline in China shows that the relative deviation of pig real time speed is within 0.5%, and the relative deviation of pig position is within 2.2%. [Received: October 11, 2023; Accepted: March 7, 2024]
  Keywords: pigging process; undulating pipelines; gas-liquid two-phase flow; pig-tracking; gas exhausting.
  
  
• A study on the transient permeability behaviour of coal core under confinement  
  by Arpita Roy, Santanu Bhowmik, Pratik Dutta 
  Abstract: A high-volatile bituminous coal core was maintained at 40 C, for flooding separately with helium, methane, and carbon dioxide in steps, up to 6 MPa and under various confining pressures (8.2 MPa, 9.2 MPa, and 10.2 MPa). Time-variations and correlation among the flow parameters were analysed during the non-steady state flow. Changes in the effective stress and the specific pore volume were significant at higher confining pressure but less/negligible at lower confinement pressure. Permeability varied inversely with gas pressure within a pressure step but as pore pressure was decreased, the permeability was found to decrease. Permeability also varied with the volumetric flow rate, whereas negative trends were observed with effective stress and cleat compressibility. Effective stress dominated the gas permeability significantly and directly, but indirectly affected specific pore volume and cleat compressibility. In general, helium and CO2 permeability were observed to be the lowest and highest among the gases, respectively. Helium, methane, and CO2 permeability in coal are tested at different effective stresses. Changes in permeability and important parameters with time are investigated. [Received: September 19, 2023; Accepted: February 29, 2024]
  Keywords: pore pressure; confining pressure; effective stress; gas permeability; cleat compressibility; Indian coal.
  DOI: 10.1504/IJOGCT.2025.10066449
   
  
• Investigating a machine learning algorithms applicability for simulating the apparent viscosity of waxy crude oil in a pipeline  
  by Andaç Batur Çolak 
  Abstract: Accurately estimating the formation of viscosity is a vital aspect of pipeline functioning. A study was undertaken here to investigate the precision of utilising a machine learning system for predicting the viscosity of waxy oil in a pipeline environment. A neural network model was developed to ascertain the viscosity of waxy crude oil based on a collection of eight independent parameters. The network model, derived from 30 experimental data points, consists of a hidden layer including 14 neurons. An accuracy analysis was conducted by comparing the predicted viscosity of the network model to the experimental viscosity. The model was built via the Levenberg-Marquardt training algorithm. The accuracy of the artificial neural networks predictions was assessed by calculating the mean squared error value of 2.75 x 10-3 and the correlation coefficient of 0.99850. The models anticipated viscosity values had an average deviation of 0.5%. The experiment yielded conclusive evidence that the specifically engineered artificial neural network successfully forecasted the viscosity of waxy crude oil within the pipeline with great precision. [Received: November 15, 2023; Accepted: May 9, 2024]
  Keywords: crude oil; pipeline; wax; viscosity; machine learning.
  
  
• Simulation and analysis of natural ice-making based on gravity heat pipes  
  by Xiaohong Gui, Shengwei Wang, Junhui Huang, Ziqiang Zhu, Chengyang Zhao 
  Abstract: The emerging natural ice-making technology has garnered significant attention due to its potential to utilise natural cold sources for reducing mine temperatures. This paper suggests employing gravity-based heat pipe cooling technology and employs FLUENT to simulate the heat transfer process in heat pipes and the natural ice-making phenomenon. Research findings reveal that the devised single-tube ice-making model operates without extra energy consumption and effectively produces ice by relying solely on the temperature variance between the water and its surrounding environment. At three varying temperatures (262.15 K, 266.15 K, 270.15 K), the rate and thickness of ice formation increase inversely proportional to the temperature decline, indicating a negative correlation. Moreover, with higher inlet wind speeds (4 m/s, 7 m/s, 10 m/s), the rate and thickness of ice formation increase, showcasing a positive correlation. Finally, the heat pipe structure equipped with fins in the condensation section can partially expedite the ice formation rate and augment the ice thickness. These research findings are of substantial significance in mitigating high-temperature heat hazards in mining environments. [Received: June 2, 2023; Accepted: December 12, 2023]
  Keywords: mine heat damage; ice production; gravity heat pipe; numerical simulation; natural cold source.
  
  
• Development of coal quality exploration technique based on convolutional neural network and hyperspectral imaging  
  by Swati Hira, Manoj B. Chandak, Devendra Kumar Sakhre, Lalit Kumar Sahoo 
  Abstract: Coal is Indias prime energy source, contributing about 60% of total electricity production. Coal India, a major coal-producing public sector unit, has produced record 703.2 million tons of coal during the year 20222023. Therefore, this paper proposes an idea of instant prediction of coal quality parameters using hyperspectral imaging and deep neural network. We have collected coal samples from 35 different coal mines of all areas of Western Coalfields Ltd (WCL), and 257 different types of samples have been generated. All 257 coal samples were imaged using camera PIKA NIR 320. The RegNet model was applied to predict coal quality based on moisture, ash, volatile matter, gross calorific value, fixed carbon, and sulphur. The results were validated through chemical analysis results received from the lab. The proposed approach achieved good prediction accuracy, nearly 96% for coal quality parameters. Moisture showed the highest accuracy, 96.09% in quality prediction. [Received: October 25, 2023; Accepted: April 14, 2024]
  Keywords: coal quality parameters; hyperspectral imaging; HSI; deep learning; spectral data; spatial data; PIKA NIR-320.
  
  
• Study of in-cylinder mixing performance of gas-fuel engine under PFI-DI hybrid injection condition  
  by Tianbo Wang, Yu Wang, Jing Chen, Lanchun Zhang, Li Li, Yanyun Sun 
  Abstract: To further explore the possibility of integrating port fuel injection (PFI) and direct injection (DI) to enhance the in-cylinder mixing performance in natural gas engines, a computational fluid dynamics (CFD) model of PFI-DI hybrid injection was developed to analyse the effects of PFI/DI supply ratio on methane mixing uniformity. The results indicate that the best mixing performance is achieved under the PFI method, with a high percentage of 56.13% for the best methane concentration region (BMCR) at ignition. When the PFI/DI supply ratio is 70/30, the BMCR percentage at ignition is the highest compared to other hybrid injection scenarios, and the methane distribution is more favourable to flame propagation than 100% direct injection. When the PFI/DI supply ratio stands at 65/35 or below, the BMCR percentage at ignition tends to stabilise, influenced by in-cylinder flow velocity, turbulent kinetic energy, and concentration differentials. [Received: December 4, 2023; Accepted: May 29, 2024]
  Keywords: port fuel injection; PFI; direct injection; DI; mixing performance; natural gas engine; hybrid injection.
  
  
• Experiments and numerical investigation on rock-breaking enhancement mechanism of supercritical CO2 jet drilling  
  by Can Cai, Shengwen Zhou, Hao Chen, Bangrun Li, Wenyang Cao, Lang Zeng, Xianpeng Yang, Kejie Chen, Tianzhou Li, Liehui Zhang 
  Abstract: Supercritical CO2 (SC-CO2) jet drilling technology has been proposed to solve the problems of low rock-breaking efficiency and severe thermal wear of PDC cutters in high temperature formation. However, the rock-breaking enhancement mechanisms of SC-CO2 jet on PDC cutter are poorly understood. Therefore, in this paper, SC-CO2 jet-PDC cutter composite rock-breaking experiments and numerical simulation have been employed to study the fundamental factors of SC-CO2 jet enhanced rock-breaking and the influence of different working parameters on composite rock-breaking. The results indicated that the rock debris carrying and impact effects of SC-CO2 jet are the fundamental causes of cutting force reduction. The main reason for the SC-CO2 jet cooling cutter is the heat absorption of gas expansion and phase transition. The research findings offer a theoretical basis for SC-CO2 jet-PDC cutter composite rock-breaking and could support gas drilling, hot dry rock drilling, and deep oil-gas development. [Received: 25 April 2024; Accepted: 24 June 2024]
  Keywords: supercritical CO2 jet; rock-breaking; numerical simulation; PDC cutter; experimental study; rock debris carrying; one-way fluid-solid coupling; cooling effect; jet impact.
  
  
• Early detection of overflow based on genetic algorithm for capturing multiple feature changes in managed pressure drilling  
  by Meng Wang, Zhiyong Chang, Mengxuan Cao, Jiasheng Fu, Xiaosong Han 
  Abstract: Drilling overflows can result in significant losses of money and personnel. So early detection of overflows is of great practical importance. In this paper, six managed pressure drilling features related to overflow are selected, outlet and inlet flow difference, standpipe pressure, methane, ethane, pump flush and hook height. Then the variance, slope and mean of each feature within a statistical time window are calculated. Their thresholds are optimised to detect the overflow point according to the change of statistics by an improved multi-objective genetic algorithm. Logistic chaotic mapping is used to initial the genetic algorithm, and the Levy flight is employed to improve the mutation operator. Experiments show that the new algorithm achieves an average overflow recall rate of 93.7%. The method is able to provide early warning for drilling engineers, thus further safeguarding wellbore safety. [Received: April 7, 2024; Accepted: June 6, 2024]
  Keywords: overflow detection; genetic algorithm; multiple feature; managed pressure drilling.
  
  
• Comparative analysis of energy consumption and carbon emission in the boil-off gas recondensation process  
  by Kun Huang, Xin Wang, Li Cao, Kun Chen, Nan Zhou, Yuxuan Gao 
  Abstract: In this study, the goal is to minimise energy and carbon emissions in liquefied natural gas (LNG) receiving stations by optimising the boil-off gas (BOG) recondensation process. Four processes were evaluated using a performance model that considered both energy and emissions. A genetic algorithm optimised the parameters for lowest possible consumption and emissions. The analysis revealed that while increasing stages of recondensation and compression, and altering cooling methods, led to a minor increase in energy consumption, it resulted in significant emission reductions. Higher BOG content further amplified these savings. Notably, a two-stage recondensation process with pre-cooling and post-cooling (case D) achieved the greatest reduction in carbon emissions, confirming its effectiveness in reaching carbon neutrality goals, despite a slight rise in energy use compared to the base process (case A). [Received: March 19, 2024; Accepted: July 4, 2024]
  Keywords: BOG recondensation; parameter optimisation; energy consumption; carbon emission; process selection.
  
  
• Experimental investigation for partially premixed compression ignition in a diesel engine using n-butanol, biodiesel, and diethyl ether blends  
  by Gangeya Srinivasu Goteti, P. Tamilselvan 
  Abstract: This research aims to optimise combustion by reducing emissions and improving performance parameters. This research also investigates biodiesel usage and an ignition improver with an increased compression ratio of 20 by supplying n-butanol with preheated air. The experimental work was first conducted with diesel to generate baseline data. It was then performed using a blend of n-butanol, diesel, and an ignition improver. The experiment was repeated by using the combustible mixture B25N15DE1, which contains Prosopis juliflora methyl ester, diesel, DEE, and n-butanol vapours on a volume basis. The n-butanol mists were added by port injection in the proportion of 15% into the preheated air stream to attain partially premixed compression ignition. The increased brake thermal efficiency (33.21%) and reduced emissions of hydrocarbons with 65 ppm and carbon monoxide of 0.29% were observed, along with the increased heat release rate (48.1 J/ CA) at a partially premixed mode. [Received: 14 June 2022; Accepted: 24 June 2024]
  Keywords: brake thermal efficiency; combustion; crank angle; emission; heat release rate.
  
  
• Prediction and optimisation of electricity market clearing price in Turkey by using machine learning methods  
  by Murat Ince, Ahmet Kabul, Mesut Aksoy 
  Abstract: This research aims to reduce price instability in the market clearing price (MCP) in Turkey by estimating MCP using machine learning techniques based on production resource-based data. The model will balance market prices by shifting from a price-based to a resource-based approach, minimising the price of electricity units by decreasing imported energy production and increasing domestic and renewable energy production. Thus, in this study, the effect of MCP on electricity unit prices and forecast values until July 29, 2023, was compared. By using past year data between 2014 and 2022, the MCP price in 2023 is determined. As a result of artificial neural network prediction, the average MCP value for 2023 was revealed 85.9 USD. The best results were obtained with artificial neural network (ANN) (R2 = 0.8827, RMSE = 0.0309 and MAE = 0.0223). Also, the model predicts estimated 2023 energy production by incorporating real-time production values from energy resource production data. The performance indicators of the implemented forecasting methods increase efficiency in future production forecasts and contribute to accurate pricing in energy purchases. [Received: February 17, 2024; Accepted: July 7, 2024]
  Keywords: market clearing price; MCP; energy efficiency; machine learning; regression; Turkey; artificial neural network; ANN.
  
  
• A prediction of China's dependence on foreign oil up to 2060  
  by Guangyue Xu, Lanmei Zang, Shuang Li, Qiuyu Song, Kyaw Jaw Sine Marma 
  Abstract: Chinas dependence on foreign oil has increased rapidly in the past few decades. If it continues to grow at the current rate, it will have a series of negative impacts on energy security, economic development, and international competition. The future trajectory of Chinas foreign oil dependence has become the most critical subject for debate. This paper focuses on such issues from three different perspectives - the historical perspective of Chinas oil dependence on foreign countries, the main factors affecting Chinas oil dependence on foreign countries, and the prediction of oil dependence on foreign countries. The forecast shows that Chinas oil dependence on foreign countries will likely reach its peak before 2030, and it is expected to reach its peak as early as 2026, with a maximum value of 75.24%. The realisation of this possible peak depends on the control of oil demand and the progress of oil production technology. Therefore, it is necessary to increase innovative technology orienting the oil industry and control consumption to address with high dependence on foreign oil. [Received: October 4, 2023; Accepted: February 12, 2024]
  Keywords: China’s petroleum; external dependency; prediction; energy security; peak.
  
  
• Development of a data-driven screening model for miscible carbon dioxide flooding  
  by Palang Moronke Guful, Cavit Atalar 
  Abstract: Carbon dioxide enhanced oil recovery methods (CO2-EOR) offer both enhanced oil recovery and carbon sequestration benefits, however their profitability depends on reservoir properties and CO2 injection design which necessitates a robust screening tool to evaluate its feasibility. This study presents a novel data-driven screening tool to automate the screening process for miscible CO2 flooding. A compositional numerical simulator (CMG GEM) was used to develop a database modelling heavy, black and volatile oils to understand the impact of oil gravity on miscibility. Artificial neural networks (ANNs) were trained using this database to predict EOR performance under various conditions. Our approach addresses the limitations of traditional EOR screening criteria, which often rely on oversimplification and expert judgement. We employed a rigorous validation process, including a univariate sensitivity analysis and comparison with CMG GEM simulation results, to ensure the tool’s reliability. The ANN showed strong predictive capability, with performance indicators indicating high accuracy. This tool not only facilitates rapid and accurate CO2-EOR screening but also enhances decision making by integrating a wide range of reservoir rock and fluid characteristics. This study presents a significant advancement in the automation of EOR screening processes, providing a user-friendly and reliable solution for the oil and gas industry. [Received: 21 May 2024; Accepted: 27 July 2024]
  Keywords: screening tool; miscible CO2 flooding; neural networks; carbon sequestration; enhanced oil recovery; EOR; data-driven modelling.
  
  
• Study of rock drillability evaluation based on drilling parameters of cutting rig  
  by Xiaolei Yue, Zhongwen Yue, Yang Li, Yifei Yan, Xu Wang 
  Abstract: Accurate assessment of mechanical properties and interface information in layered rock formations is crucial for informed decision-making in geotechnical engineering. In this study, we investigated the rock drillability distribution to determine interface information in layered rock masses. Using a self-developed digital rotary drilling system, we conducted indoor experiments on layered rock masses with varying strength grades. We proposed a rock drillability index (Ld) based on the correlation between drilling specific energy and penetration rate, and analysed its variation within the rock mass. Our results demonstrate significant fluctuations in Ld across rock strata, particularly at interfaces, indicating high sensitivity to interface recognition. Additionally, we found that Ld has a positive relationship with penetration rate and a negative correlation with rock strength, reflecting both the rock's resistance to drilling damage and the interaction between the rock formation and drilling rig. In conclusion, Ld accurately identifies layered rock mass interfaces and establishes the relationship between drillability and rock strength. This study provides a theoretical framework and methodology for the application of digital drilling technology in engineering rock masses. [Received: March 20, 2023; Accepted: January 10, 2024]
  Keywords: interface identification; drillability index; layered rock mass; measurement while drilling rock.
  
  
• Modern steel production using biomass energy in 21st century: blessing or curse?  
  by Avash Kumar Saha, Ramesh Kumar, Arup Kumar Mandal 
  Abstract: The global shift towards renewable energy has increased biomass utilisation, driven by climate concerns, energy security, and fossil fuel volatility. This review examines biomass’s role in decarbonising steel production, a significant CO2 emitter due to its reliance on carbon-intensive processes. Biomass, including wood pellets, ethanol, and palm oil, offers a renewable alternative to fossil fuels. Research shows that biochar can replace coke in blast furnaces, reducing emissions. However, challenges include ensuring consistent biomass quality, optimising properties, and addressing logistical and economic issues. Economic viability hinges on biomass availability, costs, energy prices, and supportive policies. Investments in biomass supply chains and retrofitting steel plants are essential. This study compiles relevant information to determine if biomass in the iron and steel sectors will be a blessing or a curse in the twenty-first century. Despite challenges, biomass holds promise for sustainable steel production, needing careful management to avoid becoming a curse. [Received: October 16, 2023; Accepted: July 25, 2024]
  Keywords: pellets; biomass; industries; sustainable development; fossil fuels.
  
  
• Catalytic depolymerisation of Yinggemajianfeng lignite via ionic liquid pretreatment-catalytic ethanolysis tandem system  
  by Zhou-Xin Peng, Shi-Yun Xiao, Meng-Yao Li, Hong-Shu Liu, Bo-Wen Zhang, Sheng-Kang Wang, Ming Xia, Xue-Song Wang 
  Abstract: A highly active Pd-Ru/HZSM-5 catalyst was prepared and used for catalysing cracking of Yinggemajianfeng lignite (YL) treated with an ionic liquid-methanol co-solvent system (TYL) to study its structure changes. The ethanol-soluble fractions obtained from YL and TYL (ESPYL and ESPTYL) were analysed using atmospheric pressure chemical ionisation/quadrupole orbitrap mass spectrometry (APCI/Q-orbitrap MS). The yields of ESPYL and ESPTYL were 41.5 wt% and 53.0 wt%, respectively, indicating that the lignite treated with the ionic liquid-methanol co-solvent system exhibited enhanced potential for catalytic conversion. Benzyl-2-naphthyl ether (BNE) was selected as a representative model compound for YL and was fully converted to toluene and naphthol (210 C, 1 h, and 1 MPa N2), demonstrating the excellent ability of Pd-Ru/HZSM-5 catalyst in activating ethanol to generate H as a hydrogen source for the cleavage of BNE. APCI/Q-orbitrap MS analyses revealed the presence of a significant amount of oxygen-containing products in ESPYL and ESPTYL, underscoring the efficacy of the tandem system in generating oxygen-containing small molecules. [Received: December 3, 2023; Accepted: May 3, 2024]
  Keywords: lignite; ionic liquid; catalytic ethanolysis; APCI/Q-orbitrap MS; structural features.
  
  
• Modelling the impact of energy production on environmental quality of resource-rich countries  
  by Austine N. Okereke, Nancy Zigwai Yunana, Seyi Saint Akadiri, Joseph Osaro Denwin 
  Abstract: This study examines the influence of energy production on environmental degradation in resource-rich countries, utilising the pooled mean group (PMG) estimator technique spanning from 1995 to 2021. Our analysis revealed that while energy production does contribute to CO2 emissions, its impact was statistically insignificant. This suggests the potential for implementing advanced and environmentally friendly techniques in the production process. Furthermore, the study suggests that the bulk of emissions in oil-producing countries may stem from sources other than energy production, such as oil extraction itself. Our findings support the halo effect hypothesis (HEH), indicating that foreign direct investment (FDI) is associated with a reduction in CO2 emissions in the sampled region. Considering these results, policymakers should prioritise environmentally friendly policies to attract FDI inflows in countries like Nigeria. This includes encouraging investors to embrace green energy technologies and align their investments with the country’s emission reduction targets. [Received: May 18, 2023; Accepted: May 8, 2024]
  Keywords: energy production; environmental quality; foreign direct investment; FDI; time series; Nigeria; pooled mean group; PMG; halo effect hypothesis; HEH.
  
  
• A proposed method for shale permeability tensor calculation considering shale anisotropy  
  by Zengqiang Han, Shuangyuan Chen, Xiaokun Chen, Yiten Wang, Shicong Huang, Dan Xu, Chao Wang 
  Abstract: As a common structure of sedimentary rock, bedding plane causes obvious anisotropy of shale permeability. Permeability is an important parameter for evaluating shale gas reservoirs, so it is necessary to study the percolation characteristics of shale under the influence of bedding plane. In this paper, permeability tests of different bedding angles, different confining pressure, and different percolation paths (axial/radial) were carried out on the shale specimens from the northern Guizhou Depression, China. Both axial and radial permeability tests method are based on pulse decay method. According to the test result, the influence mechanism of bedding plane on shale permeability is studied. The permeability of shale specimens decreases exponentially with the increase of confining pressure and angle of bedding direction. In addition, combined with the test results and percolation theory, a permeability tensor calculation method in shale reservoir is established. The permeability model of the measuring point is established by referring to the drill hole image data in the core well, which is presented in a spherical coordinate system. The permeability varies with the bedding angle in the shale reservoir are intuitively obtained. The results can provide reference for shale gas development and well layout. [Received: November 2, 2023; Accepted: August 24, 2024]
  Keywords: anisotropic permeability; bedding plane; shale reservoir; tensor calculation method.
  
  
• Synthesis and viscosity reduction performance evaluation of oil-soluble viscosity reducer based on molecular dynamics simulation  
  by Li Hanyong, Cui Yafang, Zhong Ziye, Yu Bo 
  Abstract: The feasibility of the synthesis of oil-soluble viscosity reducer SSM was simulated by molecular dynamics simulation combined with experimental research. Then, the oil-soluble viscosity reducer SSM was synthesised by copolymerisation of three monomers of stearyl methacrylate (SMA), styrene (SM) and maleimide (MIm) by solution polymerisation. The effects of monomer ratio, reaction temperature, reaction time and initiator addition on the viscosity reduction effect of Liaohe heavy oil were investigated. Infrared characterisation results showed that SSM was successfully synthesised. Thermogravimetric analysis results show that SSM has good thermal stability and dispersibility. The results of optical microscopy and scanning electron microscopy revealed the viscosity reduction mechanism of SSM on heavy oil. [Received: May 25, 2024; Accepted: July 31, 2024]
  Keywords: molecular dynamics simulation; viscosity reduction of heavy oil; oil-soluble viscosity reducer; SSM; viscosity reduction mechanism.
  
  
• Experimental investigation on the anisotropy of rock brittleness for reservoir evaluation based on digital drilling mechanical properties  
  by Xiaoyue Yu, Mingming He, Haoteng Wang, Qin Zhao, Mingchen Ding, Jing Wang 
  Abstract: Rock brittleness is a key indicator for reservoir excavation in energy engineering, especially in oil and gas field exploitation. In this study, we developed an energy-balance model of the rock energy characteristics during rock drilling. To evaluate the anisotropic effect of rock brittleness, a drilling-based brittleness index (BI) is derived. Digital borehole tests were conducted on substrates comprising limestone, mudstone, sandstone, and shale, probing into the energy characteristics and anisotropic nature of brittleness across distinct drilling directions (0, 90, 270, and 360). A meticulous analysis was undertaken to unravel the energy traits and the progressive evolution of the BI throughout diverse drilling directions. Results suggested that the BI of limestone and sandstone exhibited an initial descent (in the drilling direction in 090) followed by an ascent (in the drilling direction in 90180), culminating at a critical direction of 90. The order of anisotropy of rock brittleness of the tested specimens was as follows: limestone (0.95) > sandstone (0.94) > mudstone (0.83) > shale (0.82). To ascertain the reliability of proposed methodology, a comparative analysis was conducted against various methods for determining the rock brittleness, revealing a predicted error margin below 5%. The digital drilling method has potential practical applications. [Received: July 18, 2024; Accepted: August 05, 2024]
  Keywords: anisotropy; brittleness; energy characteristics; drilling.
  
  
• Fast marching method for evaluation of reserves drainage volume in shale gas reservoirs considering multi-well interference  
  by Miaomiao Liu, Fenglan Zhao, Shijun Huang, Guoliang Li 
  Abstract: The fast marching method (FMM) has shown considerable potential for rapid modelling of unconventional gas reservoirs, particularly excelling in pressure front tracking efficiency. In this study, an FMM-based evaluation method is established for analysing reserves drainage volume in shale gas reservoirs under multi-well conditions. The effects of fracturing stages, stimulated reservoir volume (SRV) permeability, fracturing stage spacing, horizontal well spacing, and fracture half-length on production are investigated. By combining numerical simulation with FMM, the production of shale reservoir is analysed, and the reservoir performance is further investigated employing a three-dimensional well network development pattern. The results demonstrate that fracturing stages have the greatest impact on drainage volume, followed by fracturing stage spacing. Fracture half-length, horizontal well spacing, and SRV permeability have the least impact on drainage volume. The three-dimensional well network development pattern can reduce interference between horizontal wells at the same layer, increasing cumulative gas production by over 20%. [Received: July 10, 2024; Accepted: August 19, 2024]
  Keywords: shale gas reservoir; reserves evaluation; fast marching methods; FMM; tridimensional well pattern.
  
  
• Route selection for mine haulage road considering dynamic topographic changes and fuel consumption  
  by Qun Wang, Qintao Niu, Yu Chen 
  Abstract: The development of an open-pit mine haulage system relies on manual trial-and-error methods to determine route selection schemes, which have the problems of high subjectivity, low efficiency, and challenges in haulage cost optimisation. Based on analysing the balance between the driving force and resistance, and the power balance of mining dump truck engines, this study proposes a fuel consumption prediction model for mining electric wheel dump trucks. A fuel consumption cost grid is constructed based on the fuel consumption prediction model, and fuel consumption costs and terrain elevation differences are used as comprehensive costs. This study proposes a haulage road route selection algorithm based on minimising the comprehensive costs and ensuring route smoothness, thereby optimising route selection outcomes. This approach offers valuable guidance for designing efficient haulage systems in open-pit mine development. [Received: 24 June 2024; Accepted: 11 September 2024]
  Keywords: open-pit coal mine; fuel consumption; route selection algorithm; haulage road design.
  
  
• Optimising mud management: adaptive moment estimation-based ANN for predicting rheological and filtration properties of KCl-PHPA-Polyol drilling fluids  
  by Raunak Gupta, Uttam K. Bhui 
  Abstract: Field results highlight the importance of real-time monitoring of drilling-fluid properties to prevent operational issues by detecting changes in fluid rheology and filtration behaviour. Traditional laboratory methods, while precise, are time-consuming, error-prone, and do not reflect the rapidly changing conditions encountered during drilling. Thus, there is a pressing need for real-time predictive models that can adapt to on-site data for immediate adjustments. This study introduces a novel method using a deep neural network to predict the rheological and filtration properties of KCl-PHPA-polyol mud, focusing on historically underemphasised parameters like pH, alongside density and Marsh funnel viscosity (MFV). Utilising 2,000 field data points, the artificial neural network (ANN) model demonstrated robust performance, achieving R2 values between 0.738 and 0.910, and MAPE from 4.54% to 9.87%. This model significantly advances traditional methods by enhancing the interpretability and utility of ANN, improving operational efficiency through accurate prediction of key rheological and filtration attributes. [Received: June 27, 2024; Accepted: July 31, 2024]
  Keywords: adaptive moment estimation; artificial neural network; ANN; artificial neural network; rheological and filtration; KCL-PHPA-Polyol; drilling fluids.
  
  
• Experimental study and application of rock electrical properties under high temperature and high pressure based on Archie's formula: a case study of Jimsar shale oil reservoir in Xinjiang, China  
  by Xing Zhang, Jiajia Feng, Chun Yin, Meng Feng, Li You, Songsong Huang, Jian Li 
  Abstract: This study conducted rock electrical experiments under high temperature and high-pressure conditions, combined with high-pressure mercury injection and nuclear magnetic resonance experiments to analyse the response characteristics of rock electrical parameters in shale oil reservoirs. The saturation index n is positively correlated with increasing porosity and oil saturation, exponentially correlated with permeability logarithm, and negatively correlated with displacement pressure, according to experimental data. The formation factor decreases with porosity, permeability, average capillary radius, and pore throat homogeneity coefficient. Based on saturation index, formation factors, storage and seepage characteristics, and pore-throat structure, permeability and effective porosity were introduced, and two saturation correction models for high temperature and high-pressure rock electrical parameters were created. The models general applicability shows that it calculates saturation more accurately than Archies formula, with only 5% average difference from oil saturation. This study provides a more accurate and effective method for shale oil reservoir saturation interpretation. [Received: March 30, 2024; Accepted: August 16, 2024]
  Keywords: shale pore throat structure; rock electricity experiment; Archie’s equation; saturation correction model; HPMI; NMR; China.
  
  
• Effect of adding fusel oil with gasoline on performance, combustion and emission characteristics of gasoline injection engine  
  by Gopinath Dhamodaran, Ganapathy Sundaram Esakkimuthu, Sathyanarayanan Seetharaman, Ramesh Krishnan 
  Abstract: Fusel oil is a 5-carbon structure fuel and it is a by-product of the alcohol manufacturing process. Fusel oil provides higher octane number and oxygen percentage compared to gasoline and this provides an opportunity to improve the performance of an engine. This study investigates the effect of adding fusel oil to gasoline on the properties of gasoline/fusel oil blends and the performance, emission, and combustion characteristics of gasoline engine. The addition of fusel oil with gasoline produced lower density, lower calorific value, and higher oxygen percentage and RON of the gasoline/fusel oil blend. The study found that for all engine speeds F30 blend produced higher brake thermal efficiency as compared to gasoline, 15.12% higher BTE is observed in the F30 blend at 2,800 rpm. At 2,800 rpm, lower hydrocarbon (48 ppm) and carbon monoxide (0.013%) is observed F30 blend, but NOx is observed with higher values. Furthermore, engine input parameters were optimised to achieve the maximum engine performance with a desirability of 0.993 and higher R2 values ranging between 0.995 and 0.998. [Received: 2 June 2023; Accepted: 19 June 2024]
  Keywords: oxygenates; octane number; gasoline; unburned hydrocarbon; carbon monoxide; fusel oil.
  
  
• A comprehensive review on biodiesel performance: advantages, challenges, policies and prospects  
  by V.N.S.R. Ratnakara Rao Guduru, Subbarama Kousik Suraparaju, Sendhil Kumar Natarajan, Ravi Kiran Sastry Gadepalli, V. Ramachandra Raju 
  Abstract: The depletion of traditional fossil fuels, escalating emissions and stringent environmental regulations in alignment with the sustainable development goals (SDGs) have catalysed significant advancements in biofuel technologies. Among these, biodiesel has emerged as a promising eco-friendly alternative to conventional diesel for use in compression ignition (CI) engines. This review elucidates the potential of biodiesel to substantially reduce emissions while maintaining engine performance comparable to that of pure diesel, thereby presenting a compelling and sustainable fuel option. Nevertheless, challenges such as increased nitrogen oxide (NOx) emissions and higher brake-specific fuel consumption necessitate innovative strategies in both production and application. This comprehensive review explores the optimisation of various biodiesel formulations, including blends with eco-friendly additives, addressing the inherent challenges and identifying opportunities to meet SDGs. This review serves as a valuable guide for researchers and developers, offering insights into selecting and refining diesel alternatives that balance performance with emissions reduction, ultimately supporting the achievement of SDGs and the transition to a greener world. [Received: 4 January 2024; Accepted: 1 July 2024]
  Keywords: biodiesel; engine performance; emissions; diesel engine; policies.
  
  
• Future of WSNs and IoT technology in the oil and gas industry, through MEMS energy harvesters  
  by Musaab Zarog 
  Abstract: Oil and natural gas represent 55% of energy sources and therefore they remain the main choice for fulfilling energy needs. For more efficiency, all machinery and equipment including thousands of kilometres of transporting pipelines need to be monitored continuously and in real-time. Any delay in detecting failures or degradation can result in a huge and serious impact on the environment, humans, and property. With the advancement of the internet of things (IoT), through wireless sensor nodes (WSNs), the response to any failure can be much faster and cost-effective. Microelectromechanical (MEMS) Energy harvesters provide a solution to power hundreds of WSNs. The objectives of this paper are to; analyse the current role of WSNs and IoT in oil and gas operations, assess the impact of MEMS-based energy harvesters on the longevity and reliability of IoT and WSN deployments. [Received: November 24, 2021; Accepted: October 25, 2024]
  Keywords: wireless networks sensors; micro-electro-mechanical systems; MEMS; energy scavenging; mechanical vibration; microsystems; ambient energy.
  
  
• Dynamic response characteristics of multi-gas in coal seam during gas injection process  
  by Gaowei Yue, Yanwen Zhang, Zihao Li, Minmin Li 
  Abstract: A one-dimensional gas-solid two-phase model for gas injection displacement was established, and the dynamic time-varying characteristics of gas injection displacement of multi-gas with different mixed gases were numerically analysed. The research results indicate that the permeability of coal seam N2 slowly decreases linearly with pressure, while the permeability of CO2 sharply decreases linearly with pressure. The numerical simulation results of the multi-gas adsorption/desorption flow model for coalbed gas injection are consistent with the measured results. Injecting a mixed gas with a high proportion of CO2 will increase the penetration time, but increase the initial recovery rate; Injecting a mixed gas with a large proportion of N2 will result in a lower initial recovery rate, but it will break through earlier and produce a large amount of nitrogen in the extracted gas in a short period of time. [Received: December 18, 2023; Accepted: April 20, 2024]
  Keywords: gas injection replacement; multi gas; recovery rate; dynamic response; time-varying characteristics.
  
  
• Production model of fractured horizontal wells in shale gas reservoirs considering different gas diffusion mode  
  by Shuyong Hu, Wenhai Huang, Jiayi Zhang, Daqian Rao, Bingyang Zheng, Tingting Qiu 
  Abstract: Because of the complexity of the shale gas seepage mechanism, the establishment of a fractured horizontal well model of shale gas reservoirs based on multiple migration mechanisms is helpful to the development of shale gas reservoirs. In this study, different matrix diffusion modes in different regions are considered. The fractured horizontal well model of the shale gas reservoir can be divided into a fracture network region (SRV region) and a shale matrix region. The quasi-steady-state matrix diffusion in the fracture network region is described by Fick's first law, the non-steady diffusion in the matrix region is described by Fick's second law, and seepage of the fracture system is described by Darcy's law. Based on the above ideas, a fractured horizontal well production model of fractured horizontal wells in shale gas reservoir is established. The Laplace transformation, Duhamel principle, and Stehfest numerical inversion are used to solve the mathematical models of seepage flow, and a sensitivity analysis of the dimensionless production curve is performed. [Received: January 22, 2023; Accepted: February 13, 2024]
  Keywords: shale gas; fractured horizontal well; seepage mechanism; gas diffusion; seepage model.
  DOI: 10.1504/IJOGCT.2025.10067655
   
  
• Analysis of sulphur deposition and well production in sour gas reservoirs considering the effect of temperature field  
  by Bo Fang, Jinghong Hu, Baozhu Li, Xinzhe Zou 
  Abstract: Sulphur deposition in deep sour reservoirs poses a significant challenge to gas well production by impairing reservoir porosity and permeability. Temperature plays a crucial role in controlling sulphur deposition, affecting both its quantity and phase. This study aims to propose a thermal-fluid coupling model to examine the changing characteristics of sulphur deposition and gas well production. By using the finite volume method for numerical solution, the model enables the determination of temperature and pressure distribution within the reservoir, facilitating the prediction of sulphur deposition phases and gas well productivity. The study reveals that considering temperature field variations in the development of sour gas reservoirs leads to increased sulphur deposition saturation and decreased gas well productivity. Gas-liquid sulphur two-phase flow does not occur within the formation. This study provides a scientific basis for optimising development strategies in sour gas reservoirs. [Received: July 3, 2023; Accepted: December 21, 2023]
  Keywords: sour gas reservoirs; temperature field; multiple-fractured horizontal well; sulphur deposition phase change; gas well production.
  DOI: 10.1504/IJOGCT.2025.10067665
   
  
• A novel approach to designing wire mesh demisters for surface separators: experimental, CFD, and artificial intelligence perspectives  
  by Mehdi Fadaei, M.J. Ameri, Y. Rafiei, Mehdi Hosnani, Mehran Ghasemi 
  Abstract: Multi-phase separators are crucial components in the petroleum industry as they separate different phases from produced fluids. One key element that influences their performance is the wire mesh demister. Typically, the design of these demisters is based on semi-empirical correlations, which may contain errors. This study involved designing and manufacturing wire mesh demisters using semi-empirical correlations. Subsequently, a gas-liquid flow loop was created in the laboratory, incorporating a horizontal gas-liquid separator. The wire mesh demisters were tested under various operational conditions within the laboratory separator, and the Stokes number in theory and experiment was measured to determine correction factors for use in the correlations. Due to limitations in water and gas flow rates in the laboratory, a CFD model was developed and verified using experimental results. After acquiring 76 simulation data points with the validated CFD model, a neural network was established to predict correction factors for the semi-empirical correlations. A new correlation was proposed for designing wire mesh demisters, with a mean square error value below 1.9%. The novelty of this study lies in introducing a new correlation for designing wire mesh demisters for field applications. [Received: November 19, 2023; Accepted March 3, 2024]
  Keywords: wire mesh; demister; separator; experimental; CFD; artificial intelligence.
  DOI: 10.1504/IJOGCT.2025.10067658
   
  
• Experimental study on the adsorption and desorption behaviours of methane in clay minerals  
  by Jian Xiong, Jiajie Deng, Wei Liu, Xiangjun Liu, Lixi Liang 
  Abstract: There is a good positive correlation between the specific surface area and the Langmuir volume VL of methane, R² reached 0.9219. The desorption process of methane shows obvious desorption hysteresis, under the same pressure, the methane adsorption amount in the desorption process is always more than that in the adsorption process, and the difference between the two is the largest when the pressure is about 5 MPa. As the pressure decreases, the desorption efficiency all show an increasing trend. When the pressure is high, the desorption efficiency curve rises slowly and the desorption efficiency is low. When the pressure is lower than about 5 MPa, the methane desorption efficiency enters a rapid increase stage, and the amount of methane desorption increases rapidly. The methane desorption hysteresis coefficients of clay minerals are different, in which the maximum of Montmorillonite is 41.91% and the minimum of Illite is 18.57%. [Received: February 13, 2023; Accepted: February 13, 2024]
  Keywords: shale gas; clay mineral; specific surface area; desorption hysteresis; desorption efficiency.
  DOI: 10.1504/IJOGCT.2025.10067664
   
  
• Experimental study on prediction of gas pressure variation during coal and gas outburst  
  by Erhui Zhang, Xukai Dong, Baokun Zhou, Lei Yang 
  Abstract: To accurately predict the variation of gas pressure during the coal and gas outburst experiment, a gas pressure prediction model was established based on Keras and long short-term memory (LSTM). Meanwhile, the ARMA and ARIMA models were selected for comparative analysis. The findings reveal that the ARMA model exhibits the shortest prediction time, but its RMSE and MAE values are the largest, suggesting that the ARMA model yields the poorest predictive performance. The LSTM model achieved the lowest RMSE, and its MAE closely approached that of ARIMA, but the ARIMA model could only predict the gas pressure in the short term. Therefore, it can be employed as the prediction model for gas pressure in coal and gas outburst experiments. The research findings offer significant auxiliary support for predicting the change of gas pressure during coal and gas outbursts, thereby facilitating further prediction and prevention of such occurrences. [Received: October 9, 2023; Accepted: February 27, 2024]
  Keywords: coal and gas outburst; gas pressure prediction; LSTM neural network; multistep prediction.
  DOI: 10.1504/IJOGCT.2025.10067654