International Journal of Oil, Gas and Coal Technology (7 papers in press)

Regular Issues

• Investigations of coal permeability under the influence of stress, matrix-fracture adsorption induced strain and volumetric strain  
  by Haizeng Pan, Chaoyu Xu, Xiaochuan Wang 
  Abstract: The evolution and distribution of coal seam permeability have a significant role to play during CBM extraction. Many permeability models assume that coal is isotropic, however, the assumption has received a lot of skepticism. In this study, an improved fracture permeability model is established, considering the anisotropy of coal. The relationship among matrix adsorption strain, fracture adsorption strain, and volume strain of coal is defined. Fracture permeability is a feature of pressure and strain caused by fracture and matrix adsorption. At the same time, the permeability model is validated by experimental data, and the results are in good accordance with the experimental data. The simulation results show that the fracture permeability in the compression direction is smaller than in the tensile direction, and the peak fracture pressure will be delayed in the non-Darcy condition. Cracks are the main passage of CBM. Therefore, studying the permeability of fractures in different directions can better improve the production of coalbed methane. [Received: January 12, 2023; Accepted: May 8, 2023]
  Keywords: permeability; anisotropic; adsorption induced strain; numerical model; coalbed methane; CBM.
  DOI: 10.1504/IJOGCT.2023.10059216
   
  
• Predicting world electricity generation by sources using different machine learning algorithms  
  by Mehmet Hakan Özdemir, Batin Latif Aylak, Murat İnce, Okan Oral 
  Abstract: Electrical energy plays a crucial role in both social and economic growth. It is thought to be an essential part of industrial manufacturing. In addition to its contribution to industry, electrical energy is essential for addressing the needs of people on a daily basis. Therefore, electricity generation prediction is crucial for accurate electricity planning and energy usage, with machine learning (ML) algorithms becoming popular for their ability to extract complex relationships and make precise predictions. With the data from the period 20002022, this study predicts world electricity generation for 2023 by different energy sources employing seven different ML algorithms, namely long short-term memory (LSTM), artificial neural network (ANN), linear regression (LR), support vector regression (SVR), decision tree regression (DTR), random forest regression (RFR) and eXtreme gradient boosting (XGBoost). The algorithms were also contrasted in the study, and it was discovered that LSTM produced the most accurate predictions. [Received: June 16, 2023; Accepted: August 19, 2023]
  Keywords: energy; electricity generation; machine learning; prediction; long short-term memory; LSTM; artificial neural network; ANN; support vector regression; SVR; decision tree regression; DTR; random forest regression; RFR.
  
  
• Feasible fuel (petrol/diesel) price monitoring technology in India without affecting government profit  
  by P. C. Prabhu Kumar, T. Ramathulasi, P. Venkateswarlu Reddy 
  Abstract: The usage of petrol and diesel has become indispensable in human life. The exponential growth of fuel prices affects the common-man life gravely. The Government of India cannot control the hike since it is the essential income catalyst for the Indian economy. The gradual increase of the fuel price impacts other sectors, mainly transportation. As the price increases day by day, the income of the people is not being increased, so the insights of the proposed research work emphasise the benefits for middle-class people. The proposed fuel price monitoring framework segregate the petrol and diesel price into three slots, namely premium, luxury, and economic, concerning the cost of the user’s vehicle and brand. The FASTag technology, which works on RFID, detects the vehicle brand and price and that information is passed to the IoT devices. The IoT structure actuates the fuel machine, which is also connected to the internet. A public cloud is maintained to analyse the vehicle price and brand, and the results will be returned to the petrol machine to finalise the fuel price slot. The comparisons are done between the existing price system and the proposed smart pricing system based on the average income generated per day. [Received: Jun 1, 2022; Accepted: May 7, 2023]
  Keywords: internet of things; IoT; cloud computing; fuel price; smart price; FASTag; radio frequency identification; RFID; India.
  DOI: 10.1504/IJOGCT.2023.10059584
   
  
• The maximum installation depth for a pre-drilled liner with floating inner tubing in horizontal well in tectonically deformed coal seams  
  by Yansen Bi, Deli Gao, Baoan Xian 
  Abstract: A horizontal completion technology of outer liner with inner tubing has been proposed to solve the problems of wellbore collapse, friction resistance and sticking in tectonically deformed coal seams. However, there is no study on the maximum installation depth of this dual-pipe structure. First, a hydraulic model of dual annulus is established to calculate the hydraulic parameters and interpret the influencing factors. Second, a quantitative prediction model of maximum installation depth for the pre-drilled liner with floating inner tubing (PL&FIT) is deduced by coupling mechanics and hydraulics. At last, a horizontal well is taken to calculated the installation depth of PL&FIT by finite difference method. The results indicate that the maximum installation depth of the PL&FIT adopts maximum reach limited by mechanics or hydraulics, which depends on the dual annulus equivalent diameter ratio (?). The maximum reach envelope is deduced for the PL&FIT. [Received: 28 October 2022; Accepted: 2 September 2023]
  Keywords: CBM; horizontal well; dual-pipe structure; tubing floating; liner installation depth limit.
  DOI: 10.1504/IJOGCT.2023.10059875
   
  
• Coal permeability evolution and gas production performance prediction under the coupling action of stress-residual water-pulverised coal  
  by Hongyan Wang, Haitao Mo 
  Abstract: Under the influence of hydraulic fracturing and drainage, coalbed methane wells will produce a large amount of pulverised coal and residual water. Stress, residual water and coal dust is well known to affect the permeability during coalbed methane mining. Most studies consider the three effects separately, which is inconsistent with the actual situation. Therefore, a dynamic evolution model of permeability based on the coupling effect of stress-residual water-pulverised coal is constructed in this paper. Numerical analysis is carried out using a commercial finite element method (FEM) software (COMSOL Multiphysics 5.6), and the model is verified by combining with field mining data. Results indicate that the gas production in the stimulated reservoir volume (SRV) is higher than that in the unstimulated reservoir volume (USRV) due to the influence of hydraulic fracturing and permeability enhancement. However, after 820 days, under the influence of the gas source, the gas production of the USRV is the same as that of the SRV. [Received: July 12, 2022; Accepted: May 10, 2023]
  Keywords: stress; gas-water two-phase flow; pulverised coal; permeability; gas production; finite element method; FEM; stimulated reservoir volume; SRV; unstimulated reservoir volume; USRV.
  
  
• Sequential thermal dissolution and oxidative depolymerisation of Cheji coal  
  by Wen-Han Wei, Xiang Bai, Xing Fan, Zhen-Yu Gao, Ran-Ran Hou, Guo-Ming Zhao, Qing Liu, Hai-Feng Zhou, Peng Liang 
  Abstract: Organic matter in soft coal (SC) and hard coal (HC) from the same mine was extracted by sequential thermal dissolution (TD) followed by oxidative depolymerisation (OD) to obtain soluble components, which were studied using both gas chromatography/mass spectrometry (GC/MS) and Orbitrap-MS to acquire detailed molecular structure information. Toluene (TOL), tetrahydrofuran (THF), and methanol (ME) were the three solvents used in sequential TD. TOL relaxes the macromolecular structure in coals and exhibits a good solubilisation effect on arenes, THF further destroys non-covalent bonds through swelling, and ME weakens hydrogen bonds among macromolecules and attacks the weak -C-O- bridged bonds. With a higher coalification degree, soluble components from HC show more aromatised structure compared to SC. After the OD treatment, aromatic compounds with a higher degree of condensation were detected in the OD products, and HC contains more fused aromatic rings. [Received: 13 March 2023; Accepted: 28 August 2023]
  Keywords: sequential thermal dissolution; oxidative depolymerisation; Orbitrap-MS; coal.
  DOI: 10.1504/IJOGCT.2023.10060437
   
  
• Investigating the impact of oil shales spread on the contamination level of fluvial sediments (case study: Qalikuh area of Lorestan, southwest of Iran)  
  by Amirsaeid Hoseini, Saeid Hakimi Asiabar, Mojhgan Salavati 
  Abstract: The present research related to the investigates the contamination of fluvial sediments Gashun and Pirbadush Streams of the Qolyan River in the Qalikuh Area knowing that the river runs through bodies of oil shales. For this purpose, 15samples were collected the sediments of the randomly. The samples were subjected to ICP.ms analysis to evaluate the concentration of heavy metals in them. Most of the changes were related to 11 heavy elements (Ag, As, Cd, Co, Cu, Mo, Ni, V, Zn, Cr, Pb) which are some of them are toxic metals (As, Cd, Pb). Evaluation of environmental indices like l-geo, EF, CF, PLI, EI, RI, and sediment quality criteria and comparison to global standards through statistical analyses done. According to Pearson's correlation coefficient, all metals are correlated with each other except silver. By performing PCA, three components were identified. Based on the outcomes of CA, the metals could be grouped into four clusters. [Received: January 26, 2023; Accepted: August 14, 2023]
  Keywords: oil shales; sediments contamination; contaminant elements; environmental indices; Qalikuh; Iran.