Forthcoming and Online First Articles

International Journal of Oil, Gas and Coal Technology

International Journal of Oil, Gas and Coal Technology (IJOGCT)

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International Journal of Oil, Gas and Coal Technology (17 papers in press)

Regular Issues

  • Natural gas demand forecasting based on a subdivided forecasting model and rule-based calibration   Order a copy of this article
    by Gisun Jung, Jinsoo Park, Young Kim, Yun Bae Kim 
    Abstract: In South Korea, with growing volatility in natural gas demand owing to the implementation of eco-friendly energy policies, accurate demand forecasting is becoming more essential. Natural gas demand in South Korea is divided into city and power generation gas. To forecast the volatile energy demand considering daily and regional characteristics, detailed mathematical models and rules to calibrate subtle variations are needed. Power generation gas is more difficult to predict because of exceptional conditions changing the demand pattern owing to sudden weather changes. We propose a subdivided mathematical model that reflects use and daily and regional characteristics. Additionally, adopting rule-based calibration improved forecasting accuracy compared with using only the mathematical model. We performed a forecasting test for one year and confirmed that the average error rate was approximately 2.9%, a substantial reduction in mean absolute percentage error (MAPE) compared to the previously employed moving average method, which validates our proposed method. [Received: October 26, 2021; Accepted: August 13, 2022]
    Keywords: demand forecasting; rule-based calibration; time series; energy operation; natural gas.
    DOI: 10.1504/IJOGCT.2022.10051201
     
  • Effects of Senna auriculata extract on viscoelastic, thixotropic and filtration properties of water based drilling mud   Order a copy of this article
    by Hameed Hussain Ahmed Mansoor, Srinivasa Reddy Devarapu, K.P. Jibin, Robello Samuel, Sabu Thomas, Swaminathan Ponmani 
    Abstract: The limitations and setbacks observed in the nanomaterials enhanced water-based mud (WBM), led to the emergence of eco-friendly mud. In this study, a better enhancement in the rheological properties of Senna auriculataenhanced water-based mud (SWBM) at 30 C, 70 C and 110 C is observed. Different concentrations, viz., 0.5, 1.0, 1.5 wt.% of Senna auriculata are used to study its effects on the rheological and filtration properties of WBM. Thermal stability and aging studies are performed for both WBM and SWBM. The experimental results are then modelled using rheological models. The results reveal that Senna auriculata improve the thermal stability and rheological properties of drilling mud and significantly decrease the American Petroleum Institute (API) filtrate. The rheological performance data of NFWDF project a better fit with the Herschel-Bulkley model and suggest improvement in rheological and filtration properties. This study serves as an important prelude for the development of new environmental friendly, biodegradable, recyclable and cost effective additives for WBM to improve its rheological properties. This research is also expected to aid the industry by resolving major issues in deep well drilling and HPHT drilling. [Received: May 10, 2022; Accepted: September 17, 2022]
    Keywords: mud; Senna auriculata; rheology; frequency sweep; thixotropy.
    DOI: 10.1504/IJOGCT.2022.10051743
     
  • Drilling efficiency enhancement in oil and gas domain using machine learning   Order a copy of this article
    by Aditi Nautiyal, Amit Kumar Mishra 
    Abstract: Oil and gas are non-renewable natural resources that require a great marvel of engineering, planning, and huge capital investment. Drilling Efficiency Enhancement means increasing the rate of penetration (ROP) and avoiding downhole complications like stuck pipe, wellbore collapse, etc. Drilling is a complex activity, prediction of ROP and downhole complications depend upon the various drilling parameters, bottom hole assembly designing, drill bit selection, mud type, mud weight selection, well trajectory designing, revolutions per minute (RPM), and formation parameters which exhibit linear or nonlinear relationships with the objective function. This research work is focused on machine learning algorithms like Random Forest, Artificial Neural Network, etc., for the development of the ROP prediction model, hyperparameter tunning methods like RandomisedSearchCV() to enhance model accuracy, evolutionary particle swarm optimisation (PSO) algorithm to maximise ROP, and an exhaustive list of parameters that are deemed necessary for the development of an accurate and generalised ML model. [Received: June 28, 2022; Accepted: September 18, 2022]
    Keywords: drilling efficiency enhancement; machine learning; random forest; artificial neural network; ANN; rate of penetration; ROP; downhole complications.
    DOI: 10.1504/IJOGCT.2022.10051744
     
  • Detection methodologies on oil and gas kick: a systematic review   Order a copy of this article
    by Fotios N. Zachopoulos, Nikolaos C. Kokkinos 
    Abstract: A gas kick might lead to disastrous consequences if it is not early detected and adequately mitigated. The current study provides valuable information about the latest methodologies developed as responses to a kick. A PRISMA systematic review was conducted to research the latest methods and techniques during the last decade. The review results were presented and discussed in a comprehensive and classified approach. It is worth noting that several new early kick detection approaches have been developed during the last decade. Most of the discussed developments focused on filling the gaps in the currently applied methodologies centred on traditional approaches for analysing kick’s behaviour. However, due to the complex behaviour of such an event, several factors were usually oversimplified, leading to the compromised accuracy of the methodology. Recommendations were also proposed for analysing the kick’s behaviour using modern and robust techniques such as computational fluid dynamics. [Received: June 28, 2022; Accepted: October 17, 2022]
    Keywords: oil and gas drilling; well control; kick detection; kick prediction; PRISMA analysis.
    DOI: 10.1504/IJOGCT.2022.10052066
     
  • Disaggregated energy consumption and ecological footprint: proposing an SDG framework for newly industrialised countries   Order a copy of this article
    by Tomiwa Sunday Adebayo, Seyi Saint Akadiri, Yusuf Adamu, Godwin O. Olasehinde-Williams 
    Abstract: This paper considers newly industrialised countries (NICs) as examples to evaluate the interrelationship between non-renewable energy (oil, coal and gas), renewable energy (hydro and geothermal) and ecological footprint, using panel data from 1990 to 2018. The findings from both the common correlated effects mean group (CCEMG) and augmented mean group (AMG) estimators reveal that economic growth intensifies ecological footprint. Furthermore, non-renewable energy (coal, oil and gas) amplifies the deterioration of the environment, while renewable energy (hydro and geothermal) does not enhance the environment. In addition, the causality provides credibility to the findings generated from the AMG and CCEMG long-run estimators. The results of this study are significant for policymakers in the NICs in terms of achieving the sustainable development goals (SDGs). [Received: 20 March 2022; Accepted: 7 October 2022]
    Keywords: ecological footprint; coal; gas; oil; geothermal; hydro; newly industrialised countries; NICs.
    DOI: 10.1504/IJOGCT.2022.10052074
     
  • Estimating coal consumption in Turkey using machine learning methods   Order a copy of this article
    by Hande Erdoğan, Mehmet Kayakuş, Mustafa Terzioğlu 
    Abstract: In this study, coal consumption was estimated by using machine learning techniques. In the model in which variables related to coal consumption were used, the R2 value was 0.811 for the artificial neural network and 0.853 for the support vector regression, and it was observed that the model made successful predictions. The answers to important points such as the level of coal consumption in the future, the impact of the consumption on the climate, and the size of investment in the clean energy resources required for the energy needed if coal consumption is abandoned will be considered in this study to guide the researchers and decision makers. [Received: April 20, 2022; Accepted: June 6, 2022]
    Keywords: coal; coal consumption; artificial intelligence; machine learning; estimation; Turkey.
    DOI: 10.1504/IJOGCT.2022.10052695
     
  • Comparative study on multicylinder DI diesel engine using hybrid fuel blends (diesel-biodiesel-ethanol derivative) as fuel   Order a copy of this article
    by Rajendiran Gopal, K. Mayilsamy, R. Subramanian, R. Venkatachalam, N. Nedunchezhian 
    Abstract: The present work focuses on the experimental study of multicylinder DI diesel engine using diesel-biodiesel-ethanol based fuel blends. The blends contain diesel, biodiesel and alcohol are 60:30:10% on a volume basis. The measured emission was converted into a specific basis and the overall cycle emission was also calculated. The combustion parameters such as cylinder pressure history, maximum pressure and its angle, rate of pressure rise, heat release rate, and angle of 5, 10, 50, and 90% mass burning were compared. A little lower peak pressure was observed for hybrid fuel blends (<7%), the premixed heat release was lower than diesel fuel whereas the diffusion stage heat release rate was higher. The lower rate of pressure rise for hybrid fuel blends shows its suitability in diesel engines in terms of combustion noise. Higher thermal efficiency, lower specific and cyclic emissions than diesel expect unburned hydrocarbon in the exhaust. [Received: September 4, 2021; Accepted: November 14, 2022]
    Keywords: hybrid fuel; performance; emission; combustion; heat release rate; mass burning; ESC cycle emission.
    DOI: 10.1504/IJOGCT.2022.10052915
     
  • Optimisation of biogas yield from anaerobic co-digestion of dual waste for environmental sustainability: ANN, RSM and GA approach   Order a copy of this article
    by Aqueel Ahmad, Ashok Kumar Yadav, Achhaibar Singh, D.K. Singh 
    Abstract: The main objective of this study was to find the best way to turn food waste and animal manure into biogas. In this research work, an L25 orthogonal array was developed for three factors and five levels of parameters and optimised through the response surface method (RSM) and genetic algorithm (GA). Experiments were conducted to collect data on the variation of the cattle dung and food waste mixing ratios (25:75, 50:50, 75:25, 100:0 and 0:100 w/w %), retention times (7, 9, 11, 13 and 15 days), and digester temperatures (20, 25, 30, 35 and 40 C). Concerning the obtained data, an artificial neural network (ANN) model has been developed to estimate biogas production yield. The RSM and GA analyses showed that the optimal parameters were a 0:100 (w/w %) mixing ratio, 15-day retention time, and at 40 C digester temperature and the corresponding biogas yield was 551.774 ml/day and 551.776 ml/day, respectively. [Received: August 1, 2022; Accepted: November 19, 2022]
    Keywords: anaerobic digestion; biogas production; artificial neural network; ANN; response surface methodology; carbon free sustainable energy; genetic algorithm.
    DOI: 10.1504/IJOGCT.2022.10053130
     
  • Testing and comparative analysis of dynamic and quasi-static compressive and tensile properties of hard coal   Order a copy of this article
    by Xianjie Hao, Bingrui Chen, Guangyao Pan, Qian Zhang, Yulong Chen, Yingnan Wei 
    Abstract: The comparison of mechanical properties of hard coal under different conditions is important for the occurrence of coal mine dynamic disasters. This study adopted six tests, namely, the static tensile test, static tensile test, dynamic compressive test, dynamic tensile test, and coupled dynamic-static tensile and compression test, to analyse the relationship of the mechanical properties of coal under different conditions. The results shows that: 1) the tensile strength of this type of hard coal under dynamic loading is 2-7 times higher than that under static loading; 2) the static tension-compression ratio is between 1/16 and 1/64, and the dynamic tension-compression ratio is between 1/2 and 1/40. The tension-compression ratio of coal is approximately three times higher under dynamic loading compared with that under static loading; 3) the dynamic strength increases with the axial static load within a certain range, but the dynamic strength of coal may decrease beyond this range. [Received: February 21, 2021; Accepted: October 15, 2022]
    Keywords: coal; strength; tension-compression ratio; static loading; dynamic loading; coupled dynamic-static loading.
    DOI: 10.1504/IJOGCT.2023.10053445
     
  • After-sales indicators in the liquefied petroleum gas industry: a hybrid multi-criteria decision-making approach in an uncertain environment   Order a copy of this article
    by Amir Mehdiabadi, Amir Karbassi Yazdi, Peter Fernandes Wanke, Henrique Luiz Correa 
    Abstract: Many stakeholders are involved in liquefied petroleum gas (LPG) after-sales service. Using soft computing, we rank the after-sales service of Iranian LPG companies in terms of global competitors* best practices, comparing four global companies that offer after-sales services as benchmarks. Fuzzy importance and performance analysis (FIPA) was used to identify customary after-sales performance indicators. Then, we used step-wise weight assessment ratio analysis (SWARA) to determine their relative weights. Using fuzzy complex proportional assessment (FCOPRAS), we ranked the top 12 Iranian LPG companies in terms of market share. FIPA, SWARA, and FCOPRAS are combined in this paper for the first time to identify the most important factors for ranking LPG companies in the world-class after-sales services category. [Received: January 18, 2022; Accepted: June 18, 2022]
    Keywords: after-sales service; fuzzy MCDM; grey relational analysis; GRA; LPG industry.
    DOI: 10.1504/IJOGCT.2023.10053882
     
  • Experimental investigation and performance improvement of a new combined T-junctions gas-liquid separator   Order a copy of this article
    by Fachun Liang, Lingqi Xin, Jingwen Zhao, Shen Song, Sigang Wang 
    Abstract: The objective of this paper is to study the gas-liquid separation performance and its improvement of a new combined T-junctions separator by experiments. This separator is constructed of large-diameter T-junctions (50 mm and 60 mm), symmetrically arranged in annulus. The test conditions include complete separation and incomplete separation. The gas-liquid flow characteristics of the combined T-junctions were visually observed and analysed during the separation process. The separation characteristic was quantified (F) and the effects of liquid level, inlet superficial velocities (JG1 and JL1) and outlet valve opening degree on the separation efficiency (F) were confirmed. The results show the connections between the parameters and separation efficiency. Based on the above, a self-regulating level controller is designed, which can significantly extend the range of inlet gas velocity (JG1) to 4.5 times and inlet liquid velocity (JL1) to two times for complete separation, but the level controller fails when the inlet gas-liquid velocities are too high (JG1 > 10.27 m/s, JL1 > 0.52 m/s). [Received: 14 December 2021; Accepted: 7 August 2022]
    Keywords: gas-liquid separation; combined T-junctions; experimental study; liquid level control.
    DOI: 10.1504/IJOGCT.2023.10053929
     
  • Design and fabrication of microfluidic test kit for enhanced oil recovery in low salinity NaCl flooding   Order a copy of this article
    by Sanggono Adisasmito, Rhesa Muhammad Faisal 
    Abstract: A microfluidic test kit with a flowrate capacity of 0.01100 uL/min and pressure of 0-50 psig was designed and fabricated to test four series of salinity injections and subsequently compare the recovery factor (RF). Homogeneous rock patterns with PMMA material were used to create a microfluidic chip with a porosity of 27.8% and a permeability of 2.8 Darcy. The crude oil has an API of 31.9, while the formation water has 10,958 ppm in salinity. The injection solutions were NaCl with 600, 6,000, and 11,000 ppm salinity. The injection was then visualised and processed by a program in Python language to obtain saturation data and recovery factor. An increase in RF was observed in the NaCl injections with salinity lower than formation water. The highest RF, up to 30%, was generated from 600 ppm of NaCl injection. [Received: 23 November 2021; Accepted: 7 August 2022]
    Keywords: enhanced oil recovery; low salinity waterflooding; microfluidic test kit; recovery factor; experimental investigation; homogeneous rock pattern; polymethyl methacrylate; PMMA; microfluidic device.
    DOI: 10.1504/IJOGCT.2023.10053930
     
  • Stochastic production scheduling for water-oil displacement by reduced-order models generated using liquid production rates   Order a copy of this article
    by Ehsan Roeinfard, Mehdi Assareh 
    Abstract: In this work, we show an effective approach for application of reduced order model (ROMs) constructed with proper orthogonal decomposition (POD) using liquid production rates for snapshot generation. These ROMs are used to maximise oil production while controlling associated water production. Using ROMs, we perform a parallel genetic algorithm (PGA) and consider liquid production rates as decision variables. The balanced rates are used for injection wells, based on open-flow potential and total amount of produced reservoir volume. The net present value (NPV) is selected as objective function to ensure project profitability and to penalise water production. The NPV by ROM optimisation is approached to within 98% of the NPV obtained by optimisation using the full-order model demonstrating acceptable accuracy. A synthetic model and a real field sector are used for evaluation. The optimisation runtime reduces by 55% in the synthetic model and 71% for optimisation with ROM in the sector case. [Received: April 4, 2022; Accepted: July 14, 2022]
    Keywords: production scheduling; parallel genetic algorithm; PGA; reduced-order models; ROMs; waterflooding; proper orthogonal decomposition; POD.
    DOI: 10.1504/IJOGCT.2022.10052914
     
  • Preparation and mechanism of viscosification for recyclable associating polymer with low damage for fracturing   Order a copy of this article
    by Chengyu Zhou, Min Zhou, Linghao Zeng, Yuan Sun, Mingyao Lei, Yifan Li, Benhui Li, Wei Wan, Peng Zhang 
    Abstract: Due to the complicated and variable formation conditions, P(AM-AA-APPEA) was developed. The viscosification mechanism was analysed via relative molecular weight, infrared spectroscopy (IR), nuclear magnetic resonance spectrum (1H-NMR), rheological properties, and scanning electron microscopy (SEM). It shows that M = 1.25*106 (M represents molecular weight). The polymer is composed of amides, hydroxyl groups and benzene rings. When the shear rate is 170 s-1 with continuous shear for 120 min at 90°, the viscosity is maintained at about 50 mPa·s. Gel breaking performance, formation damage, dynamic filtration, matrix permeability and fracture conductivity experiments show that it has easy glue breaking, low surface tension, low residue content, good compatibility and good rheological property. At 0.3% thickener concentration, the conductivity damage rate is 41.56%, the dynamic filtration coefficient is 4.24 * 10-5 m·s-1/ 2, and the permeability loss rate is 16.4%. The recovery performance experimental results show that it has good recyclability. [Received: October 22, 2021; Accepted: July 28, 2022]
    Keywords: associating polymer; viscosification mechanism; low damage; fracturing; scanning electron microscopy; SEM.
    DOI: 10.1504/IJOGCT.2022.10050563
     
  • A review of all aspects of dry coal cleaning methods and evaluation of widely used applications   Order a copy of this article
    by Murat Kademli 
    Abstract: Although there are many developments in the energy industry, coal still holds its vital place and seems to have a major role in future. That is why the direct utilisation of coal becomes impractical even impossible in those days. Thus, the aim of this review is for all aspects of dry coal cleaning methods be overviewed, analysed and evaluated, including the applicability to the industry in the face of wet methods. The density-based methods have potential than the other dry coal cleaning methods and have made great development within the coal preparation industry. The Ep values of air jigs or air tables are between 0.13 g/cm3 and 0.26 g/cm3, but fluidised bed separation method are between 0.03 g/cm3 and 0.07 g/cm3. It provides rivalry with wet methods and is a serious alternative for coal preparation. [Received: January 17, 2022; Accepted: July 20, 2022]
    Keywords: dry coal preparation; separation efficiency; density-based methods; non-density-based methods; comparison of dry methods; particle size effect.
    DOI: 10.1504/IJOGCT.2022.10049836
     
  • Multi-product and multi-period maritime oil logistics model with a cooperative approach among hubs   Order a copy of this article
    by Mehdi Razi, Alireza Rashidi Komijan, Peyman Afzal, Vahidreza Ghezavati, Kaveh Khalili-Damghani 
    Abstract: In this paper, the modelling of maritime oil logistics problem in non-cooperative and cooperative approaches is addressed. The problem includes several hubs; each hub has vessels and boats for maritime transport. Rigs are supplied in a time window. In non-cooperative model, each hub supplies its own rigs. In the cooperative model, it is possible to share resources among hubs. Genetic algorithm (GA) and invasive weed optimisation (IWO) are used as solution approaches. To demonstrate the efficiency of solution methods, 15 numerical examples are designed and the results are compared with GAMS. The results indicate that the IWO algorithm has high efficiency in obtaining near-optimal solutions in a shorter CPU time. Also, cost is decreased significantly when cooperative approach is applied. Using optimisation models lead to a considerable decrease in expenditures of maritime oil logistics. The proposed model can be widely used for of oil and gas companies involving in offshore logistics. [Received: March 21, 2022; Accepted: July 20, 2022].
    Keywords: maritime oil logistics; routing; cooperative approach; invasive weed optimisation algorithm; genetic algorithm.
    DOI: 10.1504/IJOGCT.2023.10053635
     
  • Evaluating the effect of petroleum price volatility on government revenue in Ghana   Order a copy of this article
    by Riverson Oppong, Clarence Nii Aryee Aryeequaye, Frank Gyimah Sackey 
    Abstract: The Ghanaian economy is highly exposed to petroleum price fluctuations (volatility) since petroleum revenues is a major contributor to total government revenue. The resulting volatility in government revenue also has a bullwhip effect on other sectors such as the private sector, making planning difficult and complex. This study examines the effect of petroleum price volatility (PPV) on government revenue and economic growth using quarterly time series data for the period 2010 to 2020. The study adopts the autoregressive distributed lag (ARDL) for estimating the models. Three regressions are estimated to address the set objectives of the study. A pairwise correlation matrix was adopted to determine the relationship between the variables. The findings indicate petroleum price volatility has a negative effect on government revenue both in the short run and the long run. Furthermore, the findings also demonstrate petroleum revenue makes a significant positive contribution to the growth of Ghanaian economy. [Received: January 5, 2022; Accepted: June 18, 2022]
    Keywords: price volatility; autoregressive distributed lags; ARDL; petroleum revenue; cointegration; Ghana.
    DOI: 10.1504/IJOGCT.2022.10050521