Determination of crude oil physicochemical properties by high-temperature gas chromatography associated with multivariate calibration

Rodrigues, Érica V. A.; Silva, Samantha R.C.; Romão, Wanderson; Castro, Eustáquio Vinícius Ribeiro de; Filgueiras, Paulo R.

doi:10.1016/j.fuel.2018.01.139

Cited by 27 publications

(14 citation statements)

References 30 publications

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“…The imprecision demonstrated by this model can be attributed to the wide range of viscosity variation from 4.2 cSt (HFO-11 at 115 °C) to 5058.4cSt (HFO-13 at 27 °C) and the inherent nonlinear correlation of this property with temperature variation, as can be seen at Figure . The same difficulty in fitting a PLS model to predict oil viscosity was presented by Rodrigues et al The authors stated that the divergence between the viscosity values predicted by the model and the reference values can be attributed to the nonlinear behavior of kinematic viscosity in function of temperature.…”

Section: Resultsmentioning

confidence: 78%

Application of Near-Infrared for Online Monitoring of Heavy Fuel Oil at Thermoelectric Power Plants. Part I: Development of Chemometric Models

Costa

Gonçalves

Neta

et al. 2019

Ind. Eng. Chem. Res.

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In Brazil, thermoelectric power plants (TPP) are responsible for about 25% of the electric energy generated. Of the energy supplied by the thermoelectric plants, 11% comes from the burning of heavy fuel oils (HFO). The monitoring of these oils is of great industrial interest in order to maintain their quality, avoid damage to the engines, and guarantee the energy supply. In this sense, this work investigated the potential of near-infrared (NIR) spectroscopy combined to partial least-squares (PLS) and artificial neural network (ANN) models for online monitoring of temperature, density, water content, and kinematic viscosity of the HFO used at Energetica Suape II S.A. Chemometric models were calibrated to predict the properties of interest in the temperature range typically found at thermoelectric power plants (from 25 to 120 °C). The results show that NIR spectroscopy combined with multivariate calibration is a powerful tool for online monitoring of HFO. ANN models presented a better performance than PLS models, mainly for nonlinear properties like kinematic viscosity; however, all determination coefficients were bigger than 0.95 for all properties when compared to standard methods. The next step of this work will comprise the installation of an industrial NIR at TPP and evaluate the model's performance when applied in real industrial process.

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Section: Resultsmentioning

confidence: 78%

Application of Near-Infrared for Online Monitoring of Heavy Fuel Oil at Thermoelectric Power Plants. Part I: Development of Chemometric Models

Costa

Gonçalves

Neta

et al. 2019

Ind. Eng. Chem. Res.

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“…From this study, it is obvious that much higher carbon numbers can be detected by using FT-ICR-MS, due to its ability to separate elemental compositions by a number of carbon atoms when compared to HT-GC × GC. [557][558][559][560][561] 556 , with permission from Elsevier.…”

Section: Atmospheric Pressure Photoionization (Appi)mentioning

confidence: 99%

Analytics Driving Kinetics: Advanced Mass Spectrometric Characterization of Petroleum Products

et al. 2021

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The current state-of-the-art in analysis techniques for petroleum fractions has progressed substantially during the last decade. This has helped to further improve the lumping procedures and modeling approaches of these complex systems. Recent advances in gas chromatography (GC), GC-field ionization mass spectrometry (GC-FIMS), and comprehensive gas chromatography (GC × GC) have made it possible to determine the compositions of fractions with up to 45 carbon atoms and in some cases up to C80. The combination of MS techniques with other selective detectors and reversed-phase column combinations has made it possible to quantify even traces of heteroatomic compounds in these complex hydrocarbon matrices. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), in some cases combined with GC × GC for the lighter part, has pushed the characterization of larger macromolecules in particular asphaltenes. Matrix-assisted laser desorption/ionization (MALDI) is also used widely for this purpose but has the disadvantage that quantification is not obvious. The development of more detailed characterization techniques has not remained unnoticed in the petrochemical society, and more recently in the petrochemical kinetic modeling society. More detailed characterization of petrochemical fractions has made the implementation of detailed kinetic models for simulation and optimization possible including more and more molecular detail. Additionally, advances in photo-ionization mass spectrometry (PI-MS) have allowed the detection of reactive intermediates and direct kinetic measurements in time-resolved experiments. It can only be expected that this trend will continue and that the application field will move from now primarily petrochemistry, (from catalytic cracking, over hydrotreating and hydrocracking, to pyrolysis, combustion, and steam cracking) to larger-scale chemical recycling and biomass conversion processes.

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“…The physicochemical characterisations of the crude oil samples were performed to determine properties like density, pH, viscosity (kinematic and dynamic), API gravity, moisture, and ash contents (Appenteng et al 2013;Nwadinigwe and Alumona 2014;Ofodile et al 2018;Rodrigues et al 2018). For each parameter, the experiment was conducted trice, and the mean value determined for quality assurance.…”

Section: Crude Oil Characterisationmentioning

confidence: 99%

Feldspar-banana peel composite adsorbent for efficient crude oil removal from solution

2020

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The problem of oil spill pollution associated with the transport of crude oil and its products across the globe is of serious concern. The sorption technique has proved to be promising for oil spill treatment but is limited by the hydrophilic nature of most natural organic sorbents. The combo of natural organic and inorganic sorbents have been found to enhance the hydrophobicity for oil sorption. Therefore this study was aimed at the preparation of a novel feldspar-banana peel biochar composite (FBPC) with enhanced hydrophobicity for the sorption of crude oil. The prepared sorbent was characterised by the scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques, while the crude oil was characterised using standard methods. Batch sorption was used to determine the effect of contact time (30–150 min), temperature (25–100 °C), pH (2.0–10.0), oil concentration (4.0–12.0 g/L) and sorbent dosage (0.1–0.5 g) on sorption. SEM analysis of FBPC revealed a porous structure, while XRD confirmed the crystalline phases of feldspar. The crude oil samples had pH (6.40–6.60), density (0.960 0 0.962 g/cm3), kinematic viscosity (24.0–27.6 cSt) and API gravity (24.25–24.51°). The Langmuir model with R2 > 0.7781 presented the best fit than the Temkin and Freundlich model in the isotherm analysis, while the pseudo-second-order model with R2 > 0.9711 was applicable in the kinetics of sorption. The thermodynamic analysis revealed a decrease in randomness at the crude oil-FBPC interface. The prepared FBPC was found to be an efficient inorganic–organic composite sorbent with enhanced hydrophobicity for the sorption of crude oil.

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Determination of crude oil physicochemical properties by high-temperature gas chromatography associated with multivariate calibration

Cited by 27 publications

References 30 publications

Application of Near-Infrared for Online Monitoring of Heavy Fuel Oil at Thermoelectric Power Plants. Part I: Development of Chemometric Models

Application of Near-Infrared for Online Monitoring of Heavy Fuel Oil at Thermoelectric Power Plants. Part I: Development of Chemometric Models

Analytics Driving Kinetics: Advanced Mass Spectrometric Characterization of Petroleum Products

Feldspar-banana peel composite adsorbent for efficient crude oil removal from solution

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