Viscosity modeling of reservoir fluids using the Friction Theory with PC-SAFT crude oil characterization

Abutaqiya, Mohammed I. L.; Zhang, Jieyi; Vargas, Francisco M.

doi:10.1016/j.fuel.2018.06.062

Cited by 19 publications

(34 citation statements)

References 43 publications

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“…The saturate, aromatic, and resin content of a crude oil are determined simply using infrared and near-infrared spectroscopy at high pressure and temperature [66]. The composition and density of saturated hydrocarbons and aromatic ones, and the structural-group properties of resins and asphaltenes in four heavy, highly viscous oils of Northern West Siberia [63] and five light crude oils with low asphaltene content from the Middle East region [62] are shown in Figure 2b.…”

Section: Saturates Aromatics Resins and Asphaltenes Distribution Amentioning

confidence: 99%

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Occurrence and Characterization of Paraffin Wax Formed in Developing Wells and Pipelines

et al. 2019

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Deposition and precipitation of paraffin wax in pipelines are major problems in the production, transfer, storage, and processing of crude oil. To prevent complete clogging, it is necessary to minimize and remove deposited wax in pipelines and tubing. Significant research has been done addressing the mechanisms of wax formation and its composition. In this review, the status of research and perspectives on the occurrence and characterization of the paraffin wax that forms in crude oil developing wells and pipelines has been critically reviewed. Several approaches for detecting paraffin wax and managing wax formation damage during oil recovery were discussed. This review also highlighted the effects of temperature and crude oil type on wax formation.

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Section: Saturates Aromatics Resins and Asphaltenes Distribution Amentioning

confidence: 99%

“…The mechanisms of asphaltene precipitation concerning the nature in solution (a) and the distribution of saturated hydrocarbons (HCs), aromatics, resins, and asphaltenes and the density of some crude oils from different regions (b). The data highlighted in yellow refer to the Middle East[62], while those in green are for Northern West Siberia[63].…”

mentioning

confidence: 99%

Occurrence and Characterization of Paraffin Wax Formed in Developing Wells and Pipelines

et al. 2019

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“…There are also several methods for modeling the viscosity of complex mixtures, including expanded fluid theory [31][32][33][34] , friction theory [35][36][37][38][39] , free volume theory (FVT) 40,41 , hard sphere models [42][43][44] , residual entropy scaling 45,46 , Eyring's absolute rate theory 47,48 , and GC methods [49][50][51][52] .…”

Section: Introductionmentioning

confidence: 99%

Effect of Composition, Temperature, and Pressure on the Viscosities and Densities of Three Diesel Fuels

et al. 2019

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In this work, a Rolling-Ball Viscometer/Densimeter is used to measure high-pressure, hightemperature (HPHT) density and viscosity data from 298.2 to 532.6 K and pressures up to 300.0 MPa for three different diesel fuels. The densities and viscosities have combined expanded uncertainties of 0.6% and 2.5%, respectively, with a coverage factor, k = 2. Two of the diesels, Highly Paraffinic (HPF) and Highly Aromatic (HAR), contain a larger paraffinic and aromatic content relative to the others, and are standard engine test fuels. The third is a Ultra-Low Sulfur Diesel (ULSD) that resembles an unfinished commercial diesel. Detailed compositional information is also reported for each diesel that provides a basis for interpreting the impact of composition on density and viscosity at high pressures. Both density and viscosity data are correlated to Tait-type equations with uncertainties of 0.6% and 4.0%, respectively. The Tait equations provide a facile means to compare observed differences in the density-pressure and viscosity-pressure profiles of the three different diesels. Density data are modeled with the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) equation of state (EoS) with pure component parameters calculated representing diesel as a single, pseudo-component only requiring average molecular weight (Mave) and hydrogen to carbon ratio (RH/C) as inputs. Viscosity data are modeled reasonably well using entropy scaling coupled with the PC-SAFT EoS and information on the diesel Mave and RH/C. The HPHT viscosity data are also modeled reasonably well with Free Volume Theory (FVT) with model parameters correlated to Mave and RH/C.

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“…Computational cost and complexity can be reduced further through pseudo-component viscosity mixture models. Examples of these models include expanded fluid theory (EFT) [37][38][39][40], friction theory (FT) [41][42][43][44][45], free volume theory (FVT) [46,47], the Dymond-Assael (DA) hard sphere model [48][49][50], and Eyring's absolute rate theory [51,52]. Motahhari et al [38,39] applied EFT to model the viscosity of several crude oils characterized as mixtures of pseudo-components at temperatures to 473 K and pressures to 552 bar.…”

Section: Introductionmentioning

confidence: 99%

“…These authors fit FT parameters to viscosity data above the saturation pressure and made predictions below the saturation pressure. Abutaqiya et al [45] applied FT to model the viscosity of ten Middle Eastern crude oils represented as mixtures of pseudo-components. These authors proposed a new fitting approach for FT and reduced the required number of input parameters for each pseudo-component from two to one.…”

Section: Introductionmentioning

confidence: 99%

Entropy scaling based viscosity predictions for hydrocarbon mixtures and diesel fuels up to extreme conditions

Rokni

Moore

Gupta

et al. 2019

Fuel

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An entropy scaling based technique using the Perturbed-Chain Statistical Associating Fluid Theory is described for predicting the viscosity of hydrocarbon mixtures and diesel fuels up to high temperatures and high pressures. The compounds found in diesel fuels or hydrocarbon mixtures are represented as a single pseudo-component. The model is not fit to viscosity data but is predictive up to high temperatures and pressures with input of only two calculated or measured mixture properties: the number averaged molecular weight and hydrogen to carbon ratio. Viscosity is predicted less accurately when the mixture contains high concentrations of iso-alkanes and cyclohexanes. However, it is shown that predictions for these mixtures are improved by fitting a 2 third parameter to a single viscosity data point at a chosen reference state. For hydrocarbon mixtures, viscosity is predicted with average mean absolute percent deviations (MAPDs) of 12.2% using the two-parameter model and 7.3% using the three-parameter model from 293 to 353 K and up to 1,000 bar. For two different diesel fuels, viscosity is predicted with an average MAPD of 21.4% using the two-parameter model and 9.4% using the three-parameter model from 323 to 423 K and up to 3,500 bar.

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Viscosity modeling of reservoir fluids using the Friction Theory with PC-SAFT crude oil characterization

Cited by 19 publications

References 43 publications

Occurrence and Characterization of Paraffin Wax Formed in Developing Wells and Pipelines

Occurrence and Characterization of Paraffin Wax Formed in Developing Wells and Pipelines

Effect of Composition, Temperature, and Pressure on the Viscosities and Densities of Three Diesel Fuels

Entropy scaling based viscosity predictions for hydrocarbon mixtures and diesel fuels up to extreme conditions

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