Quantification of Viscosity for Solvents−Heavy Oil/Bitumen Systems in the Presence of Water at High Pressures and Elevated Temperatures

Chen, Zehua; Li, Xiaoli; Yang, Daoyong

doi:10.1021/acs.iecr.8b04679

Cited by 20 publications

(3 citation statements)

References 46 publications

(128 reference statements)

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“…In addition, extra-heavy oil (bitumen) exists under pressure in the reservoir [8], and viscosity affects its mobility and production flow [9,10]. Thus, several efforts have been directed toward the prediction of the viscosity of bitumen (and of mixtures with solvents) at various temperatures and pressures [2][3][4][6][7][8][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Viscosity–Temperature–Pressure Relationship of Extra-Heavy Oil (Bitumen): Empirical Modelling versus Artificial Neural Network (ANN)

et al. 2019

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The viscosity data of two heavy oil samples X and Y, with asphaltene contents 24.8% w/w and 18.5% w/w, respectively, were correlated with temperature and pressure using empirical models and the artificial neural network (ANN) approach. The viscosities of the samples were measured over a range of temperatures between 70 °C and 150 °C; and from atmospheric pressure to 7 MPa. It was found that the viscosity of sample X, at 85 °C and atmospheric pressure (0.1 MPa), was 1894 cP and that it increased to 2787 cP at 7 MPa. At 150 °C, the viscosity increased from 28 cP (at 0.1 MPa) to 33 cP at 7 MPa. For sample Y, the viscosity at 70 °C and 0.1 MPa increased from 2260 cP to 3022 cP at 7 MPa. At 120 °C, the viscosity increased from 65 cP (0.1 MPa) to 71 cP at 7 MPa. Notably, using the three-parameter empirical models (Mehrotra and Svrcek, 1986 and 1987), the correlation constants obtained in this study are very close to those that were previously obtained for the Canadian heavy oil samples. Moreover, compared to other empirical models, statistical analysis shows that the ANN model has a better predictive accuracy (R2 ≈ 1) for the viscosity data of the heavy oil samples used in this study.

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Section: Introductionmentioning

confidence: 99%

Viscosity–Temperature–Pressure Relationship of Extra-Heavy Oil (Bitumen): Empirical Modelling versus Artificial Neural Network (ANN)

et al. 2019

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“…They evaluated and compared the performance of the IM rule with the volume-translated PR EoS. Chen et al 30 also developed a technique for the quantification of the viscosity of light solvents−heavy oil/bitumen−water systems as a function of pressure in a temperature range of (287.9−463.4 K) by using the PR EoS along with the modified alpha function and binary interaction parameters. Six different mixing rules were evaluated and compared in their study.…”

Section: Introductionmentioning

confidence: 99%

Measurements and Correlations of Thermophysical Properties for Multicomponent Solvent/Live Bitumen Mixtures

et al. 2022

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We report new measurements and correlations of the density, viscosity, solubility, and K-values of multicomponent solvent/live bitumen systems with applications to the solvent-aided thermal recovery of bitumen. The density, viscosity, solubility, and K-values of live bitumen and a multicomponent solvent composed of n-C4, n-C5, n-C6, n-C8, and n-C10 were measured at a pressure range of 1−6 MPa and a temperature range of 343.15−503.15 K. A systematic approach is presented that can be adapted for the construction of input PVT models for thermal reservoir simulations. The measured data are correlated with the temperature-and pressure-dependent correlations used in commercial thermal reservoir simulators. Accepted agreements were found between all the predicted properties and experimental data of the multicomponent solvent/live bitumen system. The data and the parametrization approach find applications in the design and optimization of solvent-aided thermal recovery of bitumen.

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“…10 Although much efforts have been directed toward the prediction of the viscosity of bitumen with solvent mixtures, in some cases under different temperatures and pressures as shown by several researchers, there is still limited research to accurately make the prediction with light oils used in the mixtures. Chen et al 11 proposed a way to accurately predict the viscosity for light solvents (i.e., methane, ethane, propane, n-butane, n-pentane, N 2 , and CO 2 )−heavy oil/bitumen/water systems as a function of pressure in a temperature range of 287.9−463.4 K. The LV and ALV (L is the oleic phase, V is the vapor phase, and A is the aqueous phase) phase equilibria of the aforementioned systems were calculated using the Peng−Robinson equation of state (PR EOS) with modified α functions and binary interaction parameters (BIPs). The six widely used mixing rules for predicting the viscosity of solvents−heavy oil/bitumen systems pertaining to vapor−liquid equilibria were compared and evaluated, while the linear mixing rule was used for hydrocarbons−water mixtures.…”

Section: Introductionmentioning

confidence: 99%

New Method to Predict the Viscosity of Bitumen Diluted with Light Oil Using a Modified Van Der Wijk Model under Reservoir Temperature and Pressure

et al. 2021

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In this study, we introduce a new method for the prediction of the viscosity of bitumen diluted with light oil under reservoir temperature and pressure. This two-step method works as follows: first, predicting the bitumen viscosity under reservoir temperature and pressure using the classical Mehrotra and Svrcek model, and then subsequently using it in the modified Van Der Wijk (MVDM) model. This model formed from the modification of the original Van Der Wijk model was developed from the consideration of the interactions between like molecules in different binary components of the mixture. In this study, the bitumen viscosity was predicted with an average absolute deviation percentage (AAD%) of 3.86. The accuracy of the MVDM was investigated from the experimental results obtained from the rheological studies of three binary mixtures of light oil (API 32°) and bitumen (API 7.39°). Dead oils were mixed on a mass fraction basis. The viscosity was measured at a temperature range of 45–110 °C and a pressure range of 0.1–6 MPa. For comparison purposes, a reworked Van Der Wijk model (RVDM) was used in the same method and compared to the MVDM. The latter was more accurate than the RVDM with AAD% values of 8.88, 8.02, and 5.07 in predicting the viscosity of the three mixtures of 25, 32.5, and 50% bitumen with light oil. On the other hand, the RVDM had AAD% values of 12.42, 11.43, and 7.87 for the same mixtures, respectively. The applicability of this method was further verified by comparing its accuracy to another reported method using published data and it was found that the MVDM had AAD% values of 1.86, 6.55, and 2.823 when predicting the viscosities of the three mixtures under reservoir temperature and pressure conditions.

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Quantification of Viscosity for Solvents−Heavy Oil/Bitumen Systems in the Presence of Water at High Pressures and Elevated Temperatures

Cited by 20 publications

References 46 publications

Viscosity–Temperature–Pressure Relationship of Extra-Heavy Oil (Bitumen): Empirical Modelling versus Artificial Neural Network (ANN)

Viscosity–Temperature–Pressure Relationship of Extra-Heavy Oil (Bitumen): Empirical Modelling versus Artificial Neural Network (ANN)

Measurements and Correlations of Thermophysical Properties for Multicomponent Solvent/Live Bitumen Mixtures

New Method to Predict the Viscosity of Bitumen Diluted with Light Oil Using a Modified Van Der Wijk Model under Reservoir Temperature and Pressure

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