Development of a generalized model for predicting the composition of homologous groups derived from molecular type analyses to characterize petroleum fractions

Hosseinifar, Pouya; Shahverdi, Hamid Reza

doi:10.1016/j.petrol.2021.108744

Cited by 8 publications

(13 citation statements)

References 35 publications

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“…Moreover, in some cases, specific gravity data may also not exist. However, the following relations were chosen from our previous work [72] to estimate the required physical properties under conditions where some of which may be unavailable.…”

Section: Auxiliary Relations For Supporting the Six-point Methodsmentioning

confidence: 99%

Prediction of the ASTM and TBP distillation curves and specific gravity distribution curve for fuels and petroleum fluids

Hosseinifar

Shahverdi

2022

Can J Chem Eng

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A predictive approach called the six-point method is developed to construct distillation curves of different petroleum fluids based on the information of six points of the distillation curve at volume percentages (5, 10, 30, 50, 70, and 90). Indeed, six diverse mathematical equations are developed, which establish relationships between the six mentioned distillation temperatures and physical properties (SG and T b ) of petroleum fluids. Having predicted the six points, a third-order polynomial curve can easily be fitted over these data. Accordingly, the six-point method is well capable of predicting the distillation curve of both American Society for Testing and Materials (ASTM) D86 and true boiling point (TBP) data for any arbitrary petroleum fluid using only their physical properties. Two auxiliary relations are also presented to estimate the physical properties that may not be available for a petroleum fraction. These relations enable the model to receive pairs of (Mw,SG) and (Mw, T b ) as input parameters, instead of (SG, T b ). A useful transfer function is also developed to convert the TBP curve predicted by the six-point method to the specific gravity distribution curve. Furthermore, a new set of experimental data obtained from the distillation test is also presented in this work. The experiment has been performed on the petroleum cuts resulting from the crude oil atmospheric distillation unit and Linear Alkyl Benzene (LAB) production unit. The model performance was carefully evaluated against a wide range of literature data as well as new experimental data provided in this study, and the mean of average absolute deviations (AAD%) values was 1.98% for about 233 samples, including 2039 data points.

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Section: Auxiliary Relations For Supporting the Six-point Methodsmentioning

confidence: 99%

Prediction of the ASTM and TBP distillation curves and specific gravity distribution curve for fuels and petroleum fluids

Hosseinifar

Shahverdi

2022

Can J Chem Eng

Self Cite

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“…To inform more details about the comparison of PNA and SAP methods, the readers are referred to other references. [9,37] Figures 3 and 4 show the behaviour of categorized data for six homologous groups resulted from PNA and SAP analyses. Although the behaviour of categorized substances is partly detectable, significant dispersions are still observed in the trends of data.…”

Section: Development Of Models For Predicting Eos Parametersmentioning

confidence: 99%

“…As a suggestion, it would be better to use the PNA method for light and medium petroleum fluids (Mw < 300 and SG < 0:9) and the SAP method for heavy fractions. [2] The generalized model presented in the work of Hosseinifar and Shahverdi [37] is recommended for determining the molar composition of either PNA or SAP…”

Section: Predicting the Molar Composition Of Homologous Groupsmentioning

confidence: 99%

“…T A B L E 5 Specifications of the reservoir fluids used in this study [47,48] Oil Normal boiling point values of plus fractions have been calculated using the distillation curve method. [52] T A B L E 6 The sequence of computational steps for seven different characterization procedures [37] Proposed model in Equation (5) Proposed model in Equation…”

Section: Predicting Eos Parameters Of Homologous Groupsmentioning

confidence: 99%

“…As with the traditional Pederson's approach, the main three steps (determining the molar composition, estimation of EOS parameters, and providing a lumping method) also need to be pursued here for homologous groups resulting from any unknown fraction. In the first step, the generalized model presented by Hosseinifar and Shahverdi [37] is used to predict the molar composition of both PNA and SAP sub-fractions derived from the main plus fraction. The second and third steps of the characterization are also provided in this research.…”

Section: Introductionmentioning

confidence: 99%

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An effective characterization procedure for petroleum reservoir fluids using molecular type methods and cubic equations of state

Hosseinifar

Shahverdi

2022

Can J Chem Eng

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Two eminent molecular type composition methods (paraffins, naphthenes, and aromatics [PNA] and saturates, aromatics, and polynuclear aromatics [SAP]) are employed to construct new characterization procedures for predicting the phase behaviour of petroleum fluids using a modified Peng-Robinson equation of state. The PNA and SAP methods divide a petroleum fraction into (PNA) and (SAP) homologous groups, respectively. Two generalized models are developed to predict the physical properties (Mw, SG, T b ) and equation of state (EOS) parameters (T c , P c , ω) for both PNA and SAP sub-fractions. Each generalized model covers 18 different correlations in a single mathematical form that enables the model to return 18 outputs for PNA and SAP sub-fraction parameters. A new lumping method is also developed to convert triple PNA or SAP pseudo-components into single characterized fractions. Accordingly, seven different characterization procedures are introduced and compared with one another. The first two procedures are completely constructed based on the proposed models, and the other procedures encompass the models already developed. The results obtained from the simulation of the differential liberation test for 12 diverse reservoir fluids and bubble pressure prediction for 40 oil samples revealed that the first two methods (1 and 2) could enhance the abilities of the traditional characterization procedures for reservoir fluid modelling. The mean value of average absolute relative deviations (AARDs) over a total of 52 oil samples is about 6.5% for the proposed methods and is about 13.2% for the best previously existing methods. Moreover, an efficient workflow is provided for the parameter tuning process, which is notably capable of reducing the level of prediction errors using only three adjustable parameters.

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Prediction of petroleum viscosity from molecular weight and density

Stratiev

Shishkova²,

Dinkov³

et al. 2023

Fuel

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Development of a generalized model for predicting the composition of homologous groups derived from molecular type analyses to characterize petroleum fractions

Cited by 8 publications

References 35 publications

Prediction of the ASTM and TBP distillation curves and specific gravity distribution curve for fuels and petroleum fluids

Prediction of the ASTM and TBP distillation curves and specific gravity distribution curve for fuels and petroleum fluids

An effective characterization procedure for petroleum reservoir fluids using molecular type methods and cubic equations of state

Prediction of petroleum viscosity from molecular weight and density

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