An Investigation on the Feasibility of Simulating the Distribution of the Boiling Point and Molecular Weight of Heavy Oils

Abstract

Thirty-four heavy oils originating from the four main groups of crude oils around the world-I group: light, low sulfur (30-400 API; S ≤ 0.5% mass); II group: light sulfur (30-400 API; S = 0, 5-1.5% mass); III group: heavy, high sulfur (15-300 API; S = 1.5, 3.1% mass); IV group: extra heavy, high sulfur (150 API, S ≥ 3% mass)-were investigated for distribution of boiling point and molecular weight. The three-parameter distribution model of Riazi and the four-parameter Webull extreme distribution function were tested to approximate the distribution of the heavy oil properties mentioned. It was found that the Weibull extreme more accurately approximates the heavy oil boiling point distribution up to temperatures of 750 • C, and molecular weight distribution up to 955 g/mol. To approximate distribution of higher values extrapolation is needed. Riazi's distribution model was found to be more precise in the extrapolation than the Weibull extreme.

Dependence of visbroken residue viscosity and vacuum residue conversion in a commercial visbreaker unit on feedstock quality

“…Density, characteristic factor Kw and distillation characteristics of the vacuum residual oils and atmospheric residual oils are presented in Table 1. The vacuum residual oil distillation characteristics were obtained by extrapolation of the distillation data of the atmospheric residual oils employing Riazi's boiling point distribution model [4]. Table 1 presents data of Riazi's boiling point distribution model parameters A T , B T , and also data of squared correlation coefficient R 2 (higher than 0.99 for all atmospheric residual oils) IBP,°C 540 540 541 538 541 540 542 542 540 539 539 10% 553 558 558 561 557 552 562 567 567 566 577 30% 578 599 576 603 595 585 616 621 628 616 652 50% 605 645 637 650 641 628 689 690 706 664 733 70% 657 716 702 703 704 692 798 803 814 719 832 90% 751 855 812 811 826 798 1016 1001 1020 815 991 95% 781 961 900 847 888 876 1184 1148 1128 861 1066 FBP 1150 1037 963 916 946 952 1240 1203 1383 940 1229 Kw 11.64 11.39 11.28 11.13 11.55 12.01 11.60 11.97 11.40 11.40 11.50 confirming the excellent fit with the measured distillation characteristics.…”

Some Comparison Results for Moving Least-Square Approximations

“…The matrix −A 2 D −1 is symmetric and positive semi-definite (see [11]). Therefore, L(a) = a, a , a ∈ R m is a Lyapunov function for (15). Indeed…”

“…For some application of moving least-squares approximation to predict chemical properties of oils see [15], [16], [17], and [18].…”

Empirical Modeling of Viscosities and Softening Points of Straight-Run Vacuum Residues from Different Origins and of Hydrocracked Unconverted Vacuum Residues Obtained in Different Conversions

“…Unfortunately, the determination of the VR's T 50% can be problematic when high-temperature simulated distillation (HTSD) is used, due to the inability of the entire amount of the VR sample to evaporate and enter the gas chromatographic column [30,31]. In this work, we employed HTSD to measure the distillation characteristics of diverse vacuum residues, and the continuous boiling point distribution model of Riazi [32] was applied to atmospheric residue distillation data to estimate the VR's T 50% . Then, we used this information to calculate the VR's molecular weight and to model the VR's rheological properties: viscosity and softening point.…”