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Article

The Incompatibility Pitfall in Refining Opportunity Crude Oils

1
LUKOIL Neftohim Burgas, 8104 Burgas, Bulgaria
2
Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Georgi Bonchev 105, 1113 Sofia, Bulgaria
3
Central Research Laboratory, University Prof. Dr. Assen Zlatarov, Professor Yakimov 1, 8010 Burgas, Bulgaria
4
Department of Computer Systems and Technologies, University Prof. Dr. Assen Zlatarov, Professor Yakimov 1, 8010 Burgas, Bulgaria
5
Black Oil Solutions, 2396 Koudekerk aan den Rijn, The Netherlands
6
Department Industrial Technologies and Management, University Prof. Dr. Assen Zlatarov, Professor Yakimov 1, 8010 Burgas, Bulgaria
7
Department Chemical Technologies, University of Chemical Technology and Metallurgy, Kliment Ohridski 8, 1756 Sofia, Bulgaria
*
Author to whom correspondence should be addressed.
Processes 2025, 13(2), 593; https://doi.org/10.3390/pr13020593
Submission received: 31 January 2025 / Revised: 14 February 2025 / Accepted: 18 February 2025 / Published: 19 February 2025

Abstract

:
Refining light and heavy oils in different proportions seems attractive, especially in cases of geopolitical, economic, environmental, and logistical constraints. The economical attractiveness could be undermined in cases where incompatibility occurs. The current study explores a highly complex refinery performance during processing a blend consisting of 17 crude oils of which one was extra light, five were light, nine were medium, and two were heavy. A n-heptane dilution test, using centrifugation, was employed to assess the colloidal stability of crude oils. In addition, a previously established correlation to relate crude oil vacuum residue fraction Conradson carbon content to asphaltene peptizability Sa according to ASTM D 7157 was also availed for the purpose of evaluating colloidal stability. It was found that the crude desalter amperage increases with the S B N I B N ratio and Sa reduction, reaching its maximum allowable value of 180 A at the S B N I B N ratio of 1.35, and Sa of 0.64. The S B N I B N ratio was found more reliable in predicting oil compatibility than the other S B N I N m a x ratio used to assess colloidal stability in various research. Along with the increase in crude desalter amperage, fouling of the heat exchangers of a crude oil distillation plant was also recorded. An intercriteria analysis of process data together with crude composition data, and compatibility indices revealed that the amperage enhancement is statistically meaningfully related to an increase in the heaviest crude oil content in the process blend and the compatibility indices S B N I B N ratio and Sa, while the fouling was related only to the content of one of the light crude oils in the processed blend.

1. Introduction

The wide diversity of the composition of petroleum makes the process of crude selection in petroleum processing an extremely complicated and challenging task. Moreover, refineries typically process a blend of crude oils instead of a single crude oil [1]. The selection of crude oil or blends of crude oils not taking into account the constraints of the refinery and the characteristics of the selected crude oils can lead to poor performance in terms of desalter upset [2,3,4,5,6], unexpected high corrosion rate [7,8,9,10,11,12], unexpected high fouling rate [2,13,14,15], and equipment failure [16,17,18], resulting in a huge loss of profit opportunity due to unplanned shut down to fix the related technical problems (repairing of damaged equipment, cleaning of fouled equipment, replacement of corroded pieces of equipment like tubes, damaged parts of rotating equipment, and others).
The heaviest and most polar fraction of crude oil—asphaltenes—is that part of petroleum that causes many problems in both exploration and oil refining [19,20,21]. They contribute to water–oil emulsion stabilization [22,23,24], impairing in this way the crude oil dewatering and desalting process, and tend to form sediments leading to increased equipment fouling [25]. The content of asphaltenes is by itself not a reliable indicator for the occurrence of incompatibility issues, desalter upsets, and increased fouling. The presence of naphthenic acids in appreciable amounts in crude oil is also a concern because they can deteriorate the dewatering and desalting process [26], and provoke a high corrosion rate [27]. Unfortunately, the preliminary detection of likely high corrosivity of crude oil is also a major challenge. The total acid number (TAN) employed to classify the crude oils as acidic (TAN > 0.5 mg KOH g−1) [28], and therefore corrosive, has failed to predict the corrosiveness of crude oils from Indonesia and Nigeria having TAN of 0.3 mg KOH g−1 and sulfur content of 0.24% [10]. All of this illustrates how complicated the chemistry of petroleum is, which makes the process of predicting the behavior of a single crude oil or blend of crude oils during processing very difficult. The processing of discounted heavier, sour, and more acidic crude oils (TAN (total acid number) exceeding 0.5 or 1.0 mg KOH/g) coined “opportunity crudes” has always been tempting for refiners in their quest to improve profitability. The refining of “opportunity crudes”, however, can represent extraordinary technical challenges, and in fact, the opportunity seems to reflect their prices and not an intrinsic profitability due to the appearance of unplanned shut downs for equipment cleaning and repairing that is a result of the processing of opportunity crudes [29]. In order to reduce the technical risk of processing the opportunity crudes, a better knowledge of complex interactions taking place during blending crude oils is required. Some blends turn out inappropriate because they promote the formation of asphaltene deposits or stable emulsions [30,31], while there are suitable blends that may mitigate the effect of fouling due to the presence therein of natural fouling inhibitors [32]. Crude oil compatibility has been comprehensively investigated using the colloidal stability principles [33,34,35,36,37]. Wiehe and Kennedy [38,39] presented the basics of the oil compatibility model. According to it, a crude blend or a mixture of oils is compatible when the ratio of solubility blending number (SBN) to the maximum insolubility number (INmax) of all the oils is S B N I N m a x > 1.4 [38,39,40]. INmax equals the highest IN of the oils in the mixture [40]. These two oil solubility parameters are determined by mixing the crude oil with toluene and n-heptane in various ratios and observing whether each mixture dissolves or precipitates asphaltenes by using an optical microscope [36]. Another dual solvent titration method that employs toluene and n-heptane and an optical probe for the detection of asphaltene flocculation is ASTM D 7157 (S-value) [41]; this method s reported to apply the same threshold value of not lower than 1.4 for the S-value to control severity in a commercial visbreaker to maximize conversion while producing colloidally stable fuel oil [42]. The threshold value providing compatibility when the dual solvent titration method that employs xylene and n-heptane and optical probe ASTM D 7112 (p-value) [43] for the detection of asphaltene flocculation equals 1.20 (p-value > 1.2) based on the relation of S-value to p-value as shown in Equation (1) and in Figure 1.
P v a l u e = 0.475 × S v a l u e + 0.5342 R 2   =   1.00
Shishkova et al. established that the crude oil desalting efficiency of a commercial desalting and dewatering unit deteriorated when S B N I N m a x 1.4 of the processed crude blends [44]. They determined both oil solubility parameters by using an n-heptane dilution test with centrifugation as explained in [45]. Another dual solvent titration method that employs 1-methylnaphtalene and cetane and an optical probe for the detection of asphaltene flocculation, ASTM D 7060 (p-ratio) [46], reportedly uses a threshold value of p-ratio s not lower than 1.1 (p-ratio > 1.1) [40]. Vermeire and Heyberger [40], investigating 35 fuel mixtures, ascertained that the prediction of compatibility of oil blends by using the three methods ASTM D 7157, ASTM D 7112, and ASTM D 7060 showed the following per cent of good predictions of measured stability utilizing the total sediment potential (TSP) and total sediment acceleration (TSA): 57%, 51%, and 73%, respectively, when the threshold values for S-value and p-value were set at 1.4, and a p-ratio of 1.1. Lowering the threshold value from 1.4 to 1.1 for the S-value and p-value increased the percentage of good predictions to 74 and 77%, respectively [40]. These results suggest that the threshold value of S B N I N m a x 1.4 appears conservative. The study of Alonso et al. [47], however, reported that blends of extra heavy and heavy crude oils with intermediate and light crude oils exhibited colloidal instability when S-value determined by the ASTM D 7157 method was lower than 1.5, metastability for 1.5 < S-value < 2.0, and stability for S-value > 2.0. All these reports confirm the statement of Guzman et al. [48] that the prediction of the compatibility of crude oils is still a pending issue, and that the threshold value of parameters S-value, p-value, and p-ratio can be different for the distinct investigated cases.
Sharma et al. [49] pointed out that the colloidal stability characteristics are not always sufficient to provide the required information for the prevention of the formation of stable emulsions during crude oil desalting and dewatering. The stable emulsions can be manifested by the buildup of a rag layer, higher water content in desalted crude, and/or increased amperage of desalter [49]. Increased amperage that reached the maximum allowable value was observed when an opportunity crude oil (specific gravity of 0.9453, and sulfur content of 5.75 wt.%) blended with 16 other crude oils in different ratios was processed in the LUKOIL Neftohim Burgas refinery (LNB). In addition, a high fouling rate in the crude oil heat exchangers in one of the crude distillation units was registered during the refining of crude blends of eight petroleum oils with the opportunity crude oil. The processing of the same opportunity crude oil in blends with the other twelve crude oils, however, did not indicate any signs of fouling that put forth questions about the relation of opportunity crude processing to the heat exchanger fouling. An intercriteria analysis of crude blend characteristics, process data related to fouling, and desalter amperage was performed, which revealed the factors controlling the observed phenomena.
In this study, the reasons for the amperage spike in a crude desalter unit during processing a blend of seventeen crude oils are investigated. Factors like the contents of individual crude oils in petroleum blend, and the compatibility indices solubility blending number (SBN), insolubility number (IN), insolubility blending number (IBN), the ratios SBN/INmax, SBN/IBN, and the asphaltene peptizability (Sa) correlation and their influence on the crude desalter amperage has been evaluated by using intercriteria analysis (ICrA). The ICrA as an artificial intelligence tool to evaluate the presence or absence of statistically meaningful relations no matter whether they are linear or not in contrast to the correlation analyses which detect only linear relations has been the preferred method to investigate the variables mentioned above. Unlike correlation analyses, the ICrA provides information not only on the degree of correlation (consonance), but this consonance can be both positive and negative, and also on the degree of dissonance [50]. To the best of our knowledge, no reports have appeared in the literature yet dealing with the crude desalter amperage spike and its relation to the contents of the crude oils processed, their properties, and the characteristics of the crude blend, including compatibility indices. In addition, no evidence has been provided in the literature which compatibility ratio SBN/INmax or SBN/IBN better describes the colloidal stability of oil mixtures.
The aim of this article is to investigate the phenomena of high amperage in crude desalter and heat exchanger fouling during processing blends of 17 crude oils, one of which pertains to the group of “opportunity crudes”, and discuss the obtained results.

2. Materials and Methods

Seventeen crude oils were processed in the LNB refinery during the study. Their properties are summarized in Table 1. These crude oils were examined for their colloidal stability by using an n-heptane dilution test with centrifugation as detailed in [51]. The solubility blending number of the processed crude blends was calculated using Equation (2) as described in [52].
S B N b l e n d = i n V i × S B N i
where
  • SBNblend = Solubility blending number of the crude oil blend;
  • SBNi = Solubility blending number of the “i-th” individual crude oil in the blend;
  • Vi = Volume fraction of the “i-th” individual crude oil in the blend.
The insolubility blending number of the processed crude blends has been calculated using Equation (3) as described in [52].
I B N = i n M i × a i × I N i i n M i × a i
where
  • Mi = Mass percentage of the “i-th” individual crude oil in the blend, wt.%;
  • ai = content of C7–asphaltenes in the “i-th” individual crude oil of the blend, wt.%;
  • INi = insolubility number of the “i-th” individual crude oil in the blend.
In addition to the solubility blending number and insolubility blending number, the stability indices solubility power (Sp) and critical solubility power (Sp critical) were determined on the basis of the results from the n-heptane dilution test with centrifugation as described in [51]. The blend stability indices Sp blend and Sp critical blend were calculated by using Equations (2) and (3), where the SBNi was substituted by Spi in Equation (2) and INi is substituted by Sp criticali in Equation (3).
Table 2 presents data on the properties of vacuum residual fractions distilled from the studied crude oils in a laboratory true boiling point (TBP) column (Euro Dist System from ROFA Deutschland GmbH Lohmar, Germany) designed to perform according to the ASTM D 2892 [53] requirements.
The atmospheric residue from the TBP column was fractionated under vacuum, from 1 to 0.2 mmHg, in a Potstill Euro Dist System from ROFA Deutschland GmbH according to the ASTM D 5236 [54] requirements to obtain the investigated vacuum residue fractions boiling above 540 °C. The properties of vacuum residue fractions were used to correlate with asphaltene peptizability (Sa-value) measured by the dual solvent titration method ASTM D7157 [41] as explained in [55]. Equation (4) relates the Sa-value to the vacuum residue Concarbon content as shown in Figure 2.
S a = 0.9469 0.0109 × V R   C C R R   =   0.969 ,   st .   error   =   0.02
where
  • VR CCR = Concarbon content of petroleum vacuum residue, wt.%;
  • Sa = the peptizability of an asphaltene according to ASTM D 7157.
The evaluation of the relations of oil characteristics to process data can be made by using either correlation analysis or intercriteria analysis (ICrA) [44,56,57]. However, while the correlation analyses are capable of detecting relations that are linear, the ICrA allows finding statistically meaningful relations of any type (linear or nonlinear). That is the reason why we prefer the evaluation to be performed by using ICrA. Details of the theory and application of ICrA are given in [44]. ICrA estimates two intuitionistic fuzzy functions: μ and υ, whose values determine the extent of the relationship between the studied parameters. For μ = 0.75 ÷ 1.00 and υ = 0 ÷ 0.25, a region of statistically meaningful positive consonance is obtained, whereas at μ = 0 ÷ 0.25 and υ = 0.75 ÷ 1.00, an area of statistically meaningful negative consonance is derived. All the other cases are considered to be dissonance. Two software packages for ICrA were established and freely available as open source from https://intercriteria.net/software/ and detailed in [58,59,60]. Before the ICrA evaluation, all the variables are normalized using the normalization formula (Equation (5)).
X n e w = X X m i n X m a x X m i n
where
  • Xnew = Normalized variable (crude desalter amperage, Sa, SBN, IN, IBN, and others);
  • X = Actual value of the investigated variable;
  • Xmin = The minimal value of the investigated variable;
  • Xmax = The maximal value of the investigated variable.
Figure 3 summarizes the methodology used in this research.

3. Results and Discussion

Table 3 presents the range of variation in the seventeen crude oils in the processed crude blends in the LNB refinery for the two investigated periods of time October–November 2024 and December 2024–January 2025 when the opportunity crude oil ITR was processed.
The data in Table 3, which are daily averages, indicate that the content of the opportunity crude oil ITR reached a maximum of 10.7 wt.% in the processed crude oil blend for the investigated period of time.
Figure 4 visualizes the daily composition of petroleum mixtures for the two periods when the opportunity crude oil ITR was refined. The data for the composition of the petroleum blend along with the compatibility indices of the individual petroleum oils was employed to calculate the compatibility blending indices SBN and IBN by using Equations (1) and (2).

3.1. Compatibility Indices of Individual Crude Oils and Their Mixtures

Table 4 summarizes the compatibility indices determined by the n-heptane dilution test (SBN, IN, and SBN/IN) as described in [46] and the Sa-value calculated by Equation (4). The crude oils CPC, Azeri Light, and TEN did not indicate any precipitation of asphaltenes during the performance of the n-heptane dilution test. For that reason, it was not possible to determine the compatibility indices SBN, IN, SBN/IN for these crude oils.
It is evident from the data in Table 4 that the crude oils El Bouri, and Rhemoura have S B N I N ratio at the borderline of 1.4, while all the other crude oils following Wiehe’s qualification can be considered colloidally stable. It is worth mentioning here that the opportunity crude oil ITR exhibited the lowest solubility of asphaltenes (IN = 78; Sa = 0.573) and the highest solubility power of maltene fraction.
Table 5 displays the values of compatibility indices calculated on the base of data from Table 4 and using Equations (1)–(3).
If the rule S B N I N m a x > 1.4 proposed by Wiehe et al. [33,34,35] is applied for the investigated cases, it would mean that all the crude oil mixtures studied, except the blends that did not contain the opportunity crude oil ITR, were incompatible. This would also mean that crude oil desalter efficiency should have dropped as reported in [40,46]. In reality, however, the crude desalting efficiency did not decrease and remained at the level of about 93% for the whole investigated space of time. The introduction of opportunity crude oil ITR in the processed petroleum mixture started on 29 October 2024 for the first period of processing this crude oil in the LNB refinery (October–November 2024) and on 28 December 2024 for the second period of refining the ITR crude oil (December 2024–January 2025). That was associated with a decrease of S B N I N m a x ratio from 1.47 to 1.05 for the first period and from 1.59 to 1.13 for the second period. At this very low S B N I N m a x ratio of about 1.1, the crude oil desalting efficiency should have dropped from about 95 to about 73% after Shishkova et al. [44], which was not observed during the processing of ITR crude oil. These findings suggest that the use of S B N I N m a x ratio may not always be associated with the observation of phenomena related to oil incompatibility, such as deterioration in desalination efficiency. For that reason, we adopted the method proposed by van den Berg [52] summarized in Equations (2) and (3). In this way, the S B N I B N ratio was calculated, and as evident from the data in Table 5, there are cases (from 3 November to 8 November 2024) where this ratio was lower than the borderline of 1.4. Nevertheless, as stated above, the efficiency of the desalting of the crude blend was not affected at all. Instead of a deterioration in desalination, an increase in amperage was recorded, which will be discussed below.

3.2. Commercial Crude Desalting and Dewatering Unit Amperage Varaiation and Its Relation to the Compatibility Indices

With the introduction of opportunity crude oil ITR in the LNB refinery, an increase in crude desalter amperage was registered (Figure 5). It reached the maximum allowable value of 180 ampers for the crude desalter when the ITR content in the processed crude oil mixture reached 10 wt.% during the first period of ITR processing (October–November 2024) (Figure 5 and Figure 6). Interestingly, during the second period of processing the opportunity crude oil ITR (December 2024–January 2025), the maximum amperage of the crude desalter reached 140 ampers at 10.7 wt.% ITR in the processed petroleum mixture (Figure 5 and Figure 6). The amperage value of the crude desalter was found to correlate with the S B N b l e n d I B N ratio as computed by Equations (2) and (3) and the asphaltene peptizability as calculated by Equation (4) (Figure 7). Based on this data set, one may conclude that the amperage of the crude desalter is controlled by crude blend compatibility expressed by the S B N b l e n d I B N ratio and asphaltene peptizability assessed by Sa-value.
In order to assess the presence of statistically meaningful relations between the crude blend composition, compatibility indices, and the crude desalter amperage, an ICrA evaluation of the data from Figure 4 and Table 5 was performed. The results of the ICrA evaluation are summarized in Table 6 and Table 7. One can see from the data in Table 6 and Table 7 that the amperage has statistically meaningful positive consonances with the content of ITR in the processed crude blend (μ = 0.8; υ = 0.18) and IBN (μ = 0.85; υ = 0.13), and statistically meaningful negative consonances with the S B N b l e n d I B N ratio (μ = 0.10; υ = 0.88) and Sa (μ = 0.07; υ = 0.91). These findings suggest that the insolubility of asphaltenes in the opportunity crude ITR and its content in the processed petroleum mixture that affect the S B N b l e n d I B N ratio and Sa value were the governing factors controlling the amperage value in the crude desalter. Apparently, during the second period of ITR processing in the LNB refinery, the other crude oils in the processed oil blend were more appropriate in terms of their minimization of the S B N b l e n d I B N ratio and Sa of the petroleum mixture (see the data in Table 5 and Figure 7a,b). By using the regression equations shown in Figure 7a,b which relate the compatibility indices the S B N b l e n d I B N ratio and Sa to the crude desalter amperage, it was estimated that the content of opportunity crude oil ITR in the crude blend processed during the second period (December 2024–January 2025) may be increased from 10.7 wt.% up to 20 wt.% at the expense of a reduction in the crude oil Basra Med from 9.3 wt.% to 0.0 wt.%. This enhancement of ITR content in the processed crude blend will be associated with a reduction in the S B N b l e n d I B N ratio from 1.45 down to 1.36 that should correspond to a crude desalter amperage value of 176 A.
The following Equations (6)–(8) derived in this work could be used to quantitatively assess the effect of the compatibility indices S B N I B N and Sa on the crude oil desalter amperage.
D S A = 589.67 303.87 × S B N I B N R   =   0.937   st .   error   =   12.6   A
D S A = 1011.5 1305.1 × S a R   =   0.967   st .   error   =   9.1   A
D S A = 482.6 223.2 × S p S p c r i t i c a l R   =   0.925   st .   error   =   13.6   A
where
  • DSA = crude desalter amperage, A;
  • S B N I B N = ratio calculated by using Equations (2) and (3), and the data for SBN, and IN of individual crude oils shown in Table 4, and the content of individual crude oils in the processed mixture;
  • S a = asphaltene peptizability calculated by Equation (4);
  • S p S p c r i t i c a l = ratio calculated by using Equations (2) and (3), and the data for Sp and Sp critical of the individual crude oils shown in Table 4, and the content of the individual crude oils in the processed mixture.
The maximum allowable amperage of 180A of the crude desalter calculated by Equations (6)–(8) can be achieved at S B N I B N of 1.35, S p S p c r i t i c a l of 1.36, and Sa of 0.64. The conclusion made by Wiehe [38,39] that compatibility issues may occur when the S B N I N < 1.4 is confirmed by the results of this work, whereas the finding of Ancheyta [61] that compatibility issues may not take place when the ratio S p S p c r i t i c a l > 1.0 was not confirmed in this research.
Various tests and compatibility indices have been used to evaluate the colloidal stability of crude oils [1,45,48,62,63,64]. Guzmán et al. [62] reviewed most of them omitting the ratio S p S p c r i t i c a l , which has been discussed by Ancheyta [61] at a later stage. S-value, Sa, and So determined by the ASTM D 7157 have been employed to evaluate colloidal stability by Alonso et al. [47], and Guzmán et al. [48]. In the present research, three compatibility indices were availed: S B N I B N , S p S p c r i t i c a l , and Sa. In order to use S-value and So in the current study, data of 16 crude oils different from those processed at the LNB refinery were analyzed for their S-value, So, Sa, and the densities of the crude oils and vacuum residual oils, measured at 15 °C. The range of variation in the crude oil density was between 0.7936 and 0.9394 g/cm3, while that of the vacuum residue fractions fluctuated between 0.9612 and 1.1261 g/cm3. It was found that the So correlated with the correlation of Correra et al. [64] given as Equation (9) as indicated in Figure 8.
δ c o = 24.042 d 0.5 4.5989
where
  • δ c o = solubility parameter of the crude oil, MPa 0.5;
  • d = crude oil density at 15 °C, g/cm3.
The equation relating the δ c o solubility parameter to the So-value is given as Equation (10).
S o = 0.3327 × δ C O 5.33 R   =   0.94 st .   error   =   0.06
The other parameter Sa (asphaltene peptizability) was established to correlate with the vacuum residue fraction density as shown in Figure 9.
Equation (11) summarizes the dependence shown in Figure 6.
S a = 2.866 2.061 × V R d R   =   0.914 st .   error   =   0.05
Equations (10) and (11), along with data about the crude oil contents (Figure 4) and crude and vacuum characteristics summarized in Table 1 and Table 2 and Equations (2) and (3), were employed to calculate the S-value of the processed petroleum blends. The correlation of crude desalter amperage to calculate the S-value developed in this research is given below.
D S A = 405.53 157.02 × S v a l u e R   =   0.884 st .   error   =   16.7   A
The maximum allowable amperage of 180 A of the crude desalter computed by Equation (12) equals an S-value of 1.44, which is in agreement with the statement of Alonso et al. [47] that at an S-value lower than 1.5, the crude oil blend is unstable.
The Sa calculated by Equation (11) was also used to be related to the crude desalter amperage. Equation (13) exhibits the correlation of Sa computed by the vacuum residue density and the crude desalter amperage.
D S A = 965.0 1210.8 × S a R   =   0.955 st .   error   =   10.7   A
where
  • Sa* = asphaltene peptizability calculated by Equation (11).
The correlations of DSA (Equations (6)–(8), (12) and (13)), established in this research, indicate that the most accurate prediction of the crude desalter amperage is that based on the Sa parameter calculated from the vacuum residue Conradson carbon content.
The correlations developed in this work (Equations (10) and (11)), together with the crude oil density variability and vacuum residue data reported in [44], indicate that So should fluctuate between about 0.5 and about 1.0, while Sa can vary between about 0.5 and 0.9. If one takes a look at the data reported by Guzmán et al. [48], one can see data for an So of 2.56, which is far away from the range specified above. Moreover, for this crude oil, the density reported is 0.7731 g/cm3 which would equate to an So of 0.1 according to Equation (10). The reported ranges of variation in the section “Precision and Bias” in the ASTM D 7157 [41] for S-value is between 1.29 and 4.23, for Sa it is between 0.4 and 0.85, and for So it is 0.46–1.36, that is in agreement with the range determined by using Equations (10) and (11). Therefore, Equations (10) and (11) could be used for the purposes of the verification of the parameters Sa and So measured by the ASTM D 7157 standard. It is understandable that additional data can improve the accuracy of the predictions of Equations (10) and (11).

3.3. Commercial Crude Distillation Unit Heat Exchanger Fouling

During the first period of processing the opportunity crude oil ITR in the LNB refinery (October–November 2024), a significant reduction in the heat transfer coefficients of the heat exchangers which heat the crude oil coming from tanks before entering the crude desalter in the crude distillation unit-2 (CDU-2) was registered (Figure 10). The processing diagram of the heat exchanger network in CDU-2 is presented in Figure 11. A curious observation shown in Figure 10 was that for the second period of processing the ITR crude oil (December 2024–January 2025), no impairing of the heat transfer coefficients of the heat exchangers of CDU-2 was registered (Figure 10).
Another interesting finding was that the other crude distillation unit (CDU-1) in the LNB refinery did not exhibit any signs of fouling and heat transfer deterioration in the heat exchangers heating the crude oil coming from the tanks before entering in the crude desalter when ITR containing petroleum blend was processed. The initial guess that the heat exchanger fouling in CDU-2 was provoked by the incompatibility of the ITR-containing petroleum blend was not in agreement with the observation for the second period of ITR processing in CDU-2 (Figure 10) and both periods of ITR processing in CDU-1. In order to look for the presence or absence of statistically meaningful relations between the oil compatibility indices, crude blend composition, and heat transfer coefficients of the heat exchangers T-101, T-102, T-109, and T-110 in the CDU-2 for the first period of ITR processing at the LNB refinery, an ICrA assessment was performed. Table 8 and Table 9 present data of the μ- and υ-values from the ICrA evaluation for the investigated variables. It is evident from the data in Table 8 and Table 9 that both the content of ITR crude oil in the processed petroleum blend and the compatibility indices are in dissonance with the heat transfer coefficients, meaning that these variables have no impact on the heat exchanger fouling. The only variable that is in a statistically meaningful negative consonance with the heat transfer coefficients is the content of the light crude oil TEN in the processed petroleum mixture (μ = 0.12; υ = 0.82), implying that the increase in the TEN content in the crude blend is associated by a decrease in the heat exchanger coefficients.
The shell-and-tube heat exchanger with floating head T-101 was shut down for cleaning in November 2024 and as depicted in Figure 12, a layer of solid deposit was found on the floating head. A sample of this deposit along with a sample taken from another deposit laid down on the internal surface of the tubes were analyzed and the results from the analysis are summarized in Table 10.
It is interesting to note from the data in Table 10 that both samples indicate a relatively high content of inorganic material judged by the low values of loss of ignition. The floating head deposit sample contains 53.5 wt.% inorganic material while that from the internal surface of the tubes—23.5 wt.%. The inorganic material of the floating head deposit sample has a very high content of iron (34.4 wt.%), followed by silicon (14.4 wt.%), sulfur (7.5 wt.%), aluminum (5.5 wt.%), and calcium (4.7 wt.%). The inorganic material of the internal surface of the tubes also exhibits the highest content of iron (27.2 wt.%), followed by sulfur (14.8 wt.%), calcium (8.7 wt.%), silicon (6.7 wt.%), chlorine (6.3 wt.%), sodium (6.0 wt.%), barium (2.0 wt.%), and aluminum (1.8 wt.%).
These analyses strongly suggest that the main cause of fouling is the presence of iron sulfide. Fouling by iron sulfide deposition was mentioned as the main reason for fouling in the cold section of the preheat train [65]. Fine FeS, typically 1–20 micron in size, may be formed when iron-containing formation or production water comes in contact with H2S-containing crude. Indeed, after the extraction of the deposits with toluene, a fluffy material remained. Alternatively, larger FeS particles may result from corrosion in pipelines, vessels, and storage tanks.
Fouling can sometimes also be attributed to the deposition of organic material, especially asphaltenes. However, the atomic H/C ratio of the deposits is 1.7 (deposit from the floating head) or 1.6 (deposit from the tubes) which suggests it is a mixture of asphaltenes (typical H/C ratio 1.1, reference [55]) and maltenes. Soxhlet extraction using toluene and heptane shows that the amount of asphaltenes is only 14.3 %w (floating head) or 9.2 %w (in the tubes), indicating that asphaltene deposition is not a major contributor. Moreover, it is our experience that when the amount of inorganics in the deposit is larger than about 5 wt.%, the root cause is inorganic rather than organic. The presence of organic material is simply due to the coating of the inorganic deposits with higher molecular weight hydrocarbons and the fact that some crude oil remains after draining the heat exchangers.
A plausible explanation of the observed fouling of the heat exchangers in CDU-2 with increasing the content of the light crude oil TEN in the crude oil blends containing the opportunity crude ITR could be that the TEN cargo contained filterable solids (mainly FeS). It is also possible that the TEN crude facilitated the transfer of fine FeS from the tanks, e.g., by forming stable emulsions. The fact that CDU-1 was not affected may be due to its different configuration: CDU-1 starts with an Alfa Laval plate heat exchanger whereas CDU-2 starts with a conventional shell and tube heat exchanger.

4. Conclusions

The investigation of crude oil compatibility and its effect on petroleum refining when opportunity crudes are processed is still a pending issue. The exact number of the ratio of solubility blending number to insolubility number ( S B N I N ) that provides the colloidal stability of the oil mixture is still a question of debate. Another aspect of the dispute concerns the denominator of the ratio ( S B N I N ): whether it should be the maximum insolubility number (INmax), which is the highest IN of the oils in the blend, or the blended insolubility number (IBN), which is calculated using the asphaltenes content of each oil in the blend multiplied by the insolubility number of the oil.
The opportunity crude oil ITR, processed in two periods at the LNB refinery, was characterized by the highest insolubility number among the other sixteen crude oils refined together with it. For that reason, any content of ITR in the processed crude blend was associated with a value of S B N I N m a x   ~1.1. The value of this ratio of 1.1 in previous published research suggested a reduction in crude desalter efficiency that was not recorded in this study. Instead, it was found that the S B N I B N ratio correlates with the amperage of crude desalter, reaching its maximum allowable value of 180 A at about 10 wt.% of the opportunity crude oil ITR in the petroleum mixture. The performed ICrA revealed that the content of ITR and the compatibility indices S B N I B N ratio and Sa have a statistically meaningful relation to the crude desalter amperage. The developed correlations in this research suggest that the content of ITR in the crude blend may reach up to 20 wt.% when the crude oil desalter amperage does not go beyond 180 A if the crude blend consists predominantly of intermediate crude oils, while the content of light crude oils is minimized and the ratios S B N I B N and S p S p c r i t c a l are higher than 1.35 and 1.36 respectively, and S-value is higher than 1.44, and Sa does not drop below 0.64. In this study, the S B N I B N ratio was found to better relate oil incompatibility expressed by issues with the amperage of crude desalter than the S B N I N m a x ratio. Correlations were developed relating the density of crude oil with the ASTM D 7157 parameter So and the density of the vacuum residual fraction with the parameter Sa. On their base, it was suggested that the possible range of variation in So is 0.19–0.95 and Sa is 0.5–0.9 for virgin crude oils.
The observed fouling during the processing of opportunity ITR crude oil blended with mostly light crude oils like the TEN crude oil was found by ICrA to be related only to the content of the light crude oil TEN in the petroleum mixture and not to the ITR, or any compatibility indices. A deposit analysis strongly suggests the fouling was due to the deposition of iron sulfide.

Author Contributions

Conceptualization, D.S. and I.S.; methodology, G.G. and V.T.; software, V.B. and K.A.; validation, R.D., A.N. and R.N.; formal analysis, A.V.; investigation, D.Y.; resources, F.v.d.B.; data curation, F.v.d.B.; writing—original draft preparation, D.S., I.S. and F.v.d.B.; writing—review and editing, D.S., I.S. and F.v.d.B.; visualization, V.T.; supervision, K.A.; project administration, G.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Prof. Dr. Asen Zlatarov University—Burgas, Project: Study of the process of inhibiting the precipitation of asphaltenes in petroleum fluids by chemical additives, No NIH-502/2024.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s).

Acknowledgments

We are grateful to the chemical engineers Georgi Stoilov, and Evgeni Ivanov from LUKOIL Neftohim Burgas Process Departmernt for their valuable work related to fouling issue in heat exchangers of CDU-2.

Conflicts of Interest

Authors Dicho Stratiev, Ivelina Shiskova, Rosen Dinkov, Angel Nedelchev, and Georgi Georgiev were employed by LUKOIL Neftohim Burgas. Author Frans van den Berg was employed by Black Oil Solutions. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Kumar, R.; Voolapallia, R.; Upadhyayulab, S. Prediction of crude oil blends compatibility and blend optimization for increasing heavy oil processing. Fuel Process. Technol. 2018, 177, 309–327. [Google Scholar] [CrossRef]
  2. Collins, T.; Barletta, T. Desalting heavy Canadian crudes. Sour Heavy 2012, 1–5. Available online: https://www.digitalrefining.com/article/1000566 (accessed on 8 January 2025).
  3. Stark, J.L.; Nguyen, J.; Kremer, L.N. New method prevents desalter upsets from blending incompatible crudes. Oil Gas J. 2002, 100, 89–91. [Google Scholar]
  4. Sorathia, P.D.; Baldania, A.D. Problems Occurring in De-Salter plant of Crude oil and its solution. JETIR 2017, 4, 64–69. [Google Scholar]
  5. Nasehi, S.; Sarraf, M.J.; Ilkhani, A.; Mohammadmirzaie, M.A.; Fazaelipoor, M.H. Study of Crude Oil Desalting Process in Refinery. J. Biochem. Tech. 2018, 9, 29–33. [Google Scholar]
  6. Khan, M.K.; Riaz, A.; Minhoe, Y.; Kim, J. Removal of naphthenic acids from high acid crude via esterification with methanol. Fuel Process. Technol. 2017, 165, 123–130. [Google Scholar] [CrossRef]
  7. Al-Moubaraki, A.H.; Obot, I.B. Corrosion challenges in petroleum refinery operations: Sources, mechanisms, mitigation, and future outlook. J. Saudi Chem. Soc. 2021, 25, 101370. [Google Scholar] [CrossRef]
  8. Meriem-Benziane, M.; Bou-Saïd, B.; Nasser, B.; Boudissa, I. Numerical study of elbow corrosion in the presence of sodium chloride, calcium chloride, naphthenic acids, and sulfur in crude oil. J. Petrol. Sci. Eng. 2021, 198, 108124. [Google Scholar] [CrossRef]
  9. Patrick, B.N. Understanding Naphthenic Acid Corrosion in Refinery Settings. Ph.D. Thesis, University of California, Berkeley, CA, USA, 2015. [Google Scholar]
  10. Laredo, G.C.; Lopez, C.R.; Alvarez, R.E.E.; Cano, J.L. Naphthenic acids, total acid number and sulfur content profile characterization in Isthmus and Maya crude oils. Fuel 2004, 83, 1689–1695. [Google Scholar] [CrossRef]
  11. Huang, B.S.; Yin, W.F.; Sang, D.H.; Jiang, Z.Y. Synergy effect of naphthenic acid corrosion and sulfur corrosion in crude oil distillation unit. Appl. Surf. Sci. 2012, 259, 664–670. [Google Scholar] [CrossRef]
  12. Flego, C.; Galasso, L.; Montanari, L.; Maria Gennaro, M.E. Evolution of Naphthenic Acids during the Corrosion Process. Energy Fuels 2014, 28, 1701–1708. [Google Scholar] [CrossRef]
  13. Kondyli, A.; Schrader, W. Understanding “Fouling” in Extremely Complex Petroleum Mixtures. ACS Appl. Energy Mater. 2020, 3, 7251–7256. [Google Scholar] [CrossRef]
  14. Asomaning, S.; Watkinson, A.P. Petroleum stability and heteroatom species effects in fouling of heat exchangers by asphaltenes. Heat. Tran. Eng. 2000, 21, 10–16. [Google Scholar] [CrossRef]
  15. Hong, E.; Watkinson, P. Precipitation and fouling in heavy oil–diluent blends. Heat. Transf. Eng. 2009, 30, 786–793. [Google Scholar] [CrossRef]
  16. Guo, L.; Kuang, J.; Liu, S.; Shen, S.; Liang, L. Failure mechanism of a coil type crude oil heater and optimization method. Case Stud. Therm. Eng. 2022, 39, 102398. [Google Scholar] [CrossRef]
  17. Li, Q.; Li, Q.; Wu, J.; Li, X.; Li, H.; Cheng, Y. Wellhead Stability During Development Process of Hydrate Reservoir in the Northern South China Sea: Evolution and Mechanism. Processes 2025, 13, 40. [Google Scholar] [CrossRef]
  18. Li, Q.; Li, Q.; Cao, H.; Wu, J.; Wang, F.; Wang, Y. The Crack Propagation Behaviour of CO2 Fracturing Fluid in Unconventional Low Permeability Reservoirs: Factor Analysis and Mechanism Revelation. Processes 2025, 13, 159. [Google Scholar] [CrossRef]
  19. Zheng, F.; Shi, Q.; Vallverdu, G.; Giusti, P.; Bouyssiere, B. Fractionation and Characterization of Petroleum Asphaltene: Focus on Metalopetroleomics. Processes 2020, 8, 1504. [Google Scholar] [CrossRef]
  20. Speight, J.G. Petroleum Asphaltenes. Part 2. The effect of asphaltenes and resin constituents on recovery and refining processes. Oil Gas. Sci. Technol. Rev. IFP. 2004, 59, 479–488. [Google Scholar] [CrossRef]
  21. Paczuski, M. Modification of Asphaltene Dispersions in Crude Oil. In Physicochemistry of Petroleum Dispersions in Refining Technology; IntechOpen: London, UK. [CrossRef]
  22. Abdulredha, M.M.; Hussain, S.A.; Abdullah, L.C. Overview on petroleum emulsions, formation, influence and demulsification treatment techniques. Arab. J. Chem. 2020, 13, 3403–3428. [Google Scholar] [CrossRef]
  23. Peñaloza, I.M.; Chauhan, G.; de Klerk, A. Desalting Behavior of Bitumen. Energy Fuels 2021, 35, 15618–15627. [Google Scholar] [CrossRef]
  24. Perez, P.L.; Zaragoza, J.N.; Patel, N.K.; Dion, M.A. Impact of Asphaltene Stabilizers on the Elasticity of a Crude Oil–Water Interface and Its Correlation to Demulsification under Desalting Conditions. Energy Fuels 2022, 36, 275–289. [Google Scholar] [CrossRef]
  25. Patil, P.D.; Kozminski, M.; Peterson, J.; Kumar, S. Fouling Diagnosis of Pennsylvania Grade Crude Blended with Opportunity Crude Oils in a Refinery Crude Unit’s Hot Heat Exchanger Train. Ind. Eng. Chem. Res. 2019, 58, 17918–17927. [Google Scholar] [CrossRef]
  26. Zhu, H.; Wang, Q.; Yan, Y.; Xu, Y.; Liu, S.; Zhang, S.; Xu, J.; Yang, C. Effect of Naphthenic Acid and Metal Ions on Emulsification of Heavy Oil. Energy Fuels 2022, 36, 2561–2571. [Google Scholar] [CrossRef]
  27. Alvisi, P.P.; Lins, V.F.C. An overview of naphthenic acid corrosion in a vacuum distillation plant. Eng. Fail. Anal. 2011, 18, 1403–1406. [Google Scholar] [CrossRef]
  28. Rana, B.S.; Cho, D.W.; Cho, K.; Kim, J.-N. Total Acid Number (TAN) reduction of high acidic crude oil by catalytic esterification of naphthenic acids in fixed-bed continuous flow reactor. Fuel 2018, 231, 271–280. [Google Scholar] [CrossRef]
  29. Ramirez-Corredores, M.M. The Science and Technology of Unconventional Oils Finding Refining Opportunities; Elsevier: Amsterdam, The Netherlands, 2017; pp. 164–165. [Google Scholar]
  30. Rogel, E.; Hench, K.; Miao, T.; Lee, E.; Dickakian, G. Evaluation of the compatibility of crude oil blends and its impact on fouling. Energy Fuels 2018, 32, 9233–9242. [Google Scholar] [CrossRef]
  31. Bambinek, K.; Przyjazny, A.; Boczkaj, G. Compatibility of Crude Oil Blends Processing Issues Related to Asphaltene Precipitation, Methods of Instability Prediction-A Review. Ind. Eng. Chem. Res. 2023, 62, 2–15. [Google Scholar] [CrossRef]
  32. Van den Berg, F.G.A.; Kapusta, S.D.; Ooms, A.C.; Smith, A.J. Fouling and Compatibility of Crudes as Basis for a New Crude Selection Strategy. Pet. Sci. Technol. 2003, 21, 557–568. [Google Scholar] [CrossRef]
  33. Wiehe, I.A. Fouling of Nearly Incompatible Oils. Energy Fuels 2001, 15, 1057–1058. [Google Scholar] [CrossRef]
  34. Wiehe, I.A. Asphaltene Solubility and Fluid Compatibility. Energy Fuels 2012, 26, 4004–4016. [Google Scholar] [CrossRef]
  35. Schermer, W.E.M.; Melein, P.M.J.; van den Berg, F.G.A. Simple Techniques for Evaluation of Crude Oil Compatibility. Pet. Sci. Technol 2004, 22, 1045–1054. [Google Scholar] [CrossRef]
  36. Wiehe, I.; Kennedy, R.J. The Oil Compatibility Model and Crude Oil Incompatibility. Energy Fuels 2000, 14, 56–59. [Google Scholar] [CrossRef]
  37. Wiehe, I.A.; Kennedy, R.J. Application of the Oil Compatibility Model to Refinery Streams. Energy Fuels 2000, 14, 60–63. [Google Scholar] [CrossRef]
  38. Wiehe, I.A. Self-Incompatible Crude Oils and Converted Petroleum Resids. J. Disper. Sci. Technol. 2004, 3, 333–339. [Google Scholar] [CrossRef]
  39. Wiehe, I.A. Process Chemistry of Petroleum Macromolecules; Taylor & Francis Group, CRC Press: Boca Raton, FL, USA, 2008; pp. 223–224. [Google Scholar]
  40. Vermeire, M.; Heyberger, B. Study to Evaluate Test Methods to Assess the Stability and Compatibility of Marine Fuels in View of the IMO MARPOL Annex VI Regulation 14.1.3 for 2020 Sulphur Requirements. Report no.11/19, Concawe 2019. Available online: https://www.concawe.eu/wp-content/uploads/Rpt_19-11.pdf (accessed on 22 January 2025).
  41. ASTM D7157–18; Standard Test Method for Determination of Intrinsic Stability of Asphaltene-Containing Residues, Heavy Fuel Oils, and Crude Oils (n-Heptane Phase Separation; Optical Detection). ASTM International: West Conshohocken, PA, USA, 2022.
  42. Nedelchev, A.; Stratiev, D.; Stoilov, G.; Dinkov, R.; Lepidis, K.; Sharpe, R.; Russell, C.A.; Petkova, N.; Petkov, P. Visbreaker performance improvement by optimisation of process conditions and application of chemical additive treatment program. Oil Gas. Eur. Mag. 2013, 3, 147–153. [Google Scholar]
  43. ASTM D7112-19; Standard Test Method for Determining Stability and Compatibility of Heavy Fuel Oils and Crude Oils by Heavy Fuel Oil Stability Analyzer (Optical Detection). ASTM International: West Conshohocken, PA, USA, 2024.
  44. Shishkova, I.; Stratiev, D.; Sotirov, S. Petroleum Chemistry and Processing Investigated by the Use of Intercriteria Analysis; Publishing House of Bulgarian Academy of Sciences: Sofia, Bulgaria, 2024; pp. 124–141. [Google Scholar]
  45. Nemana, S.; Kimbrell, M.R.; Zaluzec, E. Predictive crude oil compatibility model. US patent 7,618,822 B2, 17 November 2009. [Google Scholar]
  46. ASTM D7060−12; (Reapproved 2014) Standard Test Method for Determination of the Maximum Flocculation Ratio and Peptizing Power in Residual and Heavy Fuel Oils (Optical Detection Method). ASTM International: West Conshohocken, PA, USA, 2014.
  47. Alonso, F.; Castillo, J.A.; Ancheyta, J.; Torres-Mancera, P. Evaluation of the Effect of Addition Order on the Compatibility of Binary Crude Oil Blending. Energy Fuels 2024, 38, 23358–23366. [Google Scholar] [CrossRef]
  48. Guzmán, R.; Rodríguez, S.; Torres-Mancera, P.; Ancheyta, J. 550 Evaluation of asphaltene stability of a wide range of Mexican crude oils. Energy Fuels 2021, 35, 408–418. [Google Scholar] [CrossRef]
  49. Sharma, E.; Shown, B.; Sulakhe, S.; Naik, V.M.; Thaokar, R.M.; Juvekar, V.A. Forecasting the Problem of Excessive Oil Entrainment in a Desalter Using Spinning Drop Method. ACS Omega 2024, 9, 12768–12778. [Google Scholar] [CrossRef]
  50. Atanassov, K.; Atanassova, V.; Gluhchev, G. Intercriteria analysis: Ideas and problems. Notes Intuitionistic Fuzzy Sets 2015, 21, 81–88. [Google Scholar]
  51. Shiskova, I.; Stratiev, D.; Tavlieva, M.; Nedelchev, A.; Dinkov, R.; Kolev, I.; van den Berg, F.; Ribagin, S.; Sotirov, S.; Nikolova, R.; et al. Application of Intercriteria and Regression Analyses and Artificial Neural Network to Investigate the Relation of Crude Oil Assay Data to Oil Compatibility. Processes 2024, 12, 780. [Google Scholar] [CrossRef]
  52. van den Berg, F.G. History and Review of Dual Solvent Titration Methods. Energy Fuels 2022, 36, 8639–8648. [Google Scholar] [CrossRef]
  53. ASTM D 2892–20; Standard Test Method for Distillation of Crude Petroleum (15-Theoretical Plate Column). ASTM International: West Conshohocken, PA, USA, 2023.
  54. ASTM D5236–18a; Standard Test Method for Distillation of Heavy Hydrocarbon Mixtures (Vacuum Potstill Method). ASTM International: West Conshohocken, PA, USA, 2023.
  55. Stratiev, D.; Nikolova, R.; Veli, A.; Shishkova, I.; Toteva, V.; Georgiev, G. Mitigation of Asphaltene Deposit Formation via Chemical Additives: A Review. Processes 2025, 13, 141. [Google Scholar] [CrossRef]
  56. Atanassov, K.; Mavrov, D.; Atanassova, V. Intercriteria decision making: A new approach for multicriteria decision making, based on index matrices and intuitionistic fuzzy sets. Issues Intuitionistic Fuzzy Sets Gen. Nets 2014, 11, 1–8. [Google Scholar]
  57. Chorukova, E.; Marinov, P.; Umlenski, I. Survey on Theory and Applications of InterCriteria Analysis Approach. In Research in Computer Science in the Bulgarian Academy of Sciences; Atanassov, K.T., Ed.; Studies in Computational Intelligence; Springer: Cham, Switzerland, 2021; Volume 934. [Google Scholar] [CrossRef]
  58. Mavrov, D. Software for InterCriteria Analysis: Implementation of the Main Algorithm. Notes Intuitionistic Fuzzy Sets 2015, 21, 77–86. [Google Scholar]
  59. Mavrov, D. Software for Intercriteria Analysis: Working with the Results. Annu. Inform. Sect. Union Sci. Bulg. 2015, 8, 37–44. [Google Scholar]
  60. Ikonomov, N.; Vassilev, P.; Roeva, O. ICrAData—Software for InterCriteria Analysis. Int. J. Bioautomation 2018, 22, 1–10. [Google Scholar] [CrossRef]
  61. Ancheyta, J. Relative compatibility index for evaluation of the compatibility of crude oil blends. Geoenergy Sci. Eng. 2023, 230, 212246. [Google Scholar] [CrossRef]
  62. Guzmán, R.; Ancheyta, J.; Trejo, F.; Rodríguez, S. Methods for determining asphaltene stability in crude oils. Fuel 2017, 188, 530–548. [Google Scholar] [CrossRef]
  63. Moura, L.G.M.; Santos, M.F.P.; Zilio, E.L.; Rolemberg, M.P.; Ramos, A.C.S. Evaluation of indices and of models applied to the prediction of the stability of crude oils. J. Pet. Sci. Eng. 2010, 74, 77–87. [Google Scholar] [CrossRef]
  64. Correra, S.; Merlini, M.; Di Lullo, A.; Merino-Garcia, D. Estimation of the solvent power of crude oil from density and viscosity measurements. Ind. Eng. Chem. Res. 2005, 44, 9307–9315. [Google Scholar] [CrossRef]
  65. Lemke, H. Fouling in refinery equipment—An overview. In Proceedings of the AIChE Spring Meeting, Houston, TX, USA, 14–18 March 1999. [Google Scholar]
Figure 1. Relationship between S-value and p-value.
Figure 1. Relationship between S-value and p-value.
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Figure 2. Dependence of Sa on vacuum residue Conradson carbon content.
Figure 2. Dependence of Sa on vacuum residue Conradson carbon content.
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Figure 3. Experimental methodology.
Figure 3. Experimental methodology.
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Figure 4. Composition of the crude blends processed in the periods October–November 2024 (a) and December 2024–January 2025 (b) when the opportunity crude oil ITR was processed.
Figure 4. Composition of the crude blends processed in the periods October–November 2024 (a) and December 2024–January 2025 (b) when the opportunity crude oil ITR was processed.
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Figure 5. Crude desalter amperage variation when the opportunity crude oil ITR was processed in the LNB refinery for the two investigated periods of time October–November 2024 and December 2024–January 2025.
Figure 5. Crude desalter amperage variation when the opportunity crude oil ITR was processed in the LNB refinery for the two investigated periods of time October–November 2024 and December 2024–January 2025.
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Figure 6. Changing the desalting amperage as the opportunity crude oil ITR content of the processed oil blend varies.
Figure 6. Changing the desalting amperage as the opportunity crude oil ITR content of the processed oil blend varies.
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Figure 7. Correlation of crude desalter amperage with the S B N b l e n d I B N ratio (a) and asphaltene peptizability (b).
Figure 7. Correlation of crude desalter amperage with the S B N b l e n d I B N ratio (a) and asphaltene peptizability (b).
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Figure 8. Relationship of ASTM D 7157 So-value to the δ c o solubility parameter.
Figure 8. Relationship of ASTM D 7157 So-value to the δ c o solubility parameter.
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Figure 9. Dependence of ASTM D 7157 Sa-value on vacuum residue fraction density.
Figure 9. Dependence of ASTM D 7157 Sa-value on vacuum residue fraction density.
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Figure 10. Altering of the heat transfer coefficients of the crude oil heat exchangers during the processing of the opportunity crude oil ITR in the LNB refinery for the periods of time October–November 2024 and December 2024–January 2025.
Figure 10. Altering of the heat transfer coefficients of the crude oil heat exchangers during the processing of the opportunity crude oil ITR in the LNB refinery for the periods of time October–November 2024 and December 2024–January 2025.
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Figure 11. Heat exchanger network in CDU-2 employed to heat the crude oil.
Figure 11. Heat exchanger network in CDU-2 employed to heat the crude oil.
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Figure 12. Appearance of the floating head of the shell-and-tube heat exchanger with floating head (T-101).
Figure 12. Appearance of the floating head of the shell-and-tube heat exchanger with floating head (T-101).
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Table 1. Physical and chemical properties of the 17 crude oils processed in the LNB refinery during the study.
Table 1. Physical and chemical properties of the 17 crude oils processed in the LNB refinery during the study.
Processed Crude OilsTartarugaJohan SverdrupKEBCOCPCHelmBasra MediumBasra HeavyAzeri LightTENITRArab LightArab HeavyEs SiderRhemouraUnity GoldGulf of SuezEl Bouri
OriginBrazilNorwayKazakhstanKazakhstanNetherlandsIraqIraqAzerbaijanGhana Saudi ArabiaSaudi ArabiaLybiaTunisiaGuyanaEgyptLybia
Density at 15 °C, g/m30.8930.88490.87180.8010.9350.88310.90820.8290.83080.94530.8580.8910.8400.8480.8550.8730.888
Sulfur, wt.%0.730.821.760.561.713.213.940.150.3415.751.92.970.40.570.451.531.71
Chloride, mg/kg262.5153.73337.5455.431.196.828.630.43210.52485.941.938.565.126.6
TAN, mg KOH/g0.150.30.130.060.810.20.260.320.030.160.060.280.090.220.220.0530.06
Water content, vol.%0.4460.4160.1660.040.6830.1590.30.0410.040.1270.0340.0620.0840.0250.0770.0610.062
Pour point, °C−360−18−15−30−36−36−36−24−30−36−3612−18−390
TBP distillation fraction yields. wt.%
IBP *-110 °C 7.67.68.118.02.28.57.213.613.77.39.67.07.411.110.88.36.4
110–180 °C8.07.89.718.95.59.88.815.515.38.311.79.113.812.812.010.49.3
180–240°C7.58.39.013.26.48.58.012.511.26.910.18.010.410.69.78.88.6
240–360°C18.923.221.923.420.618.617.925.222.415.321.319.022.023.222.220.820.7
IBP *-360°C42.046.948.873.634.645.441.866.862.637.852.743.053.757.654.748.245.0
360–540°C28.627.626.517.628.824.624.020.721.522.124.624.626.423.825.725.328.8
>540 °C28.524.623.87.835.629.033.211.515.039.121.731.316.817.618.625.525.2
Na, mg/kg54.91.31.11.5151.415.67.48.06.53.95.26.011.92.46.711
Ni, mg/kg20.820.68.34.414.518.219.318.512.031.911.715.614.914.210.823.6
V, mg/kg22.515.166.81.6566.873.575.17.26.529.711.747.96.912.818.250
Fe, mg/kg52.017.97.66.04.045.94.87.54.52.310.04.14.82.74.212.3
As, µg/kg68.09814818.848.278.541.321.516.970.361.7114.686.94.670.351.4
Ca, mg/kg12.27.22.31.620.24.74.16.65.33.94.43.86.342.237.4
C7-asphaltenes, wt.%4.34.23.40.510.26.39.70.70.216.24.73.31.96.22.06.28.2
* Note: IBP = initial boiling point; TAN = total acid number.
Table 2. Physical and chemical properties of the vacuum residue fraction distilled from the 17 crude oils processed in the LNB refinery during the study.
Table 2. Physical and chemical properties of the vacuum residue fraction distilled from the 17 crude oils processed in the LNB refinery during the study.
Vacuum ResiduesDensity at 15 °C, g/m3Concarbon Content, wt.%Sulfur, wt.%Nitrogen, wt.%Saturates, wt.%Aromatics, wt.%Resins, wt.%C7-Asphaltenes, wt.%C5-Asphaltenes, wt.%
Tartaruga1.008116.31.3540.92216.261.48.114.322.4
Johan Sverdrup1.0225201.7741.92212.759.911.016.427.4
KEBCO0.99717.530.519.361.84.514.418.9
CPC0.94778.381.3610.31140.648.47.63.411
Helm1.05423.253.0130.3447.351.414.327.041.3
Basra Medium1.061527.056.50.3176.363.57.922.330.2
Basra Heavy1.07128.97.10.4155.258.010.026.936.9
Azeri Light0.9679.50.50.44430.664.04.01.45.4
TEN0.980611.61.0640.62124.970.13.81.25.0
ITR1.1234.39.30.54081.351.910.036.846.8
Arab Light1.02918.74.90.2811.469.17.112.319.5
Arab Heavy1.0423.65.80.4379.457.711.621.332.9
Es Sider0.99115.6001.050.73121.359.78.810.219.0
Rhemoura1.04123.7001.80.59.259.58.123.231.3
Unity Gold0.99414.71.3180.5220.364.14.810.915.7
Gulf of Suez1.02419.6713.3580.3812.555.59.922.132.0
El Bouri1.05025.5003.30.537.864.99.817.527.3
Table 3. Scope of fluctuation in the contents of the individual crude oils in the processed petroleum mixture.
Table 3. Scope of fluctuation in the contents of the individual crude oils in the processed petroleum mixture.
Content of Crudes in Petroleum MixtureMinMax
Tartaruga0.01.1
Johan Sverdrup0.832.8
KEBCO0.720.2
CPC2.929.7
Helm0.011.1
Basrah Medium0.029.1
Basrah Heavy0.023.0
Azeri Light1.014.1
TEN0.340.6
ITR0.010.7
Arab Light0.03.7
Arab Heavy3.220.4
Es Sider0.016.9
Rhemoura0.010.5
Unity Gold0.00.9
Gulf of Suez0.00.5
El Bouri0.014.7
Table 4. Compatibility indices of the seventeen crude oils processed in the LNB refinery during the study determined by using the n-heptane dilution test and Equation (4).
Table 4. Compatibility indices of the seventeen crude oils processed in the LNB refinery during the study determined by using the n-heptane dilution test and Equation (4).
Processed Crude OilsN-Heptane, wt.% in Crude Blend at the Onset of Asphaltene PrecipitationSBNINSBN/INSaSpSp critical
Tartaruga4094591.600.76229.017.4
Johan Sverdrup6192382.390.72431.512.3
KEBCO5086461.870.74928.914.4
CPCNPDNPDNPDNPD0.84521.4NPD
Helm55111522.140.68943.021.5
Basrah Medium4590521.720.64930.216.6
Basrah Heavy50102541.910.63035.417.7
Azeri LightNPDNPDNPDNPD0.83327.5NPD
TENNPDNPDNPDNPD0.81127.3NPD
ITR35113751.510.57343.928.5
Arab Light4080511.570.73725.215.1
Arab Heavy5594452.090.68529.813.4
Es Sider4071461.560.76922.213.3
Rhemoura3083601.370.68431.422.0
Unity Gold5079421.860.77928.814.4
Gulf of Suez4086541.580.72627.316.4
El Bouri3094681.380.66530.821.6
Note: NPD = not possible to determine due to the absence of precipitation of asphaltenes with n-heptane.
Table 5. Compatibility indices of petroleum mixtures for the investigated space of time.
Table 5. Compatibility indices of petroleum mixtures for the investigated space of time.
NoDateSBNIBNSBN/IBNSBN/IN maxSaNoDateSBNIBNSBN/IBNSBN/IN maxSa
128.10.202479.2948.11.651.470.6782117.11.202478.7046.81.681.050.723
229.10.202479.1251.21.541.050.6642227.12.202484.2046.61.811.590.714
330.10.202480.0054.01.481.070.6572328.12.202484.4048.01.761.130.709
431.10.202480.0055.21.451.070.6542429.12.202483.9752.91.591.120.688
51.11.202479.1455.21.431.060.6542530.12.202483.9055.11.521.120.679
62.11.202479.4356.91.401.060.6442631.12.202484.0657.21.471.120.669
73.11.202479.9257.71.391.070.640271.1.202583.5057.51.451.110.666
84.11.202478.3757.41.371.040.642282.1.202583.8056.81.481.120.668
95.11.202478.0557.81.351.040.641293.1.202585.0955.41.541.130.673
106.11.202478.9558.51.351.050.640304.1.202585.5954.71.561.140.676
117.11.202478.0058.81.331.040.642315.1.202586.4553.81.611.150.681
128.11.202479.0758.21.361.050.647326.1.202586.7653.21.631.160.684
139.11.202479.2856.01.421.060.660337.1.202587.4852.31.671.170.689
1410.11.202479.8954.61.461.070.671348.1.202588.6652.31.701.180.691
1511.11.202479.8752.11.531.060.688359.1.202584.8351.71.641.130.697
1612.11.202480.2953.11.511.070.6833610.1.202584.9151.71.641.130.699
1713.11.202479.7649.81.601.060.6983711.1.202585.2152.11.641.140.699
1814.11.202478.9248.91.611.050.7033812.1.202585.6553.01.621.140.699
1915.11.202479.2548.21.641.060.7083913.1.202585.5549.61.731.140.707
2016.11.202478.8147.01.681.050.7234014.1.202585.8049.41.741.140.707
Table 6. μ-values from the ICrA evaluation of the data for the crude blend composition compatibility indices SBN, IBN, Sa, and crude desalter amperage for the two opportunity crude oil ITR processing periods at the LNB refinery.
Table 6. μ-values from the ICrA evaluation of the data for the crude blend composition compatibility indices SBN, IBN, Sa, and crude desalter amperage for the two opportunity crude oil ITR processing periods at the LNB refinery.
μKEBCOSver-DrupCPCBasra MArab HBasra HAzeri LTENITRHELMGOSMUnity GoldEs SiderArab LTarta-RugaRhe-MouraBouriSBNIBNSBN/IBNSaAmpe-Rage
KEBCO1.000.490.530.530.440.530.460.420.330.370.110.110.330.240.110.270.320.510.380.600.590.38
Sverdrup0.491.000.260.570.350.190.540.270.360.460.120.240.540.280.120.500.240.730.270.770.770.23
CPC0.530.261.000.300.480.770.330.630.450.360.130.200.170.200.130.130.060.160.520.340.350.63
Basra M0.530.570.301.000.460.200.710.120.410.270.130.350.750.400.130.690.380.670.350.630.600.31
Arab H0.440.350.480.461.000.450.690.310.700.030.020.160.440.110.020.450.120.550.680.360.270.68
Basra H0.530.190.770.200.451.000.250.720.400.370.240.150.030.220.240.010.130.180.470.260.280.56
Azeri L0.460.540.330.710.690.251.000.150.610.150.020.250.690.230.020.700.220.700.550.520.460.51
TEN0.420.270.630.120.310.720.151.000.450.470.210.150.060.180.210.050.120.150.510.260.320.56
ITR0.330.360.450.410.700.400.610.451.000.140.020.180.450.110.020.460.080.480.880.210.180.80
HELM0.370.460.360.270.030.370.150.470.141.000.510.340.240.480.510.200.540.270.140.420.500.15
GOSM0.110.120.130.130.020.240.020.210.020.511.000.740.260.721.000.210.550.030.010.130.160.02
Unity Gold0.110.240.200.350.160.150.250.150.180.340.741.000.520.770.740.460.350.190.160.260.290.14
Es Sider0.330.540.170.750.440.030.690.060.450.240.260.521.000.500.260.930.430.580.380.490.460.32
Arab L0.240.280.200.400.110.220.230.180.110.480.720.770.501.000.720.440.530.240.110.320.360.09
Tartaruga0.110.120.130.130.020.240.020.210.020.511.000.740.260.721.000.210.550.030.010.130.160.02
Rhemoura0.270.500.130.690.450.010.700.050.460.200.210.460.930.440.211.000.480.570.390.430.400.33
Bouri0.320.240.060.380.120.130.220.120.080.540.550.350.430.530.550.481.000.300.090.280.290.04
SBN0.510.730.160.670.550.180.700.150.480.270.030.190.580.240.030.570.301.000.410.690.650.32
IBN0.380.270.520.350.680.470.550.510.880.140.010.160.380.110.010.390.090.411.000.120.110.85
SBN/IBN0.600.770.340.630.360.260.520.260.210.420.130.260.490.320.130.430.280.690.121.000.870.10
Sa0.590.770.350.600.270.280.460.320.180.500.160.290.460.360.160.400.290.650.110.871.000.07
Amperage0.380.230.630.310.680.560.510.560.800.150.020.140.320.090.020.330.040.320.850.100.071.00
Table 7. υ-values from the ICrA evaluation of the data for the crude blend composition compatibility indices SBN, IBN, Sa, and crude desalter amperage for the two opportunity crude oil ITR processing periods at the LNB refinery.
Table 7. υ-values from the ICrA evaluation of the data for the crude blend composition compatibility indices SBN, IBN, Sa, and crude desalter amperage for the two opportunity crude oil ITR processing periods at the LNB refinery.
υKEBCOSver-DrupCPCBasra MArab HBasra HAzeri LTENITRHELMGOSMUnity GoldEs SiderArab LTarta-RugaRhe-MouraBouriSBNIBNSBN/IBNSaAmpe-Rage
KEBCO0.000.480.450.360.540.310.510.460.650.260.050.290.440.190.050.440.010.470.600.370.390.60
Sverdrup0.480.000.710.320.620.650.420.600.610.180.050.180.240.160.050.230.110.240.700.210.200.74
CPC0.450.710.000.600.490.080.650.260.520.260.030.210.600.230.030.580.260.820.460.650.630.35
Basra M0.360.320.600.000.430.570.190.680.480.320.080.110.100.090.080.110.040.230.540.260.290.59
Arab H0.540.620.490.430.000.390.290.560.280.600.140.240.320.320.140.260.220.420.290.620.710.30
Basra H0.310.650.080.570.390.000.590.200.450.280.060.230.600.240.060.560.210.660.380.580.570.29
Azeri L0.510.420.650.190.290.590.000.720.360.470.150.170.090.200.150.030.120.270.420.450.510.47
TEN0.460.600.260.680.560.200.720.000.430.170.060.230.600.240.060.570.220.720.370.620.560.32
ITR0.650.610.520.480.280.450.360.430.000.490.140.230.310.320.140.250.250.500.100.770.800.18
HELM0.260.180.260.320.600.280.470.170.490.000.010.120.330.100.010.320.100.350.490.200.130.48
GOSM0.050.050.030.080.140.060.150.060.140.010.000.010.070.010.000.070.030.130.150.020.000.14
Unity Gold0.290.180.210.110.240.230.170.230.230.120.010.000.070.020.010.080.090.220.250.150.120.26
Es Sider0.440.240.600.100.320.600.090.600.310.330.070.070.000.100.070.010.130.200.380.270.310.44
Arab L0.190.160.230.090.320.240.200.240.320.100.010.020.100.000.010.120.050.190.310.110.060.33
Tartaruga0.050.050.030.080.140.060.150.060.140.010.000.010.070.010.000.070.030.130.150.020.000.14
Rhemoura0.440.230.580.110.260.560.030.570.250.320.070.080.010.120.070.000.130.150.320.280.320.38
Bouri0.010.110.260.040.220.210.120.220.250.100.030.090.130.050.030.130.000.040.240.050.050.29
SBN0.470.240.820.230.420.660.270.720.500.350.130.220.200.190.130.150.040.000.570.290.330.65
IBN0.600.700.460.540.290.380.420.370.100.490.150.250.380.310.150.320.240.570.000.870.870.13
SBN/IBN0.370.210.650.260.620.580.450.620.770.200.020.150.270.110.020.280.050.290.870.000.110.88
Amperage0.600.740.350.590.300.290.470.320.180.480.140.260.440.330.140.380.290.650.130.880.910.00
Table 8. μ-values from the ICrA evaluation of the data for the crude blend composition; compatibility indices SBN, IBN, and Sa; and heat transfer coefficients of the heat exchangers T-101, T-102, T-109, and T-110 for the first period of ITR processing at the LNB refinery.
Table 8. μ-values from the ICrA evaluation of the data for the crude blend composition; compatibility indices SBN, IBN, and Sa; and heat transfer coefficients of the heat exchangers T-101, T-102, T-109, and T-110 for the first period of ITR processing at the LNB refinery.
μKEBCOSver-DrupCPCBasra MArab HBasra HAzeri LTENITRHELMSBNIBNSBN/IBNSaAmpe-RageK-Heat T-101K-Heat T-102K-Heat T-109K-Heat T-110
KEBCO1.000.380.730.700.740.790.770.260.440.030.460.450.550.500.510.800.800.710.77
Sverdrup0.381.000.400.400.330.320.360.450.270.500.710.230.720.780.240.370.340.360.33
CPC0.730.401.000.780.890.860.900.080.430.030.490.430.530.380.550.870.880.840.88
Basra M0.700.400.781.000.790.770.750.180.470.050.530.460.490.390.570.770.780.710.79
Arab H0.740.330.890.791.000.810.820.170.530.020.510.530.460.320.580.810.820.840.84
Basra H0.790.320.860.770.811.000.880.150.410.010.510.400.590.420.480.940.950.820.89
Azeri L0.770.360.900.750.820.881.000.160.380.030.460.390.570.460.530.900.910.800.87
TEN0.260.450.080.180.170.150.161.000.610.350.380.630.340.470.530.120.120.200.08
ITR0.440.270.430.470.530.410.380.611.000.120.320.940.060.140.820.360.380.510.42
HELM0.030.500.030.050.020.010.030.350.121.000.360.110.350.460.060.020.020.030.07
SBN0.460.710.490.530.510.510.460.380.320.361.000.280.720.660.280.460.460.460.49
IN0.450.230.430.460.530.400.390.630.940.110.281.000.020.130.840.350.370.510.42
SBN/IBN0.550.720.530.490.460.590.570.340.060.350.720.021.000.820.130.610.600.470.52
Sa0.500.780.380.390.320.420.460.470.140.460.660.130.821.000.150.450.450.340.38
Amperage0.510.240.550.570.580.480.530.530.820.060.280.840.130.151.000.470.470.620.50
K-heat T-1010.800.370.870.770.810.940.900.120.360.020.460.350.610.450.471.000.970.830.87
K-heat T-1020.800.340.880.780.820.950.910.120.380.020.460.370.600.450.470.971.000.840.89
K-heat T-1090.710.360.840.710.840.820.800.200.510.030.460.510.470.340.620.830.841.000.80
K-heat T-1100.770.330.880.790.840.890.870.080.420.070.490.420.520.380.500.870.890.801.00
Table 9. υ-values from the ICrA evaluation of the data for the crude blend composition; compatibility indices SBN, IBN, and Sa; and heat transfer coefficients of the heat exchangers T-101, T-102, T-109, and T-110 for the first period of ITR processing at the LNB refinery.
Table 9. υ-values from the ICrA evaluation of the data for the crude blend composition; compatibility indices SBN, IBN, and Sa; and heat transfer coefficients of the heat exchangers T-101, T-102, T-109, and T-110 for the first period of ITR processing at the LNB refinery.
νKEBCOSver-DrupCPCBasra MArab HBasra HAzeri LTENITRHELMSBNIBNSBN/IBNSaAmpe-RageK-Heat T-101K-Heat T-102K-Heat T-109K-Heat T-110
KEBCO0.000.550.230.240.230.190.200.700.530.420.500.530.420.440.470.160.160.270.16
Sverdrup0.550.000.540.500.610.620.580.470.660.010.210.710.230.140.690.580.590.570.55
CPC0.230.540.000.170.080.120.070.880.530.420.470.550.450.560.420.090.080.130.04
Basra M0.240.500.170.000.170.190.190.750.470.380.410.500.460.540.380.170.170.240.11
Arab H0.230.610.080.170.000.180.160.800.440.440.460.460.530.650.400.160.140.140.09
Basra H0.190.620.120.190.180.000.100.820.570.440.470.600.400.530.510.030.030.170.05
Azeri L0.200.580.070.190.160.100.000.820.590.420.520.590.410.480.450.070.070.170.06
TEN0.700.470.880.750.800.820.820.000.350.070.580.340.620.460.440.820.820.770.83
ITR0.530.660.530.470.440.570.590.350.000.340.640.040.920.820.160.600.590.470.53
HELM0.420.010.420.380.440.440.420.070.340.000.080.340.110.030.400.440.440.420.44
SBN0.500.210.470.410.460.470.520.580.640.080.000.700.250.280.680.490.490.510.44
IN0.530.710.550.500.460.600.590.340.040.340.700.000.970.820.150.620.610.480.53
SBN/IBN0.420.230.450.460.530.400.410.620.920.110.250.970.000.130.850.360.370.510.42
Sa0.440.140.560.540.650.530.480.460.820.030.280.820.130.000.800.480.500.610.53
Amperage0.470.690.420.380.400.510.450.440.160.400.680.150.850.800.000.490.490.360.43
K-heat T-1010.160.580.090.170.160.030.070.820.600.440.490.620.360.480.490.000.000.130.05
K-heat T-1020.160.590.080.170.140.030.070.820.590.440.490.610.370.500.490.000.000.120.04
K-heat T-1090.270.570.130.240.140.170.170.770.470.420.510.480.510.610.360.130.120.000.13
K-heat T-1100.160.550.040.110.090.050.060.830.530.440.440.530.420.530.430.050.040.130.00
Table 10. Analysis results of the samples of deposits taken from the fouled T-101 heat exchanger.
Table 10. Analysis results of the samples of deposits taken from the fouled T-101 heat exchanger.
CharacteristicsDeposit from the Floating Head of T-101, CDU-2, 13.11.2024—Sample Before Ignition of OrganicsDeposit from the Floating Head of T-101, CDU-2, 13.11.2024—After Ignition of Organics at 650 °CDeposit Taken from the Internal Tubes of T-101, CDU-2, 15.11.2024—Before Ignition of OrganicsDeposit Taken from the Internal Tubes of T-101, CDU-2, 15.11.2024—After Ignition at 650 °C
Loss on ignition at 650 °C (3 h), %46.5 76.5
Soluble in toluene, %42.9 72.8
Soluble in n-heptane, %28.6 63.6
Element composition 42
C, %22.3 52.0
H, %3.1 6.9
N, %0.2 0.2
H/C atomic ratio1.7 1.6
Fe, %19.734.411.927.2
S, %14.27.512.714.8
Ca, %3.24.73.78.7
Si, %2.314.40.96.7
Cl, %1.60.17.06.3
Al, %0.65.50.21.8
La, %0.50.80.10.2
Ba, %0.50.70.82.0
Zn, %0.30.50.30.5
K, %0.30.60.30.7
V, %0.20.60.20.5
Ti, %0.20.40.10.3
Mo, %0.20.10.20.1
Mn, %0.10.20.10.2
Cr, %0.10.20.00.1
Cu, %0.10.20.10.2
Ni, %0.10.20.10.2
Pb, %0.10.10.50.4
Na, %0.11.10.26.0
Sr, %0.10.10.10.3
Mg, %0.10.50.11.1
P, %0.00.10.00.2
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Stratiev, D.; Shishkova, I.; Georgiev, G.; Dinkov, R.; Nedelchev, A.; Nikolova, R.; Veli, A.; Bureva, V.; Atanassov, K.; Berg, F.v.d.; et al. The Incompatibility Pitfall in Refining Opportunity Crude Oils. Processes 2025, 13, 593. https://doi.org/10.3390/pr13020593

AMA Style

Stratiev D, Shishkova I, Georgiev G, Dinkov R, Nedelchev A, Nikolova R, Veli A, Bureva V, Atanassov K, Berg Fvd, et al. The Incompatibility Pitfall in Refining Opportunity Crude Oils. Processes. 2025; 13(2):593. https://doi.org/10.3390/pr13020593

Chicago/Turabian Style

Stratiev, Dicho, Ivelina Shishkova, Georgi Georgiev, Rosen Dinkov, Angel Nedelchev, Radoslava Nikolova, Anife Veli, Veselina Bureva, Krassimir Atanassov, Frans van den Berg, and et al. 2025. "The Incompatibility Pitfall in Refining Opportunity Crude Oils" Processes 13, no. 2: 593. https://doi.org/10.3390/pr13020593

APA Style

Stratiev, D., Shishkova, I., Georgiev, G., Dinkov, R., Nedelchev, A., Nikolova, R., Veli, A., Bureva, V., Atanassov, K., Berg, F. v. d., Yordanov, D., & Toteva, V. (2025). The Incompatibility Pitfall in Refining Opportunity Crude Oils. Processes, 13(2), 593. https://doi.org/10.3390/pr13020593

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