PTQ Q2 2025 Issue

MFCCT predictions based on the SBN and IN data for source oils

Volume %

Source crude

SBN

Blend 7

Blend 8

Blend 9

Blend 10

Blend 11

Blend 12

Crude 9 Crude 10 Crude 11 Crude 12 Crude 13 Crude 14 Crude 15

63 48 71 73 50 81 30

31 26 35 32 35 47

53 47

52.9

17 83

0.1

SBN mix

56 31

56 47

54 35

56 47

73 47

51 32

Refinery client

IN max

Compatible

Assessment Onset (mL/g)

1.01 0.91

0.62 0.87

0.74 0.77

1.02 0.95

1.00 0.73

BCI

KBC (MFCCT)

Low risk Compatible crude proportions

Assessment

Table 3

reinforcing its reliability and accuracy to prepare the feed crude slate. This validation highlighted MFCCT’s ability to replicate and enhance traditional blend evaluations. Case study 2 The second case study is based on data from another refiner who provided full crude assays for seven source oils, including Wiehe’s numbers (SBN and IN) as the onset data. Both SBN and IN are dimensionless values, and they are derived from Wiehe’s proprietary titration methods con- ducted at 60°C. Specifically, SBN is determined from the heptane dilution test, whereas IN is obtained from the tolu - ene equivalence test. Table 3 presents the SBN and IN data, including the proportions of the six blends evaluated for the crude feed slate. The refiner’s assessment on compatibility was based on SBN mix and IN max , depending on the volumetric propor - tions of source oils. As shown in Table 3, all six blends are considered stable, and the source oils are compatible per Wiehe’s compatibility criterion (SBN mix > IN max ). MFCCT was independently applied to evaluate these six blends using the source oil data. For onset values, both SBN and IN were translated to a single onset in mL of n-hep - tane per g of sample for each source oil, enabling their use within the tool. This translation is performed automatically within the Petro-SIM simulator. As shown in Table 3, MFCCT predicted that all blends were stable and compatible source oils, aligning with the refiner’s or Wiehe’s assessment. Additionally, MFCCT pro - vided additional insights into blend stability. For instance, the predicted onsets for Blend 9 and Blend 10 were 0.62 and 0.74 mL/g, respectively. These are borderline values for classification as high risk, which was confirmed by the refiner based on their experience. Key findings Together, these case studies emphasise the power of advanced analytical tools in crude compatibility assessment

and blend management. The case studies collectively high- light the value of advanced tools like MFCCT in assessing crude compatibility. Key findings include:  The tool’s ability to predict blend onsets with high accu - racy, preventing costly operational risks. v The development of the BCI, which quantifies non- linearity and provides actionable insights into crude compatibility. w The model accounted for the non-linearity of blend onsets, which traditional linear mixing rules often miscalcu - late, leading to operational risks. x More than 40 refinery blends were tested, validating the MFCCT tool’s predictive capabilities. Broader applications MFCCT’s predictive capabilities extend beyond compat- ibility analysis with applications across various refinery processes: • Planning and scheduling: Supports crude selection and scheduling, enhancing flexibility for slate mixes and com - plementing linear programming models. • Crude storage and handling: Assesses sludge build-up risks. • Processing: Evaluates feeds for process units, such as desalters and preheat exchangers, and identifies fuel oil blend stability risks. Conclusion As the refining industry continues to navigate a rapidly evolving energy landscape, the MFCCT stands out as an essential solution for improving operational efficiency and reliability. By tackling the ongoing challenge of crude com - patibility, MFCCT equips refiners with the insights they need to optimise operations, make informed decisions, and mitigate risks. Opportunity crudes, though economically appealing, often bring unpredictable properties. This variability pre- sents both challenges and opportunities. With its robust

PTQ Q2 2025