## 4 Discussion
\begin{table}
\begin{tabular}{l|c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Nu**} & \multirow{2}{*}{**Conv.**} & \multirow{2}{*}{**HDM**} & \multirow{2}{*}{**T-R1**} & \multirow{2}{*}{**T-R2**} & \multicolumn{2}{c}{**ATB**} & \multicolumn{2}{c}{**PBPO,**} & \multirow{2}{*}{**R-1 AT**} & \multirow{2}{*}{**R-2 AT**} & \multirow{2}{*}{**Urals**} & \multirow{2}{*}{**Sib Light**} & \multicolumn{1}{c}{**Basrah**} \\  & & & & & & & & & & & & \\  & & & & & & & & & & & \\ \hline Conv. & 0.00 & 0.16 & 0.06 & 0.09 & 0.70 & 0.65 & 0.15 & 0.54 & 0.34 & 0.60 & 0.26 \\ \hline HDM & 0.16 & 0.00 & 0.18 & 0.21 & 0.68 & 0.65 & 0.23 & 0.55 & 0.39 & 0.51 & 0.32 \\ \hline T-R1 & 0.06 & 0.18 & 0.00 & 0.05 & 0.64 & 0.60 & 0.07 & 0.54 & 0.29 & 0.57 & 0.19 \\ \hline T-R2 & 0.09 & 0.21 & 0.05 & 0.00 & 0.64 & 0.61 & 0.12 & 0.50 & 0.29 & 0.58 & 0.20 \\ \hline ATR TSE & 0.70 & 0.68 & 0.64 & 0.64 & 0.00 & 0.37 & 0.75 & 0.40 & 0.57 & 0.38 & 0.20 \\ \hline PBFO, TSP & 0.65 & 0.65 & 0.60 & 0.61 & 0.37 & 0.00 & 0.61 & 0.55 & 0.64 & 0.29 & 0.30 \\ \hline R-1 AT & 0.15 & 0.23 & 0.07 & 0.12 & 0.75 & 0.61 & 0.00 & 0.54 & 0.28 & 0.67 & 0.24 \\ \hline R-2 AT & 0.54 & 0.55 & 0.54 & 0.50 & 0.40 & 0.55 & 0.54 & 0.00 & 0.32 & 0.56 & 0.20 \\ \hline Urals & 0.34 & 0.39 & 0.29 & 0.29 & 0.57 & 0.64 & 0.28 & 0.32 & 0.00 & 0.86 & 0.18 \\ \hline Sib Light & 0.60 & 0.51 & 0.57 & 0.58 & 0.38 & 0.29 & 0.67 & 0.56 & 0.86 & 0.00 & 0.39 \\ \hline Basrah Heavy & 0.26 & 0.32 & 0.19 & 0.20 & 0.20 & 0.30 & 0.24 & 0.20 & 0.18 & 0.39 & 0.00 \\ \hline \end{tabular} Note: Green color means statistically meaningful positive relation; Red color implies statistically meaningful negative relation. The intensity of the color designates the strength of the relation. The higher the color intensity, the higher the strength of the relation is. Yellow color denotes dissonance.  
\end{table} 
Table 4: \(\mu\)-value of the ICrA evaluation of relations between the different variables characterizing hydroreracker performance. \begin{table}
\begin{tabular}{l|c c c c|c c c|c c c} \hline \hline \multirow{2}{*}{\(\mu\)} & \multirow{2}{*}{**Conv. **} & \multirow{2}{*}{**HDM**} & \multirow{2}{*}{**T-R1**} & \multirow{2}{*}{**T-R2**} & \multicolumn{2}{c}{**ATB**} & \multicolumn{2}{c}{**PBPO,**} & \multirow{2}{*}{**R-1 AT**} & \multirow{2}{*}{**R-2 AT**} & \multirow{2}{*}{**Urals**} & \multirow{2}{*}{**Sib Light**} & \multicolumn{1}{c}{**Basrah**} \\  & & & & & & & & & & & Heavy \\ \hline Conv. & 1.00 & 0.84 & 0.82 & 0.81 & 0.28 & 0.33 & 0.83 & 0.39 & 0.61 & 0.35 & 0.23 \\ \hline HDM & 0.84 & 1.00 & 0.71 & 0.69 & 0.30 & 0.33 & 0.75 & 0.38 & 0.56 & 0.44 & 0.17 \\ \hline T-R1 & 0.82 & 0.71 & 1.00 & 0.91 & 0.23 & 0.28 & 0.81 & 0.33 & 0.55 & 0.28 & 0.30 \\ \hline T-R2 & 0.81 & 0.69 & 0.91 & 1.00 & 0.24 HDM; however, this hypothesis features a great deal of uncertainty. More data is needed to categorically prove the detrimental effect of Basrah Heavy vacuum residue processing in the hydrocracker on HDM. Indeed, the data in Tables 3 and 4 show that the improvement of HDM has a negative statistically meaningful relation to the sediment content in the ATB, confirming that the HDM improvement retards the process of sediment formation. [PERSON] et al. [43], and [PERSON] et al. [45] showed in their studies that the demetallization efficiency is proportional to the conversion of asphaltenes. Our data, although characterized by a higher dispersion than the data of [PERSON] et al. [43] (see Figure 14), also supports their conclusion, indicating that HDM and hydrodeasphaltization are interrelated. The data in Figure 14 indicate that the regression developed on the basis of the data for the period 9 April 2022-28 November 2022 is very well fitted to the points fot the dates beyond that period obtained after the maintenance work performed in December 2022 on the commercial ebullated bed vacuum residue hydrocracker.