PTQ Q4 2024 Issue

– 1st stage: Max desalting, 1.0 to 1.2 bar – 2nd stage: Max desalting 0.8 to 1.2 bar

Total wash water: 6 to 8 vol% optimal Wash before preheat: 2 to 2.4% Wash water at mix valve: 4 to 5.6%

SARA content (saturate, aromatic, resin, asphaltene) % Saturate % 54 Aromatic % 32 Resin % 7 Asphaltene % 6 Waxes % 6

Crude API Viscosity

: Crude blend : 29.5 : 29 cst at 15 o C : 10.73 cst at 40 o C : ~2.5 cst at 145 o C : 30 to 80 ppm : 1.56

Limited mix valve DP based on crude conductivity & emulsion band, to achieve optimal desalting i.e. Salt <0.5 ptb

Wash water

Mix valve

Total metals CII

Interface level vs Residence time 1st stage : 60 to 70% 2nd stage: 40 to 50% Emulsion at Tryline: 3 to 4 in 1st stage Emulsion at Tryline: 2 to 3 in 2nd stage

Temperature: >138 o C to 145 o C Operation 140 o C+: Water solubility in crude increase not possible to achieve BS&W <0.2 vol%

Level control

Feed quality

Temperature

Grid/ Electric eld

Demulsier /Chemicals

Demulsier: Embreak 2W2020/2W157i – Resolve water in oil emulsion – 5 to 10 ppm dosage

At Optimal Mix valve, design crude conductivity

Solids wetting / Secondary breaker: Embreak 2163 – Based on lterable solids removal target (3 to 7 ppm)

Voltage : 400 volts (+/- 10) Amperage: 90 amps (+/- 10)

Figure 4 Key desalter parameters optimisation strategies

as fluid rates, viscosity, temperature, residence time, voltage and amperage, level monitoring type and calibration, wash water rates and quality, and mix valve design. w Operational and chemical: Establishing baseline moni - toring for performance-influencing operational and chemical parameters, such as temperature, pressure, mix valve DP, and emulsion studies for demulsifier efficacy validations at different dosage rates for desalter operating conditions using a portable electric desalter (PED). x Surveys and statistical analysis: Performing statisti - cal analyses, including multiple regression analysis (MRA). Desalter benchmark tools and MRA statistical tools identi - fied performance-influencing factors affecting salt removal efficacy (see Figure 5 ). y Focus on key parameters: Selecting the top two to three performance-influencing parameters from the MRA analysis, with wash water flow and mix valve DP influencing the salt output based on statistical analysis for the case study refin - ery (Figure 5). Troubleshooting discrepancy parameters After data analysis, an essential step before desalter opti - misation is performing calibration and validation exercises on variables that show significant variations (more standard deviations). The following is a summary of the influencing parameters that were troubleshot for discrepancies:  Interface level: The reference refinery used a capaci - tance-based level measurement instrument. Interface level remained steady even with the growth of the emulsion layer, confirmed with validated on-field try-line/try-cock samples. A 10-15% discrepancy in interface level measurement was addressed after level instrument calibration. After a few months, level fluctuations were wider without any emulsion layer growth, and desalter brine control level actuator hunt - ing was observed as an influencing variable. Interface level fluctuations were addressed after brine control valve tuning.

and water (BS&W) less than 0.2 vol% in desalted crude has been the predominant refinery target for decades. However, due to growing concerns about downstream catalyst poi - soning and the integrated design with atmospheric residue hydrotreating (ARHDT) and residue fluidic catalytic crackers (RFCC), the focus is now on achieving crude desalting targets of less than 0.5 PTB to enhance plant operation reliability. The critical aspect of desalter troubleshooting and opti - misation is establishing safe operating boundary ranges for each key control parameter. These boundaries are deter - mined based on desalter design, historical data analysis, and current baseline process operating conditions (see Figure 4 for key optimisation parameter boundary limits established for the Southeast Asian refinery). It is essential to review KPIs at each stage of desalter operating parameter optimisa - tion, fine-tune the safe operating boundary ranges based on analytical and operational data analysis, and perform peri - odic instrument calibrations and troubleshooting to address any offsets observed in critical monitoring parameters. Data analysis and troubleshooting discrepancy parameters The desalted crude salt outlet is influenced by various fac - tors, including crude flow rate, crude properties (density, viscosity, filterable solids, and conductivity), desalter temper - ature, voltage and amperage, wash water flow rate, wash water pH, wash water chloride levels, mix valve differential pressure (DP), slop oil rate and quality, demulsifier dosage, solids wetting agent dosage, interface level, internal recycle water rate, and mud wash frequency and duration. Analytical and process data analysis was performed in the following sequence:  Crude fluid quality: Collation of crude characteristics data, such as density, viscosity, salt content, BS&W, SARA analysis, and crude compatibility. v Mechanical: Summarising all desalter design data, such

PTQ Q4 2024