Fossil feed contaminants
Wash water quality
Wash water
Average 5 ppm wt 100 ppm wt 200 ppm wt 25 ppb wt 2 ppm wt 1 ppm wt 15 ppm wt
Max
Fossil feed
Average
Max
Chlorides Ammonia Sulphides
10 ppm wt 200 ppm wt 300 ppm wt 70 ppb wt 5 ppm wt 2 ppm wt 30 ppm wt
Nitrogen-based Sulphur-based
1,000 ppm wt 10,000 ppm wt
1,500 ppm wt 20,000 ppm wt
Chlorides * Oxygenated Phosphorus
1 ppm wt 120 ppm wt 1 ppm wt 2 ppm wt
3 ppm wt 300 ppm wt 2 ppm wt
Oxygen
Carbonates
Metals
Metals 4 ppm wt * Due both to the presence of organic chlorides solvents in the imported gasoil and from the H 2 make-up streams coming from the CCR unit, due to upsets of the chloride guard beds (the catalyst is regenerated via the injection of perchloroethylene or similar chlorine-based organic agents)
Cyanides
Table 2
This is especially crucial in HDT units, which are highly sus- ceptible to upsets due to substantial changes in feedstock qualities and operating conditions. An electrolyte model provides in-depth insights into these complex systems, informing reliability and design engineers about operating efficiencies, as well as corrosion and fouling risks. Case study: DHT co-processing feasibility study A European refinery aiming to produce ultra-low sulphur second-generation renewable diesel has outlined plans to co-process renewable feeds at its existing diesel hydro- treater (DHT). In pursuit of this goal, the refinery has engaged OLI Systems Inc. to conduct a feasibility study. The primary objective of the study was to assess the impact of the biogenic feedstocks on the unit’s operations. This included identifying potential process bottlenecks, establishing quality and incorporation rate limits, and defin - ing a safe operating envelope. Additionally, the study aimed to provide recommendations for key modifications to opera - tional parameters and suggest the installation of new equip- ment to ensure the safe and profitable operation of the unit. The first phase of the project focused on evaluating the status of the unit, including quantifying bottlenecks and limitations associated with running the plant with 100%
Table 1
Ionic modelling Electrolyte models provide insights into corrosion and foul- ing risk in HDT units. Thermodynamic analysis of HDT streams at varying feedstock qualities and operating conditions (temperature, pressure, pH, and composition) can be used to evaluate fouling and corrosion potential. Ionic mass balance throughout the unit aids in the com- prehensive assessment of fouling and corrosion risks across the process scheme. By establishing operating envelopes, operators can determine the safe introduction of biogenic feedstock, avoiding highly corrosive conditions and thereby extending the life and reliability of the units. Ionic mod- els also assist in identifying significant modifications to the process scheme, guiding the design and selection of appropriate materials for tower internals, heat exchangers, overhead systems, and piping systems, ensuring the safe incorporation of a higher percentage of biogenic feedstock. Electrolyte chemistry modelling plays a critical role in understanding the behaviour of complex water and hydro- carbon streams in downstream oil and gas process units.
Recycle gas
Recycled compressed gas
Gas compressor
Reactor e uent
03 out
01 out
02 out
Sweet gas
AA sour gas
Sep-1
Hex 01
Hex 02
Hex 03
Lean amine
S-2 S-3
Rich amine
04 out
05 out
06 out
Amine absorber
Intermittent wash water
NH HS corrosion & fouling risk
Hex 04
Hex 05
Hex 06
S-4
Flash tank
Continuous ww inj. mixer
Mix-3
AA rich amine
09 out ww
10 out
07 out
08 out
09 out
AC01 out
10 out
Diesel stripper condensate
ww
Hex 10
Intermittent ww inj. mixer
Diesel stripper OVHDs
Hex 07
Hex 08
Hex 09
HP separator
DS OVHD receiver
DS OVHD coolers
Solid
Continuous injection system
HP sep. sour gas
To diesel stripper
HP separator HC
Tail gas
LP separator
Diesel stripper
NH Cl corrosion & fouling risk
DS water
Pre-heat
LP separator HC
Wild naphtha
HP separator water
Diesel product
Stripping steam
LP separator water
Figure 3 OLI Flowsheet ESP – 100% fossil feed – ionic survey
92
PTQ Q2 2024
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