REFINING INDIA 2025

REFININGINDIA 9-10 SEPTEMBER 2024 LE MERIDIEN HOTEL, NEW DELHI 22-23 SEPTEMBER 2025

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Emerging landscape of India’s crude oil refining sector

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Hydroprocessing of waste cooking oil to SAF 3 Co-processed SAF via the kerosene hydrotreater is low-cost and readily available 5 Application of CFD as a diagnostic tool to resolve flow-induced failures in process units 7 Smart control, real impact: AI-driven autonomy cuts energy use, emissions, and operator burden 9 Maximising alkylation unit throughput during the summer months 11 Role of nuclear gauges in delayed coking and ebullated bed hydrocrackers 13

Ms Vartika Shukla, Chairman & Managing Director Engineers India Limited

The oil and gas sector has played a key role in the growth of India’s industrial sectors. The country’s crude oil consumption is antici- pated to increase vis-à-vis

expansion of the consumer market, making India the largest source of global oil demand growth during this decade, as per the Indian Oil Market Outlook 2030 published by the International Energy Agency (IEA). The trend can be traced in terms of India’s pro- jected crude oil processing capacity, which is expected to reach around 310 MMTPA by the end of this decade from around 257 MMTPA at present. Demand for both fuels and petrochemical products is a key driver for these anticipated capacity additions, which are planned mostly by the state- owned refineries. It is important to note that the per cap- ita polymer consumption in India is almost one-third of the global average. The coun- try faces shortfalls across the range of pet- rochemical products, including commodity polymers such as polypropylene (PP), pol- yvinyl chloride (PVC), linear low-density polyethylene (LLDPE), high-density poly- ethylene (HDPE), and polyethylene tere- phthalate (PET), as well as low-volume, high-value niche petrochemicals like super- absorbent polymers (SAP), among others. This situation suggests that there will be a need to install a number of liquid and gas crackers in the years to come. In addition, scenarios such as plateau- ing gasoline demand by the year 2037 – primarily influenced by the penetration of electric vehicles (EVs) in the transporta- tion segment – upgrading the bottom of the barrel, processing a higher volume of high TAN opportunity crude, and improving the Energy Intensity Index (EII) to achieve the first quartile (Q1) targets necessitate new refinery configurations. This will provide flexibility of operation to owners, adoption of energy-efficient technologies that are amenable to the product supply demand trends, and commercialisation of crude oil to chemicals conversion processes, to name a few. The HRRL-Rajasthan Refinery Project (RRP), with a petrochemical intensity of around 26%, as well as HMEL’s Petro addi-

Valorising plastic pyrolysis oil by co-processing in FCC units for enhanced circularity Driving value maximisation with process digital twins and data analytics Naphthenic base oils: status and outlook Unlocking full value from spent precious metal catalysts in India’s refining sector Optimising renewable fuel feedstock pretreatment Fully eclosed, zero-emission coke handling

Figure 1 Vizag Refinery modernisation project, HPCL

tion project, India’s first rasid upgradation facility (RUF) at HPCL-Vizag ( Figure 1 ), the propane dehydrogenation (PDH) units by Gas Authority of India Limited (GAIL) and Petronet LNG Limited (PLL), and upcom- ing large petrochemical projects by IOCL- Paradip and BPCL-Bina are all testaments of the nation’s progress aligned with the emerging industrial trends. India may see a decline in liquefied petro- leum gas (LPG) consumption for domestic applications primarily due to the prolifer- ation of piped natural gas (PNG) network across the country, making LPG available as a petrochemical feedstock. Further, the demand for aviation turbine fuel (ATF) is anticipated to grow approxi- mately sevenfold from the present con- sumption level of around 8-9 MMTPA by 2040. As India prepares for the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) regulation, with a target of 1% sustainable aviation fuel (SAF) blending in ATF by 2027, refin- ers have already started exploring a vari- ety of feedstocks for SAF production. It is important to note that the country’s bio- fuels programme is already in full swing, and several biorefineries are anticipated to be installed at various locations in India based on diversified feedstocks to meet the demand of fuel-grade ethanol for blending in gasoline and production of green chemi- cals. Technology developments in this area are also opening avenues for pathways like Alcohol-to-Jet (ATJ) to produce SAF in the

years to come, potentially enabling the integration of biorefineries with existing refineries. The ongoing energy transition has already pushed refiners to pursue several decarbon- isation initiatives. Harnessing renewable energy sources could be a game-changer in reducing the overall emissions of refinery complexes. Refiners are already exploring instruments such as green power purchase agreements through equity mode, the inte- gration of concentrated solar thermal tech- nology with process units, AI-enabled digitalisation and automation, green hydro- gen production, and carbon capture and utilisation (CCUS), to achieve their net- zero emissions objectives. For instance, some state-run oil and gas companies have already implemented or are in the process of implementing green hydrogen production units using water electrolysis technology. Also, harnessing nuclear energy, espe- cially using small modular reactors (SMRs) with a power production capacity of around 300 MW, presents an opportunity for the oil and gas sector, which accounts for around one-third of India’s primary energy mix. In conclusion, the Indian refinery sector is already on the path of transforming from fuel to feedstock-based units in the long term. This transition accelerates efforts towards decarbonisation, catering to the twin objectives of addressing the country’s energy security needs while meeting the growing demand for chemicals and petro- chemical products sustainably.

21 Automated anomaly detection and lifetime prediction for reciprocating compressors 23 Analytical solutions for the oil industryand hydrogen clean energy projects 25 Rethinking safety in reactor maintenance: innovations to reduce confined space entry 27

Hybrid (fresh and regenerated) catalyst loading reduces fill cost and carbon footprint Making your green HVO/HEFA project greener Reliable measurement in extreme refinery conditions with gamma/ radiometry technology

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refining india 2025

Hydroprocessing of waste cooking oil to SAF

S A Farooqui, R Kumar, Rakesh Baghel, P Alam, and T Khan Anil K Sinha Biofuels Division, CSIR – Indian Institute of Petroleum

tripartite agreement (NDA) and MOU with Mangalore Refinery and Petrochemicals Limited, CSIR-IIP, and EIL have been signed to set up the demonstration commercial unit. MRPL is installing a demonstration plant to manufacture 220 BPD of SAF. The engineering consultants have com- pleted basic design engineering package, detailed feasibility report, and pre-pro- ject activities for the SAF plant at MRPL. The board approval for the plant construc- tion, equivalent to $60 million, has been obtained. The pretreatment section of the plant is in the initial procurement stage. With a feed price of Rs 70/kg (0.8 $/kg), the minimum fuel selling price (MFSP) for SAF production in India is Rs 126 Rs/kg (1.6 $/kg). Byproduct prices are taken with- out considering the premium due to green products: naphtha Rs 56/kg (0.7$/kg), gas Rs 69/kg (0.85 $/kg), H₂ Rs 177/kg (2.2 $/ kg). The CSIR-IIP process is available for commercial implementation in India and abroad for interested investors/refiners. For international recognition and cer- tification of its SAF, CSIR-IIP pre- sented its technology to the ASTM International Committee and Federal Aviation Administration in August 2020. It created a collaboration area at ASTM named AC-644-CSIR-IIP HEFA-Variant Aviation Biofuel, which is code-named Hydroprocessed Esters and Fatty Acids – Synthetic Kerosene with Aromatics, HEFA- SKA). CSIR-IIP SAF is under evaluation by ASTM D4054. The complete approval process of any new SAF at ASTM occurs in four stages (Tiers 1, 2, 3, and 4). The batches of fuel supplied by CSIR-IIP have been tested as per ASTM Tiers 1 and 2. Tiers 3 and 4 are not mandatory for all cases. The report and the newly proposed annexure have been reviewed by original equipment manufactur- ers (OEMs). Following this review, the OEMs are expected to recommend balloting.

Aviation is a significant contributor to global carbon emissions and air pollution. Jet fuel is essential for powering aircraft engines and can comprise up to 70% of a plane’s maximum takeoff weight. Due to the industry’s rapid growth and extended asset life spans, addressing its climate impact is particularly challenging. Sustainable avia- tion fuel (SAF) represents a significant leap forward in the aviation industry’s efforts to reduce environmental impact. SAF con- tributes to reducing the aviation industry’s carbon footprint and is a potential offset for CO₂ emissions. To date, 11 conversion methods for the manufacturing of SAF have been approved, and 11 more are presently being assessed by ASTM International.¹ The US has led SAF development with numerous initiatives and investments. The EU is at the forefront of SAF adoption, partly due to its ambitious climate goals. SAFs may cut CO₂ emissions by up to 80% and are presently utilised in commercial avi- ation. Waste fats, oils, greases, municipal solid waste, forestry and agricultural lefto- vers, wet wastes, and non-food crops grown on marginal land are some of the sources (feedstock) from which it may be made. 2,3 By 2050, the EU wants to reach 65%, and several nations have set even higher SAF goals. Additionally, corporations, air- lines, and cargo carriers are keen on inves- tigating and expanding the usage of SAF. 4 The US targets to reduce GHG emissions by 20% in 2030, equivalent to 3 billion gallons of SAF by 2030. The UK aims to achieve a mandate of 10% SAF by 2030 and 75% by 2050. The EU is target- ing 63% SAF by 2050, including 28% e-jets, starting with 2% SAF in 2025. On November 25th, 2024, India’s petro- leum ministry announced that the National Biofuels Coordination Committee has set a goal to blend 1% of SAF with jet fuel by 2027 and 2% by 2028. 5 CSIR-IIP began working on SAF tech- nology at a lab scale in 2008. In 2011, a pilot plant with a capacity of 20 litres per day for SAF was commissioned, based on CSIR-IIP’s design and funded by the Department of Science and Technology. In 2010, an India-Canada consortium was formed between International Science and Technology Partnerships Canada and Global Innovation & Technology Alliance India to develop the SAF technology. CSIR-IIP was the lead from India, while Pratt & Whitney was the lead from Canada. CSIR-IIP estab- lished a pilot plant facility to develop the process and successfully produced 60 litres of SAF, meeting ASTM D1655 speci- fications for Jet A/A-1. The SAF was then sent to Pratt & Whitney for testing. In 2013, the project demonstrated that CSIR-IIP’s SAF technology has the poten- tial for scale-up and commercialisation. The process ( Figure 1 ) was later scaled up from the lab scale (TRL-02) to TRL-06 with CSIR funding, followed by financial support from the Indian Air Force (IAF) for bulk fuel pro- duction and commercial development. CSIR-IIP has produced and supplied ~8,700 litres of SAF to the IAF. IAF used this SAF in ground and flight trials (logging

Pretreatment not required with certain feedstocks

Hydrogen consumption 3 wt%

Light gases Light HC, H and CO Naphtha (C-C) SAF (C-C) Diesel range (C+) Water

biomass derived oil & fats

Pretreatment

Deoxygenation/selective cracking/isomerisation

MW = 200-300

Max. SAF mode ~55% feed basis UCO as feed

Figure 1 Summary of the CSIR-IIP SAF process

Light gases & naphtha

Pretreatment (de-gumming/ bleaching)

Isomerisation/ selective cracking

Hydrotreating

HEFA-SPK (2-step)

Kerosene (IIP-SKA) (Parans (I, N, C,) and aromatics) Paranic (I, N, C) kerosene (HEFA-SPK)

Plant oils Animal fats

N-Parans isomerised to improve cold ow properties

Oxygen removed Olens saturated

Large molecules cracked to jet fuel range

Paran diesel (HEFA-SPK)

CSIR-IIP process (HEFA-SPK -1-step)

Hydroprocessing route (Hydro-deoxygenation Hydrocracking, Hydro-isomerisation Aromatisation, Cyclisation Hydrogenation)

Plant oils Animal fats

Diesel (IIP-SKA) (Parans (I, N, C,) and aromatics)

Pretreatment

Hydroprocessing (HEFA pr ocess)

Figure 2 One-step CSIR-IIP process and two-step HEFA process

lises a patented catalyst (EP3191565A1, US 10,351,782, US 10,457,875), which is easy to implement and economical com- pared to globally available SAF processes. SAF yield is in the range of 55-60% by mass of feedstock, along with other sal- able co-products of low-sulphur (<5 ppm), renewable diesel (80-90 cetane), naphtha, and liquefied petroleum gas (LPG). In the CSIR-IIP process, hydrocarbon liq- uid distillate yields up to 80%. The process uses non-noble metal-based catalysts and a feed-agnostic approach (any vegetable oil fats can be used as feedstock). CSIR- IIP SAF has been demonstrated on civilian aircraft with a 25% blending of Jet A1 and military transport planes with a 10% blend- ing of Jet A1. SpiceJet conducted a short pilot test flight and a 45-minute demonstra- tion flight in 2018, aboard a turboprop air- craft. The fuel was a 25% HEFA-SKA SATF produced by CSIR-IIP blended with ATF (Jet A-1) in one engine. The performance find- ings were satisfactory. Currently, CSIR-IIP has transferred its technology information to EIL (a public sec- tor engineering company) for the commer- cialisation of its technology, which is to be marketed by EIL to interested investors. A

90 hours) and in the Republic Day fly-past. After receiving the engine trial feedback and fuel testing reports, the Centre for Military Airworthiness & Certification (CEMILAC), the approving agency for IAF aircraft, granted provisional clearance for the use of CSIR-IIP SAF in IAF aircraft with 10% blend- ing. The company has produced 20,000 litres of SAF at its pilot facility in Dehradun. The CSIR-IIP process offers a single-step method to convert plant-derived oils and animal-derived fats into hydrocarbons. The produced SAF contains hydroprocessed esters and fatty acids synthetic kerosene with aromatics (HEFA-SKA), which is very similar to crude-based aviation fuels. The SAF approved via the two-step HEFA pro- cess does not contain aromatics and is lim- ited by the maximum blending of 50%. The differences between the CSIR-IIP SAF pro- cess and the two-step HEFA process are shown in Figure 2 . CSIR-IIP SAF can exceed 50% blend- ing, as the SAF produced in this process is closer to the jet A/Jet A-1 in hydrocarbon composition. The SAF produced contains cyclo-paraffins <15%, aromatics <10%, and normal and iso-paraffins ( Figure 3 ). The CSIR-IIP demonstration plant uti-

References 1 https://www.lexology.com

2 https://www.icao.int 3 https://www.iata.org

4 https://www.spglobal.com 5 https://www.topsoe.com 6 https://indianexpress.com

7 IN731/DEL/2011 process for preparing fatty acid methyl ester from fatty acid triglyc- erides, https://patentscope.wipo.int/search/ en/d etail.jsf?docId=IN211566199&_cid=P21- LWXI3V-72642-1 8 https://www.gminsights.com/ industry-analysis/used-cooking-oil-market 9 Tulashie, S. K., Kotoka, F., The potential of cas- tor, palm kernel, and coconut oils as biolubricant base oil via chemical modification and formula- tion. Thermal Science and Engineering Progress 2020, 16, 100480. 10 Perera, M., Yan, J., Xu, L., Yang, M., Yan, Y., Bioprocess development for biolubricant produc- tion using non-edible oils, agro-industrial byprod- ucts and wastes. Journal of Cleaner Production 2022, 357, 131956. 11 https://www.futuremarketinsights.com/ reports/lubricants-market 12 Beran, E. Experience with evaluating bio- degradability of lubricating base oils. Tribology International 2008, 41 (12), 1212-1218.

0 10 20 30 40 50 60 70 80 90

CSIR-IIP SAF 50% CSIR-IIP SAF Jet-A

Parans (iso & normal)

Cyclo-parans

Aromatics

CSIR-IIP SAF 50% CSIR-IIP SAF Jet-A

79 65 50

11 21 32

9.8 14.2 18.2

Figure 3 CSIR-IIP SAF, 50% blend and Jet A compositional analysis by GCxGC

refining india 2025

Co-processed SAF via the kerosene hydrotreater is low-cost and readily available

Raju Chopra and Ignacio Costa TOPSOE

volumes. The catalyst system must manage both deoxygenation and dewaxing to ensure jet fuel meets freeze point requirements. Meeting freezing point specifications with dewaxing catalysts Biogenic feedstocks, when hydroprocessed, tend to produce straight-chain paraffins (n-paraffins), which can raise the freezing point of the jet fuel product. This poses a challenge when meeting strict SAF speci- fications, such as Jet A or Jet A-1. To meet the cold flow properties requirements of Jet A and Jet A-1 fuels, deep dewaxing of these biogenic paraffins is essential. To address this, highly selected, high- performance dewaxing catalysts such as Topsoe’s TK-930 D-wax™ are deployed. These catalysts use selective isomerisation to reshape the molecular structure, lowering the freezing point without sacrificing bio- genic carbon retention or yield. The n-par- affins are isomerised to iso-paraffins, which have much better cold flow properties with- out losing any biogenic carbons to the gas and naphtha ( Figure 1 ). This catalyst has been designed to operate even at reactor pressure as low as 25 barg. At this level, a highly selective dewaxing catalyst and HDO selective grading serve as a drop-in replace- ment for existing kerosene hydrotreaters. Figure 2 demonstrates how to maximise SAF yield in a kerosene hydrotreater with the right catalyst loading, using selective hydrodeoxygenation (HDO) and isomerisa- tion catalyst.

As the aviation sector accelerates its decar- bonisation efforts, sustainable aviation fuel (SAF) is seen as the most promising tool to cut lifecycle emissions. One of the quick- est and readily available ways to scale SAF output is by using co-processing – a method that integrates renewable feedstocks directly into conventional refinery units. It is also cost-effective and easily implementa- ble because co-processing leverages cur- rent refining, transport, and storage assets, minimising capital expenses. Among the ways refineries can introduce co-processing, the kerosene hydrotreater stands out as the most immediate and effi- cient route. However, what are the technical enablers of co-processing SAF in kerosene hydrotreaters, and why is this approach par- ticularly suitable in terms of readiness, effi- ciency, and compliance? Co-processing: rapid route to renewable jet fuel Co-processing blends renewable feed- stocks, such as used cooking oil, vegeta- ble oil or animal fats, with fossil-based feed in existing refinery units. The result is a drop-in, partially renewable fuel that com- plies with American Society for Testing and Materials (ASTM) specifications for jet fuel. Unlike standalone renewable fuel units, co-processing requires only limited invest- ment. It takes advantage of existing assets and can be implemented quickly with rela- tively simple changes. Topsoe, for exam- ple, has supported more than 90 successful co-processing projects globally to produce various renewable fuels, demonstrating that this pathway is not experimental – it is proven, refined, and reliable.

Number of carbon atoms: 14 Boiling point: 254˚C Melting point: 6˚C

Hydrocracking

Number of carbon atoms: 18

Boiling point: 317˚C Melting point: 28˚C

-25

-50

Normal alkanes 3-methyl isomers 2-methyl isomers

Hydroisomerisation

-75

-100

Number of carbon atoms: 18 Boiling point: 313˚C Melting point: -6˚C

Carbon atoms in molecule

Figure 1 Hydroisomerisation as a more efficient pathway for lowering the freezing point

Fossil naphtha + gases Renewable propane

Fossil kerosene Renewable feed

Hydrotreating reactor

Splitter

Biogenic carbon Fossil carbon

HDO/HDS catalyst

2.7%

Dewaxing catalyst

Jet A or A - 1 SAF

2.5%

Figure 2 Co-processing renewable feedstocks in a kerosene hydrotreater

Fine-tuning operating conditions for optimal output

involves a few technical adjustments, and it may not be feasible for every kerosene hydrotreating unit. Renewable feedstocks contain high lev- els of oxygen, which must be removed during hydroprocessing. This increases hydrogen demand – sometimes by more than 30 times the consumption per volume of feedstock compared to fossil kerosene. Compressor upgrades or process adjust- ments may be needed to ensure supply. The kerosene hydrotreating unit should be eval- uated to ensure it can meet the tempera- ture requirements of the dewaxing catalyst. If the existing reactor heater cannot provide the necessary heat duty, an additional heat source may be required to achieve the new operating temperature. Corrosion control is an important ele- ment, as acidic components and chlorides in renewable feed can trigger corrosion. Material compatibility checks and, in some cases, repositioning of wash water injection points may be required to manage the for- mation of ammonium chloride salts. Also, triglyceride-based feedstocks produce more water as oxygen is removed. Units must account for this by increasing water handling capacity, particularly at the sepa- ration stage. Co-processing demands tailored catalyst configurations and, in some cases, higher

offer different trade-offs. Diesel hydrotreat- ers could be an option for producing SAF; however, the renewable carbon is dispersed across the diesel product range rather than being concentrated in jet fuel, making the SAF yield lower per input volume and, there- fore, less cost-competitive. With hydrocrackers, one advantage is flexibility. They can handle a broad range of feedstocks and are typically equipped with hydrocracking and/or dewaxing catalyst. They can also produce multiple renewable fuel types, including SAF. However, they are also key hydroprocessing units in the refin- ery, targeting a series of objectives, which can be detrimental to SAF yields, making this solution also less cost-competitive. It has been found that the majority of biogenic content (approximately 80-85%) is landed in diesel product. The kerosene hydrotreater, even with operating conditions that may not be opti- mal for advanced catalyst systems (for example, dewaxing catalyst), provides a narrow, efficient path for SAF producers who aim to scale rapidly and meet immedi- ate SAF mandates with minimal delay.

Operating conditions for co-processing SAF vary depending on feedstock type, target product, and unit design. Key parameters include: • Hydrogen-to-oil ratio : Must be increased to account for the high hydrogen consump- tion of the renewables feedstocks. • Temperature and pressure : Need to be optimised to balance reaction rates, cata- lyst activity and selectivity. • Liquid hourly space velocity (LHSV) : Influences contact time and conversion effi- ciency; must align with catalyst capacity and feed characteristics. Conclusion Co-processing is a fast track to SAF pro- duction that can function as a short-term solution to comply with the upcoming SAF mandates in the next few years. Among vari- ous options, co-processing renewable feed- stocks in kerosene hydrotreaters is a great choice for SAF production with respect to lower operating cost, lower capital invest- ment, higher recovery of biogenic carbon in the SAF product, short implementation time, and low payback period. This method can save up to two years of construction time compared to building new facilities.

Why the kerosene hydrotreater is the fastest route for SAF

Co-processing to produce SAF can be implemented across various hydroprocess- ing units in a refinery, including kerosene hydrotreaters, diesel hydrotreaters, and hydrocrackers. Among these, the kerosene hydrotreater and hydrocracker stand out as the most effective units for SAF production, offering flexibility and compatibility with current refinery operations. The kerosene hydrotreater, for instance, targets the jet fuel fraction specifically. This means more of the biogenic carbon from renewable feedstock ends up in the final SAF product. This is especially relevant in some regions, where carbon-14 analysis is used to verify renewable content. Another benefit is simplicity. Co- processing in this unit can reach up to 5% of renewable feedstock by volume, and it will require changes to the catalyst system of the unit and an increase in the hydro- gen supply. However, the low capital costs enable refiners to launch SAF production quickly and with a short payback period. Kerosene hydrotreaters vs alternative units While diesel hydrotreaters and hydrocrack- ers are also viable for SAF production, they

Modifications for co-processing in the kerosene hydrotreater

Although straightforward, co-process- ing SAF in the kerosene hydrotreater still

Contact: RACH@topsoe.com

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refining india 2025

Application of CFD as a diagnostic tool to resolve flow-induced failures in process units

Pruthviraj Nemalipuri, Arun Kumar, Abdul Quiyoom, Pranab K Rakshit, and Prashant Nandanwar Bharat Petroleum Corporation Limited

Background: Case 1: Reactor effluent air cooler (REAC) tube plugging issue in DHDS unit The diesel hydrodesulphurisation (DHDS) unit was commissioned in 2000 with a design capacity of 2.0 MMTPA, later revamped in 2005 to increase capacity to 2.54 MMTPA. The REAC, DDE4 A-D, is constructed using duplex metallurgy and consists of four bays: A, B, C, and D. Monthly thermography is carried out to monitor its thermal performance and detect any abnormalities. Since June 2023, recurring tube plug- ging incidents have been observed in bays DDE4A and DDE4B, as indicated by ther- mography. To mitigate salt deposition in the upstream section of the REAC, the hot separator temperature was increased by 14°C. Wash water maximisation also did not improve tube plugging phenomena. During the scheduled catalyst replace- ment shutdown in August 2023, the REAC tubes were cleaned. Despite the cleaning, tube plugging reappeared in November 2023 and increased in subse- quent months, with plugging consistently confined to bays A and B. No issues were detected in bays C and D. Another shut- down was taken in April 2024 to perform tube cleaning. Deposits collected during both shutdowns were analysed in the lab- oratory, revealing that the primary com- ponent was ammonium chloride salts. The recurring plugging pattern necessitates a thorough investigation to identify the root cause and implement an effective solution. Case 2: Hydrogen blistering issue in rich amine flash drum The vacuum gas oil hydrodesulphuri- sation (VGOHDS) unit, commissioned in 2011 with a design capacity of 1.7 MMTPA, includes a rich amine flash drum which receives rich methyl diethanolamine (MDEA) from the recycle gas scrubber and cold flash drum off-gas scrubber. This ves- sel operates at a pressure of 7-8.5 kg/cm² and a temperature of approximately 40°C, with pressure maintained via split-range control using make-up hydrogen. Excess pressure is relieved through a knockout drum (KOD), and the MDEA level is regu- lated to the amine regeneration unit. The vessel is protected by two pressure safety valves (PSVs) set at 10.5 kg/cm². During the 2024 turnaround inspec- tion, significant hydrogen blistering was detected on the internal surface of the flash drum, particularly in shell courses two and three, covering an area of approx- imately 6 m² across four zones. Around 300 hydrogen blisters were identified below the amine inlet nozzle. Ultrasonic thickness measurements showed localised wall thinning, with remaining metal thick- ness ranging from 10 to 11 mm. These findings point to evolving corrosion pat- terns, warranting a detailed analysis and design review to prevent recurrence.

Plugging (red dots) in DD E4A tubes

Plugging (red dots) in DD E4B tubes

Figure 1 Plugging of the REAC tubes

Case Study 2: CFD analysis to identify and mitigate wall corrosion in rich amine column During a turnaround inspection of the VGOHDS unit, severe hydrogen blister- ing was observed on the internal surface of the rich amine flash drum ( Figure 3b ). Preliminary analysis suggested that flow- induced corrosion, possibly due to improper nozzle orientation, was the root cause. To investigate further, a CFD study was conducted using the actual drum geom- etry. Simulations evaluated internal flow patterns for three nozzle orientations: 180°, 90°, and 45°. The results showed that the existing 180° orientation led to direct jet impingement of H₂S-rich amine on the vessel wall ( Figure 3c ), causing localised turbulence and corrosion. In contrast, the 90° orientation redirected the incoming flow away from the wall, resulting in smoother flow patterns and significantly reduced wall impact ( Figure 3d ). Based on these insights, the nozzle ori- entation was modified to 90° and imple- mented during the plant turnaround, which is expected to minimise wall erosion and wet H₂S corrosion, thereby extending the equipment life and improving overall relia- bility of the rich amine flash drum. These studies demonstrated the effec- tiveness of CFD as a diagnostic and design optimisation tool in refinery oper- ations. By visualising internal flow pat- terns and predicting the impact of design changes, CFD enables informed decision- making, reduces trial-and-error modifi- cations, and significantly improves the reliability and safety of critical process equipment. By visualising internal flow patterns and predicting the impact of design changes, CFD enables informed decision-making

D2 D1 C2 C1 B2 B1 A2 A1

Figure 2a Snapshot of plant REAC manifold (existing); 2b Exiting manifold geometry and predicted phase contours; 2c Modified geometry and predicted phase contours

1 0.889 Velocity Magnitude (m/s)

0.778 0.667 0.556 0.444 0.333 0.222 0.111 0

Figure 3a Snapshot of amine column; 3b Snapshot of H₂ blusters on the wall; 3c Predicted velocity contours on the wall with existing inlet nozzlen; 3d Predicted velocity contours on the wall with modified inlet nozzle

inlet manifold configuration as a poten- tial contributor to this issue. To validate these concerns and explore improvement opportunities, a detailed CFD study was conducted. Multiphase CFD simulations were per- formed to compare the gas-liquid velocity profiles and wash water dispersion pat- terns in the existing vertical inlet mani- fold ( Figure 2b ) with a proposed horizontal arrangement ( Figure 3b ). Results from the simulation revealed flow maldistribution in the current vertical configuration, with poor phase mixing. In contrast, the horizon- tal configuration achieved a more uniform flow distribution and enhanced gas-liquid mixing, ensuring better wash water disper- sion ( Figures 2a and 1b , predicted phase fraction contours). These findings aligned with the licensor’s assessment and provided strong technical justification for modifying the REAC inlet manifold design. The CFD-driven insights supported the implementation of the hor- izontal manifold configuration, expected to improve wash water effectiveness, min- imise corrosion risks, and significantly reduce the likelihood of future tube plug- ging in REAC.

The application of computational fluid dynamics (CFD) as a diagnostic and trou- bleshooting tool is valuable for diag- nosing complex flow issues in refinery process units, offering detailed insights into internal fluid flow dynamics that are difficult to measure experimentally. In this work, CFD was applied to address two critical challenges: flow maldistribu- tion in the DHDS unit’s REAC and hydro- gen blistering in the rich amine flash drum inlet nozzle flow impingement on the vessel wall of the VGOHDS unit. Through simulation and design evaluation, CFD enabled root cause identification and guided effective design modifications to improve the reliability and performance of both systems. Case 1: Mitigation of REAC tube plug- ging through CFD analysis In the DHDS unit, plugging of the REAC tubes, particularly in DDE4A and DDE4B ( Figure 1 ), raised operational concerns. Investigations pointed towards uneven flow distribution and poor wash water dis- persion as likely causes. Corrosion stud- ies, along with recommendations from the process licensor, identified the REAC

AHEAD A long history of looking

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refining india 2025

Smart control, real impact: AI-driven autonomy cuts energy use, emissions, and operator burden

Jagadesh Donepudi and Michelle Wicmandy KBC (A Yokogawa Company) Nitin Soni Yokogawa, INDIA Hiroaki Kanokogi Yokogawa, Japan

As refiners contend with increasing com- plexity, ageing control systems, and grow- ing sustainability pressures, AI-driven autonomy is shifting from ambition to real- ity. Reinforcement learning (RL) – a branch of artificial intelligence (AI) that learns through interaction – offers a way to navi- gate this complexity without relying on pre- defined models or manual tuning. Think of it as a skilled operator who learns by doing, adapting to what works and adjusting deci- sions in real-time without a rulebook. Unlike traditional proportional-inte- gral-derivative (PID) or advanced pro- cess control (APC) systems, which require extensive engineering and struggle in non- linear environments, RL adapts in real time. According to Energies Media, the oil and gas sector faces challenges such as defect detection, cybersecurity, and logis- tics network optimisation. However, AI offers a powerful advantage that converts raw data into actionable insights, enhanc- ing operations while reducing costs. The World Economic Forum adds that digital technologies could lower global industrial emissions by at least 4% by 2030, posi- tioning RL as a high-impact tool for effi- ciency and decarbonisation. RL learns via real-time interaction, mak- ing it well-suited for dynamic, multivari- able environments like refineries. This article explores the real-world applica- tion of Factorial Kernel Dynamic Policy Programming (FKDPP), an RL devel- oped by Yokogawa and the Nara Institute of Science and Technology. Tested and deployed in live plant operations, FKDPP acts like an experienced process engineer who never sleeps, constantly learning, adjusting, and ensuring the system stays in balance even when conditions change. Inefficiencies in Traditional Control Methods Traditional control strategies, including PID control and APC, are well-established but exhibit limitations when applied to highly nonlinear and dynamic industrial environ- ments. Tuning PID loops for non-linear valve behaviour remains difficult and often leads to suboptimal performance under distur- bances or feed variations. Furthermore, APC implementation cycles are lengthy, typically requiring seven to eight months, and necessitate extensive step testing for model identification. These factors limit the responsiveness of traditional controls to real-time changes. Reinforcement learning has been explored as a solution; however, con- ventional RL algorithms (such as Deep Q-Networks) demand a large number of tri- als and are highly sensitive to the training dataset. Such characteristics make them unsuitable for real-world process control, where each trial carries operational risk, safety implications, and cost. The indus- try requires an RL algorithm that is both sample-efficient and robust across variable process conditions.

Yokogawa oce

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Process history data for two years

Figure 1 FKDPP AI model lifecycle, from data collection to field deployment via Control AI Station

reduce energy use, and stabilise operations under these dynamic inputs. Following training and validation, the FKDPP model was implemented in the plant’s CENTUM TM VP control environment. During a controlled trial, the AI system operated the column autonomously for 35 consecutive days. While Figure 2 highlights overall achievements, the FKDPP system also delivered highly specific improvements in level control, heat recovery, and distur- bance rejection, as outlined below: • Precise maintenance of liquid levels within the distillation column. • Optimised use of waste heat, reducing reboiler energy consumption. • Elimination of off-spec product batches. • Real-time response to weather-induced process disturbances. The AI controller achieved these results without operator intervention, demon- strating autonomous handling of setpoint adjustments and disturbance rejection. Importantly, when the plant underwent rou- tine shutdown and subsequent restart, the AI model resumed operation without requir- ing retraining, underscoring its robustness. Results Quantitative results from the ENEOS case study highlight the value of FKDPP in refin- ery and chemical operations: Energy savings: Steam consumption for the controlled column was reduced by approximately 40%.

Emissions reduction: A corresponding reduction in CO₂ emissions was achieved through optimised heat recovery. Operational stability: Variability in key pro- cess variables was minimised despite fluc- tuations in feed composition and external temperature. Product quality: 100% of batches met required specifications, eliminating losses associated with reprocessing or disposal. Operator workload: Autonomous opera- tion reduced the burden on control room personnel, enabling a shift towards higher- level supervisory tasks. The algorithm’s ability to maintain con- trol without re-tuning further reduces main- tenance overhead, making it a sustainable solution with long-term benefits. Conclusion The successful deployment of FKDPP dem- onstrates the viability of reinforcement learning as a control strategy in opera- tional refinery environments. By addressing key limitations of traditional and earlier AI approaches – namely, sample ineffi- ciency and sensitivity to process variation – FKDPP offers a path forward for AI-enabled automation. Beyond technical performance, the AI system delivers measurable improve- ments in ROI, sustainability, and pro- cess resilience. Energy efficiency gains directly impact operating costs and car- bon intensity, aligning with broader indus- try goals for decarbonisation. Additionally, the system enables consistent quality and throughput, positioning it as a tool for maintaining competitiveness in volatile markets. The integration of FKDPP into refinery operations represents a significant step toward autonomous process control. As further applications are explored, ranging from three-phase separators to upstream and midstream assets, this technology is poised to play a key role in the next genera- tion of smart manufacturing systems.

To overcome these limitations, FKDPP was developed as a data-driven, self-adaptive control model requiring significantly fewer learning trials compared to conventional RL techniques. In simulation environments, it achieved stable control of complex pro- cesses such as distillation and decantation within about 30 learning iterations, demon- strating its rapid convergence capability. Unlike data-sensitive deep learning models, FKDPP is designed for resilience against process variability, enabling deploy- ment in real-world industrial systems with- out retraining for every operational change. Figure 1 illustrates this four-step process. FKDPP’s architecture is optimised to reduce sample complexity and maintain control objectives under disturbances. Integration into existing control systems is achieved through a dedicated Control AI Station operating at Level 2.5/3 of the auto- mation architecture, interfacing with the distributed control system (DCS) via Open Platform Communications (OPC) protocols. Case Study: Autonomous Operation of a Distillation Column A chemical production unit operated by ENEOS in Japan served as the testbed for FKDPP deployment. The unit includes a dis- tillation column previously managed via man- ual intervention, especially under varying ambient conditions and feed disturbances. The objective was to assess whether the AI controller could maintain product quality,

Autonomous control

Safe operation and improved productivity

Reduced costs and time loss

Two years

Only high-quality products were produced, so losses in the form of fuel, labour costs, time, etc. that occur due to production of o-spec products were eliminated

Areas that previously could not be controlled with PID control and APC were autonomously controlled by reinforcement learning- based AI (the FKDPP alg o rithm)

Managed and controlled with CENTUM VP integrated production control system

Simultaneously achieved safe operation and improved productivity, with stable quality, high yield , and energy saving

Figure 2 Summary of operational benefits observed from FKDPP deployment at ENEOS, including yield, safety, and automation gains

Contact: jagadesh.donepudi@kbc.global

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refining india 2025

Maximising alkylation unit throughput during the summer months

Rinav Shah and Lalit Mathpal reliance industries limited

the tube bundles in the last 10 exchangers were replaced with Curran-coated bundles. Although the reliability of the frequently fail- ing refrigerant condensers was improved due to restrictions on heat transfer by coat- ing, the exchangers’ condensing capabili- ties decreased and adversely impacted the refrigeration duty. The impact is more prominent in summer, with the higher cool- ing water temperature, while the effect is minimal during the winter. HTRI software was used to evaluate the duty impact of one condenser, and a con- tribution of 1% production loss was esti- mated per condenser. It was decided to replace the coated bundles in two out of 10 condensers with non-coated ones to restore heat transfer efficiency. The risk of fouling is addressed by enhanced cool- ing water flow and parameter monitoring. To ensure no reliability issues (fouling, leak- age) in the long term, the flow measure- ment frequency has been increased from once a quarter to twice a quarter, and the exchanger inspection and cleaning practice has been institutionalised every winter. Installing two additional Condensers A simulation study was used to validate the benefit of installing two additional con- densers. It shows that installing an addi- tional heat exchanger to each refrigeration condenser train can handle approximately 8% more refrigerant vapour flow and/or further subcool the refrigerant to a colder temperature. Cooler refrigerant/higher refrigerant flow reduces the temperature in the alkylation reactor, allowing a higher feed rate to be processed. A 3-4% pro- duction improvement is expected follow- ing the implementation of this scheme. These simulation findings were also con- firmed by actual operating data, which showed that under the same set of condi- tions and with colder refrigerant tempera- ture, higher plant throughput was achieved. Another challenge was to design a layout that considered space constraints and cost minimisation. The other important requirement for sus- taining the higher throughput is to maintain sulphuric acid regeneration (SAR) capac- ity at maximum. A SAR unit that undergoes corrosive service, has high reliability con- cerns due to frequent shutdown require- ments. Reliability upgrade drives for the SAR unit have also been initiated to ensure that SAR availability does not constrain achieving higher throughput. Conclusion This article discusses the optimisation of a refining alkylation unit using innovative, carefully planned modifications, designed to improve alkylate production by 8-10% during the summer months. Replacing non- coated tube bundles in two condensers has already yielded benefits this summer. The other two modifications are currently being implemented.

The alkylation process is an important cata- lytic refining process used to convert light olefins (such as butylene) produced in fluid- ised catalytic cracking units and cokers into a highly valued gasoline component called alkylate. Alkylate is one of the best gasoline blending components as it contains no ole- fins, no aromatics, very low sulphur, a low Reid Vapor Pressure, high octane, and good distillation properties. This makes alkylate an ideal blending component for meeting stringent emissions requirements. Jamnagar Refinery operates a sulphuric acid (H₂SO₄) catalysed C₄ alkylation unit to produce alkylate from liquefied petroleum gas (LPG) feeds. In alkylation, a light olefin feed (C₃ through C₅) reacts with isobutane in the presence of H₂SO₄ to produce alkylate, a branched paraffinic hydrocarbon with a high-octane value. Due to the high margin in alkylate, maximising alkylation unit pro- duction remains a key focus. A comprehen- sive study was undertaken to identify and resolve these limitations, aiming to maxim- ise production and profitability. While the unit operates efficiently in cooler months, summer throughput drops due to temper- ature-induced constraints in the refrigera- tion system. This article summarises the throughput constraint and improvement plan for maximising the throughput during the summer months. Alkylation reaction is favoured at lower temperatures. Higher temperature results in increased olefin polymerisation, lower octane, and higher acid make-up. Efficient heat management, including heat removal in the refrigeration section, is important for maintaining optimal reaction conditions and unit throughput. This exothermic reaction’s heat is managed through auto refrigera- tion, which involves vaporising some of the lighter hydrocarbons, primarily isobutane, from the reaction mixture. These vapours are then compressed and condensed in the plant’s refrigeration section. The alkylation unit is equipped with refrigeration compres- sors and multiple condensers. The refrig- eration section takes vapours from the alkylation reactors and the feed chillers, compresses and cools the stream, and then returns it to the chillers and reactors for fur- ther cooling ( Figure 1 ). Alkylation unit throughput is strongly dependent on refrigeration duty and very sensitive to chilled water (CW) supply tem- peratures. Refrigerant condensers play a significant role in condensing compres- sor discharge vapours for refrigerant liq- uid supply to reactors. During the summer, when heat losses are high and the cool- ing water temperature is high, the limits of the refrigerant condensers are reached. This causes a rise in compressor discharge pressure, leading to a reduction in com- pressor discharge condensation and thus refrigerant flow. Reactors operated at high reaction temperatures dramatically favour polymerisation reactions and higher acid consumption. The overall impact is a rise in

Refridgeration compressor

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Figure 1 Alkylation unit’s refrigeration system

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30.50 31.00 31.50 32.50 32.00 33.00 33.50

Figure 2 Summer cooling water temperature and alkylation throughput

around 5°C, compared to the design approach of <4°C. During the summer months, the wet bulb temperature exceeds 28°C, and due to the higher approach, the CW supply temperature increases, impact- ing the refrigeration condenser capac- ity and resulting in throughput limitation. The maximum actual cooling water sup- ply temperature during the months of May and June reaches 33.5-34°C, compared to the design supply temperature of 32°C. The increase in temperature versus design resulted in heat duty loss across refrigerant exchangers. The reason for the underperformance of the cooling tower is attributed to the age- ing/deterioration of the internals. The CT performance issue was studied by the RIL team in collaboration with the original equipment manufacturer (OEM) to evalu- ate the cooling tower performance and for- ward path. Based on the study outcome, it was decided to replace ageing fills with high-efficiency ‘trickle fills’, which offer bet- ter efficiency. The expected improvement in cooling water temperature is 1.0°C, which would improve the refrigerant condenser duty substantially. The estimated improve- ment is verified with actual operating data and simulation results. The implementation of this scheme is being done in a phased manner, as cooling tower cells are only available during the winter months. Heat Transfer Improvement These condensers historically had issues with fouling and frequent leaks, leading to production losses on each occasion. To increase the reliability of these exchangers,

reactor temperature, resulting in through- put restriction. A study was undertaken to maxim- ise alkylation throughput in the summer months, sustainably and cost-effectively. The objective of the study was to identify and implement engineering solutions that would: ○ Overcome summer-specific refrigeration condenser limitations. ○ Enhance cooling efficiency. In this article, the impact of refrigerant condenser limitations during summer con- ditions, which can restrict production, is discussed along with a plan for remedial action. The following three options were identi- fied and evaluated to enhance refrigeration duty for alkylation throughput improvement:  Cooling water temperature reduction by cooling tower cell fills replacement.  Replacing existing Curran-coated tube bundles with non-coated in two condensers to improve heat transfer.  Installation of two additional condensers to provide an additional heat transfer area. Cooling Water Temperature Reduction During the summer, the cooling tower tem- perature exceeds the design value and remains at and above 33°C. As the cooling water supply temperature increases, the compressor discharge pressure increases, while heat transfer, compressor flow, and alkylation unit decrease ( Figure 2 ). A 10-cell cooling tower is supplying cool- ing water to the alkylation plant. The cooling tower’s approach temperature (cold water temp – wet bulb temp) consistently remains

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