REFINING INDIA 2025

refining india 2025

Data Analytics Evaluation The application of data analytics in pro- cess industries has improved significantly, due to the development of next-genera- tion information technologies, such as the Internet of Things (IoT), Big Data, Cloud Computing, ML, and AI. It has evolved from descriptive analytics, which focuses on what happened, to diagnostic analyt- ics, which focuses on why it happened, to predictive analytics, which focuses on what will happen, to prescriptive analyt- ics, which focuses on what should happen ( Figure 3 ) . In prescriptive analytics, decision aid is the open loop, whereas decision auto- mation results in the closed loop. We endeavour to achieve ‘automation wher- ever possible’, minimising the need for human intervention to carry out necessary actions.

models being used in process industries. There are multiple ways to build these models, and the following are the generic steps involved in the model development process after identifying the appropriate use case ( Figure 4 ): ○ Identifying the required dataset. They may be available in a single source or mul- tiple sources. ○ Sanitising the data. ○ Exploring correlations among them. ○ If the goal is to identify a good operating zone, data will be segregated with respect to operation conditions of good vs poor. Segregated clusters and their behaviours will be studied in detail. The contributing parameters for deviations from the best will be identified, and the model will be tuned and validated. ○ Once the model is validated, it will be deployed online. The model will provide insights and guide operators to reach the optimal operating zone in real time. Process Digital Twins – New Way of Working A process digital twin consisting of real- time process simulation models and data

analytic models offers a new way of work- ing by providing near real-time optimisa- tion for improving operational excellence and uncovering hidden opportunities: ○ It provides a precise view of operational constraints and capabilities. ○ Real-time monitoring of key perfor- mance indicators of process, equip- ment, energy, and APC enables us to identify and close the performance gaps immediately. ○ It provides insights into the best timing for catalyst replacement during its end-of- run conditions, based on remaining cata- lyst life, increased utilities consumption, and yield patterns. ○ Real-time early event detection and pre- dictive and prescriptive models will help to avoid process upsets and interruptions. ○ A real-time process reliability model helps to avoid corrosion and erosion issues. ○ Faithful ‘steady-state’ plant models will be available for offline ‘what-if’ analy- sis for various plant requirements, such as: ▪ Identifying alternate feedstocks that

with high solvency and low pour point, have a promising future, as these can be blended in variable quantities with Group II/III par- affinic base oils to achieve the set of proper- ties required for specific applications. There is an overcapacity situation for all types of base oils, and naphthenics are also affected in the same way. In the future, any increase in production is likely to come from enhanced operating rates alone, as no major capacity addition is envisaged in this space due to the scarcity of naphthenic crude. However, the silver lining in this area is the patents for the production of NBOs from LCO, slurry oils, and other such feedstocks. If the availability of NBO is enhanced, its demand may grow significantly due to the inherent advantages of using these base oils in specific situations. Thus, there is a possibility of producing NBOs in India if a feedstock tie-up can be done on a long-term basis for naphthenic crude. Alternatively, the availability of feedstock from the RFCC unit can be considered by Indian refiners for captive consumption. The FY2024-25 data indicate an average cost, insurance, and freight (CIF) India price of $1,245 per ton. Adding 5% basic cus- toms duty to it increases the price to $1,307 per ton. The cost of production of NBOs var- ies with fluctuations in crude prices, availa- bility of NBO in specific regions, severity of demand, and logistical issues. A simplistic estimate, ignoring logistics cost and considering FY2024-25 figures for crude oil prices (Indian basket), indicates that the average CIF India price for NBO (all grades combined) along with conversion costs – including the cost of utilities and off- sites, labour, maintenance, and storage and handling – at the rate of 70% of the feed cost, gross margin during the year works out to $260 on a per ton basis. There may, however, be variation in the margin when project-specific figures for utilities and labour costs are used for individual projects. Nevertheless, the NBO project indicates positive margins and provides comfort to the investor, though it would be prudent to carry out detailed feasibility studies of the project before any decision is taken. can be processed within the existing hard- ware to maximise the profits. ▪ Changes in operating conditions for the respective changes in product/grades, changes in feed/product pricing, and more. ▪ Conducting debottlenecking and revamp studies to identify bottlenecks in the plant for capacity enhancement. ▪ ‘End-to-end optimisation’ covering all the unit operations of process units The process digital twin is a result of col- laboration among multiple departments at Reliance. There is a clear roadmap for implementing process digital twins across all process units in the coming years. The significance of the process digital twin evolves from monitoring and control to continuous optimisation, ultimately aiming for full autonomy in the near future. References 1 Gao, L.B., Jia, M.D., Liu, D.Q. (2022) Process digital twin and its application in petrochemical industry. Journal of Software Engineering and Applications , 15, 308-324.https://doi.org/10.4236/ jsea.2022.158018.

Data Science/Data Analytics Model Development for Process Industries

Early event detection, developing soft sen- sors, and identifying good operating zones are the best examples of data analytics

○ Greases also contain mineral as well as bio-based base oils. NBO forms a small part of the total base oils. ○ Other applications where NBOs are used include refrigeration oils and lubes/process oils used in cold climatic conditions. Global Capacity and Production/Consumption of Naphthenic Base Oils Global capacity for NBOs is in the range of 6 MMTPA spread across the US, China, Brazil, the Netherlands, Sweden, Germany, and Japan. Against this capacity, the pro- duction is in the range of 3.5 MMT, indicat- ing an operating rate of 58%. The operating rate in NBO capacity has remained low due to its niche applications and traditionally higher prices than those of paraffinic oil, as well as the preference of societies to use cheaper oil wherever possible. Figure 2 shows the global capacity spread for NBO in the year 2024. Among the producer countries for NBOs, the US is the largest producer and a major exporter to the rest of the world. China is both the importer and exporter of it. At the regional level, the US is a major exporter, whereas China and Japan are largely bal- anced. All other regions are in deficit in the product. The global past trend in production/ consumption of NBOs is shown in Table 2 . Indian Market for Naphthenic Base Oils Considering the Indian market space, the entire quantity of various grades of NBO is imported. The consumption of NBOs in India during the financial year 2024-25 is in the order of 135 KT. More than 85% of this import during the year was from two coun- tries – the US and Sweden. Brazil, China, Japan, and Belgium accounted for the bal- ance of imports. Ergon Refining, Nynas, and Calumet Refining accounted for 80% of the total imports of NBO in India. Apart from the supplies directly from the producers, some trading companies are also active. Most of the consumption falls in the vis- cosity range of 9 to 10 cSt, 18 to 23 cSt, 90 to 100 cSt, and above 900 cSt @ 40 o C ranges. Transformer oil is the largest outlet for NBOs, followed by rubber process oil or

Lube fractions

Ranate Dewaxed lube fraction

Dewatered & distilled naphthenic crude oil

Step 2: Solvent extraction

Step 3: Chill dewaxing

Step 1: Distillation

Step 4: Hydronishing

Naphthenic base oil

Solvents

Gases, naphtha, SKO, residue

Aromatics, polars, sulphur, nitrogen

Wax

Figure 1 Block flow diagram for production of naphthenic base oils

Miscellaneous applications 6%

Japan 3%

Brazil 1%

Germany 6% Netherlands 3%

Transformer oil 32%

Greases 10%

Sweden 7%

White oils 14%

USA 45%

China 35%

Global capacity - 6 MMTPA

Rubber process oil / tyre oil 24%

Metalworking uid 14%

Figure 2 Global capacity spread for naph- thenic base oil: 2024

Figure 3 Consumption breakdown of naph- thenic base oils in India 135 KT (2024-25)

the US is likely to remain a surplus coun- try, while all other regions are expected to go into deficit for NBO by the end of the upcoming decade. Lately, the focus on sustainability has led to developments around re-refined lube oils, which may impact the requirement of virgin lubes, specifically in the case of paraffinic lubes. Alhough the collection and refining of lubes is a challenge, there are technolog- ical advancements in achieving the proper- ties of Group II and even Group III base oils. However, as the Group I paraffinic base oils capacity is being deinstalled and the capac- ity for Group II and Group III paraffinic base oils is being enhanced, the solvency of these oils is being sacrificed. This is where NBOs,

tyre oil, metal working fluids, white oils, and greases. The consumption breakdown of NBOs in India by end use for the year 2024- 25 is given in Figure 3 . In all these applications, generally a blend of paraffinic and NBOs is used. Hardly ever is any product produced using pure NBO. Outlook for Naphthenic Base Oils Major demand for NBOs is expected to arise from Asia Pacific, including China, Japan, and India, which are anticipated to be the major contributors. Going forward, the demand for NBO is likely to register a composite growth rate of 4% to 5% per annum over the next decade if the ‘business as usual’ scenario is considered. Globally,