Overcoming CDU Challenges

Article by Sandeep Ram Mohan

How refineries can overcome CDU challenges to boost the bottom line

ENERGY makes up approximately two-thirds of a refinery’s operating costs (not considering crude oil costs).1 The crude distillation unit (CDU) separates crude oil into different products within the refinery that are then processed to create automotive fuels or petrochemicals.

 A typical CDU requires unprocessed crude oil to be heated to temperatures of 360°380°C2, which consumes an equivalent of approximately 2% of the crude oil the CDU processes3. The CDU operation impacts the rest of the refining process units significantly, making it critical to a refinery’s bottom line.

This article looks at the operational challenges refineries face as they look to drive optimal CDU performance and considers how they can use technology to develop effective solutions. 

Scoping the challenges

Changes in crude oil composition can significantly impact the quality and quantity of a refinery’s products. This limits the refinery’s options in the crude oil it can process, as it is constrained by its existing processes and facility, as well as the products demanded by its market.

Refineries must accurately analyse the economic and processing feasibility of the crudes available, to choose the most optimal crude or blend. Even for a refinery processing crude oil from the same source, the composition of the crude oil extracted from the same well can vary with the depth of the well and the year of production.4

The nature of crude oil introduces further analysis challenges. Crude oil is a complex combination of hydrocarbons. Approximately 600 different hydrocarbons have been identified in crude oil5. Analysing these complex crudes or blends, by breaking down their compositions and representing them in terms of numerous sub-components can be tricky.

6070% of the energy required to heat crude oil is recovered from hot streams tapped out of the crude distillation column using a network of heat exchangers called crude preheat trains6. These exchangers are frequently fouled by the crude oil they heat, diminishing their heat transfer capacity and leaving the burden of heating crude oil to the required temperature on the fired heaters. The additional fuel burned makes up for the heat transfer loss due to fouling and adds to operating cost. Fouling also increases hydraulic resistance in the heat exchangers.

 Throughput reduction, by way of increased hydraulic resistance, is considered the most significant cost of fouling for most oil refineries.7 Nevertheless, cleaning heat exchangers can take 314 days, depending on the severity of fouling and can cost up to US$40,00050,000 per heat exchanger, not to mention the lost revenue from the downtime incurred.8 The economic benefit from cleaning is not the same for all units, so the challenge for refineries is determining the right cleaning schedule. Most refineries predict fouling based on historic trends. In such cases, crude compositions or process conditions, which both impact fouling levels, are accounted for in a very limited way9

Additionally, the various types of heat exchangers employed in a CDU are difficult to analyse operationally without the refinery operators’ expert knowledge.

Another challenge is around visibility of column operations. To understand the internal operation of a distillation column, hydraulic and thermal analyses of its operation need to be completed. The complexity involved discourages operators. The sensitivity of the column operations for different operational factors and the implication those operations have on profitability makes it crucial for the refinery’s business health.

Flooding is the most common capacity limitation in distillation columns. When a column floods, tray efficiency diminishes, separation deteriorates and products are produced off-spec. Flooding can also cause issues such as cavitation of the bottom pump. To avoid the onset of flooding, operators cut throughput, which causes the plant to lose capacity10. This highlights how important it is for refinery operators to have clear insights into the operation of their crude distillation columns.

There are also issues with the complexity of the CDU. Typically, it entails multiple recycle streams running between the crude distillation columns and the heat exchanger units in the crude preheat train. The flowrate and temperature of each stream depends on the functioning of the distillation column, affects the crude preheat train’s heat transfer and thereby the fuel consumption of the fired heaters. Accurate analysis of the operation of such integrated systems requires multiple iterations.

Finding a solution

The good news is these solutions exist and are used globally with success. The only step left is for refineries to adopt them. The following capabilities are essential to overcome the challenges mentioned in the preceding section.

High-fidelity asset management

Complex combinations of hydrocarbons in crude oil pose a challenge when characterising a crude oil assay or blend of assays. To accurately predict flowrates and properties of process streams in a refinery, one must characterise every stream in the refining process in terms of a uniform set of components. Assay management simulation software can break down the constituents of crude oil or any blend of crude oils into a series of distinct hypothetical components.

 These standard hypothetical components are used to represent every stream across the refinery model. This enables the process simulator to deliver an accurate prediction of both the yields and properties of streams at any point in the process.

Integrated heat exchanger models

Accurate simulation of heat exchanger operations in the context of a broader process simulation is important here. Advancements in process simulation technology allow engineers to put rigorous models of heat exchangers into the process flowsheet from within the integrated software, without having to switch between different software.

 The mechanical information in heat exchanger models helps simulate or predict potential operational issues. Fired heater models can also accurately simulate the amount of fuel consumption. It is worth noting, however, that the improvement in heat transfer, from cleaning heat exchangers, may not result in an equivalent saving in fuel consumption.

Better solver technologies

The nature of the distillation process warrants a rigorous thermo-hydraulic analysis of the distillation column operation, made possible by the latest advancements in process simulation technology.

Process optimisation and model calibration are significant challenges that arise when dealing with simulation models of process units with multiple recycle streams and integrated heat exchanger networks, such as in the CDU. This is due to the complexity in integrated systems that requires multiple iterations before the solver in the process simulator can converge the integrated model. Conventional “sequential modular” solvers used by process simulators can take an inconveniently long time to converge such models. However, new “equation-oriented” (EO) solver technology allows models to be solved quicker by solving them concurrently.

Refinery data connectivity and ease-of-use

Any simulation model is only useful if it accurately represents the current operating conditions of a process unit. Considering that refineries operate in a continually-changing environment, the ease of calibration of simulation models is of paramount importance while considering any process simulation technology.

The value of any solution also depends on its ease-of-use. The key is to give equal focus to developing powerful features and making the user interface (UI) intuitive. Latest process simulation software has enhanced UI, which reduces the learning curve for new users.

Looking ahead

The technologies mentioned above can be brought together to deliver considerable savings to refineries. Ultimately, the refinery can realise substantial savings at every level, from crude preheat train monitoring (using simple heat exchanger models) right through to integrated CDU monitoring.

Refineries today have the technology available to run their assets at maximum capacity while reducing operational risk, although not all have leveraged its value. Nevertheless, improvements in CDU operations can bring a considerable boost to refineries’ bottom line and many have already started significantly profiting from these technologies.

References

  1. Emerson. (2012). Energy Efficient and Always On-Spec. Round Rock, Texas: Emerson Process Management.
  2. Gorak, A, & Schoenmakers, H (2014). Distillation: Operation and Applications. Oxford: Elsevier.
  3. Gadalla, M. (2012). New energy efficient redesign of an existing crude oil distillation unit. Cairo, Egypt: Chemical Engineering Dept at The British University in Egypt.
  4. Jokuty, P. (1999). Properties of crude oils and oil products. Ottawa: Environment Canada.
  5. Giles, H. N. (2003). Crude Oils. In A. C.-2. Products, & S. J. Rand, The Significance of Tests of Petroleum Products: A Report. Bridgeport, NJ: ASTM International.
  6. Yeap, B. L. (2003). Designing Heat Exchanger Networks to Mitigate Fouling, PhD Thesis. Cambridge,UK: Cambridge University, Department of Chemical Engineering.
  7. Yeap, B. L., Wilson, D. I., Polley, G. T., & Pugh, S. J. (2004). Mitigation of crude oil refinery heat exchanger fouling through retrofits based on thermo-hydraulic fouling models. In Trans IChemE, Part A, Chemical Engineering Research and Design (pp. 53-71). Cambridge, UK: Institution of Chemical Engineers.
  8. Joshi, H. M., & Brons, G. (2003). Chemical Cleaning of Oil Refinery Heat Exchangers - The Need for a Joint Effort. Heat Exchanger Fouling and Cleaning: Fundamentals and Applications. Santa Fe, New Mexico: ECI Digital Archives.
  9. Coletti, F., & Macchietto, S. (2009). Refinery pre-heat train network simulation undergoing fouling: Assessment of energy efficiency and carbon emissions. International Conference on Heat Exchanger Fouling and Cleaning VIII. Schladming, Austria: www.heatexchanger-fouling.com.
  10. Kister, H. (2016, March). How to troubleshoot tower floods. The Chemical Engineer, pp. 42-49.

Article by Sandeep Ram Mohan

Senior product specialist, Aspen Technology

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