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Jul-2014

CO2 absorbers in LNG production: design pitfalls

Part 1: temperature control in a split flow absorber. To prepare gas for liquefaction, its CO2 content typically is reduced to 50 ppmv or below by absorption into an amine treating solvent.

Clayton E Jones, Nathan A Hatcher and Ralph H Weiland
Optimized Gas Treating Inc

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Article Summary

Most solvents are based on N-methyldiethanolamine (MDEA) promoted with lesser amounts of piperazine, although 2-(2-aminoethoxy)ethanol, known commercially as Huntsman’s DIGLYCOLAMINE® agent (DGA®) and BASF’s ADEG, has found use in this application.

There are several pitfalls in designing the CO2removal system:
• Absorbers that use fast reacting solvents such as piperazine-promoted MDEA may be subject to instabilities should operating conditions deviate significantly from process licensor recommendations.
• Sometimes energy consumption can be greatly reduced and solvent usage optimised if the absorber is operated with fully-lean solvent flowing at a low rate to the column top, and a larger semi-lean solvent flow to a location part way down the tower. This is a split-flow arrangement that may allow the top part of the absorber to be made quite a bit smaller diameter than the bottom part, thereby saving shell and internals costs. However, there is a possible effect on mass transfer performance which is the subject of Part 2 of the series.
• Split-flow plants can be especially sensitive to departures from normal operating conditions, to the extent that even a slight change in a crucial process parameter can lead to failure-to-treat by a very wide margin. In these cases, small changes do not lead to the expectedly small responses in performance. This is discussed in Part 1.

These pitfalls are by no means unique to treating gas in LNG production. For example, ammonia production where CO2 is removed to a few hundreds of ppm is subject to the same concerns. Hydrogen production and the manufacture of various synthesis gases are other examples. The commonality, however, is the removal of CO2 to concentrations measured in tens and hundreds of ppm using solvents having fast reaction kinetics with carbon dioxide.

The first item in this list, column instabilities, has been addressed for both absorbers and regenerators in other articles1,2. The focus of Part 1 of this article is an operational pitfall involving a split-flow absorber in an LNG unit. First, some of the basic principles on which mass transfer rate-based simulation relies are explained. Then, a detailed case study is used to expose a design and operational issue that caused an otherwise excellent design to fail.

Mass Transfer Rate-based Simulation of Amine Units

There are two fundamentally different methodologies for simulating any column used to separate mixtures of chemical species: ideal-stage and mass transfer rate-based. Calculations employing ideal stages have been used for about 80 years. The method is so old and well-understood it needs no exposition here. However, it suffers from a serious drawback—to connect ideal stages to real trays and tower packing, numerical values for tray efficiency and height equivalent to a theoretical plate (HETP) are needed. Unfortunately, in amine treating, there is no reliable way to determine the right values, other than using good quality data from an already operating plant. Of course, for a grassroots design there simply are no data. Thus, while the ideal stage approach can be used to fit the ideal-stage model to data, it must be honestly viewed strictly as a regression or fitting model, one that completely lacks any predictive power. Inability to predict performance reliably leads to uncertainty and oftentimes gross overdesign — this is a serious weakness.

One of the easiest ways to understand the principles of mass transfer rate-based simulation is by analogy with heat transfer. Heat exchangers have been designed this way for so long that after a first course in heat transfer we really don’t give much thought to the fact that the methodology’s basis is a heat transfer rate model. The simplest case is a shell and tube exchanger heating water with condensing steam on the shell side.

The shell-side temperature is constant at the saturation temperature of the steam, but on the tube side the water temperature gradually rises along the length of the tubes. If this heat exchanger were modeled as a single ideal stage, the outlet water temperature would be in equilibrium with the steam so it would be at the steam temperature regardless of the physical size of the exchanger itself. The exchanger’s efficiency in this model would be the value needed to achieve a “match” with the real measured outlet temperature. The idealized model had to be corrected empirically, after the fact. This certainly cannot be called predictive—it’s just a fit of a very poor model to measured data. Could this model be used to design another exchanger? Yes, but only if the conditions were the same. Could it be used to “predict” performance at other operating conditions (different water flow rate, different steam temperature)? The answer is ‘possibly’, but with decreasing reliability as conditions move away from those of the original, matching case. This is patently not the way we design heat exchangers. Yet, it is still the most commonly used method for designing much more expensive and complex mass transfer equipment.

Modern heat exchanger design is done using sophisticated software; however, the underlying principles have remained largely unchanged since long before the publication of Kern’s classic work3 nearly 65 years ago. Whatever the method used for carrying out the calculations, be it hand calculation or computer programs, heat exchangers are designed using heat transfer rate models. Correlations are used that relate tube- and shell-side film coefficients to flows and fluid properties, and then the heat transfer rate is calculated using these coefficients along with temperature difference driving forces and heat transfer areas. The engineer provides the exchanger geometry and specifies the design conditions (fluid flow rates and properties), and these are sufficient for the design to be done completely without engineer-supplied guesses. He is never asked for an efficiency of any kind, or for artificial parameters needed to patch up model inadequacies. This is a 100% predictive model—but only in the last 25 years has mass transfer equipment design and analysis been put on the same solid basis. Ideal-stage calculations still dominate, despite the availability of vastly superior methods. The penalty is often over design to compensate for the inherent uncertainty, and sometimes outright failure.

At its core, a mass transfer rate model focuses on the rate of exchange of chemical components between two phases as driven by the extent to which temperatures and species concentrations between phases are not at equilibrium. This is the very antithesis of the ideal-stage model with its assumption of perfect equilibrium, not disequilibrium. Figure 1 shows schematically two phases being contacted in some portion of the biphase on a tray or in a segment of packing within a column. The main premise is that the mass transfer process is characterised by interfacial areas and mass transfer coefficients in the vapor and liquid phases on either side of the interface. In no sense are these parameters adjustable any more than are the film coefficients used in heat transfer. The flow of high and low viscosity fluids across trays and over packing agitates the fluids and results in specific values for mass transfer coefficients.

Engineers are not free to pick and choose coefficient values to obtain the preferred result or some preconceived notion of what the separation should be. On the contrary, values of the coefficients are a function of fluid flows, fluid properties, and the mechanical design of the specific tower internals as expressed in well-established correlations. The parallel with heat transfer is extremely close. Tower performance is predetermined and predictable in exactly the same way and to exactly the same extent as heat exchanger performance. Every tray in an operating plant is a real tray. The continuous nature of contact in a packed column is handled by dividing the height into a large number of short segments and numerically integrating across the column. Each short segment has its own unique characteristic mass transfer parameters that depend on the particular packing (vendor, brand, material, size) in each segment and on the fluids and their flow rates. Both the simulated and real separation a column achieves depend directly on what specific internals are in the column. Mass transfer rate-based simulation has the authenticity that simply cannot be achieved with theoretical stages regardless of embellishments. This is the basis for the ProTreat® simulator, the original mass transfer rate-based tool used for the simulation of a wide variety of gas treating processes.


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