A. T. ALDAIEL, M. M. ALMULLA and M. A. ALNAJRANI, Saudi Aramco, Dhahran, Saudi Arabia; and K. CHAITANYA, A. DESHPANDE and V. HARISMIADIS,
Hyperion Systems Engineering, Modeling and Simulation, Pune, India
M
odern plants are heat integrated and are increasingly more auto-mated. Smooth processing con-ditions dull the operators’ skills in handling abnormal events. Likewise, fewer young people are entering refinery operations as senior personnel retire. To remedy the expe-rience gap, a Middle East refinery opted to use an operator training simulator for a new diesel hydrotreater. This program focused on training and fine-tuning the needed skill set for the hydrotreater opera-tions’ employees.BACKGROUND
Long production runs and few major upsets within the process diminish the oper-ators’ skills in handling infrequent or unfore-seen situations. In practice, this is unfore-seen with operating losses through poorly managed disturbances, delays in achieving maximum throughput, inability to follow customer demands or exploiting market opportuni-ties and unrealized profits. In addition, it is becoming increasingly more difficult to recruit and train new operators effectively.
The situation is exacerbated by the market competition for local skilled resources.1
An effective method that can support improved plant operator skills and main-tain process understanding and engineering analysis is a dynamic process simulator.2 This simulator can be either:
• Generic, standard or customized—
Providing only a typical representation of the actual process unit.
• Custom-tailored and detailed—
Accurately representing the end-user’s actual unit, by closely following the process and instrumentation diagrams.
There are arguments in favor of using a generic, standard or customized simulator
as a training tool (see Table 1). They are based on its immediate delivery and low cost. However the return value for these systems can be low; experienced operators will not see these simulators as relevant to actual plant operations.
A custom-tailored simulator is more effec-tive in training. It costs a fraction of a percent of a modern process unit, and the payback time can be significantly less than two years, depending on how it is applied.
The value to the corporation using such a simulator can be huge due to avoiding pro-duction losses or major plant incidents. Simi-larly, significant improvements are seen in safety and environmental compliance. Due to the greater understanding of the value that simulators can bring in improved operational
performance, operator training simulators are becoming a requirement for grassroots plants. If they are used before plant commis-sioning and for a detailed troubleshooting of the control system, a simulator can pay for itself before the plant is even operational and provide continuous value to the plant.3
This case history investigates a new oper-ator training simuloper-ator for a diesel hydro-treater plant in the Middle East.
DIESEL HYDROTREATING PROCESS Hydrotreating reactions take place in a fixed-bed reactor at elevated temperatures (300°C–400°C) and pressures (30–130 atmospheres), in the presence of a catalyst consisting of an alumina base impreg-nated with cobalt and molybdenum.4,5
Feed
Hydrogen-rich recycle gas Sour water
Product Gas to amine treater
for H2S removal
A schematic process flow diagram for a diesel hydrotreater.
FIG. 1
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OCTOBER 2011 HydrocarbonProcessing.comFig. 1 is a schematic of the equipment and process flow streams for a typical diesel hydrotreating (DHT) unit. Liquid feed (at the bottom left hand side in the diagram) is pressurized, preheated and mixed with hydrogen-rich recycle gas. The resulting mixture flows through a fired heater where
it is totally vaporized before entering the reactor. The hydrotreating reactions, i.e., desulfurization, denitrogenation, satura-tion and cracking, occur on a fixed-bed catalyst. The reaction effluent is partially cooled and flashed at the hot separator ves-sel. The vapor flow is further cooled. The
resulting mixture of liquid and gas enters the cold-separator vessel at about 40°C and 45 atmospheres.
Most of the hydrogen-rich vapor from the cold-separator vessel is recycled to the reactor, passing through an amine contac-tor to remove hydrogen sulfide (H2S). Any excess gas from the cold-gas separator vessel joins the sour gas from the stripping of the reaction liquid product.
The bottoms product from the stripper is the final product from the hydrotreating unit. The overhead gas from the stripper is flared off or recycled. The amine solution to and from the recycle gas contactor comes from and is returned to the refinery’s main amine gas treating unit.
MODELING HIGHLIGHTS
A commercial off-the-shelf dynamic process simulator software package was used to model in high fidelity and from first principles all plant equipment. A typical screenshot for a model flowsheet is shown in Fig. 2. Process modeling included:
• Oil assay. An oil assay with a series of pseudo-components was configured to represent the oil properties. About 35 com-ponents were used to describe the simulator material streams.
• DHT reaction kinetics. All reac-tion types (desulfurizareac-tion, denitrogena-tion, aromatics saturadenitrogena-tion, hydrocracking, etc.) were modeled. Reactions were tuned to match the heat and mass balance pro-vided by the process licensor. The model-ing accounted for impurities, like CO and H2O that could act as catalyst poison.
• Recycle gas compressor. Anti-surge control and compressor startup sequence were incorporated into the model. Thus, the operator could be trained in following the exact compressor startup procedures, either in distributed control-system (DCS) mode or in local mode.
• Hydrogen makeup reciprocal com-pressors. The manual loading and unload-ing provisions for compressor was modeled.
The operator can change the compressor load from the DCS only, exactly as in the actual unit.
• Gas-amine contactor columns. The H2S absorption in amine was modeled using a reaction in the column. Foaming, including liquid entrainment, was simu-lated when conditions were appropriate.
• Diesel quality. The final hydrotreated diesel product quality was matched to licensor data, i.e., ASTM D86 curve.
• All control loops were tuned, so that the reaction to disturbances is quick
Process model flowsheet in simulator.
FIG. 2
Total plant S/D 1
SH-001 H12
ESD logic application in simulator.
FIG. 3
TABLE 1. Types of training simulators available
Simulator type Definition Characteristics
Standard A typical unit Not accurate representation of the end user’s plant or control system.
operation
Generic A typical plant Not accurate representation of the end user’s plant or control system.
Customized Modified standard Seems closer to the end user’s unit operation or plant. Often, this or generic models similarity is limited to equipment and instrument tag-names.
Not accurate representations of the end-user’s plant or control system.
Custom P&ID based Accurate simulation of end user’s plant.
Modeling is based on P&IDs and a copy or accurate emulation of the control system.
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47but stable. A number of complex control loops were tuned, using the lambda tuning method.6 The controller tuning parameters obtained can be utilized as the initial values in the actual DCS to expedite commis-sioning.
• Emergency shutdown system (ESD) was modeled in the simulator, using a series of simple logic blocks. To facilitate trouble-shooting and monitoring of the shutdown system during abnormal conditions, the logic diagrams were used as backgrounds, and red/green colored feedback for true or false respectively, was used for signals going from the ESD to the DCS or to the field.
A typical screenshot of the ESD model is shown in Fig. 3.
• “Fast action” buttons have been provided for the draining and filling of hold-ups. This was done to ensure that the operator does not wait for long times dur-ing start-up and shutdown for a vessel to empty or fill-up.
System architecture. A typical opera-tor training simulaopera-tor (Fig. 4) is composed of three main elements:
• Instructor station
• Calculation engines
• Operator stations (i.e., DCS consoles).
The master simulator environment provides the necessary tools to prepare and seamlessly integrate the aforementioned elements:
• Instructor station. In this case, it was built in the native simulator system.
It contains graphics that are based on the DCS system and includes the field-opera-tor duties. It provides all the necessary tools for the operator to navigate through the plant, generate equipment malfunctions, create training scenarios, and review the performance of the operators. Typically, there is one PC used by the instructor.
• Calculation engines. The process model calculations are done in a series of
“engines.” The overall process model is divided over a number of smaller models.
These individual models are interconnected by multi-component streams, using physi-cal property information obtained directly from the simulator’s physical property and thermodynamic database. Each one of these models is running on a single CPU-core. A number of PCs may be used to run a process model.
• DCS engineering station. It per-forms all DCS functions (controller calcu-lations, alarm managing, etc.) and allows a control engineer to modify the database.
It is connected to the operator stations, as
in the real plant. The connection between the simulator master environment and the DCS engineering station is through a spe-cial link designed to allow it to function as an integral part of the dynamic simulation system, e.g., simulator starting/stopping, loading/saving initial conditions.
• Cross-reference tables in the simula-tor link process model variables, instruc-tor functions, etc. with the DCS and ESD input and output points.
In this particular project, one instructor station PC and three simulator worksta-tions were used. This was done to ensure that the simulator system can achieve at least 2 x real time (i.e., simulate the plant phenomena in half the time that would be needed in reality) and in all operating conditions. The workstations were con-nected to a DCS system—consisting of four dual-screen operator stations, one engineering station and two FCS servers, performing the control calculations. The
architecture of the delivered system can be seen in Fig. 5.
Malfunction and scenarios. A mal-function can be defined as an unexpected, abnormal occurrence, e.g., a valve that does not operate as commanded or expected.
The introduction of malfunctions is one of the most important aspects of simula-tor based training. They are used by the instructor to test a trainee-operator’s abil-ity to analyze, and to correctly respond to, similar challenges in the physical plant.
Without a malfunctions capability, simu-lator-trained operators would be capable of handling a plant only under normal operat-ing conditions. Malfunctions for operator training simulators can be classified as:
• Standard malfunctions. These are malfunctions that are automatically pro-vided by the simulator system and are accessible through the instructor station (e.g., valve failure to its safe mode, global
Simulator master
Instructor station DCS Engineering station
Operator station
Instructor station Color laser printer
Delivered simulator system architecture.
FIG. 5
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OCTOBER 2011 HydrocarbonProcessing.compower failure, etc.) Note: These standard malfunctions depend on the simulation software used; although similar between vendors, the standard malfunctions are not necessarily the same.
• Custom malfunctions. This refers to the special equipment malfunctions that the simulator vendor must configure, especially for the delivered simulator (e.g.
heat exchanger tube rupture, catalyst poi-soning, etc.)
• Generic custom malfunctions.
These are malfunctions that must be custom-designed and implemented in the simulator for all similar equipment, e.g., blockage for all filters, fouling for all heat exchangers, etc.
Custom malfunctions. In the simula-tor delivered, the main/starting instrucsimula-tor
station page contains a series of navigation buttons, leading to different categories of custom malfunctions. A part of the page can be shown in Fig. 6. Each page contains detailed schematics that can be used by the instructor for easier control of the malfunc-tions. These schematics include custom-ized trends, transmitter values, etc., and they support the instructor in training the operator. Fig. 7 is a typical implementation.
Training scenarios. Scenarios enable the plant instructors to record and replay predefined sequences of events. Such events may be simple, i.e., closing a valve or trip-ping a pump or executing a malfunction;
but they are quite complex as a plant nor-mal shutdown. All operator actions can be recorded and replayed by the instructor.
These simulator features contribute to
training operators on emergency situations and the plant operation procedures. Now, operators can receive hands-on experience for troubleshooting rare and complex situ-ations, and the instructors can closely track the operators’ activities.
For the delivered operator training sim-ulator modeling system, a number of pre-configured scenarios were incorporated into the model (Fig. 8). Some are listed here:
• Loss of feed
• Loss of recycle gas compressor
• Loss of amine feed to the low pressure amine absorber
• Fuel/pilot gas to furnace failure
• Steam failure
• Less feed to unit
• Loss of product pumps.
Trainee evaluation methodology.
The trainee operator evaluation is based on their ability to maintain the plant at its nominal steady state. In this event, steady state is characterized by a series of variables, their acceptable operational limits (e.g., HH/LL alarms or ESD triggering points) and their relevant importance. When a malfunction is triggered, the operator is expected to:
• Recognize the plant area to respond
• Understand what is not functioning correctly
• Mitigate any adverse effects.
The simulator system keeps track of the variables specified and reports the time that the variables in question are above or below the acceptable limits. The smaller the areas above/below these limits, the better the skills of our operator. A weighted aver-age of the response provides the “score” for each operator. This is shown schematically in Fig. 9.
Project milestones. The main project milestones are listed in Table 2. The typical work-breakdown structure for an opera-tor training simulaopera-tor is shown in Table 3. Comprehensive tests of the model are required and include:
Process battery limit
Part of the main navigation page, leading to a series of custom malfunctions.
FIG. 6
A detailed schematic for heat exchanger fouling and tube rupture malfunctions . FIG. 7
A typical screenshot showing the training scenario summary window. The “loss of recycle gas compressor” scenario is selected and ready to run.
FIG. 8
TABLE 2. Project milestones
Milestone Week into the project
Kick-off meeting 0
Preliminary design review meeting 6 Critical design review meeting 11 Model acceptance test 25 Factory acceptance test 50 Site acceptance test 54 Training simulator “ready for use” 56
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49• During model acceptance tests, local model stability tests, training scenario and custom malfunctions detailed review, plant shutdown and start-up should be done.
The earliest that modeling challenges are identified, the better. Accordingly, the simulator vendor will have enough time to review modeling without impact on the delivery schedule.
• Factory acceptance test for the train-ing simulator should be done as a dry run of the actual plant startup, and actual startup procedures and manuals should be used. Commitment to this approach should be obtained from all involved par-ties, including proponent, EPC contractor and simulator vendor.
• A simulator is a multi-purpose tool.
It should be used to identify early any DCS modifications or design changes required that would normally be uncovered during commissioning. A simple statistical analy-sis of the factory acceptance test punch-list items for the current training simulator proj-ect revealed that over 53% of the observa-tions were related to the design of the DCS or the ESD. Details are shown in Fig. 10.
Benefits. The main benefits from this grassroots plant operator training simula-tor are:
• Troubleshooting and validating the plant process control system:
o It was verified that the control sys-tem operates as intended, without generat-ing spurious equipment trips.
o The DCS graphics and controls were reviewed prior to plant commission-ing and updates were suggested; a number of observations were reported. The actual DCS was updated to incorporate these changes. For example missing graphics or graphics elements were identified; associa-tions of graphics with the DCS controls were updated; incorrect DCS connections were fixed.
o Design changes were proposed, such as adding air or power backup to cer-tain critical valves or motors.
o Reasonable estimates for the con-troller tuning parameters were provided;
these are realistic starting points for the commissioning of the actual plant.
• Reviewing the emergency shutdown logic:
o Cause and effect logic was rigor-ously tested on the simulator.
o Improvements were suggested and verified prior to plant commissioning. For example, delay timers were changed, and trip limits were reviewed.
• Verification of the plant startup and shutdown procedures. The factory accep-tance test was conducted as a dry-run of the actual plant startup and shutdown, using the detailed procedures provided by the EPC contractor. This allowed the par-ticipants a) to test the simulator system, ensuring that all objectives are met, and b) validate, clarify and improve the facil-ity operating manuals to be used for the actual startup.
• Facilitating the operator training:
o Simulator provided a series of cus-tom malfunctions and training scenarios
o Continuous personnel training and operator certification achieved
o Since the simulator was available six months prior to plant commissioning, the operators were fully trained on the new control systems functions, graphics and project configurations.
After model troubleshooting and deliv-ery of the simulator system, experienced operators commented favorably on the similarity between the dynamic response of the simulator and existing plants using the same technology. These factors are expected to play a significant role for the real plant, resulting in:
• A faster and smoother startup and achievement of the nominal steady state
• Increased process understanding for both engineers and operators
• Safer and more efficient operation under transients and abnormal conditions
• Longer plant runs and prolonged catalyst life, since extreme or adverse opera-tional conditions are avoided.
Status and future work. The DHT simulator was successfully delivered to the site six months before the actual plant start
635
Heater exit temperature, °F
Time below
A typical example of an operator evaluation.
FIG. 9
Factory acceptance test observations for current project categorized.
FIG. 10
TABLE 3. Work breakdown structure for the operator training simulator
Activity Effort, %
Model building 45
Project management, quality, 15 documentation
Instructor station 5
Integration and testing 12.5 Reviews, acceptance tests (factory, site) 10 Updates (plant data alignment) 7.5 Training and documentations 5 Total 100
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up. Since delivery time, the operators used the simulator extensively, obtaining confi-dence, learning about the plant behavior, and getting hands-on training on opera-tional procedures and in mitigating the effects of equipment malfunctions.
After the plant commissioning, startup and attaining the nominal steady state, the simulator was successfully updated to reflect the realities in the plant. Thus, it will continue to offer a) valuable insight to engineers for verification of plant design
updates, controllability and de-bottle-necking studies, b) continuous training and certification to plant operators, and c) increased value for the shareholders for the years to come. HP
LITERATURE CITED
1 Resnik, C., “Better Operator Ergonomics Increase Plant KPIs,” Automation World, December 2009.
2 Pankoff, J. A. Sr., Use a Competency-Based Approach to Develop High-Performance Workers, Hydrocarbon Processing, August 1999.
3 Harismiadis, V. I., “Earn two million dollars a year.
Dynamic Process Simulation: DCS Integration,
Dynamic Process Simulation: DCS Integration,