2011Modeling And Simulation Case Study of a Batching Operation of Crude Oils In a Pipeline System

Copyright 2011, Pipeline Simulation Interest Group
This paper was prepared for presentation at the PSIG Annual Meeting held in Napa Valley, California, 24 May – 27 May 2011.
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A BSTRACT
An existing 20″ pipeline system is being modified to operate in a batching mode to integrate the production of a new field. Two dismissible crude oils will be pumped in a specific batching scheduled to minimize the mixing volume and avoid further contamination of the highest quality oil. The fluids to be carried by the pipelines are primarily crude oils with density differences of approximately 15% and dynamic viscosity ratios up to 12.5. Both the transient response and steady-state analysis are being performed for each of the two pipelines and the entire system to determine its operating constraints and estimate the batch volume to be received at the end facility. The conducted analysis estimates the contaminated interface volume in this pipeline segment for various pipeline operating conditions. Determination of blending interface was calculated by using a pipeline simulation approach.
From the pipeline modeling, it was observed that the mixing interface is slightly larger when the lighter oil batch is followed by the heavy oil. In addition, results indicated a similar mixing trending of the two fluids when the batching cycle is modified. One of the critical parameters in the calculations is the dispersion coefficient that is linear dependent of the molecular diffusion coefficient. Thus, a parametric analysis was included in the estimation of the volumes for both cases, since an exact diffusion coefficient value was not available for these types of crude oils. The pipeline modeling results provided a good estimate of the volume interface. The mixing volumes calculated by this
approach are not only relevant for the operational stand point of view of the pipeline, but they are good indicators for the economic feasibility of the pipeline operation and project expansion. Thus, this study presents results from the pipeline modeling and covers the basic parameters that will affect a batching operation of two different fluids.
I NTRODUCTION
The oil transport system under consideration is composed of an existing 84 miles of 20″ diameter pipeline connecting Oil Center “A” (OCA) to a refinery facility. In addition, a 20″ diameter pipeline that runs from another Oil Center “B” (OCB) ties into the OCA pipeline at a node junction. Therefore, from the node junction to the refinery facility, both systems share a common 20″ pipeline that travels approximately 73 miles through a relatively downhill terrain. The two oil centers are managed by different operators, and they provide oil with different characteristics. Therefore, the operation of the system is based on a batch transport philosophy.
The design batch transport system has been performed by flow rate control at oil centers and pressure control at the refinery receiving facility. However, a production increase is anticipated from OCA. Thus, the transport philosophy has been modified to adjust this increment of capacity. The proposed operating method is based on pressure control at the oil center. Thus, maximum flow capacities will be restricted by the MAOP of the system while variable flow rates will be imposed. The targeted production will vary from 4,300 GPM to 3,700 GPM at the light crude oil center, OCA, while OCB was scheduled to maintain a constant rate of approximately 1,500 GPM.
The most remote location is the light crude oil center, OCA, which is at an elevation of approximately 1,200 ft above sea level (ASL). Crude oil is pumped upslope to the top of a mountain at approximately 4,300 ft ASL, and then it travels downhill to the refining facility. In the downhill path of the OCA pipeline is a junction connecting a pipeline originating from the heavy crude oil center, OCB. OCB has an elevation
PSIG 1111
Modeling and Simulation Case Study of a Batching Operation of Crude Oils in a Pipeline System
Augusto Garcia-Hernandez, Southwest Research Institute®
2 AUGUSTO GARCIA-HERNANDEZ PSIG 1111 of approximately 3,500 ft ASL, and the crude oil is pumped
downhill to the junction at node, with an elevation of
approximately 1,650 ft ASL.
A multi-product pipeline is being used to transport two
different products in sequence in the same pipeline.
Therefore, there is no physical separation between the
different products. Some mixing of adjacent products occurs,
producing an interface between the two fluids. This interface
is removed from the pipeline at receiving facilities and
segregated to prevent contamination. However, the proper
determination of the interface length and volume is critical
from the operation and economical standpoint. If the interface
length is underestimated, it will cause a contamination of a
good quality product. If an overestimation occurs, it represents a loss in profits since a good quality product may be sent through an unnecessary refining process. Therefore, a very detailed analysis of the mixing interface and volume was conducted through a pipeline modeling of the entire system. This modeling effort includes steady state and transient conditions as well as the batching operation and its corresponding sequences.
P IPELINE M ODEL
SwRI developed a 1-D pipeline fluid model of the existing facility to simulate normal operation of the pipeline and estimate batches lengths and their properties. The system model includes the fluid sources originating at the oil centers, all piping between the oil centers and refining receiving facilities, and the automated systems that are currently in place. This analysis has been performed on the existing 20″diameter pipeline and includes physical processes and parameters such as heat transfer, friction losses, valve operation, elevation profiles, etc. The analysis quantifies the batch volume and estimates the mixing zone for a normal batching cycle operation. An example of the cycling operation is presented in Figure 1.
Both the transient response (batching cycles) and steady state analysis has been performed for each of the two pipelines and the entire system. A steady state model has been used to obtain the initial conditions for the transient modeling. Steady state conditions were simulated based on the normal operating conditions. Steady state flow was also verified with the pipeline modeling, considering all the pressure constraints of the system, such as MAOP of the pipeline, maximum delivery pressure of the oil centers, minimum pressure at the highest elevation point to avoid slack conditions, and maximum pressure at the junction and refining facility. Transient scenarios have been simulated based on the normal batching sequence established for this system. The transient scenario includes valves switching, flow rate ramp-up and coast down for each facility, as well as changes of the pressure control set point at the refining facility.
Figure 1. Batching Cycle between the Two Oil Centers The hydraulic pipeline model was built using a commercial pipeline simulator. A schematic of the model is presented in Figure 2. The built pipeline model was debugged to ensure that the information inputted is correct and the software algorithm is computing the right values. Steady state cases were simulated to refine and validate the model against operating data. A good agreement between the model predictions and the real data was obtained in this validation.
Figure 2. Schematic of the Pipeline System
The computational models developed include the following characteristics and elements:
∙Main process boundary conditions, constant flow, or pressure at the inlet and outlet of the pipeline systems.
∙Pumping stations’ performance characteristics and operating conditions.
∙Ambient temperature (summer case).
∙Recycle loop for each pump and a bypass valve for each station.
∙Fluid properties at various temperatures such as viscosity,
density, vapor pressure, bulk modulus, diffusion
coefficients, etc.
Batch
Batching Cycle
OCA
OCB
Pumping Time [hrs]
time, 3.4 hrs dead time
PSIG 1111 Modeling and Simulation Case Study of a Batching Operation of Crude Oils in a Pipeline System 3
∙A slightly compressible liquid (SCL) equation of state was used, as it allows for batched tracking of fluids, blending, and definition of several liquids with their respective percent composition.
∙The equation of state diffusion used is based on the second difference in density. Therefore, the majority of the diffusion occurs at the start of the batch where the density difference is sharpest, but some diffusion occurs along the entire length of the piping system. This diffusion parameter depends on the Reynolds number and type of crude oil transported and it may be tuned to match actual pipeline diffusion by increasing or decreasing the amount of diffusion. Therefore, a sensitivity analysis was conducted considering equivalent diffusion coefficients as references to improve the modeling results.
∙Piping layout, geometry, and elevation profiles.
∙Surrounding average ambient and soil temperatures based on the summer conditions.
∙Heat transfer coefficients for the pipelines, coatings, and soil.
∙Valves are part of the model to allow the start-up and shutdown of the pumping stations and the isolation of specific pipeline branches or sections.
Modeling Results
Steady State Results
The pipeline computational simulations were performed on the pipeline system and included physical processes and parameters such as heat transfer, friction losses, valve operation, elevation profiles, etc. The analysis quantified various parameters such as pressure, velocity, fluid properties, and temperature along the pipeline for the different operating conditions.
The modeling approach includes an initial verification of the steady state conditions of the pipeline system when the light and heavy crude oils are flowed separately. Flow rates provided were considered as initial values and then they were adjusted based on the constraints of the system. The maximum allowable operating pressure (MAOP) was the limiting factor for determining the maximum flow to be delivered in the pipeline system. In addition, other critical points were the junction node, mile 7 of the OCA – junction line, and oil pumping facilities. Therefore, minimum, normal, and maximum flow rates to be delivered for each oil center were established before starting the transient sequences and batching cycles. Examples of the hydraulic profiles for some of the simulated flow rates were generated, and they are presented in Figure 3 and Figure 4. Hydraulic profiles illustrate values of temperature, pressure, density, elevation, MAOP, and flow rate for the OCB – junction node – refining facility system, as well as for the OCA – junction node – refining facility system. In order to maximize the flow rate from both facilities, the pressure set point at the receiving refinery was adjusted considering a minimum value of 152.3 psig as a constraint. Another important factor was the pressure at the peak locations of both pipelines. A minimum pressure above the vapor pressure of the fluid was maintained with some margin to avoid slack conditions in the pipeline system.
Figure 3. Steady State Conditions Profile from OCA to
Refinery Facility
Figure 4. Steady State Conditions Profile from OCB to
Refinery Facility
For the batching cycles, the normal flow rate of each oil center considering all the pressure constraints and set points of the entire system. Batching schedules and pumping duration were based on the data presented in Table 1. Thus, the batch duration determined the amount of fluid received at the refining facility since the flow rates were adjusted based on the steady state conditions obtained previously.
Transient sequences were defined as a real pumping-pipeline system since the pipeline simulation was fully dynamic and Steady State Conditions for the Light Crude Oil Center
Pumping 6300 GPM
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Steady State Conditions for the Heavy Crude Oil Center
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4 AUGUSTO GARCIA-HERNANDEZ PSIG 1111 interactive. Switching the batches included a normal
shutdown of the pumping stations, considering flow
recirculation prior to stopping the pumping action and then isolation of the pipeline system with the line break valves. Thus, the pressure level in the pipeline reduces during the shutdown of the station. A linear flow ramping down was considered for stopping the pumps and a 2nd degree polynomial curve was utilized for closing the recirculation valves. Thus, high transient pressure surge was avoided during the shutdown of the pipeline system. Pressure reflections were observed within the normal range. Dead time of the pipeline was used for the start-up cycle, valve line-up, and initial flow ramping. Starting a new cycle involved a series of combined events, such as flow ramping and continuous adjustments of the pressure set point (PSP) at the receiving facility. PSPs were regulated based on the pressure at the pumping facilities and junction node. For example, during the transition of the light to heavy crude oil batch, the PSP of the refinery facility was initially adjusted to 330 psig and then it was ramped down to 152.3 psig, while the flow rate at OCB facility was changing from approximately 6,400 GPM down to 4,900 GPM since this batch was pushing a much lower viscosity fluid. Thus, the system DP/DL changes over time as the batch moves through the pipe. A steady state condition was reached after all the transient events were completed; thus, a PSP of 152.3 psig at the refinery facility and a flow rate of 4,935 GPM from OCB are maintained for the rest of the batching period. A detailed description of the transient sequences utilized during a batching cycle is presented in Table 1. A typical batch cycle will involve start-up of the main and booster pumps with the station in recycle mode, establish pressure set point at pumping facility, pressurization of the pipeline to avoid slack conditions, set back pressure control at receiving facility, smooth opening of the valve at the receiving facility, start main pumps, and close the station recirculation lines to stabilize the flow.
Figure 5 shows how the batch from the OCB facility displaces the OCA product from the pipeline. The change is density which indicates the presence of a different batch in the
significant transthermal effect is observed when a batching cycle is initiated. That thermal effect affects the viscosity and density values of the flowing fluid to some extent. In addition, the drastic change in viscosity produces a surge in the pressure losses that have to be monitored to avoid any critical surge pressure that could affect the integrity of the pipeline.
Table 1. Batching Schedules and Sequences Used in the
Transient Simulations
Figure 5. Transient Temperature and Density Profiles for the Heavy Crude O il Pushing the Lighter Oil.
The contamination level of the interface volume is affected by the change in viscosity and density along the pipeline due to the temperature and the batch composition effect. Parameters, such as transport velocity of the fluid and Reynolds numbers, are very critical for the mixing or blending phenomenon that occurs during a batching operation. The growth of the mixing interface is determined for various parameters, such as thermal effects during start-up and shutdown of the pipeline, methods of start-up and shutdown, line pressuring, and transient effects of the system (dynamic of the pipeline system). Another important phenomenon that affects the length of the interface volume is the compatibility and diffusion of the products being transported. In this case, the presence of two different oils minimizes that effect. However, the diffusion is an
PSIG 1111 Modeling and Simulation Case Study of a Batching Operation of Crude Oils in a Pipeline System 5
important factor to successfully estimate the mixing interface that occurs during a batching operation. For the simulations performed, a diffusion value was considered within the normal value for these two types of oils. However, this value could be adjusted after the pipeline system is operated to obtain more accurate results. Diffusion coefficients are usually determined by experimental testing of the fluids or empirical correlations. In the case presented in this study, correlations provide a wide range of value of diffusion coefficients due to the presence of heavy hydrocarbons. However, standard values were used based on the type of crude oils.
Figure 6. Transient Temperature and Density Profiles for
the Light Oil Pushing the Heavy Crude O il Transient Results
An entire batching cycle was simulated for the pipeline system. This cycle includes pumping light oil first followed by heavy oil and then light oil again. Pumping times were set as specified. Moreover, pressure set points were adjusted based on the pressure constraints of the system and the pumping limitations for the batching operation. Thus, volumes received at the refining facility were observed to be within the expected values. All transient results were obtained for the entire pipeline system including each pumping and receiving facility. Those results are presented in Figure 7 through Figure 12. The pressure transient effects observed in the pipeline system are more critical during the start-up of the pumping facilities due to change in momentum and fluid properties when a new batch is introduced in the system. In addition, various pressure constraints of the system, such as minimum pressure at the highest elevation points and MAOPs values, were considered.
Transient results presented in Figure 12 show the batch size based on a density difference criterion. In order to recognize the presence of a new batch, the density values were monitored over the entire batch cycle at the receiving facility. Thus, a quality criterion was used to determine the actual limit
of each batch. A 99.8 - 100% density criterion was used to identify the limits of the mixing and batch volumes. In addition, the pressure set points (PSP) adjusted at the refinery facility during the batching cycles are presented in Figure 7 and Figure 8.
Figure 7. Transient Events Results at the Refinery Facility
during a Batching Cycle
Figure 8. Transient Events Results at the Refinery Facility
during a Batching Cycle The PSP at Refinery was maintained constant at 345 psig when OCA was pumping at 936 psig. The flow rate ramped up from 4,670 GPM up to a steady flow of 6,270 GPM. This change in flow during the batching is due to a transient effect of the DP/DL caused by the higher viscosity fluid that was pushed by the light crude oil. OCB started pumping and the PSP at the refinery was ramped down from 345 psig to 152.3 psig to dampen all the pressure transient effects while maintaining an acceptable pressure at the highest elevation points; thus, slack conditions were avoided. At the same time, OCB was pumping a constant pressure of 320 psig; again a flow ramping was observed in this facility as well. However, in this case, the ramp was in opposite direction from high flow rate to semi-steady flow. Another small transient effect in the
6 AUGUSTO GARCIA-HERNANDEZ PSIG 1111
flow rate was originated by the closure of the recycle line of the station. A second dead time was reached when the OCB pumping cycle was completed. Thus, the next batch was started from OCA with a PSP at the refinery of 152.3 psig and then it was ramped up to 345 psig while the flow was ramping smoothly from the OCA facility. As soon as all transient pressure waves dampened down in the pipeline, the flow rate was stabilized to 6,270 GPM to complete a full batching cycle. Figure 9. Transient Events Results at the Junction Node
During a Batching Cycle
Figure 10. Transient Events Results at the Light Crude Oil Center During a Batching Cycle
Figure 7 through Figure 12 present transient values of density, viscosity, pressure, and flow rate during a normal batching cycle of the heavy and light crude oil centers. Those parameters were used to estimate the length of each batch as well as its volume. A density ratio defined as the density value of light oil divided by density value of heavy oil was calculated for the entire batching cycle at the refinery facility to estimate the interface and batch volumes. Results of the density ratio are presented in Figure 12.
Figure 11. Transient Events Results at the Heavy Crude Oil Center During a Batching Cycle
Figure 12. Density Ratio at Refining Facility During a
Batching Cycle
S UMMARY AND C ONCLUSIONS
Hydraulic simulations of the pipeline system were conducted for steady state conditions as initial base for the transient scenarios. Those simulations were utilized to verify that the flow rates to be used in the batching cycle were reasonable and within the normal operating conditions expected for the system. Maximum, normal, and minimum flow rates were calculated for each oil center considering the pipeline and facilities constraints. It was found that for the heavy crude oil center – OCB, the normal flow rate of 4,900 GPM and maximum flow rate of 5,100 GPM can be adequately handled for this pipeline system.
The batching cycle operation included various sequences and actions, such as pumping station shutdown, pipeline isolation, valves line-up, pumping start-up, pipeline start-up, pressure and flow control, and flow stabilization. All those actions
Light Crude Pipeline
PSIG 1111 Modeling and Simulation Case Study of a Batching Operation of Crude Oils in a Pipeline System 7
were included in the dynamic simulation of the system. It was found to be critical the pressure control at the receiving facility when the Heavy Crude Oil center is starting and ramping up the flow rate. High transient pressure should be avoided by adjusting the PSP at the refinery. The regulator located at the refinery facility was ramped up and down to dampen down the transient surge pressures created by the effect of one batch pushing another. In addition, back pressure was used to avoid slack conditions in the system while respecting the pressure constraints along the pipeline. Each pumping facility was under pressure control and flow rate ramping was observed during each batching cycle of both fluids. The difference in fluid properties and temperature originates significant changes in the pressure losses along the system that can create high surge pressure; thus, those changes were monitored. Another important parameter in the transient events was the speed of sound associated with each fluid since they have different bulk modulus values that affect the pressure reflections velocity and waves amplitudes.
It was found that the mixing volume interface is affected by diverse parameters, such as the start-up and shutdown of the pipeline, thermal effects, fluid properties and diffusion between the fluids. One important parameter that was adjusted in the pipeline simulations is the diffusion coefficient. In conclusion, the findings detailed in this case study show that the mixing volume generated during a batching operation depends on many factors as mentioned before. In the case studied here, two incompatible oils are pumped into a common pipeline system where many challenges of how to operate the pipeline during the batch transition are presented as well as how they affect the blending interface and its length. Moreover, pressure limits were established for the heavy crude oil facility based on the flow requirements of the system. The results from this analysis provide an estimate of the expected volume during the batching operation to be undertaken. However, a field survey of the mixing volumes is recommended during the normal operation. Thus, the results from this study can be adjusted and improved based on real field data. R EFERENCES
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8 AUGUSTO GARCIA-HERNANDEZ PSIG 1111
TABLES
Transient Sequences Applied in one Batching Cycle
Time (hrs) Cumulative
Time (hrs)
Event
Duration Facility Action
Initial Final (hrs)
0.0 48.3 48.3 48.3 Light Crude Oil Center ‐ OCA Pumping into pipeline
48.3 48.6 48.6 0.3 Light Crude Oil Center ‐ OCA
Shutdown of the Station, stop pumping
48.6 51.0 51.0 2.4 All Pipeline System Dead Time
51.0 51.3 51.3 0.3 Heavy Crude Oil Center ‐OCB Valves line‐up and pumps start‐up
51.3 51.4 51.4 0.1 Heavy Crude Oil Center ‐OCB Flow stabilization in the
station
51.4 51.9 51.9 0.4 Heavy Crude Oil Center ‐OCB
Flow ramp‐up in the pipeline (closing station recirculation)
51.9 72.7 72.7 20.8 Heavy Crude Oil Center ‐OCB Pumping into pipeline
72.7 72.9 72.9 0.3 Heavy Crude Oil Center ‐OCB
Shutdown of the Station, stop pumping
72.9 75.3 75.3 2.4 All Pipeline System Dead Time
75.3 75.7 75.7 0.3 Light Crude Oil Center ‐ OCA Valves line‐up and pumps start‐up
75.7 75.8 75.8 0.1 Light Crude Oil Center ‐ OCA Flow stabilization in the
station
75.8 76.2 76.2 0.4 Light Crude Oil Center ‐ OCA
Flow ramp‐up in the pipeline (closing station recirculation)
76.2 110.5 110.5 34.3 Light Crude Oil Center ‐ OCA Flow stabilization in the pipeline system
110.5 124.5 124.5 14.0 Light Crude Oil Center ‐ OCA Steady Flow in the pipeline system
Table 1. Batching Schedules and Sequences Used in the Transient Simulations。