“Pigging” is one of the most frequent practices in the operation and maintenance of pipelines. Pigging can be a dangerous practice that can cause serious damage to pipelines. There may be a variety of objectives for pigging operations, such as cleaning and inspecting flowlines or performing other maintenance tasks. Therefore, flow assurance engineers need to be able to understand pigging in order to maintain smooth flow of flow assets.
Operators should accurately estimate the liquid volumes displaced in pigging operations. This will impact the design and operation if receiving process equipment is used, such as separators, slug catchers, and other devices at the outlet of pipelines. This will show you how to run simulations and analyze transient liquid reactions in terms peak liquid flowrates, pigging displacement volumes, and overall pigging performance. This analysis can now be performed more efficiently with evoleap’s floating tools software than with traditional methods. We will compare flotools with traditional methods using Excel and the OLGA Gui.
Pre-Processing
flotools allows you the possibility to quickly create multiple cases for a study, and then instantly process them. The following parameters can be used to analyze the pigging displacement volume, peak flowrates and pipeline system.
Inlet Liquid Flowrate
Watercut
Gas Lift Rate
Inlet temperature
Parametric Studies tool is one of the most powerful features of flotool. It makes this process extremely simple and streamlines it.
It can be tedious to manually create cases in a study with multiple cases. To use the OLGAGU parametric tool, a comma separate list of each value would be needed for each case. A spreadsheet using Excel is typically used to organize each case’s parameters and visualise how they would look. The flotools parametric study tool simplifies this process. Once you have created a base instance with a specified parameter at a given value, flotools lets you create different cases using that parameter with different values. This is done by providing a separate list of values separated by commas. For example, let’s say the base for a study has the watercut at 0.2 for the inlet fluid rates. The study then requires that the watercut be adjusted between 0.2-0.8 with increments equal to 0.2. A comma separated list, such as “(0.2,0.4,0.6,0.8)” could be provided. The flotools program will then generate the different cases containing those values.
The next important step when generating parametric studies is to identify the case naming conventions. flotools makes it easy to do this. It provides an integer index value for each study variable when generating the parametric research. In the following figure is an example file naming pattern using study variables references.
Each study variable has a linked index. In this case, watercut (WC), which is linked to %3, is the third variable. These indexes can be used to identify the cases. You also have the option to add unlinked variable references that can be used by flotools. These variables could be more descriptive in naming cases.
The generate cases button will display a badge indicating the total number to be generated. Once you select the button, flotools will create all of the cases specified in your file. The cases can be run from there.
Post-Processing
Processing the results using the OLGA GUI took too much time due to the limitations of this GUI. You can only load one case at a time into the OLGA GUI. We found that 47 of the complete cases could not be loaded into the OLGA gui simultaneously. It is possible to only extract trend and profile data during a single simulation. However, what if you want to obtain the maximum value of the simulation, rather than the value from the previous time step? For this project, it was necessary to extract 4 different data sets.
Using flotools made the process easier. Simply load the cases into a flotools workspace, and then you can plot them.
After you have obtained the data, you can use Excel to create plots of the volumetric pig displacement. The ZPIG (pig position in branch) outputs were used to extract the exit time for each case. The displacement volumes were then obtained using Liquid Standard Flowrate Plots. This was done by integrating the QLST value between the pig exit and launch times. Next, you must format all data correctly to generate the pivot tables.
The parametric plots feature of flotools allows you to plot liquid volume rates against specified parameters. Using the calculation tool, flotools can be used to calculate the pig displacement volume as well as maximum liquid and maximum gas rates.
With flotools it’s easy to create all of the cases required for a study. The entire process, even for a case-based matrix with more than 50 cases was completed in just a few seconds (or less if you are an expert user).
Due to the limitations of Excel, the OLGA simulation software interface took around 10 times as long as Excel to produce the desired plots. These limitations include the limitation of how many cases could be loaded into OLGA GUI simultaneously and how much data could be exported at once. This workflow method had a rate limit because the data was exported in segments.
The following table summarizes the time required for each method.
OLGA/Excel method:
Open cases in GUI (11 minutes) and export QLST/ZPIG to.csv
ZPIG Data (2 minutes): Time pig exits
Between pig launch times and exit times, integrate QLST (7 min).
Generate pivot tables (3 minutes)
Format plots (create titles, axis labels, etc.) (10 minutes)
Total (34 min)
flotools method
Open flotools, load cases (5 min)
Open parametric study software and choose variables, filters/slices. (2 minutes)
Format plots (two minutes)
Change filters (2 minutes) and duplicate plots
Total (11 min)
A difference in processing times could be crucial when the case matrix is to be modified or the simulations need rerun. The flotools parametric analysis tool makes it possible to save time and make modifications to an existing parametric studies instead of creating a new one. Also, parametric plots can be created to analyze results from parametric studies and then modified slightly to cover a range of comparisons.
Conclusion
Using flotools in a common flow task such as studying pig displacement levels can lead to a faster process than traditional methods such the OLGA GUI. The flotools efficiency increase is due to several factors. These include flotools being able to process all case file instances in a single instance, calculation leveraged within flotools, data handling and visualization in flotools. These arguments should be extended. It should also be noted that flotools is able handle all cases in the case matrix, even those with large data files. OLGA GUI only has a maximum number of cases it can handle. Also, flotools can be used to eliminate the need of additional post-processing programs like Excel. It also ensures that calculations are repeatable within flotools. The workflows in flotools are designed for flow assurance applications. Therefore, it is easy to quickly derive meaningful results if you have an accurate understanding of both the input data and the output data.
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