Pigging is one of most common procedures in the operation of pipelines. The buildup of liquids or solids in flowlines can cause plugging, cracks and other problems that could lead to severe damage. The objectives of pigging operations could include cleaning, inspecting, and other maintenance operations. For flow assurance engineers, it is important to understand pigging to ensure flow assets are running smoothly.
Operators need to accurately anticipate the total liquid volumes that will be displaced during pigging operations. It is important because this will affect the design and operation for receiving process equipment like separators and water slug traps located at the outlets of pipelines. This section will explain how one can run a series of simulations to analyze the transient liquid responses in terms of the peak liquid flowrates and pigging displacement volume. This analysis is possible with flotools program, which has a higher efficiency level than traditional methods. Our approach will be compared to more traditional methods such as Excel or OLGA GUI.
Pre-Processing
OLGA simulation software allows the creation of a multi-case study and the processing of the results. This discussion will examine the pigging displacement volumes and peak flowrates of a pipeline system. We will do this by changing the following parameters.
Inlet Liquid Flowrate
Watercut
Gas Lift Rate
Temperature at the inlet
Parametric Studies, one of flotools most powerful tools, simplifies this process and makes it very easy.
Manually creating cases for a study that has many cases can be repetitive and often impractical. This is especially true if the case matrix is large. The probability of making mistakes is high. For each parameter to be changed using the OLGA Gui parametric tool, a comma-separated list of all values for each case would be needed. A spreadsheet in Excel would typically be used to organize the data and visualize the results. This process is simplified by the flotools parametric studies tool. You can create a base case that has a particular parameter set at a certain value. Then, flotools will allow you to create other cases with the same parameter but different values. A study could have a base case with a watercut of 0.2 for inlet liquid rate and study that requires the watercut to be between 0.2 – 0.8 with increments at 0.2. If this is the case, flotools can generate different cases from the comma-separated lists such as “(0.2),0.4,0.6, 0.8” or similar.
Next, you need to determine the naming convention of the many cases. This can be done easily with flotools by simply providing an integer index for each study variable while creating the parametric studies. Below is an example of the file name pattern that uses study variable references.
Each study variable has an associated index. For example, watercut (WC), is linked with %3, which is the third study variable. The cases are named using these indexes. Each case is identifiable by a system of naming them. Unlinked variables can also be added to flotools so that they can be referenced by another variable. These could be useful, as they can provide a more descriptive way to name cases.
The generate cases button displays the total number of cases that will be generated. Once the option is selected, flotools will generate the required number of cases at a specified location in your file. You can run the cases.
Post-Processing
Due to limitations in the GUI, processing the results of the study was slow. There are a limited number of cases you can load into the GUI when using the OLGA GUI to extract results. The OLGA GUI could only load 47 of the cases at once. We also found that only 47 of the cases could be loaded into the OLGA GUI simultaneously when extracting trend data and profile data. But what if we wanted the maximum value from the simulation rather than the value at the end? Four separate extractions were needed to obtain the entire data set for this project.
The process of using flotools was much simpler. You simply need to place the cases into a flotools workspace. The results can then be plotted.
The traditional method of obtaining data is followed by Excel to create plots showing the volumes of pig displacement. Each case had its pig exit times extracted from ZPIG outputs. The displacement volumes were then calculated using Liquid Standard Flowrate, (QLST), plots. Each case was then combined the QLST from the pig launch to exit time. Next, format the remaining data to create the pivot table.
The flotools parametric plots tools allow you to plot the liquid rate against any parameters. You can calculate the pig displacement volume and maximum liquid rate with flotools’ calculations tool.
With flotools, it is easy and fast to create all the cases needed for a study. Even with a case matrix that had over 50 cases, the whole process took less than a minute (or less for skilled users).
The limitations of Excel’s OLGA GUI meant that it took 10 times longer to create the desired graphs than using the OLGA Gui. These limitations include the limit on how many cases can be loaded into the GUI at once and the limit on how much information could be exported. The rate-limiting aspect of this workflow was exporting data in segments.
Here is a quick summary of each method:
OLGA/Excel method:
Open cases in GUI and export QLST, ZPIG and.csv (11 Minutes)
ZPIG data (two minutes): Find the time that a pig leaves.
Integrate QLST (Quick Launch and Exit Time) (7 Minutes)
Generate pivot tables (3 minutes)
Format plots (create titles, axis labels, etc.) (10 minutes)
Total (34 Minutes)
flotools Method:
Open flotools and load boxes (5 minutes)
Select variables and filters to open parametric study tools. (2 minutes)
Format plots (2 min)
Make duplicate plots and modify filters (about 2 minutes).
Total (11 Minutes)
This can make a difference if the case matrix must be modified, and therefore the simulations have to be rerun. The parametric tool flotools allows for the copying and modification of an existing parametric research, which can reduce the time required to complete the project. The parametric plots created to analyze parametric results can also be copied and slightly modified to cover different comparisons.
Conclusion
Using flotools can be a more efficient way to accomplish a common flow-assurance task, such as studying pig displacement volume. The flotools’ efficiency boost comes from several factors. These include flotools’ ability to process all cases in one instance, the calculations made within flotools, as well as the ease with which data is handled and visualized in flotools. To elaborate on these points, flotools can handle all case files in the potential case matrix. OLGA GUI, however, has a limit to the number of cases it is able to handle simultaneously. The use of flotools would also eliminate the need for additional post-processing software like Excel. Additionally, it ensures consistency in results when using flotools calculations. Additionally, flotools workflows are specifically designed to be used in flow assurance engineering applications. Thus, meaningful results can easily be obtained by using flotools.
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