In the fourth of a series of episodes, Pipeliners Podcast host Russel Treat welcomes Dan Sensel, Jason Dalton, and Kyle Miller from Marathon Pipe Line to discuss the ongoing maintenance and monitoring of leak detection systems.
The discussion focuses on specific pipeline situations involving instrumentation, leak detection, optimizing alarms, pressure and metering considerations, the accuracy of measurement equipment, batched products, and more topics.
Listen for real-world applications that you can apply to your operation and role to support leak detection, safety, and risk mitigation.
Instrumentation Issues in Leak Detection Systems: Show Notes, Links, and Insider Terms
- Marathon Pipe Line (MPL) is a subsidiary of Marathon Petroleum Corporation that owns, operates, and develops midstream energy infrastructure assets. MPL operates pipelines, storage tanks, and barge dock facilities.
- Dan Sensel is the Leak Detection Project Lead at Marathon. Find and connect with Dan on LinkedIn.
- Jason Dalton is the leak detection and hydraulics supervisor at Marathon. Find and connect with Jason on LinkedIn.
- Kyle Miller is the pressure control process lead at Marathon. Find and connect with Kyle on LinkedIn.
- Listen to Episode 54 – Leak Detection Program Management
- Listen to Episode 57 – Managing Liquid Pipeline Slack Line
- Listen to Episode 61 – Relief Valves in Liquid Pipelining
- Leak Detection is the process of monitoring, diagnosing, and addressing a leak in a pipeline to mitigate risks.
- The Real-Time Transient Model (RTTM) for leak detection simulates the behavior of a pipeline using computational algorithms. The model, which is driven by the field instrumentation, monitors discrepancy between the measured and calculated values potential caused by a leak. RTTM uses flow, pressure, temperature, and density among many other variables.
- Ultrasonic inline inspection uses sound waves to send a signal into a steel pipe to detect the presence of corrosion or cracks within the pipe.
- API 1130 defines the requirements for leak detection in pipeline operations.
- API 1130 Figure C-1 (page 31) shows how a CPM (computational pipeline monitoring) system should use instrument data.
- API 1149 defines the requirements for using computational models to evaluate uncertainties in a pipeline that affect leak detectability.
- IMP (Integrity Management Program) Risk Assessment uses a calculation to determine the potential risk by weighing the likelihood of a hazardous event and the consequences if the event were to occur.
- Pressure instrumentation includes various sensing devices to measure the elements of pressure, temperature, liquid level, flow, velocity, composition, density, and weight.
- Pressure transmitters provide warning alarms if the pressure exceeds set high and low limits.
- Meter proving is a method of physically testing the accuracy of a meter through the proving process of measuring temperature, pressure, flow rate, and density against a known prover.
- A PD meter (Positive Displacement meter) requires fluid to mechanically displace components in the meter in order to measure flow.
- A turbine meter uses the mechanical energy of a fluid to rotate a “pinwheel” (rotor) in the flow stream to measure flow.
- An ultrasonic meter measures the velocity of a fluid using ultrasound technology to calculate volume flow.
- A Coriolis meter measures the mass flow of liquid and natural gas as opposed to just volumetric flow.
- Metering for O&M (Operations & Maintenance) and energy/resource efficiency is defined by the U.S. Department of Energy as the measurement of quantities of energy delivered. For example, kilowatt-hours of electricity, cubic feet of natural gas, pounds of steam, and gallons of water.
- Pump efficiency testing measures critical aspects of the pump’s operation including water flow rate, inlet pressure, pump discharge pressure, and energy input to the pumping plant.
Instrumentation Issues in Leak Detection Systems: Full Episode Transcript
Russel Treat: Welcome to the Pipeliners Podcast, episode 69, sponsored by EnerSys Corporation, providers of POEMS, the Pipeline Operations Excellence Management System, compliance, and operations software for the pipeline control center. Find out more about POEMS at EnerSysCorp.com.
Thanks for listening to the Pipeliners Podcast. We appreciate you taking the time, and to show that appreciation, we are giving away a customized YETI tumbler to one listener each episode. This week, our winner is Anthony Fisher, with Berry Petroleum. Congratulations, Anthony, your YETI is on its way.
To learn how you can win this signature prize pack, stick around to the end of the episode.
This week, we welcome back Dan, Kyle, and Jason from Marathon Pipe Line to talk about issues with instrumentation and the impact on leak detection. Marathon trio, welcome back to the Pipeliners Podcast.
Jason Dalton: Hi, Russel.
Kyle Miller: Glad to be back, buddy.
Russel: Just so the listeners know, this took a little bit longer than planned because we had some technical difficulties, which we’re all fairly confident we have worked out now. I guess we’ll know here in about 30 minutes whether they’re all worked out.
Kyle, Dan, and Jason, I asked you guys on this week to talk about metering and instrumentation, and how that impacts leak detection. I’ll tee this up by saying I think when people are implementing leak detection programs, one of the things that occurs is, they often fail to consider what’s necessary for the ongoing care and feeding, if you will, of a leak detection system.
What’s your experience with the challenge of getting the instrumentation where it needs to be, in order to support doing a good job with leak detection?
Dan: That’s always a challenge, especially if you’re trying to retrofit a system, or if you’re taking on new ownership of a system, new operatorship, trying to get that system up to snuff with what your leak detection requirements are. Different companies are using different technologies, and that can lead to gaps when we take something over.
We have a fairly robust leak detection adequacy process that reviews the pipelines, where we review all pipelines every five years. New pipelines are reviewed immediately to determine what is the appropriate leak detection method. We look at, what instrumentation do we have, and what may be needed to get it to an adequate level of leak detection.
Reviewing pressure transmitters, and meters, and all of those things are part of that process.
Russel: What would go into making the decision about what leak detection approach is best suited to a particular pipeline?
Jason: The way that we do it is, we feed the data from our IMP risk assessment into an algorithm we’ve got. We sat back many years ago and tied specifically detection systems to the operational risk of the system and the complexity of the system.
If you’ve got a system that’s really short, of one mile, two mile, like a spur line feeding a tank farm, obviously, a real-time transient model is not going to work on there. You just don’t have the length. It’s overkill.
It’s overly complex, whereas if you’ve got interstate line, high diameter, high flow rate with multiple batched products, a line balanced system might not be a good fit for that, just because there’s better data and you’ve got a significant risk just due to the size of the line. The risk and the complexity are the two things that we chiefly look at.
Russel: That makes perfect sense. When you’re looking at something that’s new to your organization, maybe a system you’ve acquired, and you’re evaluating the instrumentation, what are the kinds of things you’re looking for with regards to what’s installed?
Jason: First pass we tend to look at is the measurement equipment. Your leak detection system, most often, is dependent on how accurate your measurement equipment is. If we take a line over and they’ve got orifice meters, or they’ve got unprovable ultrasonics, we’ll take a hard look at, do we need to upgrade that?
We’re old school in that we stick by turbine meters and PD meters, and we have a lot of fixed provers. One of the first things that we typically do when we take a system over is to consider a measurements upgrade. The other thing we take a look at is, where are all the pressures installed?
The pressure instrumentation is a lot easier for us because it feeds multiple processes, so you get more telemetry and you get more data on what’s really going on in the pipeline, based on how many pressure transmitters you’ve got installed. We’ll throw a lot of those at a system when we take it over, usually.
Russel: Pressure is easier to retrofit than metering, for sure, right.
Russel: It’s interesting to me. I’m surprised that you guys use a lot of turbine type meters for your leak detection. At least in my experience, that’s a bit old school. Is there a reason you don’t move towards ultrasonics?
Dan: Our measurements group tends to use turbine meters for our custody transfer meters. In many of our lines, we’re taking advantage of our custody transfer meter, which is the turbine meter, provable turbine meter.
In instances where we have to install an integrity meter, or a meter that’s sole purpose is for leak detection, in those cases, we will go with an ultrasonic to cut that cost and to get that different technology in there.
Russel: People that are familiar with leak detection are familiar with this, but there’s a distinction between those meters used for custody transfer and those meters used solely for leak detection.
With the ones used solely for leak detection, one of the issues is, I want to minimize pressure loss across the meter, where in custody transfer, the issue is, I want the most accurate, and consistent, and reproducible measurement possible. Of course, one of the challenges is — having two different kinds of metering technology, that by itself could cause some issues.
Dan: Yeah, and of course if you’re using a real-time transient model or any model that is an internal monitoring of the pipeline, based on pressures and flow rates, your leak detection limits are going to be dependent upon the accuracy and the error of your metering.
It’s important to make sure that you understand the limitations of your system before you establish what thresholds you’re going to use because that can lead to extra false alarms.
If you set the thresholds too low, and if you set the thresholds at one percent, and your metering is only good to one percent, you’re going to be driving yourself crazy trying to figure out what’s going on.
Russel: That’s exactly right. The other thing you have to look at is, what is the accuracy of the meter? Taking in consideration not just the primary element, the meter itself, but all the things you’re doing around O&M for the meter, because all that impacts accuracy as well.
For those meters that are not custody transfer, what kind of practices are you putting in place to calibrate and prove those kind of meters?
Jason: For us, we have very few what I would call integrity meters. Other operators typically will put a meter every segment, so, between pump stations. We go away from that, and we just use the custody transfer at the receipt and delivery ends.
One of the reasons that, as Dan mentioned, every measuring device has some error, and in our real-time models, those errors stack up and influence the level of leak detection that we can put on the line.
In the rare cases where we do have a UT meter or some other technology, typically, those are balanced against a custody transfer model or custody transfer meter somewhere and we’ll continue to watch that meter and see if they start to get out of balance. In a way, we’re proving the less accurate meter that’s downstream with a more accurate meter upstream.
Russel: It’s more of a reference meter kind of proving.
Russel: By custody transfer, I’m proving to a legitimate prover, you call it your IMP, your integrity meters, which are there purely for leak detection, those are proved against an upstream meter or a downstream meter that’s custody transfer.
Dan: In some cases, we’ll have proving connections at those meters, and we’ll use a portable prover to prove them on some PM cycle.
Jason: If there’s a significant change to facility piping, or we put a new meter in, or we do any maintenance on it, we’ll bring in a temporary prover on a trailer and prove that.
Russel: That all makes sense.
Dan: As Jason mentioned about where we tend to go to adjust inlet in our receipt and delivery meters instead of having station flow meters, part of that is, our systems are significantly batched, shipping both heavies, and lights, and various different types of product.
The air that gets generated by having those various products going across an intermediate meter can really impact your leak detection performance. You end up in a situation where, when you do have a deviation on one of those station meters, you’re spending a lot of time trying to figure out, what’s it due to? Rather than responding to the alarm as if it’s a leak.
There’s less confidence in those meters due to all the variability going across them.
Russel: I think that’s worthy of unpacking a little bit because that’s a little bit counter intuitive. You would think that in leak detection, more metering would be better.
You guys, is that unique to the situation of batching a lot of different density products, or you think you would see the same kind of thing if you’re shipping more of a consistent product like a crude oil?
Jason: I think it’s unique to a batched system. For example, if you’ve got a lot of those with midpoint meters that are out on individual segments, if you don’t have the ability to prove them, then as the product quality or the product grades change as they go across that meter, if you can’t prove it, you’re going to have to reduce your measurement precision a little bit.
If you’ve got a long line, let’s say you’ve got 10 segments, and you stack all those errors on top of each other as you’re also trying to track batches through the line, they could significantly impede the lowest achievable threshold that you could get without generating a lot of false positives.
Russel: That makes sense because each different density product is going to have a little bit different meter factor.
Russel: That little bit of difference could be enough to impact the sensitivity of the model and start throwing false alarms.
Jason: For example, even past that, we are starting to move a lot of blended crudes. The blended crudes have the impact of, they’re not homogeneous. That means that the density of that grade of crude oil is not consistent all the way through the batch, or the block module just isn’t consistent all the way through the batch.
You can prove the meters on both ends of the line at the beginning of your delivery and 10 minutes later, you have a completely different line fill. Per old modeling, the fluid’s not changed, so there shouldn’t be a reason to prove, or when you prove, you find out your API gravity changed by two or three.
Russel: It’s a small change, but enough to make a difference from a leak detection standpoint.
Kyle: In our longest lines, we may have 20, 30, 40 different batches. From the leak detection, let’s say, the user level, we train ourselves to recognize what a batch change looks like, so if we get a leak alarm, one of the first things we look at is, has there been a batch change? Do we think the meter factor is off?
To Dan’s point, we don’t want to waste a lot of time fighting with things like that, rather than treating it like it’s an actual leak.
Russel: This is one of those things where I’m thinking about this and the complexity of that. It just supports my innate belief that everything is easy until you know enough about it.
Dan: That is, for sure, true.
Russel: [laughs] If you can’t use additional throughput meters because of the nature of your operation, are you augmenting your leak detection with pressure, or density, or that type of thing?
Dan: Definitely pressure. We go through and look at all the elevation profiles of the lines and determine where pressure transmitters are needed.
The system we use, not only do we bring in the RTTM model, but also one of the first steps in analyzing a leak alarm would be to trend pressures on the system and look for deviations or for pressure decay in any place that would be unexpected.
It takes a lot of analysis to figure out what pressure should actually be doing on the line when you have multiple batches in the line, and multiple changes in pump configuration, and things like that going on. We try to bring as much data as we possibly can to the analysts view so that they can make the right decision.
Russel: At least in my experience, there’s a lot of what I’d call local knowledge. I need to know the individual systems and how those individual systems behave in order to do that analysis.
Kyle: Right. We have lines that maybe have long sections that are a little bit shallower than average, and therefore are more susceptible to swings due to daily ambient temperature. Once again, from a user level, the temperature is a bigger offender to us than meter factor.
During certain seasons of the year, like right now, you may have a 10 or 15 degree, 20 or 30 degree temperature swing during the course of the day. On a shallow line, that’s going to make a big difference. The model may not adjust in time, and we have to go in there and make those tweaks, based on experience.
Russel: The other thing I wanted to talk about around this idea about instrumentation. We’re getting into some operational considerations. I want to talk more about the O&M of the instruments themselves.
I think what we’ve done, so far at least, is illustrate just how sensitive these models can be to changes in calibration, or fluids, or temperatures, or that type of thing.
Obviously, to the extent I can get a better job of maintaining my instruments, the better my leak detection system is going to run. In addition to just my normal O&M and calibration, are you doing things where you’re going through any kind of periodic check or review to see if you can find things that look like the instruments aren’t behaving as they should be?
Jason: Yes, in a roundabout way. The reason is, with the complexity of a real-time model, you’re going to start to see really quick if you’ve got something acting up, or if you’ve got a transmitter that’s not spanned correctly.
There’s been times that Dan will come over and say, “Hey, we’ve got a leak alarm on such and such system, and every other transmitter on this line looks fine, and we’ve got a transmitter that’s reporting a pressure that’s five PSI lower than what all the calculations say it should, and what it was reporting yesterday.” We’ll have the area go out and re-span the transmitter.
It’s a positive for us, with the amount of data we’re bringing in, that we can find out if something is going off the rails really quickly.
As far as the rest of the calibration, a lot of the good things about a CPM-based leak detection, if you’re looking at a line balance or a composite line balance, most of that equipment is DOT covered. Which means that once a year, not to span 15 months between checks, that instrumentation has to be DOT inspected to make sure that it reports the correct values.
Dan: Just part of our leak detection process here is maintaining a database of all of the instrumentation that we are using, in any way associated with our leak detection models. Per API 1130, those are added to PMs within our maintenance system and calibrated per schedule.
Russel: That’s kind of getting, guys, to the question I was asking because I think to do a good job of leak detection impacts the O&M.
Your needs are going to impact the procedures that the guys looking at the pressure-related safety transmitters and the custody transfers metering, there’s going to be things in their procedures that they’re doing that provide for cross checks and feedback to the leak detection group.
I think, for somebody who’s not put in a CPM system before, it’s easy to overlook that reality.
Jason: I think a good strategy would be to have a minimum amount of leak detection specific equipment. In our CPM system, I can’t think of a single transmitter, or meter, or device that was installed solely for the leak detection system.
What I mean by that is, we put this system in after these lines had been installed for many, many years, so we were able to piggy back our needs on the needs of other processes.
Our measurements equipment comes from, frankly, the cash register or the company, so when we need the meters to be accurate, there are other departments that also need them. Our pressure transmitters are used for the pressure control initiatives and also measurement because you have to have accurate pressures going through your meter routes.
The easiest way to make sure that your equipment is as up-to-date as possible is to use it in as many ways as possible.
Russel: That’s right. The more people that are relying on it, the more likely you are to do a good job of keeping that equipment maintained.
Russel: I’ve never thought about it that way, but that’s an excellent point.
Kyle: The transmitters also help us with the pump efficiency testing, testing whether control valves are being worn out, looking at the surge relief events to see how the valves are acting. As we’ve mentioned, pressure transmitters are typically a pretty easy sell.
Russel: With the way things are going in terms of the cost of the transmitters and the cost of the communication, they just keep getting less and less expensive. It’s almost to the point that the things you have to do to modify the pipe to mount them are more costly than the other parts of the package.
If you were advising a small liquids pipeline operator that is thinking they need to get a CPM in place, how would you tell them to approach this around all their instruments? I think we’ve covered that about use the instruments you have, but what else might you advise somebody who’s getting started putting a program in?
Dan: I would review the accuracy of those instruments and look at something like API 1149, which is going to tell you what kind of error you can expect in your leak detection. To do that analysis and understand, based on the instruments you have today, what kind of benefit is your leak detection system going to give you?
If your leak detection system, based on the errors that you have, is only going to tell you if you have a 10 percent flow leak, then you may need to look at investing in additional instrumentation if that doesn’t meet your risk management goals.
It’s important to understand, like I said, those limitations that are imposed by your hardware out in the field before you even get to your software side.
Jason: My advice would be to keep in mind what you’re trying to do here. You are trying to minimize the consequences of a loss of containment as much as possible. If you do like Dan said, and with your current equipment, the best you’re going to get is a 10 percent leak rate, but you can take that money and patrol the line on a daily basis.
The better option is to go away from a CPM system and to patrol the line more actively. You got to balance the amount of money that you have available, or resources that you have available, versus the end goal. Sometimes, it’s not the fanciest equipment you can get. You can use old, tried and true methods, as long as you reduce the consequences of the leak.
Russel: Again, I think that’s very well said. The other point we’ve made is that every operation is different, depending on the nature of the pipe, the nature of the product, and where it’s located. Like everything else, there’s a lot of factors to consider.
I think one of the things that’s challenging on the metering side is that you have this issue about accuracy, but you also have an issue around bias. What I mean by that is, every metering type has its own innate accuracy, but it also tends to have its bias.
What I mean by that is, if I’ve got a meter, and it’s a one percent meter, it’s going to tend to measure either a little bit high or a little bit low of the actual, if you were doing something in a lab.
When you combine meters of different types, you have to be careful about how you’re managing that uncertainty or that error across different meter types. If you’ve got a system and it’s got orifice meters, and turbine meters, and ultrasonic meters, and Coriolis meters all combined, that in itself could be problematic, just because of the different meter types.
Have you ever seen anything like that in a system that you guys are acquiring and taking over?
Jason: One of the ways that you can account for that is through API 1149. API 1149 has got a lot of calculations in it, and you can stack up the accuracy of different pieces of equipment and help to generate your overall threshold.
If you’ve got a PD meter that’s good to a .002 percent, and you’ve got a turbine meter that’s good to the .015, all of those factors can go into calculating your overall leak detection threshold.
That’s the way that we deal with it. We’ve got a lot of systems where we’ve got one type of measurement or formula on one end, and a different type on the other end. It all gets rounded up into a final calculation for detection threshold.
Dan: As far as biased, I think sometimes that can come down to just system familiarity as well, where there are some systems where we’ll know that it tends to run a little with a positive leak rate or a negative leak rate, and that becomes the norm.
Over time, we’ll look to balance that out, work with our measurements department to try to get that to be as accurate as possible and as centered as possible, so that we get the full advantage of all of our threshold.
Russel: Right. Being a guy who grew up in measurement, I think the other thing that’s important to understand is that getting the accuracy of your measurement is not just about your meter. It’s also all the things you do to manage that meter side. How often is it calibrated? How is it calibrated? What’s the accuracy of the equipment you’re using for calibration? All of those things will impact.
When you work with your measurement department, that’s the kind of thing you’re talking about is, what can they do, either through the equipment itself or through the way they’re calibrating, and operating, and maintaining that equipment to improve the overall station accuracy to dial things in better?
What’s certainly true is to the extent the instrumentation becomes more accurate, and to the extent you get that data more often, your leak detection system is going to be able to operate more effectively.
Kyle: It’s like Dan said earlier. You have to go in with your goals, and from then on out, you’re going to get what you pay for.
In our world, with thousands and miles of pipe, with hundreds of different products batched, I think people who aren’t in this industry and don’t do this line of work would be surprised that a meter on one end and a meter on the other wouldn’t be good enough.
You really have to think about this as energy. There’s a certain amount of energy going into the pipe, and some of that’s coming out, and some of it’s being lost due to the environment. There’s so much heat transfer that goes into this, and that’s what the pressure transmitters and that’s what the temperature sensation is all about.
Russel: When we talk about energy being lost, we’re not talking about product coming out of the pipe. We’re talking about the energy we introduce to move the product is lost as the product is moved, so the pumping energy that we apply is not the velocity we get at the end of a long segment of pipe.
Kyle: Right. It’s a 200 mile heat transfer problem.
Dan: Of course, you have friction.
Russel: Guys, this has been great. As always, I appreciate it. Thanks for coming back. I’m sure we’re going to have a lot more things we need to talk about as we go forward with all this. As always, I really appreciate you all participating on the podcast.
Kyle: Always a pleasure, buddy.
Dan: Nice to talk to you, Russel.
Russel: I hope you enjoyed this week’s episode of the Pipeliners Podcast, and our conversation with Kyle, Dan, and Jason. Just a reminder before you go, you should register to win our customized Pipeliners Podcast YETI tumbler. Simply visit pipelinerspodcast.com/win to enter yourself in the drawing.
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Thanks for listening. I’ll talk to you next week.
Transcription by CastingWords