This week’s Pipeliners Podcast episode features first-time guest Floyd Baker of Antea North America discussing the use of digital twins technology in the pipeline industry.

In this episode, you will learn about the fundamentals of digital twin technology, how this technology is being deployed throughout the oil and gas industry, how to start utilizing digital twin technology in the pipeline industry, the business case for getting started, and more valuable information around digital twins in pipelining.

Digital Twins in Pipelining: Show Notes, Links, and Insider Terms

• Floyd Baker is Vice President of Antea North America. Connect with Floyd on LinkedIn.
  • Antea is an industry leader in asset integrity management and digital twin software. Antea specializes in the development of highly flexible software solutions and in supplying integrated services for industrial sectors such as oil and gas. Learn more about Antea at antea.tech.
    • Access these digital twin technology resources from Antea to learn more about the potential use of this technology in the pipeline industry.
    • Access Floyd Baker’s new eBook, “A Primer on Digital Twins.”
• Integrity Management (Pipeline Integrity Management) is a systematic approach to operate and manage pipelines in a safe manner that complies with PHMSA regulations.
• Digital Twin is a virtual representation of a physical object or system across its lifecycle, using real-time data to enable understanding, learning and reasoning. With this innovative digital tool your team can virtually create, test, build and monitor a product, providing real-time insights that make it easier to find hidden issues, fix and get to market faster.
• The Industrial Internet of Things (IIoT) refers to the extension and use of the Internet of Things (IoT) in industrial sectors and applications. With a strong focus on machine-to-machine (M2M) communication, big data, and machine learning, the IIoT enables industries and enterprises to have better efficiency and reliability in their operations.
• ILI (Inline Inspection) is a method to assess the integrity and condition of a pipe by determining the existence of cracks, deformities, or other structural issues that could cause a leak.
  • API RP 548 (API 548) is a recommended practice developed and published by API that provides users with information and guidance on developing and implementing Integrity Operating Windows (IOW) to help strengthen their Mechanical Integrity (MI) programs. This RP is meant to explain the importance of — and help facility owners create, put into place, monitor, and maintain an IOW program for each vulnerable unit and piece of equipment in their facility. The current and 1st Edition of API RP 584 was published in May 2014.
    • Integrity Operating Windows (IOWs) are sets of limits used to determine the different variables that could affect the integrity and reliability of an asset. Essentially, IOWs are the limits under which the asset can operate safely.
• OSHA (Occupational Safety and Health Administration) is an agency in the United States Department of Labor. Their mission is to “assure safe and healthy working conditions for working men and women by setting and enforcing standards and by providing training, outreach, education, and assistance.”
• PHMSA (Pipeline and Hazardous Materials Safety Administration) is the federal agency within USDOT responsible for providing pipeline safety oversight through regulatory rulemaking, NTSB recommendations, and other important functions to protect people and the environment through the safe transportation of energy and other hazardous materials.
• The Bellingham Pipeline Incident (Olympic Pipeline explosion) occurred on June 10, 1999, when a gas pipeline ruptured near Whatcom Creek in Bellingham, Wash., causing deaths and injuries. Three deaths included 18-year-old Liam Wood and 10-year-olds Stephen Tsiorvas and Wade King.
  • Listen to Larry Shelton discuss his first-hand experience reviewing the aftermath of the incident in Pipeliners Podcast Episode #79.
• Enterprise Resource Planning Systems (ERPs) are used in businesses to manage company resources, integrate tasks, manage risks, localize financial accounting, and ensure quality checks.
• Adoption Phase is one of five phases in the Buyer Decision Process for New Products. The adoption process for a new product is the mental process through which an individual passes from first learning about an innovation to final adoption. The five stages of the consumer adoption process are awareness, interest, evaluation, trial, and adoption.
• Petrochemical is an industry branch that produces organic intermediate products such as refinery products, natural gas, plastic, rubber, and fiber raw materials.
• Stress-Strain Curve (Stress/Strain) for a material gives the relationship between stress and strain. It is obtained by gradually applying load to a test and measuring the deformation, from which the stress and strain can be determined. These curves reveal many of the properties of a material, such as yield strength and ultimate tensile strength.
• Metallurgy is the branch of science and technology concerned with the properties of metals and their production and purification. Metallurgy can be classified as extractive, mechanical, or physical.
• CP Values is the specific heat capacity of a fluid sample divided by the mass of the sample.
• Cathodic Protection is the most common electrochemical technique used to prevent corrosion on buried metallic pipelines where the applied coating has failed or been damaged exposing bare pipeline metal to the soil.
• GIS (Geographic Information System) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data.
  • Geospatial information is data referenced to a set of geographic coordinates that can often be gathered, manipulated, and displayed in real-time.
• Pointclouds are a collection of millions or billions of individual measurement points from the surface of objects. They can be acquired by laser scanners, drones, or 3D cameras. Pointclouds represent reality for powerful 3D visualization while providing geo-spatial information for accurate mapping.
• SCADA (Supervisory Control and Data Acquisition) is a system of software and technology that allows pipeliners to control processes locally or at remote locations.
• DCS (Distributed Control Systems) are typically installed at facilities and are distinct from a SCADA system, which monitors and controls a geographically disperse system such as a pipeline.
• Computerized Maintenance Management System (CMMS) is software that centralizes maintenance information and facilitates the processes of maintenance operations. It helps optimize the utilization and availability of physical equipment and assets.
• Data Historian is a software program that records the data of processes running in a computer system. Organizations use data historians to gather information about the operation of programs to diagnose failures when reliability and uptime are critical.

Digital Twins in Pipelining: Full Episode Transcript

Russel Treat:  Welcome to the Pipeliners Podcast, episode 210, sponsored by EnerSys Corporation, providers of POEMS, the Pipeline Operations Excellence Management System, compliance and operations software for the pipeline control center to address Control Room Management, SCADA, and audit readiness. Find out more about POEMS at EnerSysCorp.com.

[background music]

Announcer:  The Pipeliners Podcast, where professionals, Bubba geeks, and industry insiders share their knowledge and experience about technology, projects, and pipeline operations. Now your host, Russel Treat.

Russel:  Thanks for listening to the Pipeliners Podcast. I appreciate you taking the time. To show the appreciation we give away a customized YETI tumbler to one listener every episode. This week, our winner is Press Johnson with Magellan Midstream Partners. Congratulations, Press. Your YETI is on its way. To learn how you can win this signature prize, stick around at the end of the episode.

This week, Floyd Baker with Antea joins us to talk about the use of digital twins in pipelining. Floyd, welcome to the Pipeliners Podcast.

Floyd Baker:  Russel, it’s good to be here. Thank you for having me.

Russel:  As I normally do, I’d like to ask you if you could do a brief introduction, tell us a little bit about who you are and your background, and tell us how you got into pipelining.

Floyd:  Sure. I can do that. My name is Floyd Baker. I’m the vice president of Antea North America. I’ve been in the asset integrity business, literally 40 years — that’s all my career, my entire career. Asset integrity, and specifically as it relates to pipeline integrity management.

Spend a whole lot of my time on the technical side, meaning the testing equipment, robotics, and phaser, ultrasonics, and all these kinds of good things, long-range guided-wave ultrasonics, and then migrated my way over to software platforms where we actually manage any kind of data associated to pipelines.

Russel:  Cool. I asked you to come on to talk about digital twins in pipelining. I’m notionally aware of what a digital twin is because of my background in automation and some of the stuff I’ve done looking at IoT, the Internet of things. Maybe we should start with, what’s a digital twin?

Floyd:  A digital twin is a digital representation of a physical object. That’s the quick answer for it. There are different levels of digital twins and, to me, one steps up to greater value than the other. The digital twin that we reference with regard to asset integrity and pipeline integrity specifically is one that is intelligent. It’s an intelligent digital twin. It actually speaks to you. It tells you things.

Russel:  Probably I’ll talk about digital twins around rotating equipment as a place to start, because I think that the idea of a digital twin is probably foreign to a lot of the people that are listening to this podcast, so might be helpful to do a little education.

My exposure to digital twins has been around rotating equipment where they build a 3D model of the equipment — so a 3D model of something like a pump. Then they’re able to animate that 3D illustration — so you can actually see things moving — and then they apply other visualization techniques, like color, where blue is cold, yellow is running, and red is hot. That kind of stuff. Where you begin to see, not only in this digital representation of the pump, but its internal components and how they’re behaving. You visualize vibration, you visualize temperature, you visualize speed, and things of that nature.

I think most people have seen something like that in a video game or something. You’ve seen something like that.

Floyd:  Exactly. That is more of a process engineering type digital twin. Usually, it’s constructed of all of its original design data, or even before design and construction, in the prototype phase. The digital twins that we use in energy typically are static digital twins.

It’s a point cloud rendering, a 3D laser scanning, and then that 3D model is the visualization we look through. We can even overlay that on the 3D model of the asset itself, or the pipeline in this case, and show the color-coding you referred to. The color-coding we most mostly focus on are things like the process type, so we can better understand how that process acts and reacts with the metallurgy, the pressure envelope, the pipe itself, or risk. We do risk analysis within the platform. It actually speaks to the color codes in those 3D models, so you can actually understand where the risk is in your pipeline and know where to focus those maintenance dollars, where they create the most value.

Color-coding in our case can be just about for anything and t can be interchangeable. You can change at any moment. If I want to look and see what the process is, if I want to look and see where’s my risk is, if I want to look and see even scheduling situations, if I’ve got inspections or some kind of maintenance activity that has been scheduled and it’s past its due date, I can identify those through color-coding as well, to better understand where I need to focus those maintenance resources to stay in compliance. Very useful visualization.

Russel:  I’m trying to think about the audience and I’m trying to translate a little bit, and I may be oversimplifying. I can certainly see in a static visualization, something like an offshore structure, an offshore platform. Then I visualize the stresses and strains in the metal by understanding the loads that are being applied.

Then I’m basically taking all the math that’s happening to do that analysis, and I’m illustrating it in 3D and then I’m applying some kind of color palette or something that allows me to visualize stresses and strains. I think most of us that are engineers can kind of get their head around that.

Then I would say, when you start talking about rotating equipment, you can start thinking about, “Well, I’m going to put instruments on this rotating equipment. Now I’m going to visualize what those instruments are telling.” Right?

Floyd:  Yeah.

Russel:  The idea is I’ve got a digital representation of a facility or a piece of equipment, and then I’m adding additional data to be able to tell me something about how it’s operating. Is that kind of…?

Floyd:  Yeah, it is. It’s basically creating optimizing contextualization. The visualization part makes it much easier for one to contextualize so that that’s key there. Being able to access that information…First off, I’d like to point out you hit the nail on the head a moment ago.

IIoT, the Industrial Internet of Things is the enabler. This is the enabler from it just being a picture to an intelligent digital twin. Those sensors that speak to us, that’s where the live information comes from.

We can manage information from all different sources. We can integrate with other platforms that collect specific types of data that we want to also manage here. We can import things like ILI data. Any of your above-ground surveys. All that data can be all integrated and all aligned so that one can actually look at these visualizations and glean something from them, make quick, fast critical decisions. The key here is access to that information is all in the same space. It’s accessible in the same space.

Anything from if you’re integrated to your SCADA, then you’ve got operational data. If you’re integrated in the platform, you’ve already got all your mechanical data and all your integrity data. Meaning everything that OSHA, PHMSA, all those folks are having us do, and that we really should do in order to maintain a safe and reliable pipeline.

All this information can be accessed right there, even integrated into the ERP. When it suggests you have some work to do, you can actually create that, let’s just say work plan, inspection test plan, or whatever it is to communicate to the ERP, to generate a notification, which would then convert to a work order and actually get stuff done, execute some activity and get some work done.

Russel:  When you start talking about software, and all this conversation is software, right? I’ve been working in software pretty much my entire professional career. I’m always a little leery when this stuff gets a bit hand-wavy. You start telling me about all the things I could do.

When I start working around software, I very quickly become a show-me guy. You’re going to have to show me because I know you can do all this. It’s just a matter of time and money. Just give me a room full of smart people, feed them Coca-Cola and pizza, and you can do anything in software.

It’s helpful if we kind of run this a little bit down to ground and make it a bit more specific for people, rather than talking about all the things that are possible. I would ask, I think my first question is, so I’m not familiar with pipeliners using digital twins for the pipe.

Is that fairly new, are people doing this? I would be familiar with it when you’re looking at design and laboratory testing stuff, but in terms of real operating pipelines, I don’t know that I’ve come across anybody doing that. I’m curious. What is the state of people doing digital twins in pipeline?

Floyd:  Downstream oil and gas, that’s the adoption phases there. We’re doing it. I would say 80 percent of our installations are integrated and create that digital twin. Midstream, upstream, the adoption phase, we’re still in the earlier stages of it, not too early, but earlier stages of it.

The show-me part of it, that’s the case where people have to have the desire to first. Again, downstream oil and gas, already there…

Russel:  When you’re talking about petrochemical, refining, the things that are the heavy process industries, that makes sense to me because there’s huge value, and those are heavy engineering operations. They really need to know a lot about the process. To me that makes sense. They’ve got a lot of rotating equipment. They got a lot of pieces and parts where this is really important.

Floyd:  A lot of mass in motion there.

Russel:  Yeah. When you start getting into the pipelines, pipelines historically has been more about dudes and trucks. We’ve always had engineers and such, but we’re late to the data party. I’ll say it that way. The way we get our data’s different.

You’ve got a processing facility, most of their data’s real-time. They’re highly instrumented, with lots and lots of real-time feeds. We’re not as highly instrumented. We’re highly instrumented around the facilities and the pumps, but not highly instrumented around the pipe itself, right?

Floyd:  Right. The kinds of data that you really need in that environment, though, if you think about it, it didn’t have that much of a requirement for instrumentation. You’re going to track a few things, right? Some stress/strain, maybe pressure, of course, flow rates, temperatures. Nothing real complex.

Russel:  Actually, I think that’s a really good point, Floyd. The key things you’re going to be looking at is you’re going to be looking at stress/strain in the pipe, you’re going to be looking at…There are all kinds of things that would bear on that, but fundamentally, all you’re looking at is stress/strain. You’re going to be looking at metal loss, and you’re going to be looking at features.

Floyd:  And CP values, right. That’s another.

Russel:  CP values. Then the other thing you’re going to be looking at is pressure and probably pressure cycles. No, I think that makes a lot of sense. Yeah.

Floyd:  Again, two things. One is operational performance, and that’s what the pipeline industry has been doing for many, many years. This is what they do, and they do it really well. The part that hasn’t been so great, but it’s better now since I guess about 2001 or so when really DOT got really involved…

Russel:  After the Bellingham incident, yeah.

Floyd:  Yeah. This is where those two collide, this is where those two connect, where the integrity part meets the process part and they both speak to each other. They both have an impact on each other. Through this digital twin, you can actually look at those relationships, look at the product, and how it’s going to affect the metallurgy. Look at the pressure, see how it affects the stress. Look at the product again, how’s that going to affect corrosion, erosion, or whatever the case may be, and use those analytics to actually make decisions with, and stop things from coming together, let’s say.

Russel:  You used the term before we got on the mic and started recording, which I thought was really interesting. That was this idea of an integrity operating window. I’ve never heard that term before we talked today, but I hear that term and I think immediately I know what that means, right?

Floyd:  It comes from API 584. Again, it’s kind of like the downstream’s kind of a little farther ahead. API 584 specifically relates to integrity operating windows in plants. However, the concept is the same for us when it comes to software.

You create the ability to input certain parameters. You connect to this data source, wherever that’s at, and when those parameters are breached, you get warnings, alarms, and then even notifications, emails if you wish to specific folks, to let you know you’re either getting close to breaching or you breached an operating window.

Russel:  I am certainly not an integrity management guy and I say this all the time on this podcast, but because I’m doing the podcast, I end up talking about it all the time. I know enough to be really dangerous. I would say that the idea of an integrity operating window for a pipeline is really pretty straightforward.

I need to know kind of the base stress/strain loading in the pipe. I’m talking about based on its orientation, it going uphill or downhill, ground movement, water crossings, all that. I need to know the cathodic health of the pipe. I need to know what features exist in the pipe, and from that I define an operating window.

An operating window is basically the max pressure I’m going to operate it at, right?

Floyd:  Yeah, exactly. Remember the stress values of your design parameters. You’re going to put the lower end of it if it’s carbon steel, you’re going to put the lower end of a pressure value and …

Russel:  This is really good, Floyd. I’m going to get a little animated about this because I think most pipeline operators, their integrity operating window is all around pressure management.

Floyd:  In many cases.

Russel:  When you start going to a digital twin, I can start doing things that I don’t have the resources to do now. There’s always a trade off in liquid pipelining between pressure cycles and product movement. To strike a balance between those things, that’s very difficult to do the way we currently do things.

With a digital twin and the ability to visualize, I actually create a way for different departments to talk about the same asset and they can say, “Well, here’s the impact this has on the asset.” Others can say, “Well, that’s what this means for me.” and so forth. It facilitates conversation.

Floyd:  It’s great for collaboration. If you think about that a step further, let’s talk about actual maintenance activities. If you’re talking about one of your compressor stations or something and you got planning work and it’s at a remote site.

Now you can look at this digital twin, actually take measurements to measure things like scaffolding height, or who knows, maybe you have to have a crane out there so you can measure off for staging a crane for a heavy lift or something.

You can do all this stuff in a digital twin and actually manage the logistics because you’ve got the geospatial information, and you’ve got your Google Maps in the platform as well that you can actually tell people how to get there, what they’re going to do. Here’s how you do it and have it all done when they get there, and yet you didn’t even have to leave the office to do all that planning. The only time you were on-site is when you actually execute the maintenance activity.

Russel:  That’s an excellent point, Floyd. The other thing that comes up for me, and this has been thematic in a lot of the integrity management podcasts I’ve done, is that what’s happening is that the tools are getting better. Their ability to identify features is getting better. Consequently, I’m getting a lot more data about the pipe.

I may not be identifying more critical features, but I’m identifying more features overall. I have a bigger set of things to manage. That’s going on universally. Pretty easy these days, particularly in a liquid system, to run a hydraulic model and I can extrapolate and understand what’s the pressure, every foot along the pipe.

I can start seeing pressure waves, pressure cycles, and other things that are acting on the pipe. And the biggest problem with all this data is you’re not going to make sense of it by wading through it. You have to have a tool for visualization.

Floyd:  It’s really hard to wrap it all in, in our heads and make decisions if you don’t have a tool like this in front of you. Again, figuring out what do you do first? You mentioned more data. There is much more data than there ever was when it comes to pipelines nowadays.

How do you determine where’s my most critical, highest priority? The risk tool is designed to do just that. It creates that 5×5 matrix that puts those high-risk areas up in this upper right-hand corner, and you know where to focus your energy.

You know where it all needs to be done. You got to do something about any kind of a feature that you’re looking at, but you want to go after those high-risk ones first in order to minimize or mitigate the risk of any kind of catastrophic event taking place.

Russel:  Yeah, sure. When you start talking about visualization of a digital twin around a pipeline, are there any standards?

Floyd:  For digital twin?

Russel:  For how you visualize.

Floyd:  No there’s many different ways you can visualize. It could be through just a 3D model. It could be through pointcloud.

Russel:  Give me a definition if you would of pointcloud.

Floyd:  That’s your laser scanning data. Pointcloud is handy. It’s mostly used if you’re starting the whole life cycle from pre-construction, through construction, and through the lifecycle of a pipeline. You can actually 3D laser scan and actually have a visual representation of that. It looks like a picture. It looks like a picture only you can give it intelligence and it’s geospatially referenced. Not only just a picture, it actually knows where it’s at in space.

Russel:  Doing a podcast, we don’t have an opportunity to look at any of this stuff, but I’m curious, how quickly can an engineer get tuned into these visualization techniques. What’s the learning curve. Is it pretty intuitive or is it pretty steep? How does that work?

Floyd:  Given where we are in society today, I know with me, my attention span is sunk. I read a report a while back and I believe maybe it was Google that did some kind of research study, and determined that humans now have the attention span of a goldfish. Yeah. 8 or 10 seconds.

I thought about that for a minute. People get used to social media, flipping through their smartphones and Internet just flipping through. It really takes a lot to get their attention. To me, that is the key component to the visualizations.

From the younger generations coming in the industry today, whereas we’ve got us older guys, we’re stepping back and being more of a mentor position to these younger guys, or retiring, or whatever the case may be.

The best way to get these guys really in-tuned and really immersed into what they’re working on is through visualizations. These visualizations, again, it’s just a matter of looking at them. Listening to what they’re telling you, looking at what they’re telling you, and you can actually make some decisions.

Whereas if you’re looking at tabulations, you might flip through spreadsheets for days before you can actually really understand what you’re looking at. It makes for a lot more immersed research and understanding, and it makes for a very quick decision.

Russel:  That certainly makes sense to me. I’ve had this conversation kind of notionally with a number of folks around the integrity management space around all the data that’s there, and how do you visualize this? How do you deal with these very large data sets and so forth?

The question I would ask is, you’re kind of talking about where we are in the life cycle of digital twins in the pipeline space. I would assert that most people in the pipeline space don’t really know what a digital twin is, or they’re just getting educated about it.

Floyd:  I think you’re right. A lot of them are, but if you think about it, the digital twin was kind of on its way. It’s really how you define the digital twin because you don’t have to have a pointcloud of it, you don’t have to have a 3D model of it, but you just need to have a visual representation of it, and you need to be able to see that in GIS, geospatial.

There are some different ways that you’re used to looking at already, which still could create the digital twin. Again, it’s a matter of giving it intelligence. That means the IoT aspect. The IoT is the enabler for digital twin, and also another good point is even the connected worker.

Even where you have guys out in the field and doing things, they’re actually doing it in a platform so that the information they’re gathering — and the data they’re gathering in the field — is immediately uploaded and available for visualizations in the platform. Yeah, this is another key component of where data comes from.

Russel:  What do you think pipeliners need to know about this whole conversation related to digital twins? What would you ask that people take away from this conversation?

Floyd:  The most important part is being able to visualize information and make decisions. Another key component is having access to all that information in one visualization, right at your fingertips, and not having to dig around in different data silos to find it, wherever that might be.

The ERP, maybe a SCADA, maybe it’s DCS, maybe it’s who knows? Shared folders, wherever it’s at. It’s all right there in one space. It takes data to create a digital twin or an intelligent digital twin. This is where you find all data and you’re either connected via remote sensors, through SCADA, or through Data Historian, also through ERP or CMMSs.

By the way, this isn’t what’s possible. This is what’s happening. We already do it downstream and now in the pipeline industry. So, a better understanding of how you can save so much time — just an example on a downstream situation would be 1,000 assets in a facility, and $1.2 million a year in savings just by one item, and that’s access to information. They call it time to find, TTF. Having access to the information, you’re not looking around for information all the time. You’ve got to get it all right there at a click of a mouse.

Russel:  That’s a huge deal in most pipeline companies. I would argue that the GIS vendors are telling you they can do it all, and the work management system vendors are telling you that they can do it all. Now the digital twin guy’s telling me he can do it all.

I would just say, I get the value proposition, but I would be skeptical about what’s it going to take to get there. Now, I should be careful about how I say that. What I’m trying to do is I’m kind of framing in my mind, what my summary of this conversation is, which I do from time to time when I do these, what are my takeaways?

Here’s what I would tell you that my takeaways are about the whole idea of digital twins around pipelining. It’s definitely part of the future. It’s going to become critical as a way to manage these very large, very complex, very dynamic data sets. I think we’re very much in the infancy of understanding how to deploy it

Floyd: Yes, the implementation is key.

Russel:  All the technology is there, but we, as an industry, are infants in terms of understanding how to deploy it and use it. If a pipeline operator were coming to me, what I would say is look for an area where you can add value and learn and grow from there.

Floyd:  Scalability is key. You’re exactly right because it all does seem overwhelming. This is one of the things that we always impress upon our customers or potential customers, don’t try to bite that whole elephant at the same time.

It’s a scalable platform, a scalable concept, and that’s the best way to approach it. Another way to think of this, too, is we’ve all been in a state of digitalization. Everyone has begun to digitalize things, especially hereafter COVID, after a little over a year’s lockdown, so digitalization is the first step. Once you’ve digitalized all of your documentation, all your workflows, then really you’re talking about digital transformation. Digital transformation is a journey, so the digital twin is in that digital transformation journey.

Russel:  I would absolutely agree with that, Floyd. That’s very well said. That it’s part of the journey and it’s going to be a big part of the future for sure.

Listen, this has been awesome. I really appreciate your taking the time to come and talk to us about all this. For the listeners that want to know more about all this, just go to the website, look up the episode and peruse through the show notes. We’ll get Floyd and his team to link up some resources and you guys can use that to learn more.

Floyd:  It was really good talking to you, Russel. I enjoyed it. Thank you so much for having me.

Russel: I hope you enjoyed this week’s episode of the Pipeliners Podcast and our conversation with Floyd. 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.

If you’d like to support the podcast, please leave us a review on Apple Podcast, Google Play, or on your smart device podcast app. You could find instructions at pipelinerspodcast.com.

Russel:  If you have ideas, questions, or topics you’d be interested in, please let me know on the Contact Us page at pipelinerspodcast.com or reach out to me on LinkedIn. 

Thanks for listening. I’ll talk to you next week.

Transcription by CastingWords