This episode of the Pipeliners Podcast features a discussion with Marissa Anderson of Magnolia River and Gary Choquette of PRCI about the Pipeline Open Data Standard (PODS) and the new SCADA Link module. The conversation explores how PODS provides a geospatial framework for managing pipeline data, the value of linking SCADA data to precise pipeline locations, and the broader implications for leak detection, hydraulic modeling, and asset management. The guests also highlight the importance of data standards and governance in advancing safety and efficiency across the pipeline industry.

SCADA Connect component of PODS Show Notes, Links, and Insider Terms

• Marissa Anderson is the GIS Implementation & Consulting Manager at Magnolia River. She is also the Chair of PODS Integrity Regulatory Task Module Work Group. Connect with Marissa on LinkedIn.
  • Magnolia River – An engineering and GIS services company that provides pipeline and utility solutions
• Gary Choquette is the Executive Director of Research at PRCI. Connect with Gary on LinkedIn.
  • PRCI (Pipeline Research Council International) – An industry research organization that funds and manages collaborative projects to improve pipeline safety, reliability, and efficiency.
• PODS (Pipeline Open Data Standard) – An industry database standard designed specifically for pipeline operators to manage and organize pipeline-related data, including spatial and attribute data.
• SCADA Link (PODS Module) – A new PODS module that connects SCADA sensor data (e.g., pressure, temperature) to their precise locations on the pipeline, improving accuracy for operations, maintenance, and leak detection. Learn More
• PHMSA (Pipeline and Hazardous Materials Safety Administration) is 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.
• GIS (Geographic Information System) – A system for capturing, managing, and analyzing spatial or geographic data. In pipelines, it’s used to visualize where assets and events are located along a pipeline.
• Linear Referencing – A method of spatially locating data along a linear feature, such as a pipeline, where events (like welds, valves, or sensors) are tied to specific points along the pipe.
• Spatial Database – A database designed to store and query data defined by geometric space. PODS uses this to map pipeline assets and events in GIS.
• SCADA (Supervisory Control and Data Acquisition) – A system used in pipelines for real-time monitoring and control of field devices such as sensors, compressors, and valves.
• SCADA Tag – A label or identifier in SCADA systems that represents a specific measurement point, such as a pressure or flow reading.
• RTU (Remote Terminal Unit) – Field devices that connect sensors and instruments to SCADA systems, transmitting data from remote sites.
• Flow Computer – A device that calculates flow rates and volumes of product in pipelines using inputs from meters and sensors, often integrated into SCADA systems.
• Hydraulic Modeling – The use of mathematical models to simulate fluid behavior in pipelines, supporting system optimization, planning, and leak detection.
• Gas Control – A pipeline operations function focused on monitoring and managing gas flow, pressures, and balances across a pipeline network.
• Line Pack (Pipeline Inventory) – The volume of product stored in a pipeline, which can change based on pressure and flow, critical for leak detection and balance calculations.
• P&ID (Piping and Instrumentation Diagram) – Engineering drawings that show the physical and functional relationship of piping, equipment, and instrumentation in a system.
• Innovative Leak Detection Project – A joint PRCI and PHMSA research initiative to enhance pipeline leak detection by improving measurement accuracy and reducing uncertainty in pipeline data.
• Noise (in data) – Variability or errors in measurement data that obscure true operational signals, making leak detection and system balance more difficult.
• Meter Balance / Pipeline Balance – A calculation comparing inputs and outputs of product in a pipeline to check for leaks or unaccounted losses.
• Inventory Calculation – Determining how much product is in a pipeline by combining measurements of flow, pressure, and volume.
• ILI (In-Line Inspection) – Pipeline inspection using specialized tools (often called “pigs”) to measure wall thickness, dents, corrosion, or other integrity issues inside the pipe.
• Pig Data / Pipe Tally Data – Data collected from in-line inspection (pig) runs, including wall thickness, dents, ovalities, and other conditions, used for integrity management.
• Class Location – A regulatory designation in gas pipelines that defines population density along the pipeline route and drives requirements for design, operation, and safety.
• HCA (High Consequence Area) – Pipeline locations where a release could have significant impacts on public safety or the environment, requiring heightened safety and monitoring measures.
• Depth of Cover – The thickness of soil or material covering a buried pipeline; important for safety, integrity, and regulatory compliance.
• Seam Type – The type of weld seam used to manufacture a pipe, which can affect pipeline integrity and inspection results.
• Wall Thickness – The thickness of a pipeline’s steel wall, a critical attribute for determining pressure rating and safety margins.
• Digital Twin – A digital replica of a physical asset (like a pipeline) that uses real-time data and models to simulate, analyze, and optimize performance.

SCADA Connect component of PODS Full Episode Transcript

Russel Treat: Welcome to the “Pipeliners Podcast,” episode 405, sponsored by EnerSys Corporation, providers of POEMS, the Pipeline Operations Excellence Management System, operations and compliance software for the pipeline operator to address safety program management, control room management, and field operations. 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, Russell Treat.

Russel: Thanks for listening to the Pipeliners Podcast. I appreciate you taking the time. To show that appreciation, we’re giving away a customized YETI Tumbler to one listener every episode. This week, our winner is Brett Kurkowski with Tallgrass Energy.

Congratulations, Brett. Your YETI’s on its way. To learn how you can win this signature prize, stick around till the end of the episode. This week, we speak with Marissa Anderson of Magnolia River and Gary Choquette of PRCI about the recent SCADA Connect release of PODS, the Pipeline Open Data Standard. Marissa, Gary, welcome to the Pipeliners Podcast.

Gary Choquette: Thanks.

Marissa Anderson: Thanks, Russel.

Gary: Pleasure to be here.

Marissa: Yes.

Russel: Glad to have you guys. Let me do what I like to do as a way to kick this off, ask you guys to introduce yourselves, tell us a little bit about who you are, what you do, and how you got involved with PODS. If you don’t mind, Marissa, can I ask you to go first?

Marissa: Sure. I hold the role in PODs as the PODs technical coordinator. I work with the technical aspect of the data model. I’m also a GIS manager at Magnolia River. I work with the PODS data model every day.

I had an idea for the PODS organization, and I presented it. Ever since then, I’ve been involved with the organization. That idea was the regulatory module. That’s now available for download.

[crosstalk]

Russel: Awesome. We’ll have to ask a little bit about that as well because I’m curious what y’all do there. Gary, same question, a little bit about yourself, what you do, and how you got involved with PODS.

Gary: I am currently the executive director of research with Pipeline Research Council International, aka PRCI. My background is pretty much jack-of-all-trades related to pipeline operations, which included, and in my stint, a large portion of hydraulic modeling, system optimization, gas control, those types of functions.

Russel: You may not have that some of that background in common for sure.

Gary: Yeah. Obviously, data was a large part of my previous role. PODS just naturally fit in that it’s a way to organize and manage data.

Russel: For listeners that maybe are new or haven’t heard some of the other episodes I’ve done with PODS, can one of you guys tell me a little bit about what is PODS? What is your charter? What is your mission? What you do?

Marissa: PODS stands for a pipeline open data source standard. It’s a template database that you put your data into. When you download the database, it’s an empty database, and you can load your own data in. It’s geared towards transmission and gathering pipeline operators, the midstream sector.

It contains the attributes, the dropdown values, domain values that are geared for those systems. It’s also based on linear referencing. Which means that the pipeline holds the location, and all the events are draped off of that pipe.

It features it’s a spatial database, which isn’t important. A lot of other databases out there are just relational. There are a series of tables, but this is a spatial database geared to be used in GIS, so you can see the locations of your data.

Russel: Yeah, I remember very early on when I was getting involved with pipelining deeply, this is over 20 years ago, when PODS was a fairly new thing and when people were just learning about…They were at the end of what you could do with relational databases, and they were all struggling with how do you do this in a relational database?

Yeah. I think PODS has filled a very important need in the industry. You’ve basically built a database approach specific to pipeline.

Marissa: Yes, exactly.

Russel: It’s way more robust than when I first saw it all those years ago.

Marissa: We’ve added more to it. We have a lot of different committees, a lot of different modules being added to it that users can pick and choose, and see which ones they want to download that pertain to their organization.

Russel: For people that aren’t familiar with GIS, maybe don’t work in that, the nature of those data structures is different than what you find in typical databases. The nature of data in a pipelining world is different because it’s all about where it occurred on the pipe.

Everything is about where was it done on the pipe. Everything’s anchored back to where does it exist on the pipe, which is unique to our business. It’s unique to our business.

Marissa: Not only where it existed, but what’s around it in the environment and how can you tie that in.

Russel: Exactly. I talk about this. I got this from a friend of mine. He talks about why it means a lot to be a pipeliner and what’s unique about being a pipeliner. What’s unique about being a pipeliner is our critical infrastructure runs through people’s neighborhoods.

GIS is the way we know where our pipeline is and what’s going on with the pipeline versus what’s going on around the pipeline. From a risk management standpoint, from an operations standpoint, that’s mission critical for sure.

What drove the need for SCADA Link? SCADA Link is one of the newest modules that you put out. I participated in a couple of the technical calls. I will confess I started with a fairly big misconception about what you were trying to do with SCADA Link. Maybe tell us a little bit about, what is SCADA Link with PODS? What drove that need?

Gary: Fundamentally, SCADA Link is a way to tie physical SCADA data points to where it actually physically connects to the pipeline. That could be pressures. It could be temperatures, could be gas chromatographs. Any sensor that you put on the pipeline, it’s a way to tie back where it resides.

The driver for that really hinges from, again, my days back in system optimization and gas control. We would know roughly where a sensor was based on some kind of naming convention for the sensor, a discharge pressure on a compressor station, but that didn’t always exactly match up, in your mind, where it physically was installed versus where conceptually you thought it was installed.

This is just a way to really tie the data down to exactly where it resides. Specifically, this implementation was driven by a portion of a project that PRCI is doing as a research project in conjunction with PHMSA to enhance leak detection technologies. Again, for any online system with CPM and the like, it’s really critical to match up where the data is relative to the hydraulics of the pipeline.

Russel: I wish I had a nickel for every hour I’ve spent trying to figure that out in my career, like where I think the instrument should be versus where the instrument actually is. Just in a simple thing, like understanding where your meters are located and how they relate to doing a balance, it’s a big dadgum deal.

[crosstalk]

Russel: very much. The bigger you are as a company and the more meters you have, the more non-trivial that is.

Gary: Exactly right. It’s got a lot of other tangential benefits too. Now, like Marissa said, it’s a geospatial database. You can actually, if you’re doing PMs for calibrations or whatnot, you can actually optimize your route based on…Now I know the actual lat/longs of these.

If you have a problem with the sensor, you might say, “Who’s the closest tech to that sensor?” All that is available now as a capability. Whereas before, you’d have to just generally know.

Russel: [laughs]

Russel: I could tell horror stories about that. I literally could tell horror stories. I’ve probably done more than two dozen SCADA builds in my career, either standing up a control room or doing some major kind of lift on a control room. Every single time, it started with a walkdown. Every single time, probably 20 to 30 percent of what people knew was wrong.

It materially impacted things about how you either operated the pipeline or how you balanced the pipeline or something, just because a pressure was on a different side of a valve or something like that. It just matters. It matters a lot.

Gary: It does. Absolutely.

Russel: For a lot of people that are running old infrastructure, getting that stuff accurate is a challenge, for sure.

Gary: Just think about all the personnel turnover that we’re having in the industry too. A lot of these technicians have been out there for years and years. They can walk right up to it. They know where it’s at. Now you have somebody new that has to take over for that technician.

Again, having the actual geospatial component to that, they could walk right up to a lat/long point and say, “Here’s the transmitter that I need to address.”

Russel: Or you have a hydraulic engineer that’s trying to do some planning. They’re working off of old P&ID drawings that nobody’s verified. That never happens, right?

Gary: [laughs]

Gary: Let’s talk a little. I want to talk a little bit about what SCADA Link is and what it isn’t. When we first started, when I first got involved and got invited to participate in some of the committee discussions, I was asking a lot of questions about SCADA tags. This is not about SCADA tags.

Gary: Not directly.

Russel: This is about instrumentation.

Gary: SCADA tag is one of the fields in the database. That allows the ability to link the data in PODS to what gas control or whoever’s actually using. That’s one of the parameters.

Obviously, it’s a lot more than that. It’s what is the sensor. If you want to get down to the make and model, you could add that as data. You could put last calibrated data. There’s lots of different levels you could add. Mostly, it’s this is where it’s physically connected on the pipeline.

If the gas control operator is seeing something unusual with that point, it lets them and/or the leak detection experts or the optimizers really drill down into, is that a real physical issue, or is that just an error in the sensor? If it is, where do you go to pinpoint it and address it based on the lat/long-type data?

Russel: You mentioned that PRCI is involved with a project that’s helping to drive this. Can you tell us a little bit about that project and what it is?

Gary: Certainly. It’s called Innovative Leak Detection. It is a multi-year project, co-funded between PRCI members and PHMSA, that fundamentally is how do you enhance leak detection technologies as a whole to remove noise from the system. What I mean by noise is every measurement that you have, every meter is going to have some natural uncertainty in it.

Add on top of that, especially on gas pipelines, you have the pipeline inventory, the pack itself is a key component in trying to determine do you have a leak or not. You can measure the ins. You can measure the outs. You can measure the change in inventory in the pipeline. In an ideal system, all that equals zero. Ins equals outs, but it doesn’t happen that way in the real world.

The primary function of this project is how do you systematize removing uncertainty and noise in your measurements, both at the meter level and at the pipeline inventory level, such that if you do see a change in lost and unaccounted for, it’s more likely to be a true leak or theft or products leaving the system you’re not expecting. You can identify it more timely and at smaller thresholds.

Russel: I’ll talk to this a little bit. If I’m using some kind of computational pipeline model, so something that’s running in real-time, taking the data from SCADA…It’s calculating real-time line pack. It’s looking for balance. It’s looking at balance every one minute to five minute. Little things make a big difference.

Little things like where exactly is the meter, where exactly is the pressure, what exactly is the diameter of the pipe, those kinds of things, they end up making a big difference.

Gary: Some of the things we’re finding in our research is — again, this is a bigger issue for gas systems because of the compressibility of the product — there’s a lot of error in the inventory calculation. A lot of the common applied methods for pack calculation are wrong. They assume I’ve got a pipe of 28 inch inside diameter. That actual diameter is really super critically important.

Especially if you have pipelines where the pipe diameter is not uniform or it’s partially looped, the simple volume diameter calculations that most system operators currently use in their SCADA systems will underestimate the total inventory in that pipeline. That’s because of the pressure loss in the pipeline.

Where it’s looped, you have a lot less pressure drop per mile. Therefore, it acts like a bigger diameter than it actually physically is, compared to the average weighted diameter for that pipeline.

Russel: I would also say that things like depth of cover, elevation, things like that, if you’re really trying to dial it in tightly, and particularly in a gas system, those things can have a material difference. They can impact your overall accuracy and uncertainty.

Anybody who’s done this kind of work in the last 30 years, they were thinking they did pretty good knowing they had a meter in, a meter out, a pressure at both ends, and gas analysis. Let’s do a calculation. They were thinking, “That’s way better than what we used to do.”

Gary: Honestly, with what we have for technologies today, especially with data systems, we can do so much more than we’ve done in the past. The advantage of having it as a standard data set versus each operator trying to come up with their own system, that really makes adoption of the technology, the implementation of the technology a whole lot easier.

Then you don’t have to match up to all these different formats. That’s where PODS really brings high value to the table.

Russel: No doubt. Getting to an agreed industry standard accelerates everything because we’re not chasing what is the data. We know what the data needs to be. We’re just trying to get the data populated. We can focus on getting good data versus what the data should look like.

Gary: Then it allows integrations with multiple different other systems because you have a common interface.

Russel: What are some of the other things that are applications for SCADA leak? We’ve talked about leak detection. What are some of the others?

Gary: We talked about, for the maintenance of the transmitter, that that certainly simplifies it. As far as asset management and tracking, there’s lots of potential there, linking it with maintenance management systems.

When was it last calibrated? When was it installed? Where do you have really old transmitters that maybe are potentially in need of replacement? Just information is knowledge, and knowledge is power kind of thing.

Russel: Some of the things I’m thinking about are more around…Well, I’ll say this this way. A lot of the hydraulic engineering tools and the computational pipeline modeling tools, the simulators and so forth, they’re all driven by they have to have all that information about the pipe and the system to be able to run their math and do their simulations.

The idea that I have one place that is my source of truth and I can get my data from the source of truth, the level of work required to maintain the care, and feeding required for some of these more advanced modeling tools and engineering tools comes way, way down and gives me a lot more value.

Gary: Absolutely. I 100 percent agree. One of the things that people often overlook is, again, how critical that diameter is.

How many times a pipeline gets modified, you have to reroute because somebody’s doing a moving a road or highway or somebody wants to build a house, whatever it is, a lot of times those hydraulic models don’t get updated to match the actual field install.

Having it tied to a dataset allows you to automatically export that and say, “Is my hydraulic model still current, or has something really changed?”

If you have a system where you’re assuming it’s the same diameter everywhere, but we know that’s not really the case because you have, again, higher design factors, Class 3 locations, more wall thickness, it’s the diameter to the two-and-a-half power. A small change in diameter highly impacts the hydraulic capability of that pipeline per flow.

Russel: Yeah. Something like going into an old piece of thin-wall pipe and pulling it out, and you take out two miles of pipe and you put in two miles of pipe. Now it’s thick wall because you’re doing some kind of integrity remediation. That impacts that. It makes a difference, and it’s larger than what people realize.

Gary: Yeah, absolutely.

Marissa: In PODS, the pipeline sensor is a point, and it’s on top of a pipe segment. That segment is where you have your diameter, wall thickness, seam type information. Since that sensor point is part of the pipeline, it also links to the rest of the assets, where the valves are on the pipe, where the flanges are, etc.

Then you can also pull your depth of cover, like you mentioned, for that pipe. You can pull your class information, your latest class for the pipe, if it’s gas, if it’s HCA, or spill analysis, and you want to pull that in. Any of the analysis that you’ve put into PODS can be related back to that sensor point, and you can extract that and include more granular data, too.

Russel: Yeah. That actually brings up another kind of interesting question. To what degree does wall roughness impact simulation and hydraulic calculations?

Gary: Yeah. It depends on where you are in the actual flow rate of the pipe, right? As far as laminar versus turbulent and all that kind of stuff. A lot of times, you can get by, right? That if you have pipe that’s not subject to internal corrosion, usually some simple assumptions will get you by fairly well.

That’s not always the case. Honestly, I think the bigger problem is where are you accumulating liquids or other grime in the system. That’s probably a more frequent and bigger impact. Again, that’s the importance of matching up what the ideal hydraulic models are versus what’s actually happening in the real world.

What’s actually happening in the real world is only as good as how accurate your pressure transmitters are, and knowing exactly where they are on your pipeline.

Russel: I think one of the things that we’re saying here that is compelling to me is typically we have thought about doing this stuff, primarily focused on the sensors, but now we’re talking about being able to do it focused on the pipe itself and what’s on the pipe.

Gary: Yeah, exactly.

Russel: That allows you to do a level of tuning in the model, a level of tuning in the leak detection performance that really wasn’t available previously. Now, it has other issues in terms of computational load and all that, but it allows you to get to something you couldn’t get to before.

The fact that now there’s a model and the folks that are building the hydraulic models and the simulators and all that can start looking at building an interface so that they can accept PODS data, that’s a huge deal, particularly for folks that are running simulators.

One of the things that makes simulators for training in gas control so prohibitively costly is the level of effort to configure them and keep them configured. This could radically, radically change that.

Gary: Agreed.

Russel: Anything else that you think is a benefit of SCADA Link, maybe another application we haven’t talked about so far?

Gary: SCADA Link goes beyond just the transmitter itself. It also includes some of the RTUs and flow computer-type information connected to those sensors. Again, taking it beyond just the endpoints, it allows you, again, to better manage your total assets. Again, where do you have older hardware that potentially needs to be replaced? Where is it located?

All that could even feed into dynamically generating lists for construction contractors to go out and…

[crosstalk]

Gary: equipment and all that kind of stuff.

Russel: There’s so much value in, simply stated, having good maps, good, rich maps. There’s a lot of value in that. Most people don’t have it, particularly around this kind of equipment. It creates an opportunity now to start getting a real good handle on that.

Where is the industry in terms of deploying PODS SCADA Link? Has anybody done anything so far? Is there anything that we ought to be keeping our eyes on about implementation and deployment of PODS SCADA Link?

Marissa: Operators have downloaded it. I know they’re looking at it and testing it. It’s a module. For people who are already on PODS 7, they can add it into their existing database. If they’re not on PODS 7, you can download the feature classes and add it to your existing database.

It won’t be a part of APR, which is the PODS 7 location referencing, but you can add it to older databases as well. It’s just a schema that you can add in.

One of the questions I had was, what do you do if you don’t know where your sensors are? You know they’re on a piece of pipe, but you don’t know where on that piece of pipe. We did add a pipe segment identifier into that sensor feature class so that you can start by putting them in the database. Then, as you go out with your GPS unit, you can refine the location because data is not always perfect.

Russel: [laughs]

Russel: Data is rarely perfect. Awesome. Listen, I find this really interesting. I think it’s fascinating. Unfortunately, I’ve never really had an opportunity to work with GIS. I’ve worked around it a lot, but I’ve never actually worked with it.

There’s some things that come up for me that I think could be really compelling around…How would I take this data and get it into a digital twin? How do I create a hydraulic model and turn that into something useful and meaningful? How do I make that quick and easy? There’s questions that come up for me about that.

This is something that I’m going to have to keep my eye on because I think it could have some real value for the industry.

Marissa: How do you incorporate the pig data, the pipe tally data? Because you mentioned roughness. Your pipe tally data is going to have your dents, your ovalities. It will measure your wall thickness at each piece.

Gary: That echoes where I was headed. We could go so much further in the industry with just more and better data. ILI data is a good example of that. Being able to track run over run, the changes in a corrosion pit depth. Is that a corrosion growth rate? Comparing different types of tools’ performance, run versus run, that’s got value.

It’s all about what can we do with more data and, from an analytic perspective, if there’s an opportunity there, making sure that we have a corresponding data standard in place, just so that it doesn’t take a lot of effort to manipulate different data sets before you can do the analysis. The standard is so important.

Russel: It’s foundational. We’ve been talking obliquely, if you will, about data quality, like, “I have it all. It’s all accurate. It’s all timely,” all that sort of thing.

When I start looking at these kind of projects, there’s two fundamental prerequisites to all the other stuff that we want to do. The first is we have to have the standard for the data. The second is we have to have governance for the data. Without those two things, it’s hard to get to the value that good data promises.

Gary: What happens if you don’t have those standards is every operator develops their own ad hoc, de facto standard. Then you have company mergers or trying to work and coordinate with other people or other people doing data analysis.

There’s so much effort to build the different interfaces with all these different types of formats that it really gets to the point where some of it’s just not feasible to do.

Russel: That’s absolutely true. I find this whole conversation about data and data governance — I don’t know — to me, it’s often overlooked. It’s not often well understood. We tend to assume, “We’ll just put it in a database. It’ll be good.” No, not really.

That’s like saying, “If I put the paper in a file cabinet, I can find it.” No, not really. [laughs] Have to have a way to index it and locate it.

Gary: Maybe you can get a little ChatGPT-based robot to…

Russel: [laughs]

Russel: crawl in your drawers and search for it.

Russel: Right. That’s what we need. We need a ChatGPT-based robot that goes out in the field and finds all of our stuff.

Gary: [laughs]

Gary: There you go.

Russel: Somebody’s probably working on that. When you think about it, somebody’s probably working on that. Anyways, look, it’s about time. I think we’re coming to the end of our time. Like I said, I think this is a fascinating conversation. It certainly queues up some ideas for me. Any last words or comments from you guys before we wrap up?

Gary: I’ll just take a plug. Number one, I’m going to get on a little bit of a soapbox, if you don’t mind, to, number one, express my sincere appreciation for what you do, Russel, to help educate the world about pipelines as a whole.

The pipeline industry, most people in the US don’t know it, but more than half of their energy that they use on any given day comes to them via a pipeline. The fact that they don’t know it is a tribute to how reliable the pipeline systems are.

We do have failures. When the failures happen, it’s not good. Anything we as an industry can do to reduce and eliminate those failures, we need to be doing. This is just one small step that we described here, of what the industry is doing as a whole to continually improve.

As a transportation method, pipelines are one of the most safest ways that we can move product. There are far fewer fatalities or injuries associated with pipeline transportation than there is with most any other transportation system, including walking across the street.

Just think about how critical our infrastructure is and what our modern society would be like if you suddenly turned off all the pipelines. People would die.

Russel: The reality is, if you shut down the pipelines, society would collapse. Because we wouldn’t have fuel to put in our cars. We wouldn’t have gas to run our lights and our air conditioning. Anybody living in the summer in Texas without air conditioning is going to go crazy in about eight days. I say this based on my experience following some hurricanes in the Houston area. [laughs]

Gary: Again, thank you for what you do, Russel, to help the industry keep pushing forward and making us perform better and keep that diligence to make sure that we have reliable assets that can safely provide what our society needs.

Russel: Gary, thanks for the kind words. I appreciate it. It’s become a labor of love, for sure. I will also say that one of the things I frequently say about pipeliners is we’re like offensive linemen. We only get our number called on the PA when we screw up.

Gary: [laughs]

Gary: There you go.

Russel: The best of us, you never heard of.

Gary: Hidden heroes. That’s my phrase.

Russel: Marissa, any final comments before we wrap up?

Marissa: If you’d like to take a look at the SCADA Link module, you can go to the PODS website, which is pods.org. There’ll be a link on there where you can take a look at some of the information about it. For members, you’ll have access to download it and take a look at what the feature classes are.

Russel: Thanks for that. That’s great. One of the things we’ll also do is…There’s a PDF document that we were provided. We will load that up on the Pipeliners Podcast website, attach it to the show notes for this episode. We’ll provide a link to the PODS website that takes you directly to some information about SCADA Link, try to help facilitate, get the word out.

Great. Thank you, guys. I enjoyed it. We’ll have to have you back again soon.

Gary: I would welcome that. It was fun. Thank you, Russel.

Marissa: Thank you.

Russel: I hope you enjoyed this week’s episode of the “Pipeliners Podcast” and our conversation with Marissa and Gary. Just a reminder, you should register to win our customized Pipeliners podcast YETI tumbler. Just visit pipelinepodcastnetwork.com/win and enter yourself in the drawing.

If you’d like to support the podcast, you can leave us a review. You can do that wherever you happen to listen. There’s instructions at pipelinepodcastnetwork.com.

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Russel: Finally, if you have ideas, questions, or topics you’d be interested in, please let me know on the Contact Us page at pipelinepodcastnetwork.com, or reach out to me on LinkedIn. Thanks for listening. I’ll talk to you next week.