Episode Transcript
Rhett: On this episode of Pipeline Things, we discuss Chris's ever-growing challenges with choosing restaurants and the difficulty with going out to dinner with him and his wife. If you've been there, you know what I mean.
As a side note, we have our great guest returning to discuss the really shocking conclusions in an IPC paper. And if I asked you, would you expect MFL to perform better than ultrasonics and selective steam oil corrosion, what would you say? Well, hang on and find out what our authors say.
All right. Welcome to today's episode of Pipeline Things. I am, again, really excited to be in this series because where we're talking about today is we're going to be bringing back a return guest. I think a super esteemed, really well-known, well-beloved member of the pipeline industry.
And we're going to be talking about what I think was actually a very good crop of IPC papers and one in particular today. Before we get into that, though, Chris, you know, Chris, I don't know if you're aware of this or not. You probably are. Do you know that you're difficult to go to dinner with?
Chris: Oh, I actually know exactly where we're going with this now. This is so easy. I actually am not. No, no, no, no. I get to answer. I get to answer. It's all about setting expectations.
Rhett: Well, the expectations of my wife is she is afraid to go to dinner with you and Amanda because she's like, if I pick a restaurant, Chris is going to hate it.
Chris: That is not true. It is not true. It's all about setting expectations. If she was to say, hey, we're going to take all eight of our kids to go to dinner, I'd be like, oh, it's all for a game. Where are we going? Hat Creek? Let's crush this. We can go to Chuck E. Cheese for all I care.
But if you're like, we're going on a date night, and I paid for a sitter, we're getting a good meal.
Rhett: That's just a good meal defined by Chris. Here's the problem. If you've not been to dinner with Chris, Chris goes with very high expectations as a foodie.
Chris: That is not true.
Rhett: These are all false expectations. It's borderline verbal assault with a waiter. She's going to get at least 20 questions about what her favorite item is. What would she order if she was on a desert island? What should he avoid? Do they make the sauce with homemade ingredients? Are the herbs grown in the backyard?
And then after she answers all those questions, Chris will order. something completely different.
Chris: Maybe restaurants should just have a performance spec and then I can do all my homework before we get in there. You know what I mean? This is pretty easy.
Rhett: So what I was laughing about, though, is that if you ever ask Chris, What his opinion is on a restaurant, A, you're going to get an opinion. And it might not be a good opinion. He might say something like, that restaurant's terrible.
Chris: I would say it's not for me is what I would say. Oh, he might say it's terrible. Because we all have different tastes. It's like movies, right? You have your own tastes.
Rhett: Well, the reality is you find out, well, oh, Chris, you didn't order this. Or, oh, you didn't do that. Or, wait, you went to that location? Well, that location's different.
Chris: I asked the waiter. It's not my fault it wasn't good.
Rhett: And then Chris writes it off. And the reality is you've got to ask a few more questions and you find out, well, Chris, your experience honestly wasn't really representative of everybody else's experiences.
Chris: Which is also why I don't write Google reviews. I keep these thoughts to myself.
Rhett: Thank God. We'd probably get sued if you wrote Google reviews on most of the restaurants that we've been to.
Chris: Look, I hope that many of you out there that have dined with us have enjoyed y'all's experience because of the art.
Rhett: Just don't ask Chris what he thought of it after. That's what you don't do.
Chris: If you pick. If I pick, usually it's okay.
Rhett: This ties into today's episode really well.
Chris: This is so good. So people are going to start calling me for recommendations based on the show today?
Rhett: Yes. We're launching a second podcast, which is Pipeline Food. No.
The reality is it really ties into today's episode because as we talk about today's episode, there were some conclusions, striking conclusions that were drawn. in this uh and before we bring on our guest
Chris: I will say this though as part of this I will lead into it I will say this I usually don't put anything in there I think it's more about the journey not know so much the results it's very much like how i prep to go to dinner with either a client or with friends or by myself because I’m in I’m hungry it's setting those expectations from the beginning and saying what am I trying to get out of this meal?
And I feel like today's podcast is, this is so perfect. You did such a good job with the segue. I think as you guys are listening through today's chat, think about that, right?
Like what was the intent, the expectation, what do we try to get out of this thing today? And I'm really excited about how our guests are going to walk us through that.
Rhett: So. The paper that we're talking about today is IPC 2026-186359. The title is Evaluation of Selective Seam Weld Corrosion Inline Inspection Technology Capabilities, authored by Zach Booth, Tom Bubenick from DMV, and Josh Bremner from P66.
Before we get into it, I want to say the reason that I, like, just read the abstract, and it's like, generally ultrasonic tools did not perform as well as MFL.
If I state that conclusion with no qualifications, I guarantee you every listener right now just turned up the volume, got focused, pulled over to the side of the road.
Chris: Do we need a disclaimer? That is not our perspective. This is something that was in the report. Do we need to start disclaiming that?
Rhett: And that's my point. In this podcast, you're going to need to listen to it all the way to the end to understand the qualifications on that statement and the conclusions that were drawn because it was a really well done study.
Chris: This match is not endorsed or accredited by.
Rhett: It is endorsed by me. And without further ado, we are going to introduce our guest on the podcast. Tom, welcome back to the show. Zach, welcome to the show. So far, again, as I've already alluded to, our guests will be Tom Bubenick and Zach Booth.
Tom, you've been on before, but if you don't mind. Since the last, I think it's almost been two years ago. What have you been up to in the last two years?
Tom: Wow, that's a long time ago. It's hard to remember that it's been two years.
Rhett: If you could summarize it in three sentences, ideally, it would be great.
Tom: I was thinking about a few things as well, and I realized that I've actually been around, you'll be surprised, 48 years. I've been working in the pipeline industry.
Rhett: Congratulations.
Tom: Well, about 1979. So that's almost 50 years away. That's a long, long time ago.
Chris: Thank you, Tom.
Tom: Lucky enough to work with some great people over the years. And I've learned so much from them. And that's one of the things I hope that we're able to convey a little bit here today is the importance of learning. And Zach Booth, he's one of the guys that's doing that.
Rhett: Zach?
Tom: Podcast as well. So good to have him.
Rhett: Zach, tell us, if you don't mind, introduce yourself to the audience. Tell us a little about you. And again, welcome to the show.
Zach: Thank you. Yep. First time. Excited to be here. So my name is Zach. I have been at DNV as an engineer for 10 years now. Graduated from the Ohio State University.
Rhett: Hey, can we edit that out? Is that mis producer? Can we just edit that part out right there?
Zach: That gives me my own level of standing here, I think. I'm an integrity engineer. I work on a lot of in-line inspection projects. I've helped operators basically run their dig programs where I'm receiving their dig results and helping them determine what to do at those locations.
And then I've also worked on a lot of projects that are joint industry type of projects to improve inline inspection tools, including both crack tools and the project we're discussing today, which include both MFL and UT.
Chris: You know what I just realized?
Rhett: What?
Chris: Zach, I think you're the youngest guest we've had on the podcast.
Rhett: You sure about that?
Chris: I think so. And when I think of you, also think of YPP. Aren't you pretty involved in YPP, Zach?
Zach: Yes, thanks for reminding me of that. I've been involved with YPP for a long time. Started out just helping out where I could. Ended up planning our flagship event for a couple years, our YPP symposium. So was setting the agenda, gathering all the speakers. And now I am our vice chair.
Chris: Yeah, I love it. So took a little opportunity there. Everybody's listening. YPP guys get involved. We love it. We love what these kids are doing.
They're doing a great job. If you're more like Tom and maybe closer to Rhett and I's age group, get involved, right? Raise your hand. Try to be a mentor. Plug in. let's keep these guys excited and engaged.
So I was really excited when Tom mentioned that you were in the projects. I was like, man, this is a great opportunity to bring you in because I love this sandwich here, right? It's like Tom, us, you. It's perfect. Love it. Welcome to the show, bud.
Rhett: So I'm going to jump right in. So the paper that we referenced, IPC 186359 from this year, revolves around the PRCI project into E413. And before I give you a chance to just describe that project, Zach, I want to set the stage for the audience.
Because while I do welcome emails, in fact, I relish challenging emails, I want to set the stage for all the vendors that are listening out there and to the operators that the results of this study apply to the specific systems that were tested, right?
And so some statements are going to absolutely be made in this podcast that some people will find incredulous, maybe even they disagree with. And you're going to need to hang around to the very end to hear them clarified and don't take the statements out of context.
But they really speak to the importance of qualifying individual ILI systems and the time that needs to be put into individual ILI systems.
And I might say the danger of characterizing technology as a whole, hence my segue with Chris because he just broad strokes restaurants based on one experience.
You know, here, you really want to be careful with that. So, again, I... I love this paper. I'm really excited about this podcast. So without further ado, Zach, if you don't mind, can you set the stage and tell me a little bit about the background of this project and how y'all set up the test setup at the PRCI facility?
Zach: Yeah, so Josh Bremner was the lead of the project and his goal when introducing this project was really actually focused on the identification side. So can you...differentiate selective seam weld corrosion from coincident corrosion on the seam, because that would just be such a, in and of itself, would be such a significant leap for the industry, if we're capable of doing that.
So we had 10 pipe joints where we manufactured selective seam weld corrosion, and those pipe joints we chose specifically because we had some eddy current testing, where we knew that there was some natural CMR defects on those joints.
So we thought that would provide a little bit more of a challenging environment for the tools that were running in the flow loop and pull string tests than just like brand new pipe where sometimes there's this stigma that manufacturing defects are too easy to see and they don't provide a challenge.
Rhett: I love it.
Zach: Tools. So. I can get into the manufacturing process of the actual defects. I can get into the analysis process we'd like.
Rhett: Yeah, no, let's talk a little bit about if you don't mind. So I like the fact that y'all use vintage material. I think that's important. And the process I do think is important, right? So let's dive into that a little bit. So obviously you're simulating selective seam weld corrosion. Can you talk a little bit about how you did that and the process that you used? And then I'll ask a follow-up question after that.
Zach: Yeah. So we started by manufacturing corrosion profiles in certain locations over the seam weld. So we wanted these corrosion profiles to look relatively natural, as natural as we could make them. So we didn't overly design them.
They were a little bit ad hoc. We had the...manufacturer that we were using, we gave them a length and a width for the corrosion profile. And then they were free to sort of play with what the actual profile looked like.
And we specifically told them we wanted there to be deeper areas and shallower areas. And I think that turned out pretty well. If you look at the corrosion profiles within the paper, you'll see that I think they look pretty natural.
And then we used an EDM notch to create the selected seam up corrosion over the profile. By using the EDM notches, the manufacturer ground the edges of the profile to create sort of a semi-ellipse so it wasn't just a square bottom.
And then by having an uneven profile that you are using the EDM notch on, that's also going to create some ridging on the bottom of the... profile to create a little bit more of an uneven surface
Rhett: yes this was really I'll vouch for what you're saying there Zach, it's really well thought out I was showing Chris the figure four as like it's got a it's a pretty corrosion profile if I can use that word for corrosion like really varied across the thing um and then i want you to talk a little about that so you you guys had 104 artificial defects right did y'all very give me give me a picture because SSWC doesn't all look the same some of it looks like you could slide a dime right through the middle and that's all you see, some of it looks very wide uh did y'all also variability the very did you variability did you vary the shape of those can I use the word groove or groove ratio
Zach: yeah so we uh one the uh EDM notches were ground also and the other profile direction so they had a v-shape to them uh there's i think there's a picture in the uh paper where we uh show that um that cross-section vehicle and then the width of the EDM notches ranged from four millimeters down to a half
So we had a wide variety of ranges, and the lengths of the selective seam weld corrosion also varied from one inch up to 10 inches. So, we were really trying to capture a wide range of anomalies to see how the performance would change with the changing metrics.
Thomas: One of the reasons we did that was to try to represent a range of severities from kind of minor to really severe yeah so we get defects in there that were as shallow as oh 10 percent or so and as deep as 80 or more percent
Rhett: so the the next question i'm going to have is uh ground truth right so how did you guys establish truth in measuring these profiles um you can you speak to that
Zach: yeah so this is actually this was a challenge for the project and i think is going to continue to be a challenge for the industry um we put a lot of effort into the NDE efforts in this project.
Laser scan was the simplest method that we used and what was used as truth for the majority of defects. But in some cases, the defects were too narrow for the lasers to see all the way to the bottom.
So to account for that, we tried to use some phased array. But typically the profile next to the notch was too varied to have any success with that we also tried to use molds where we would make a mold of the defects the mold and then scan the mold itself and we had issues establishing a true zero reference point with that um so ultimately to make sure we had reliable truth data we destructively tested about 25 of the defects we manufactured so that included both cross sections and cryo fracture through the axial plane
Rhett: Yeah, I love that. So just to give the audience some, some, some, some repeat there. So you guys manufactured in the paper, 104 artificial defects, right? With a combination of, this is not just machine corrosion, which I love. I love the realistic, like kind of uneven pattern throughout it.
Then you did an EDM notch through the center of those corrosion patterns, right? And you had variations in the profiles above that EDM notch, which are great and variations in the depth.
I thought it was interesting in here. You said of the 104 defects, the laser profilometer successfully scanned 87, right? So about 20%, you know, for the audience's benefit, struggled from a laser profilometry standpoint, which I think is something absolutely to be aware of in the ditch.
And then you're right. I really love the fact that you guys set ground truth based on the destructive metallography when necessary.
So now that we've got solid data set. They got solid measurements on the data set. Tell me, how did you execute the pool test? And can you give me a you can't tell me the names of the vendors. I know the innocent will be protected for the sake of the innocent. But can you tell us the makeup of the vendors that participated in this program and how they were run through these samples?
Zach: Yeah. So the MFO, we had a total of seven vendors who initially ran through the pull string and flow loop tests. The MFL vendors all ran in the pull string and that had a makeup of mostly MFL-A plus the MFL-C tools. We did have one MFL run that was just the MFL-A.
We gave each vendor an opportunity to run at multiple velocities and multiple passes of each velocity because we also wanted to evaluate the repeatability of the analysis over multiple passes and over multiple velocities.
And then we had two crack tool runs that one was an EMAT and one was a UT CD plus the UT wall thickness tool. And the UCD tool ran through the flow loop while we conducted a full string test with the EMAT.
Rhett: Gotcha. So just to give the audience some perspective, three MFL tools, one UCD tool, and one EMAT technology participated in this. And before we go to break, the last question I want to ask is, at a high level, how did the execution of this go?
Was this give us your sizes and then that's the end of the project? Or was there a give and take, a back and a forth here with the vendors? How did you design that to happen?
Zach: Yeah, so that was really important for the project. The project was a research project. We didn't perceive steam well corrosion specs from the beginning, and we were really trying to understand what the capabilities in this area were.
So it wasn't just a, hey. run your tool and then give you give us results and then we're going to validate it and try to crush you guys in the report um we were uh had a feedback process which either the vendors where they ran their tools they gave us prelim results and then we gave them three defects out of the hundred uh as like prelim digs where they could sort of calibrate their runs and understand how they were performing and then they would provide us a revised listing we would evaluate that and then we provided them an additional 20 defects which gave them a chance to calibrate their listing again and then they provided us a final listing which was utilized for our final performance validation.
And then in the actual PRCI report, I don't think we had enough space to do this in the IPC paper. We compared how their results changed from the prelim analysis to the final analysis.
Chris: So, Zach, I think you brought up a really important distinction there that I wanted to highlight in this segment. And it was a research project.
And I think that's important because your comment was you didn't have a performance spec that you were judging against. And I think that's the separation, right? That really sets the scope.
So back to like our restaurant analogies, like what's the expectation here? So when we look at validating a performance spec, we have to turn to 1163, right? API standard 1163. And in it, there's a pretty clear process on how that performance spec is developed, right?
And I'm just going to pick one of them, essential variables, right? And so... when we're to say hey we're going to give them feedback on their performance if it's towards a spec we kind of already have a defined process that we follow.
And this is not necessarily what you guys were doing. It was more of a, hey, we have these samples. We want to see how well these guys can target identification is what we heard you say of select sea mold corrosion. And we're giving these guys feedback.
And I think that's a really important distinction for our audience when you're listening is it's this is not postured as a performance validation test. This is postured more as a research and saying, hey, these are the flaws we have. this is what we were able to come up with.
Let's see how you're able to perform and then how can we go from there? So I just wanted to say, I think that was a really good distinction that you made there for us.
Rhett: You know, and I think, Chris, it is really important because it feels like so much of what happens at PRCI, like, gets characterized that way. And I don't think it's the intent, right? Where it's like, it's like a gotcha project. Like, gotcha, you didn't do what you were supposed to do.
And I wonder if some of that feeds from, you know, I always tell operators, if you don't talk to your analyst enough, they always assume when you call, you're only calling to tell them something's bad, right? So they only engage these projects assuming that you're trying to tell them something bad.
And I think that that's really important, that you can do some really good research like this to understand and improve the state of the art of the tools, not hold them to a spec.
Chris: And these were all done at PRCI's TDC, right? And the TDC stands for Development. Development Center, which is development, right? Not necessarily validation, right? It's not just every time something goes there, it's, oh, we're going to judge you. Rather, it's this is where the facility and that platform is used to bring in some technologies where we were researching what their performance is, not saying we're going to validate their performance. And I think that's an important distinction we wanted to bring up.
Rhett: So, audience, we – Oh, you want something you wanted to say before the break?
Zach: One more thing. Something that I think is exciting for me in this project is that you'll see a range of performances from tool to tool. But something that I like to focus on with this project is that it shows that we're capable of doing some of these things with identification and that we're on our way to identifying and sizing select CMU corrosion well, at least for the defects that we had in this. uh defect set so yeah you'll see a range of um performances but we're expecting that to continue to improve for every vendor that's working on this. And that's exciting for me.
Rhett: All right. Well, oh no, we got another, we got another, it's like a Postscript. Postscript, let's go.
Thomas: I'll make one more comment if you don't mind. A friend of mine, Pat B, I think some of you guys know him, said once when a new ILI technology was developed and commercialized, we know a lot about the capabilities of the technology. We knew what it might detect. We knew what it might size and so on.
But what we didn't know or what we don't know are the limitations. And that's one of the roles of research. Yes, under certain conditions and deadline inspection or an NDE, we'll find something and we'll size it well.
What we're hoping to do in projects like this is to demonstrate, you know, where do you get a little bit in trouble? Where might you not see something, especially if it's severe? And so that was one of the goals of projects, this project and projects like this is to understand capabilities as well as limitations of the technologies that are brought to bear.
Rhett: Absolutely. Well, audience, you're going to need to hang on with a break because when we get back, we'll talk about exactly why MFL is better than ultrasonics at detecting selective steam well corrosion. And if you just stop the podcast there, you're not going to get the rest of the answer and you'll be just as salty as Chris is about me insulting his restaurant selection. So hang on until we get back.
Chris: You love my restaurant selections.
Rhett: All right. As we get back onto the show, this is where the meat, as we continue our conversation with Zach and Tom on their IPC paper, examining, I want to make sure that I get it right, examining the evaluation of selective seam weld technologies, right?
Not interrogating those technologies and not trying to pin them, but really just looking at what their capabilities are. So let's start with the first class, right? If you guys don't mind, what did you find with the MFL tools? And just to reiterate, there were five MFL tools. I want to make sure I get that right. Five MFL technologies in this study. What did you find?
Thomas: Well, you know, it was interesting. And this is true of all of the technologies. Almost to a company, or rather to a system that was used, they underpredicted the depths of the anomaly.
It sometimes weighs some pretty significant amounts, 10, 15, and sometimes more percent off from the actual depth that we had determined through the laser mapping or destructive testing.
Then we can kind of look at, say, MFL versus ultrasonic or rather acoustic technologies. We're grouping in the UTCD and the EMAT together as acoustic.
Rhett: Wait, before you go there, Chris, we just need to make sure. Misapplication point number one. MFL undersizes selective seam well corrosion. There we go. I want to get out all the misapplications right out, Tom, so that the audience can have those and run with them. And then I can be challenged at PPIM when people get upset. So you have undersizing and MFL.
Thomas: I will say that based on the systems that we were able to test and the analyses that they were using, right? Some of these guys were using kind of more experimental analysis methodologies.
In those experimental methods, some of them performed pretty well. Some didn't do as well as they hoped for.
Rhett: But, you know, it's interesting because you went straight to sizing, Tom, but you said this study was originally set up, or Zach said it was set up from an identification standpoint. What about from a detection and identification standpoint on the MFL specifically?
Thomas: We found that detection across the board was really good. It was generally great for MFL, a little bit less so far UT, or rather acoustic technologies, but they were good at detecting things.
They could tell you that there was something present at that location. Identification then is telling you, is it selective seam weld corrosion? Is it coincident corrosion? Is it a combination of those two? And so that's where identification comes in. And most folks may think that's not so important, but I'll tell you why it is.
It's important because The ILI companies in their analyses take into account what they know about the defect. If they recognize that it's a selective seam well corrosion defect, they can do an analysis that's a little different than if it's just, let's say, an axial groove or an axial slot.
So those are the differences that become important when you're trying to get good data, when you're trying to get accurate results from your ILI.
Chris: Yeah, Tom, I love that distinction. And I'll jump in here and say... know, we recognize that, let's say we are looking at a performance specification.
Most of the time, what we have been accustomed to reviewing in performance specifications typically is a table that leverages the pipeline operator forums dimension classes, right?
And those dimension classes are terminologies that we're comfortable with. General metal loss, axial slotting, axial grooving, et cetera. And that's where we'll find these statistics, right? We'll just say, hey, if you have this dimension class, here's our POD, PRI, and sizing tolerances.
But that's very different, right? And that's what you're getting to, Tom, is that just because we can detect something that has these dimensions, that doesn't mean that I know what it is.
And so oftentimes that's why we go and we look at those tables that we find in performance specifications that say things like, can you find pitting? Right. Or can you find selective seam weld corrosion? Can I find axial cracks? Right. And that's where now the vendor is saying one part is me detecting it and sizing it. Another thing is me translating that into something useful to you. Like, what do I think this is?
And I think that's a really important distinction that you brought up. And I just wanted to add some of that structure to the conversation and saying it's one thing for us to be able to say yes. the morphology that was tested was being I think you said generally under predicted by MFL.
But once they understand the morphology and begin to think it crosses a seam it's vintage ERW it's been in the line this long and the operator thinks they have the challenge now they can start looking at those amplitudes and start applying different analysis techniques to it to start refining it and i think that's again i think a big part of what you guys were trying to demonstrate in the project
Thomas: so right
Rhett: I got a question in here because of the five MFL technologies, not all of them were MFL-A, and two of them had combined MFL-C and MFL-A.
And I don't know if you can comment on that, but for the audience, it's important to recognize that, again, even within the distinction of MFL, all MFL is not the same. But were you all able to distinguish anything, or did you even attempt to, or is it worthwhile to try and do anything between MFL-A and MFL-C in this study?
Thomas: We'll be careful about that because we agreed as part of the program to anonymize the results we wanted. But I'll tell you a couple of things. One was it's always been said that axial MFL or MFL-A doesn't detect long, narrow things. It doesn't size them, doesn't identify them well.
A long crack, for example, in the axial direction is not going to get picked up by any MFL tool. what we found was even the mfla did an excellent or did a very good job of detecting that there was something present so tools that are out there today the way in which they're analyzing the data they're finding stuff.
And that's always been something I've said about MFL. It's a great detection tool.
Chris: So let's qualify that a bit. I do have to jump in, Tom. Now, if I were to look, because right now the reference we have is the IPC paper, and figure four is this really big flaw, right, where you have this pronounced metal loss that crosses a seam. Are you saying when you have metal loss that crosses a seam, MFL-A could say, hey, you have coincident features, a long seam and metal loss?
Or are you saying the MFL-A, your observation was it was able to recognize that there was something targeting the seam more acutely?
Thomas: Yeah. I believe it was recognizing things were targeting the seam. There was something in addition to just the metal loss.
Chris: Got it.
Thomas: But we also know that MFL doesn't do a great job on these long, narrow things, or so we think. MFL, some of the vendors did pretty good, plus or minus 10% or so, but some of them, you know, they struggled. Instead of maybe plus or minus 10%, they might have been plus or minus 20%. Or in some cases, more than that. Plus or minus 20% is not a very good spec.
It means that you reported it 25%, could be 5%, or could be 45%. And so those are big differences. And those are the things operators I think need to understand and take into account. And that's where programs like this will help.
Rhett: Zach, do you have something you want to say? I keep seeing you jump there.
Zach: And getting into the MFL-A versus MFL-C thing, something that was a bit challenging in that regards is that the performance varied so much from MFL to MFL vendor that. we only had one vendor who ran an MFL-A without MFL-C so we weren't really able to correlate uh is this a difference because it's an MFL-A vendor or is it a difference just because valid differently um so yeah
Chris: yeah and and we're gonna add some context here right um are we we are so we we all recognize that there are different resolutions when we talk about MFL technology.
And not just within the resolutions, there's also the capabilities of are they using one axis or triaxial sensors? A lot of these MFL systems, they also have multiple technologies. Right. So when we actually call an MFL tool, is it really just a horizontal hall effect sensor?
A lot of times it's not right. They'll combine it with some kind of IDOD discrimination. They'll combine it with some some other type technology that is they're part of their ip but it's packaged in traditional language that we'll call an mfl tool and so it's also important guys again for the audience here this is not challenging the paper but saying you know we have to recognize there's anecdotes here right what the takeaways here are um these these broader strokes saying there's lessons learned here that get us to get creative and if you guys have heard me talk at all at ypp it's you know be curious right ask questions ask questions don't take these little nuggets and use them as rule of thumbs but say i can say that we could use MFL-A to detect if i have a like a screening mechanism from integrity do i have something attacking my seam.
But maybe you need to be real careful about saying, can my vendor help me do a seam assessment? And I think that's where the discrimination is. And I think that's the takeaway from what you guys are talking about right now.
Rhett: Tom, I have to ask because in the statement, which is so shocking, MFL vendors identified and differentiated. SSWC and Coincident Corrosion more consistently than acoustic vendors, which we're about to get into. I want to hold that. I'm just like, acoustic vendors are just waiting.
But in there, you said one ILI vendor identified SSWC and Coincident Corrosion 96% and 100% of the time. And one vendor performed really well. Why, in your opinion, did that one vendor outshine? I mean, enough where you drew attention to them out of the group of five.
Thomas: Okay. Let me say a couple of things on this. One is that, again, some of these vendors were trying different things, all right? If they're using a different analysis algorithm, analysis method, for selective seam weld corrosion, then they're using far axial slots and different from what they're using for axial grooves.
I think you have a better ability to size them, okay? MFL, lots of things happen when that corrosion goes from here to here. You know, when it gets really tight, at that point, it's hard for MFL to do things.
And that's because the flux leakage field varies a lot by, you know, is it this tight or is it this tight? And that's what we're looking at. When those inspection vendors identified well, they sized better. Okay? And I think that gives you a little hint as to what they're doing.
If they know what's a selective seam weld corrosion, don't just use the same algorithms that you should use for extra grooves. Use a separate algorithm for SSWC. And I think that's what helped that one vendor do a better job of sizing the anomalies itself.
But again, identification, that's critical. I identified it in a selective seam weld corrosion because if you can't identify it, you can't apply some special analysis for
Chris: and and that and that goes to application right so you know and ideally when you're collaborating with your ally vendor right you're the reality is it's a partnership right like hey we have an asset that we need to maintain the integrity on when we're deploying a technology that's not a test for the vendor right it's a collaboration it's we've chose you it's kind of like pokemon I choose you pikachu right it's like i'm using i'm using you to help me understand what's going on in my pipeline.
And so those are the anecdotes that you want. It's like, hey, did you find something in the seam in the final report or the prelim? Sure. Then that engagement happens, right? It's like, so we are seeing things in the seam. Is there something that you can do, ILI vendor, in your ILI system where in that system, you're looking at your algorithm and saying, is there something that we can do that can improve my ability to respond to this pipeline?
Thomas: Yes. A lot of folks, there's a portion of the industry in general that wants to consider in-line inspection as a commodity. You buy the service, you get the results, you make your decisions. There's so much more information available in in-line inspection signal than what shows up in a spreadsheet of results.
The key to doing that is that interaction between you and the inline inspection companies. I got news for you. That's what the in-line inspection companies love as well. They hear, you mentioned it, when things go wrong. They need to hear not only they did poorly on this one, but these are the handful or the majority where you did a good job so that they can start to tweak their systems and do a better job of sizing, identification, and detection.
Chris: Yeah, there was a gentleman that I used to work with, and he doesn't listen to the podcast, but he used to say something.
Rhett: Who is this person?
Chris: It's Yoxie.
Rhett: What?
Chris: Yeah. You know, I love that guy. Also big guy at YPP, right? You drop Pat Veeth, so I'll drop Yoxie and say, you know, he used to tell me sometimes.
Rhett: I don't know that anybody other than you calls him that.
Chris: Okay, fine. Mr. Yoxel, Mr. Christopher Yoxel. He would tell me, you know, when I used to work with him at Rosen over there, he would say, Chris, we need to remember, right? We need to turn the object into a subject. Right. It's not just about the pipeline. It's about what are we trying to understand about the pipeline and have have a discussion about it. And so I just I thought of that and I think that's important, guys.
What's next? We've got to get to the ultrasonic side. Let's go. You're delaying, bro.
Rhett: I'm not delaying. Y'all are having a great conversation. But I've got to get to the end. Tom, I need you to comment on the performance of acoustics in this study. And if you can, tell me what you did wrong to draw the conclusions that acoustic didn't perform as well.
Chris: He said, what did you do wrong, not what they did wrong.
Rhett: That was intentional in that question.
Thomas: Well, let's keep in mind a little bit the difference between a UT crack detection and a UT wall. UT crack detection tools aren't necessarily set up to find corrosion. I mean, they were designed to find cracks, planar reflectors that are basically perpendicular to the pipe wall.
I mean, that's what their algorithms were developed on initially, and that's what they do really well. When you start throwing variables into them, like you know, I've got an angled crack or I've got a V-shaped corrosion, it becomes more difficult.
And if that profile is changing, those reflections that the ILI system is using to help determine what it is and what size of it, they become harder to understand and interpret.
So one of the reasons I think that the acoustic systems had more trouble was basically They were looking for a wide variety of geometries, and they were set, probably, to look at cracks.
And so, to a little bit of an extent, that raises some issues. But it also raises a point that I made before, and that's UT is typically a better sizing tool than it is a detection tool, because lots of things will contribute to losing the reflection of somebody. roughness, debris, any other number of different things, wrong angle. But UT’s tools for cracks, for example, excel.
And that's where they usually have their strengths. We didn't see as much on this one that that would be the case. And it might have been that we didn't have a big enough population of ILI companies to look at. Again, we had UT CD company. So we're not saying this is how all UT CD tools are we're saying that's how the one that we evaluate
Rhett: and that's really important to to interject right because i'm poking fun because i love i absolutely love the way y'all worded things in the corrosion and the conclusions i'm sorry it's like it's like clickbait it's that good but it is really important to recognize audience rage bait is that would be a great one um there were only first off when the paper draws conclusions it groups acoustics into a category right. Most of us would typically divide ultrasonics from EMAT, right?
But in the paper, they're grouped together. I want the audience to recognize that. And there's only one vendor from each. So this is where I want to pause and take my soapbox for a moment and say that if you don't like statements such as the following being made, which is MFL vendors identified and differentiated SSWC more consistently than acoustic vendors. Or if you don't like a statement that says one acoustic vendor was unable to produce repeatable depths while the other did not report any differences in depths between the passes.
And this raises questions about the veracity of the data analysis conducted by the provider. If you don't like those statements and they get you angry, then you should participate in this study. If you don't want technology broad stroke characterized by one or two vendors who maybe aren't as mature or were doing this as a test, then you have to be there.
Chris: Or the importance of them being anonymous, right?
Rhett: Yes. So again, I just wanted to pause there, right? So there were clearly some challenges with the ultrasonic side of things in this study or the acoustic sides, as I'll label it. But we really only had two looks.
One was an EMAT tool and one was a UCD tool. And we both know there are more than one EMAT and one UCD provider. And certainly on the EMAT side, the technology deployments are completely different among the EMAT.
Chris: Yeah, and there's a lot of distinctions here, guys, right? And I'll try to highlight some of the key points without going through all the technologies. So it is important while in the study the results were grouped as acoustics, the measurement principle, as most of you will know on the podcast, between an ultrasonic and a traditional EMAT are very different.
Rhett: Absolutely.
Chris: And when you're looking at a UCD tool, they did mention that there is a wall measurement component to it, and that's because— when when you're looking for those linear indications those more crack like planar flaws that that are reflectors we don't know what the orientation of that radial component is is it really vertical perpendicular to the to the longitude of the pipe or is it a hook crack where it skews a little bit and in the real world they won't know that.
And so when they're looking at the 45 degree shear wave, it's important for them to know what the wall thickness is. So if metal loss has consumed that wall thickness, the dynamic of the ultrasonics will change. And that's an important part of doing ultrasonic crack analysis.
Whereas with EMAT, you don't have that challenge, right? It's a little bit different. Usually you're having a shear horizontal wave that's going through the wall thickness across the perpendicular of it.
And so at that point, you're truly just looking for reflections. And that's where you have a different challenge of like steep sided corrosion or surface breaking lamination. start serving as interference with your ability to characterize what type flaws.
So for everybody listening, we understand all of those complexities. We're just trying to lump up the results and say, at the end of the day, this is what we saw. And if you don't like the results, get more involved and put your name on it.
Rhett: All right, guys. I'd like to know from both of you. First of all, thanks for an absolutely excellent publication. Thanks for the absolutely excellent conclusions. Where do you want to see this study go from here? You had a wish list. What's one thing you want to see it tackle next time? And I'll tell you what, Zach, we haven't heard from you. You keep trying to jump in. You're just not forceful enough to override Chris.
Chris: He's being polite.
Rhett: Yeah, he's too polite.
Chris: That's a good thing, by the way.
Rhett: Where would you like to see this go next?
Zach: I would really like to see more natural defects incorporated within the defects set. I think that's something that I wish we had the opportunity to do within this project. um because the we all know that the morphology is just uh different for those natural defects.
And then honestly i think having uh more like vendor representation would be great uh there's a lot of analysis to do when you bring it when you have all these different vendors so it is but it directly correlated to a level of effort um but
Something that has kind of been a theme of what we've just talked about today. We only had one EMAT vendor. We only had one UTCD. So maybe more focus on the crack and side of things could be really beneficial in the future.
Rhett: Absolutely. Tom, what about you?
Thomas: Okay, well, a couple of good points. I agree with Zach that projects like this or programs like this serve dual purposes.
They help understand what the technologies can do and they help provide information back to the ili companies so that they can improve those capabilities.
There's kind of a timeline that happens when technologies are developed they start with detection they go from detection to identification then they go from identification to size. okay so the first thing you ever hear about on a technology that that's just coming out, like one for selective seam weld corrosion, and it's, hey, look, we can find you.
We're gonna show it to you. Here it is, we found it for you. The second thing you should look for is, are they identifying right? Identification kind of gets shoved in the carter because a lot of folks don't really understand it, but it has an intimate impact on how that analysis is conducted. If you don't identify these things right, you're not philosophized.
That's just a fact of nature you'll see that again as a tool is developed or technologies develop first detection then identification and then you get into science you know initially i've heard a lot of pipeline companies tell me well they don't really care about identification or sizing no they they need to flip that around they do need to care about those sort of needs because that's what's going to make a difference if they want to get more accurate results.
And I think we're seeing that transition on selective seam weld corrosion. Some of the advisors when we started this program, they said, you know, I don't care about sizing. I care about identification because they recognize this. If they could say it was selective seam weld corrosion, they'd go out and dig it up. Sizing, though, is becoming important. We're seeing that transition in and where folks are now trying to use the sizing.
Is that selective seam wall corrosion really worse than somebody else's? First, you get it right relatively. Defect A is worse than defect B. And eventually, you get it right absolutely. Defect A is 50%. Defect B is 20%.
So those are where we need to see things go. I think we need to see people do a better job of identifying selective seam wall corrosion. Detection seems pretty good. And then once they identify it, use that information to size better.
Zach: I think with identification as well, something that would be helpful is that we saw in the project is that each ILI vendor was using slightly different terms for identifying what they were seeing. And that was a big challenge for us.
Something that I love to see is consistency would be great, but I know that's going to be a challenge because each ILI vendor is so passionate about the way that they identify it. But even just very well thought out definitions of these anomalies would be so helpful because sometimes we get something back and it was challenging to figure out what exactly they meant.
Chris: I'll go a different way, Zach. And let's not make this a discussion. You and I can do this over the...
Rhett: This is a whole other podcast, bro.
Chris: The panelists that we're going to have at YPP, we could have a beer over and talk about this. But I would say, I'll leave it as a question. Should that actually be the vendor's responsibility or should that be the operator's responsibility, right? So once they provide you with dimensions and data, because per 1163, you get to get the viewer data of the signatures. is it the operator's responsibility to take it to that next step so that that's an open question and i would just say you know for everybody on the podcast i would say one i really appreciate this topic you know what we like to do is bring things that are happening to our audience so you guys can have exposure to them.
And so there's a lot of points in here like, oh, well, how did you verify the depths? Why did you use EDMs? Why did you do this? That's not the point of today's conversation, guys, right? What we want to do is bring you guys cool work that's happening so that it instigates you guys to say, I want to have a conversation about this. I want to ask questions. I want to reach out to these guys.
Rhett: So many calls to actions here as I close this out. Vendors, you need to participate so that you can influence the outcome. um operators you need to invest time and resources and understanding the technologies and working with the vendors that that loop that process of securing identification and then once you nail down identification being able to adjust your algorithms is so important and um this this study i think was really was really well done um Tom and Zach thanks for presenting it at IPC thanks for sharing it thanks for doing such great research.
To our audience, hope you enjoyed it. We're going to continue this study again. I really think the crop of IPC papers was quite good this year, and we look forward to more discussions like this. We'll see you again in a couple of weeks as we go on to another discussion. Thanks for joining us on Pipeline Things.
This episode of Pipeline Things is executive produced by Kara Turner. We would like to thank the studio, Texas Collective Studio, for their facilities, and, of course, my life partner and esteemed host, co-host. co-host Christopher DeLeon. Also want to recognize a co-author on the paper, Josh Bremner, and the support of PRCI Project NDE 413 and the IPC publication 2026-186-359.
