Episode 351 | Weight Material

0:00Drilling fluids touch just about everything in the drilling process. We're here to deconstruct the drilling process and drilling fluid concepts to provide a deeper understanding of our industry. In each episode we'll share information, talk to interesting people and maybe share a few stories along the way. Welcome to the Flow Line, a production of AES Drilling Fluids brought to you by Matt Offenbacher and Justin Goethe-A. Everybody, welcome back to another episode of the Flow Line. I've got my lovely co-host in here, Matt. Offenbacher for those who don't know. Matt, tell us a little bit about yourself if someone's tuning in for the very first time. Um, wow, that's a lot. Should we tell them to go back to episode one? Yeah, yeah, yeah, yeah. Okay. But she's year and will boost her downloads. Like, there's a lot in it for us for you to just do that.

1:02Right. Well, with that said, folks, if you are tuning in or maybe you're a new listener, yeah, go back to episode one, Matt. Uh, does a great job of just sharing, uh, you know, why we did this and the purpose and intent and here we are almost 400 episodes later and, uh, the purpose and intent and mission is still the same to continue to educate folks willing to listen. Yeah. So, for Matt and I to have the odd therapy session amongst each other and for the rest of the wide world or drilling world to listen in on. It's all out there. That's it. But Matt, what's anything fun and exciting to share besides, uh, drilling fluid stuff? Huh, man, uh, baseball, uh, you know, big, they had the all, that's the all star breaks. The all star game was the other day. Okay. And, um, uh, but the trade deadline is coming up early August and today, the Astra is traded, um, you know, foundational guy, Lance McCulloch, the Brewers. Whoa.

2:02More or less like a salary thing, but like great Houston guy. Yeah. Um, did a lot of great things for us, struggled through injuries kind of this the last year of his contract. And so I think, uh, we just needed to clear up some roster spots. But, wow, I guess apparently it'd been like they'd been trying to do this for a long time, but now it's happening and, uh, so crazy. I'm thinking about that a lot. I bet. Is that the guy who owns the coffee shop in the closer house? Yeah, he got out of that like they, they turned it into something else, but yeah, same guy. Okay. Um, and he was super cool to my kids and I mean, their stories all over the city of great things he's done for people. Yeah. Uh, so good guy, good athlete. Huh. So yeah, just like, then they haven't filled his spot, uh, I guess yet. No, but they have so many roster spots. So they traded him another, another pitcher, Colton Gordon, um, but they have several players. So, um, uh, uh, Renelle Blanco, who has been on the injured list, he's been in AAA ready

3:09to come up. Uh, Hayden was nesky, also kind of recovering stretched out. So like they have, they have plenty of pitchers. Okay. Um, so we'll see what happens. What I suspect those guys are going to come up and, and you know, get on the Major League roster and hopefully help us out for a big push at the end of the season. No kidding. And where are we sitting, uh, win percentage wise here? Are we doing okay? We're going to stand. Well, okay. So we are not good. However, no one in the A L is good. So the thing is they could probably make the playoffs of being like a 500 team. No, a few games behind below 500 at this point. Uh, what? You know, some of the issues that they played better recently, but they got off to a pretty rough start. Okay. So, um, the problem is they're, they're, there's a chance of them making the playoffs. You got a GM and a, uh, uh, uh, manager who are both, uh, in the last year, their contracts.

4:10So they want to show that they can do something magical and, yeah, not get fired. Um, so all the things. Okay. Yeah, that's the, that's the last. Well, after all start break, it's, uh, you got to put it in the second gear and, and get after it. Like you said, um, it's kind of interesting. You know, when you talk about, you know, baseball and it's, you know, how well they were doing and, and then, you know, the sort of progression of performance, uh, we oftentimes talk about progression and performance in mud. Actually, believe it or not. Uh, and at the end of the day, you're always being measured. Um, our customers obviously have, uh, you know, they, they have a certain goals and, sort of things that they, they have in metrics and KPIs, which, uh, then falls back on us. And at the end of the day, you want to continue to perform and we often get asked, uh, you know, to demonstrate, uh, you know, the performance and then we go in and present or, you know, we shared on a biweekly basis sometimes more often, sometimes less, but, um, it's an interesting conversation.

5:11Uh, just sort of overall talking about performance benchmarks, sort of how we think through that and really the challenges if you've got a big, uh, sample, uh, size, uh, you know, if you're drilling in some words, like say the Permian where you've got rigs all over and, um, so it's, uh, these things, worth an interesting conversation. Matt, what do you think? Yeah, absolutely. Because there's, there's just so many layers to this. Um, it's, and I mean, how do you, I don't know, sometimes it's like through the color of glasses you're looking through what conclusions you make, you know, can all be subjective. So how do we quantify that and make it less subjective, um, more meaningful? So yeah, cool. Well, uh, Matt, let's, let's first talk, um, you know, when it, when we talk about different benchmarks, uh, and that meaning, you know, this is where we'd like to, you know, this is where we are. This is, you know, sort of the, I guess, ideal case where we drilled in this many days for this cost of foot or whatever metrics we're looking at, um, you try to beat that

6:16benchmark or that sort of the goal. Um, but there's more than just that. So let's talk about sort of the different kinds of different benchmarks to sort of lay down the groundwork there. I mean, there can be, it depends on what you're trying to measure, right? And, uh, so, I mean, are you trying to drill the fastest well ever in your area? Um, you know, are you trying to lower costs by 10% across the board? Um, what do those look like? Uh, is it, I mean, you know, cost per foot? Is it, you know, days on well? Um, and not only that, but there's so many moving parts. How do you say, okay, this is a drilling fluid, like drilling fluids got us there, not a new drill bit, right? Not, or, you know, here's how much I can attribute to this, this kind of thing. Um, you know, I found it really interesting kind of kind of starting out with like records,

7:17you know, you see these fastest, whatever in the whatever. Uh, what's actually interesting is to talk to larger operators. And I mean, this is presented to AADE, um, showing kind of the, the distribution curve of, like, predictability of wells and like records. And there's just like a very tale that you want to overlap on each of those distribution curves. Cause the likelihood of risk just goes up exponentially. Right. So like, as much as we want to find something that makes a huge difference, and like we don't ever stop pursuing that, the other aspect of this is if you load your well up with so much risk so that you can drill faster than anybody else, you may get it on one well. Right. But let's say you got nine others in the project and odds are you will have that record well. But one of those other nine is going to be a disaster because of all the risk you took on that

8:17didn't introduce the downside of that risk. Yeah. And then you have a train wreck and, and what we've seen time and again, particular larger operators is, like we would rather have consistency, then we would have like one well that we can go run and tell the boss is what a great job we're doing. Yeah. And I think that's kind of an interesting aspect in, you know, in some of those areas. Yeah. Do you think, I mean, it's different operators have different philosophies, but, uh, do you find some operators have the push it until it breaks to know what our limit is? And then we build around that. Or do you, I mean, because the size and, and risk profile of certain operators, uh, certainly much different. You say you have a large public versus a small private, um, cause I know just the, the behavior on which people drill and try things is different amongst operators, uh, which could probably be an old, hold another topic of discussion, but, but, but for,

9:21for our purpose, um, consistency and continuity, uh, over time has shown to, to provide the greatest results. And now there's exceptions to those rules, but that that's what I've sort of observed. Um, but what, I guess going back to what's your thoughts around pushing until it breaks to find the new, say, records, okay, let's, that's not, we know we can get there. How do we then repeat that? I think that there's a combination of, so one, sometimes you see, particularly with, with bigger operators, their objectives are very much like consistency, more of the same. And so culturally, many times you see less motivation to try new things because the bonus isn't drill, you know, 10% faster this quarter. Um, it's deliver X number of wells per the schedule. They sandbag it and they'll go on vacation in October. Uh, you know, there's, there's that kind of thing. Um, and then you see, you know, I think like you're alluding to, like the privately helds,

10:23generally can't afford to have a disaster as well. Um, they don't, you know, they're running a one-ray program, something like that. It's just, um, it's so disruptive to everything because let's say you have that train rig, what, wreck well, now your fracks schedules thrown off. There's all these other things that, yeah, um, it's not just the drilling costs. It's everything else gets thrown up in the air and you don't, you don't have enough, uh, scale to sort of tell your frack fleet, like we'll just, we'll just move some things around between everything we have to do. Yeah. Uh, but, you know, I think this is very much, you know, we had Fred do priest on here years ago. And part of his sort of challenge was, you know, what they called the, uh, you know, the fast drill process at X on a trademarked kind of concept. But, um, my understanding of the situation was there, there had become too many rules of thumb. And so it was like, well, we just don't drill faster than X feet an hour because somebody somewhere else got stuck.

11:24Yeah. Or we don't, and, and there were certain things like that that weren't fully contextualized. And, and this is where Fred was, you know, physics based drilling, get your limit, figure out your limiters. If that limiters in your way, what can you do to reduce it? Um, but like push the envelope, but understand why the envelope, needs to be pushed or where it needs to be pushed. Um, and this is where I think you can be quite constructive where, you know, it would be okay. Well, listen to what the well is telling you. Um, do you're up for an engineering? Like, is there anything that tells you you can't do this or is it we always do this? Cause we've always done, always done this. Yeah. Um, and, I mean, we've seen, well, one time we twisted off and therefore our, you know, the only amount of pull we can have on our pipe is X percent. So we have to backroom all the time. And okay, well, so it happened once, was there anything else to that? Like, um, sometimes we sort of paint ourselves into a corner,

12:24yeah, without really understanding what got us there. And then, you know, we really are like, yeah, those limits should be pushed. And, you know, Elon Musk, you know, kind of his biography is pretty fascinating, just by way of, he would go with this rocket stuff and he would ask somebody like, hey, why do we have to do this? And they would say, well, you know, um, we've just always done it that way or, okay, well, I went and looked into it because you told me and it turns out in like 1964, when they were testing these things, like this was a problem. And he's like, so this has just become a rule of thumb with no context. Yeah. And so he sort of turned around and said, if we were going to put any of these limits or design additions onto anything, you've got to put your name on it and tell me why. And the ultimate argument was like a rocket engine, it goes through these tests, who cares how it's made if it passes the tests. Yeah, right?

13:26And so it's, it's an interesting approach to engineering where you say, okay, well, why do we do this? And then we talk about whole cleaning all the time, right? It's like, oh, well, I have this rule of thumb. My yield point needs to be certain amount of the whole size. It's like, well, you didn't have pumps back then. Yeah, like this is, you know, whole cleaning and biology are just not as tied together as they're made out to be, you know, it needs to be contextualized with the well, the flow rate, all these other things. Yeah. Um, and if, if we stick to these things, we can actually, you know, be held back. So, um, I think that there is, you know, I appreciate some of the folks who want to be aggressive. I think also when we want to be aggressive, we want to be aggressive in context, right? And it's not changed five things and then, you know, trying to figure out which one did what? Yeah. I think that's, that's a big issue we have with trying to do even like we, we had a different episode on base oils, right? And it's like, well, that people don't benchmark very well.

14:28They bring fresh synthetic oil out there, drill a couple of wells, get excited at how fast they drill and never go back and look at, well, what if I, what if I brought fresh diesel mud out there and did the same thing? What are my economics then? Right. So apples to apples is obviously big. Um, you know, and, and fluid attribution to me is, is huge, right? So like, if you have a train rink with mud, mud, was it preventable? I mean, did we have a bunch of losses because we drilled into an area where we frankly didn't know how bad things were? You know, not LC, you know, LCM can't cure everything. There's just certain areas. But like, if I run out of product, you know, if you have to wait on mud, if we make a mistake, like those are things where, you know, competent people, facilities, logistics really set you apart. I think the frustrating thing for us is we have these amazing facilities.

15:28We have amazing facilities, people, we have amazing logistics. And I think sometimes what we find is that because we don't have as many train racks, it like, sell to nobody really waits on things when you can do what our people can do, which is fabulous. Yeah. But people don't notice a problem they never had. And so I think sometimes, you know, how do you shake that out so that, you know, imagine what could have happened? No, you know, to me, like, what is the frequency that we, and that is where we've kind of tried to benchmark even the value, like, hey, these are how many loads we've handled without NPT or, you know, some of those things just to contextualize how over and over we've been able to do those things. Same thing with like, hey, we ran into something. Did we warn the customer in advance? Did we know, you know, did we do offset studies and say, you know, we need to mitigate this risk upfront as opposed to why didn't we see this coming?

16:29You know, so I think there's, there's a lot in the drilling fluids world when you have access to offset data, when you have sort of your ducks in a row and you're making the right recommendations. You know, I think it's easier to quantify the bad ones, I guess, from a benchmarking perspective. When things go well, you know, you might not get noticed as much. And then I guess that we've talked about this as far as like case history and stuff like that, you know, who really gets the credit? I mean, I'm amazed at the number of, well, we drilled a record in this and this and that, you know, and you'll see for the same well, like the mud company, the bit company, the directional company, the drilling contractor. I mean, and look, they all probably had a part, but they're all sort of taking individual credit for something that, you know, as parts of a whole. Yeah. So the famous LinkedIn record sort of announcement, so he's always make me chuckle.

17:34Yes. You know, and I'll say sometimes folks will say, you know, big shout out to the, you know, the Patterson team, you know, team effort, this and the other. And so I've actually seen other folks, uh, Tay, other vendors on there, but it's rare. It's normally like this bit just crushed the amazing record. And then everyone else I was on that rig, I'm sure was like, well, what about blah, blah, blah. So that, yeah, again, I was kind of as an aside, sort of funny. Or then too, you know, of course I've had buddy drilling engineers that are like, I drilled the best well. And I was like, yeah, good job. Well on the project management side, yes. Would you run the break handle like, you know, what, but nonetheless, it's kind of funny. Talk about the sample space. And this is one that, you know, over the years, I got spoiled when I first came down to the US, drilling nothing but Marcellus swell. And so whenever you would look at performance over time, you didn't have to normalize much because the wells were already normalized.

18:38Yeah. You know, with, you know, a few little things here and there, like there wasn't much difference, right? And so when you're drilling the same profile to relatively the same depth, with almost like identical mudwades across the entire region, you can really fine tune and figure out where if things are going wrong, why? Because you don't have to account for different things. But in places like the Permian, Haynes, well like, many regions that have different producing formations and different regions that if you cross this highway, it's way different than this highway. If you drill south versus north, everything's going to go completely sideways. Yeah. All that stuff, Matt. So how do you personally, as we as AES think about samples space and account for all these different nuances? I mean, I think the big thing is to emphasize that one well isn't going to tell the whole story. And this goes, I mean, this goes both ways, right? Like you trial a new product and you have to trip five times because the tools aren't working.

19:42You know, like, is that my fault? Probably, I mean, the directional company will say it is, but in reality, probably not. But one well doesn't always tell the whole story, but a good success you want to build on. So I think, if I go to KPI and we have a well that I was talking about, I want to highlight the wins or the points where we believe we contributed the most without, like, man, expect carbon copies of these from now on, just understanding, like, hey, we've got some momentum here. Let's focus on these things that worked. Yeah. Let's try and replicate that and make sure we're all in the right place with that. But, you know, sometimes we'll normalize it by rig. And it is interesting because sometimes you can suss out, especially with some of the data sets we have, like, this rig's doing better than another one. Sometimes, the salt, the salt's control in this rig is not performing as well as the salt's control over here.

20:43Like, we'll just see it in delusion rates and other things. And those are things we can go to the customer about and say, like, this will lower your mud bill and talk about it further. But, you know, by rig, you know, by pad, but are they all the same benches, did you knock off a couple of bone springs and then drill a D, or like by, you know, a particular field or, you know, a lot of times in West Texas, well, is it, you know, is it Midland-Based or Delaware? Because those are very different conversations. Yeah. I think even, you know, Oklahoma, we know sort of our spots that are comparable. And I mean, in the Northeast, there's like, you know, there's like, Debutica or some of those areas. And it's a bit funny because people group the Northeast, but like, yeah, parts of the Marceles are like drilling into the side of a snowbank. You know, it is, I mean, they're knocking out two miles in a day as like SOP that's, that's to be expected at this point. Yeah.

21:47And that started from somewhere, right? So someone took a risk. But, um, all that being said, I think, you've got to group these things together as reliably as you can. Yeah. But it's quite frustrating. I think even, you know, when we talk about benchmarks, you go to bid and we have literally been told by customers, like, oh, you know, you were over by a certain amount and it's like, well, they said you could drill this well in like six days with, like, and it's like, this isn't possible in this area. Like, we know that. And they're like, well, they just had the lower bid and it's like, well, do you want me to lie? Like, yeah, this is where, you know, more context, the, you know, we've talked to customers like, whole size, um, bench, uh, dilution rates, like, what are, what are we going to compare to try and make this more apples to apples? Yeah. Um, because just picking your best well in a general geographic reason or

22:49geographic area doesn't get you there. Um, and, and then it becomes like, well, my cherry picking, you know, to make myself look good. Like, how, how honest can we be with the data when we know we have to eliminate some of it because it's out of context, but like, how much in context we are like, well, don't include that one. It was, it was a disaster and it's not related, but yeah, disasters can be drilled out here and, you know, 90th percentile, they don't happen, but they happen. Yeah. Um, so, uh, I think, you know, that I guess the other part of this is, you know, we've alluded to it, but, um, cognitive bias, uh, and, you know, this is where we had a problem. Let's say it is, there was an issue, um, or something went really well, and that's fresh on somebody's mind, and then they look at the data through the lens of, I feel good about you or I don't feel good about you.

23:50Yeah. Um, and it is, you know, we're drilled so many wells so fast. Um, and so it's just surprising where even in a KPI, you know, where the covers a quarter or two, or it's like, well, let's go back to that well and it's like, right, we drilled that well and it went really well, but here's why, and then it's like, wait, so like, what do we do different and you're sort of like re-explaining something that the person oversaw. Yeah. But it's just they've, they've seen so much since then that they kind of have to be refreshed, um, that, uh, I think in both ways, I think even with a benchmark, even a benchmark, you know, us capturing the little winds of, hey, we, we reconfigured the solid, we got the solid control company we reconfigured that saved you about $8,000. Um, we've done that on five wells now. Um, you know, that's not a significant, insignificant amount of money over time,

24:52right? Yeah. Um, so the hard part is that when that becomes just like what you do, it's no longer like your baseline anymore, right? Yeah. Um, so I think even that's where some of the nuanced recommendations our people make, we need to, we need to spend more time emphasizing those. Most definitely. Yeah. And, you know, one thing that's interesting, we've talked about this for a long time is we always seem to just naturally gravitate towards cost per foot. Um, are there, are there other metrics that you believe are worth noting, uh, for drilling fluids, performance, maybe some that over time have become more important to certain operators, maybe something that we've keen in on, uh, because we have now rolled out our different softwares, our visibility and data tracking is now, uh, I would say more granular, uh, any sort of thoughts

25:52around that? I mean, I, the thing that I see is using anyone benchmarking isolation is not necessarily constructive. So everybody wants to see cost per foot. They want to see cost per day. You know, cost per 10 K or days per 10 K, right? You know, whatever any of those things. Yeah. Cost per barrel of whole drill has been an effort to sort of benchmark. Hey, we're drilling some slim hole and, you know, some not so slim. Um, you know, days on well, uh, I think can be relevant. But even that is like, okay, well, if we're just drilling, do, you know, is it rig release, to rig release, or is it drilling days or, you know, or mud report days? Yeah, mud report days. Like what does all that look like? Um, uh, you know, I do think that there, there's more we can, you know, dilution rates, I think it can be somewhat helpful. But the frustrating thing is,

26:54um, capturing decisions that are made by, uh, the operator that incur costs, but that is a decision they made. It increased our mud bill, but it was a better economic decision for them. Yeah. Um, and so I mean, you know, these cost per barrel, or if you're in a lost prone area and you lose a ton of mud, um, you know, the argument I would make is, okay, let's go, let's stop drilling. Let's run a temperature log. Let's isolate the thief zone. Let's, you know, spot some LCM or, you know, do a squeeze job and then let's go back to drilling where, you know, an operator with like 30, you know, 70% returns or whatever I would say, I'm not doing any of that. Like, throw some stuff in that's not going to plug a tool and let's get to TD. Yeah. Um, that is a better decision for them, but it is a higher mud bill. Right. Um, and so breaking that out, or say, okay, we made this decision because it was the best decision for well delivery.

27:56Um, you know, so it kind of brings me into my next sort of thought and I had a conversation with one of my customers over the weekend. Um, and we were just talking about drilling performance overall, versus like the last few years. And at a very high executive level, he know, he, he sort of has come up with what we were here. Now we're here. Um, whether it's, whether it was better or worse, I'm not going to get into the details, but he's like, you know, it's interesting. But there's nothing that I can attribute that the change in performance to. And, um, I'm trying to figure that out. And so I've reached out to the drilling contractors and, um, you know, this at and the other. And so I said, well, man, like, you know, I know we've brought up the, you know, lots of different rigs that you have running around this region. How do you isolate and when, how are you measuring that? Um, because like if, let's just say,

29:01hypothetically, you spend a bunch of money on one vendor and that vendor looks like they're, you know, over their AFE. Well, then when you go back to looking at your overall well economics, have your, you know, drilling costs per foot or whatever, your well delivery costs have they improved or has your costs to supply come down. And I guess I say all that to say is how do you at, like, how would you manually take, like, let's say we did a performance diagnostic. We took all our rigs that drilled eight different formations with 12 different rigs and figured out, okay, what, like in progression, did we do better or did we do worse? And what does that even mean? Well, then you go to MWD and you go to directional, then you go to bits and then you go to rig and then you go to drill pipe and then you go to this and you go to that. The answer to me has to be AI, eventually taking all of this data and figuring out, are we actually performing better as a company

30:05or does it go back simply to just like, are drilling costs in our production, like our drilling and completion costs have come down, our production per well is going up. Good enough. You know, like, well, I don't know if you call it good enough, but I think the big mis we see now is the relationships between all those things. Yeah. You know, I was sort of mortified to see one of these data companies like, you know, hey, you can just query, what is the best drill bit in this county? And it's like, well, you're missing a lot of, like the fact that it will give you an answer without asking you, okay, what's the whole size? What's the TVD? Like, and we've even seen these mismatches where, you know, if a customer say like, hey, we think some of our peers are outperforming us in this area. And then I was like, well, they just call their bench different numbers, but the TVDs are different. Like, those are easier, that's shallower. Yeah. You know, we've come across these things quite regularly where you can make it as complicated as you want and try and find some relationships. And there are

31:08statistical ways to do that, even without AI. But what we also see is, I mean, at the end of the day, if the well-economic speak, like, that's the most important thing, right? Like, if my cash flow is what it's supposed to be. And that also sort of captures what you see with what you would call moves to like Tier 2 and Tier 3, or I'm drilling deeper benches, you know, I'm drilling barnets and woodfords. And these, you know, they have good production, but I can't expect them to drill the same as a shallower well. And so, you know, the question is, I mean, this was one thing that, you know, Aliva Gibbs has brought up. They're seeing a lot more legislation about some of the stuff that people avoided figuring out who had the mineral rights to. But now they need that acreage to be productive. And so they're litigating. We're for a while there. They're like, don't

32:12have time for it. Don't need to mess with it. Let's move on. But as the primary acreage is brought into production, the question is now like, okay, how do we, how do we do this? And then I think the other aspect of this from benchmarking perspective, you talk about interdependencies is, you know, I'm sure they've come with some new term for this, but we're seeing a lot more people go back and try and, you know, catch a well between a few wells or catch a well like on producing pads where you have more depletion, you have more interference. But man, we could we could not get a couple more Ds. We own it. We've already got the facilities like this makes sense. And so for an operator, I think, you know, they can almost just look and say, okay, these, these things remain economic and efficiencies are driving, you know, better economics or at least consistent economics, you know, harder to drill well, but better production or cheaper to

33:13cheaper to drill now than it was. And I'll take less production because my cash flow stays the same or whatever. Yeah. I think the AI stuff, I'd believe it at more if I hadn't seen so much crap so far. But do you, and so not to cut you off, but, but then I agree, is it because we don't have clean enough data being fed into the AI? Or is it because the AI in itself is not like, hypothetically, you dump a big data sent to AI and say, whatever, I'm trying to identify trends over the last 18 months and you've got a table with 50 different drilling fluids, things per well. I mean, so yeah, that's what I'm curious on. Is it just the industry doesn't have clean enough data to feed it or is it just the AI is not at a place where it's prepared to handle the data that we have? I think it's a little bit of everything. So the data cleaning, I think people are doing a pretty good job of that stuff from what I've seen and then look, you know, there's probably somebody

34:17out there who can, you know, run circles around me on this. But the other thing I see tremendously is that there's not enough data. And I don't mean like volumes, but I mean context. So yeah, this can be like, why did we do this? Like, I can see that I nudged at this depth for some of these wells, but I don't know why. And they perform better. But I don't, you know, do the logs that I have align with some change in formation that was actually the decision somebody made on the sub surface team. Is that anywhere or is it just my well data shows we have a slightly different trajectory on these wells and they performed better? And so I think there's just elements that simply are not recorded. But I have everything the rig did, you know, the EDR captures all this stuff. And so contextualizing those things as I think has been somewhat problematic to drive decisions. You know, and this is why we updated our reporting system, right? Yeah, is we had a lot of stuff

35:20where it's like, look, I can tell you mudwades, I can tell you some other things. But the fact is, we want to be able to tell customers with much greater context. What is going to work and where the risks lie? And so, you know, that required us asking our personnel to input more information. We had to make it easier for them to gather that data. We had to make it intuitive. And then we have to gather it, right? So even as we've rolled out a new reporting system, like you don't start to see the winds for like six months until those data tables start filling up with sufficient sample space to tell us something, you know, that we're confident is reliable to tell a customer. So it's a lot of things. I once again have been surprised at how reluctant or maybe it's just we're stuck in our own domains, but because we're lucky to be fluids guys because we'll get blame for

36:23everything, which means, you know, we'll go look at gamilogs, we'll go look at whatever we can get our hands on to try and solve a problem because if it could be a fluid problem, you'd have to rule it in or out, which means we may as well try and see if we can do anything to solve the problem with our limited knowledge. And so the questions we'll have are like, have, you know, can you overlay these two things? Like, well, I can, but I've never done it. Yeah. So, I don't know, I should only get better, right? For sure. But I do wander as far as like key pieces of information we continue to not have, or we don't have in relation to other things that may limit what AI can help us with. Yeah. So, yeah. No, I, and sort of the closing out of that is because there are so many services working together, but don't have access to together data, to your point, except for the operator. But when you have, you know, in some cases, one drilling engineer looking after all of it,

37:26they're half the time spending time approving invoices, not, you know, and then asking us questions to answers that they want. But, you know, then we have, and then they have to figure out how to compile collective answers from everyone and piece it together to then deliver the message to their drilling manager, drilling supervisor. So, I think there's just so much more room for improvement on that kind of going back to the question, are you performing better or worse, and if you're performing worse, why, and if you're performing better, what have we done? Yes. It is, it has, and it still remains, very difficult question to answer. By feel like we're making progress. Yes. I mean, I think we are making progress, but, you know, it's even as much monitoring as we have in the field, we've talked about the gap between the design you do at the, you know, in the office and what happens in the field, or even, you know, getting the buy-in or, you know, hey,

38:28we're not going to call this in, but this is what we're going to do. So, yeah, it's, it's a, it may be a longer road than people think, but I also think that there's a lot of rich opportunity to bring this all together, and it's certainly something we're putting a lot of energy into, and, you know, regardless of where it comes from, if our customers perform better, because they're working with us, and we can show them that, we keep our jobs. That's it. And everyone likes jobs, because jobs means food on the table. Absolutely. Interesting conversation. I know we've almost ripped through 40 minutes, and for those who've lasted this long, really appreciate you listening. You must have found this conversation as interesting as we did. If you want to chime in, add anything, ask any questions, you can reach out to Mad Nye on LinkedIn, or you can reach us at the fulllinepodcast.asfluids.com. Be sure to check out the YouTube page, website, and again, if you have any questions or topics, ideas for a show, we are always hungry for that. And with

39:34that, means that everyone take care for now. Cheers. Take care. Thanks for listening. Please tune in next week for another exciting episode of The Flow Line. And remember, may your returns always be full and your trips always smooth. The use expressed in this program belong to participants and not their employees. The program is for informational purposes only, and cannot take the place of seeking professional advice. Copyright AES Drilling Fluids.