Liberty Energy Inc. (LBRT) Earnings Call Transcript & Summary

This webcast presentation is for Bank of America clients only. If you are a member or representative of the press or media, please disconnect now. And now I'd like to turn the call over to Chase Mulvehill.

Yes. Thanks, Sarah, and thanks, everyone, for joining the next session here. Next up, we've got Liberty Oilfield Services who, after the recent announcement that it's acquiring Schlumberger's OneStim U.S. completion business, is set to become the second largest completion service company in the U.S. Liberty is consistently thought of as one of the technology leaders in U.S. completions. And it's no different when it comes to digital with the company's digital strategy really focused on 3 areas: number one, employing subsurface engineering and well design to improve well productivity and lower the cost per barrel for their customers; number two, advancing equipment design and operations through engineering, real-time automation and predictive analytics to lower its operating cost; number three, using real data-driven analysis and design approach to reduce environmental impact and improve emissions. Joining us from Liberty today, we're lucky to have Ron Gusek. Since November 2016, Ron has been President of Liberty Oilfield Services. Ron has really established himself as one of the most forward-thinking individuals in the industry. Ron is joined today by Leen Weijers, the Vice President of Engineering at Liberty. Leen has been with Liberty since its founding and previously was at Pinnacle Technologies where he was instrumental in developing FracproPT, a frac growth simulator. Joining me today in moderating the call is Mike Sabella who most of you know is on our oilfield service team here at Bank of America. So Ron, really appreciate you joining us today and take it away.

Thanks very much, Chase. Good morning, everyone. Appreciate the opportunity to be with you today and share a little bit about our digital strategy at Liberty. We're going to talk a little bit about the past and how we got to where we are and maybe a little bit about the future as well. So going back to the beginning, certainly want to look at where we started. A digital platform, of course, being nothing new for us here at Liberty. While it is one of the latest buzzwords, it has been part of our DNA since our founding. Before we pumped our first frac job, Liberty had built the first comprehensive database of petrophysical and completions well data for every well drilled in the Bakken. We had already developed correlation techniques to find out what drove well performance in the Bakken. We knew the relative performance of different operators. This data-driven engineering of the stimulation programs laid the foundation for what we would be executing for our early customers, a major step change in Bakken completion design to one that was the genesis for modern completion practices in the basin. When we began, our very first frac fleet had a satellite on it. We gave customers iPads, a bit of a rarity 9 years ago, so that they could receive real-time transmission of their frac data and watch in real time while we could watch that same data in our offices. That digital connection ensured complete alignment between us and our customers and visibility for the E&P company as we pump the new designs. For almost 9 years, the Liberty team has been a leader in the use of technology-enabled business model. That model is key to our ability to drive value creation and underlies every aspect of our business. Leading-edge technology deployment, innovation in ESG and a differential and adaptive culture have enabled us to deliver differential returns. Our CROCI has averaged 27% over 8 years, exceeding the S&P 500 by 1.5x, something we are quite proud of in our industry. The decisions we make in each of these areas to advance the company are all supported by data, and most importantly, data that we have confidence in. We are excited by the opportunity to further enhance our digital capabilities, along with our footprint and scale, through our recently announced acquisition of the Schlumberger OneStim platform. As you can see on Slide 4, the combination of the 2 organizations will result in an unrivaled pure-play frac company. This will further strengthen our ability to carry on our track record of delivering outsized returns on invested capital. At Liberty, our digital strategy has been focused on 4 key areas. The biggest of those is subsurface engineering and well design. Leen, our doctor in residence, is going to delve into these technologies in some detail in a minute. We also have emphasis on data-driven equipment design, operations optimization and environmental improvement. We will spend a couple of minutes touching on initiatives in these areas as well. Scalable cloud-based business systems are critical to supporting the growth of Liberty. They play a role in many aspects of our business. We'll look at one of those and its role in understanding opportunity for efficiency improvement. With that, I will turn it over to Leen to delve into the details of our downhole intelligence world.

Thank you, Ron. Part of the Liberty DNA is downhole intelligence. Liberty's customers -- or customer-facing goal is to understand the reservoir and what it requires in terms of a frac solution. We do not push products but our solutions center around reducing the cost of our customer to bring a barrel of oil to the surface, and this is on Slide #7 currently. The solution tools we use span the development cycle and are intended to spiral up the frac design we bring to customers, aiming to get better as we learn more. Starting with data, we focus on bringing data from a variety of sources together, scrutinized for accuracy. We turn the data into knowledge with some of our field study tools, such as FracTrends and LibertyMVA. We turn knowledge into action by making frac design changes and changes to the frac recipe this doctor and his team may prescribe to a customer, as backed up by big data analytics and laboratory testing. Finally, we turn this process into value for customers through production and economics evaluation tools. Fraconomics helps determine big picture sensitivities. Simple and complex frac and reservoir modeling evaluates those sensitivities on a more detailed scale per well, per pad or a foreign area. We're now moving to Slide #8 and let me now focus on the big data analytics side of our approach to help lower our customers' cost to raise a barrel of oil to the subsurface. Our team, we are second to none, with world-class engineers scraping public and internal data sources to build an extensive proprietary database that is unique in combining petrophysical, completion and production data. Our data analytics in a specific area, for example, here on the right-hand side, the Midland Basin, can identify the main production levers in a specific area. That's not necessarily driven by proppant intensity only. We list here on this slide 6 of these completion levers. For example, stage intensity or proppant type or average proppant concentration, but other parameters may also make it to become the main production driver in an area based on the analysis. For all of these drivers, we evaluate how they impact production economics in the chart on the bottom, where we determine, for example, given a customer's high or low input cost for water, a major cost item for customers that we often don't see, how the dollars per BO metric can be minimized and how does change -- how these changes can optimize the frac design. Our job is to determine which of these production levers delivers the biggest bang for the buck. Now back to Ron for a continuation on Slide 9.

Equipment design and manufacturing is another area in which we rely heavily on a digital data stream to drive our decisions. This data comes from 2 sources. We collect a significant amount of data summarizing our daily operations and the issues that arise over the course of the day. The information gleaned from the analysis of that data helps inform our manufacturing decisions. By identifying key equipment issues on location and the true impact of those issues on operations, we can prioritize changes in equipment design with confidence in the return on that investment. The second...

Please stand by. I think we may have lost Liberty. Hang on 1 second. [Technical Difficulty] Please stand by. We're having Liberty dial back in. They dropped the line. So please stand by.

Are we back in?

Yes, Ron, you're back in. Sorry.

Sorry about that. We're not either, but tell us where you lost us.

Yes, Slide 9. So if you want to start back on Slide 9, that's where we lost you.

All right.

Equipment design and manufacturing.

All right. So equipment design and manufacturing, we were talking about there. Yes. All right. Equipment design and manufacturing is another area in which we rely heavily on a digital data stream to drive our decisions. The data comes from 2 sources. We collect a significant amount of data summarizing daily operations and the issues that arise. The information gleaned from the analysis of that data helps inform our manufacturing decisions. By identifying key equipment issues on location and the true impact of those issues on operations, we can prioritize changes in equipment design with confidence in the return on that investment. The second data source is the equipment itself. There is an array of sensors on every piece of equipment, recording operating metrics every second, of order 180,000 data points in that time frame. That data provides insight into the performance of each component under all operating conditions, allowing identification of minor issues before they become major ones but also providing the ability for component optimization. Our rapid innovation cycle leans heavily on the massive volume of data collected across our fleet on a daily, weekly and monthly basis, ensuring engineering of next-generation parts, incorporates the most recent learnings from the field. Changes are then moved rapidly to the manufacturing stream with the goal of delivering data-driven improvements out to operations as quickly as possible.

All right. Moving on to Slide #10. We use integrated cloud-based systems from our Oracle ERP to our iPhone-based logistics management software. Performance reporting and assessment are key for us, and we've done this at Liberty since day 1. Our field engineers are at the spear point of this data collection effort. For example, by tracking how we spent 1,440 minutes out of every day on a frac location, mostly on pumping, but sometimes on essential non-pumping tasks or sometimes on downtime due to internal or third-party costs. Digital tracking and reporting helps us to understand, amongst others, why we may be down, which water company we would love to team up with and helps determine what we need to do to maximize the time we spend pumping. This has helped push Liberty to an industry-leading average stage count of nearly 200 stages per crew per month.

Our digital platform informs our approach to subsurface engineering, to improving operational efficiency and to equipment design and optimization. It also plays a key role in the work we do to minimize the social and environmental impact of frac operations. Looking at Slide 11, you can see 2 important areas where we employed robust data collection and evaluation to drive innovation on a Liberty location, with the goal of reducing the social impact of hydraulic fracturing operations. Noise, dust and truck traffic represented an opportunity for us to be better. A large data set allowed us to quantify the potential improvements and, ultimately, design and deploy solutions that dramatically change the game. A 2-year effort ultimately led to the Liberty Quiet Fleet, of order 3x quieter than a conventional frac fleet. Working closely with the PropX team, we were able to engineer a proppant delivery system that reduces dust levels to well below the most stringent OSHA requirements everywhere on location but the blender hopper. These advancements, guided by data, have made locations dramatically better for the people who work on them and for those who live nearby an active operation. We've been looking at electric frac fleets for many years now, not only how to build the best pump but also the best way to power them. Here too, a digital approach has helped ensure we will deploy the industry-leading solution when it comes to maximizing efficiency and minimizing emissions. Working closely with the manufacturers of both engines and turbines, we employed robust emissions modeling software to develop emissions profiles for the various power sources across a wide range of operating environments, varying load requirements, environmental conditions and operating performance metrics. Slide 12 shows a simplified cartoon of the results of the modeling. Rather than simply adopt what was the industry standard for power generation, robust analysis has instead pointed us in a better direction, utilizing natural gas reciprocating engines rather than turbines. We have a long history of environmental progress driven by our goal to be the best at what we do and informed by our digital platform, the data it provides and our confidence in that data. Our strong commitment to our digital strategy fosters collaboration and innovation, both within Liberty and with our many partners, both customer and supplier. It ensures we can quickly deliver the right technology targeted to address the specific issue and subsequently evaluate the success of the implementation. While we are energized by all that we have accomplished to date, we remain very excited about future opportunities as we continue to grow our digital efforts. With that, we'll wrap up the formal presentation and turn it back to you, Chase, for Q&A.

Yes. Yes. Thanks, Ron. Thanks, Leen. Obviously, a lot to unpack here. A really good presentation. Clearly, that you have a differentiated strategy when it comes to digital, especially when you compare it to other pressure pumpers. So maybe if you can just summarize for us in a few sentences just what is your digital strategy and what differentiates that from some of your larger peers because some of the smaller guys really don't really have, I guess, an explicit digital strategy. And then what makes your digital strategy a more sustainable advantage over time?

Yes. Thanks, Chase. I'll take a stab at that, and then maybe Leen will toss in some thoughts as well. But I think as you highlighted -- first of all, I think we have quite a number of peers who just don't have a strategy in line with what we have been thinking about, whether you talk about subsurface engineering capabilities or surface capabilities. But when you think about us compared to maybe some of the larger organizations that operate in this space, I think we're different in a couple of regards. First of all, I think we're very targeted in our approach. I think there are organizations out there that have maybe had more a philosophy of research and development for the sake of R&D and ultimately find technologies that might be interesting to deploy, and then they send a sales team out to try and sell the latest widget that they've developed. I think we're a lot more targeted in our thought process. In other words, I think we aim to have a strategy from this standpoint that's driven by our customers' needs. So we want to think about a specific problem that exists out there in the field and then work on a solution to that particular problem. And so I would point to the Quiet Fleet as an example of that. We had a situation in Colorado where we operate within -- as close as 500 feet to somebody's home. That represents a challenge for our customers here in Colorado. And so we have the technical capability to address a problem like that and ultimately bring a solution to the table. So I think we're a lot more issue-focused in terms of how we do that and then I would also say a lot more data-driven in how we think about these things. It's easy to get caught up in the latest buzzwords of the day. E-fleets became all the rage maybe 18 months ago or 24 months ago. But I think when that conversation started to happen, a, everybody thought we were going to change to electric fleets overnight but ultimately thought that there was only one way to approach that problem. And I think we were prepared to take a step back and rather than rush into something and just deploy a me-too solution to that, think about how we could use data to ultimately deliver what was going to be a better solution in that particular situation. So while that doesn't necessarily make you a first mover in that area, I think it ultimately means that we deliver the right answer in the long run. So I think those are a couple of ways we think about things differently there.

If I can add to that -- sorry, if I can add to that, Chase. Maybe on just the strategy for collecting subsurface data and modeling from that and then to determine what we can do to optimize production and optimize economics, one of the things I can say is that most of our peers -- data about completion or some completion data, production data, of course, is available in our industry through, for instance, Drillinginfo and IHS. And most of our peers have subscriptions to their services. So -- but their approach is often that when a customer may want help for production optimization is that they do a case study. They pull data from these different sources and analyze it. Our approach is different there that we have a consistent data collection effort and data scrutinizing effort, check and double-check what that data means. We have a team that does nothing else in that. Even if we have no studies needed from a customer in a specific area, we still consistently every day pull data from each of these different basins, scrutinize it so that it's available to do a study when needed. And of course, we regularly do these studies also just on a large basin scale type. So we can see how kind of the production levers, how they change in different basins, maybe over time or for a specific area. So we're ready when a customer in a specific area asks that we have this study available and can probably provide it to them within a 1 or 2-day time frame. Very quick turnaround with the targeted effort, consistent data collection that we do every day instead of just ad hoc for a specific study that a customer requests.

And that's probably a good segue into kind of another question. Kind of thinking more about subsurface operations and the digital innovations that are potentially there. Completions seem to be an area ripe for digital innovation. And so maybe could you talk about some of the opportunities that you -- either you're kind of attacking today or some solutions that you have out there today or maybe some things that you're thinking about developing? Because obviously, you've got frac cluster efficiency that is pretty poor still to this day. You've had frac hits, parent-child interference, things like that, that have been an issue on subsurface. So just maybe kind of talk to what you're seeing out there and kind of what you're doing to solve some of these issues.

Yes. I can maybe -- certainly talk a little bit about maybe some of the next big problems that our customers are asking us to look into. And you bring up a very interesting one. Perf cluster efficiency is a big one today. I can -- maybe just stepping back a little bit. Liberty has been at the forefront of some of these changes to perforation design through our company's life very early on. Ron mentioned it earlier in the call, we were instrumental, I think, to -- especially in the Bakken, at the time we got started there, sliding sleeve completions were the thing to do there as the industry was dominated by demand for service companies and service companies could actually demand the type of frac design where they could improve their efficiencies. So sliding sleeve jobs were good for service companies, not necessarily good for our customers. And this is one change that Liberty made around the year 2012, 2013, our first few years in the business, where we saw a tremendous uplift, maybe typically 10% uplift or so just attributed to going from sliding sleeve to plug and perf. Overall, the production improvements that we made with our design were significantly larger than that, but attributed to just that change in perforation design, about 10% of the production uplift. Now today, we're at the forefront again of another change that we've been working on with our compadres at Liberty Resources, and that is to maybe ease off a little bit on stage intensity and work quite a bit more heavily on perforation cluster intensity. So that trade-off typically results in lower frac cost as a company can complete a well with fewer stages. But we've seen that we can actually do that, let go of that criteria a little bit as long as -- and not really impact the production response negatively. But it's a way again to bring down the dollars per BO, work on the dollar side to reduce the stage count, very important in this stressed market and -- while not impacting production. So -- and it's things like that, that we can work on with our kind of data-constrained physics models and the statistics. But also especially on the cost of design side, this is more of a modeling effort, frac models, reservoir models, calibrated and working jointly because a lot of that data, unfortunately, is not available in the public domain, but we get some of that data -- I think we're better than most of our peers in obtaining this data, not just through the frac jobs that we do ourselves, but also through some customers who trust us enough that provide that data for us to do expanded studies and see the impact of that perf cluster intensity where others really cannot see that because it's not available in the public domain. That's a lengthy answer, but I hope that answers your question.

Chase, I might jump in there and just add a little bit more from maybe a higher-level standpoint that I think your question points to, which is just how dynamic the situation is and why it is so important to have a digital strategy around subsurface engineering. If you think about how the completion of a well has evolved, since the time we really got started on this shale revolution, so backing up a decade and change now, it's quite phenomenal the progress we've made, and a lot of that even just in the last 5 or 6 years or thereabouts. But I guess the point of that is that things continue to evolve, things continue to move. There's never a place where we get to a static answer that is the right answer for a well. And in order to be in front of that, in order to be able to work with the customers to help them continue to move forward in their completion, to find the right answer given the economics of the day, whatever the price of oil might be or a change in completion design that continues to drive up recovery rates or something like that, you have to have a subsurface engineering strategy to go along with that. And so that's why we see it as so important to have a team here that is focused on building that data set every day and ultimately working so closely with the customers on that. It's something that will play a role for many, many years to come in fracturing just given how dynamic the world is that we work in.

Yes. Absolutely.

Hey, Ron and Leen, thanks. That's very helpful. This is Mike. I'm going to hop in with a question here, if I could. So Liberty, you all maintain a massive database with production and completion data. Can we just talk maybe, is most of that public domain data? Or is there a proprietary data in there that customers have agreed to share with you? And if it includes the latter, how do you get your customers to agree to share the data? It's always been my impression that E&Ps don't really want to share their data. Is that changing?

I don't think so. But I think the main reason I think they're willing to share that data, of course, boils down to trust. They trust us that we can do something maybe with that data included in our analysis that we maybe could not have provided without that data being included. Now again, I don't think that business environment is changing. There are certainly some of our customers who request a second opinion on what we see in just public data that do not want to share their private data, and that's totally fine because we want to leverage our pumping services and help out where we can. But there are other customers who actually do create kind of more intelligence about maybe our opinion of what we need to do to kind of provide the biggest bang for the buck in an economic type of analysis. And they see, I think, the need, especially with the fact that public data, especially in Texas, is not always very complete, that we can do a better job with the analysis when some of that data that they can provide that's not in the public domain is included. So of course, we have to be very careful with that. We don't share data with anybody, period. So raw data in our database is never shared. That's a very safe way to protect it. What we do share, and companies know this ahead of time when we obtain their private data, is the results of a specific analysis in, say, an area, so if we draw a box around maybe an operator's acreage, may include information from wells that are maybe not their wells. But we bring that data into the results of an analysis, for example, to determine what the biggest drivers, the biggest leverage are for production response. But again, the raw data behind that analysis is never shared with anybody, period.

Mike, I think it's important to say that this has been a work in progress that maybe has started from our very beginning. I don't think customers agree to share data with you until they trust you. And so I think we've worked hard to build a reputation since our beginning that, a, we're a trustworthy organization. Leen pointed to the fact that we never share raw data. It is housed in our database, and only analysis as a result of looking at that data is ever shared with people. So we're -- you have to work hard to build trust there, but I think you also have to work hard to build trust in the information that you ultimately provide. Operators do not see value in sharing data with an organization if that data doesn't lead to tangible conclusions that they can execute on in the field. And so I think starting way back with the design optimization in the Bakken, it ultimately led to a meaningful step change in completions there. We have built that trust with the E&P community such that they know that when we take that data in house, a, it's going to be treated with care; but b, that the work that we do with that and ultimately the results that we produce and recommendations that we make are sound, engineering-based recommendations that are provided with the best interest of them at heart with the goal of lowering their cost to produce a barrel of oil rather than some service company motivation to find a way to pump more expensive fluid or more sand in the ground or something like that. So I think that's really been a -- that's really been an effort that has paid a lot of dividends over the 8 years of time we've had. I think the other thing that really helped them consider sharing data is just the fact that results get better. Leen alluded to it being key that more data ultimately provides a better outcome. If you think about our database, it's massive, we would argue unrivaled. But even at something north of 100,000 wells, I mean, that's not even the number of credit card transactions that take place in a second. And so if you think about the ability for just plain old multivariate analysis without any engineering support behind that to arrive at the best possible conclusion, that's not really true in our scenario. You can ascertain shopping patterns and things like that from credit card transactions because there's just so many of them. But we suffer in some regards from almost a shortage of data in our particular world to arrive at the conclusions we need to. Every extra data point, particularly directly related to the area we are focused on, helps to improve our analysis capabilities there. And so I think operators recognize that they are only better served by contributing data to the effort. They all benefit from the results of that.

Yes. Understood. That's a real helpful response to that. If we can just kind of follow up, you offer LibertyMVA, which is the big statistical software model that helps you evaluate kind of the complex relationships in well performance and completion parameters. Can you talk to like how many of your pressure pumping companies have built data-driven models like this? And maybe just talk to how your statistical model would compare to kind of what some of the E&Ps have to offer.

Yes. To our knowledge, our peers do not have that consistent daily effort to look -- to scrutinize that data with a team of people -- about 5 people we have here at the Denver office. Some offer through subscriptions, again through Drillinginfo or IHS to do this kind of ad hoc, pull data, et cetera, for a specific study that a customer may request, but I don't think they have that consistent effort, at least among our peers as much as we know about that. On the differentiation, maybe about what our E&P customers can provide with multivariate statistics and things like that, they certainly, of course, do that. They have -- many of them have large databases with their own wells. Some of the areas where we can help is to help them understand from what is available in the public domain, what their neighbors are doing, for example. And their benefits -- often on the E&P side, the benefit is that they have much better geological data than kind of the more global data that we have on a per basin basis. So combining that effort with maybe some of their better geology background and knowledge about what happens in their specific area of the field, with our completion knowledge and the data that we have to back it up and the modeling efforts that we have to help them out, I think, is a great combination in many cases.

That's helpful color. We did have a question come in, and it kind of ties into kind of where I was going to go next. The question that came in is, how much of your completions that you do today actually involve you providing subsurface data solutions? And then the question that I had, which is kind of related, that, I guess, on the subsurface side, you provide a packaged solution kind of along with your basic pumping solutions when you think about subsurface digital solution. So why do you think this is the right pricing strategy? And why not really unbundle it and sell it discretely?

All right. Thank you for that question. To go maybe to your first question first, in some way, I think we help probably at least half the customers that we work for on the pumping side. And the level of help we provide can be different. Sometimes, some of the bigger companies we work for these days, some of the majors have their own tech teams. They do internal R&D. They do internal analysis. Sometimes, we may provide a kind of a second opinion for these teams to help them with something, but we do not have kind of a day-to-day help with frac design work for them. And other customers, maybe that's about 1/4 of our customers, we help them with frac design changes or again make tweaks to what they provide based on what we think works better in a specific area. To go to your second question, our sole goal for maybe charging for technical work, and that's not really what we've done over Liberty's lifetime, and we're not planning on that either. Our sole goal in a company, and it goes for everybody in the company, is to keep our frac crews busy, right? That's where all the work is being done. Those -- the folks there provide our paychecks for everybody in the company. And it also translates to work on the technology side. And we feel that offering our technology, the help we can provide customers is a way to engage our customers. It's a way to leverage our pumping services. And we feel there's way more value in doing it that way than to charge and maybe add 0.1% to the company's revenue from the technology side.

Chase, I'd maybe add to that a little bit. Sorry to jump in there. If you think about who we've been as a company, we've always been about a partnership model. And so I think you could really think about that 2 ways. We could offer consulting as a commodity service, in which case, we now have a -- or as a stand-alone service, in which case, we now have a scenario where the customer viewed that as a service that they had procured and ultimately could do whatever they wanted with. They could take that and bid out the design because they bought that design. But I think in the interest of building a long-term relationship with our partners on the E&P side, it makes sense for us to deliver that part and parcel with the level of service that we provide on location. And I think that just goes towards building that long-term relationship that we aim to have with each and every one of our customers, cementing the bond that we have where they get top-notch service out on location, but that is also supported by leading-edge technical capabilities in the office to ensure that the design we execute in the field is the best possible design. And I think as we think about that going forward, we've drilled a lot of, we'll call it, Tier 1 acreage in many of the basins that we're in. We -- as we continue to move ahead in each of the basins, the acreage that we are going to be drilling or working on with our customers is going to change, and that ultimately means potentially increased technical complexity and further engineering needs as we go forward. So we continue to see the opportunity to partner with our customers in this area grow and grow and grow. And I think from our standpoint, that only strengthens the relationship between Liberty and those customers as we look to the future.

Yes. I guess that kind of leads me to another question and just kind of thinking about real-time data analytics. I think there's a push starting out there in the industry today to really kind of capture more real-time data analytics, especially on the frac side, thinking about frac complexity, lean, thing like that -- things like that, so you can change frac design on the fly. And so if the industry really starts to transition towards that, how important will it be to really have that subsurface digital knowledge and ability to advise your customers and change frac designs on the fly?

Yes. I can take a stab at that, Chase. Of course, that's tremendously important. And before we can maybe do that on an efficient basis, of course, we need to walk before we are able to run. And I think that's what we're doing today with our knowledge there and our extensive combined production, completion and petrophysical databases and our physics-based constraint models and things like that. So certainly, we see promise in certain technologies that are very nimble, I think, in their application. I want to maybe jump to -- a sealed wellbore pressure monitoring, for example, is a very nimble way to determine kind of maybe in a subset of what is happening. And this can also be done on producing wells, et cetera, where we can see pressure perturbances as offset wells are hit by frac jobs from a well we're treating. This provides information on the time it takes, for example, for the hit to occur into a frac job, maybe tied back to a volume of pumping and maybe tied back then to how length and fracture height are progressing over the duration of a job, helping to calibrate our models. And that can be tied back then to perf cluster efficiencies and things like that, that can help us understand better of what we need to do to improve that perf cluster efficiency and what kind of volume is needed to improve the SRV that we have around the well in the best possible way. So -- and these are then things, of course, we can -- with those technologies that we deploy in the field today in the form of our Well Watch technology where we can make suggested real-time changes to customers. Now today, a lot of that is still maybe looking after a stage or looking maybe after a well, evaluate and then go back to the customer, maybe this is what you need to do on the next well. It's still not often in a real-time sense, although we could. But often, there's so much work going on that is often taken for reevaluation afterwards and then taken on a design change for a next series of wells we're pumping.

I might add to that, that as much as we continue to advance the digital capabilities for doing that, ultimately, I think we hope we get to a place where artificial intelligence can take a real-time data stream coming from the equipment on location, the data that we collect on surface and also some amount of subsurface sensors and make decisions about how to optimize our frac, but we're not there yet today. And so to go along with that, you have to have people who can look at that data and ultimately make appropriate decisions around that. I think back to when I started as a frac engineer and I would -- and I sat in a particular customer's office and satellited frac jobs for them. Three jobs a day was kind of the going rate for us. It was a different time back then, just single-stage wells. And -- but I think through my capabilities as an engineer and how those progressed from the first time I ever sat down and satellited one of those jobs to -- by the time I had observed hundreds and hundreds and hundreds of them and what my ability was to make interpretations and ultimately recommendations around how to improve that design. We still have an engineer sit on every frac location we have, watching every frac stage that goes in the ground. And so as that team of folks continues to build up a reservoir of knowledge around how fracs behave in particular areas and what they see from the data that's coming, we have that inherent ability or that capability internally now through that team to help make real-time decisions based on the data that we have available to us today. That will continue to evolve. The amount of data we get and the artificial intelligence around interpreting that data will continue to grow. But between now and the time where a computer can run a frac job, there will still be a huge amount of human input to that. And so I think that's equally important to us as we think about our digital strategy is recognizing that a great team of folks who know and understand hydraulic fracturing are still critical to making great use of that data for our customers.

Yes. It seems like a logical part of the business, especially as we really kind of push towards real-time data analytics. One last question. Kind of a little bit over time here, but just kind of went in with this one about the merger between you and Schlumberger's OneStim and just really kind of talk about the synergies on the data side. Obviously, Schlumberger has got a lot of geologic and petrophysical data sets. Not sure what kind of collaboration opportunities you're going to have there. And then I think you mentioned some patents in some of the literature from the presentations. Could you just kind of talk about the synergies on the digital side with the combination of OneStim?

Yes. I'd be happy to touch a little bit on that. And just to correct you, of course, this is an acquisition of Schlumberger OneStim's North American assets. But we're very excited about joining forces, and they have -- especially on the modeling side, they have some very high-end modeling tools that we typically do not use. Our approach on the modeling side is typically a bit more simplistic and typically good enough for the understanding that we have of the subsurface. And it makes us nimble and very responsive in outputting the results that we have. But we now, with, for instance, their Kinetix software, have the ability to also go quite a bit more complex for those cases that kind of warrant a more complex analysis where the data is available to feed models like that. Of course, they also bring a variety of different products. For example, their BroadBand products, especially in conjunction with Well Watch, is a great way to maybe see if we can limit fracture growth, if frac hits occur on a regular basis or too early on in a job. So I think we're quite excited about kind of what they bring on that side. And of course, there's also, as you mentioned, the possibility of petrophysical data and things like that, that we can benefit from that we maybe currently could certainly maybe improve on -- for the fact that it's just a very large scale, big picture, petrophysical data set instead of -- and sometimes missing some of the details that we need that hopefully they can work on, but that's -- or they can help provide, but that's still a work in progress, Chase.

Of course, we can't move the customer data directly over. That data belongs to the customers. But certainly, I think we would hope that post close of the transaction, when we reach a point where -- when we can start to have conversations -- direct conversations with those customers, we will go out and visit with each and every one of them and talk to them about the analysis work that we do and the efforts that we have ongoing internal to Liberty with the hope of adding all of that data to our database and furthering our capabilities. So it's -- it ultimately is our hope that particularly given the synergies we have from a customer standpoint, we didn't have a huge amount of overlap there, we could significantly grow our data set in that regard. Of course, they come with a huge amount of inherent knowledge. They've been technology leaders in the industry alongside of Liberty. And I think third-party data certainly suggests that they are very well viewed in that regard. So we're, from a combination standpoint, incredibly excited about what they're going to bring to the table, the breadth of knowledge that they bring to the table, the experiences that they have that I think will further elevate the platform we're able to put forward once we get through the close of the transaction. So yes, very excited about what we're going to end up with together.

Yes. Obviously, a nice opportunity for Liberty in that acquisition. And overall, really excited about what Liberty has to offer on the digital side. This has been a good hour spent walking through your digital strategy. And hopefully, the audience has gleaned a better appreciation of kind of what you bring to the table from a digital perspective I know that we have. So with that, we're kind of closing. And Ron, Leen, appreciate the time. I'm not sure if you'll have any closing remarks, but I'll turn it over to you guys just in closing.

Just want to say thanks very much, Chase. We appreciate the opportunity, appreciate the great work that you guys are doing and I think what was a -- what's been a great day and a bit so far of conversation, but look forward to hearing the rest of the day as well. So we appreciate the opportunity to be part of it and share a bit of Liberty's story. Apologies for our technical difficulties. Clearly, we're going to have to work on our digital strategy around telephones, and we'll see if we can get that fixed. But it's -- but this is obviously an important piece of the world for us. It'll be a very important part of our world going forward. And so appreciate the chance to share.

Thank you.

Thanks again. And thanks, everybody, for joining.