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Secrets to Unlocking Data in the Energy Industry

On March 3, Ripcord hosted a webinar about the role of data in the energy sector. Trevor Hicks, Managing Director at Stonebridge Consulting and member of the PPDM Association Board of Directors, stepped in as the speaker for Secrets to Unlocking Data in the Energy Industry.

With a wealth of experience in both the energy and software industries, Trevor gave plenty of useful insights from a unique perspective. During this in-detail discussion, we covered questions like:

  • Trevor’s background and how he got into the energy industry
  • The role technology and data play in the oil and gas industry
  • Why data is considered a valuable asset for energy companies
  • Different challenges that utilizing data faces in the energy industry
  • Why the CPDA designation is important for working in this field

Listen to the full conversation here.


Trevor Hicks: So thanks, everybody, for joining. Yeah, so I’ll talk a little bit about my background. So, how did I get into the energy industry? It was actually, I’ll admit, it was a little bit by mistake. I was an undergraduate at University of Tulsa and was approaching graduation, got a phone call from the Chairman of the math department, I was a math major, and so I’m kind of a nerd, and said these guys out in Schlumberger and I needed some help part-time with software testing and so I went out there, got a part-time job while I was an undergrad. Then I wound up staying with Schlumberger for about 18 years, so that’s what got me into the business. I did a variety of things at Schlumberger, worked, but mostly software engineering, for the most part, was kind of the unifying theme across all the different roles I had there, but worked on software for factoring, wire line drilling, and the biggest job I wound up having there was the Head of Engineering for SIS in the United States, which was, the SIS is their commercial software group. And, in the years subsequent to Schlumberger, where I left there in 2009, I had a few different roles, Baker Hughes for a few years, worked for a pipeline software company for a few years, and I’ve been with Stonebridge, I just had my four-year anniversary here [at] Stonebridge Consulting where I lead, I’m Managing Director here where I lead our, now what we call our smart source group, and that’s where we’re doing technical support and services, mostly for data management and data services for oil and gas companies.

[2:15] "Tell me a little bit about what Stonebridge does, and how you help with your plans." 

Okay sure, yeah, so I would say, the easiest way that I can sum up Stonebridge is to say that we do… We’re doing data integrity, and that’s what we’re really helping our customers achieve, and I don’t know how common that language is, data integrity, and I use it kind of deliberately. Sounds like we’re still getting comments on echo, sorry. So, hopefully, it’s not on my end there, but data integrity, what I’m deliberately trying to draw an analogy there between asset integrity and data integrity because data really is an important strategic asset for oil and gas companies, and there are some pretty close analogies between the sorts of maintenance and service and support efforts that you would do for your physical assets that you really need to do for you data as well, and so fundamentally, that’s what we’re all about is making sure that that data is serving the purpose that it was created for, that you have quality, you have correctness, that your processes around managing that data are efficient. So that’s really kind of the fundamental bottom line of what we’re all about there.

And just to even kind of touch back on the comment I was making about data being a strategic asset, that’s language that I try to be a little bit careful about because asset does have a fairly precise meaning in the financial world. When you say asset, you’re talking about something that generates cash flow that you advertise or depreciate on your books, and so when you... One of the things that I think you need to be careful about when you’re talking with your CFOs and financial folks about calling data an asset is the fact that when you say the word asset, that means something very specific to most of the folks who work in a finance kind of role. However, I’m still very comfortable using that language simply because, in most cases, for an oil and gas operator, your data really is an asset on your books. It’s not explicitly separated out as a separate line item. I’ve never seen an oil company that reported data as an actual asset on their books. However, when you think about when a well is drilled, there’s a lot of data gathering activities, which are typically capitalized into the cost of a well, and you think about your wire line logs, your directional surveys, your core samples, your core analysis, your mud logs. You’re spending a lot of money on data, and that money is typically capitalized into the well, and just to throw out round numbers, but it’s typically, for a well that’s shield in North America today, you’re generally going to spend at least a million dollars on data, if not more, and that cost is, again, capitalized into the well asset, and so then if you multiply that out, just again, thinking broadly, not trying to put any auditable numbers out there here, but if you’re a relatively large operator, say, with 20,000 wells, and if each of those wells has at least a million dollars a data in it, that’s $20 billion that you have put on your books that’s data. Now, of course, that may be depleted and advertised over a course, so maybe as a company operating 20,000 wells, maybe you’ve only got 10 billion left of data on your books, but the fact of the matter is, is that data is an asset, and it’s on your books, and it’s gigantic numbers, and so it needs to be, it’s worthy of investment.

[6:31] "What’s one of the most challenging aspects of creating a robust data practice and process?"

Trevor Hicks: I would say, probably, there’s a couple of challenges here that I would talk about, but I would say the biggest one is that it’s just simply that the vast majority of people don’t see data as an asset that they wanna follow robust procedures and processes around. It’s difficult to put governance in place around managing the data asset, and part of that comes from having a top-down commitment from your executive team about taking those kind of processes and procedures seriously. In fact, it even takes, from the executive team to define governance and practices and processes around data handling and data management, and I think most companies are doing that with respect to cyber security, for instance, and trying to keep things from leaking out. However, it is the case, though, that it’s difficult to kind of get that focus on managing the asset property, and I think, first is, I think back to Schlumberger, they invested very heavily in safety procedures and processes, and there was zero tolerance around driving practices and that sort of thing, and I think that’s fairly common across a lot of companies across the industry, but, and again, those processes and procedures are fundamentally about keeping the assets safe, whether those are human assets or your physical assets, and I think what’s required is that mindset to say, look, this data is an incredibly valuable asset and it’s worth investing in good governance and process and procedures. And in fact, one of the things that I also say, too, is that around defining that process is that a lot of folks will define a process, and there’s not very good compliance to it, the teeth aren’t behind it, and really process, if you put in a process and you don’t put in compliance, you really haven’t made a process, you’ve just made a suggestion. So that’s also a big part of that is just getting that, kind of that will behind the governance.

[8:53] “What’s your recommendation on selling the importance of data of the chain?”

Trevor Hicks: I think I was kind of touching on that, is just to highlight, and if you can put that into more concrete numbers for your particular business, so much the better. Like I said, I’m using extremely round numbers without really a whole lot of basis in documentation there, but it would be probably a recently simple process within most operators to pull financials from a half a dozen wells and say, "Okay, how much did we really spend on data as we were developing this well?" and extrapolate that across your industry. I think once you get that big number in front of somebody’s eyes, I think that’s going to really be a wake-up call because I don’t think most people think in terms of the fact that just how much data is on their books.

[9:51] “If you’ve seen data from production drilling operations administrative data, what quantifies the million dollar number?”

Trevor Hicks: Okay so, when I made up that million dollar number, some of that data was included, so production data’s not included, that was operational. Really talking about the drilling, really it’s the drilling data because that’s what, it’s the drilling costs that get capitalized into the well asset, so the data that you capture while you’re drilling is typically your wire line logs, and your open logs while you’re logging, the cost of your NWD and LWD services. To the extent that those are broken out from your directional driller and stuff, so maybe those costs might, I say, be bundled in some cases, but your NWD, LWD costs, certainly, the costs on your drilling surveys is, this is just data, you’re buying data. Your core samples, that’s data. Even though, yes, you’re getting a physical core as well, but honestly, it’s data is what you’re spending the money on. Your mud log, I would even go further to say some of your completion activities, if you look at your flow back testing, your drill stem testing, all of these activities are not about physically making whole, or dropping some piece of equipment in the well. They’re about taking measurements, and those measurements are the data, and again, it’s, I’ve talked at ya, I’ve talked to some friends who work as auditors on oil, for oil companies, and that’s where I kind of got the million dollar number from was to say, look, that’s a reasonable number in terms of what they would expect to see in terms of these kinds of data costs on a well that’s being drilled in the United States today. So, it’s an estimate, it’s a big round number, it’s not something that — for any given well or any given company — that I would put a stake in and go to bat for. But again, I think it’s useful in this kind of context here just to kind of give you an idea of the magnitude of the number that you should probably expect as typical.

[12:10] “What are the challenges organizations have in getting access and analyzing the data?”

Trevor Hicks: Gosh, the challenges there are myriad, and in fact, that’s what keeps me in business is the fact that there are a lot of challenges. I think, probably, the biggest challenge and the thing that’s most common that we see across companies is that, is the fact that it’s difficult for people to know, two things: what’s the real answer, what’s the real data? You see spreadsheets all over the place that are cobbled together with data from many different sources that are generally not documented. I worked with a client a few years ago, and won’t name them of course, but the asset team that I was working with had a spreadsheet that they called their Frankenstein spreadsheet, and that’s because they stitched this data together from a lot of different sources, and there was one row per well, and I don’t know, I’m probably going to get the exact number of columns wrong and, of course, it probably would shift over time, but they had, to my recollection, they had about 575 columns on this spreadsheet. And again, the source of that data was not necessarily documented, and in fact, that was an attempt to solve some of these problems. You don’t know where your data’s coming from, you don’t know if you’ve got the best data, have you found all the data, and creating this Frankenstein spreadsheet was actually, in some respects, it was a better data practice than you see in a lot of other places where they just kind of leave you out on your own to go out in the wild and see what you can find. At least in this particular case, they had somebody who was paying attention to data management and was assembling this spreadsheet, and could tell you where the data was coming from for the most part, so yeah, as crazy as it sounds, that actually was a better data practice than you often see in a variety of places. So, getting to a point where you have, typically, what we would call a master data system. And if I’m using a term of art there that’s unfamiliar, I’ll define it very briefly, but a master data system is where you are defining what is your system of record for various different kinds of data, and often, people will start with well header information. That’s kind of the most important thing to start with, your locations, well names, well numbers, that sort of thing. What companies will do there with creating this master data system is defined. Okay, we’ve got this same kind of data that’s sitting across, in some cases, especially when you talk about well header, it’s often sitting in dozens of different systems that have no, that aren’t necessarily linked, that don’t have any connections, so you’re bound to see errors cropping up in the data in some different systems. And so what a master data system allows you to do is to define, okay look, if we’re looking at well name and well location information, maybe WellView or some other kind of software like that, that’s what we want to call our system of record. And what the master data system will allow you to do is to build connectors to all your different operational and transactional systems and bring that together in one place and create what you would call a golden record. And then kind of define, okay look, this is your best source of data, and that way you’ve got a reference point where you can say, now look, this is really, as far as our company goes, this is for giving piece of data, this is what we consider to be our best data. Then you can even go further with that technology and do what we would call a write back, and you can actually have all these systems subscribing to that golden record. That helps to enforce that consistency across the systems, and so everybody’s working with the same data at the same time. So, that’s a really important concept we’ve mastered with data quality, data governance, and in fact, that’s stuff I can go back to. If I can plug Stonebridge a little bit, we actually do have some really sophisticated, outstanding software products called Inner Hub that is a master data system. But whether you use our software or you use, there’s other competitors in the marketplace, that’s the kind of system that I think is absolutely critical if you’re going to address some of these data challenges that oil companies are typically seeing.

[16:48] “Are there technology applications that you find most helpful to creating and maintaining this mastery of the system?”

Trevor Hicks: So again, I kind of made a little commercial for my company’s product. I do want to be clear that we’re not the only product on the marketplace, and there are other folks that you can be successful with, but I think that master data system is critical, and one of the other pieces of technology that’s also critical that is a data quality rules engine, the data quality system that’s gotta check your attributes across different systems for consistency and completeness, and here, actually, want to plug another organization that I’m associated with, which is called The Professional Petroleum Data Management Association, or PPDM. I sit on the Board of Directors of that group and I’ve been on the board since 2011 and served as Chairman of the Board for six years as well. This is a, one of the things that PPDM does is we have developed a... And this is a nonprofit association, so I’m not actually plugging anything for my own personal benefit here, but we’ve defined more than 3,000 data quality rules that are available to member organizations that they can use and apply to their data, which will, again, help to kind of, but within a system, do you have consistency within your data? The simplest go-to example I always use there is to talk about it tubular, so if you’ve got data about a tubular, well you would expect your outside diameter to always be greater than your inside diameter on that tubular.

Now, obviously, most of the rules that we’re looking at are a little more complicated, a little more sophisticated than the obvious errors like that, but that’s the kind of thing that these rules are intended to capture. So that’s another technology piece that I think is critical, and I’ll say one other thing that I think is also critical, it’s less of a technology piece, although there are technologies that support this, but it’s also your business glossary. The reason for this is there are a lot of terms that we use in the oil and gas industry which… And the problem here, this is kind of an interesting problem because everybody thinks they know what they mean, and most of the time it’s fine. I’ll use the example of a SPUD date. Everybody thinks they know what a SPUD date is, and everybody, and it’s, look, most of the time, your definitions are going to come out consistent, but the problem is, is that SPUD date actually isn’t 100% the same for everybody everywhere. If you’re drilling a pilot hole with a spudder rig and you’re only there for a few days and you just did the pilot hole as a least hold type of thing and you’re going to come back and drill the real well in a couple of months, well what’s your SPUD date on that day, on that well? There are other kinds of exceptions that I could bring up as well, but the thing is that, again, if you don’t have a consistent definition of SPUD date, you actually have kind of the worst of all possible worlds here, which is that it works most of the time. So what happens is a lot of oil and gas companies don’t have really good robust definitions around something like SPUD date, and then because it usually works, you don’t have the definitions, you don’t have the process for dealing with the fact that two people may have conflicting definitions for that SPUD date. Like I said, your land administration folks may want to use one SPUD date to make sure that that lease hold is captured. Well, your drilling manager wasn’t used to that SPUD date because they’re being incentivized on making a hole and drilling that well in X number of days, and that initial SPUD date would probably not work very well for that computation. So it’s making sure that you’ve got that business glossary, and so you’re able to kind of broker those different definitions and be able to say that there may be different kinds of definitions for different kinds of SPUD date.

One of the things to also bear in mind when you’re getting in those arguments over how are you going to define something like SPUD date is it’s not necessarily important to win the argument, it really isn’t. What’s important is that if you genuinely have multiple definitions for a term and how you’re going to compute something or calculate it, that you have a genuine business need for, that both of those terms make it into your system somewhere, and that you do, then you do the training and explanation for everybody so they understand what dates mean, or what different terms mean and how they’re intended to be used. I would say, that’s probably the third critical component that I would also reference there.

So, let me go back to the questions. I’ve been monologuing a little bit there, and I do like the sound of my own voice, I’ll admit, so let me see what else we’ve got here. Some people thanking for PPDM. Yes, PPDM is a fantastic organization and I certainly would encourage each of you, if you are working in any kind of management capacity in the oil and gas industry, to take a look at PPDM and to consider your membership. If your company won’t join, you can join as an individual for only $100 a year. And I may even turn back, too, I got a couple other things with PPDM that I may want to plug a little bit as well.

[22:23] “What are some of the major obstacles that companies face when converting from an older or outdated system to a newer technology application or master data system?”

Trevor Hicks: Well, I think the number one obstacle really is, it’s dealing with the legacy data quality issues. For instance, one of the things that we saw with a lot of companies, and we’re still seeing it every now and then, although most of the upgrades have happened, but just to use an example of a company that we work with pretty regularly called Peloton Software, and their product WellView. When they moved from WellView 9 to WellView 10, one of the things that they added into their data model was the ability to capture multi-stage frack data, and that’s not something [that] was in their data model prior to that. So people were putting all kinds of data into comment fields, user-defined fields, that sort of thing. So it’s understanding what kinds of practices were being done where people were doing workarounds or they were creating all kinds of future data headaches for themselves. But, look, and not to try and criticize anybody — you do what you have to do to get your job done, you gotta deliver — but I would say it’s uncovering all those little "gotchas" which are really the most challenging part. If it’s just a straight port from one data model to another, I mean, you could typically build a mapping from one system to the next, depending on the complexity of the system, how much data are you going to be able to move. Look, that’s a few weeks to create that kind of mapping, and migrate the data over, create a few consistency, quality, kind of check some type checks there. The really hard part is knowing where the bodies are buried in the old system, and what are all the shortcuts and crazy things that you all did that were unique to your company, and that have to be accounted for in getting that data migrated over into your new systems. That’s really the, we see that every single time. That’s where the time sync always is, and it’s impossible, and the problem for consultants like us — not that you all have to feel sorry for us — but the problem for a consulting company that’s coming in to try to deal with that is it’s very difficult to estimate in advance the amount of effort and cost that's going to go to into dealing with those kinds of issues. Because oftentimes, our customer doesn’t even, they’re not even fully aware, going in, of some of these challenges that they’re going to have in front of their legacy systems. So that’s where your time and cost overruns typically are coming from. Of course, as the consultant, we blame the bad data. That’s just what we have to do, I guess, but that’s the biggest thing. I think, if you’re able to start off that kind of project with an in-depth assessment and you understand... What kind of data issues and challenges you’ve got in your existing systems, and you really understand it beyond just that intuitive sense of, "Oh, our data sucks," that’s really critical to the success of migrating to a new technology, is doing that kind of assessment.

[15:51] “In your opinion, why does the oil and gas industry seem slow to adopt or invest in data-driven technology, such as business process, data management, data warehouse, and analytics?”

Trevor Hicks: Well, I think that’s a really good question, and I think the why, more than anything, is the fact that it’s easy; it’s easier to get oil and gas executives to invest in physical assets than it is in tangible things. I think most of the folks running the companies, yeah, they’ve worked in the field, they’re geologists, they’re reservoir engineers, production engineers, that sort of thing, and I really think the background, again, I’m not trying to be critical of any particular person or profession or whatnot, but I think you just get in the habit over decades in your career of seeing investment in things driving your company’s success, and maybe not necessarily understanding some of the role, some of the things that can go wrong with it. And the fact that when your data environment’s challenging, as I was talking about with the WellView 9 issue, where you couldn’t natively store frack stage data... Well look, sometimes your folks are doing the best they can with systems that themselves are difficult to keep up to date with how the industry’s changing. So I think it’s a matter of, again, just having folks at the top who are maybe a little more digital native. I think, as we see people that are, what you would term generational change and digital natives are becoming more and more prevalent in leadership roles across the industry, I think those attitudes are going to be a little bit different. But I think the other thing is that, going back to my initial comments about data being an asset, I think it’s often not really framed for executives in that light where they really realize just what is the vast quantity of sums of money that are being spent to acquire data, and just how much of their balance sheet really is data, even if it’s not exclusively recognized as such.

[28:28] “Have you ever had challenges as it relates to poor quality regarding digitalization of well logs, well reports? What’s the impact of that?”

Trevor Hicks: Oh yeah, that’s a substantial challenge. I worked on a project some years ago for a reasonably large operator that was in the process of digitizing their old paper well files. I would say the most difficult... My role on that wasn’t so much the digitization, I was to find the taxonomy for that, for their system, but one of the challenges that we had in scanning was that we were only, this came out of the dark ages, but we were only able to scan to images, we weren’t able to scan to data. And I think the technology that you’re seeing today where you’re able to scan to data, I mean, it’s such a godsend to the industry because, particularly, if you’re dealing with legacy data. But even, I still see tally sheets and stuff that are done by pencil and paper out in the field, so, but being able to scan to data is such a critical thing for the quality of the data. Particularly when you’re looking at the legacy data, being able to execute that successfully is a massive time saver and it’s also, again, the quality is, you can’t compare because any time... One of my other favorite sayings is that the keyboard is the mortal enemy of data quality, so being able to automate that process to where you’re able to scan a table and have software that’s going to accurately record that into appropriate attributes and columns and a data field, that’s really critical to that success.

And yes, a soft plug for Ripcord, which I’m happy to read, and this is actually one of the reasons why I was highlighting that point because I know this is what y’all do [and I] want to be a good guest on your webinar, but I really am being serious that being able to scan the records, being able to extract the data, making the analog content to be analyzed and truly used as an asset. That’s a vital kind of technology, and we are undergoing this digitization of the industry, and that’s something which we hear is going digital. In some sense, it’s easy for me to kind of be a cynic is say, "Well gosh, I remember working on digital oil field projects 20 years ago, so what’s new about being digital today?" But really, I think fundamentally, where we are really changing as an industry is, as I said, I mentioned that we still have had some pencil and paper types, some artifacts that we’re still generating today. I think those are going away. But again, going back to that vast quantity and that vast valuable treasure trove of data that oil and gas companies are still holding, being able to scan those artifacts into usable data is tremendously valuable, and don’t think that that legacy data isn’t valuable. I mean, look at what’s happening in the Permian Basin over the last 10 years. Well look, the Permian Field is 80 years old, and so if you think people aren’t referring to 80, 90 year old well logs, you’re wrong. That kind of data is still being heavily used today and helping to understand the migration of where the oils been flowing, and understanding how the reservoir pressures have been changing over the decades, and the different productive techniques, and the impacts on that, and being able to really optimize recovery as a result. You look at the tremendous productivity increase in Permian Wells since they started drilling the tight wells in the last 10 years or so. A lot of that has to do with, not only just the data that’s being generated today, but it’s being able to make really economic and productive use of that legacy data, and having that kind of capability to scan those legacy files into usable data is tremendously valuable.

[32:59] “Field operations, in my experience, prefer the paper and pen tally method, and they’re very resistant to electronic data catcher. How do we bring them onboard?”

Trevor Hicks: So, I think that’s something which is, well, I think there’s a couple of answers to that questions. So I think first, it takes a top-down commitment. As I was mentioning, part of my experience with Schlumberger, there’s just some things that the executives there wouldn’t tolerate when it came to safety, and I’m grateful for it. I mean, they were fantastic in that respect in my opinion, and so I think part of it is getting that top level commitment to say, "Look, I don’t care if you don’t like it, this is the way it’s going to be, and this is a requirement of your job, and if you don’t want to do it this way, then you’re going to have to find some other place to work." And that’s a difficult thing for executives to get behind, but I think that’s part of it. I think the other part of it, too, is that we, as people who are providers of technology that we’re asking people to use, we’ve gotta make sure that we make it as easy and intuitive to use, and as reliable. I think that’s the real thing is making it as reliable as pen and paper is really key because, everybody, I guess part of it is, you have to make it so that you don’t. So I guess on the one hand I’m saying, look, you gotta have people that are willing to stand up and make you do it the right way, but on the other hand, you want to make it so that doing it the right way is easier than doing it the wrong way. Because when you’re capturing information, here’s the thing in our business, 99% of the time, the person who’s capturing some kind of information is not the person who’s going to ultimately be consuming it later. So their incentive to do it right and get it right is — even as well-intentioned as you might be and as you want to be, and everybody wants to do a good job — the fact of the matter is, the person who’s producing the data, like I said, is typically not the consumer, and so they’re not going to care as much about that consumer as they just want to get their job done. So again, I think this is something which is critical when you think about taxonomies. You think about what kind of forms are you asking people to complete? Are you asking them to type in a bunch of things that you really could find out some other way that you could find out easier in some other format? Are you making it easy for people to do the right thing? And so, that’s a challenge, I would say, for software vendors, but as well as for IT and data staff as well because [with] a lot of cases, that’s what you’re either designing or delivering are these kinds of interfaces and these work processes. So just to kind of, I know I got a little long-winded there, but just to kind of sum that up and say, "Look, yeah, make it easier to do the right thing than the wrong thing," and that’s incoming upon us as software data professionals.

[36:08] "What’s one trend or new technology that you’re most excited about for really changing the industry in the coming years?"

Trevor Hicks: Well, that’s a good question. I think if you’d of asked me that question two or three years ago, I would have said it’s this ubiquity of the analytics capability that we’re seeing and, of course, statistical techniques in software. We’re applying statistical techniques and software, the big data type stuff that’s been, it’s nothing new under the sun, I mean, this is all stuff that was worked out in the ’50s and ’60s, if not earlier in many cases. So that’s the answer I would’ve given you a few years back, but I think everybody’s kind of already grasped that now. I would say, for me, I think it’s Blockchain, which also is kind of a buzzword compliant thing there. But the thing I have to caveat this with is that it’s got nothing to do with Bitcoin or any of these digital currencies or anything of that nature, which I think is actually kind of unfortunate that that’s been the perception that’s come out around the Blockchain technology is these kind of shady, well, I don’t want to insult anyone, but these things that are considered shady by many people, types of digital currencies and people don’t understand what’s it for, and it’s for crooks and drug dealers and all that kind of stuff. So that’s one application of it, but I think really, as I’ve started to kind of get aware of, just within the last six months to a year or so, is the potential for Blockchain to really revolutionize how transactions are conducted across different entities, across different companies. Being able to automate the payment of drilling contractor while they’re making hole, and getting rid of your invoices and a lot of your approval steps, and a lot of the human interaction has to go on there. If you’ve done a good job on your data governance, you define your terms in your business glossary and you agree on what things mean, and what your systems of record are going to be, and all your master data systems. So all the stuff that I’ve talked about prior with data governance, it all applies to big successful Blockchain, but that allows you to get that auditable, verifiable, correct transactions that really streamline payments, which is, you think okay fine, the vendor obviously wants to get paid faster. But it’s also in the best interest of the operator as well because being able to simplify their procedures and make them more accurate and correct is also going to provide a financial benefit to them, even if they’re losing some of the financial benefit at that time, value of money, by paying faster. But anyway, that’s what I see as the thing that I’m most excited about right now.

[39:10] "Is there anything else you’d like [us] to know about PPDM?

Trevor Hicks: Yes, absolutely. One other thing, which I’m very excited about with PPDM, I talked a little bit about the data rules. I think we’re also, we’re best known as a data model as well, which is still industry standard, which is used by lots of different software companies and companies around the world. But the other thing that we’ve invested very heavily in within the last few years is really transforming ourselves into a professional society for data managers. So in addition to the, kind of the technical work products that we’ve created — I mentioned the data model, the rules engine — we’ve done a lot around defining what is a well? What is a completion? Some of these types of things, as critical as they are, I think what I’m also very excited about where we’re going is along the lines of professional development and community building. One of the things that we’ve introduced in the last few years was this certified petroleum data analyst designation. So this is a way of defining a standard of professional expertise and competence and it’s really a challenging certification. I took the certification myself last year because I’ve been pushing all the new associates that I hire into my firm, putting goals on them to, longer term goals, these are multi-year goals to achieve the CPDA designation. And I thought, "Well shoot, I need to put my money where my mouth is and see what this is all about," and so I took the examination last year for the CPDA and fortunately I was able to pass. It would’ve been kind of embarrassing for me, I think, to fail that exam, but really, it was a challenging exam, and I think if I had not put the effort in to study for that, it would’ve, I’m not sure that I could’ve stepped in cold and passed. The reason I bring that up is just to point out that if you see somebody with the CPDA designation, I would say they really know what they’re talking about. I know it’s not something which is a trivial thing to achieve, and so that’s the other thing that I would encourage those of y’all that are listening there is to consider that. Take a look at the CPDA designation, see if it’s right for folks in your firm, for yourself, because it really is a meaningful designation. If you achieve the CPDA, then, like I said, you really know about oil and gas data management on both a broad and a deep level, in my opinion. So that’s the other thing which I’m most excited about.

I also say, I guess one other thing about PPDM, if you’re in Houston, I’ll be speaking at the PPDM Houston Data Expo on April 9th, so I want to encourage you to sign up to attend that conference. I’ll be talking a little bit more about this data as an asset and how that… I’ll be going a little bit more in-depth into some of those topics that I was touching on here, but if you want to see me in person and shake my hand, whatever, I’ll be there at that conference on April 9th in Houston. I think we’re still working on the details, but I fully intend to attend the event that Ripcord is going to be planning as well.

Happy to spend the time, I don’t know if there’s any other, any other big questions that y’all have for me. I’m happy to stick around here for at least a few minutes. I got a client calling in about 10 minutes, but happy to stick round until then.

[43:24] “Advice or knowledge to share for those of us who generate data and sell to clients?”

Trevor Hicks: Well, I would say if you’re selling data, I think the most critical thing there is to make yourself easy to work with. So I would say conforming to your data standards, understand how your customers are going to be consuming that data, and making your data as easy as possible for your clients to consume is key because again, that’s just kind of avoiding the whole translation mix-up. So if you can, if there are PPDMs out, if you can natively provide that data in a PPDM data model, that’s just going to make things so much easier for your clients. That’s just totally across the board there.

[44:19] “Do accountants frown on data on the balance sheet as an asset?”

Trevor Hicks: Absolutely they will frown on that, and I would say for two reasons. So one is, as I’ve already highlighted, the data’s already on the balance sheet in a lot of cases. Now, that doesn’t capture every bit of data. Like I mentioned, I was just kind of talking about the data that you incur while you’re drilling. And I would say it also would apply to a lot of your expiration data, your seismic type of acquisition, which you could probably, I’m not as familiar on that side of things, but I would imagine, a lot of those data costs are being capitalized into kind of a field asset. But perhaps I'm speaking a little bit out of turn there.

But, the other thing is, with putting data on the balance sheet is how do you value it? So, if you put data on the balance sheet, you can’t just say it’s an asset. Do you value it at cost? Well, it’s hard to say, what did you pay for this data? Like, if you’re talking about your production data, what did you pay for it? Well, you kind of acquired it and you paid for sensors, but you didn’t... It’s not something that you had an external cost for, so it’s difficult to push that kind of data onto the balance sheet. If it’s data that you purchased externally, well it’s not really your asset. If it’s public data, if it’s something you got from IHS or Drawing Info, or Geo-Logic, or some of those kinds of companies, that’s not really your asset either. In a lot of cases with seismic data, you’re only licensing that data. You don’t necessarily really even own it, so given all those issues of ownership and such. But really, I think fundamentally, to put a valuation on data, you would have to have some kind of cash flow model for the data, or you’d have to have a market for the data. I don’t think you could come up with a really persuasive or convincing model for each one of those, for either one of those outside of some very narrow cases there. So I would say that you’re probably beating your head up against a brick wall if you want to try and convince accountants to... Your SOX auditor is not going to be happy with you if you try and sneak data as an asset on your balance sheet, let’s put it that way. You’re not going to slide anything by your auditors in that respect, so the fact that it’s capitalized into your other assets, I think that’s, that’s as close as we’re going to get. Like I said, still, it’s typically a substantial number for any operator. If you were to multiply it out, how much of your balance sheet is data? It’s going to be a big number for sure.

[47:22] “How often are CFOs involved in your work in advocating for the value of data?”

Trevor Hicks: I would say it’s pretty typical. I think in most of the cases, it's typical to see them be pretty heavily involved because typically, when we are going to work with an operator, we are dealing with not just the operational data, the technical data, we’re dealing with the production accounting, and division DOIs and all this other kind of data that really touches very hard onto the fans side of things. So besides the fact that oftentimes CFOs, a CIO will report to a CFO, which gets them engaged, kind of by default organizationally when we’re working with an operator, again, the fact that we are putting in systems that had the potential to automate some of the data transactions and data movement across systems is, it’s going to get the CFO’s attention, both from a positive and in some cases. I won’t say negative, but I think if you start talking about pushing data into an accounting system from some other kind of system, which is, in a lot of cases, what we wind up doing, you’ve got to be very careful about ensuring that you’re doing this. And well, you have to be very careful, let’s just put it that way, because if you do something that’s going to cause your books not to balance, or is going to bring you out of SOX compliance or whatever, something like that, then that’s the sort of thing to look. If you’re out of SOX compliance, a CFO, I don’t know how often it actually happens, but they can get led off in handcuffs for that, so they’re going to take very keen interest to anything that’s touching the production accounting systems and that sort of thing. So yeah, I would say most often we are talking to both the CIO and the CFO when we’re engaging work with an operator.

[49:38] “What typically prompts operators to reach out to Stonebridge and start working with you?”

Trevor Hicks: That’s a good question because I don’t know if there’s a typical answer to that. I think [in] a lot of cases, it’s an MNA transaction and they need some help integrating the data from a company that they’ve purchased. That’s probably, if I was to go to a typical way that we get engaged, that’s one of them. But I think a lot of cases, also, probably the most other case is that folks want to engage on a big data analytics kind of capability, or they want to enhance the capabilities that they already have. Oftentimes, they’ll say well, "We’ll just throw Spotfire on top of our databases and that’s going to give us all these magic answers," and it doesn’t take very long for an operator to realize that the state of their data is not giving them good answers, that you’re actually kind of better off not trusting what those kinds of algorithms are going to produce, just given the state of the data quality. And so, a lot of times, the ideal is when someone embarks on that kind of journey, they engage us at the beginning and we can help them to avoid those kinds of pitfalls and make sure that they’re making positive investments all along the way.

But again, what also happens is, that a company will make you start down that road, realize that their data issues are deeper than what they had thought, and then they need some experts to come in and help clean things up, and that’s what we’re able to provide. Yeah, and the MNA side, too, I say it is buyers, but really, I would love to see sellers engage, if not us, engage somebody more often because I think, or put a data manager on the team, because one of the other things that we see is folks that they make commitments about data that they’re going to provide, and their internal systems are not up to the job. It even happens that sellers in an MNA deal are selling physical assets and they promised seismic data or other data, but they don’t even have license to. So they actually have to go out into the marketplace and purchase the data that they promised as part of this transaction. So, I would say that’s one of the things that I would really encourage operators to do is to pay a lot closer attention to, add a data manager to your MNA team, whether you’re buying or selling, because there’s a lot of headache and heartache that they’re going to be able to save you in a lot of cases. Yeah, and understanding the value of the data. Look, if you have the data manager on your purchasing team, and this is kind of advisory service that we offer, so of course I’m plugging in our company, but we offer that kind of advisory service. We’ll put somebody on your MNA team that’s going to help assess the data that the seller is offering to you, and be able to incorporate the quality of that, of the data assets that are going to come with the physical assets and help you understand what kind of problem are you stepping into with integration effort, and how much do you need to budget in time and money. And also, are there ways that we can help minimize that and get you off of those technical service agreements, which are always charged at outrageous rates, so that’s certainly another valuable service that we offer.

And yeah, and the last comment, thank you, super helpful and formal, in fact, I do need to bail here in a minute because, as I’ve mentioned, I’ve got a client call that I’ve got to take, and certainly was happy to speak with everybody, and appreciate all the great questions. I hope you all found it interesting, and I’m sure Ripcord will provide my contact information if y’all want to follow up with additional discussions, I’m happy to, or you can find me on LinkedIn, whatever. Happy to follow up with discussions. Whether you’re looking to buy something from me or not, I’m happy to continue to discuss and help you out however I can. Alright, so thanks y’all, appreciate it.

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