
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.
The in-detail discussion covered questions like:
- Trevorâs background and how he got into the energy industry
- The role technology & data play in the oil and gas industry
- Why data is considered an 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 Trevorâs conversation here:
https://www.youtube.com/watch?v=Wlh2mqs7lWY
Transcript
Trevor Hicks: So thanks, everybody, for joining. Yeah, so Iâll talk, yeah, a little bit about my background. So, how did I get into the energy industry? It was actually, Iâll 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 Iâm 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, and then I wound up staying with Schlumberger for about 18 years, so thatâs what got me into the business, and I did a variety of things at Schlumberger, worked, but mostly software engineering, for the most part, was kinda 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 Iâve been with Stonebridge, I just had my four year anniversary here, Stonebridge Consulting where I lead, Iâm Managing Director here where I lead our, now what we call our smart source group, and thatâs where weâre doing technical support and services, mostly for data management and data services for oil and gas companies.
Okay sure, yeah, so I would say, the easiest way that I can sum up Stonebridge is to say that we do⊠Weâre doing data integrity, and thatâs what weâre really helping our customers achieve, and I donât know how common that language is, data integrity, and I use it kinda deliberately. Sounds like weâre still getting comments on echo, sorry. So, hopefully itâs not on my end there, but data integrity, what Iâm 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, thatâs what weâre 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, and yeah, so thatâs really kinda the fundamental bottom line of what weâre all about there, and just to even kinda touch back on the comment I was making about data being a strategic asset, thatâs 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, youâre 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 youâre 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 kinda role, but however, Iâm 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. Itâs not explicitly separated out as a separate line item. Iâve 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, thereâs 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. Youâre spending a lot of money on data, and that money is typically capitalized into the well, and just to throw out round numbers, but itâs typically, for a well thatâs shield in North America today, youâre generally gonna 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 youâre 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, thatâs $20 billion that you have put on your books thatâs data. Now, of course, that may be depleted and advertised over a course, so maybe as a company operating 20,000 wells, maybe youâve only got 10 billion left of data on your books, but the fact of the matter is, is that data is an asset, and itâs on your books, and itâs gigantic numbers, and so it needs to be, itâs worthy of investment. So, just to read the question here that Iâm seeing, so whatâs one of the most challenging aspects of creating a robust data practice and process? And, I would say, probably, thereâs a couple of challenges here that I would talk about, but I would say the biggest one is that itâs just simply that the vast majority of people donât see data as an asset that they wanna follow robust procedures and processes around. Itâs 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 itâs difficult to kinda 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 thatâs 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 whatâs required is that mindset to say, look, these data is an incredibly valuable asset, and itâs 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 thereâs not very good compliance to it, the teeth arenât behind it, and really process, if you put in a process and you donât put in compliance, you really havenât made a process. Youâve just made a suggestion, so thatâs also a big part of that is just getting that, kinda that will behind the governance. The next question is, couple of questions there, so, âWhatâs your recommendation on selling âthe importance of data of the chain?â I think I was kinda 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, Iâm 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, and I think once you get that big number in front of somebodyâs eyes, I think thatâs gonna really be a wake up call âcause I donât think most people think in terms of the fact that just how much data is on their books. So, âIf youâve seen data from production drilling âoperations administrative data, âwhat quantifies the million dollar number?â Okay so, when I made up that million dollar number, some of that data was included, so production dataâs not included, that was operational. Really talking about the drilling, really itâs the drilling data because thatâs what, itâs the drilling costs that get capitalized into the well asset, so the data that you capture while youâre drilling is typically your wire line logs, and your open logs while youâre 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, youâre buying data. Your core samples, thatâs data. Even though, yes, youâre getting a physical core as well, but honestly itâs data is what youâre 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. Theyâre about taking measurements, and those measurements are the data, and again, itâs, Iâve talked at ya, Iâve talked to some friends who work as auditors on oil, for oil companies, and thatâs where I kinda got the million dollar number from was to say, look, thatâs a reasonable number in terms of what they would expect to see in terms of these kinds of data costs on a well thatâs being drilled in the United States today. So, itâs an estimate, itâs a big round number, itâs 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 itâs useful in this kinda context here just to kinda give you an idea of the magnitude of the number that you should probably expect as typical. So, âWhat are the challenges organizations have âin getting access and analyzing the data?â Gosh, the challenges there are myriad, and in fact, thatâs what keeps me in business is the fact that there are a lot of challenges. I think, probably, the biggest challenge and the thing thatâs most common that we see across companies is that, is the fact that itâs difficult for people to know, two things, whatâs the real answer, whatâs 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 wonât name them of course, but the asset team that I was working with had a spreadsheet that they called their Frankenstein spreadsheet, and thatâs because they stitched this data together from a lot of different sources, and there was one row per well, and I donât know, Iâm probably gonna 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 donât know where your dataâs coming from, you donât know if youâve 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 Iâm using a term of art there thatâs unfamiliar, Iâll 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. Thatâs kinda the most important thing to start with, you locations, well names, well numbers, that sort of thing, and what companies will do there with creating this master data system is defined. Okay, weâve got this same kind of data thatâs sitting across, in some cases, especially when you talk about well header, itâs often sitting in dozens of different systems that have no, that arenât necessarily linked, that donât have any connections, and so, youâre 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 weâre looking at well name and well location information, maybe WellView or some other kind of software like that, thatâs what we wanna 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 kinda define, okay look, this is your best source of data, and that way youâve 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, and then you can even go further with that technology and doing what we would call a write back, and you can actually have all these systems subscribing to that golden record, and that helps to enforce that consistency across the systems, and so everybodyâs working with the same data at the same time. So, thatâs a really important concept weâve mastered with data quality, data governance, and in fact, thatâs 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, thereâs other competitors in the marketplace, thatâs the kind of system that I think is absolutely critical if youâre gonna address some of these data challenges that oil companies are typically seeing. So, what sort of technology, like, oh okay, so I kinda, I answered the question before I read it, but, âAre there technology applications âthat I find most helpful to creating and maintaining âthis mastery of the system?â So again, I kinda made a little commercial for my companyâs product. I do wanna be clear that weâre 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 thatâs also critical that is a data quality rules engine, the data quality system thatâs gotta check your attributes across different systems for consistency and completeness, and here, actually, wanna plug another organization that Iâm associated with, which is called The Professional Petroleum Data Management Association, or PPDM, and I sit on the Board of Directors of that group, but Iâve been on the board since 2011 and served as Chairman of the Board for six years as well, and this is a, one of the things that PPDM does is we have developed a, and this is a nonprofit association, so Iâm not actually plugging anything for my own personal benefit here, but weâve 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 youâve 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 weâre looking at are a little more complicated, a little more sophisticated than the obvious errors like that, but thatâs the kind of thing that these rules are intended to capture, so thatâs another technology piece that I think is critical, and Iâll say one other thing that I think is also critical, itâs less of a technology piece, although there are technologies that support this, but itâs also your business glossary, and 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 itâs fine, and Iâll use the example of a SPUD date. Everybody thinks they know what a SPUD date is, and everybody, and itâs, look, most of the time, your definitions are gonna come out consistent, but the problem is, is that SPUD date actually isnât 100% the same for everybody everywhere. If youâre drilling a pilot hole with a spudder rig and youâre only there for a few days and you just did the pilot hole as a least hold type of thing and youâre gonna come back and drill the real well in a couple months, well whatâs 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 is that, again, if you donât have a consistent definition of SPUD date, you actually have kinda the worst of all possible worlds here, which is that it works most of the time, and so what happens is a lot of oil and gas companies, they donât have really good robust definitions around something like SPUD date, and then because it usually works, you donât have the definitions, you donât 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 wanna use one SPUD date to make sure that that lease hold is captured. Well, your drilling manager wasnât used to that SPUD date because theyâre 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 itâs making sure that youâve got that business glossary, and so youâre able to kinda 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 youâre getting in those arguments over how are you gonna define something like SPUD date is itâs not necessarily important to win the argument, it really isnât, whatâs important is that if you genuinely have multiple definitions for a term and how youâre gonna 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 theyâre intended to be used. I would say, thatâs probably the third critical component that I would also reference there. So, let me go back to the questions. Iâve been monologuing a little bit there, and I do like the sound of my own voice, Iâll admit, so let me see what else weâve got here. Some people thanking for PPDM, yes. PPDM is a fantastic organization, and I certainly would encourage each of you all 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 wonât join, you can join as an individual for only 100 bucks a year, so I definitely, and they may even turn back, too. I got a couple other things with PPDM that I may wanna plug a little bit as well. So, the next question, âWhat are some of the major obstacles âthat companies face when converting âfrom an older or outdated system to a newer âtechnology application or master data system?â Ugh, well, I think the number one obstacle really is, itâs dealing with the legacy data quality issues. For instance, one of the things that we saw with a lot of companies, and weâre 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 thatâs not something which was in their data model prior to that, and so people were putting all kinds of data into comment fields, user defined fields, that sort of thing, and so itâs 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 itâs uncovering all those little gotchas, which are really the most challenging part. If itâs 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 gonna be able to move, look, thatâs a few weeks to create that kind of mapping, and migrate the data over, create a few consistency, quality, kinda check some type checks there. No, the really hard part is, what do you say? 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. Thatâs really the, we see that every single time. Thatâs where the time sync always is, and itâs impossible, and the problem for consultants like us, and not that you all have to feel sorry for us, but the problem for a consulting company thatâs coming in to try to deal with that is itâs very difficult to estimate in advance the amount of effort and cost that itâs gonna go to to dealing with those kinds of issues because oftentimes, our customer doesnât even, theyâre not even fully aware, going in, of some of these challenges that theyâre gonna have in front of their legacy systems, and so thatâs where your time and cost overruns typically are coming from. Of course, as the consultant, we blame the bad date. Thatâs just what we have to do, I guess, but thatâs the biggest thing, and I think, if youâre able to start off that kind of project with an in-depth assessment and you understand what youâre dataâs, what kind of data issues and challenges youâve got in your existing systems, and you really understand it beyond just that intuitive sense of oh, our data sucks, thatâs really critical to the success of, migrating to a new technology is doing that kind of assessment. Alright, so next question from Sarah Hood, âIn your opinion, why does the oil and gas industry âseem slow to adopt or invest in data-driven technology, âsuch as business process, data management, âdata warehouse and analytics?â Well, I think thatâs a really good question, and I think,I think the why, more than anything, is the fact that itâs easy, itâs 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, theyâve worked in the field, theyâre geologists, theyâre reservoir engineers, production engineers, that sort of thing, and I really think the background, again, Iâm 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 companyâs 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 environmentâs challenging, as I was talking about with the WellView 9 issue where you couldnât 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 industryâs changing, and so I think itâs a matter of, again, just having folks at the top who are maybe a little more digital native, so 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 gonna be a little bit different, but I think the other thing is, too, is that, going back to my initial comments about data being an asset, I think itâs 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 itâs not exclusively recognized as such. So, question from Chad, âHave you ever had challenges âas it relates to poor quality regarding digitalization âof well logs, well reports, whatâs the impact of that?â Oh yeah, thatâs 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, and I would say, the most difficult, my role on that wasnât 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 werenât able to scan to data, and I think the technology that youâre seeing today where youâre able to scan to data, I mean, itâs such a godsend to the industry because, particularly, if youâre 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 because, particularly, when youâre looking at the legacy data, being able to execute that successfully is a massive time savior, and itâs also, again, the quality is, you canât compare because, anytime, one of my other favorite sayings is that the keyboard is the mortal enemy of data quality, and so being able to automate that process to where youâre able to scan a table and have software thatâs gonna accurately record that into appropriate attributes and columns and a data field, thatâs really critical, I think, to that success. And yes, a soft plug for Ripcord, which Iâm happy to read, and this is actually one of the reasons why I was highlighting that point âcause I know this is what yâall do. Wanna be a good guest on your webinar, but I really am, Iâm 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. Thatâs a vital kind of technology, and we are undergoing this digitization of the industry, and thatâs something which we hear is going digital. In some sense, itâs easy for me to kinda be a cynic is say, well gosh, I remember working on digital oil field projects 20 years ago, and so whatâs 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 weâre still generating today. I think those are going away, but again, going back to, again, 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 donât think that that legacy data isnât valuable. I mean, look at whatâs 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 arenât referring to 80, 90 year old well logs, youâre wrong. That kinda data is still being heavily used today and helping to understand the migration of where the oilâs 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 thatâs being generated today, but itâs 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. Okay, so another great question form Sarah Hood, âField operations, in my experience, âprefers the paper and pen tally method,â yep, âand theyâre very resistant to electronic data catcher. âHow do we bring them onboard?â So, I think thatâs something which is, well, I think thereâs a couple of answers to that questions, so I think first is, it takes a top-down commitment. As I was mentioning, part of my experience with Schlumberger, thereâs just some things that the executives there wouldnât tolerate when it came to safety, and Iâm 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 donât care if you donât like it, this is the way itâs gonna be, and this is a requirement of your job, and if you donât wanna do it this way, then youâre gonna have to find some other place to work, and thatâs a difficult thing for executives to get behind, but I think thatâs part of it, but I think the other part of it, too, is that we, as people who are providers, the technology that weâre asking people to use, weâve gotta make sure that, that we make it as easy and intuitive to use, and as reliable. I think thatâs 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 donât, so I guess on the one hand Iâm 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 wanna make it so that doing it the right way is easier than doing it the wrong way. âCause when youâre capturing information, hereâs the thing in our business, 99% of the time, the person whoâs capturing some kind of information is not the person whoâs gonna ultimately be consuming it later, and so their incentive to do it right and get it right is, even as well intentioned as you might be and as you wanna be, and everybody wants to do a good job, the fact of the matter is, the person whoâs producing the data, like I said, is typically not the consumer, and so theyâre not gonna care as much about that consumer as, they just wanna get their job done, and 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, thatâs a challenge, I would say, for software vendors, but as well as for IT and data staff as well âcause a lot of cases, thatâs what youâre either designing or delivering are these kinds of interfaces and these work processes, so just to kinda, I know I got a little long winded there, but just to kinda sum that up and say, look, yeah, make it easier to do the right thing than the wrong thing, and thatâs in coming upon us as software data professionals. So, shifting gears a little, whatâs one trend or new technology that youâre most excited about for really changing the industry in the coming years? Well, thatâs a good question. I think if youâd of asked me that question two or three years ago, I woulda said itâs this ubiquity of the analytics capability that weâre seeing, and of course, statistical techniques in software, weâre applying statistical techniques and software, the big data type stuff thatâs been, itâs nothing new under the sun, I mean, this is all stuff that was worked out in the â50s and â60s, if not earlier in many cases, so thatâs the answer I wouldâve given you a few years back, but I think everybodyâs kind of already grasped that now. I would say, for me, I think itâs Blockchain, which also is kind of a buzz word compliant thing there, but the thing I have to caveat this with is that itâs 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 thatâs been the perception thatâs come out around the Blockchain technology is these kind of shady, well I donât wanna insult anyone, but these things that are considered shady by many people, types of digital currencies and people donât understand whatâs it for, and itâs for crooks and drug dealers and all that kind of stuff, so thatâs one application of it, but I think really, as Iâve 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 theyâre 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 youâve 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 gonna be, and all your master data systems, so all the stuff that Iâve 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 itâs 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 gonna provide a financial benefit to them, even if theyâre losing some of the financial benefit at that time, value of money, by paying faster, but anyway, thatâs what I see as the thing that Iâm most excited about right now. So, is there anything else youâd like to know about PPDM? Yes, absolutely. One other thing which Iâm very excited about with PPDM, I talked a little bit about the data rules. I think weâre also, weâre 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 weâve invested very heavily in within the last few years is really transforming ourselves into a professional society for data managers, and so, so in addition to the, kind of, the technical work products that weâve created, I mentioned the data model, the rules engine, weâve 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 Iâm also very excited about where weâre going is along the lines of professional development and community building, and one of the things that weâve introduced in the last few years was this certified petroleum data analyst designation, and so this is a way of defining a standard of professional expertise and competence and itâs really a challenging certification. I took the certification myself last year because Iâve 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 wouldâve 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 wouldâve, Iâm not sure that I couldâve stepped in cold and passed, and 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 theyâre talking about because I know itâs not something which is a trivial thing to achieve, and so thatâs the other thing that I would encourage those of yâall that are listening there is to consider that. Take a look at the CPDA designation, see if itâs 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, thatâs the other thing which Iâm most excited about, and I also say, I guess one other thing about PPDM, if youâre in Houston, Iâll be speaking at the PPDM Houston Data Expo on April 9th, so I wanna encourage you to sign up to attend that conference, and Iâll be talking a little bit more about this data as an asset and how that⊠Iâll be going in a little bit more depth into some of those topics that I was touching on here, but if you wanna see me in person and shake my hand, whatever, Iâll be there at that conference on April 9th in Houston. Weâre gonna get links to CPDA, thatâs fantastic. Invite out to an event for data innovators in the industry that weâre hosting next week, yeah thatâs correct, yep, so I think weâre still working on the details, but I fully intend to attend the event that Ripcord is gonna be planning as well. And yeah, seeing some thanks, youâre welcome. Happy to spend the time, I donât know if thereâs any other, any other big questions that yâall have for me. Iâm 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. Okay, so, okay another question. âAdvice or knowledge to share for those of us âwho generate data and sell to clients?â Well, I would say, itâs, yeah, if youâre selling data, I think the most critical thing there is to make yourself easy to work with, and so I would say conforming to your data standards, understand how your customers are gonna be consuming that data, and making your data as easy to consume for your clients as possible is key because again, thatâs 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, thatâs just gonna make things so much easier for your clients, thatâs just totally across the board there. Yeah, so next question there, âDo accountants frown on data âon the balance sheet as an asset?â Absolutely, they will frown on that, and I would say for two reasons. So one is, as Iâve already highlighted, look, the dataâs already on the balance sheet in a lot of cases. Now, that doesnât capture every bit of data. Like I mentioned, I was just kinda talking about the data that you incur while youâre 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, Iâm 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 Iâm, perhaps, 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 canât just say itâs an asset. Do you value it at cost? Well, itâs hard to say, what did you pay for this data? Like, if youâre talking about your production data. What did you pay for it? Well, you kind of acquired it and you paid for sensors, but you didnât, itâs not something that you had an external cost for, so itâs difficult to push that kinda data onto the balance sheet. If itâs data that you purchased externally, well itâs not really your asset. If itâs public data, if itâs something you got from IHS or Drawing Info, or Geo-Logic, or some of those kinds of companies thatâs not really your asset either. In a lot of cases with seismic data, youâre only licensing that data. You donât 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 youâd have to have a market for the data, and I donât 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 youâre probably beating your head up against a brick wall if you wanna try and convince accountants to, your SOX auditor is gonna, is not gonna be happy with you if you try and sneak data as an asset on your balance sheet, letâs put it that way. Youâre not gonna slide anything by your auditors in that respect. So yeah, so the fact that itâs capitalized into your other assets, I think thatâs, thatâs as close as weâre gonna get. Like I said, still, itâs typically a substantial number for any operator, if you were to multiply it out, how much of your balance sheet is data. Itâs gonna be a big number for sure. âHow often are CFOs involved in your work âin advocating for the value of data?â I would say itâs pretty typical. I think in most of the cases when, typical to see them with, to 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, weâre dealing with the production accounting, and division DOIs and all this other kinda 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 weâre 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, itâs gonna get the CFOâs attention, both from a positive and in some cases, I wonât say negative, but I think if you start talking about pushing data into an accounting system from some other kind of system, which is what, in a lot of cases, what we wind up doing, youâve gotta be very careful about ensuring that youâre doing this, and well, you have to be very careful, letâs just put it that way, because if you do something thatâs gonna cause your books not to balance, or is gonna bring you out of SOX compliance or whatever, something like that, then thatâs the sort of thing to look. If youâre out of SOX compliance, a CFO, I donât know how often it actually happens, but they can get led off in handcuffs for that, so theyâre gonna take very keen interest to anything thatâs 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 weâre engaging work with an operator. âSo, what typically prompts operators to reach out âto Stonebridge and start working with you?â Thatâs a good question âcause thereâs a, I donât know if thereâs a typical answer to that. I think a lot of cases, itâs an MNA transaction, and they need some help integrating the data from a company that theyâve purchased. Thatâs probably, if I was to go to a typical way that we get engaged, thatâs one of them, but I think a lot of cases, also, probably the most other case is that folks wanna engage on a big data analytics kinda capability, or they wanna enhance the capabilities that they already have, and oftentimes, theyâll say well, weâll just throw Spotfire on top of our databases, and thatâs gonna give us all these magic answers, and it doesnât take very long for an operator to realize that the state of their data is not giving them good answers, that youâre actually kinda better off not trusting what those kinds of algorithms are gonna 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 theyâre making positive investments all along the way, but again, what also happens is, again, 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 thatâs what weâre 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, âcause one of the other things that we see is folks that, they make commitments about data that theyâre gonna provide, and their internal systems are not up to the job, and itâs even happens that sellers in an MNA deal are selling physical assets and they promised seismic data or other data, but they donât even have license to, and so they actually have to go out into the marketplace and purchase the data that they promised as part of this transaction, and so, I would say thatâs 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 youâre buying or selling, because thereâs a lot of headache and heartache that theyâre gonna 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 Iâm plugging in our company, but we offer that kind of advisory service. Weâll put somebody on your MNA team thatâs gonna 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 gonna 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 thatâs another, 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 Iâve mentioned, Iâve got a client call that Iâve 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 Iâm sure Ripcord will provide my contact information if yâall wanna follow up with additional discussions, Iâm happy to, or you can find me on LinkedIn, whatever. Happy to follow up with discussions. Whether youâre looking to buy something from me or not, Iâm happy to continue to discuss and help you out however I can. Alright, so thanks yâall, appreciate it.