Petro.ai, experts in machine learning and AI for geotechnical data science and providers of the industry-leading integrated analytics platform, announces a new offering enabling modern analytics from legacy data lakes using integrated data ingestion pipelines on Amazon Web Services (AWS). Petro.ai on AWS leverages the scalability and flexibility of AWS infrastructure to accelerate discovery of oil and gas insights through the fusion of operational and subsurface data.
“While our industry has done a great job collecting and storing data in internal systems, building new value with this data has been incredibly difficult.”
Dr. Troy Ruths, Founder and CEO of Petro.ai
“The next wave of optimization requires two things: lower costs and enhanced outcomes. Petro.ai on AWS delivers immediate savings versus legacy systems while enabling more agility and better insights through the fusion of subsurface and operational data,” explained Dr. Troy Ruths, Founder and CEO of Petro.ai.
The automated integration of Petro.ai with Amazon S3, AWS Lambda, and AWS VPC minimizes time spent loading, normalizing, and managing data while providing the elastic compute power required for modern analytics at enterprise scale.
Petro.ai’s proprietary technology incorporates AI and machine learning to facilitate the amalgamation of over 50 oil and gas data types, delivering integrated analytics and cross-disciplinary collaboration.
Petro.ai supports collaborative analytics that span the entire upstream value chain—drilling, completions, and production. Quickly operationalize digital strategies with pre-built modules. Mitigate risk by deploying software workflows being used internationally across multiple basins and use cases. Supercharge internal teams with an open system that allows for easy data access and custom development.
Petro.ai is quickly becoming an industry standard with marquee customers across the globe including Diamondback Energy (Nasdaq: FANG) and Noble Energy (Nasdaq: NBL).
Highlights from the Invest with James West podcast with Dr. Troy Ruths, Founder and CEO of Petro.ai, and Dr. Mark Zoback, Stanford University Professor of Geophysics, Director of the Stanford Natural Gas Initiative, and Technical Advisor at Petro.ai
James West: What is geomechanics and why does it apply to the development of unconventional reservoirs?
Mark Zoback: To me, it’s the integration of the physical properties of the geologic formation, the fractures, and the other attributes that they have in a geomechanical sense. But, most importantly, it’s the forces that are acting in the rocks. That’s at the core of development of unconventional resources, because the key technology is horizontal drilling and multistage hydraulic fracturing.
Hydraulic fractures follow the stresses in the rock. In other words, once you know what the forces are, you can be predictive about what the hydraulic fractures would like to do.
JW: At this stage, how is machine learning and AI being applied?
Troy Ruths: In a previous podcast, I talked about AI being at the bottom of the pyramid. In this respect, what we’re trying to do is make it easier for the end user to get access to data types, run the interpretation, and then collaborate and predict on those within the context of geomechanics.
The other big area is fingerprinting patterns. Let’s say you have a productivity pattern or that one interval is more productive than the other. If we can tie that to a key variable going through a nice technical analysis from the perspective of geomechanics, then you can go look for that fingerprint elsewhere.
We’ve had a lot of success doing that and I think that’s two big places where AI and Machine Learning have really helped act as a catalyst for a lot of these principles that Mark has put together in the book that he just put out.
MZ: Even after a couple of hundred thousand wells, which means a couple of millions of hydraulic fractures, we still have recovery factors of only 25% for gas and less than 10% for oil. So, we’re leaving more than 90% of the oil behind.
We can take these new ideas and then using the tools of Petro.ai, test those ideas against existing data and frame the problem in a whole new way to gain understanding. It’s one thing to have an idea, but it’s another thing to know whether that idea is going to work before you try to implement that idea at scale.
That combination of bringing new ideas and then confirming the applicability of those new ideas in an area of particular interest to a particular company—that’s where we’re going to really leverage these new ideas. We can figure out what’s important and what’s not and then try to attack this recovery factor problem, because we haven’t solved that through brute force and trial and error.
All of these questions surround the idea of vertical hydraulic fracture growth. We think about hydraulic fractures growing horizontally away from the horizontal well, but they also grow vertically. That’s controlled by the forces in rock and how you do the hydraulic fracturing. Well, if hydraulic fractures are growing up, they’re not growing out. The issues of well spacing, infill drilling, and stacked pay are all linked in a three-dimensional way to a condition presented to you by the Earth. You can’t change that. But, if you can characterize it and link it to the completion process, you have a shot at optimizing.
JW: If we defined the 2017 to 2019 era in US onshore as what my colleague Steve Richardson eloquently pointed out as “the megapad misstep era.” What would you say were the reasons some of the companies erred and how they corrected course since then?
TR: There’s substantial interaction between parent wells and wells that are landed in different zones. So, the assumption that you can take a type curve and multiply it by well counts has been proven not to be a viable way to understand how you’re exploiting that cube.
When you step into that 3D problem, you need to take into account the vertical propagation of fractures and the interactions of wells that are brought online at the same time versus brought online at different times.
All of that is explainable through these concepts that Mark is talking about and is something that you can measure and actually infer ahead of time.
As we step into this next era of megapads, people are realizing that they just can’t develop intervals. They need to develop the entire pad together.
JW:So what inning do you think the North American unconventional oil and gas industry is in now in terms of drilling and completion efficiencies?
MZ: I’d say we’re in the sixth or seventh inning with respect to drilling efficiencies. It’s remarkable what’s being done out there in terms of drilling and completions efficiency, but I think we’re in the second inning when it comes to understanding about what should be done. We know how to do it. We know how to do it efficiently, but I don’t think we really understand. We have a lot of data under our belt now, but there are literally millions of wells that could be used to exploit unconventional hydrocarbons in the Lower 48. Before taking advantage of any of these opportunities, we have to start incorporating a better understanding of what to do regardless of how efficiently it could be done.
JW: How do you and the geomechanics team bring it all together at Petro.ai?
TR: You know James, we’re trying to reinvent the workflow and I think we’ve talked about this in a lot of different ways. When I put the Petro.ai team together with Mark, I wanted to provide a team and vision that our clients could get behind and really help us reinvent the workflow. It’s going to be working with our clients to understand their challenges and their assets, but also bringing a lot of these new concepts to the table.
I really think that we’re one of the few players in the space that can bring this level of insightfulness and technical expertise, while at the same time, leveraging those millions of data points that a company is sitting on.
Petro.ai expands its Technical Advisory Board with the addition of Dr. D. Nathan Meehan, President of CMG Petroleum Consulting and the 2016 President of the Society of Petroleum Engineers.
“Throughout his career, Nathan has become known as an extraordinary engineer and an even better leader,” explains Dr. Troy Ruths, Founder and CEO of Petro.ai. “We are thrilled to partner with such an outstanding individual. It is our aim to infuse each Petro.ai workflow with the care and expertise that Nathan has delivered to the industry.”
Previously, Dr. Meehan was President of Gaffney, Cline & Associates; Senior Executive Advisor for Baker Hughes; Vice President of Engineering for Occidental Petroleum; and General Manager, Exploration & Production Services for Union Pacific Resources. Dr. Meehan holds a BSc in Physics from the Georgia Institute of Technology, an MSc in Petroleum Engineering from the University of Oklahoma, and a PhD in Petroleum Engineering from Stanford University. He is an SPE Distinguished Member and the recipient of the SPE Lester C. Uren Award for Distinguished Achievement in Petroleum Engineering, the Degolyer Distinguished Service Medal, the SPE Public Service Award, and has been named an Honorary Member of the SPE. Dr. Meehan has also received the World Oil Lifetime Achievement Award and the Petroleum Economist Legacy Award. He has served on the National Petroleum Council and is a long-standing member of the Interstate Oil and Gas Compact Commission.
“I am very proud to be joining the Petro.ai team as the Senior Advisor for Reserves and Emissions,” reports Dr. Meehan. “I’ve been fortunate to work with the world’s largest energy companies through reserves reporting processes and I also share Troy’s passion for delivering tools to the industry that will foster reductions in emissions, and ultimately, a transition to clean burning energy.”
With this addition, the Petro.ai Technical Advisory Board includes global experts in both geomechanics and reservoir engineering.
“I’m absolutely delighted that Nathan is joining Petro.ai. I’ve known Nathan since he was a PhD student at Stanford several decades ago. More importantly, I have had the pleasure to connect with him a number of times since then: in his leadership roles with both operating and service companies, his activities as a private consultant, and his professional service as President of the SPE,” explained Dr. Mark Zoback, Petro.ai Senior Advisor in Geomechanics. “I can think of no one who could bring a wider range of experience and expertise to Petro.ai and help us to better serve our current and future clients through cutting-edge software and services.”
Richard Gaut: Geoff, thanks for joining us on our Passion for Change interview series! You’ve written a really influential book, Bits, Bytes, and Barrels: The Digital Transformation of Oil and Gas, that our customers have been talking about, that’s getting a lot of publicity, and that is part of the zeitgeist now. It is so great to have you on as a guest for our very first video interview.
Geoffrey Cann: I very much appreciate the invite. Thank you so much.
RG: Across the oil and gas complex, what do you see as the technology with the largest opportunity for a digital solution to make an impact?
GC: The digital solution which offers the greatest potential today – by far – is the world of artificial intelligence and machine learning. The oil and gas industry is blessed with enormous deposits of data assets, which have accumulated over the years and will continue to accumulate.
Unfortunately, this data sits in places where the industry has either forgotten it exists, doesn’t understand its value, or dismisses it out of hand as being “dirty data”. I believe that the fastest way to value in the world of digital isn’t necessarily to generate more data, though that’s very easy to do. Instead, it is harvesting the data assets that you’ve already got. If you wanted a shot that you could pull today that would yield a meaningful outcome, it would be to apply artificial intelligence or machine learning somewhere in the business.
RG: Where do you see folks on this transition from managing their own IT systems versus finding service providers in the cloud? What’s the industry doing to manage these huge data volumes?
GC: Well, the first challenge that the industry has to come to grips with is, as you point out, is the enormous growth in the volume of data out there. There’s the first problem. How do you get your arms around all of this data and, if you’re an oil company, can you afford to stand up your own incremental infrastructure year-on-year, just to store all of this data?
That brings with it all kinds of other interesting questions: Where do you locate your data center? How do you handle backups and recoveries? How do you build in your redundancies? What about your redundant power supplies? How are you going to even fuel it, since so much energy goes into running a data center.
The leading oil and gas companies have concluded that the right answer is to shift off of this “roll your own” infrastructure and to leverage the capabilities afforded by the large cloud computing companies. Migrating out of your proprietary data center and onto cloud infrastructure. That, in turn, opens up all of the new business model possibilities that we’ve seen from other industries that have migrated ahead of oil and gas. That’s step one.
Step two, though, has to be investing in the talent and the capability to take the data that you’re sitting on and make sense of it. That’s where the need to bring onboard data scientists and other data specializations comes from; so that you can begin to extract the value promise from all of that data.
RG: There’s a really great phrase in the book that I learned and I hadn’t heard this one before, Geoff. It’s “wetware.” Can you tell me what “wetware” is?
GC: Well, if software is what’s on your computer and hardware is an iPhone, then wetware is you and me. We are our own compute capacity. It’s just up here in your brain where things are wet! So wetware refers to the humans that are working with both hardware and software. For the time being, we are going to be in a wetware world. We’re going to have lots of people managing and administering our facilities and our assets.
RG: The fact the matter is that humans just weren’t designed for it. Wetware just is not capable of digesting, ingesting, or contextualizing these incredible volumes of data that we’re now privy to.
GC: Quite right. As humans, we learn at a certain pace and so we are at a significant disadvantage when you think about the pace of digital change in how fast machines are able to learn.
RG: It feels like there’s some top-down initiatives at the board level to undertake some of these transformation initiatives, but when the rubber meets the road inside the company things are more challenging. What have been that the successful strategies that companies have undertaken to take a tangible first step after that memo comes down from the board?
GC: The short and quick path forward that most companies take is that they will create some kind of digital task force, innovation council, or digital Center of Excellence somewhere in their organization. Then it becomes this group’s job to move digital initiatives forward. This can work, but in my view it needs four essential ingredients for success. One, it needs organization. Two, it needs to have resources so it can actually do things: money and budget to spend. Number three is that it needs to have ways of working. Fourth is that team needs to have real hard measures of success. If you don’t have those four ingredients, your task force is not going to be successful.
The second ingredient you have to have in place is it’s got to be implemented in a business unit. To get to a successful outcome, the business unit itself has to be ready to embrace this digital change. That means changing the performance metrics for the manager in that unit. Then, you need to train the workforce in that unit so that they know that what’s coming at them is an expectation of the company. If the workforce doesn’t embrace these changes and drive digital growth, then the whole unit will suffer.
RG: You make a really interesting argument about what competes for capital in an up market versus what competes for capital in a down Market. Would love to hear your specific thoughts about that.
GC: We have some real challenges in the context of how to drive this change agenda forward. You can go from midstream companies with a viable digital game plans underway, to upstream companies, and even to refineries. The place in the value chain doesn’t matter; the digital agenda should continue to run regardless of where we are in the cycle.
RG: Another thing that I was really interested in was IT and OT and their roles in digital transformation. If you could just walk us through how they end up managing these projects.
GC: Sure. Most commercial businesses will have an Information Technology (IT) department and within it you’ll find the team that makes sure the email system works correctly, the ERP systems are supported properly, and that the infrastructure is in place to do things like Zoom calls. They let you bring your tablet to work and gives you single sign-on and all that sort of stuff. IT’s specialization is integrating these multiple technologies together and making them appear seamless. That’s one of their secret sauces. The are generally very good at patching, keeping complex systems going, and securing and providing a whole range of services responding to employee needs.
OT is what we call Operational Technology. OT is what you find in a plant as it runs 24/7. It never shuts down. It is responsible for keeping physical infrastructure running within certain set points. OT can go by the name SCADA, which stands for Supervisory Control and Data Acquisition. Here, you’re supervising an asset and you’re capturing the data from that asset as it’s running. Historically, IT and OT have been two separate solitudes.
The problem, though, is that in a digital world, they start to come together. If you look at the oil and gas industries from one end of the spectrum to the other (upstream, midstream, downstream, retail, trading, or capital projects), you’ll find slight and distinct differences all the way along the chain. Differences in ghw people think about an approach the world of IT their world of Operations Technology and how they connect in the world of digital technology. There isn’t a clear cut answer emerging … yet.
RG: This has been really fantastic, Geoff! I greatly appreciate the opportunity to visit with you. I wanted to show the group that we have our own copy of Bits, Bytes, and Barrels that you were kind enough to help us print our own Petro.ai logo on. So, if this is something that you are interested in, follow us on LinkedIn and join our Petro.ai ommunity and we will give you an opportunity to get a copy of Geoff’s book. We’d love to share this with you. But, before we sign off is there any wisdom you’d want to share with us as parting words?
GC: Not one thing, but three things! The first is that I write a weekly article series about digital innovation in oil and gas which is available on my website. It’s absolutely free. A companion to that is a podcast that I also publish every week on iTunes, Stitcher, and Spotify and all the places where you find podcasts. It’s called Digital Oil and Gas. Third, a government agency asked me if I would turn my book into a training course and so I did that for them. I built all the materials and then recorded all the materials as a series of online lectures and they’re available on Udemy for about the same price as the book itself.
RG: Thanks so much for taking the time.
GC: You bet. I’m delighted to do it and look forward to doing this sometime in the future again. Take care.
Three factors are pressuring the oil and gas industry to make dramatic changes: enduring low oil prices, high operating costs, and the growing popularity of sustainable investing. With these mounting pressures, many operators are turning toward tech solutions.
Oil and gas has been using enterprise software and data-based decision making for decades, but what’s new since 2010 are advances in the tech space, like data storage, processing, and machine learning.
Dr. Carolyn Seto, Director of Upstream Research at IHS Markit, told CNBC News, “They [energy companies] are realizing that they’re not IT companies. They’re not software developers…They are partnering with these [tech] companies to be able to gain access to these new technologies, as opposed to taking the development costs themselves of building out capabilities within their organization.”
The right technology can help operators streamline operations. In the “Frac to the Future; Oil’s Digital Rebirth” equity research piece from January 2020, Barclays estimates growth in O&G digital services leading to $150 billion in annual savings for oil producers. As part of the same research, Barclays highlights a select group of companies, including Petro.ai, that are creating the “digital well of the future.”
Over the past decade, during the rise of unconventional drilling, Petro.ai has been a pioneer in providing leading-edge solutions for the oil and gas industry. Our workflows have become trusted in every major North American basin, from the Permian to the Bakken and Duvernay. In fact, 1 out of 3 drilling rigs running in North America today is operated by a Petro.ai customer.
What makes us different? We’re not a big Silicon Valley company working with oil and gas companies. We’re a Texas company with roots in the oil and gas industry. We understand the business inside and out: from location to the cloud. Learn more.
During his 13 years managing Fidelity’s Magellan Fund, Peter Lynch navigated the fund to returns double that of the S&P 500. From 1977 to 1990, the Magellan Fund’s annual returns averaged more than 29%, with assets under management growing from $18 million to $14 billion.
Mr. Lynch has been credited with bringing a variety of investment frameworks to the masses using common-sense terminology: “Invest in What You Know”, “Growth at a Reasonable Price”, and my personal favorite, “Ten Bagger”— a stock that increases in value by at least 10 times its purchase price.
Victims of Their Own Success
As energy specialists can tell you from experience, “investing in what they know” has been painful over the last decade. OFS bellwether Schlumberger is priced below 2008 crisis levels, as are several global E&Ps. If nothing else, these producers have proven their ability to grow over the past decade, flooding the market with excess capacity. “Growth at a Reasonable Price” is a perfect description of the current backdrop: prices flirting with all-time lows as a result of remarkable production growth.
Back to School
Like any commodity product, oil prices can be simply described as a function of supply and demand. From Econ 101: reduced demand at the same level of supply reduces the market clearing price, as does increasing supply with a constant level of demand.
Currently, public energy equity investors believe that both are happening simultaneously: supply is increasing (ample US shale) and demand is falling (trade wars, coronavirus). The result is rapid declines in commodity prices, and the enterprise values of the firms that produce them.
Peter Lynch On Demand
“Everybody’s assuming the world’s going to not use oil for the next 20 years, or next year. China might sell five million electric vehicles next year, but they might also sell 17 million internal combustion engines. … Near term, liquid natural gas and liquid petroleum gas might replace diesel fuel for trucks.”
“The difference between a glut and a short is 1 million barrels per day. The world consumes 100 million barrels per day … and shale’s going to slow down. We’ve gone from [producing] 5 million barrels per day in the US, to 12.5. People think that’s going to continue; I don’t think it will.”
Historically, Peter Lynch has shown an uncanny ability identify investment opportunities using simple frameworks. After examining both supply and demand assumptions, Mr. Lynch is of the opinion that supply assumptions are overly bullish, while demand assumptions are too bearish. Put these two things together, and energy equities may be poised for a “ten bagger”.
My energy finance career began in late 2014. As commodity prices fell from $100 to $35, I had a front row seat to the devastation. To quote Berkshire Hathaway’s 2001 letter, “you only find out who is swimming naked when the tide goes out.” It turned out that many unconventional operators and service businesses didn’t own bathing suits. My job was to identify fundamentally strong businesses that needed additional capital … not to survive, but to thrive in the new “low tide” environment. To follow Buffett’s analogy, I was buying flippers and goggles for the modest swimmers.
Following 18 months of carnage, commodity prices began to improve in 2016. Surviving operators had been forced to rethink their business models: pivoting from “frac ‘n’ flip” to “hydrocarbon manufacturing”. Over the following two years, I familiarized myself with hundreds of service companies and their operator customers. The entire industry was chasing two seemingly conflating objectives: 1) creating wells that are more productive 2) creating wells that are less expensive. This is the Shale Operator Dual Mandate: make wells better while making them cheaper.
Shale Operator Dual Mandate
As an oil service investor, I was uniquely focused on how each company I met helped their customers accomplish the Shale Operator Dual Mandate. Services that achieved one goal would likely survive, but not thrive. However, those that helped customers meet both goals were sure to be the winners in the “new normal” price environment of $50 oil.
Transformations happened quickly throughout the OFS value chain. Zipper fracs drastically improved surface efficiencies, ultralong laterals were drilled further than ever before, in-basin sand mines appeared overnight, and new measurements came to the fore. These new measurements deliver incredible insights: fracture half length, well productivity by zone, vertical frac growth, optimal perforation placement, and much more.
In Basin Sand
While zipper fracs, long laterals, and local sand have taken over their respective markets, new measurements have struggled to gain traction outside of “science pads”. Frustrated technical service providers bemoan the resistance to change and slow pace of adoption in our industry. These obstacles failed to slow the advance of zipper fracs, long laterals, and local sand … why have disruptive new measurement technologies been on the outside looking in?
Challenge #1: Unclear Economics
The first challenge for new measurements is unclear economics. Despite the recent improvements, unconventional development remains cash flow negative … and has been since its inception.
The above data suggests ~ $400B of cash burn since 2001 … small wonder operators are wary of unproven returns on investment! (Note: to be fair, operators were incentivized by capital markets to outspend cash flow for the great majority of this period. Only recently has Wall Street evolved its thinking to contemplate cash on cash returns, as opposed to NAVs).
For any technology to become mainstream, it must either immediately lower costs (e.g. zipper fracs, local sand) or have obvious paybacks (e.g. long laterals). New measurements, by contrast, do not clearly map to economic returns. Instead, these service providers tend to focus on “interesting” engineering data and operational case studies. Operators will not put a technology into wide use until its economic impact is fully understood. This can mean waiting months for offset wells to come online or years for neighboring operators to release results.
Challenge #2: Changing How Customers Work
The second challenge, which is just as important to end users, is that service providers must deliver insights within a customer’s existing workflow. Operators are busier than ever before. E&P companies have experienced waves of layoffs, leaving those remaining to perform tasks previously done by now-departed colleagues.
In addition, many service providers don’t appreciate the opportunity cost of elongating an existing customer workflow to incorporate new variables. A smaller staff is already being asked to perform more work per person; it should be no surprise that customers are hesitant to allocate budget dollars to perform even more individual work.
Challenge #3: No Silver Bullets
While each new diagnostic data type is an important piece of the subsurface puzzle, no single element can complete the picture on its own. Instead, each measurement should be contextualized alongside others. For example, fiber optic measurements can be viewed alongside tracer data to better determine which stages are contributing the most to production. When each diagnostic data source is delivered in different medium, it becomes nearly impossible to overlay these measurements into a single view.
The Oxbow Theory
The combination of the above factors leads to the “Oxbow Theory” of new measurement abandonment. As you may know, as rivers age, certain sections of the river meander off course. Over time, sediment is redistributed around the meander, further enhancing the river’s bend. Eventually, the force of the river overwhelms the small remaining ‘meander neck’, and an oxbow lake is created. Sediment deposited by the (now straight) river prevents the oxbow lake from ever rejoining the river’s flow. By the same token, new measurement techniques that do not cater to existing workflows may be trialed but will not gain full adoption. Instead, they become oxbow lakes: abandoned to the side of further-entrenched workflows.
Our Solution: Petro.ai
Petro.ai is the only analytics platform designed for oil and gas. If you’re an operator, we can help make sense of the tsunami of data delivered by a fragmented universe of service providers. If you’re a service company, we can help deliver your digital answer product in a format readily useable by your customers. Please reach out to email@example.com to learn more.