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.
As North American shale reservoirs reach maturity, the need to optimize development plans has become more demanding and essential. There are many variables that are within our control as we design a well: lateral length, landing zone, completion design, and so on. In situ stress is clearly not something we can directly control, but we can optimize around using an under-appreciated mechanism: well orientation.
The vast scale of available data on monthly production and well orientation provides an opportunity for data science and machine learning to help optimize on this variable.
Our team at Petro.ai has done some clever work, investigating how well orientation with respect to the maximum horizontal stress can be an important variable in well design. This unique approach blends principles of geomechanics with data science techniques to uncover new insights in completions design.
We had the incredible opportunity to visit Calgary on January 22nd, during a thankfully mild week, for a lunch and learn about the effects of well orientation on production in the Montney and Duvernay. We greatly appreciated the warm welcome, fantastic turnout, and keen interest in our presentation by Petro.ai VP of Analytics Kyle LaMotta. He brought his passion and expertise to an awesome and insightful event!
Because of the amazing response in Calgary, we wanted to bring this lunch and learn event to some upcoming cities. Coming soon to:
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”.
Happy New Year to everyone. I took some time over the last couple weeks to reflect on the decade behind us, as well as the decade ahead of us. As all of us found out on January 1st, our friends at the JPT took some time to do exactly that! In case you missed it, here’s a link to the article.
A Changing Industry
It is obvious that data science and analytics are front-of-mind for the SPE. The group has gone so far as to redefine the role of Management and Information Director as Data Science and Engineering Analytics Director. There cannot be a clearer signal that data science and analytics are critical to the next chapter of oil and gas. At Petro.ai, we are proud to have been at the forefront of delivering Data Science and Petroleum Analytics to the industry since 2013.
A Common Vision
Each member of the technical leadership of SPE shares a vision for the future of petroleum technology. The technical directors unanimously declared that our “traditionally fragmented industry must become more integrated and collaborative. A primary solution to breaking down those barriers: the continued evolution and adoption of digital technologies.”
While there are many great quotes in the article (you’ll find several below), this is the most striking. The group is acknowledging that the status quo isn’t good enough and is issuing a call to action to the industry. All of us have experienced the pain of the last 5 years; we’ve made great strides to streamline and improve our processes, but the work isn’t done yet. I am convinced that Petro.ai will help the industry achieve this goal.
Data Science and Engineering
“Work flows will be more consolidated and integrated, a departure from the current status quo according to discipline, de-facto norms dictated by software, or the way things have always been done … Organizations will have to break down traditional work flow-deadline mandated “compartments” through a fundamental change in their culture …”
—Birol Dindoruk, Data Science and Engineering Analytics Director
This quote is incredibly exciting for me to read, since the team at Petro.ai shares the same view. Today, data is stored and curated according to the OFS service line that collected the data: drilling data in a drilling database, completions data in a completions database, and so on. In order to perform any meaningful data science or analytics at the well level (much less the reservoir level), a great deal of data cleansing, engineering, and normalization must be done. Petro.ai eliminates these repetitive tasks and empowers engineers by delivering high-caliber data and analytics tools.
“Ultimately, the industry will need a better understanding of the production mechanism of unconventional wells. It’s not the same as in a conventional well where it’s just plain Darcy flow through a matrix [and the industry is] not going to solve these completions challenges with just completions engineers. This is a cross-discipline issue, and our biggest companion in this is reservoir engineers.”
—Terry Palisch, Completions Director
The gap between completions engineers and reservoir engineers remains wide, even within single asset teams. During a recent Petro.ai training course, we asked completion engineers and reservoir engineers to list the 5 most important factors in delivering a highly productive well. The two groups did not share a single common factor within the top five. At Petro.ai, we believe that geomechanics is critical to bridging the gap between completions engineers and reservoir engineers. We have partnered with Dr. Mark Zoback to incorporate his expertise into Petro.ai, delivering powerful geomechanical insights to engineers of all disciplines.
“When it comes to reservoir technologies, the industry has neglected [unconventionals] for quite some time because it was always about drilling and completions. Now that cash flow has shrunk and the treadmill of drilling and completing wells has slowed, the reservoir discipline is getting more attention. More emphasis is being placed on recovery factors as companies try to squeeze more out of each existing well … For this approach to be successful … the industry needs to further improve its understanding of the unconventional reservoir.”
—Erdal Ozkan, Reservoir Director
I absolutely agree with this quote; economically increasing recovery factor is the ultimate challenge in unconventionals. One of my colleagues calls this the Shale Operator’s Dual Mandate: increase production while decreasing spend. More simply: do more with less. Engineers are learning every day what levers they can (and cannot) pull to achieve this goal. The challenge is disentangling the multiplicity of factors that can impact a well’s productivity: lateral length, completion intensity, fluid system, landing zone, parent/child (horizontal spacing), parent/cousin (vertical spacing), etc. There are simply too many factors for a human brain to internalize and reason about. The good news? Machine learning is the perfect tool to solve interconnected, large-scale problems like this. Petro.ai delivers pre-made machine learning models that allow operators to identify which AFE dollars matter the most, allowing engineers to spend time (and money) on things that matter and eliminate things that don’t.
It’s been an incredible year! We launched into 2019 with determination to become even more focused on what we love doing — helping our clients accomplish more with their data. We care about the journey that knowledge takes form the source to the board room, and helping our clients deliver new insights.
In the process of aligning our company, product, and focus, we changed our name from Ruths.ai to Petro.ai so that our new name reflects our mission — to build and deliver not only a new way of organizing information in oil and gas, but also a new way to run the E&P business, built solidly on data. We’ve worked in drilling, reserves, completions, production, portfolio management, subsurface, artificial lift, EOR and A&D. We’ve had the opportunity to visit our customers in oil and gas cities across North America, and we’ve hosted and attended some incredible events. Here are some highlights from 2019.
Building the team
Petro.ai doubled in size. We welcomed so many amazing team members. Not just in the Houston office, but in our new Montreal office as well. We’re a group that likes to work hard and play hard, supporting each other and our customers every step of the way.
To make room for everybody to do their best work, our Houston headquarters moved a few blocks to its new location in the Houston’s downtown historic district at 114 Main, Suite 200. If you haven’t had a chance to come by and check out the new space, reach out and plan a visit! We love having guests come by and experience a part of our culture.
Back at the ranch
Petro.ai held its annual retreat near Brenham, Texas to bring the whole team together— the Houston and the Montreal offices— for in-depth brainstorming, teambuilding, and of course, some Texas barbecue.
The retreat served as an opportunity to discuss the latest trends in data science, oil and gas, and ways to keep pushing the edge cases of our industry.
Four Weeks, Seven Cities
When we launched our petroleum analytics meetups in Houston this past summer, we had a vision to take them on the road as well—one O&G town at a time. We picked cities where we had clients, conferences, and new connections we wanted to make. The 2019 Petro.ai Pub Crawl kicked off in Dallas, then went to Midland, Oklahoma City, Tulsa, Denver, Calgary, and ultimately back home for one last event in Houston.
The Power of Purple
If you saw us at one of the conferences we attended this year, from the SPE OKC Oil and Gas Symposium in Oklahoma to the ATCE in Calgary—you may recognize our colorful purple booth. The power of purple is giving customers a seamless user experience and delivering even better tools for oil and gas workflows.
The Petro.ai Channel
We created almost 30 videos this year showcasing some of our workflows and new features. You can see them all and subscribe to our YouTube channel. Some highlights include our Q&A series with world geomechanics expert, Stanford professor, and Petro.ai technical advisor Dr. Mark Zoback. You can check out the full playlist here.
Standing Room Only
Not only have we been able to build some incredible tools this year, but we’ve also had the honor and opportunity to offer week-long geomechanics courses and many, many training sessions on client sites throughout the year. Our instructors work hard to make technical concepts not only accessible but engaging. One recent highlight: our Technical Director Lucas Wood captivated a crowd at the TIBCO Analytics Forum. When the crowd asked for more advanced material, he adapted examples on the fly to match the curiosity in the room. We are so grateful for all the engagement, not only at this event, but at all our training sessions throughout the year, from Houston to Midland to Denver.
Petro.ai Founder and CEO Troy Ruths made multiple appearances on expert panels and interviews throughout the year. Not only does he remain accessible to every single member of the Petro.ai team, but also to the whole Petro.ai community. He’s passionate and committed to sharing big ideas about the future of the industry, and that drive shapes the whole company. As an expert in oil and gas, data science, and tech culture, Troy can talk about it all. Check out his guest appearance on a podcast discussing “The Future of AI in O&G.”
Lastly, but most importantly…
We have incredible customers—both long-time clients and newcomers this year—and we feel so grateful to keep offering the very best products and services. We really take the trust placed in us very seriously and look forward to all the projects and milestones ahead in 2020.
On November 25th, Petro.ai Founder and CEO, Dr. Troy Ruths, was a guest on the Invest with James West podcast series hosted by James West, Senior Managing Director & Partner at Evercore ISI. During the 30-minute podcast, James and Troy discuss trends of artificial intelligence and machine learning in the oil and gas industry and how Petro.ai is changing the way E&P companies plan, develop, and operate their assets.
The Role or AI
The creation and application of artificial intelligence
requires a lot of data. Oil and gas operators have always generated large
quantities of data, but the massive increase in activity the industry has seen
as a result of unconventionals created an ideal environment for AI. Each well,
and even each stage, can be seen as a unique data point where operators are
constantly changing and experimenting. The real power of AI is in unlocking all
“People think of AI at the top of the pyramid,” says Troy.
“But the future is with AI at the bottom of the pyramid—the new backbone
that serves information up to the enterprise, and humans are going to remain at
the top of the pyramid.” This view represents a departure from how many individuals
see AI but promises a much greater impact to operators. Engineers today think
about their data in terms of spreadsheets or databases. The data layer of the
future provides significantly more context while being much more intuitive. This
is the role played by Petro.ai, intelligently storing, integrating, and activating
more than 60 types of oil and gas specific data, as well as associated metadata.
Many of these data types that are ingested by Petro.ai, like microseismic events,
fiber, or electromagnetic imaging data don’t have a standard home today.
Challenges to AI Adoption and Change
“I would negatively
correlate ability to adopt new technology to oil price. The better the oil
price is, the harder it is to get technology adoption,” remarked Troy. The
current price environment is ideal for technology adoption, especially when it
comes to AI. Operators are at a point now where they need digital tools to help
them do more with less. The other impediment to AI adoption revolves around
education. AI can mean a lot of different things to different people and there
is a level of education that still needs to take place to inform the industry
on how AI can best fit into their organizations.
Troy goes on to explain another challenge, “AI can only
extrapolate from what it’s seen, and that can be a problem in a world where the
solution may be outside of what we’ve actually tried in the past.” Petro.ai
incorporates principles of geomechanics into our workflows, bridging the gap
between what we know from physics with machine learning.
AI in Upstream O&G
When prompted by James on the differentiated approach
upstream analytics, Troy noted that “A lot of the new software that has entered
the space is focused on operational efficiency and labor.…but honesty, those
aren’t going to be needle moving enough for the industry. We’re focused on the
needle moving problem, which is how can we reengineer. We need to reengineer how we approach these
unconventional assets.” Good engineering done in the office is going to
drive real improvements.
With recovery factors, well spacing, or frac hits, operators
really need to focus on the productivity drivers for a resource unit. These
questions cannot be investigated in isolation and some of the best practices we
have seen come from bundling disparate workflows together. For example, a
completions engineer may want to look at several different data types simultaneously.
They may want to look at and ask questions about geology, drilling or surface
constraints. This example goes back to humans being on top of the pyramid. The
engineer needs to be fed with the relevant information, which is where AI can
really help. Petro.ai not only serves up this data, but also uses a complex
system model built using geomechanics and machine learning that takes engineers
through an 8-step workflow to understand the key productivity drivers for a
The industry has clearly learned that unconventionals are
extremely difficult to develop profitably – even in the Permian. These are very
complex systems with stacked pay that will require good engineering to be
properly developed. This is good news for digital companies in 2020. In a
broader sense, Troy sees operators evolving “towards surgical development,
we’re going to go away from factory drilling and go more towards surgical.”
However, some operators are clearing embracing digital more than others and so
we expect a clear bifurcation in operator performance.
Listen to the podcast for the full discussion on AI and
machine learning in oil and gas and the future for data in the energy sector.
Learn how Petro.ai merges theory with operational data to inform asset development strategies in this short video with geomechanics expert, Stanford professor, and Petro.ai Technical Advisor Dr. Mark Zoback.
Every well that gets drilled is an opportunity to gain more insight and understanding. The team behind Petro.ai believes in building tools for people to use the data they have to draw the right conclusions. How can machine learning aid geomechanics? Learn more about the Petro.ai approach in the above video.
What are the opportunities and challenges with unconventionals? What can geoscience offer to unconventional development? What role can data science play? For a brief discussion, watch this video of Petro.ai Founder and CEO Dr. Troy Ruths with Stanford University Professor of Geophysics, and Petro.ai Technical Adviser, Dr. Mark Zoback.
The next installment our Q&A series with geomechanics expert, Stanford professor, and Petro.ai Technical Advisor Dr. Mark Zoback touches on how a better understanding of geomechanics can lead to completion designs that improve well performance.