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Data Science & Analytics Passion for Change

Passion for Change: Rife Resources

with Bob Lamond, VP Asset Development at Rife Resources Ltd. 

Tell us about your background and what you do now.

I started my career as a technical geologist, educated in Ontario, Canada, then went to grad school for Paleontology at the University of Utah. In the middle of studying trace fossils in Utah and Kenya, I was recruited by Exxon & ultimately did not complete my Master’s degree. Initially, I had no desire to work in oil and gas – I wanted to be a paleontologist! I really fell in love with the huge datasets, the incredibly bright people, and the massive, global projects that Exxon was working on. And so, with stars in my eyes, I returned to Calgary to begin working at Imperial Oil.

At Imperial, I was first exposed to geologic modeling, where you develop three-dimensional computer models of the subsurface geology that allow us to test development plans and production strategies prior to drilling. That’s when I started getting heavily exposed to the computing side of geology and began to see the promise of a new way.

After a few years, I left Imperial Oil and went to Shell Canada for about five years – working almost purely as a geologic modeler, building models (a lot of geostatistics) and trying to incorporate those into our development plans in Canadian heavy oil and tight gas assets.

Following this, I joined Murphy Oil, working both here in Canada and in Houston. For some reason, they gave me – a computer modeling geologist – the opportunity to manage a subsurface team. At the time, a career in management was something I absolutely did not want to do. It has turned out to be the best (work-related) gift I’ve ever been given!

Two and a half years ago, I joined this amazing little company – Rife Resources. Rife Resources is a private exploration and production company in Western Canada that also manages the assets of Canpar Holdings and Freehold Royalties. 

My current title is a little unusual—VP of Asset Development. My job has been to focus on geology and subsurface engineering, but also on the innovation and analytic side for the company. At Rife, we traditionally do small ‘e’ exploration, we do geologic mapping, lease land, we plan and drill wells, we operate our fields responsibly. But what we’re really trying to do to stand out is to be creative in the fields where we’re working. These areas have been seen drilling for over 50 years and thus everyonealready knows everything about them. Well, you know, it turns out not everything! With our humble little company, in our humble old oil fields, we’ve recently drilled some consistently amazing & top-producing wells just from applying good technology mixed with traditional geology and engineering.

On the Freehold and Canpar side, we manage millions of acres of land, thousands of different leases, with thousands of wells that pay us royalties on a month-by-month basis. It’s a phenomenally rich data set, especially at a small company, for applying analytics.

Because these companies have been around for a few decades here in Canada, they’ve previously had a very traditional way of doing this work; paper and manual effort, numerous spreadsheets, phone calls, and so on …. until now. What we really endeavored to do over the last few years is to streamline, modernize, and finally be able to better track our assets. This very much appeals to my data-loving side.

We have seen enough early success that we have even started a small business unit we call “Analytics and Innovation”. This small team is being managed by another semi-ex geologist, Shayne Chidlaw, and is helping now to support projects across all disciplines in all three companies.

Why do you have a passion for change in this industry?

I have a real passion for streamlining and modernizing our industry. We’ve relied on paper and multiple Excel projects and the ‘gut feel’ way of doing things too long. Doing things the way we’ve always done them—we gotten stuck maybe a decade behind where we should have been, and now we must spend the money & effort to do this work and the analytics properly. 

You really don’t need a ton of money to get started in this work. You need access to data. You need some people to help compile & sort it, get it in the right place. Then, you just need some creative people, demonstrate a new way of working and spur them to make magic happen. When you have a good project that works, it breeds curiosity and excitement in others, and really gets teams going. 

My absolute work passion revolves around managing people. I find management most effective when you focus on people’s enjoyment and their fulfillment at work—if they love what they’re doing, if they feel the tasks they’re working on are important, and if they work for people who are highly interested in what they’re doing. They come to work charged up. They bring their best ideas. They bring their best work every day. So where does analytics fit into that? It allows people to show their creativity. 

It’s no fun punching through a whole bunch of paper spending all day trying to compile data. It is hard to be creative with the few minutes left to work after you spent all day data gathering. What is fun is to have a dynamic dashboard where you can quickly and confidently dig through information and tools you can modify to effectively get meaningful things done.

Do you think this 2020 downturn will speed up the transformation or slow things down?

I think it could go either way. It really should drive innovation because people are going to have to begin doing more with less. Unfortunately, when conditions are really poor, it leads management not to want to pay for the workforce or the data that they would need to do that.

As a company, we are asking ourselves, “Are we in survival mode, maintain mode or thrive mode? Do we just want to limp along, so that at the end of this, the last person can turn off the lights? Do we want to maintain? So at the other end of this downtrend, we come out the same as before. Or, do we want to use this time to come through this stronger, more nimble, with more people using technology?”

Another way of looking at this is that there will be no new energy company that will start up without a data scientist, or at least an eye on starting with lean, efficient data processes. That’s going to be the transition. Too early to know the details, but all new companies are going to be structured fundamentally differently than the old ones. We’re going to need to be the mammals on the other side of this extinction.

What successes have you seen in data science, machine learning, or AI?

I do love the idea of using machine learning to explore and find insights about physical reality, but then rerunning the whole process iteratively, where the machine is informing the human and the humans are informing the machine, and repeating. It’s like a co-learning process. 

Using data science and AI—you can get an answer every time, but is that answer actually grounded in reality or physics and thus will it be useful to predict the future?

Seismic data makes one of the best examples. Geophysics has been far ahead of the industry and have been using computer guided technology for a long time.

When you move into applications like AI for automatic legal document translation, or take lease documents and attempt to apply machine learning/AI to interpret detailed clauses, you naturally generate lots of skepticism in land and legal colleagues!

So, how do you get people to have an open mind, give the technology try and then potentially embrace it? I see more of a human struggle than a computer struggle right now.

How have you seen other competitors start to adopt data science or analytics?

Personally, I prefer being a bit more on the leading edge versus letting others work the bugs out before we try it. It’s a lot more fun, but not always more effective. Other companies (including us) are doing amazing things right now, and it makes the most sense for us to learn from others and be a “fast follower” on most technologies.

We all benefit from people sharing open data, open processes. Companies like Petro.ai who work with multiple different companies—the learnings build up and become massively valuable for companies like us—we can’t afford to be on the cutting edge of too many things. No other company has the same issues and problems we have, and we’re not at the size or scale that makes any sense for us to be the innovators of everything. 

I have made it a policy for myself my team to share as much as we are able with industry, with companies like Petro.ai, with really any interested party, not just because we will ultimately benefit, but that the whole industry stands to benefit from the sharing of these things.

A small but current example of this: in the meeting I had just before this interview, one of our production engineers – who could just have been just doing his ‘job’, generating Excel sheets & reports day after day, took the time and initiative to innovate, taught himself how to  pull data from a few of our databases, built his own dashboard, and then shared it with everyone. This initiative is going to be both useful and contagious!

Being at a small company like us, we are nimble enough to be a hotbed for innovation. We just won’t have the funding to make it a bigger scale type project. That’s where we rely on companies like Petro.ai to help us out, where you guys have the ability, the skill, and technology, and you see what other companies are doing. 

Would you suggest any good books or blogs that you’re reading?

One of my favorites by Nassim Nicholas Taleb, who wrote Antifragile and The Black Swan, is Fooled by Randomness. I’ve been pushing this antifragile mentality within the company and should be considered as essential reading during this downturn. Another book about analytical thinking that I really enjoyed is by Jordan Ellenberg, How Not to Be Wrong: The Power of Mathematical Thinking.

I have also reread the classic Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig. While definitely dated, it contains some beautiful parallels with our current battles of the romance of new technology with the nuts and bolts of older reliable tech. Mostly unrelated, I am rebuilding an older titanium road bike in my spare time, when I get away from my computer.

A podcast I always find soothing and wonderful is This American Life with Ira Glass. It’s just a great way to think about other things and other people and puts you in a good headspace every time. 

Do you think there’s a difference between the way you guys in Canada are viewing this pandemic and this market versus some of your peers in the United States?

Canadians have been trying to work within cash flow and dealing with lower commodity prices for multiple years now. Most people here have been dealing with this reality for quite some time. I think this creates less of an acute feeling of despair despite how bad the market is currently. A survivor mentality is well-entrenched in Calgary. 

On the flip side though, no one seems to bounce back like you guys do. Americans may seem to be in a steeper trough at the moment, but I predict that you will rebound and climb out of this a lot faster than us up north. Our sine wave is just a little more muted than yours.

In your own words, how would you describe what Petro.ai is?

I love the promise of being able to use our data in a flexible tool environment. I have a problem with ‘brittle’ software that says: “this is how you want to look at the data, this is how you want to work the data, this is what your graphs should look like, this is what you get to do.” 

With Petro.ai, we want to look at our data in our own way and designed specifically for the needs of our own companies. It allows us to build projects that we’re really not able to build ourselves in a shorter time than we could have built it. 

Like everyone, we are facing budget reductions everywhere in our company. However, when we brought up continuing with Petro.ai, we still said yes. This is a really important project for us, and success here will allow us to emerge in a stronger, thriving and antifragile state on the other side of this downturn. 

 Bob Lamond is a creative, dynamic, and caring subsurface manager with >20 years of diverse unconventional development and production geology background. 
 
Categories
Business Intelligence Tools Data Science & Analytics Drilling & Completions Geology & Geoscience Passion for Change Reservoir Engineering

Passion for Change: Bonanza Creek Energy

with Kyle Gorynski, Director Reservoir Characterization and Exploration at Bonanza Creek Energy

If you missed the first part in this series, you can find the start of our conversation here.

Why do you think there’s been so much hesitation around change?

There’s a strong engrained culture in oil and gas with  a generation of people who’ve been doing this for decades – although on completely different rocks, play types and extraction techniques. There’s been pushback on adopting new geology or engineering software because people become so comfortable and familiar with the tools they use. I think a lot of it is simply the unique culture in oil and gas. Shale is still new, and our guesses are still evolving. I think we’re getting closer and closer to what that right answer is.

New organizations will have to adopt new technologies and adapt to new trends, because there’s no other way to make this business work.

As a scientist or engineer or manager in this space, we really have to be cognizant that the goal of a lot of vendors out there is not to help you get the right answer, it’s to make money. The onus is on us to vet everyone and make sure we’re getting the answers we want. 

Machine learning is simply another tool, like a physics-based model, aimed to help us predict an outcome and increase the precision and accuracy of these predictions. People have made pretty fantastic inferences from these kinds of tools. 

You can’t just pay a company to apply machine learning to a project. You need to help them utilize the correct inputs, the relationships, and ensure the predictions and outcomes match the other observations you have from other datasets.

I don’t think any organization should be cutting-edge for the sake of being cutting-edge. The goal is to solve these very specific technical challenges quicker and with more accuracy. Our job is to extract hydrocarbons in the most safe, environmentally friendly, and economic fashion. Technology like machine learning and AI are tools that can help us achieve these goals and needs to be done correctly.

Can you share any successes around data science or machine learning at your company?

The industry has been using these techniques for a long time. In their simplest form, people have been cross-plotting data since the early days of the oil and gas industry, trying to build relationships between things. At the beginning of my career, I remember using neural networks to predict log response.

Now we use predictive algorithms to help us predict log response where we don’t have certain logs. Let’s say we want to predict lithologies—carbonate-clay-quartz-feldspar content in a well— we’ll build relationships between triple-combo logs, and more sophisticated, but scarce elemental capture spectroscopy logs. We don’t have ECS logs everywhere, but we have triple-combo everywhere, so if you can build a relationship between those, then you have a massive dataset you can use to map your asset. That’s a simple way we use this type of technology. 

Like almost every company now, we’re also predicting performance. That’s how we’re able to make live economic decisions. We have a tool where we can put in a bunch of geologic and engineering inputs and it’ll predict production rates through time that we can forecast, add new costs, and run economics live. We’re running Monte Carlo simulations on variable rates, volumes, lateral length, spacing, commodity pricing, and costs that are based in our best estimates to predict tens of thousands of outcomes to try to help us better understand what the best decision could possibly be. I think that’s the most impactful place it’s being used, and I think that trend is being adopted more and more in industry as I talk to my peers. 

Type curve generation is no longer grabbing a set of wells and grouping them together and fitting a curve to it, but it’s trying to predict the infinite amount of outcomes that are between the extremes.

Have you seen any success among your competitors using technology, specifically data science and analytics tools?

There’s some great work out there across the board. I had a lot of fun at Encana (now Ovintiv) seeing a lot of my peers who are exceptionally smart really trying to adopt new technology to solve problems. I’ve seen some amazing work getting people to adopt new ideas, new thoughts, new predictions. I like going to URTeC. I think that’s a fantastic conference. I always find a number of great sets of technical work that has come out. 

I think the industry is doing a great job. There’s a ton of really smart people out there that know how to do this work. I think a lot of young people are really adopting coding and this bigger picture approach to subsurface, where it’s not just you’re an engineer or you’re a geoscientist, you really have to understand the fluid, the pore system, the stresses, what you’re doing to it. There’s no way we can be impactful unless we understand the really big picture, and people are getting much better at that, trying to use tools and develop skillsets that allow them to solve these problems a lot quicker.

How would you describe Petro.ai?

We see you guys as filling a gap we have. It’s the ability to pull data together. It’s the ability to simply apply big data to a dataset we quite frankly don’t have the time or the capability to do in-house. Petro.ai provides us with a very important service that allows us to get to a point that would take us 12-18 months to get to on our own, but in only a couple months. What we really like about it is the fact that we’re developing something that’s unique and new and therefore has our input and involvement, so we’re not just sending you a dataset and asking for an answer, we’re trying to say what we think drives the results, and we also want your feedback. So you’re also a group of experts as well that not only have your own experiences, but you’ve seen people’s assets and plays and how everyone else in industry is looking at it, so it’s nice to have this group of consultants that have the same goal – to address a problem and try to figure it out. We want to get to an answer as quickly as we possibly can and start to apply those learnings as quickly as we possibly can. 

Kyle Gorynski is currently Director of Reservoir Characterization and Exploration at Bonanza Creek Energy.  Kyle previously worked at Ovintiv where he spent 7 years in various technical and leadership roles, most recently as the Manager of Reservoir Characterization for their Eagle Ford and Austin Chalk assets.  Although he is heavily involved on the technical side of subsurface engineering and geoscience, his primarily focus is on their practical applications in resource and business development . Kyle received his B.S. and M.S. in Geology from the University of Kansas in 2008 and 2011, respectively.
Categories
Drilling & Completions Passion for Change Reservoir Engineering

Passion for Change: Bonanza Creek Energy

with Kyle Gorynski, Director Reservoir Characterization and Exploration at Bonanza Creek Energy 

Tell us about your background and what you do now.

I’m from Kansas and got my Bachelor’s and Master’s degrees in Geoscience at University of Kansas, then moved straight out to Denver. Spent the first seven years of my career with Ovintiv, which was previously Encana, and had various roles, starting with mainly geology functions, and eventually working as a manager. I’ve always been interested in the technical side of the industry and novel approaches to petrophysics, geomechanics, and reservoir mapping, and how new data and new analyses can drive decision-making. It’s important that our decisions are driven through science and statistics and less through drillbit and opinion alone. I joined Bonanza Creek about a year and a half ago.

I’m the Director of Reservoir Characterization and Exploration. This role has two primary functions. One is an asset development function and the other is Business Development/Exploration. Asset development is the value optimization of our asset to maximize on key economic metrics by: 

  • understanding the subsurface to determine baseline performance
  • understanding key engineering drivers that impact performance 
  • applying those insights to modify things in real-time like spacing, stacking, completion design, well flowback etc.

At Bonanza Creek, one of the things our CEO Eric Greager likes to say is, “We’re unique because we have the agility of a small company, with the technical sophistication of a larger enterprise.” 

This allows us to respond to things that are changing quite rapidly, from the costs of goods and services to our own evolving understanding of the reservoir. By rapidly adapting, we’re able to maximize value and economic return.

That’s the main piece. The other part of the role is the exploration and business development function. We apply the same principles I just described to other assets inside and outside our basin and work with the greater operations and finance groups to determine an asset’s current value and what its potential future value could be.

How do you incorporate technology into your approach?

Technology is applied everywhere we possibly can. We have powerful technically savvy people who can develop tools and use tools to guide all our decision making. 

That’s where Petro.ai comes in. We need help building additional tools to make real-time decisions. That’s going to help us stay lean and agile but also make sure we have the right information to be making the most informed decisions. It comes down to the right data and the right people.

We need the ability to make decisions at multiple levels within an organization, so decisions can be made quickly without a top-down approach but with a high level of trust. We need to make sure the technical work is vetted and have a culture of best practices built-in for engineering and geoscience evaluation so we can have a lot of trust in our workflows. When that expertise is already built into tools—a lot of the equations, the input, the math—that helps us have trust in the inputs as well as the outputs and allows us to make those quick decisions.

How do you define real-time?

Our ultimate goal on the completions side is to be making real-time changes while we’re pumping – so minute by minute. That’s what motivated the project we have going with Petro.ai, to start turning knobs during the job, making sure the reservoir is sufficiently stimulated and not over capitalized. 

Let’s say we have sixteen wells per section permitted, but all of a sudden commodity prices drop and it’s at forty bucks, so we’ll only drill eight of those wells. Once those eight wells are in the ground, you’re stuck with that decision. Then maybe commodity prices go up, and we get a good price on sand or water, then we rerun the economics and what the type curves look like. Then we’ll make a new decision, for example, on the amount of sand or water or what the size of our stages are. 

We are making really quick decisions in terms of completions on a well-by-well basis. As price fluctuates and we’re teetering on the edge of break-even, we have to be real flexible in terms of trying to maximize the economics. 

Our next step with Petro.ai is using our 3D seismic data, well architecture, geosteering, and drilling data to understand what kind of rock we’re actually treating to make sure we’re putting a specific design for that specific formation, and we’re also reading the rock at the same time. We’re taking that information, which is mainly pressure response during the job, and trying to learn from that live.

Why do you have a passion for change in this industry?

I’m passionate about understanding the subsurface and the whole E&P industry and our evolving understanding of unconventionals. I’ve always been passionate about the big picture, trying to zoom out and understand how everything interconnects.

Change is a reality. It’s unavoidable. The pace of change and the path you take differs between organizations. The industry as a whole has been incredibly slow to adopt change. We’re now on the verge of a large extinction event. The E&P companies that remain will be in a better position to thrive once this is all over.

Unfortunately, something even as simple as generating a return on your investments has eluded many companies. For these companies, it is often the stubborn top-down culture that has resisted change and is their greatest detriment. It’s an exciting and scary time today. However, these events allow the best to survive and force others to adapt and change – for the better. 

Investments on a single well can be aprox. 6 to 10 million dollars for a 2-mile lateral in the U.S.. Investments on learning are 10s to 100s of thousands of dollars for an entire year. There’s a lot of capital destruction that could have been avoided by doing homework, collecting data, doing analysis, and connecting the dots from math to modeling to statistics all the way to a barrel of oil.

Science often ends up in a folder. It takes good leadership, management, and technical work to ensure that you’re making decisions with all your data and information. The point is to make better decisions and to make better wells. 

The conversation continues here.

Kyle Gorynski is currently Director of Reservoir Characterization and Exploration at Bonanza Creek Energy.  Kyle previously worked at Ovintiv where he spent 7 years in various technical and leadership roles, most recently as the Manager of Reservoir Characterization for their Eagle Ford and Austin Chalk assets.  Although he is heavily involved on the technical side of subsurface engineering and geoscience, his primarily focus is on their practical applications in resource and business development . Kyle received his B.S. and M.S. in Geology from the University of Kansas in 2008 and 2011, respectively.
Categories
Drilling & Completions Reservoir Engineering Transfer

The Impact of Well Orientation on Production in North American Shale Basins

Full house at the January 22nd Calgary Lunch and Learn presented by Kyle LaMotta, VP of Analytics at Petro.ai, on the impact of well orientation in the Montney and Duvernay plays

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:

For more info on all our upcoming events, please join the Petro.ai community for updates.