Q: What’s the Petro.ai strategy for making capital decisions in this rising commodity price market?
A: “Petro.ai is powerful because it allows you to hold other things constant in the digital twin that we create from your reservoir,” Richard Gaut, CFO of Petro.ai responds drawing on years of experience with a leading energy private equity group. "Petro.ai allows you to try different permutations and combinations of the number of wells and the number of benches that you access and how hard you frac each well. Then Petro.ai brings in all those different tradeoffs that happen as you’re increasing sand or decreasing sand, widening spacing or tightening spacing, commodity pricing going up or commodity pricing going down.
“Tracking all those different cost/benefit tradeoffs in a digital twin of your actual reservoir where you can be confident that if you run different scenarios that is what would have happened if you ran that experiment in the ground.
“Investment at the pad level or at the DSU level, the drilling spacing unit, is all about your internal capital budget, what your board has approved as to what you can spend in capex that year. So, the questions become should we use some of our extra cash to pay down debt, buy more people or drill more wells, do more D&C work?
“If a well costs $8 million to drill and complete, the question is how long does it take to generate a return on the money that I’ve put into the ground? The biggest piece in our industry that influences how you get a return is what the commodity price is.
“If you’re using a DSU design that’s priced for a mid-60’s environment, you’re putting four wells per section because that’s what made sense at $65 a barrel. Now it’s a different market entirely with $95 a barrel. Operators should be thinking about putting more wells into the ground to take advantage of these higher prices. That means thinking about downspacing to put in more wells per DSU.
“Now if you bring them closer together there might be some degradation but the uplift in the commodity price can outweigh the negative impact of the degradation. As you squeeze them together, they might be a little worse, but are they $30 a barrel worse? To test those concepts, to do that cost/benefit analysis is difficult taking a lot of internal effort, bringing a lot of internal data together, stopping your engineers from their task of drilling wells. So, while it is an extremely important economic decision, it is a distraction from the day-to-day work.
“Petro.ai gives managers and financial sponsors leadership and confidence that they’re making the right capital budgeting decisions. And equally important, that leadership can react as quickly as the commodity price moves.
“Another example is with service pricing. Sand pricing has spiked recently. Using that as an example, the cost/benefit analysis that one of our customers would do goes beyond just the number of wells. The operator is also answering how much fluid to put in each well, how many stages to put in each well, what’s the volume of sand that I should put in each stage. As the price of sand changes from week to week, operators need to continuously optimize as your input costs change.
“Using Petro.ai, operators can run many different scenarios of how a DSU would perform if you completed the wells with differing amounts of sand. These scenarios can be contextualized with respect to how the performance of that well would change. As the cost/benefit analyses are run, if there’s some performance improvement from putting more sand down hole, but the price of sand has doubled, is it worth it to increase the volume of sand? Do you recoup that investment from sand?”
Petro.ai becomes a confidence engine driving your complex decisions with scenario options that are highly accurate. The real risk is not taking advantage of the Petro.ai access to rapid cost/benefit tradeoffs that stabilize and scrutinize your shale reservoir and lead you to investment strategies that work in the current market state and in the future.
