Pad Design Duplication: Run the Numbers in Petro.ai to See If It’s Really a Good Fit
Data Science & Analytics

Pad Design Duplication: Run the Numbers in Petro.ai to See If It’s Really a Good Fit

Rosemary Jackson  •  

Q: My neighbor has drilled some pretty successful wells on the neighboring lease, is using their pad design and completions scenario a good idea?

A: It’s not simple. You know you’re putting in a pad. You know what’s been done before. Can you make this one like your neighbor’s? I put these questions to Dr. Brendon Hall, VP of Geoscience and Kyle LaMotta, VP of Analytics.

Hall: This is a good question. On the one hand when you use a data driven approach you need to understand what has been working in the region around the pad that you want to design and incorporating that data to let you make a better design.

LaMotta: And companies have a lot of perception risk that they’re trying to be conscious of.

Hall: Right, if you do exactly what was done nearby and it doesn’t work out, you can blame it on geology or you can blame it on the company you modeled from. If you do something different and it doesn’t work out, then it’s your fault. But the real risk is, you’re always assuming what was done nearby was best or even good enough.

LaMotta: That’s the problem. I think the risk of copying your neighbor is there’s lots of changes geographically and geologically even across a short distance that can affect the outcome of the performance. Those things are hard to understand if you’re just looking at another operator. From the analytics perspective, just trying to look at someone else’s data and make correlations is really difficult.

That’s what Petro.ai provides, this extra layer of understanding the relationships of lots of variables. And then being able to calculate things like drainage and predict stress that are big drivers of productivity.

Companies lock in most of the well lifecycle from their neighbor. The big things that would be changing are well spacing, intervals that are being targeted, and then the high-level completions design which is proppant and fluid. Everyone is going to drill a 2 mile lateral if they have the acreage to do it. Everyone’s going to put in at least 60 stages. No one’s going to put wells closer than 600 feet apart, but they might do them 1000 feet apart.

People in general are doing the same thing, but what we’ve seen is even within that base design there’s a lot of room to change things. You can move a well 50 feet up or down or left or right and that can have a big impact on the productivity.

area overview well pad

Hall: And not just stopping there but connecting productivity to economics. If we’re just trying to maximize production then yes, put as much proppant into the ground as possible. But there’s a point of diminishing returns where the price you pay to put proppant in the ground exceeds the returns you get from the additional production.

LaMotta: That’s a really good point. Every operator has their own objective function and what they’re trying to maximize. You don’t know what it is. One operator, your neighbor, might want the best IP because that’s going to make headlines.

But other companies might want to drill the most economic pad. Or they want the fastest cash flow. Or they want to have the best capital efficiency. Everyone has different constraints that they’re operating within; they want to maximize different things.

Hall: That objective function is hugely important because if you assume the financial metrics that you’re trying to optimize are the same as what your neighbor is doing then you might interpret what they’re doing in a completely different and erroneous way. That doesn’t necessarily mean it’s going to be the best for your strategy.

LaMotta: The time horizon is important too because you might be looking at a pad two years ago that was very productive but if you reevaluate that with today’s economics where the price of commodities change, the price of completing the wells change, drilling the wells change, technology has changed.

We’re looking back at pads that are anywhere from a few months to five years old and a lot of things can change over that time horizon. The fourth dimension of this is time.Where you are in time is going to have a big effect on the economics.

updated well level performance

Hall: It is hard for operators and a real trade off. The information from a neighboring pad is valuable and relevant on one level. But what we’ve found is that, just like Kyle said earlier, small differences can mean big changes in productivity returns.

LaMotta: Everyone that we’ve talked to, every company is chasing what someone else has done as an important input. But companies do this internally as well. They have two pads that are really close together maybe only a mile or two apart. Both of them are owned and operated by this company but the first two wells that they drilled were both really good producers. They moved to the west a couple of miles, basically repeated the same pad, put in a well, same lateral length, same landing zone, same completion design, same everything and the new well performed much worse than the original wells. Then they ask, we did everything the same, what’s different?

And that’s the point there can be many things that are different. To be confident in drilling your next pad, test your strategy by crunching your data and your variables through the Petro.ai algorithms to see if it’s a fit worth spending millions on.

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