Company Created In-House Tools and Petro.ai
Data Science & Analytics

Company Created In-House Tools and Petro.ai

Rosemary Jackson  •  

Q: We have a type curve analysis tool with sensitivity inputs that we use internally in our company. How does Petro.ai fit in with what we’ve already developed?

A: Charles Connell, VP of Product explains, “A lot of companies use multivariate models to predict well performance. It’s common for companies to have an off the shelf tool or to use Spotfire, MATLAB, or R scripts to make something that they can plug in some different data types and see if they can accurately predict how a well is going to perform.Then, they can use that as a design tool.

“That’s very similar to what Petro.ai does when we run our analysis with clients. The key differentiator for Petro.ai is that we provide a more sophisticated analysis in that we have drainage and the frac fingerprint. We work three dimensionally, so we have both the vertical and the horizontal interference with the parent/child interaction. And we have the highest accuracy rate of any analytical tool in oil and gas today.

The in-house tools that we’ve seen don’t have any of that higher-level analysis. They’re simplified approaches and usually, two dimensional. There is no vertical interaction. There’s no drainage. We’ve added drainage as a feature in what we’ve built. Petro.ai knows the industry workflow and the variables that matter. Companies want to play with different inputs to see if that’s significant or not. And they’re starting to understand that in unconventionals they have to go beyond their in-house type curve planning tool because it doesn’t have the accuracy or versatility needed to work in shale.

“Companies will still do their type curve work and have a type curve for an area because that’s their first read. But instead of just a type curve they can use Petro.ai to see how a well performs if they change the lateral length or if they put it in a new location.

type curve and drainage dynamo model

“What we’ve done is take the kind of workflow that they’ve built in MATLAB and in Spotfire and put it in Petro.ai. Now companies understand the complexity and don’t want to manage creating the analytics; they want us to sophisticate their understanding and add the drainage features. They want us to make it easier for engineers to use. Having it in MATLAB or Spotfire means only certain people are able to make new models. Companies want something that all their team can play with to make models so they can explore different variables.

“Petro.ai already has the key features, the sensitivities that oil and gas needs for a full, accurate analysis of the subsurface. We have a great web interface. You can jump in and start using Petro.ai like you’re using your Spotfire tools right now.

“If a client already does have a workflow, I’m sure that ours has important additional features that they don’t have. We manage it and we help them run it and they don’t have to do that internally. Petro.ai has been developed to have parity with what our clients have now. We add the high accuracy of trained models that predict results based on the important geoscience that companies are missing in their in-house created tools.

PETRO
114 Main Street Ste. 200, Houston, TX 77002
4-5609 Avenue du Parc, Montreal QC, H2V 4S8

© 2020 Petro.ai All Rights Reserved