We have one goal at Petro.ai. We want to make your oil & gas patch a billion-dollar success. We want your story to be built with the real shale narrative, with the real translation of the rock, with a real way to grasp your opportunities in your space, in this time.
As part of our multi-step process for calibrating and validating the Digital Twin, one of the key steps is the Drainage Model. We use that as a feature when we’re predicting the well productivity. “And consistently it’s one of, if not the highest in importance of all the features. We have our own way of creating this drainage area that uses geomechanics and some machine learning processes. That’s heavily built off diagnostic data collected in the field. Microseismic data is also used to inform the shape.
You’re bringing Petro.ai into your company knowing that productivity will increase, pad design will improve, documentation will be consistent and there will be an ongoing and continuous learning process. How are those goals accomplished?
Lowering costs is a permanent part of the Oil & Gas Industry. With Petro.ai, each point in the well lifecycle can be addressed for economic viability.
Even our clients that already have their pad strategy finalized and are working on completions optimization, want to run their current well configuration through the Petro.ai geomechanics-based Global Earth Model and Economics Engine. They want to see if what they’re pouring millions of dollars into is the right path moving forward. At Petro.ai we’ve seen that less can mean more in pad construction with some surprising results.
Digital twin: Petro.ai creates a real-time digital counterpart of shale reservoirs, integrating well data, production, and subsurface data like stratigraphy and geomechanics. We integrate data as it becomes available, so it is always up to date. We have AI models that learn from the digital twin to make predictions of well performance and optimal development plans.