Global energy technology company SLB has introduced Neuro autonomous geosteering, which dynamically responds to subsurface complexities to drill more efficient, higher-performing wells, while reducing the carbon footprint of the drilling operations.
Using artificial intelligence (AI), Neuro geosteering integrates and interprets complex real-time subsurface information to autonomously guide the drill bit through the most productive layer or ‘sweet spot’ of the reservoir.
During conventional geosteering operations, geologists must manually interpret this data to identify a well target, update the well plan and trajectory, and communicate this to the directional driller.
Neuro geosteering does all of these steps end to end, without any human intervention.
“Neuro autonomous geosteering is a remarkable industry-first achievement that is for drillers what the autonomous vehicle is for drivers. Using advanced cloud and edge AI capabilities, the system automatically selects the best route for drilling the well based on high-fidelity downhole measurements, bringing the well trajectory in line with the real-world conditions of the reservoir.
“By drilling more consistent and higher-producing wells, our customers can optimize their field development plan while reducing operational emissions from drilling over the lifetime of the asset,” said Jesus Lamas, president, Well Construction, SLB.
Neuro autonomous geosteering builds on the technology foundation of SLB’s Neuro autonomous directional drilling, which drills wells to a defined well target in accordance with the well plan.
It also incorporates high-fidelity downhole measurements that ensure certainty of well placement in the best part of the reservoir.
In Ecuador, SLB deployed Neuro autonomous geosteering to drill a 2,392-foot lateral section of an onshore well for Shaya Ecuador.
During this operation, SLB's autonomous system completed 25 autonomous geosteering trajectory changes, with each interpretation and decision cycle taking only seconds.
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