23/05/2026
How are you still drilling your wells, old traditional anolog ways? Correlating offset wells and drilling datas with excel spreadsheet, or using a static drilling or reservoir model that cannot be dyanimically optimized in realtime with necessary feedback implementation immediately achieved like sending command to the rotary steerable system to alter the drilling direction spontaneously.
WellSteer Oilfield Technology Services Limited proud to announce our drilling optimization solutions THE SWEET SPOT TRACKER (SST) DIGITALLY CONNECTED OILFIELD SOLUTIONS SERVICES next-generation AI-powered digital solutions for DRILLING OPTIMIZATION.
Together with Laversab and iOTAS, we're delivering a unified environment were mathematics, edge computing engineering models and software, real-time operations, and enterprise AI work seamlessly, helping asset-intensive organizations improve their drilling operational excellence, improve safety, and optimized well production and performance.
The Sweet Spot Tracker (SST) is a real-time geosteering platform built to maximize in-zone footage on horizontal wells. It does this by combining three sources of judgment that, on most rigs, work in isolation:
An AI classifier that learns from offset wells before spud and keeps learning as the current well progresses, station by station.
A structural model built from prior-well interpretations (and seismic, where available) of the top and base of the sweet spot, recalibrated every time a new pick is made on the current well.
The geosteerer, whose accept / edit / reject decisions on each proposed control point become the ground truth that refines both the AI and the structural surfaces.
SST runs against a live rig feed(Laversab and iOTAS) in real time, and offers a playback mode for after-action review and training. Two independent zone classifications — one from the structural model, one from the AI — display side-by-side along the well so the geosteerer sees immediately when the two agree or diverge. Convergence raises confidence; disagreement suggests human expert control point review.
Please contact us: [email protected]; +2347032616140.
