Video Improving Reservoir Performance Through Autonomous Well Intervention Solutions
The Intervention and Stimulation Alliance is improving reservoir performance using digital and autonomous solutions.
Enhanced technologies for improved well economics with repeatability, reliability, and reduced carbon
Neuro autonomous solutions enable our autonomous directional drilling capabilities that build wells in the most efficient and consistent manner possible, regardless of the rig, field, or trajectory. It does so by focusing on intelligent planning and execution in combination with our suites of surface and downhole automation.
This means that your trajectory stays right on plan because our technology enhanced by Neuro solutions measures the exact strength of the earth’s gravitational and magnetic fields every second. We also use 3D reservoir mapping in real time to help pinpoint the BHA’s exact subsurface location and determine the precise steering responses needed. And this enables real-time reservoir characterization, which not only keeps you on track, but it gets you to the sweet spot in the reservoir pay zone.
Drilling with rotary steerable systems requires operating in manual mode, involving a command sequence applied repeatedly to control the curve trajectory and comprises multiple interventions and downlinks from the directional driller at the surface for steering force, toolface (TF) orientation, and measurements. Downlinks to the BHA and tool data fed back to the surface for adjustments in commands are called control-loop time, which can be as much as 20 minutes. And it is the bane of every directional driller’s existence. Until now.
Neuro autonomous solutions enable our autonomous downhole control technology that guides our steering and other tools. These autonomous controls overcome control-loop with advanced BHA components that assess the data and react at the time and place needed.
Autonomous directional drilling supports our effort in reducing carbon footprints because it integrates technology that eliminates the need for engineers to travel to wellsites. Using Performance Live digitally connected service, domain experts access data from anywhere at any time—the workplace, the home, or wherever they can log onto our robust network. By reducing personnel on the rig site, associated travel (even travel to a workplace), HSE risks, and environmental impact diminish equally—without inhibiting performance.
Now, advanced BHA components assess the data and react at the time and place needed, even when heading into the zone of exclusion (ZOE) or into rugged downhole conditions. So autonomous directional drilling improves performance, enabling more consistency from job to job, site to site, because data is real time, immediately accessible, enabling customers and domain experts instant collaboration for better, more consistent drilling outcomes.
Autonomous directional drilling solutions are proven by deployments drilling a total of 26,000 ft of curves. Field testing includes a wide variety of trajectories and formations in U.S. land, the North Sea, and the Middle East. In one published case from the Permian Basin—where very high shock and vibrations, high rpm, and drilling in the ZOE—Neuro solutions guided our steerable system while drilling seven curves on seven unconventional wells on a particular asset. Comparing it to offset wells on the same asset, the curves required 42% fewer downlinks and the on-bottom drilling speed increased by 39%.
Autonomous directional drilling (ADD) is part of our SLB Neuro™ autonomous solutions that use advanced cloud-based software and connected intelligent systems to create a continuous feedback loop between surface and downhole. This significantly increases the efficiency and consistency of E&P operations while reducing human intervention and footprint, laying the groundwork for fully autonomous operations in the near future.
With repeatable and reliable system autonomy, ADD helps lower carbon footprints while measurably improving well economics. SLB domain expertise combines with machine learning (ML) models through automated closed-loop workflows that deliver differentiated performance to customers across the energy value chain.
Development of our autonomous capabilities is based on four pillars, which are intelligent planning and execution capabilities, along with automation of select surface downhole technologies surrounding essential task and related activities in well construction.