Display and analyze drilling data (time series and depth series) combined with geological data for computer assisted operations monitoring and performance improvement.
DrillSpot allows drilling teams to monitor drilling parameters in real-time and make data-driven decisions to optimize drilling performance.
The integration of drilling hazards prediction algorithms helps proactively identify and avoid potential operational problems.
Сompare the current wellbore position with that of either the wellplan or the current target line in conjunction with geosteering interpretation in StarSteer.
Quickly visualize the current trend of the wellbore and its relationship to target horizons.
DrillSpot processes raw drilling data using machine learning algorithms to provide you with 19 automatically recognized rig activities and numerous KPIs.
This combined with geological data from Solo Cloud from any number of wells brings deep insight into routine drilling operations efficiency and identifies areas of improvement.
With DrillSpot's flexible and automatically updating analytics reports, users can track and analyze various key performance indicators (KPIs) for their operations.
Drilling data streamed from WITSML is automatically stored in optimized databases within Solo Cloud. Data is alwaysavailable regardless if the original source is still active or not.
Users can access stored data includingrig activity, KPIs and hazards through Rest API, Python SDK or extractedthrough Solo Connect.
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All ROGII solutions work together in Solo Cloud, which allows users to collaborate and share data in real-time.