SparkCognition Case Studies Cognitive Analytics for Oil and Gas
Cognitive Analytics for Oil and GasSparkCognition
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Analytics & Modeling - Big Data Analytics
Analytics & Modeling - Machine Learning
Analytics & Modeling - Predictive Analytics
Oil & Gas
|[Process Optimization - Remote Diagnostics]|
SparkPredict detects both Stuck Pipe and Wash Out conditions with high accuracy.
|[Efficiency Improvement - Operation]|
SparkPredict provides an in-context advisory system technicians can use to quickly find documents and other digital resources to address issues, automatically provide meaningful remediation steps, and seamlessly communicate and share data with team member
|[Efficiency Improvement - Maintenance]|
For Electrical Submersible Pumps (ESPs), SparkPredict predicts failures days in advance.
The average lead times for detection of these failures is: Stuck Pipe: 1.2 hours, Wash Out: 2.3 hours.
SparkCognition targeted two failure modes, accounting for 85% of all ESP failures, and were able to provide the following median forewarning: Electrical Short: 5.5 days, Mechanical Breakdown: 6 days.