SPE Online Education
Predicting Drilling Dysfunction With AI-powered Automation
Recorded On: 06/18/2019
To adapt to a rapidly changing market, oil and gas operators above all need to seek out stability in their operations, and that means eliminating, or at least minimizing, drilling dysfunction. Artificial intelligence applications offer the industry new ways to reach this goal, including:
Prescriptive maintenance: Using machine learning algorithms, prescriptive analytics use historical and current data to predict an impending asset failure, pinpoint when and why it will happen, and recommend potential plans of action.
Monitoring downhole conditions: AI algorithms use sensor data to analyze downhole conditions and immediately alert personnel when an issue arises, increasing speed and accuracy of detection.
Increased operational safety and insights: Natural language processing technology is able to extract information from unstructured data, including insights on well and reservoir performance and on potential safety hazards.
Cyber threat detection: Anomaly detection software monitors the behavior of devices within a network and flag any unusual behaviors or abnormal signals being sent out, allowing them to catch even subtler cyber attacks.
VP of Solutions, SparkCognition
Mr. Herve joined SparkCognition as the VP of Solutions. Herve is an executive with US and international success in operations, P&L, technology, business development, marketing, sales, and client relations.
Herve’s comprehensive experience in oil and gas spans large-scale project leadership, IT, engineering, manufacturing, and operation.
Herve holds multiple patents in the field of ultrasonic and has authored many technical papers. He is a member of numerous professional organizations including the Society of Petroleum Engineers. Over the years, Mr. Herve has frequently been published in Bloomberg, Oil & Gas Journal, Journal of Petroleum Technology, World Oil, The Houston Chronicle, Drilling Contractor, and is a frequent speaker on diverse management and engineering subjects.
Herve was a late comer to the AI revolution. He only started working on Artificial Intelligence in 1985. Artificial Intelligence had already been defined 30 years earlier.
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