Exebenus Pulse Analyze and improve
Use your experience. Predict risk.
Making informed decisions requires a clear, moment-to-moment understanding of the situation. Important information may be buried in previous experiences or in real-time data. During execution, machine learning agents are fed real-time data to recognize deteriorating conditions that may lead to events such as stuck pipe and well control issues. Pre-approved mitigation steps can be taken to avoid downtime.
Predicting drilling events by the smart use of data
The Exebenus Pulse Machine Learning (ML) Agents pre-empt and predict events that may result in nonproductive time. The agents enhance the value of collected data by providing dynamic trends and models. They improve offset well analysis by identifying unreported near misses and providing guidance on drilling parameters to optimize performance.
Exebenus Pulse ML Agents use data that is readily available in all well operations to provide predictive analysis and avoid undesired events. By using an engineering approach to ML, engineers can easily understand and trust the results.