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.

Exebenus ML Agents focus on high-value predictive scenarios, such as differential sticking, hole cleaning and well bore geometry.

Key benefits
  • Pre-empt and predict drilling events
  • Capture lessons learned; standardize best practices
  • Learn from past and current experience to continuously improve performance
  • Improve planning and expand knowledge

Exebenus Pulse ML agents are specifically designed for use in operations center environments, ML agents

  • consume real-time WITSML data and provide WITSML data outputs
  • integrate with and visualize in existing real-time operations software to minimize training needs
  • support operations center workflows to monitor, analyze, and advise rig crews

The Exebenus Pulse ML Agents can be deployed stand alone or as agents in Exebenus Pulse.

 

Benchmark performance. Continuously improve.

Exebenus Pulse scours your digital library as well as third-party real-time databases to extract maximum value from current and historical data. Exploring past events, comments, comparable BHA combos, and WITSML data and formation data, Exebenus Pulse helps you benchmark and measure your operational performance. By logging decisions and capturing lessons learned today, you identify the best performing products and establish new best practices that will guide your teams worldwide in future projects.

Because Exebenus Pulse automatically logs and lets you flag events during operations, it reduces the time your team needs to spend doing post-operational reports. Reporting becomes a quick and concise process that focuses on the essentials, such as deviations from plan.

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Take a closer look at Exebenus Pulse

Exebenus Pulse connects each stage of your planning and execution.

 

The Exebenus services team works to ensure that your company’s workflows are properly integrated and digitalized when deploying and implementing the Exebenus Pulse solution. Exebenus Service


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Past lessons learned are incorporated in the correct procedure and available in context of operation step.
New lessons learned that are flagged during the operation can be reviewed post operation and added to the company library of lessons learned as appropriate.
In post-operation review, lessons learned with broader relevance are assigned to e.g. operation, rig, product model, and added to any new procedure where these assignments are matched.