By Ainur Kaken
Over the last few years, the well integrity discipline experience has seen a massive decline, with experts retiring and leaving the industry. At the same time, digitalization and artificial intelligence (AI) have rapidly evolved to become a strategic opportunity for our discipline, allowing Well integrity experience to be gained across various disciplines between completions, reservoir engineering, with exposure in drilling, production and flow assurance.
Digital tools today are a major opportunity for our well integrity discipline and are increasing the pace of learning and exposure to well integrity issues that would otherwise not be available without years of well onsite experience. Digitalization of historical log data supports the growing use of latest AI tools.
Data collection and analytics are already widely used to optimise Well Integrity Management throughout the whole well lifecycle from Basis of Design to Abandonment. Since different disciplines and expertise are involved in WI, digitalization allows optimal use of data by all parties involved, establish common language, clear communication, and have a complete workflow of all processes that can be easily visualized and updated as required. Digitalization of the daily Well Integrity work is expected to make it more robust in human error prevention and built for sharing experience across assets and organizations.
Advanced data analytics can also support in making highly complex decisions by analysing vast amounts of data in short periods of time, helping troubleshoot equipment or even take corrective actions in emergency events. Digital tools, whether it is ML and eventually AI tools, are targeted to improve overall decision-making process. These support tools are meant to supplement decision making, not to replace it.
Automation and AI can take over some of the Well Integrity work performed manually and repeatedly, such as retrieving, processing and reporting data.
Advanced analytics also enable the creation of digital replicas of the well (“digital twins”) that can be used to simulate and optimise well barriers design and evaluate its integrity.
To summarize, here are the main directions of Digitalization and AI development in Well Integrity:
- Robust database capturing information from well design and construction.
- Realtime monitoring and barriers test data uploaded in the Well Integrity database providing risk classification.
- Logging data uploaded to cloud and ML model providing cement and corrosion evaluation.
- Digital twin of well with 3D visualization capturing cement and corrosion logs along with geological / subsurface information (rock type and reservoir fluids).
- Reliability database for barriers and AI models predicting failure using ML models.