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AI-Driven Human Error Probability Reduction in Well Construction

A leading energy company managing well construction projects faced significant safety risks and operational inefficiencies due to human errors. The lack of standardized risk assessment models led to inconsistent safety practices, increasing the likelihood of incidents, delays, and regulatory non-compliance.

Project duration:

4 months

Output:

Risk and resilience optimization

The challenge

  • Inconsistent risk assessment methods leading to unreliable safety evaluations.
  • Frequent safety incidents caused by human errors during critical drilling operations.
  • High operational costs and downtime due to reactive risk mitigation approaches.
A predictive human error probability (HEP) model was developed and implemented to:
  • Integrate historical incident reports, expert knowledge, and real-time operational data.
  • Identify error-prone tasks and dynamically estimate human error probability.
  • Provide actionable insights for improving safety protocols and risk mitigation strategies.

Impacts

Success stories

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