Abstract
Abstract
ADNOC Offshore has developed a robust HSE Observation & Intervention program, leveraging digital solutions to enhance reporting culture and safety performance. This initiative has led to a significant decline in incident and injury rates, reinforcing our commitment to 100% HSE.
ADNOC Offshore collects HSE observation data from HSE Observation & Intervention Mobile application through which all our employees and contractors reports safe or unsafe acts or conditions by selecting various dropdown options and attaching photos when and where possible and applicable. However, the observation description captured in these reports is often incomplete, inconsistent, and unstructured, making it difficult to analyze and derive insights. Due to varied level of literacy and educational background the description typed in English may not be grammatically correct or even misspelled. The company wants to use machine learning to improve the data quality, risk rank, identify patterns and trends, and enhance the decision-making process for HSE management. The aim is to do real-time intervention at the time of reporting an event based on AI tool, further analysis for these unsafe acts & conditions and prevent those from becoming incidents. Due to the large volume of data, it was very challenging to analyze and identify trends and common hazards.