Saudi Aramco Real-Time Drilling Operation Activity Recognition & Analysis Engine
- Musab Khudiri (Saudi Aramco) | William Contreras (Saudi Aramco) | Faisal Sanie (Saudi Aramco) | Tony Jovin (Petrolink International Ltd.) | Gary Hickin (Petrolink International Ltd.) | Muhammad Kashif (Petrolink International Ltd.)
- Document ID
- Society of Petroleum Engineers
- SPE Middle East Intelligent Oil and Gas Conference and Exhibition, 15-16 September, Abu Dhabi, UAE
- Publication Date
- Document Type
- Conference Paper
- 2015. Society of Petroleum Engineers
- 1.12 Drilling Measurement, Data Acquisition and Automation, 1.12.6 Drilling Data Management and Standards, 1.6 Drilling Operations
- timely and effective decision-making, A new Innovation, Activity Recognition & Analysis Engine, Real-Time Drilling Operation, identify performance operational indexes
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|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 28.00|
In recent years, the potential value of real-time drilling data has been well documented and applied across the globe within the Oil & Gas Industry. The information is traditionally used for timely and effective decision-making for drilling operations. Real-Time work processes has helped the industry by saving millions of dollars and mitigating the occurrence of critical hole problems. Drilling departments capitalize on the benefits of real-time data even in the planning stages of a well in order to prepare detailed drilling programs based on the history of any nearby wells. The easy access of real-time active and historical data assists the avoidance of incidents based on the witnessed reaction of the formation during the drilling process.
In order to do more with the data obtained, further analysis is required on the surface data to calculate the witnessed performance for certain activities on the rig site. The first step is to analyze surface data to prepare an operational recognition system. To automatically recognize drilling activities, an algorithm was developed that uses therealtime surface parameters data to calculate the current operation state, this is based on a 2-level activity classification hierarchy. The second step is then to use the results of the operational recognition system to determine key performance indictors based on the witnessed operations. It is therefore key that both calculated methods are as accurate as possible.
This paper will describe the business justification and the process formulated to generate meaningful KPI's for Saudi Aramco to allow for benchmarking and the sharing of best practices.
|File Size||1 MB||Number of Pages||9|
Richard Mohan David, Rafael Bermudez Martinez, and Gary Stefan Aillud, Abu Dhabi Company for Onshore Oil Operations, UAE - Achieving Drilling Excellence through next Generations Workflows Enabled By Integrating Historical Drilling Data and Real-Time Data - presented at ADIPEC held in Abu Dhabi, UAE, 10-13 November 2014.