| Popis: |
Current levels of Reservoir Surveillance technology associated with intelligent well completions, such as fibre optics and permanent downhole gauges, create an increasing flow of data. Conventional routine Reservoir Surveillance tools do not help the knowledge worker anymore to cope with high-frequency real-time data. Overloaded with data handling work, the knowledge worker in our industry is not capable to reveal the great potential inherent in this data. A radical different work process and new applications of Data Mining technologies are presented to support the industry's next goal – The Smart Field. A learning Data Mining approach is presented to detect discrepancies from expected trends and patterns. These trends and discrepancies are then translated into business rules to enable the closed-loop control of oil and gas assets. Lessons learned are presented and necessary future developments are identified. |
