Abstract
Abstract
With deeper and more complex wells being drilled every year to gain access to reserves, experience and knowledge are the keys for minimizing associated risks and reducing costly non-productive time.
Over the last decade, drilling optimization processes and practices have delivered substantial drilling improvements in many different environments worldwide. This has been based on a continuous improvement cycle, consisting of four distinct phases: planning, execution, post-well analysis and lessons learned, which essentially yields personnel experience and knowledge.
Given the current demographics in the oil industry, which is heavily biased towards the 50+ years of age, the "big crew change" is just around the corner. As more and more graduate engineers enter the industry the resulting experience gap needs to be bridged.
Within the controlled environment of the office, graduate engineers are offered guidance and support during the planning phase, however real-time execution requires timely specialist advice and guidance to mitigate drilling hazards. Drilling hazards provide tell-tale signs, and if these signs are captured early, corrective actions can be taken to reduce or completely avoid their impact, reducing operational risk and well delivery costs.
This paper describes an expert system that has been developed to offer immediate guidance to support the delivery of specific real-time specialist advice – based on the system’s self-learning of previous drilling events. The expert system monitors real-time drilling parameters and uses case-based reasoning (CBR) to recognize and capture current incidents that are similar to those that have occurred in the past.
The system can be used to prevent drilling problems before they occur with real-time case-based reasoning for enhanced risk assessment and hazard mitigation. The paper will review examples of packoffs, stuck pipe and lost circulation that have been mitigated.
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