Oilfield operation and production management particularly in extreme geographic location is still a challenge from optimisation and cost-effectiveness points of view. Further, data handling and storage attract huge capital investments with little realisation of ultimate goal of effective and efficient handling and management. In this work, we propose an artificial intelligence technique of oilfield operation monitoring and intervention. Real time data generated from remote and challenging oilfields is used to decipher the performance of operational processes. We integrate the meta-heuristic optimisation searching speed of an enhanced algorithm with the robustness of fuzzy logic reasoning; based on the degree of membership functions rather than exact or extreme conditions, and the learning capability of neural networks, to derive the required intelligence. This allows a predictive and proactive intervention in oilfield operations and management. © Copyright 2016, Society of Petroleum Engineers.
|Number of pages||10|
|Publication status||Published - 6 Sep 2016|
|Event||SPE Intelligent Energy International Conference and Exhibition - AECC, Aberdeen, United Kingdom|
Duration: 6 Sep 2016 → 8 Sep 2016
|Conference||SPE Intelligent Energy International Conference and Exhibition|
|Period||6/09/16 → 8/09/16|