One of the main challenges for Intelligent Field engineers is handling large amount of data stream in real-time. Finding meaningful patterns among this huge amount of data is just like trying to find a needle in a haystack. Every day reservoir and production engineers are being bombarded with streams of massive amounts of real-time data coming from all kinds of Intelligent Field equipment’s including but not limited to Permanent Downhole Monitoring Systems (PDHMS), Multiphase Flowmeters (MPFM), MicroMotion Meters, Wellhead Gauges, Smart Well Completion (SWC), and Electrical Submersible Pumps (ESP). They spend significant amount of time and effort looking at the trends and analyzing the data to find anomalies. Moreover, the existing systems for data cleansing and summarization are based on batch processing, hence, engineers cannot make the right decision on time and they do not have the mechanism to instantly detect interesting patterns in incoming data.
The objective of this paper is to share Saudi ARAMCO’s experience with Complex Event Processing (CEP) as an emerging technology that is design for low-latency and high-throughput event processing for data stream. This paper addresses the architecture, the implementation, and the benefits of CEP as a solution for the Intelligent Field. The implementation will covers three common applications of CEP namely real-time data cleansing, pattern detection, and event driven computation. Data cleansing covers handling out-of-bound, negative, and frozen values. Patten detection enables the detection of anomalous behavior in the data stream, such as unusual buildup or drawdown in well pressure in real-time. Event driven computation is triggered by an event in the field, such as a change in downhole pressure to perform advance calculation logic such as average reservoir pressure. Implementing CEP will help reservoir and production engineers obtain clean data in real time and receive notification in case of any significant event detected.