Abstract

State-of-the-art anomaly detection systems deployed in oilfields are expensive, not scalable to a large number of sensors, require manual operation, and provide data with a long delay. To overcome these problems, we design a wireless sensor network system that detects, identifies, and localizes major anomalies such as blockage and leakage that arise in steamflood and waterflood pipelines in oilfields. A sensor network consists of small, inexpensive nodes equipped with embedded processors and wireless communication, which enables flexible deployment and close observation of phenomena without human intervention. Our sensor-network-based system, Steamflood and Waterflood Tracking System (SWATS), aims to allow continuous monitoring of the steamflood and waterflood systems with low cost, short delay, and fine-granularity coverage while providing high accuracy and reliability. The anomaly …

Date

2011

Authors

SunHee Yoon, Wei Ye, John Heidemann, Brian Littlefield, Cyrus Shahabi

Journal

IEEE network

Volume

25

Issue

1

Pages

50-56

Publisher

IEEE