Sand production is considered one of the major problems facing the petroleum industry since a small amount of sand in the produced fluid can result in significant erosion in a very short time period. Installation of a system to monitor and quantify sand production from a well would be valuable to assist in optimizing well productivity and to detect sand as early as possible. In this paper, we present a framework for sand detection and sand production rate measurement. The framework combines two modules: 1) a wireless sensor data acquisition (WSDA) module and 2) a central data fusion (CDF) module. The framework is designed to collect data from oil pipeline using acoustic sensors (SENACO AS100), flow analyzer (MC-II), and differential pressure transmitter (EJA110A) in real time. A test bed is established from ten acoustic sensors mounted on a closed-loop pipeline. The flow rate and the differential pressure are monitored as well. The sand is injected in the test bed with a constant flow and pressure. The output of the acoustic sensor is analyzed in order to calculate the sand production rate. The sand rate, flow rate, and pressure are digitized for wireless transmission using the WSDA module. The data are collected in the gateway, i.e., a laptop in our case. The CDF module is implemented in the gateway. The purpose of data fusion is to improve the system performance. Three different fusion methods, fuzzy art, maximum-likelihood estimator, and moving average filter are evaluated throughout the simulation and experimental results. The proposed framework is successfully tested and evaluated.
|Number of pages||10|
|Journal||IEEE Transactions on Instrumentation and Measurement|
|State||Published - Apr 2011|
- Data fusion
- sand production
- wireless sensor network (WSN)