Abstract
Intelligent well system technology enables continuous downhole monitoring and zonal production control. Knowledge of zonal multiphase rates in real time gives the ability to flexibly respond to changes in the well and reservoir performance; leading to recovery optimization, etc. Frequently, only pressure and temperature data are measured downhole. Solution of the zonal flow rate calculation problem solely on the basis of these values is possible using mathematical optimization methods along with soft-sensing tools.
This paper presents a method of automatic zonal rate allocation for intelligent wells based on measured downhole pressure and temperature data. A group of mathematical optimization algorithms is used for the rate allocation at a particular time. The inverse problem is solved by matching the calculated, downhole pressure and temperature values with those measured (possibly with limited accuracy) at certain positions.
A further step illustrates the application of soft-sensing methods to data measured in real-time. The potential for system parameter calibration and influx detection will be discussed. The resulting, zonal flow rate allocation techniques are tested on synthetic and real data, which illustrates their use as the basis of a comprehensive workflow for the control of intelligent wells and fields.
