Improving reservoir performance using intelligent well completion sensors combined with surface wet-gas flow measurement

Abstract

Reservoir performance, in addition to day-to-day well performance, needs to be evaluated during the life of a well. The production logging tool (PLT) is conventionally designed to provide a full set of data measurements in producing wells to evaluate well and reservoir performance. Depending on the well conditions and location, running conventional PLTs may be difficult, impossible or expensive. Therefore, an alternative approach that can be applied in lieu of PLT operations—to obtain information similar to PLTs for better reservoir management—and that can optimise reservoir production performance is desireable. Data acquisition techniques such as downhole pressure/temperature gauges, fibre optic sensors at reservoir conditions and wet-gas flow meters at the surface have been considered as a viable alternative. Such data acquisition techniques help to increase flexibility in the field development and reservoir management of problematic wells with well completion technologies such as multi-lateral, horizontal and artificial lift.

This study focused on the development of an alternative method of analysing problem well data on the basis of downhole pressure and temperature data collected at reservoir conditions. The proposed model has been based on the Joule-Thomson effect and radial heat and fluid flow equations to solve the transient wellbore pressure and temperature equations. It is expected this model can be used to analyse intelligent wells completed with downhole pressure and temperature sensors, and facilitate the monitoring of wells and reservoir performance without any PLT operation, especially for complex fields.