ABSTRACT
Optimizing production and understanding inflow from long horizontal wells in tight chalk reservoirs has traditionally been difficult. The horizontal sections of these wells have been typically segmented into four to eighteen zones, driven by completion, stimulation and reservoir management requirements. Surface controlled sliding side doors have been used in a number of wells to control the zones for production optimisation, but permanent down hole monitoring of each zone had not been undertaken in the Danish sector so far.
The subject of this paper is the installation and application of zonal pressure gauges and distributed temperature sensing in a recently drilled long horizontal oil producer in the Danish sector of the North Sea. Despite a very challenging trajectory and reservoir pressure variations along the horizontal section the well was drilled to 24,000 ft measured depth and equipped with permanent downhole monitoring and control capabilities. The horizontal reservoir section was segmented into five zones. In each zone a surface-controlled sliding side-door and a pressure and temperature gauge were installed. A fibre-optic cable for distributed temperature sensing (DTS) along the upper four zones to a depth of around 15,500 ft was installed as well. The upper four zones also contained an extra coiled-tubing operated sliding side door for restimulation purposes.
After completing the well each zone was matrix acid stimulated. Stimulation monitoring with DTS allowed quantification of zonal acid coverage and identification of the scope for re-stimulation. During initial production of the well the pressure and temperature gauges in each of the zones proved valuable for start-up operations. Cross-flow between zones was identified and this knowledge was used for improved management of commingled zonal production.
This paper describes how temperature and pressure data from each zone has been used for well production optimisation, in sometimes unexpected ways. The combination of being able to react without intervention using the real-time data has proven to be critically important and supported more efficient operations.
