Smart Wells and Resevoir Monitoring


So-called ‘smart’ or ‘intelligent’ wells are equipped with downhole sensors to monitor well and reservoir conditions, and valves to control the inflow of fluids from the reservoir to the well.  This combination of monitoring and control technology has the potential to significantly improve oil and gas recovery. However, considerable challenges remain in the formulation of control strategies to operate the valves during production, particularly when there is uncertainty associated with the reservoir description.  The SWARM Group focuses on two key research areas:

  1. The development of downhole reservoir imaging technology to monitor changes in water saturation or other reservoir parameters of interest at some distance from an instrumented well. Reservoir imaging facilitates proactive inflow control, in which control actions are taken before adverse changes in flow reach the well. Our focus is currently on monitoring using downhole measurements of spontaneous potential.
  2. The development of control strategies for smart well operations which are based on feedback between downhole measurements and valve settings, rather than the predictions of well and reservoir models. The problem with model-based control strategies is that models are always uncertain to some degree. Even history-matched models can lack predictive value, especially at the temporal and spatial resolution required to optimize inflow to a well.

  Smart wellsSmart wells 2Smart wells 3

Early water breakthrough at the heel of a conventional well (left above) and improved sweep facilitated by reactive control (left below).

Finite-element mesh (centre) used to simulate the streaming potential measured at a well during oil production.  Location of well where mesh is finest.

Simulated streaming potential in a homogeneous (right above) and layered (right below) reservoir at early (left) and late (right) times. Hot colours denote large SP.

Read about our research

The Engineer Magazine

Contact us

Matthew Jackson (