Closed-Loop Feedback Control of Smart Wells for Production Optimization Using Downhole Measurements of Self-Potential

Abstract

AbstractWe present a new closed-loop feedback inflow control strategy, based on downhole measurements of self-potential (SP), and quantify the benefit of this approach in preventing or minimizing water production. Previous studies have demonstrated that downhole measurements of SP in production wells, using permanently installed electrodes, can be used to monitor and image encroaching waterfronts that are tens to hundreds of meters away from an instrumented well; field trials have demonstrated that SP data acquisition is technically feasible. However, no previous studies have investigated the use of SP measurements for closed-loop inflow control of smart wells. SP signals arise naturally during production to preserve electrical neutrality when charge separation occurs due to gradients in pressure, temperature and composition (salinity) of the formation or injected brine. We use numerical modelling as a cheap alternative to field experiments, to develop a closed-loop feedback control strategy triggered by downhole measurements of SP at a production well and compare the performance with feedback inflow control strategies based on downhole watercut measurements. Inflow control is facilitated by ‘variable’ ICVs. Our results show that closed-loop, feedback control using downhole SP measurements can yield gains in well NPV when compared to inflow control based on conventional in-well data in a single smart horizontal well. Moreover, SP-based feedback control can be used to improve well NPV over uncontrolled well production when the reservoir does not behave as predicted. Gains in NPV are close to optimal. These results are significant because they suggest a new reservoir technology that can provide a simple but effective approach to production optimization using smart wells.