My research focuses on different aspects to enhance the utility of smart completions. Several objectives have been identified in order to develop an integrated frame of work for smart well optimization with the help of distributed measurements.
This procedure starts by applying signal processing techniques to analyze the acoustic spectrum of the measurements along the entire length of the well to calculate the speed of sound in the flowing fluid mixture. The speed of sound is then used to calculate phase fractions when two fluids are present in the mixture. We then proceed by employing inverse modeling techniques to infer downhole flow rates from additional reservoir measurements including temperature, pressure and acoustic amplitude.
The calculated flow rates and phase fraction are then used in a smart well control problem. The performance of a deterministic and a stochastic optimization algorithms is evaluated. A methodology for a defensive, near real-time optimization is suggested.