With the advancement in drilling and production technologies, deeper and more challenging formations are drilled every day. A pivotal part of sustaining this advancement is to permanently monitor the reservoir. While PDG (Permanent Downhole Gauges) have been in use since 1960s, handling and interpreting tons of rows of data has always been cumbersome. Moreover, the gauges have to be dependable enough to sustain bottom hole conditions for their lifetime (Schlumberger, 2015). Focusing attention to artificial lift applications, downhole P/T data plays a huge role in assessing if the bottom hole conditions are ideal in bringing the fluid to the surface, even if the reservoir has a high deliverability. Interestingly, completion design for submersible pumps nowadays includes downhole sensors for pressure/temperature reading, which opened doors to multiple utilization ideas and innovations. Baker Hughes in 2014 introduced a virtual flow meter concept that recorded pump parameters to optimize the working of an ESP up to 90% accuracy. Standard techniques to monitor flow are not only expensive to operate but also not readily available at all times. The following thesis takes inspiration from their approach to go one step further and gain more knowledge about the reservoir itself using the pump parameters. Through the experimental work, this thesis aims to understand how the reservoir behaves during production and shut in phases to estimate the inflow performance of the well. Estimating accurate reservoir pressures after shut in periods also helps in monitoring the productivity index of the reservoir in study.