Integrated production optimisation and monitoring of multi-zone intelligent wells

Abstract

Multi-zone intelligent wells (I-wells) completed with interval control valves and downhole sensors divide the well completion into a number of production intervals that can be managed individually. The production rate from these wells is optimised using either reactive or proactive control strategy. Zonal inflow property values are often used to estimate the zonal multi-phase flow rates (MPFRs) to inform such control strategies. Real-time measurements of the zonal downhole pressure and temperature can be used to estimate the zonal MPFRs, which are considered the main input information to production optimisation algorithms. This paper presents an integrated control and monitoring (ICM) algorithm to maximise production from multi-zone I-wells. The algorithm includes two-level optimisation to design optimum number of required flow tests and optimise either reliability of estimated zonal production (monitoring) or oil production (control). An in-house optimiser has been developed to initiate the required flow tests to perform the ICM workflow, while active soft-sensing algorithm is used to design further flow tests required either to maximise the reliability of estimated zonal properties or maximise oil production. The algorithm was validated using a commercial transient wellbore simulator OLGA™ in which a five-zone intelligent well was modelled. The simulator results were used as inputs into the ICM algorithm to test the applicability of proposed workflow. Two different workflows of ICM and MPFR were compared in this synthetic case study, and both workflows achieve satisfactory estimates of the zonal properties. However, the ICM workflow attempts to achieve the maximum oil production with a reduced number of flow tests and results in higher cumulative oil production compared to the MPFR workflow. This confirmed that there is a potential to monitor and control zonal production simultaneously with less flow tests in comparison with applying a separate control and monitoring approach. The findings of this study showed it is not necessary to have the accurate estimation of zonal properties in order to maximise the oil production from a multi-zone I-well. The proposed ICM algorithm can also be applied in multi-well flow rate allocation of an interest production system network and optimisation of start-up of multi-zone I-wells.

Multi-Indicator Intelligent Monitoring of Clinical Observations to Reduce Cesarean Section

“…Such a series of complications increase the proportion of newborns admitted to NICU. As a qualified medical staff, we should strictly follow the instructions of Cesarean section surgery, while the public should also understand the advantages and disadvantages of Cesarean section, try as possible the process of natural delivery, and reduce unnecessary Cesarean sections; in particular, the surgical indications for Cesarean section must be strictly grasped [ 1 ].…”