Optimizing oil and gas production by intelligent technology

Intelligent completion technology, namely permanent downhole monitoring and flow control devices that allow continuous monitoring and control of well flowing system, has become more and more popular today in oil and gas wells to assist well and reservoir performance management. The applications of intelligent well today are much beyond the original vision of the technology that measurement and control become possible without intervention and their associated costs by installing permanent downhole monitoring and flow control devices connected to the surface. In addition to these advantages, the technology has been used to optimize gas lift and ESP systems, sand control, formation damage control, water breakthrough, gas coning problems, and crossflow eliminations. This paper summarizes the current available intelligent technology, describes the production optimization workflow process from data acquisition to optimization and control, and focuses on a discussion of the effective approach of deploying the technology for different types of well completions and drainage volume characteristics. The majority of previous publications on intelligent completion technology have been in two areas: (1) identification of well production problems; and (2) control of the well flowing system to meet operational constraints and limits and/or improve existing well performance to higher levels. Many field examples showed that the monitoring function and the control function of intelligent completions have been applied independently. The efficiency of the integrated system could be greatly improved if monitoring and control systems are interactively integrated. Monitoring can directly guide control schemes and validate the results of their executions. The examples in the paper show that with simple interpretation of monitored data, control of well operation can be less time consuming and more effective. Likewise, downhole monitoring needs to be used with control systems so that the problems identified by monitoring systems can be treated accordingly. The approaches presented in the paper will help to maximize the value of intelligent completion.