Since the inception of Intelligent Energy over a decade ago, there has been a gradual transition from the collection and visualization of large data sets through to the intelligent analysis and interpretation of data. A recent drive towards automation has evolved from the desire to streamline ongoing activities, reduce exposure to human error and continuously position operations at the optimum operating point.

Attempts to automate the optimization process, whether through closed loop optimization or multi-variable control, have largely focused on the facilities. This approach has merit when production is on plateau, as the rates will typically be constrained by the processing capacity of the facilities. As production declines, the handling capacity of the facilities becomes less of a burden and the deliverability of the well stock gains prominence. Productivity is now constrained by well uptime along with the health of the completion.

Adequate control of the drawdown can have a positive impact on both the health of the completion and on the uptime of the well. For weak wells, the well must be beaned up at a certain rate to prevent liquid loading. Control of the drawdown is therefore paramount in ensuring a successful restart. For wells that cut water or free gas and transect multiple reservoir layers, the drawdown will drive coning and promote cross flow. As both are detrimental to production, overall productivity is driven by the ability to control and optimise the drawdown. Finally, if the rock is poorly consolidated, rapid fluctuations in the drawdown can have a detrimental impact on the rate of sand production, screen erosion and skin growth.

Within this paper, the value of controlling the drawdown will be presented along with a control solution that has proved effective at controlling the drawdown during start-up, continuous production and ramp down to within 5 psi.

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