Playbooks Supplements

Artificial Lift Techbook 2016

Issue link: http://yearbook.epmag.com/i/671218

Contents of this Issue

Navigation

Page 38 of 47

ARTIFICIAL LIFT TECHBOOK: CASE STUDY EPmag.com | May 2016 | 37 automation solution to optimize lift gas at a well. Controlling the gas-lift injection to maximize pro- duction is more complicated when a production area has limited resources such as lift gas that is shared or must be allocated between multiple wells (Figure 3). It has been common practice to initially set the gas injection rates based on expected well produc- tion. However, the lift gas rates remain static and are infrequently adjusted as production changes occur in each well. In some cases well production operators overseeing a production area might adjust the gas injection rates based on weekly or monthly production data making it virtually impossible to respond to continuously changing well perfor- mance conditions. Optimal allocation of limited lift gas between multiple wells is even more challenging since each well is unique and has differing produc- tion characteristics that change with time. This argues for closed loop control of lift gas. Automatic fow control valves and fowmeters must be connected to a control system platform such as a SCADA system. The operator sets a lift gas fow rate to the controller instead of manually stroking the lift gas valve. The next step in the hierarchy is for a supervisory controller to adjust the set point. A gas- lift optimizer can set the lift gas for a single well to maximize production of the well. However, a multi- well gas-lift optimizer can optimize the allocation across multiple wells. That can produce real benefts. There is always concern about closed loop control down at the well pad, which might be unattended for periods of time. So any optimizer solution must be able to operate in open loop or advisory mode. In this case the optimizer does not directly change the lift gas fow set point. Rather it alerts the operator to a need to change the set point and the operator makes the change. Closed loop or open loop, the optimizer is slow compared to a dynamic controller. It recognizes when a constraint is about to be violated and recommends (or makes) an immediate change to the lift gas fow set point, but otherwise it is slowly and continuously seeking the optimal allocation of lift gas. This slow and steady approach minimizes any disruption or intro- duction of variability to the process. This tends to be "easier" on the reservoir than making periodic step changes typical of a manual operation. Boosting production at multiwell sites The foundation for the GLO solution is based on gathering accurate and reliable real-time data that measures process related measurements for each well in the area to be optimized. These might include various pressure and fow measurements FIGURE 3. Maximizing production is more compli- cated when a production area has lim- ited lift gas that must be shared or allo- cated between multiple wells. Oil flow rate (Q) = Revenues ($) Gas lift injection rate (L) = Operational cost ($) FIGURE 2. Increasing gas lift injection rate above a certain value might negatively impact the production rate as the backpressure created by the lift gas exceeds the lifting effect. Lift gas Production separator

Articles in this issue

Links on this page

Archives of this issue

view archives of Playbooks Supplements - Artificial Lift Techbook 2016