Practical extremum-seeking control for gas-lifted oil production

Abstract

We present a distributed extremum seeking algorithm for the problem of production optimization of multiple gas lifted wells. The algorithm is based on "synchronization" of production performance gradients for all individual wells. It mimics the manual optimization method employed by production engineers in industry. Thus due to better understanding by industrial specialists, this method may have higher chances of being accepted in the oil and gas industry compared to other data-driven optimization methods. Performance of the proposed algorithm is illustrated by simulations.

Dither signal optimization for multi-agent extremum seeking control

“…However, this curve and its maximum are uncertain as they change with slowly varying reservoir conditions and fluid composition. This makes gas-lift a good candidate for model-free optimization methods, like extremum seeking control [12]. Omitting the fluid dynamics from the equation, this optimization problem can be formulated as finding an optimum gas injection rate u * corresponding to the maximum oil production rate, or maximum of the unknown production characteristic function f (u).…”

“…In this multi-well setting, the optimization problem becomes the optimal resource (gas) allocation problem: how to distribute the available gas injection rate between individual wells to achieve maximal total oil production from all the wells? This optimal resource allocation problem has been solved in [12] through distributed perturbation-based ESC algorithm for multi-agent systems. In this approach (as in other perturbation-based schemes), the injection rate for each individual well equals…”

“…We propose a distributed extremum-seeking scheme in which the steady-state optimizer is based on gradients synchronization [12], and the gradient estimation is performed with least-squares (LS) fits from past data [5].…”

“…Optimization is achieved by manipulating inputs through feedback of the plant outputs. Apart from applications to optimization of individual systems, ESC has been applied to optimization of systems consisting of multiple interconnected (over a network of certain topology) subsystems, resulting in a number of publications on distributed Extremum Seeking Control for multi-agent systems [9], [10], [11], [12].…”

“…Secondly, we formulate the problem of dither signals optimization in distributed ESC, which is a new class of problems within ESC for multi-agent systems. To the best of our knowledge, these problems have neither been formulated nor addressed in the prior literature on ESC (apart from our paper [12], where we briefly discuss this challenge, but only for the input signals). Thirdly, we provide a method that solves the problem of dither signals optimization for the optimal resource allocation problem.…”