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A Genetic Algorithm for Gas Lift Optimization With Compression Capacity Limitation

机译:压缩容量限制的气升优化遗传算法

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Artificial Gas Lift consists of gas injection into the tubing to reduce hydrostatic pressure loss. The oil produced from each well is a function of the gas injection rate. Some wells exhibit unstable behavior for low gas lift flow rates and the excessive use of gas causes a reduction in the production of oil due to high friction losses. Therefore the gas lift flow rate must be kept in a bounded interval. For a given amount of gas used, the production of oil varies significantly between wells, so the objective of gas lift optimization is to allocate a limited amount of gas to a number of wells in order to obtain the maximum oil production (or profit). Evolutionary algorithms were applied to achieve optimal production rates and decide which well must be closed when the compression capacity is severely reduced. The FPSO considered in this study is equipped with three _choke2Fcompressors to produce 16 wells with gas lift and export gas. Eventually, one or two compressors can have a downtime due to maintenance requirements or failures. In this case, at least one well has to be closed. The algorithm was developed to optimize the production when the compression capacity was reduced and decide which well should be shut-in. It takes into account not only the total amount of gas available but also the gas lift pressure, which can change over time. The algorithm solved a practical gas lift optimization problem and was able to automatically determine which wells had to be closed in order to produce the maximum amount of oil whenever the total gas available was not enough to simultaneously operate all wells. For the cases where the total gas available was high enough that all wells could produce, the results obtained by this genetic algorithm were equivalent to any ordinary optimization algorithm. The production optimization is an important issue even during abnormal operation conditions. The water cut increases with the aging of wells and the gas lift flow rate demand also increases. Severe compression limitations are undesirable but they can eventually occur.
机译:人造气体升降器由气体注入管道组成,以降低静压压力损失。从每个孔产生的油是气体注入速率的函数。一些孔表现出低气体升力流量的不稳定行为,并且过度使用气体导致由于高摩擦损失导致油的生产。因此,气体升力流量必须保持在有界间隔。对于所使用的给定量的气体,井之间的油产生显着变化,因此气体提升优化的目的是将有限量的气体分配给许多井以获得最大的油生产(或利润)。应用进化算法以实现最佳的生产率,并在压缩容量严重减少时,决定必须关闭。本研究中考虑的FPSO配备了三种_Choke2FCompressors,以生产出燃气升降和出口气体的16个井。最终,一个或两个压缩机由于维护要求或故障而具有停机时间。在这种情况下,必须至少关闭一个孔。该算法是开发的,以优化当压缩容量减少并决定应关闭时的生产。它不仅考虑了可用的燃气总量,也考虑到气体提升压力,这会随着时间的推移而变化。该算法解决了实用的气体升程优化问题,能够自动确定必须关闭哪个井以便在可用的总气体时产生最大的油量,以同时操作所有的井。对于足够良好的全部气体的总气体可以产生的情况,通过这种遗传算法获得的结果等同于任何普通优化算法。即使在异常运行条件下,生产优化也是一个重要的问题。随着井的老化而随之而来的水削减,气体提升流量需求也增加。严重的压缩限制是不可取的,但最终可能发生。

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