为了以经济有效的方式提高产量，运营商正在尝试人工举升方法以及数字技术如何提高其性能。
人工举升专家越来越多地将人工智能 (AI)、机器学习 (ML) 和自主操作添加到他们的工作流程中，因为这些数据驱动的技术表明，如果经过深思熟虑地开发和部署，它们可以产生提升效果。运营商还在研究高压气举 (HPGL) 井与使用电动潜水泵 (ESP) 进行人工举升的井的性能。最后，运营商有时必须决定是否冒险更换似乎运行良好的设备，即使其运行水平低于标准，以提高产量。
优化的气举工作流程和自主实施的 ESP 设定点正在帮助埃克森美孚和 Vital Energy 生产更多的石油。
气举是一种流行的人工举升方法，部分原因是该系统简单、可靠且操作成本低，但优化气举历来非常耗时。SPE 219553概述了埃克森美孚针对二叠纪盆地油井自动进行气举优化的方法。
In the quest to cost-effectively boost production, operators are experimenting with artificial lift methods and how digital tech can boost its performance.
Artificial lift experts are increasingly adding artificial intelligence (AI), machine learning (ML), and autonomous operations into their workflows because these data-driven technologies are demonstrating they can generate uplift when they are thoughtfully developed and deployed. Operators are also looking at the performance of high-pressure gas lift (HPGL) wells compared to wells using electrical submersible pumps (ESPs) for artificial lift. Finally, operators sometimes have to decide whether to risk replacing equipment that seems to be functioning, even if at subpar levels, in a bid to increase production.
Optimized gas lift workflows and autonomously implemented ESP set points are helping ExxonMobil and Vital Energy produce more oil.
Gas lift is a popular artificial lift method partly because the system is simple, robust, and inexpensive to operate, but optimizing it has historically been time-consuming. SPE 219553 outlines ExxonMobil’s approach to automating gas lift optimization for wells in the Permian Basin.
