由于生产监控系统产生大量数据，运营商正积极探索处理海量数据的方法。在此过程中，他们通过提取知识并利用这些有用的新信息来了解运营状况，从而获得新的洞察。创新技术的部署取代了对实时数据的持续人工处理，使分析师能够将宝贵的时间用于调查运营问题并采取纠正措施。

随着生成式人工智能（AI）和大型语言模型的进步，人们已在复杂的分布式环境中（例如海上油气生产）观察到利用智能体AI自主处理海量异构数据的现象。此外，人们也特别关注更环保、更节能的硬件，以减少其作为生产监控单元时对环境的影响。

OTC 36110 论文提出了一种数字解决方案，通过协调一个直观、高效的监控系统来监控系统性能并识别气举井的优化机会。

Because of the influx of large data from production-monitoring systems, operators are getting creative in dealing with the vast amounts of data. In the process, they learn the state of their operations by extracting knowledge and taking advantage of the useful, newfound information to divulge new insights. Innovative technologies are deployed to replace any continuous, manual processing of real-time data, while the analysts can spend most of their precious time investigating and taking corrective actions in their operations.

With the advancements of generative artificial intelligence (AI) and large language models, the use of agentic AI to autonomously deal with vast, heterogeneous data has been observed in complex, distributed environments such as offshore oil and gas production. Greener, energy-efficient hardware also has been notably pursued to reduce environmental footprints while functioning as production monitoring units.

A digital solution has been presented in paper OTC 36110 to monitor system performance and identify optimization opportunities in gas lifted wells by orchestrating an intuitive, efficient surveillance system.