一致性是钻井自动化未来的关键

哈里伯顿和 Vital Energy 的钻井专家认为人工智能和机器学习在油田的实施具有潜在的变革性。

石油和天然气行业已经从自动化中获益,正处于技术革命的风口浪尖,钻井技术的进步和人工智能将重新定义运营标准。

哈特能源公司最近在德克萨斯州米德兰举行的石油执行会议暨展览会上,行业专家深入探讨了两者如何重塑该行业的运营格局。

最前沿:钻井自动化。

自动化提供一致性

哈里伯顿钻井自动化生产经理 Shashi Talya 表示,自动化钻井有潜力提高性能、井眼质量和井位,同时提供通常难以通过传统方法实现的一致性水平。

“一致性是一个关键词,我认为自动化、人工智能、机器学习将帮助我们实现这一目标,”他在 11 月 16 日的小组讨论中说道。塔利亚的小组成员一致认为,在钻探过程中始终保持高水平的效率比渴望在每次钻探活动中打破记录更可持续、更容易实现。

塔利亚说,挪威哈里伯顿公司进行的一项研究表明,一致性可以在多大程度上改善钻井作业。虽然在没有自动化的情况下机械钻速平均增加了 23.4%,但在部署自动化钻井后,产量明显增加。三年来收集的研究数据也显示了井位精度的提高。

“我们确实看到了性能的提高……每个季度当我们查看客户的数据时,我们都会看到持续的改进,”他说。

塔利亚说,将人工智能集成到钻井系统中也有利于石油开采。与技术合作伙伴的合作带来了创新,例如钻井作业期间的自动化连接,这是伊拉克哈里伯顿项目的一部分。

在该项目期间,哈里伯顿使用了 Nabors 设计的智能系统,塔利亚将其比作 iPhone 的更新。“把它想象成把你的手机带回商店,现在你有了一个更智能的操作系统,你的 iPhone 现在突然变得更加自动化。”

升级后的智能系统可以更好地控制关键参数,降低运营过程中的风险,并将 ROP 提高 40% 以上。

Vital Energy Inc.资产优化经理 James Meek 表示,尽管目前人工智能的实施是该行业的一个新领域,但它与过去的井优化类似。

“我们以这种“测量、改进、自动化”的方式来思考世界,这与我们在“20 年代、30 年代、40 年代和”时期优化石油和天然气的方式没有什么不同。 “50 年代,”他说。“作为一个行业,我们做的第一件事是,我们得到的测量和数据是否准确?”如果不是,我们需要自动发出警报,让它回家并创建一个任务一种自动化的时尚。我们内部有算法可以为我们做这件事。作为一个行业,我们接下来要做的就是尝试使用当前的方法来改进资产。”

人工智能慢慢赢得信任

米克说,虽然与其他技术改进一样,石油和天然气公司已经改变了采用某些创新的方式。例如,该行业在人工智能方面仍处于“成熟空间”。而且,在成熟的道路上不可避免地会遇到坎坷。

准确性仍然是人工智能的一个大问题,操作员仍然更有可能相信人类能够处理不断变化的油田环境。

AlphaX Decision Sciences创始人兼首席执行官 Sammy Haroon表示,人工智能不像高中科学方程那样,在输入相同的情况下总是得出相同的答案。

“物理学在 100% 的时间里是 100% 准确的,或者说,当系统被完整描述时,它们是 100% 准确的,”Haroon 说。“我从事地下业务。地下是一个复杂的系统。人工智能永远不会 100% 准确,也不会在 100% 的时间准确,但它正在变得越来越接近。”

哈龙说,即使存在误差(通常很少),机器学习实际上也是在学习,因为向软件提供的数据数量和质量很高。

随着自动化的注入,钻井性能显着提高。行业数据创新团队发挥着关键作用,利用强大的数据架构和高质量的数据来提高人工智能模型的准确性和可靠性。

“从 1865 年在德克萨斯州钻出第一口井到 1998 年 Mitchell Energy 进行第一口滑水压裂,技术一直是(石油和天然气行业)的支柱,”Haroon 说。“在 21 世纪,[我们] 的使命是将人工智能引入石油和天然气领域,带着这一使命,我相信我们不是一个 25 年的行业,也不是一个 50 年的行业。我相信人工智能有能力通过其提供的所有功能使我们成为一个 200 年的行业。”

原文链接/hartenergy

Consistency is Key to the Future of Drilling Automation

Drilling specialists at Halliburton and Vital Energy see the implementation of AI and machine learning in the oilfield and as potentially transformative.

The oil and gas sector, already reaping the benefits of automation, is on the cusp of a technological revolution, as drilling advances and AI are poised to redefine operational standards.

Industry experts delved into how both are reshaping the operational landscape of the sector during Hart Energy’s recent Executive Oil Conference and Exhibition in Midland, Texas.

At the forefront: drilling automation.

Automation delivers consistency

Automated drilling has the potential to improve performance, wellbore quality and well placement, said Shashi Talya, production manager of drilling automation at Halliburton — all while providing a level of consistency normally difficult to achieve through traditional methods.

“Consistency is a key word, and I think that’s where automation, AI, machine learning will help us get there,” he said during his Nov. 16 panel. Talya’s fellow panelists agreed that consistently maintaining high levels of efficiency during the drilling process is a more sustainable and achievable goal than aspiring to break records during each drilling campaign.

A study conducted by Halliburton in Norway showed just how much consistency can improve drilling operations, Talya said. While ROP increased an average of 23.4% without automation, there was a clear increase in well delivery when automated drilling was deployed. Study data collected over the course of three years also showed an increase in well placement accuracy.

"We definitely see an increase in performance... every quarter when we look at the data from the customer, we see continuous improvement," he said.

Integrating AI into rig systems also benefits the oil patch, Talya said. Collaborations with technology partners resulted in innovations, such as automated connections during drilling operations, that were part of a Halliburton project in Iraq.

During the project, Halliburton used a smart system designed by Nabors, which Talya compared to an iPhone update. “Think of it as taking your phone back to the shop and now you've got a smarter operating system, and your iPhone is now suddenly far lot more automated.”

The upgraded smart systems provided better control over critical parameters, mitigating risks during operations and improving ROP by more than 40%.

Even though the current implementation of AI is a new frontier for the industry, it is similar to well optimization of the past, said James Meek, manager of asset optimization for Vital Energy Inc.

“We have this ‘Measure, Improve, Automate’ way to think about the world, that is no different than how we've been optimizing oil and gas in the ‘20s, ‘30s, ‘40s and ‘50s,” he said. “The first thing that we did as an industry, we said ‘Is the measurement and the data we're getting accurate?’ If not, we need to automate an alert, let it call for home and create a task in an automated fashion. We have algorithms internally that do this for us. The next thing that we do as [an] industry, we try to improve the asset using current methods.”

AI slowly gaining trust

While on a familiar path as other technological improvements, oil and gas companies have shifted how they adopt some innovations, Meek said. The industry, for example, is still in an “immature space” regarding AI. And, inevitably, there are bumps along the way to maturity.

Accuracy remains a big issue for AI, and operators are still more likely to trust humans to handle the ever-changing oilfield environment.

Sammy Haroon, founder and CEO of AlphaX Decision Sciences, said AI doesn’t work like high school science equations that always arrive at the same answer given the same input.

“Physics is 100% accurate, 100% of the time – or 100% of the systems when they are completely described,” Haroon said. “I'm [in] the business of subsurface. Subsurface is a complex system… artificial intelligence is never 100% accurate or accurate 100% of the time, but it's getting closer.”

Even with inaccuracies, of which there are often few, machine learning is actually learning, due to the amount and quality of data being provided to the software, Haroon said.

Drilling performance is showing marked improvement with the infusion of automation. The industry's data innovation teams play a pivotal role, leveraging robust data architecture and demanding high quality data to elevate the accuracy and reliability of AI models.

“From the first well drilled in Texas in 1865 to Mitchell Energy's first slick water frac in 1998, technology has been the backbone [of the oil and gas industry],” Haroon said. “In the 21st century [we] have a mission to bring artificial intelligence to oil and gas, and with this mission I believe we're not [a] 25-year sector, we're not a 50-year sector. I believe artificial intelligence has the strength to make us a 200-year sector through all the capabilities that it offers.”