数据科学是石油和天然气的未来

   2023-06-08 互联网综合消息

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核心提示:据美国钻井网站2023年6月5日报道,数据科学是石油和天然气行业的未来,这是数据解决方案公司Prescient的创

据美国钻井网站2023年6月5日报道,数据科学是石油和天然气行业的未来,这是数据解决方案公司Prescient的创始人兼首席执行官Andy Wang在接受美国钻井网站记者采访时表示的。

Wang告诉美国钻井网站记者,“数据科学将极大地提高油气作业的能力,从而提高效率、降低成本、增强安全性,并授权于IT团队和现场团队的员工”

在采访中,Wang强调,数据科学包括许多数据工具,包括机器学习,他指出这将是石油和天然气未来的重要组成部分。当被问及他是否认为越来越多的石油公司会采用数据科学和机器学习时,Wang对这两个问题都做出了积极的回应。

当被问及石油和天然气行业数据科学的一些缺点时,Wang告诉美国钻井网站记者,数据科学需要向数据驱动的文化转变,需要了解如何应用正确的数据科学来解决正确的问题。

当美国钻井网站记者询问目前石油和天然气行业对数据科学专业人员的需求是否很高时,Wang说:“我们看到需求正在增加。”

当美国钻井网站记者向总部位于休斯敦的Piper-Morgan Search的创始人兼总裁Gladney B. Darroh提出同样的问题时,Darroh告诉记者:“人们对该领域的兴趣正在增加。”

Darroh补充说:“我预计这种兴趣将转化为对数据科学专业人员的不断增加的需求,无论是直接招聘还是签订合同。”

“目前,我还没有看到需求激增,但我已经收到了越来越多的公司咨询。这绝对是一股正在积聚的浪潮。”Darroh继续说道。

位于路易斯安那州的OneSource专业数据搜索公司总裁戴夫·芒特表示,至少从该公司的油气运营公司客户群来看,对专业数据科学家的需求“在过去的两到三年里有所放缓”。

芒特说:“至少从我们看到的情况来看,需求峰值是在油价暴跌和疫情暴发之前。”

他补充说:“需求似乎主要来自陆上非常规页岩公司,这些公司处于高增长模式,拥有数百口井,他们有很多数据点可以进行抽样和统计,而不是地质分析公司、生产作业公司和矿产开采公司。”

“我们不确定对专职数据科学家的需求下降是在整个能源供应链上,还是仅仅在我们服务的领域。”芒特继续说道。

芒特继续表示:“我们看到,对能够在传统岗位上整合高端统计和数据分析的员工的需求越来越大,比如生产分析师、生产工程师和油藏工程师。”

Andy Wang最近参加了在得克萨斯州休斯敦举行的美国石油工程师协会(SPE)国际墨西哥湾岸区数据科学大会,美国钻井网站总编也出席了此次会议。此次会议被称为SPE-GCS数据分析研究小组的年度旗舰活动,来自能源和技术部门的代表参加了这次活动。

李峻 编译自 美国钻井网站

原文如下:

Data Science is the Future of Oil and Gas


That’s according to Andy Wang, the Founder and Chief Executive Officer of data solutions company Prescient, who made the statement during an interview with Rigzone.

“Data science will increase the capability of oil and gas operations dramatically to improve efficiency, reduce cost, enhance safety, and empower employees from the IT team to the field team,” Wang told Rigzone.

In the interview, Wang highlighted that data sciences includes many data tools, including machine learning, which he noted will be an important part of the future of oil and gas. When asked if he thought more and more oil companies would adopt data science, and machine learning, Wang responded positively on both counts.

Asked to list some drawbacks of data science in the oil and gas world, Wang told Rigzone that data science requires a shift to a data driven culture and requires the understanding of how to apply the right data science to solve the right problems.

When Rigzone enquired if data science professionals are in high demand in the oil and gas sector right now, Wang said “we see that the demand is growing”.

When Rigzone took the same question to Gladney B. Darroh, the founder and president of Houston based Piper-Morgan Search, Darroh told Rigzone that “interest is increasing”.

“I expect this interest will translate into an ever-increasing demand for data science professionals both on a direct hire and contract basis,” Darroh added.

“At the moment I haven’t seen a spike in demand, but I’ve been fielding more queries from companies. It’s definitely a wave that is building,” he continued.

Offering his view, Dave Mount, the President of Louisiana based oneSource Professional Search, told Rigzone that the demand, at least from the company’s client base of oil and gas operating companies, for dedicated data scientists “has been somewhat slow in the last two to three years”. 

“The peak demand, at least from what we saw, was prior to the oil price crash/Covid,” Mount said.

Wang took part in the Society of Petroleum Engineers (SPE) International Gulf Coast Section’s recent Data Science Convention event in Houston, Texas, which was attended by Rigzone’s President. The event, which is described as the annual flagship event of the SPE-GCS Data Analytics Study Group, hosted representatives from the energy and technology sectors. 

“The demand seemed to emanate mostly from onshore unconventional shale players that were in high growth mode with hundreds of wells under their operating umbrella, where they had a lot of data points to sample and statistically, vs. geologically, analyze production operations and mineral royalty companies,” he added.

“We’re not sure if the drop in demand for dedicated data scientists is across the energy supply chain or just in the segments we serve,” Mount continued.

“What we have seen is more demand for employees that can integrate higher end statistical and data analysis in their more traditional roles, i.e., production analysts, production engineers, and reservoir engineers,” Mount went on to state.



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