據(jù)美國(guó)鉆井網(wǎng)站2022年9月16日?qǐng)?bào)道，全球最大的油田技術(shù)服務(wù)公司斯倫貝謝公司日前與全球著名工業(yè)軟件供應(yīng)商Cognite公司簽署結(jié)成戰(zhàn)略數(shù)據(jù)解決方案合作伙伴關(guān)系協(xié)議，將斯倫貝謝公司的地下企業(yè)數(shù)據(jù)解決方案與Cognite公司數(shù)據(jù)整合在一起。通過(guò)這種合作關(guān)系，客戶可以將來(lái)自油藏、油井和設(shè)施的數(shù)據(jù)集成到一個(gè)單一的開放平臺(tái)上，并利用嵌入式人工智能（AI）和先進(jìn)的分析工具來(lái)優(yōu)化生產(chǎn)、降低成本和減少運(yùn)營(yíng)足跡。  

斯倫貝謝公司數(shù)字和一體化總裁拉杰夫·桑塔利亞說(shuō)：“生產(chǎn)領(lǐng)域的運(yùn)營(yíng)數(shù)據(jù)由于其復(fù)雜性和規(guī)模上缺乏情景化，是一種未得到充分利用的客戶資產(chǎn)。我們與Cognite公司的戰(zhàn)略數(shù)據(jù)解決方案合作關(guān)系將利用Cognite公司的數(shù)據(jù)融合技術(shù)，從流程保證、流程模擬和與客戶開發(fā)的定制AI解決方案等特定領(lǐng)域的應(yīng)用中提取更好、更快的算法規(guī)則。結(jié)合斯倫貝謝公司的地下企業(yè)數(shù)據(jù)解決方案，Cognite公司和斯倫貝謝公司在一個(gè)能共同操作的平臺(tái)上創(chuàng)造了市場(chǎng)上第一個(gè)可訪問(wèn)的情景化數(shù)據(jù)的產(chǎn)品。”“通過(guò)合作，我們將為客戶提供大量的數(shù)據(jù)，方便客戶使用，并快速進(jìn)行大規(guī)模創(chuàng)新，以提高產(chǎn)量，改善財(cái)務(wù)業(yè)績(jī)，并實(shí)現(xiàn)可持續(xù)發(fā)展目標(biāo)。”

斯倫貝謝公司將成為主要商業(yè)合作伙伴，獨(dú)家為客戶提供企業(yè)數(shù)據(jù)解決方案的訪問(wèn)權(quán)限。合作伙伴將利用斯倫貝謝公司和Cognite數(shù)據(jù)融合公司數(shù)十年的數(shù)字解決方案專業(yè)知識(shí)，共同開發(fā)兼容的應(yīng)用程序和解決方案。斯倫貝謝公司的領(lǐng)域驅(qū)動(dòng)AI、物聯(lián)網(wǎng)和模擬引擎與Cognite公司的高性能數(shù)據(jù)集成，以及自動(dòng)化技術(shù)幫助客戶加快生產(chǎn)資產(chǎn)的回報(bào)。

Cognite公司首席執(zhí)行官Girish Rishi表示：“Cognite公司與斯倫貝謝公司的合作為能源領(lǐng)域的客戶提供了一個(gè)安全、可擴(kuò)展的數(shù)據(jù)平臺(tái)，在此基礎(chǔ)上，業(yè)務(wù)應(yīng)用程序可以提高運(yùn)營(yíng)效率，幫助實(shí)現(xiàn)可持續(xù)發(fā)展目標(biāo)。”“斯倫貝謝公司是一家在能源領(lǐng)域具有可信賴的面向全球的公司，我們很榮幸能將它納入我們不斷增長(zhǎng)的合作伙伴生態(tài)系統(tǒng)中。”

Rishi表示：“這種合作的最初重點(diǎn)是能源領(lǐng)域的生產(chǎn)運(yùn)營(yíng)。對(duì)于客戶來(lái)說(shuō)，這意味著更好地管理數(shù)據(jù)模型，改進(jìn)實(shí)現(xiàn)價(jià)值的時(shí)間，以及增強(qiáng)從當(dāng)前資產(chǎn)組合中增加價(jià)值的結(jié)果。 ”

李峻 編譯自 美國(guó)鉆井網(wǎng)站

原文如下：

Schlumberger And Cognite Form Strategic Data Solutions Partnership 

Schlumberger and Cognite have inked a strategic partnership that would see the integration of Schlumberger’s Enterprise Data Solution for subsurface with Cognite Data Fusion. Through this partnership, customers can integrate data from reservoirs, wells, and facilities in a single, open platform, and leverage embedded AI and advanced analytics tools to optimize production, reduce costs and decrease operational footprint.

“Operational data in the production domain is a vastly underutilized customer asset due to its complexity and lack of contextualization at scale. Our strategic partnership with Cognite leverages Cognite Data Fusion to extract better and faster insights from our domain-specific applications in flow assurance, process simulation, and bespoke AI solutions developed with customers. Combined with Schlumberger’s Enterprise Data Solution for subsurface, Cognite and Schlumberger are creating the first offering in the market with access to contextualized data in an interoperable platform,” said Rajeev Sonthalia, president, Digital & Integration, Schlumberger. “Together, we will make vast quantities of data easily available for customers to use and innovate at scale quickly, to increase production, improve financial performance, and achieve sustainability goals.”

Schlumberger will be the lead commercial partner and will exclusively provide customers with access to the Enterprise Data Solution. The partners will co-develop compatible applications and solutions, leveraging decades of digital solutions expertise from Schlumberger and Cognite Data Fusion’s unique capabilities. Schlumberger’s domain-driven AI, IoT and simulation engines integrated with Cognite’s high-performance data, and automation technologies help customers accelerate returns from their producing assets.

“Cognite’s partnership with Schlumberger provides customers in the energy sector with a secure, scalable data platform upon which business applications can deliver operational efficiencies and help achieve sustainability goals,” said Girish Rishi, CEO of Cognite. “We are honored to bring Schlumberger, a company with trusted, global roots in the energy sector, into our growing partner ecosystem.”

The partnership’s initial focus is production operations in the energy sector. For customers, this means better management of data models, improved time to value, and enhanced outcomes to increase value from their current portfolio of assets.