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Big data analytics in upstream oil and gas industries for sustainable exploration and development: A review
Environmental Technology & Innovation ( IF 7.1 ) Pub Date : 2020-10-01 , DOI: 10.1016/j.eti.2020.101186
Jas Nitesh Desai , Sivakumar Pandian , Rakesh Kumar Vij

This paper reviews how upstream oil and gas organizations can rapidly dissect an expansive volume of data by taking steps to amalgamate all the data by combining the operational data and drilling rig sensor data to real-time windows using advanced analytics to mine the data for formation evaluation in the reservoir. Examination and impending the data to complex models progressively are carried out using multiple linear regressions and support vector machines to predict uncertainty. They can create strategic bits of knowledge that assist in execution while anticipating issues that help to increase drilling and production performances. Over all big data analytics helps for the sustainable development of oil and gas Industries.



中文翻译:

上游石油和天然气行业中用于可持续勘探和开发的大数据分析:回顾

本文回顾了上游石油和天然气组织如何通过采取步骤合并所有数据,通过将操作数据和钻机传感器数据结合到实时窗口,使用高级分析工具挖掘数据以进行地层评估的方法来快速分解大量数据在水库中。使用多重线性回归和支持向量机来预测不确定性,并将数据逐步检查并逐步提交到复杂模型。他们可以创造战略知识来协助执行,同时预见到有助于提高钻井和生产性能的问题。总体而言,大数据分析有助于石油和天然气工业的可持续发展。

更新日期:2020-10-02
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