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基于數(shù)據(jù)湖平臺的工業(yè)大數(shù)據(jù)分析實踐:以智能油田能效分析為例
網(wǎng)絡安全與數(shù)據(jù)治理
李滿1,,安創(chuàng)鋒1,,高靜1,牛永勝1,姚嘉琨2
1.中海石油(中國)有限公司天津分公司,; 2.中國電子系統(tǒng)技術有限公司
摘要: 工業(yè)系統(tǒng)以及工業(yè)企業(yè)應用場景日益復雜,,導致系統(tǒng)處理數(shù)據(jù)量與數(shù)據(jù)類型日益增多。面對多樣化的業(yè)務應用場景和海量多源異構數(shù)據(jù),對數(shù)據(jù)分析的流動性與靈活性要求越來越高,。而傳統(tǒng)基于數(shù)據(jù)庫的大數(shù)據(jù)分析平臺無法滿足不同結構數(shù)據(jù)匯入與數(shù)據(jù)源變化。因此,,構建了一套端到端,、高效協(xié)同的大數(shù)據(jù)分析應用實施框架,結合數(shù)據(jù)湖平臺與智能算法建立針對工業(yè)大數(shù)據(jù)的分析模型,,實現(xiàn)以業(yè)務分析需求為驅動,,結合數(shù)據(jù)湖平臺對于海量多源異構數(shù)據(jù)的處理、匯聚,、管理能力,,高效開展數(shù)據(jù)建模、準備,、測試,、訓練與驗證。最后,,在智能油田能效分析場景進行應用驗證,,成功實現(xiàn)對于智能油田能效分析場景下的系統(tǒng)預測、優(yōu)化與決策功能,,為油田全業(yè)務流程提供數(shù)據(jù)支撐,,推動智能油田可持續(xù)發(fā)展。
中圖分類號:TP393文獻標識碼:ADOI:10.19358/j.issn.2097-1788.2024.11.013引用格式:李滿,,安創(chuàng)鋒,,高靜,等.基于數(shù)據(jù)湖平臺的工業(yè)大數(shù)據(jù)分析實踐:以智能油田能效分析為例[J].網(wǎng)絡安全與數(shù)據(jù)治理,,2024,,43(11):75-84.
Industrial big data analytics practice based on data lake platform: an example of intelligent oilfield energy efficiency analysis
Li Man1, An Chuangfeng1, Gao Jing1, Niu Yongsheng1,Yao Jiakun2
1.CNOOC (China) Tianjin Branch; 2.China Electronics System Technology Co.
Abstract: As industrial systems and the application scenarios of industrial enterprises become increasingly complex, the quantity and variety of data processed by the system also increase. In light of the growing number of diverse business application scenarios and the increasing volume of heterogeneous data from a multitude of sources, the need for enhanced mobility and flexibility in data analysis is becoming increasingly apparent. The conventional database-centric approach to big data analysis is inadequate for accommodating the heterogeneous structural characteristics of data sinks and the evolving nature of data sources. Accordingly, this paper presents a comprehensive, integrated and collaborative big data analysis application implementation framework. This framework combines the data lake platform and intelligent algorithms to establish an analysis model for industrial big data. Furthermore, driven by business analysis requirements, the data lake platform′s processing, aggregation, and management capabilities are leveraged to efficiently carry out data modeling, preparation, testing, training, and validation. Subsequently, the application is verified in an intelligent oilfield energy efficiency analysis scenario. This successfully demonstrates the system′s ability to predict, optimize, and make decisions in this context, providing data support for the entire business process of oil fields and promoting the sustainable development of intelligent oilfields.
Key words :

引言

隨著全球能源行業(yè)向數(shù)字化轉型的深入發(fā)展,, “智能油田”等規(guī)劃相繼出臺,,旨在通過技術創(chuàng)新與數(shù)據(jù)驅動,實現(xiàn)油氣上游業(yè)務的全面升級,。為此,,中國海油同步立項,開展智能油田建設和勘探開發(fā)數(shù)據(jù)湖平臺的建設,。智能油田建設從各油田分散的業(yè)務應用場景出發(fā),,由各油田分公司根據(jù)自身特定的業(yè)務需求開展項目,以促進多樣化的創(chuàng)新嘗試和技術的快速迭代,;數(shù)據(jù)湖平臺作為支撐智能油田應用的數(shù)字基礎設施,,明確了集中化和統(tǒng)一化的建設方向,,旨在整合中國海油上游勘探開發(fā)的核心業(yè)務數(shù)據(jù),實現(xiàn)數(shù)據(jù)管理的統(tǒng)一化,。智能油田與數(shù)據(jù)湖平臺項目并行推進,,隨著項目的深入,兩者的融合趨勢日益明顯,,智能油田從創(chuàng)新探索邁向規(guī)范化和標準化,,數(shù)據(jù)湖平臺則在支撐應用中不斷優(yōu)化功能并擴展。以秦皇島32-6項目為試點,,成功實現(xiàn)了實時數(shù)據(jù)入湖與服務遷移,,標準化改造數(shù)據(jù)開發(fā)過程,支持快速應用開發(fā),,為中國海油智能油田與數(shù)據(jù)湖平臺的進一步融合提供了有力的支撐,。

工業(yè)大數(shù)據(jù)平臺作為推動制造業(yè)智能化轉型的關鍵力量,廣泛應用于生產監(jiān)控,、故障預測和效率優(yōu)化等環(huán)節(jié),。借助物聯(lián)網(wǎng)、云計算和人工智能等前沿技術,,現(xiàn)有平臺在數(shù)據(jù)采集,、存儲、分析和應用方面不斷增強,,為企業(yè)決策提供了堅實的數(shù)據(jù)支撐,。然而,隨著技術進步和市場需求增長,,工業(yè)大數(shù)據(jù)平臺面臨數(shù)據(jù)安全與隱私保護的挑戰(zhàn),,同時多源異構數(shù)據(jù)的增加導致傳統(tǒng)數(shù)據(jù)庫平臺存在數(shù)據(jù)流通不暢和靈活性不足的問題。數(shù)據(jù)湖平臺通過支撐業(yè)務場景分析,,能夠降低大數(shù)據(jù)分析應用開發(fā)和實施的難度,,這是與智能油田項目共同追求的目標。盡管已取得一定進展,,但仍需深入研究,,形成可復用的標準化、工程化架構,,并依托數(shù)據(jù)湖平臺工具進行產品化支撐,。

當前,智能油田應用面臨的主要問題包括數(shù)據(jù)分散,、標準不統(tǒng)一和業(yè)務流程復雜等,。這些問題不僅增加了數(shù)據(jù)處理和分析的難度,還限制了智能油田建設的整體效率和效益,。數(shù)據(jù)湖作為一種統(tǒng)一的數(shù)據(jù)存儲池,,能夠容納各種規(guī)模的結構化,、半結構化和非結構化數(shù)據(jù),,提供了潛在的解決方案,。目前,數(shù)據(jù)湖平臺主要應用于數(shù)據(jù)管理領域,,涵蓋數(shù)據(jù)資產目錄管理,、數(shù)據(jù)源及數(shù)據(jù)處理任務、數(shù)據(jù)生命周期管理,、數(shù)據(jù)治理和權限管理等功能,。盡管數(shù)據(jù)湖技術在架構靈活性和開放性方面表現(xiàn)出顯著優(yōu)勢,但其在性能效率,、安全控制和數(shù)據(jù)治理方面仍有改進空間,。將數(shù)據(jù)湖平臺與工業(yè)大數(shù)據(jù)分析相結合,可以有效應對企業(yè)級的生產分析需求,,并提升數(shù)據(jù)管理能力,。為此,本文通過調研和借鑒大數(shù)據(jù)分析領域的相關研究成果,,結合數(shù)據(jù)湖平臺與智能油田應用研發(fā)的實踐經(jīng)驗,,提出了一套基于數(shù)據(jù)湖平臺的大數(shù)據(jù)分析應用實施框架。以智能油田能效分析為例,,對所提出的大數(shù)據(jù)分析應用實施框架進行了應用驗證,。


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作者信息:

李滿1,安創(chuàng)鋒1,,高靜1,,牛永勝1,姚嘉琨2

(1.中海石油(中國)有限公司天津分公司,,天津300450,;

2.中國電子系統(tǒng)技術有限公司,北京100089)


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