石油科技论坛 ›› 2018, Vol. 37 ›› Issue (4): 41-48.DOI: 10.3969/j.issn.1002-302x.2018.04.007

• 技术创新 • 上一篇    下一篇

油田生产大数据分析应用研究

耿玉广1 张 萌2 耿英杰3 薛良玉4 张战敏1 顾龚杰1   

  1. 1. 中国石油华北油田公司工程技术研究院;2. 中国石油华北油田公司储气库管理处; 3. 中国石油勘探开发研究院计划财务处;4. 中国石油华北油田公司二连分公司
  • 出版日期:2018-09-26 发布日期:2018-09-26
  • 基金资助:
    中国石油华北油田公司科研项目“采油工程大数据应用技术研究与实践”(编号:2016-HB-Z0504)。

Application of Big Data Analysis in Oilfield Production

Geng Yuguang1,Zhang Meng2,Geng Yingjie3, Xue Liangyu4, Zhang Zhanmin1,Gu Gongjie1   

  1. 1. Engineering and Technology Research Institute of PetroChina Huabei Oilfield Company, Renqiu 062552, China; 2. Gas Storage Management Office of PetroChina Huabei Oilfield Company, Langfang 065006, China; 3. Planning and Finance Office of PetroChina Research Institute of Petroleum Exploration & Development, Beijing 100083, China; 4. Erlian Branch of PetroChina Huabei Oilfield Company, Xilinhaote 026000, China
  • Online:2018-09-26 Published:2018-09-26
  • Supported by:
     

摘要: 数字油田为石油企业采集积累了大量生产数据,为挖掘和用好这一宝贵资源,深入开展了大数据预处理、 数据建模、可视化展示、因果分析、方案优化、现场实施等系列研究,构建了以应用为导向的油田生产大数据分析流程, 建立了油田生产主营业务大数据分析模型,开发出油田生产大数据分析平台及网络版软件。平台总体架构分为数据源层、 数据平台层、应用服务层,为满足油田生产企业不同岗位需要,推出了基层版、分析版和研究版。具体介绍了以降低 抽油机井吨液举升百米耗电为目标的大数据分析、抽油机井智能工况诊断预警两个油田生产应用实例,显示在节能降 耗、降本增效、提高产量和效益等方面见到实效。大数据分析在H 油田应用3 年来,累计新增销售额(增油)3.4 亿元, 新增利润(增油及节支)2.8 亿元,为油田生产高效管控和优化运行提供了有力支撑。

 

关键词: 油田生产, 大数据, 分析流程, 数据模型, 分析平台, 节能降耗, 降本增效

Abstract: Digital oilfield has accumulated a large amount of production data for petroleum enterprises. To take advantage of the precious resources, a series of studies were made in the areas of big data pre-treatment, data modeling, visualized display, factor analysis, optimization of plan, and on-site application. The efforts included establishment of the applicationoriented oilfield production big data analysis process, construction of the big data analysis model for the main businesses of oilfield production, and development of the oilfield production big data analysis platform and software in network version. The general configuration of the platform is divided into data source level, data platform level and application service level to satisfy the need of different job positions at the oilfield. A number of versions were released, such as basic version, analysis version and research version. This paper briefs about two application cases -- big data analysis aimed to reduce electricity consumption of oil pumping unit for lifting each ton of liquid for 100 meters and intelligent diagnosis of working conditions and early warning for pumping well. The cases show a good performance in saving energy, reducing cost, and improving production and efficiency. Big data analysis has been applied in H Oilfield for three years, with the additional turnover (including additional oil production) accumulated to 340 million yuan and the additional profit (including additional oil production and reduction of spending) accumulated to 280 million yuan. It provided powerful support for high-efficiency management of production and optimization of operation at the oilfield.

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