基于Bitmap的油水井采注优化实时推理引擎

刘阳; 张天石; 李世超; 佟星; 曾鹏; 于海斌

doi:10.16383/j.aas.2017.c170132

基于Bitmap的油水井采注优化实时推理引擎

doi: 10.16383/j.aas.2017.c170132

刘阳^1,,
张天石^1,,
李世超^1,,
佟星^1,,
曾鹏^1, ,,
于海斌^1,

1.
中国科学院沈阳自动化研究所工业控制网络与系统研究室沈阳 110016

基金项目:

国家自然科学基金 61533015

详细信息

作者简介:
刘阳   中国科学院沈阳自动化研究所副研究员.2011年获得东北大学计算机应用技术专业博士学位.主要研究方向为工业物联网数据处理、语义数据处理及智能制造.E-mail:liuy@sia.cn

张天石   中国科学院沈阳自动化研究所助理研究员.2013年获得北京邮电大学自动化学院硕士学位.主要研究方向为智能优化算法以及工业物联网本体设计.E-mail:zhangtianshi@sia.cn

李世超   中国科学院沈阳自动化研究所助理研究员.2014年获得东北大学信息学院硕士学位.主要研究方向为油田优化开采以及智慧油田应用.E-mail:lishichao@sia.cn

佟星   中国科学院沈阳自动化研究所助理研究员.2012年获得哈尔滨工业大学计算机学院硕士学位.主要研究方向为自然语言处理以及工业物联网本体设计.E-mail:tongxing@sia.cn

于海斌   中国科学院沈阳自动化研究所研究员.1997年获得东北大学控制理论与控制工程专业博士学位.主要研究方向为自动化控制系统, 先进制造技术和智能电网的基础与应用研究.E-mail:yhb@sia.cn

通讯作者:
曾鹏中国科学院沈阳自动化研究所研究员.2005年中国科学院大学机械电子工程专业博士学位.主要研究方向为工业无线传感器网络, 智能电网以及需求响应.E-mail:zp@sia.cn

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出版历程
- 收稿日期: 2017-03-10
- 录用日期: 2017-05-04
- 刊出日期: 2017-06-20

A Real-time Reasoning Engine for Injection-production Optimization of Water and Oil Wells on Account of Bitmap

LIU Yang^1
,,
ZHANG Tian-Shi^1
,,
LI Shi-Chao^1
,,
TONG Xing^1
,,
ZENG Peng^{1
, ,},
YU Hai-Bin^1
,

1.
Lab of Industrial Control Network and System, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016

Funds:

National Natural Science Foundation of China 61533015

More Information

Author Bio:
  Associate professor at Shenyang Institute of Automation Chinese Academy of Sciences. She received her Ph. D. degree in computer application technology from Northeastern University in 2011. Her research interest covers industrial internet of things data processing, semantic data processing and intelligent manufacturing

  Assistant professor at Shenyang Institute of Automation Chinese Academy of Sciences. He received his master degree from School of Automation, Beijing University of Post and Communication in 2013. His research interest covers intelligence optimization algorithm and ontology design in industrial things

  Assistant professor at Shenyang Institute of Automation, Chinese Academy of Sciences. He received his master degree from the School of Information, Northeastern University in 2014. His research interest covers optimized exploitation of oilfleld and application of intelligent oilfleld

  Assistant professor at Shenyang Institute of Automation, Chinese Academy of Sciences. He received his master degree from the School of Computer, Harbin Institute of Technology in 2012. His research interest covers natural language processing and ontology design in industrial things

  Professor at Shenyang Institute of Automation, Chinese Academy of Sciences. He received his Ph. D. degree in control theory and control engineering from Northeastern University in 1997. His research interest covers basic and applied research in the areas of automation control systems, advanced manufacturing techniques and smart grids

Corresponding author: ZENG Peng Professor at Shenyang Institute of Automation, Chinese Academy of Sciences. He received his Ph. D. degree in mechatronic engineering from Graduate School of the Chinese Academy of Sciences in 2005. His research interest covers wireless sensor networks for industrial automation, smart grids, and demand response. Corresponding author of this paper

摘要

摘要: 针对油田油水井采注优化业务中，油水井数据量大、地层结构复杂以及人类经验多的特点，分析了传统推理方法在油田采注实时优化处理过程中的不足，采用事件处理思想，提出了一种基于Bitmap事件编码与匹配机制的推理引擎，有效地实现了对无效事件的过滤并提升了事件与规则的匹配效率.在油田实际数据试验平台上对该方法进行了验证并与RETE算法、LFA（Linear forward-chaining）算法的性能对比，结果验证了本文方法在实时推理能力上的有效性.
- 采注优化 /
- 推理引擎 /
- Bitmap /
- 规则匹配 /
- 事件过滤
Abstract: In the process of optimizing the injection-production in oil and water wells, complex stratigraphic structure and large amount of business data and human experience will be involved. In this situation, traditional reasoning methods cannot be effective. By introducing the event processing theory, a reasoning engine using bitmap event encoding and matching is proposed, which can filter out invalid events efficiently and improve the matching performance between events and rules. The proposed reasoning engine is implemented in a real oilfield data experiment platform. Compared with RETE algorithm and LFA (Linear forward-chaining) algorithm, the proposed method shows a better reasoning capability.
- Production-injection optimization /
- reasoning engine /
- bitmap /
- rule matching /
- event filtering

HTML全文

图 1 产生式推理引擎示意图

Fig. 1 The sketch map of production rule reasoning

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图 2 油田实时推理系统

Fig. 2 Real-time reasoning system in oilfleld

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图 3 实时推理引擎架构

Fig. 3 The architecture of real-time reasoning engine

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图 4 原子规则树

Fig. 4 Atomic rule trees

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图 5 β网络

Fig. 5 β network

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图 6 原子条件筛选流程图

Fig. 6 The flow chart for atomic condition flltering

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图 7 油水井采注协同优化流程图

Fig. 7 The co-optimization flow chart for injection-production in oil and water wells

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图 8 不同到达事件情况下性能对比图

Fig. 8 The performance comparison with difierent numbers of arrival events

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图 9 不同原子条件下性能对比图

Fig. 9 The performance comparison with difierent numbers of atomic conditions

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参考文献(23)

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基于Bitmap的油水井采注优化实时推理引擎

doi: 10.16383/j.aas.2017.c170132

通讯作者:
曾鹏中国科学院沈阳自动化研究所研究员.2005年中国科学院大学机械电子工程专业博士学位.主要研究方向为工业无线传感器网络, 智能电网以及需求响应.E-mail:zp@sia.cn

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A Real-time Reasoning Engine for Injection-production Optimization of Water and Oil Wells on Account of Bitmap

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基于Bitmap的油水井采注优化实时推理引擎

doi: 10.16383/j.aas.2017.c170132

通讯作者: 曾鹏 中国科学院沈阳自动化研究所研究员.2005年中国科学院大学机械电子工程专业博士学位.主要研究方向为工业无线传感器网络, 智能电网以及需求响应.E-mail:zp@sia.cn

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A Real-time Reasoning Engine for Injection-production Optimization of Water and Oil Wells on Account of Bitmap

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出版历程

目录

通讯作者:
曾鹏中国科学院沈阳自动化研究所研究员.2005年中国科学院大学机械电子工程专业博士学位.主要研究方向为工业无线传感器网络, 智能电网以及需求响应.E-mail:zp@sia.cn