CAJ | 학술논문

应用大数据挖掘技术可实现将采油工程海量数据转化为可用于指导油田生产的意见。由于影响吨液百米举升耗电量指标的因素众多，对于何种因素是影响区块或单井吨液百米举升耗电量指标的主要因素并不十分明确，这就需要利用大数据挖掘技术来剖析各种因素对吨液百米举升耗电量的影响。以吨液百米举升耗电量为目标，建立了相应的数学分析模型，基于油田生产数据库的海量数据，开发了数据挖掘软件，挖掘出影响阿尔油田机采井吨液百米举升耗电量的数十个关联因素，定量化泵效、沉没度等指标范围，并预测了吨液百米举升耗电量指标的未来的变化趋势，提出了措施调整建议。编制的采油工程大数据软件是实现大数据管理、数据挖掘、结果呈现的载体，包括系统管理、数据预处理、功能模块、功能应用、图形报表展示、分析模型、进程可视等功能，为用户提供了实用的数据挖掘工具平台。
응용대수거알굴기술가실현장채유공정해량수거전화위가용우지도유전생산적의견。유우영향둔액백미거승모전량지표적인소음다，대우하충인소시영향구괴혹단정둔액백미거승모전량지표적주요인소병불십분명학，저취수요이용대수거알굴기술래부석각충인소대둔액백미거승모전량적영향。이둔액백미거승모전량위목표，건립료상응적수학분석모형，기우유전생산수거고적해량수거，개발료수거알굴연건，알굴출영향아이유전궤채정둔액백미거승모전량적수십개관련인소，정양화빙효、침몰도등지표범위，병예측료둔액백미거승모전량지표적미래적변화추세，제출료조시조정건의。편제적채유공정대수거연건시실현대수거관리、수거알굴、결과정현적재체，포괄계통관리、수거예처리、공능모괴、공능응용、도형보표전시、분석모형、진정가시등공능，위용호제공료실용적수거알굴공구평태。
The use of big data mining technology can transform the mass data of oil production engineering into ideas of guiding oilifeld production. There are numerous factors which affect the power consumption indicators for lifting one ton of liquid to 100 m, so it is not quite clear which is the main factor that affect the power consumption indicators for lifting. This will need the big data mining technology to analyze the effect of various factors on power consumption indicators for lifting. With the goal of power consumption for lifting, a relevant mathematic analytic model was built, and data mining software was developed based on the mass data of oilifeld production database, and tens of related factors were mined which affected the power consumption for lifting in artiifcially lifted wells of Al Oilifeld. The target scope of pump efifciency and submergence was quantiifed. The future trend of power consumption indicators for lifting was predicted, and suggestions for related measures and adjustment were come up with. The developed big data software of oil production engineering was a carrier which realized big data management, data mining and result presentation, including functions like system management, data preprocessing, functional modules, function application, display of graphic report, analytic model, and progress visualization, providing a practical data mining tool platform for our customers.