基于大数据的页岩气井产能主控因素分析系统开发与应用  

Development and application of shale gas well productivity main control factor analysis system based on big data

作　　者：韩星 Han Xing(Jianghan Oilfield Branch Information Center,Qianjiang 433124)

机构地区：[1]江汉油田分公司信息中心,湖北潜江433124

出　　处：《石化技术》2024年第12期241-243,共3页Petrochemical Industry Technology

摘　　要：页岩气藏产能递减快,准确厘清产能主控因素对其生产开发具有重要意义。以生产分析应用场景为需求导向,集成页岩气勘探、开发、工程、压裂、试气、生产等成果数据,按照大数据分析应用思路建立页岩气井产能主控因素分析系统,通过数据挖掘技术和机器学习算法开展数据粒度细化、数据统计分析、数学建模及模型应用,实现分区、分时段产能主控因素自动分析,为井位部署、压裂参数优化设计等提供信息技术支持。The productivity of shale gas reservoir decreases rapidly,so it is important to clarify the main control factors of productivity for its production and development.In this paper,the demand-oriented production analysis application scenario,integrated shale gas exploration,development,engineering,fracturing,gas testing,production and other results data,according to the thought of big data analysis and application,the main control factor analysis system of shale gas well productivity is established,through data mining technology and machine learning algorithm to carry out data granularity refinement,data statistical analysis,mathematical modeling and model application,to achieve the automatic analysis of the main factors of production capacity divided into zones and time periods,it provides information technology support for well location deployment and fracturing parameter optimization design.

关 键 词：页岩气 大数据 数据挖掘 产能主控因素 无阻流量预测 

分 类 号：TE3[石油与天然气工程—油气田开发工程]