大数据在油气勘探开发中的应用——以川南页岩气田为例

随着油气勘探开发规模的不断发展,传统油气行业正在进入数字油气和智慧油气时代。大规模勘探开发产生的庞大数据体量,无论是在收集、存储还是提取分析等方面面临严峻挑战。本文从地质信息集成、甜点区识别、地震数据处理、钻完井以及产能优化等方面介绍了大数据分析和机器学习技术在油气勘探开发过程中的应用现状和存在的问题。以页岩气云数据智慧平台为基础,对川南页岩气长宁-威远和昭通示范区600余口气井生产数据进行分析,得出近五年川南页岩气在钻井时效、压裂参数、建井周期及产能预测方面的发展趋势及主控因素,为"十四·五"页岩气开发方案优化提供参考。

Application of the big data in oil & gas exploitation and development: Take the south Sichuan shale gas as an example

Traditional hydrocarbon industry has gradually stepped into a digital and intelligent age with the progress of hydrocarbon exploration and development. Large-scale exploration and development generated huge volume of data, making it a severe challenge for data acquisition, storage and analysis. This work, firstly, concludes the application status and problems of big data analysis and machine learning technology in oil and gas exploration and development, in aspects of geological information integration, sweet-spot identification, seismic data processing, drilling and completion and productivity optimization. Secondly, on the basis of the Shale Gas Cloud Data Intelligent Platform, this work analyzes the operation data of more than 600 wells in the Changning-Weiyuan and Zhaotong demonstration area of South Sichuan, obtained the development tendency and main-controlling factors of the well drilling period, fracturing parameter, well construction period and productivity prediction, providing a reference for the shale gas development project optimization in the 14^th five-year plan.