钻采工艺 ›› 2021, Vol. 44 ›› Issue (4): 15-18.DOI: 10.3969/J. ISSN.1006-768X.2021.04.04

• 钻井工艺 • 上一篇    下一篇

基于工程地质一体化数据库的钻头优选应用实践

钱浩东张治发,王鹏   

  1. 中国石油川庆钻探工程有限公司钻采工程技术研究院 
  • 出版日期:2021-07-25 发布日期:2021-07-25
  • 作者简介:钱浩东(1968-) , 川庆信息企业专家,1990 年毕业于成都师范专科学校数学系, 现从事钻井工程信息专业软件开发。钻井工艺研究和钻井工程设计工作。地址: (618300) 四川广汉中山大道南二段川庆钻采院, 电话:0838-5152379, E-mail: qianhd@ cnpc. com. cn
  • 基金资助:
    中国石油集团油田技术服务有限公司统筹项目“ 工程作业智能支持系统 3 . 0 构建研究”( 编号:2021 T-04-02) 。

Practice of Bit Optimization Based on Integrated Database of Engineering Geology

QIAN Haodong, ZHANG Zhifa, WANG Peng   

  1. CCDC Drilling & Production Engineering Technology Research Institute, Guanghan, Sichuan 618300, China
  • Online:2021-07-25 Published:2021-07-25

摘要: 目前优选钻头的理论方法很多,优选方法各有特点,然而利用工程地质一体化数据库,进行优选钻头的方法国内却鲜有介绍,目前,国内随着中油油服钻井智能信息系统(EISS)在中石油的全面推广,该系统围绕井筒工程产生了大量与地层和钻头相关的数据,文章突破了传统钻头选型手段,建立了基于井筒工程大数据的一种全新的钻头优选方法,通过在 GS-MX区块实践运用,有效提高了钻井效率,对其它工程参数的优选具有借鉴意义。

关键词: 井筒工程大数据, 钻头优选, 岩石可钻性, 岩石研磨性

Abstract:

At present, there are many theoretical methods for optimizing drill bits, each of which has its own characteristics. However, the method of optimizing drill bits using drilling big data is rarely introduced in China. At present, with the development of drilling intelligent information technology of EISS and data acquisition technology in China, a large amount of data related to the formation and the bit is generated around the wellbore engineering. This article has broken through the traditional drill bit selection method and established a new drill preferred method which is based on big data of wellbore engineering. Through the practical application in the GS-MX block, drilling efficiency has been improved. It has reference significance for the optimization of other engineering parameters.

Key words: big data of wellbore engineering, bit optimization, rock drillability, rock abrasiveness