A Deep Learning Based Geosteering Method Assembled with "Wide-angle Eye"（基于深度学习的地质导向方法与 "广角眼 "的组合）
发布时间：2024-01-08
元数据
名 称
A Deep Learning Based Geosteering Method Assembled with "Wide-angle Eye"（基于深度学习的地质导向方法与 "广角眼 "的组合）
科技资源标识
CSTR:11738.14.NCDC.XDA14.PP6133.2024
数据共享方式
开放下载
摘 要
The intelligent guided drilling system adopts the precise guided drilling geological system and a new rotary steering drilling tool to achieve deep drilling intelligent cruise. It can increase the amount of oil and gas exploration and ensure safety in production. However, the geosteering problem in deep wells and ultra-deep wells is still an outstanding issue due to the hostile environment for signal transmission. In this research, an autonomous geosteering method based on deep learning model is proposed, which is able to make the strategic decision of the drill bit direction in downhole operating mode. According to the characteristics of the Logging While Drilling (LWD) data, the “Wide-angle Eye” mechanism is embedded to feel the future change of stratum ahead and give preview information to the drill bit. Consequencely, the Drilling Decision Model is designed to be a Convolutional Neural Network (ConvNet). The performance of the proposed model was validated in simulation, and the experimental results indicate that the proposed method has high accuracy and robustness, appearing an enhanced capacity to predict stratigraphic changes
刘溢,朱丹丹,刘昊,杜爱民,陈冬,叶智慧. A Deep Learning Based Geosteering Method Assembled with "Wide-angle Eye"（基于深度学习的地质导向方法与 "广角眼 "的组合）. 国家冰川冻土沙漠科学数据中心(http://www.ncdc.ac.cn), 2024. https://cstr.cn/CSTR:11738.14.NCDC.XDA14.PP6133.2024.
本作品采用
知识共享署名
4.0 国际许可协议进行许可。
CSTR:11738.14.NCDC.XDA14.PP6133.2024