钻探工程2026，Vol.53Issue(3)：73-79,7.DOI:10.12143/j.ztgc.2026.03.009
钻探工程原始数据高效识别采集系统的开发与实现
Development and implementation of an efficient recognition and acquisition system for drilling engineering raw data
摘要
Abstract
To address the problems of low efficiency,high error rate in manual entry,and incomplete digital transformation in the collection of raw data from drilling engineering,this study designs and develops an efficient recognition and collection system for drilling raw data based on modern Web technologies and multimodal large models.The system adopts a front-end and back-end separation architecture,integrates mainstream technology stacks such as Vue 3.0 and Spring Cloud Alibaba,and innovatively introduces the Qwen-VL-max vision-language multimodal large model.It constructs a full-process automated processing system of"mobile terminal collection-cloud-based intelligent recognition-structured storage",realizing accurate recognition and structured parsing of paper report images.Verified through multi-scenario practical tests,the system performs excellently in terms of field recognition accuracy,adaptability to complex tables,and system robustness,significantly improving the efficiency and accuracy of drilling data entry and effectively solving the drawbacks of traditional collection methods.The research results provide key technical support for the digital management,sharing and reuse,and in-depth mining of drilling engineering data,and have important engineering value and application prospects for promoting the digital transformation of the drilling industry and building an intelligent drilling big data platform.关键词
钻探工程/原始数据采集/智能识别/多模态大模型/系统开发/数字化管理Key words
drilling engineering/raw data acquisition/intelligent recognition/multimodal large model/system development/digital management分类
天文与地球科学引用本文复制引用
杜垚森,赵光帅,杨义勇,伍晓龙,高鹏举,马汉臣,汤小仁,黄蒙福,王耀,范龙飞..钻探工程原始数据高效识别采集系统的开发与实现[J].钻探工程,2026,53(3):73-79,7.基金项目
中国地质调查局地质调查项目"钻探工程综合管理平台优化升级"(编号:DD20240205203) （编号:DD20240205203）
