福建电脑2026，Vol.42Issue(3)：6-10,5.DOI:10.16707/j.cnki.fjpc.2026.03.002
AI支持下测井曲线重构系统的设计与实现
Design and Implementation of a Logging Curve Reconstruction System with AI Support
摘要
Abstract
To address the problem of missing or distorted well logging curve data caused by instrument failures,borehole collapse,and other factors,this paper presents an AI-supported well logging curve reconstruction system.The system adopts a three-tier architecture and integrates multiple machine learning and deep learning models to fully exploit the nonlinear relationships among different logging curves and the underlying geological patterns,thereby enabling efficient and accurate curve reconstruction.Experimental results show that,over 10 repeated trials,the best-performing model in the system achieves an MAE of 0.3047,RMSE of 0.3926,and R² of 0.9024,demonstrating that the system effectively enhances the quality and efficiency of well logging curve reconstruction compared to other models,and provides high-quality data support for subsequent reservoir interpretation and exploration and development activities.关键词
机器学习/时间序列/测井曲线重构系统Key words
Machine Learning/Time Series/Well Log Reconstruction System分类
信息技术与安全科学引用本文复制引用
潘少伟,常挺..AI支持下测井曲线重构系统的设计与实现[J].福建电脑,2026,42(3):6-10,5.基金项目
本文得到陕西省自然科学基础研究计划"极端环境下核磁共振测井采集参数自适应方法研究"(No.2025JC-YBMS-286)资助. （No.2025JC-YBMS-286）
