AI支持下测井曲线重构系统的设计与实现OA

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.