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基于双向长短期记忆神经网络和多头注意力机制的测井曲线重构方法

梅雨 陈勉 申迎彬 陈军斌 胡稼轩

石油钻采工艺2025,Vol.47Issue(3):277-288,328,13.
石油钻采工艺2025,Vol.47Issue(3):277-288,328,13.DOI:10.13639/j.odpt.202503025

基于双向长短期记忆神经网络和多头注意力机制的测井曲线重构方法

A well logging curve reconstruction method based on BiLSTM neural network and Multi-Head Attention mechanism

梅雨 1陈勉 1申迎彬 2陈军斌 3胡稼轩1

作者信息

  • 1. 中国石油大学(北京)石油工程学院,北京 102249
  • 2. 中石油国际勘探开发有限公司,北京 100034
  • 3. 西安石油大学陕西省油气井及储层渗流与岩石力学重点实验室,陕西 西安 710065
  • 折叠

摘要

Abstract

Well logging curve data often suffers from partial loss due to borehole collapse and instrument failures,while re-logging incurs high costs.To address the insufficient accuracy of existing reconstruction methods,a well logging curve reconstruction method is proposed based on Physics-Prior Driven Hybrid Neural Network(PPD-HNN)in this paper.This method captures bidirectional dependencies in sequential data through a Bidirectional Long Short-Term Memory(BiLSTM)neural network,while enhancing the attention of model to critical features via a Multi-Head Attention(MHA)mechanism,thereby improving reconstruction accuracy.A Particle Swarm Optimization(PSO)algorithm is introduced for hyperparameter tuning,with geological constraints incorporated to ensure reconstructed results comply with the physical laws of logging curves,avoiding unreasonable data fluctuations.Orthogonal experiments and well logging curve completion and generation experiments were conducted using real well logging data from Qingcheng Oilfield.The optimal model architecture and hyperparameter settings were determined through orthogonal experiments.In the completion and generation experiments,such comparative models as Convolutional Neural Networks(CNN),Long Short-Term Memory(LSTM)neural networks,BiLSTM,and eXtreme Gradient Boosting(XGBOOST)were included to validate the proposed model's accuracy.The results demonstrate that PPD-HNN performs well in capturing the nonlinear relationships among logging curves and the sequential characteristics along depth,achieving an R2 improvement of approximately 19%over HNN.This method offers a novel technical approach for low-cost,high-precision well logging data restoration.

关键词

测井曲线重构/双向长短期记忆神经网络/多头注意力机制/粒子群优化

Key words

well logging curve reconstruction/Bidirectional Long Short-Term Memory neural network/Multi-Head Attention mechanism/Particle Swarm Optimization

分类

信息技术与安全科学

引用本文复制引用

梅雨,陈勉,申迎彬,陈军斌,胡稼轩..基于双向长短期记忆神经网络和多头注意力机制的测井曲线重构方法[J].石油钻采工艺,2025,47(3):277-288,328,13.

基金项目

国家自然科学基金面上项目"陆相页岩油储层密切割体积压裂缝网演化机理及有效性评价研究"(编号:52274040). (编号:52274040)

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