Three-dimensional borehole induced polarization inversion using adaptive progressive grid: Methodology and field applications

IF 2.1 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Peng Bai , Yumei Cai , Xiaolin Xu , Weihao Li , Yongheng Zhang , Zhengyu Liu
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引用次数: 0

Abstract

The borehole induced polarization (BIP) method, owing to its high sensitivity to water-bearing structures, demonstrates significant advantages in detecting small-scale and complex water-related hazards ahead of tunnels. However, its performance is constrained by traditional fixed inversion grid techniques, making it difficult to meet the demands of rapid and high-resolution detection. To address these limitations, this study proposes a bidirectionally guided adaptive grid optimization strategy This method combines the benefits of two popular grid optimization techniques, namely the sensitivity matrix reconstructed from highly anomalous observational data and the change in model parameters, to thoroughly identify and refine grid regions that with high sensitivity and significant parameter changes. Building upon this foundation, an adaptive progressive inversion framework for induced polarization is developed. Building on this, this paper further proposes an adaptive progressive inversion method for induced polarization. In the initial stage of inversion, a coarse grid is employed to alleviate the ill-posedness of the inverse problem. Subsequently, during the following inversion process, the grid resolution is progressively enhanced based on the bidirectionally guided grid optimization strategy, enabling high-precision imaging of resistivity and chargeability parameters. Numerical experiments demonstrate that the proposed adaptive inversion method, while reducing the number of grid cells by 20 %, generates higher-resolution inversion grids, significantly improves the accuracy of resistivity and chargeability distributions, and increases computational efficiency by 50 %. This technique has been successfully applied in a drill-and-blast tunnel project in Northwest China, where it accurately identified water-bearing structures ahead of the tunnel face, providing crucial technical support for pre-grouting operations.
基于自适应渐进网格的三维井眼极化反演:方法和现场应用
井眼诱导极化(BIP)方法由于对含水构造高度敏感,在探测隧道前方小型复杂水害方面具有显著优势。但其性能受到传统固定反演网格技术的制约,难以满足快速、高分辨率的检测需求。针对这些局限性,本研究提出了一种双向引导自适应网格优化策略,该方法结合了两种常用网格优化技术的优点,即高度异常观测数据重构的灵敏度矩阵和模型参数变化,彻底识别和细化高灵敏度和参数变化显著的网格区域。在此基础上,建立了感应极化自适应渐进反演框架。在此基础上,进一步提出了一种感应极化自适应逐级反演方法。在反演的初始阶段,采用粗网格来缓解逆问题的病态性。随后,在后续反演过程中,基于双向导向网格优化策略逐步提高网格分辨率,实现电阻率和充电率参数的高精度成像。数值实验表明,本文提出的自适应反演方法在网格单元数减少20%的同时,生成了更高分辨率的反演网格,显著提高了电阻率和电荷率分布的精度,计算效率提高了50%。该技术已成功应用于西北某钻爆隧洞工程,准确识别了隧洞工作面前方含水构造,为预注浆作业提供了关键的技术支持。
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来源期刊
Journal of Applied Geophysics
Journal of Applied Geophysics 地学-地球科学综合
CiteScore
3.60
自引率
10.00%
发文量
274
审稿时长
4 months
期刊介绍: The Journal of Applied Geophysics with its key objective of responding to pertinent and timely needs, places particular emphasis on methodological developments and innovative applications of geophysical techniques for addressing environmental, engineering, and hydrological problems. Related topical research in exploration geophysics and in soil and rock physics is also covered by the Journal of Applied Geophysics.
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