Scholarlink

<p>In the inversion process of the in situ stress field of deep underground engineering, only the main geological structures are usually considered. The extension interpolation method is used for the area without stratum structure information and the significant change of lithology in some small range is ignored, which greatly increases the subjectivity of the inversion model and the error of the inversion results. This study achieves the characterization of stochastic characteristics in the in situ stress field by employing a stochastic stratigraphic reconstruction technique. After validation against three basic geological model cases, the method was successfully applied to a deep-buried metal mine project. Using core data from the region, numerous stochastic geological models are constructed and the stochastic characteristics of the in situ stress field of deep rock masses are obtained. The results demonstrate that the stochastic geological models accurately predict lithology in unknown areas, with a similarity exceeding 75%. Furthermore, the inversion results indicate that the influence of geological randomness on the in situ stress field is primarily concentrated at lithological boundaries. By accounting for stratigraphic stochasticity, the resulting in situ stress field itself exhibits stochastic characteristics, providing a more comprehensive characterization of the real stress environment in the engineering area.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Stochastic Characterization of In Situ Stress Field in Deep Rock Masses Based on Stochastic Stratigraphic Reconstruction Technique

  • 期刊论文

  • 发表日期：

    2026年3月23日

查看全文
  • Zhenkun Xie,
  • Shili Qiu,
  • Shaojun Li,
  • Quan Jiang,
  • Dingping Xu,
  • Minzong Zheng

摘要

In the inversion process of the in situ stress field of deep underground engineering, only the main geological structures are usually considered. The extension interpolation method is used for the area without stratum structure information and the significant change of lithology in some small range is ignored, which greatly increases the subjectivity of the inversion model and the error of the inversion results. This study achieves the characterization of stochastic characteristics in the in situ stress field by employing a stochastic stratigraphic reconstruction technique. After validation against three basic geological model cases, the method was successfully applied to a deep-buried metal mine project. Using core data from the region, numerous stochastic geological models are constructed and the stochastic characteristics of the in situ stress field of deep rock masses are obtained. The results demonstrate that the stochastic geological models accurately predict lithology in unknown areas, with a similarity exceeding 75%. Furthermore, the inversion results indicate that the influence of geological randomness on the in situ stress field is primarily concentrated at lithological boundaries. By accounting for stratigraphic stochasticity, the resulting in situ stress field itself exhibits stochastic characteristics, providing a more comprehensive characterization of the real stress environment in the engineering area.