摘要
研究针对石盐地下采卤矿床溶腔稳定性问题及其对地表沉降的影响进行了深入分析。采用神经网络增强的地质稳定性预测算法,结合国际地质科学联合会地质稳定性数据集,对溶腔稳定性进行系统评估。结果显示,开采深度和溶腔尺寸的增大显著增加了地表沉降量,最大沉降量从3.15 cm升至12.47 cm,沉降速率从0.28 cm/a增至1.34 cm/a。研究为石盐矿床的安全开采和环境风险评估提供了科学依据。
The study provides an in-depth analysis of the stability of the cavities of common salt underground brine mining deposits and the impact on ground surface settlement.A neural network enhanced geological stability prediction algorithm combined with the International Union of Geological Sciences Geological Stability Dataset,was used to systematically evaluate the stability of the cavity.The results show that the increase in mining depth and cavity size significantly increased the amount of ground surface settlement,with the maximum settlement increasing from 3.15 cm to 12.47 cm,and the rate of settlement increasing from 0.28 cm/a to 1.34 cm/a.The study provides a scientific basis for the safe mining and environmental risk assessment of common salt deposits.
作者
吴经炜
WU Jingwei(Guizhou Geological and Mineral Group Co.,Ltd.,Guiyang 550081,Guizhou,China)
出处
《资源信息与工程》
2025年第3期50-52,56,共4页
Resource Information and Engineering
关键词
石盐矿床
地表沉降
溶腔
稳定性预测
common salt deposit
ground surface settlement
dissolution cavity
stability prediction
