摘要
为实现风化基岩含水层富水性的准确预测,以张家峁井田内的28组风化基岩抽水试验钻孔数据作为训练及验证样本,选取风化基岩的岩性组合指数、风化指数、厚度、岩芯采取率、埋深作为评价指标,提出基于鲸鱼优化算法-支持向量机(whale optimization algorithm-support vector machines,WOA-SVM)的风化基岩含水层富水性判别模型。该模型可对无抽水试验资料区域的风化基岩的富水性级别进行预测,综合利用井田内249组勘探钻孔的地质信息,实现井田的风化基岩富水性分区。研究表明,张家峁井田风化基岩整体富水性较弱,且空间分布不均;井田中部和乌兰不拉沟沿线的局部地区存在强富水性区域,但其分布范围较小,中西部和东南部有部分中等富水性区域,东北部及西南部区域几乎全为弱和极弱富水性。该方法预测的结果与实际较为吻合,研究成果可为矿井安全生产提供参考,也为风化基岩富水性预测提供了一种新思路。
In order to accurately predict the water richness of the weathered bedrock aquifer,28 groups of weathered bedrock pumping test borehole data in Zhangjimao minefield were used as training and verification samples,and the lithology combination index,weathering index,thickness,core recovery rate and burial depth of the weathered bedrock were selected as evaluation indexes.Based on whale optimization algorithm-support vector machines(WOA-SVM),a water-rich identification model for weathering bedrock aquifers was proposed.This model can predict the water-rich grade of the weathered bedrock in the area without pumping test data,and realize water-rich zoning of the weathered bedrock in the well field by comprehensive use of the geological information of 249 exploration boreholes.The study shows that the weathered bedrock of Zhangjiamao minefield is weakly water-rich as a whole,and its spatial distribution is uneven.There are strong water-rich areas in the central part of the field and the local area along Wulanbula Gully,but their distribution range is small,there are some moderately water-rich areas in the central-western and southeastern parts,and the northeastern and southwestern areas are weakly and very weakly water-rich almost all the time.The results predicted are more in line with the actual situation,and the research results can provide a reference for the safe production of the mine and a new way of thinking for the prediction of the water-richness of the weathered bedrock.
作者
侯恩科
吴家镁
杨帆
张池
HOU En-ke;WU Jia-mei;YANG Fan;ZHANG Chi(College of Geology and Environment,Xi'an University of Science and Technology,Xi'an 710054,China;Shenmu Zhangjiamao Mining Co.,Ltd.,Shaanxi Coal and Chemical Industry Group,Yulin 719316,China)
出处
《科学技术与工程》
北大核心
2025年第1期119-127,共9页
Science Technology and Engineering
基金
国家自然科学基金(42177174)。
作者简介
第一作者:侯恩科(1963-),男,汉族,陕西扶风人,博士,教授。研究方向:矿井水害防治。E-mail:houek@xust.edu.cn;通信作者:吴家镁(1998-),男,汉族,陕西安康人,硕士研究生。研究方向:矿井水害防治。E-mail:1838605010@qq.com。
