基于WOA-SVM判别模型的风化基岩富水性评价——以神府煤田张家峁煤矿为例
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1.西安科技大学 地质与环境学院;2.陕煤集团神木张家峁矿业有限公司

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TD742

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Evaluation of water-richness of weathered bedrock based on the WOA-SVM discriminant model ——Take Zhangjiamao Coal Mine in Shenfu Coal Field as an Example
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1.College of Geology and Environment,Xi’an University of Science and Technology,Xi’an;2.Shenmu Zhangjiamao Mining Co,Ltd,Shaanxi Coal and Chemical Idustry Group,Yulin,Shaanxi

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    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,提出基于鲸鱼算法优化支持向量机的风化基岩含水层富水性判别模型(WOA-SVM)。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。

    Abstract:

    : In order to accurately predict the water-richness of the weathered bedrock aquifer, a weathered bedrock aquifer water-richness discrimination model based on Whale Algorithm Optimized Support Vector Machine (WOA-SVM) is proposed by using 28 sets of weathered bedrock pumping test boreholes in Zhangjiamao minefield as the training and validation samples, and selecting the lithological assemblage index, weathering index, thickness, core take rate, and depth of burial of the weathered bedrock as the evaluation indexes. The model can predict the water-richness level of the weathered bedrock in the area without pumping test data, and comprehensively utilize the geological information of 249 groups of exploration boreholes in the wellfield to realize the water-richness zoning of the weathered bedrock in the minefield. 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 by this method 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.

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侯恩科,吴家镁,杨帆,等. 基于WOA-SVM判别模型的风化基岩富水性评价——以神府煤田张家峁煤矿为例[J]. 科学技术与工程, , ():

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  • 收稿日期:2024-03-05
  • 最后修改日期:2024-04-24
  • 录用日期:2024-05-02
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