Prediction of sandstone porosity in coal seam roof based on variable mode decomposition and random forest method  

基于VMD和随机森林算法的煤层顶板富水砂岩孔隙度预测

作　　者：Huang Ya-ping Qi Xue-mei Cheng Yan Zhou Ling-ling Yan Jia-hao Huang Fan-rui 黄亚平;祁雪梅;程彦;周玲玲;严家豪;皇范蕤(中国矿业大学资源与地球科学学院,江苏徐州221116;中国煤炭地质总局,北京100038;江苏省地质局第一地质大队,江苏南京210041)

机构地区：[1]School of Resources and Geosciences,China University of Mining and Technology,Xuzhou 221116,China [2]China National Administration of Coal Geology,Beijing 100038,China [3]The First Geological Brigade of Jiangsu Geological Bureau,Nanjing 210041,China

出　　处：《Applied Geophysics》2025年第1期197-208,235,236,共14页应用地球物理(英文版)

基　　金：National Natural Science Foundation of China(Grant No.42274180);National Key Research and Development Program of China(2021YFC2902003).

摘　　要：Evaluation of water richness in sandstone is an important research topic in the prevention and control of mine water disasters,and the water richness in sandstone is closely related to its porosity.The refl ection seismic exploration data have high-density spatial sampling information,which provides an important data basis for the prediction of sandstone porosity in coal seam roofs by using refl ection seismic data.First,the basic principles of the variational mode decomposition(VMD)method and the random forest method are introduced.Then,the geological model of coal seam roof sandstone is constructed,seismic forward modeling is conducted,and random noise is added.The decomposition eff ects of the empirical mode decomposition(EMD)method and VMD method on noisy signals are compared and analyzed.The test results show that the firstorder intrinsic mode functions(IMF1)and IMF2 decomposed by the VMD method contain the main eff ective components of seismic signals.A prediction process of sandstone porosity in coal seam roofs based on the combination of VMD and random forest method is proposed.The feasibility and eff ectiveness of the method are verified by trial calculation in the porosity prediction of model data.Taking the actual coalfield refl ection seismic data as an example,the sandstone porosity of the 8 coal seam roof is predicted.The application results show the potential application value of the new porosity prediction method proposed in this study.This method has important theoretical guiding significance for evaluating water richness in coal seam roof sandstone and the prevention and control of mine water disasters.煤层顶板砂岩富水严重影响煤矿的安全开采,是矿井水害防治的重要研究内容,砂岩富水性与孔隙度密切相关。反射地震勘探数据提供了高密度空间采样信息,利用反射地震数据开展煤层顶板砂岩孔隙度预测可获得高精度的空间分布结果。首先介绍了变模态分解法和随机森林算法的基本原理;然后构建了煤层顶板砂岩地质模型,对其进行地震正演模拟并添加随机噪音,对比分析了经验模态分解法和变模态分解法对含噪信号的分解效果,测试结果表明变模态分解法分解的IMF1和IMF2包含了地震信号的主要有效成分;提出了基于变模态分解和随机森林算法结合的孔隙度预测流程,在模型数据孔隙度预测中进行了试算,验证了方法的可行性。以实际煤田反射地震数据为例,预测了煤层顶板砂岩的孔隙度,显示了本文提出的孔隙度预测新方法潜在的应用价值,对煤层顶板砂岩富水性评价以及矿井水害防治均具有重要的理论指导意义。

关 键 词：VMD random forest method coal seams SANDSTONE POROSITY 

分 类 号：P31[天文地球—固体地球物理学]