摘要
针对煤矿井下开采中严重影响巷道布设和掘进效率的分叉煤层问题,本文借助于楔形模型和90°相位Ricker子波开展分叉煤层时间域分辨率的探讨.在上下煤层厚度小于地震子波λ/4的情况下,将Rayleigh准则和Ricker准则扩展应用到这种特殊的薄互层中,扩展后的Rayleigh准则和Ricker准则分别对应于调谐曲线中的调谐厚度点和视厚度零点,即分别指示泥岩夹层的定量和定性识别情况.利用AVF技术对泥岩夹层分辨率的影响因素进行分析,结果表明:在两种分辨率准则条件下,上下煤层厚度、泥岩夹层厚度与子波峰值频率具有反比例函数关系;定量识别泥岩夹层所基于的子波峰值频率要高于定性识别的情况;泥岩夹层分辨率极限的精准读取与识别受到地震记录信噪比的影响.综上所述,该讨论可为地震方法分辨和识别分叉煤层提供理论依据.
In this paper,we discussed the resolution of bifurcate coal seam in time domain by using the wedge model and 90°-phase Ricker wavelet,for its severely impact on roadway arrangement and drivage efficiency of the underground coal mining. We extended the Rayleigh and Ricker criterion for the mudstone interlayer of the bifurcate coal seam,in the case that the upper and lower coal seams are less than λ/4 of wavelet. The extended Rayleigh and Ricker criterion indicated the tuning thickness point and apparent thickness zero point in the tuning curve of mudstone interlayer,corresponding to the quantitative and qualitative identification situation,respectively. Thereafter,the influence factors of mudstone interlayer resolution was analyzed by using AVF technique. The peakfrequency of wavelet shows an inverse proportional function relationship with the thickness of upper and lower coal seams,mudstone interlayer. The peak-frequency of wavelet which corresponding to quantitative identification is higher than the qualitative identification situation. Additionally, the accurate identification of the resolution limit for mudstone interlayer can be influenced by the SNR of seismograms. Therefore,this discussion will provide a theoretical basis for the bifurcate coal seam resolving and identifying by seismic method.
作者
吴海波
张平松
董守华
WU Hai-bo;ZHANG Ping-song;DONG Shou-hua(School of Earth and Environment,Anhui University of Science and Technology,Anhui Huainan 232001,China;School of Resources and Geosciences,China University of Mining and Technology,Jiangsu Xuzhou 221116,China)
出处
《地球物理学进展》
CSCD
北大核心
2018年第4期1603-1608,共6页
Progress in Geophysics
基金
安徽省自然科学基金(1608085QD81)
安徽高校自然科学研究项目(KJ2016SD17
KJ2018A0071)
安徽理工大学青年教师科学研究基金重点项目(QN2017202)联合资助
