地震属性参数在煤层厚度预测中的应用

Application of seismic attribute parameters in forecasting coal seam thickness

摘要: 薄煤层厚度的变化必然引起地震波场属性参数的变化。借鉴油气勘探中提取地震属性参数技术,通过引入小波变换工具,在不同频段提取小波域属性参数,并利用BP神经网络技术进行多参数煤层厚度的综合预测,经实际资料验证,预测精度较高,误差小于10%。

Abstract: The changes of thickness consequentially bring the changes of seismic wave field attribute parameter,therefore,for reference abstraction seismic attributes technology is used in the course of exploration.At the same time introduce wavelet transform instrument,abstracting wavelet field attribute parameter in different frequency bands,and utilize BP neural network technology proceed the aggregate prediction of the multiparameter thickness of coal seam.By real data verification,the technology is feasible and the forecast with the result is less than 10% of differ.