基于时频稀疏性分析法的低信噪比微震事件识别与恢复

Automatic event detection and event recovery in low SNR microseismic signals based on time-frequency sparseness

微震监测是直观评价压裂过程和压裂效果的有效手段.微震事件识别是微震监测的首要步骤.然而对于低信噪比微震监测数据,常规识别方法很难取得满意效果.基于微震事件在时频域中的稀疏性,本文提出利用Renyi熵值表示微震监测数据的时频稀疏程度,并以时频距离为约束条件,建立以低熵值的道数为判别阈值的目标函数.本文方法能在识别出微震事件的同时,恢复出较为清晰的微震事件.通过数值计算和对实际监测数据的测试,表明该方法对低信噪比的微震监测数据有较好的处理效果.

Microseismic monitoring is an effective tool for evaluating the fracturing process and its final results. Event detection is the first step of this monitoring. However, for low SNR microseismic monitoring records, it is difficult to obtain satisfactory results using conventional detection methods. According to time-frequency sparsness of microseismic events, the Renyi entropy method is used to measure sparseness of microseismic monitor records. A target function of event detection is created which takes the number of low entropy value traces as thresholding under time-frequency constraint conditions. This method can detect microseismic events and restore clearer microseismic events simultaneously. Tests on synthesis data and real records show that this method has a good performance in processing low-SNR microseismic records.