Weak signal identification in microseismic monitoring with multi-scale morphology

Data acquired by borehole microseismic monitoring is characterized by low signal-to-noise ratio and weak energy. So it is very difficult to identify signals. We propose in this paper a multi-scale morphological approach for weak signal identification. There are some small difference in amplitude and duration between noise and signal, Therefore it can be carried out in digital analysis based on morphology. This approach decomposes data morphological characteristics, and analyzes waveform shape variance details. With different-scale structural elements, the original data can be decomposed into different scales. Then characteristics of weak signals and noise in different scales are identified and noise would be eliminated. Examples of both synthetic and real data show that the proposed approach can identify weak signals and suppress noise, which proves the effectiveness and practicability of the proposed approach.