Micro seismic event recognition method based on morphological filtering

Abstract

The invention provides a micro seismic event recognition method based on morphological filtering. The method comprises the steps of conducting spectral analysis on micro seismic data; rectifying a demodulator used for receiving micro seismic signals; selecting structural elements, combining opening operation and closing operation to form a morphological noise filter, and conducting the morphological filtering on the micro seismic data going through spectral analysis; calculating the energy ratio of a long-time window and a short-time window according to the data going through the morphological filtering, and comparing the energy ratio and triggering threshold to identify whether the demodulator has micro seismic events; and conducting microseism pickup according to the micro seismic events. According to the method, the signal to noise ratio of the data can be improved through preprocessing and further filtering treatment; the micro seismic events can be detected quickly and accurately by utilization of the energy ratio method, the fluctuation type of the micro seismic events can be identified through polarization analysis, and first arrival can be picked up accurately by utilization of self-adaptation threshold and the long-time and short-time window energy ratio method.

Description

technical field [0001] The invention relates to petroleum geophysical prospecting technology, in particular to a method for identifying microseismic events based on morphological filtering. Background technique [0002] Real-time dynamic monitoring of oilfield production with microseismic method is of great significance to oilfield development. Because hydraulic fracturing needs to obtain fracturing results relatively quickly, so as to evaluate the fracturing effect, and then adjust the mining plan in time, this requires real-time processing and interpretation of hydraulic fracturing microseismic monitoring data. The currently used microseismic monitoring data processing methods are mainly based on manual identification and first arrival inversion. Due to the long recording time and large amount of data of microseismic monitoring data, it will consume a lot of manpower and time to use manual identification and first-arrival picking of effective microseismic events. On the o...

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Problems solved by technology

Due to the long recording time and large amount of data of microseismic monitoring data, it will consume a lot of manpower and time to use manual identification and first-arrival picking of effective microseismic events. On the one hand, processing hydraulic fracturing monitoring data to obtain fracture distribution images requires A relatively long time cannot meet the needs of real-time monitoring; on the other hand, this method cannot be applied to oil and gas development monitoring

In addition, the microseismic signal is relatively weak and the signal-to-noise ratio is low, making it difficult to identify microseismic events

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