High-precision pickup method of first arrival of microseism

Abstract

The invention discloses a high-precision pickup method of the first arrival of microseism. The high-precision pickup method comprises the steps that the signal to noise ratio of microseism data is increased through the higher moment method; according to the fact of whether the current microseism wave meets all the following constraint conditions, namely the relation between the magnitude of amplitude and space, the lineup apparent velocity and the polarization characteristics, whether the microseism wave is the first arrival of the microseism is judged; according to perforation data, actual event data and the change rule of constraint conditions, by the adoption of a statistical analysis method, the threshold value of the constraint conditions is determined; under the constraint of the amplitude and the apparent velocity, according to the temporal and spatial variation characteristics of the travel time first arrival of a microseism event, the change law of the energy, the apparent velocity and the relevant information of travel time first arrival points in a big fixed time window and a small sliding time window is utilized for automatic pickup of the first arrival of the microseism event by means of the repeated iteration method. Application effects of the actual data of different areas show that the high-precision pickup method of the first arrival of the microseism is high in adaptability and reliable in result.

Description

technical field [0001] The invention relates to a method for picking up a microseismic first arrival with high precision, in particular to a method for picking up a microseismic first arrival with high precision. Background technique [0002] At present, there are mainly several methods for automatic first-arrival picking or phase identification of seismic signals, including energy ratio method, AIC algorithm, neural network method, fractal and fractal dimension method, polarization analysis method, and Kalman estimation, among which energy ratio method, AIC algorithm and neural network methods are most commonly used. [0003] The energy ratio method is the fastest and most widely used automatic picking method. In 1981, Kannasewich proposed to design and calculate the absolute value of seismic data, the long time window (LTA) and short time window (STA) of the energy or envelope surface as a characteristic function for identifying effective events. This method calculates th...

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Problems solved by technology

However, this method has its drawbacks: due to the influence of short time windows, the first arrival cannot be picked up accurately; it is difficult to distinguish useful seismic signals from high-amplitude noise

[0006] However, microseismic signals are different from general reflection seismic signals, which are characterized by weak useful signals, complex wave fields, and multiple types of seismic phases.

Therefore, the above-mentioned existing seismic signal automatic picking methods all have the problem of low accuracy for the first-arrival picking of micro-seismic signals

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