High accurate automated first break picking method for seismic records from high density acquisition in the areas with complex surface

As the application of high‐density high‐efficiency acquisition technology becomes more and more wide, the areas with complex surface conditions gradually become target exploration areas, and the first break picking work of massive low signal‐to‐noise ratio (S/N) data is a big challenge. The traditional method spends a lot of manpower and time to interactively pick first breaks, a large amount of interactive work affects the accuracy and efficiency of picking. In order to overcome the shortcoming that traditional methods have weak anti‐noise to low S/N primary wave, this paper proposes a high accurate automated first break picking method for low S/N primary wave from high density acquisition in the areas with complex surface. Firstly, this method determines first break time window using multi‐azimuth spatial interpolation technology; then uses the improved clustering algorithm to initially pick first breaks; and then perform multi‐angle comprehensive quality evaluation to first breaks according to the following sequence: "single trace → spread → single shot → multiple shots" to identify the abnormal first breaks ; finally determine the optimal path through the constructed evaluation function and using the ant colony algorithm to correct abnormal first breaks. Multi‐azimuth time window spatial interpolation technology provides the base for accurately picking first break time; the clustering algorithm can effectively improve the picking accuracy rate of low S/N primary waves; the multi‐angle comprehensive quality evaluation can accurately and effectively eliminate abnormal first breaks; the ant colony algorithm can effectively improve the correction quality of low S/N abnormal first breaks. By example analysis and comparing with the commonly used Akaike Information Criterion(AIC) method, the automated first break picking theory and technology studied in this paper has high picking accuracy and the ability to stably process low S/N seismic data, and has a significant effect on seismic records from high density acquisition in the areas with complex surface, and can meet the requirements of accuracy and efficiency for massive data near‐surface modeling and statics calculation.

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