Automatic Interpretation Of Seismic Levels And Fault

As the technology matures of seismic data interpretation, the interpretation of seismic levels and fault has become a trend in geological exploration.This paper takes seismic waves as the research object, Applying pattern recognition, wavelet analysis and intelligent ants and other mathematical alorithm to complete the automatic interpretation of seismic levels a nd faults. Primary research content and results described as follows:Through analyzing the characteristics of data to complete the SEG_Y documents parse, to complete data storage. Since the acquisition of seismic data is influenced by many factors, would generated noise. This paper use wavelet threshold filtering technique to complete waves denoising, providing high-quality data for the layer track. Then use coherent technology on seismic data to form the coherent cubes, providing fit data for fault trace.According to the characteristic of axis waveform, this paper use SOFM to track the layer. Since more too much neurons would cause burden to the net. To ensure the parameter characteristics of seismic wave, this paper use the component analysis to complete the reducing the dimension of the seismic waveform. In this paper using the SOFM net based on component analysis to track the layer, not only retains the characteristics of seismic waveforms but also improve the efficiency of tracking layer.According to the characteristics of the coherent cubes, this paper use ant colony to complete the automatic fault trace. Ants tracing algorithm time comple xity is affected by the number of ants and the iteration. Optimizing the number of ants before tracking, and constantly adjust the number of ants to improve rate of fault tracing. Experimental results show that the improved ant colony not only can identify the fault lines correctly, but also improve the tracking of the fault lines' speed.