Neural network for parameters determination and seismic pattern detection
Kou‐Yuan Huang, Jiun‐De You, Kai‐Ju Chen, Hung‐Lin Lai, An‐Jin Don · 2006
Neural network can determine the parameters of line and hyperbola. So it is adopted to detect line pattern of direct wave and hyperbola pattern of reflection wave in a seismogram. The distance calculation from point to hyperbola is calculated from the time difference. This calculation makes the parameter learning feasible. The neural network can calculate the total error for distance from point to patterns. The parameter learning rule is derived by gradient descent method to minimize the total error. Experimental results show that line and hyperbola can be detected in simulated seismic data. The detection results can improve the seismic interpretation.