Study On Multipole Array Acoustic Wave Separation Time Difference Extraction And Anisotropic Inversion Method

Compared with conventional acoustic logging,multipole array acoustic waves logging has more abundant formation physical information,which can be used to analyze formation anisotropy,evaluate formation stress and detect fracture strike.Therefore,this logging technology is becoming more and more important in the field of petroleum exploration and development,and its application is also more widely.This paper mainly studies the processing method of multipole array acoustic logging data,in order to improve the processing accuracy and speed.In order to improve the accuracy of component wave time difference extraction,this paper proposes a component wave time difference extraction method based on particle swarm optimization algorithm.This method is to find the maximum value of the correlation coefficient function representing the geometric similarity of the waveform through the global optimization ability of particle swarm optimization algorithm,and then determine the component wave time difference.Compared with the traditional slowness-time correlation method,this method reduces the setting of the time window movement step length and the time difference movement step length parameter,thereby improving the processing accuracy.This method is realized by writing a program in C language,and hooking it to the CIFLog logging processing and interpretation platform.After processing the actual cross-dipole array sonic logging data,a comparative analysis is performed.The results show that the method can extract reliable longitudinal wave,transverse wave and Stoneley wave time difference,and improve the accuracy,which has certain application value.In order to improve the speed and stability of formation anisotropy inversion from multipole array acoustic logging data,this paper proposes a two-dimensional global optimization method using particle swarm optimization algorithm to obtain formation shear wave anisotropy parameters.This method uses the Alford rotation method to obtain the fast and slow shear wave expressions,and establishes two inversion objective functions based on the principles of the smallest Euclidean distance after the fast and slow shear waves are matched and the maximum degree of similarity between the main wave waveforms,and the actual processing is optimized.The best effect is obtained by the particle swarm optimization algorithm to obtain the minimum value of the inversion objective function,and obtain the fast shear wave azimuth angle and the fast and slow shear wave slowness,so as to calculate the anisotropy size and direction.It is realized by C language programming and connected to the CIFLog logging processing and interpretation platform,and the actual data is processed.The results show that the particle swarm optimization algorithm can accurately and reliably invert the shear wave anisotropy parameters of the formation,which improves the processing speed and the stability of the processing results.