Broad-band High Resolution Seismic Impedance Inversion

Seismic wave impedance inversion is an important method for reservoir prediction and fluid identification.Compressed sensing algorithm has high accuracy and high resolution.It has become a research hotspot in the field of seismic signal processing and is used to solve many problems in seismic reservoir prediction.The application of compressed sensing algorithm in seismic wave impedance inversion is mainly based on basis-pursuit impedance inversion and matching-pursuit impedance inversion,and the compression sensing algorithm can also be used to obtain the impedance profile in pre-stack inversion.The basis-pursuit algorithm is a seismic signal processing method that uses a wavelet signal to construct a wavelet library and projects the original seismic signal onto the wavelet library to obtain a reflection coefficient.This paper aims to improve the basis-pursuit algorithm for the acquisition of broad-band and low-frequency information,so that the basis-pursuit algorithm can better utilize the low-frequency information enriched by seismic data of the marine cable and improve the resolution of the inversion method.Based on the purpose of this research,this paper uses low-frequency information as the entry point,and uses the low-frequency information,single-trace synthetic record and synthetic seismic profile to discuss the high-resolution advantages brought by low-frequency information,and proves the necessity and rationality of mining low-frequency information.Then the improvement of the constraint term and the formula derivation are carried out on the basis-pursuit method.The low-frequency sparse double-constrained basis-pursuit impedance inversion method which can better utilize the low-frequency information is obtained.Specifically,the main research work is as follows:(1)Firstly,the basic principles of the basis-pursuit inversion method are studied,and the differences and advantages of the compressed sensing algorithm compared with the traditional signal processing methods are analyzed.Compressed sensing is different from the traditional signal processing method.By constructing a wavelet library and projecting the original signal through the basis-pursuit algorithm onto the wavelet library,the sparse representation of the original signal is obtained,and a small amount of the high-precision reconstruction of the original signal is based on the principle frame of the basis-pursuit algorithm.The convolution model is introduced to introduce the basic application of the basis-pursuit algorithm in seismic signal processing.(2)Secondly,the low frequency advantage in the broad-band is discussed.In the discussion,the frequency domain basis-pursuit frequency supplement method is used to discuss the following three aspects: First,the low frequency advantage of the wavelet is discussed and analyzed.To clarify that the wavelets with rich low-frequency information have smaller side-lobe effects;second,discuss and analyze the low-frequency advantages of single-trace record,and clarify that single-trace record with rich low-frequency information have stronger amplitudes;third,Analyze the low-frequency advantages of synthetic seismic profiles,and clarify that seismic profiles with low-frequency information have higher resolution.(3)The constraint tracking term is improved for the basis pursuit inversion method.The low frequency constraint term is added to the original norm sparse term,and the traditional basis pursuit inversion method is developed into the low frequency sparse double constraint basis pursuit inversion method.The actual work area data and logging data verify the effectiveness of the method and reflect the theoretical and practical application value of this paper.