Research And Application Of Q Compensation Technology In Seismic Data Processing

Due to the incomplete elasticity and non-uniformity of the underground medium,with different time and different properties of underground medium,the seismic wave produces different degrees of amplitude energy attenuation and phase distortion when propagating in the underground medium and then the frequency band becomes narrower and the main frequency shifts to the low frequency direction,which greatly reduces the imaging accuracy and recognition of seismic data.Characterizing the basic properties of absorption attenuation of underground media by establishing an attenuation model is one of the main means of studying the absorption attenuation law of strata,and at the same time lays a theoretical foundation for the study of quality factor Q value extraction and inverse Q filtering methods.In this paper,based on the attenuation model,a variety of inverse Q filtering methods and Q value extraction and compensation techniques are discussed in detail.The theoretical model and the actual pre-stack seismic data processing results confirm the effectiveness and feasibility of the method in this paper.The theoretical and practical research significance of the main research contents are as follows:(1)This paper validates several common attenuation models and compares them with the commonly used Kolsky-Futterman model to analyze the difference between their speed dispersion and attenuation coefficient with frequency,laying a theoretical foundation for subsequent inverse Q filtering and compensation techniques.(2)The inverse Q filtering method mainly aims at the characteristics of stratum absorption and attenuation,and compensates the amplitude energy and phase distortion of the attenuated seismic wavelet,so that the seismic data resolution will be improved of.This paper mainly describes several representative inverse Q filtering methods.By comparing the theoretical models and actual data,the advantages and disadvantages and application effects of each method are analyzed,and the one with the best application effect and matching the characteristics of the target seismic data is selected.Inverse Q filtering method is the most effective to improve the imaging effect of seismic data.(3)In actual production,it is often believed that inverse Q filtering is based on the constant Q value for compensation,with low recognition and limited method usage.The more feasible Q compensation technology is to use the extraction of continuously changing Q value and inverse Q filtering method to compensate the seismic data.In Q compensation,Q value extraction becomes a key issue that affects the compensation effect.This article introduces two methods: one is the Lee's empirical formula method,which is strong in maneuverability,simple in method,and stable in the Q value field,but there is no strict theoretical basis.The other is a time-frequency domain Q value extraction method based on generalized S transform,which has strict theoretical derivation and practical application effects.Tests on the theoretical model and actual data of the target seismic data show that the method can be used to estimate the Q value of the target seismic data.(4)Either the inverse Q filtering method or the Q compensation technique is mostly used for post-stack data processing,while it is rarely used in pre-stack seismic data processing.Because the processing of seismic data overlay and other processing will destroy the original amplitude information of the data section,the post-stack seismic data contains less information than the pre-stack seismic data.Therefore,high-resolution processing of the pre-stack seismic data can better meet the imaging effect and the requirements of reservoir prediction accuracy.In this paper,the dynamic Q value estimation method is combined with the optimized inverse Q filtering method to perform Q compensation on the pre-stack angle gathers.The application effects of constant Q value inverse Q filter compensation and dynamic Q value compensation in actual data are compared and analyzed.(5)All the inverse Q filtering method' amplitude compensation operators have high-pass filtering characteristics.In the real data processing,the inverse Q filtering method can improve the resolution of seismic data effectively,but the loss of low frequency will result in the loss of effective information correspondingly,and the reliability of seismic data will also reduce.So it is not the realization of high-resolution processing strictly.In order to solve this problem,the low-frequency compensation is performed on the seismic data after inverse Q filtering,and the low-frequency components of the original seismic data after phase correction and the high-frequency components of seismic data after inverse Q filtering are superimposed in the frequency domain.Reorganize the seismic data in the frequency domain to preserve the low-frequency information of the original data and widen the high-frequency components in the future to achieve high-resolution processing of seismic data in a true sense.