A cave detection method based on the similarity lateral change rate of dip angle in frequency domain

Abstract

The invention provides a method for detecting karst caves based on the similarity lateral change rate of dip angle in the frequency domain, and belongs to the field of petroleum geophysical exploration and development. The method comprises: the first step, carrying out Hilbert transformation to the seismic data, converting the seismic data in the time domain to the complex number domain, obtaining the Hilbert seismic trace, and then calculating the instantaneous phase and frequency domain dip of the Hilbert seismic trace; The frequency domain dip angle obtained in one step is used for similarity detection to find outliers with poor continuity, that is, to use the seismic wavefield information to calculate the correlation between channels, to highlight the irrelevant anomaly boundaries, and to identify the subtle lateral inconsistencies in rock formations. The uniformity and fracture characteristics make the response characteristics of fractures and caves amplified; the third step is to carry out the edge detection of the similarity of the dip angle in the frequency domain to determine the development area of ​​the cave reservoir.

Description

technical field [0001] The invention belongs to the field of petroleum geophysical exploration and development, and specifically relates to a cave detection method based on the similarity lateral change rate of the frequency domain dip angle, which uses the frequency domain dip angle attribute results to carry out the edge detection scan of the similarity lateral change rate, which can be applied to Detection and identification of dissolved vugs in carbonate reservoirs in oilfield exploration. Background technique [0002] Similarity lateral rate of change is the similarity of seismic traces. At present, the more popular algorithms are based on cross-correlation and similarity-based algorithms. The main defect is that it only calculates the correlation relationship between adjacent traces and central traces, and cannot consider the correlation between adjacent traces. The relationship between each other in terms of structure; the second is that the combination of correlation...

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Problems solved by technology

[0002] Similarity lateral rate of change is the similarity of seismic traces. At present, the more popular algorithms are based on cross-correlation and similarity-based algorithms. The main defect is that it only calculates the correlation relationship between adjacent traces and central traces, and cannot consider the correlation between adjacent traces. The relationship between each other in terms of structure; the second is that the combination of correlation coefficients calculated in different directions has an average effect, and the more the number of calculation channels is, the more serious the average effect is, which reduces the spatial resolution and the continuity of abnormalities

[0004] The similarity lateral change rate is the similarity (coherence) of the seismic trace. At present, the technology development is relatively mature. The application in many work areas for many years shows that this method has a certain effect on detecting the abnormal points of the same axis on the seismic section. , but when the corresponding geological bodies are developed simultaneously with fractures and caves of different scales, this detection method can reflect the overall development of fractures and caves, but cannot distinguish the development characteristics of fractures and caves

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