Potential energy wave function domain seismic data quality factor estimation method

Abstract

The invention belongs to the field of geophysical processing methods for oil-gas exploration. The invention discloses a potential energy wave function domain seismic data quality factor estimation method. The method comprises the following steps: decomposing seismic data of a target area in a potential energy-wave function domain by using a Schrodinger equation of non-relativistic quantum mechanics, constructing an adaptive basis function through a Hamiltonian matrix, and calculating a mapping coefficient sequence of the seismic data in a potential energy-wave function space channel by channel; and calculating the Q estimation result of the adjacent horizon by using the mapping coefficient sequence of the potential energy-wave function space in combination with a least square method. The invention provides a seismic signal self-adaptive decomposition algorithm based on a quantum mechanics Schrodinger equation, derives a potential energy-wave function domain Q estimation algorithm, develops a high-precision potential energy-wave function domain seismic data Q estimation method, improves the accuracy of Q estimation, and provides a seismic signal self-adaptive decomposition algorithm based on a quantum mechanics Schrodinger equation. The problems that a traditional Q estimation method needs to select a frequency band and various assumption preconditions exist are solved.

Description

technical field [0001] The invention relates to the field of geophysical processing methods for oil and gas exploration, in particular to a method for estimating the quality factor of seismic data using the principle of quantum mechanics. Background technique [0002] The attenuation of seismic waves originates from the anelastic process that occurs during propagation. Attenuation can usually be divided into two parts, apparent loss and intrinsic loss. Apparent loss includes energy loss caused by processes such as formation disturbance and scattering effects and some resonance phenomena, while intrinsic loss mainly comes from energy loss caused by converting seismic energy into thermal energy and fluid flow. Apparent losses are related to media properties such as delamination and impedance contrast, while intrinsic losses are related to media properties such as fluid content, permeability and viscosity. This intrinsic medium property, which causes seismic wave amplitude at...

AI Technical Summary

Problems solved by technology

Time-domain Q estimation methods, such as rise time method and amplitude decay method, require real amplitude information, but due to the influence of wavefront expansion and transmission loss, it is difficult to obtain real amplitude information from actual seismic data

Frequency domain Q estimation methods such as spectral ratio method, peak frequency offset method, etc., the main difficulty is that there is spectral interference between adjacent reflections, and it is necessary to select an appropriate frequency band for Q estimation. The Q values ​​estimated by different frequency bands are quite different. The spectral fluctuations present in , make selecting an appropriate frequency band a very tedious task, and such methods are sensitive to noise

The time-frequency domain Q estimation method reduces the spectral interference and other problems existing in the frequency domain Q estimation method, although the characteristics of different time-frequency analysis methods will also affect the accuracy of Q estimation, using variable window time-frequency analysis methods such as wavelet transform It has been proved that the time-frequency analysis method using a fixed window, such as the short-time Fourier transform, can give a more robust and accurate Q estimate, but there is still the problem of selecting an appropriate frequency band for Q estimation

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