CN106125134A - Based on the geological data signal-noise ratio computation method of window during hyperbolic - Google Patents

Abstract

The invention provides a kind of based on the geological data signal-noise ratio computation method of window during hyperbolic.Described method includes step: window during selected hyperbolic in seismic data；When removing hyperbolic, the random disturbances in window data, obtains the first useful signal；Remove the relevant interference noise in the first useful signal, obtain the second useful signal；When utilizing hyperbolic, window data and the second useful signal, be calculated signal to noise ratio.The problem that when window is chosen when the present invention can solve the problem that, effective reflected energy is uneven；When can improve signal-to-noise ratio computation, useful signal asks for the problem forbidden so that signal-to-noise ratio computation more accurate and effective；Can ask for out by useful signal efficiently, accurately calculate seismic data signal to noise ratio, and method is simple.

Description

Seismic data signal-to-noise ratio calculation method based on hyperbolic time window

Technical Field

The invention relates to the technical field of seismic data signal-to-noise ratio calculation, in particular to a seismic data signal-to-noise ratio calculation method based on a hyperbolic time window, which is suitable for petroleum seismic exploration, and more particularly relates to a method for separating seismic data random interference and related interference by adopting an open hyperbolic time window and different methods to obtain effective signal energy so as to calculate the seismic data signal-to-noise ratio.

Background

Generally, in the field of petroleum seismic exploration, the signal-to-noise ratio is one of important indexes for measuring seismic data, and on one hand, the noise-removal method can quantitatively evaluate the quality of the noise-removal method in the seismic processing process; on the other hand, the quality of the seismic acquisition data is often evaluated in practice through calculation of the signal-to-noise ratio of the seismic data. The higher the signal-to-noise ratio of the seismic data is, the better the quality is, and the more credible the processing result is. Therefore, the signal-to-noise ratio calculation has important significance in the processing and explaining stages, and has great reference value for the quality control of the denoising method.

For the calculation of the signal-to-noise ratio of seismic data, a conventional method is to open a rectangular time window and perform the calculation of the signal-to-noise ratio on data in the time window by using methods such as an energy superposition method and a cross-correlation method, but the application effect of the methods is not good, for example, the problem that the calculation of effective signals is not accurate enough exists.

Disclosure of Invention

The present invention aims to address at least one of the above-mentioned deficiencies of the prior art. For example, one of the objectives of the present invention is to solve the problem of non-uniform effective reflected energy due to the time window selection. Another object of the present invention is to solve the problem of inaccurate effective signal acquisition in the snr calculation.

In order to achieve the above object, the present invention provides a hyperbolic time window-based seismic data signal-to-noise ratio calculation method, which comprises the steps of: selecting a hyperbolic time window in the seismic data; removing random interference in hyperbolic time window data to obtain a first effective signal; removing relevant interference noise in the first effective signal to obtain a second effective signal; and calculating to obtain the signal-to-noise ratio by using the hyperbolic time window data and the second effective signal.

In an exemplary embodiment of the present invention, the step of obtaining the first valid signal may include: performing fast Fourier transform on the data in the hyperbolic time window to transform the hyperbolic time window data from a time domain to an F-K domain; setting a threshold value in the F-K domain, and removing random interference; then, inverse fourier transform is performed to obtain a first effective signal.

In an exemplary embodiment of the present invention, the step of obtaining the second effective signal may be implemented by performing a correlation analysis by using a characteristic that the signals of the adjacent seismic traces in the first effective signal have correlation, but the noise has no correlation.

In an exemplary embodiment of the present invention, the step of calculating the signal-to-noise ratio may be performed according to formula (1), where formula (1) is

Wherein, the SNR is the signal-to-noise ratio,

$A_x\left(f\right)=\frac{1}{m}\[|X_1\left(f\right){|}^2+|X_2\left(f\right){|}^2+...+|X_m\left(f\right){|}^2\],$

wherein m represents the number of seismic channels, i is more than or equal to 1 and less than or equal to m, f is frequency, A_x(f) Amplitude spectra of seismic data in hyperbolic time window ranges without random disturbance removal, X₁(f) For the first trace of seismic data within a hyperbolic time window range without random interference removal, X₂(f) For the spectrum of the second seismic data within the hyperbolic time window range without random interference removal, X_m(f) For the frequency spectrum of the mth trace seismic data within the hyperbolic time window range without random interference removal,

$A_s\left(f\right)=\frac{1}{2(m-1)}\underset{i=1}{\overset{m-1}{\Σ}}\[Y_i\left(f\right)Y_{i+1}\left(f\right)+Y_{i+1}\left(f\right)Y_i\left(f\right)\],$

wherein A is_s(f) Is the frequency spectrum, Y, of the second significant signal in the hyperbolic time window range_i(f) For the frequency spectrum of the ith trace of seismic data within the hyperbolic time window range with random interference removed, Y_i+1(f) The spectrum of the (i + 1) th seismic data in the hyperbolic time window range with random interference removed.

Compared with the prior art, the invention has the beneficial effects that: the problem of uneven effective reflection energy during time window selection can be solved; the problem that effective signals are not accurately obtained during signal-to-noise ratio calculation can be solved, so that the signal-to-noise ratio calculation is more accurate and effective.

Drawings

FIG. 1 illustrates an example of selecting hyperbolic time windows in seismic data in accordance with a method of the present invention.

Fig. 2 shows an example of a given hyperbolic time window range and frequency threshold in accordance with the method of the present invention.

Fig. 3 shows an example of the signal and noise band range when removing random interference according to the method of the invention.

FIG. 4 shows an example of a signal-to-noise ratio curve for seismic data obtained according to the method of the present invention.

Detailed Description

Hereinafter, the hyperbolic time window-based seismic data signal-to-noise ratio calculation method of the invention will be described in detail with reference to the accompanying drawings and exemplary embodiments.

In an exemplary embodiment of the invention, the hyperbolic time window-based seismic data signal-to-noise ratio calculation method can be implemented according to the following steps:

1. firstly, selecting a hyperbolic time window on the seismic record to calculate the signal-to-noise ratio, and setting that m channels are arranged on the seismic record x (t) of the selected time window, and each channel is provided with n sampling points. A hyperbolic time window is a time window (seismic wave effective signal, the event is a hyperbola) that is opened on the seismic record along the event of the seismic wave.

2. Performing fast Fourier transform on the data in the time window, and transforming the seismic data from a time domain to a frequency wave number domain (which can be called as an F-K domain for short); selecting a threshold value in a frequency wave number domain, and removing random interference; and performing inverse Fourier transform to obtain a record y (t) (which can be called as a first effective signal) without random interference, wherein the seismic record y (t) consists of an effective signal s (t) (which can be called as a second effective signal) and relevant interference noise n (t), and is shown in the following formula (1).

y_i(t)＝s_i(t)+n_i(t) (1)

Where, i is 1, 2, 3 … …, m (m is the number of seismic traces), and t is time.

3. The record with random interference removed is subjected to correlation analysis by utilizing the characteristic that the adjacent seismic channel signals have correlation and the noise has no correlation, as shown in the following formula (2).

$\begin{array}{c}{y}_i\left(t\right)\⊗y_{i+1}\left(t\right)=\left(s_i\right(t)+n_i\left(t\right))\⊗\left(s_{i+1}\right(t)+n_{i+1}\left(t\right))\\ =s_i\left(t\right)\⊗s_{i+1}\left(t\right)+s_i\left(t\right)\⊗n_{i+1}\left(t\right)+n_i\left(t\right)\⊗s_{i+1}\left(t\right)+n_i\left(t\right)\⊗n_{i+1}\left(t\right)\\ =s_i\left(t\right)\⊗s_{i+1}\left(t\right)\end{array}---\left(2\right)$

Wherein,are the relevant symbols.

4. The spectrum of the cross-correlation is shown below:

$R_{x_i,x_{i+1}}\left(f\right)=Y_i\left(f\right)Y_{i+1}\left(f\right)---\left(3\right)$

wherein f is the frequency (Hz),for the cross-correlation spectrum of the ith trace seismic data and the (i + 1) th trace seismic data, Y_i(f) Is the frequency spectrum of the ith trace of seismic data, Y_i+1(f) The spectrum of the i +1 th seismic data.

5. Next, a signal portion (also referred to as a second effective signal) is calculated from the cross-correlation and the cross-power spectrum. Here, the present invention considers the case where the cross-correlation of the ith track and the (i + 1) th track is different from the cross-correlation of the (i + 1) th track and the ith track.

$A_s\left(f\right)=\frac{1}{2(m-1)}\underset{i=1}{\overset{m-1}{\Σ}}\[Y_i\left(f\right)Y_{i+1}\left(f\right)+Y_{i+1}\left(f\right)Y_i\left(f\right)\]---\left(4\right)$

Wherein A is_s(f) Is the frequency spectrum, Y, of the second significant signal in the hyperbolic time window range_i(f) For the frequency spectrum of the ith trace of seismic data within the hyperbolic time window range with random interference removed, Y_i+1(f) The spectrum of the (i + 1) th seismic data in the hyperbolic time window range with random interference removed.

6. And then, according to the concept of the power spectrum, the average power spectrum recorded m channels before the random interference is removed is obtained.

$A_x\left(f\right)=\frac{1}{m}\[|X_1\left(f\right){|}^2+|X_2\left(f\right){|}^2+...+|X_m\left(f\right){|}^2\]---\left(5\right)$

Wherein f is frequency (Hz), A_x(f) Frequency spectrum, X, being seismic data in the hyperbolic time window range₁(f) For the first trace of seismic data within a hyperbolic time window range without random interference removal, X₂(f) For the spectrum of the second seismic data within the hyperbolic time window range without random interference removal, X_m(f) And the frequency spectrum of the mth path of seismic data in the hyperbolic time window range without random interference removal.

7. And finally, separating the noise to obtain a signal-to-noise ratio (SNR) formula.

$SNR=\frac{A_s\left(f\right)}{A_n\left(f\right)}=\frac{A_s\left(f\right)}{A_x\left(f\right)-A_s\left(f\right)}---\left(6\right)$

The method can conveniently calculate the signal-to-noise ratio of the seismic data, and the hyperbolic time window is used for data acquisition, so that the effective reflection energy is more balanced; and random interference and related interference are comprehensively considered, and the required signal noise is more accurate. Therefore, the signal-to-noise ratio (SNR) value obtained by the method can be used as a reference standard to evaluate the quality of different seismic data.

One specific example of the present invention is described below with reference to the accompanying drawings.

FIG. 1 illustrates an example of selecting hyperbolic time windows in seismic data according to a method of the present invention, where the abscissa represents the track number in tracks and the ordinate represents time in ms (milliseconds). Fig. 2 shows an example of a given hyperbolic time window range and frequency threshold in accordance with the method of the present invention. Fig. 3 shows an example of the signal and noise band range when removing random interference according to the method of the present invention, wherein the ordinate (| x (f) |) is decibel (db) and the abscissa is frequency (Hz). FIG. 4 shows an example of a signal-to-noise ratio curve for seismic data obtained according to the method of the present invention, where the abscissa represents the trace number in units of traces and the ordinate represents the magnitude of the signal-to-noise ratio, without units.

The seismic data signal-to-noise ratio calculation method based on the hyperbolic time window is carried out according to the following steps:

a. as shown in fig. 1, firstly, selecting a hyperbolic time window according to seismic data;

b. the data in the hyperbolic time window is fast fourier transformed, and a threshold is artificially given (as shown in fig. 2) to specify the range of the signal and the random interference (as shown in fig. 3, wherein f1 represents the start frequency, f2 represents the end frequency, we define the signal between f1 and f2 as the effective signal, and the rest as noise), remove the random interference, and keep the effective signal.

c. Using the correlation spectrum for the part of the effective signalRemoving related interference by the method, and obtaining the final signal energy E_s。

d. The noise energy is obtained by subtracting the effective signal from the original recording, and the signal-to-noise ratio is obtained (as shown in fig. 4).

In conclusion, the method can efficiently extract the effective signals, accurately calculate the signal-to-noise ratio of the seismic data, and is simple and easy to implement.

Compared with the prior art, the invention has the beneficial effects that: (1) selecting a hyperbolic time window: different from the traditional calculation by opening a rectangular time window, the method disclosed by the invention can effectively avoid the problem of unbalanced statistics of effective reflection energy when selecting the time window by selecting a hyperbolic time window mode to further calculate the signal-to-noise ratio of data in the window. (2) The signal-to-noise ratio calculation method comprises the following steps: the invention provides a new signal-to-noise ratio calculation method, which comprises the steps of firstly separating out random interference, then removing relevant interference by using a relevant frequency spectrum method, estimating the energy of the rest effective signals, and calculating the signal-to-noise ratio by using the ratio of the effective signals to the total interference energy, thereby effectively separating out the effective signals and the interference and ensuring the accuracy of the signal-to-noise ratio calculation.

The method can be well applied to quality evaluation of the seismic acquisition data and quality control in the processing process, and the accuracy of seismic processing and interpretation is ensured to a great extent.

While the present invention has been described above in connection with the accompanying drawings and exemplary embodiments, it will be apparent to those of ordinary skill in the art that various modifications may be made to the above-described embodiments without departing from the spirit and scope of the claims.

Claims (4)

1. A seismic data signal-to-noise ratio calculation method based on hyperbolic time windows comprises the following steps:

selecting a hyperbolic time window in the seismic data;

removing random interference in hyperbolic time window data to obtain a first effective signal;

removing relevant interference noise in the first effective signal to obtain a second effective signal;

and calculating to obtain the signal-to-noise ratio by using the hyperbolic time window data and the second effective signal.

2. The hyperbolic time window-based seismic data signal-to-noise ratio calculation method of claim 1, wherein the step of obtaining a first effective signal comprises: performing fast Fourier transform on the data in the hyperbolic time window to transform the hyperbolic time window data from a time domain to an F-K domain; setting a threshold value in the F-K domain, and removing random interference; then, inverse fourier transform is performed to obtain a first effective signal.

3. The hyperbolic time window-based seismic data signal-to-noise ratio calculation method of claim 1, wherein the step of obtaining the second effective signal is implemented by performing correlation analysis by using the characteristic that adjacent seismic trace signals in the first effective signal have correlation and noise has no correlation.

4. The hyperbolic time window-based seismic data signal-to-noise ratio calculation method of claim 3, wherein the step of calculating the signal-to-noise ratio is performed according to equation (1),

formula (1) is

Wherein, the SNR is the signal-to-noise ratio,

$A_x\left(f\right)=\frac{1}{m}\[\left|X_1\right(f){|}^2+|X_2\left(f\right){|}^2+...+|X_m\left(f\right){|}^2\],$

wherein m represents the number of seismic channels, i is more than or equal to 1 and less than or equal to m, f is frequency, A_x(f) Amplitude spectra, X, of seismic data in hyperbolic time windows₁(f) Is the amplitude spectrum, X, of the first trace of seismic data within a hyperbolic time window range without random interference removal₂(f) Amplitude spectrum, X, of the second seismic data within hyperbolic time window range without random interference removal_m(f) For the amplitude spectrum of the mth seismic data in the hyperbolic time window range without random interference removal,

$A_s\left(f\right)=\frac{1}{2(m-1)}\underset{i=1}{\overset{m-1}{\Σ}}\[Y_i\left(f\right)Y_{i+1}\left(f\right)+Y_{i+1}\left(f\right)Y_i\left(f\right)\],$

wherein A is_s(f) Is the amplitude spectrum, Y, of the second effective signal in the hyperbolic time window range_i(f) For the amplitude spectrum, Y, of the ith trace of seismic data within the hyperbolic time window range from which random interference has been removed_i+1(f) The amplitude spectrum of the i +1 st seismic data in the hyperbolic time window range with random interference removed is obtained.