CN102279416A - Method for matching far-and-near offset-distance stacked profile phase frequencies - Google Patents

Abstract

The invention discloses a method for matching far-and-near offset-distance stacked profile phase frequencies, which comprises the steps of: extracting zero-phase wavelets with a same frequency through a mixed-phase wavelet extraction technology, and respectively performing wavelet deconvolution operations by using the extracted zero-phase wavelets with the same frequency and far-and-near offset-distance stacked profiles, so that phase frequencies of the far-and-near offset-distance stacked profiles are matched; and representing far-and-near offset-distance stacked data x(t) as x(t) = w(t)*(t)+n(t), selecting a zero-phase wavelet with a same frequency under the condition that noises n(t) are omitted, respectively performing wavelet deconvolution by using the wavelet and seismic channels of the far-and-near offset-distance stacked data, to eliminate the differences between frequencies and phases of the far-and-near offset-distance stacked data, so that the wavelet w(t) of a far-and-near offset-distance profile is a zero-phase wavelet w0(t) with the same frequency, and then performing a convolution operation by using the w0(t) and the r(t), so that a matched seismic record x(t) is obtained.

Description

The matching process of far and near offset distance stacked section phase frequency

Technical field

The present invention relates to a kind of petroleum detection technical field, be specifically related to a kind of matching process of far and near offset distance stacked section phase frequency.

Background technology

In seismic data was handled, stack was a kind of more effective denoising method.But, be difficult to extract accurately because NMO velocity generally is the interpolation speed of discrete point when carrying out normal moveout correction.Make through the seismic section after normal moveout correction and the static correction certainly exist undercorrection or proofread and correct excessive, there is certain residue time difference, can't accomplish with superimposed, cause the resolution of earthquake stacked section to reduce and in the high frequency resolution Data Processing, the high frequency loss of stacked section is serious.Because moving the stretching causes offset distance section lineups far away chap, far and near offset distance section frequency does not match simultaneously.At present for solving the inconsistent problem of phase place that the residual NMO correction amount causes, method commonly used is to carry out residual NMO correction, to undercorrection or proofread and correct excessive proofreading and correct again.At present the method for the residual NMO correction that occurs be mostly with the residual NMO correction amount as the part when static at random residual quantity handle and need high precision velocity to extract simultaneously.But because the accuracy limitations of the speed data that prior art is extracted, be difficult to satisfy the demand of residual correction.Stretch for moving, mostly adopt the way of excision or match.This is because in conventional earthquake Data Processing, and nearly offset distance often mostly has underground preferably reflection, and because offset distance is less, and the nmo stretching that is subjected to is also less, so excision is little to the influence of reflection stack result.But processing can often cause shallow-layer resolution to reduce like this, and energy loss is also bigger.Therefore, need develop a kind of VELOCITY EXTRACTION that do not need and protect the high method of amplitude simultaneously, solve far and near offset distance superposition of data phase place and the inconsistent problem of frequency.Behind the far and near offset distance superposition of data that obtains the frequency plot unanimity, when using far and near offset distance superposition of data searching reservoir, predicting oil, can realize the horizontal contrast that far and near superposition of data predicts the outcome, combination between the well shake simultaneously is tightr, makes that the prediction of reservoir and oil gas is more accurate.

Summary of the invention

The matching process that the purpose of this invention is to provide a kind of far and near offset distance stacked section phase frequency, use this matching process extracts same frequency and phase place to far and near offset distance superposition of data wavelet, utilize the wavelet deconvolution that extracts, reach elimination because the purpose of the unmatched problem of far and near offset distance partial stack data frequency phase place that residual NMO correction amount and moving stretching cause.

In order to reach above-mentioned purpose of design, the technical solution used in the present invention is as follows:

A kind of matching process of far and near offset distance stacked section phase frequency, by the mixed phase wavelet extractive technique, extract the zero-phase wavelet of same frequency, zero-phase wavelet with the same frequency that extracts is done the wavelet deconvolution computing with far and near offset distance stacked section respectively, and feasible far and near offset distance stacked section phase frequency is complementary;

Described far and near offset distance superposition of data x (t) is expressed as x (t)=w (t) * r (t)+n (t),

Ignore under the situation of noise n (t), extract the zero-phase wavelet of a same frequency, do wavelet deconvolution with this wavelet respectively at the seismic trace of far and near offset distance superposition of data, to reach the difference of the frequency plot of eliminating far and near offset distance superposition of data, make the wavelet w (t) of far and near offset distance section be the zero-phase wavelet w of same frequency ₀(t), use w again ₀(t) do convolution operation, the seismologic record x (t) after obtaining mating with r (t).

The process of the zero-phase wavelet of described extraction same frequency is: because the difference of wavelet and reflection coefficient sequence " smoothness ", the intermediary heat spectrum of wavelet is generally near initial point, and the intermediary heat spectrum of reflection sequence is away from initial point, therefore, just can realize separating of wavelet and reflection coefficient in the intermediary heat spectrum at intermediary heat spectrum design low-pass filter, the wavelet that again wavelet of intermediary heat spectral domain is converted to time domain reaches the purpose of wavelet w (t) extraction.

Under the situation of known amplitude spectrum, in the intermediary heat spectral domain, extract zero-phase wavelet:

Suppose x (t), w (t), r (t) satisfies the Di Liheli condition, and noise is a white noise; Ignore noise n (t), formula x (t)=w (t) * r (t)+n (t) substitution Fourier transform formula

$X_{\mathrm{\ω}}={\∫}_{-\∞}^{+\∞}{x}_t{e}^{-\mathrm{j\ωt}}{d}_t$

Obtain formula under frequency field:

X(ω)＝W(ω)R(ω)

X in the formula (t), W (t), R (t) they are respectively x (t), w (t), r (t) is in the expression formula of frequency field;

Formula X (ω)=W (ω) R (ω) is taken the logarithm, is converted into linear system:

ln?X(ω)＝ln?W(ω)+ln?R(ω)

Formula ln X (ω)=ln W (ω)+ln R (ω) is made Fourier inversion, is about to formula ln X (ω)=ln W (ω)+ln R (ω) substitution inversefouriertransform formula:

$x_t={\∫}_{-\∞}^{+\∞}{X}_{\mathrm{\ω}}{e}^{2\mathrm{\πj\ωt}}{d}_{\mathrm{\ω}}$

Obtain formula: $\hat{x}\left(t\right)=\hat{w}\left(t\right)+\hat{r}\left(t\right)$

Be called x (t), w (t), the intermediary heat spectral sequence of r (t);

Under known seismic wavelet spectral amplitude situation, suppose that maximum, the minimum phase component of wavelet w (t) is respectively v (t), u (t), substitution convolution formula:

$u\left(t\right)*v\left(t\right)={\∫}_{-\∞}^{+\∞}u\left(\mathrm{\τ}\right)v(t-\mathrm{\τ})d_{\mathrm{\τ}}$

Obtain w (t)=u (t) * v (t)

Formula w (t)=u (t) * v (t) is expressed as at Fourier-domain:

Wherein, w (ω), u (ω), v (ω) is respectively w (t), u (t), the expression formula of v (t) Fourier-domain;

Be respectively w (t), u (t), the phase spectrum of v (t);

Formula Logarithmic spectrum be expressed as:

With formula

Being converted to linear formula is:

To formula

The substitution Fourier inversion is about to its substitution inversefouriertransform formula:

$x_t={\∫}_{-\∞}^{+\∞}{X}_{\mathrm{\ω}}{e}^{2\mathrm{\πj\ωt}}{d}_{\mathrm{\ω}}$

Obtain formula: $\hat{w}\left(t\right)=\hat{u}\left(t\right)+\hat{v}\left(t\right)$

Wherein

Be the intermediary heat spectrum of wavelet amplitude, symmetry appears on the positive and negative axle of intermediary heat spectrum,

Be the intermediary heat spectrum of the minimum component spectral amplitude of wavelet,

Be the intermediary heat spectrum of wavelet largest component spectral amplitude,

Appear at respectively on the positive axis and negative axle of intermediary heat spectrum;

According to formula Obtain:

Wherein, It is the intermediary heat spectrum of zero phase spectral amplitude.

The beneficial effect of the matching process of far and near offset distance stacked section phase frequency of the present invention is: the unmatched problem of phase place, frequency that will handle the superposition of data of different offset distances is thought because seismic wavelet causes, handle original earthquake data by the zero phase seismic wavelet of introducing same frequency, the inconsistent while of phase frequency eliminating different offset distance superposition of data, can guarantee resolution of seismic section.Can realize simultaneously the contrast of earthquake and well, in conjunction with tightr, make that the prediction of reservoir and oil gas is more accurate between the well shake.Has good practical value.

Embodiment

The available convolution model of the relation of described seismologic record and seismic wavelet and reflection coefficient sequence is expressed as:

x(t)＝w(t)*r(t)+n(t) (1)

X in the formula (t), w (t), r (t), n (t) is respectively seismologic record, seismic wavelet, reflection coefficient and noise, under the definite situation of reflection coefficient r (t) and noise n (t), because residual NMO correction amount and moving the inconsistent of the far and near offset distance superposition of data phase place that causes and frequency that stretch, be because the phase place of seismic wavelet w (t) and frequency is inconsistent causes; Simultaneously,, can cause the resolution of x (t) to reduce, can not satisfy the demand of real work because mixed phase wavelet comes deal with data x (t) with this wavelet; Adopt zero phase phase place wavelet, come deal with data x (t) with this wavelet, can guarantee that the resolution of x (t) satisfies the demand of real work, therefore extract the zero-phase wavelet of a same frequency, do wavelet deconvolution with this wavelet respectively at the seismic trace of far and near offset distance superposition of data, to reach the difference of the frequency plot of eliminating far and near offset distance superposition of data.

Under the situation of known amplitude spectrum, in the intermediary heat spectral domain, extract zero-phase wavelet:

Suppose (1) x (t), w (t), r (t) satisfies the Di Liheli condition, and (2) noise is a white noise; Ignore noise n (t), formula (1) substitution Fourier transform formula

$X_{\mathrm{\ω}}={\∫}_{-\∞}^{+\∞}{x}_t{e}^{-\mathrm{j\ωt}}{d}_t$

Obtain formula under frequency field:

X(ω)＝W(ω)R(ω) (2)

X in the formula (t), W (t), R (t) they are respectively x (t), w (t), r (t) is in the expression formula of frequency field;

Formula (2) is taken the logarithm, and formula (2) is converted into linear system:

ln?X(ω)＝ln?W(ω)+ln?R(ω) (3)

Formula (3) is made Fourier inversion, is about to formula (3) substitution inversefouriertransform formula:

$x_t={\∫}_{-\∞}^{+\∞}{X}_{\mathrm{\ω}}{e}^{2\mathrm{\πj\ωt}}{d}_{\mathrm{\ω}}$

Obtain formula: $\hat{x}\left(t\right)=\hat{w}\left(t\right)+\hat{r}\left(t\right)---\left(4\right)$

Be called x (t), w (t), the intermediary heat spectral sequence of r (t);

Under known seismic wavelet spectral amplitude situation, suppose that maximum, the minimum phase component of wavelet w (t) is respectively v (t), u (t), substitution convolution formula:

$u\left(t\right)*v\left(t\right)={\∫}_{-\∞}^{+\∞}u\left(\mathrm{\τ}\right)v(t-\mathrm{\τ})d_{\mathrm{\τ}}$

Obtain w (t)=u (t) * v (t) (5)

Formula (5) is expressed as at Fourier-domain:

Wherein, w (ω), u (ω), v (ω) is respectively w (t), u (t), the expression formula of v (t) Fourier-domain;

Be respectively w (t), u (t), the phase spectrum of v (t);

The logarithmic spectrum of formula (6) is expressed as:

Formula (7) is converted to linear formula is:

To formula (8) substitution Fourier inversion, be about to formula (8) substitution inversefouriertransform formula:

$x_t={\∫}_{-\∞}^{+\∞}{X}_{\mathrm{\ω}}{e}^{2\mathrm{\πj\ωt}}{d}_{\mathrm{\ω}}$

Obtain formula: $\hat{w}\left(t\right)=\hat{u}\left(t\right)+\hat{v}\left(t\right)---\left(9\right)$

Wherein

Be the intermediary heat spectrum of wavelet amplitude, symmetry appears on the positive and negative axle of intermediary heat spectrum,

Be the intermediary heat spectrum of the minimum component spectral amplitude of wavelet,

Be the intermediary heat spectrum of wavelet largest component spectral amplitude,

Appear at respectively on the positive axis and negative axle of intermediary heat spectrum;

Obtain according to formula (10):

Wherein,

It is the intermediary heat spectrum of zero phase spectral amplitude.

This embodiment is the preferred embodiments of the present invention, can not limit the present invention, and concrete every rights protection scope is defined by the claims.

Claims (3)

1. the matching process of a far and near offset distance stacked section phase frequency, it is characterized in that: by the mixed phase wavelet extractive technique, extract the zero-phase wavelet of same frequency, zero-phase wavelet with the same frequency that extracts is done the wavelet deconvolution computing with far and near offset distance stacked section respectively, and feasible far and near offset distance stacked section phase frequency is complementary;

Described far and near offset distance superposition of data x (t) is expressed as x (t)=w (t) * r (t)+n (t),

Ignore under the situation of noise n (t), extract the zero-phase wavelet of a same frequency, do wavelet deconvolution with this wavelet respectively at the seismic trace of far and near offset distance superposition of data, to reach the difference of the frequency plot of eliminating far and near offset distance superposition of data, make the wavelet w (t) of far and near offset distance section be the zero-phase wavelet w of same frequency ₀(t), use w again ₀(t) do convolution operation, the seismologic record x (t) after obtaining mating with r (t).

2. according to the matching process of the far and near offset distance stacked section phase frequency of claim 1, it is characterized in that: the process of the zero-phase wavelet of described extraction same frequency is: because the difference of wavelet and reflection coefficient sequence " smoothness ", the intermediary heat spectrum of wavelet is generally near initial point, and the intermediary heat spectrum of reflection sequence is away from initial point, therefore, just can realize separating of wavelet and reflection coefficient in the intermediary heat spectrum at intermediary heat spectrum design low-pass filter, the wavelet that again wavelet of intermediary heat spectral domain is converted to time domain reaches the purpose of wavelet w (t) extraction.

3. according to the matching process of the far and near offset distance stacked section phase frequency of claim 2, it is characterized in that: under the situation of known amplitude spectrum, in the intermediary heat spectral domain, extract zero-phase wavelet:

Suppose x (t), w (t), r (t) satisfies the Di Liheli condition, and noise is a white noise; Ignore noise n (t), formula x (t)=w (t) * r (t)+n (t) substitution Fourier transform formula

$X_{\mathrm{\ω}}={\∫}_{-\∞}^{+\∞}{x}_t{e}^{-\mathrm{j\ωt}}{d}_t$

Obtain formula under frequency field:

X(ω)＝W(ω)R(ω)

X in the formula (t), W (t), R (t) they are respectively x (t), w (t), r (t) is in the expression formula of frequency field;

Formula X (ω)=W (ω) R (ω) is taken the logarithm, is converted into linear system:

ln?X(ω)＝ln?W(ω)+ln?R(ω)

Formula ln X (ω)=ln W (ω)+ln R (ω) is made Fourier inversion, is about to formula ln X (ω)=ln W (ω)+ln R (ω) substitution inversefouriertransform formula:

$x_t={\∫}_{-\∞}^{+\∞}{X}_{\mathrm{\ω}}{e}^{2\mathrm{\πj\ωt}}{d}_{\mathrm{\ω}}$

Obtain formula: $\hat{x}\left(t\right)=\hat{w}\left(t\right)+\hat{r}\left(t\right)$

Be called x (t), w (t), the intermediary heat spectral sequence of r (t);

Under known seismic wavelet spectral amplitude situation, suppose that maximum, the minimum phase component of wavelet w (t) is respectively v (t), u (t), substitution convolution formula:

$u\left(t\right)*v\left(t\right)={\∫}_{-\∞}^{+\∞}u\left(\mathrm{\τ}\right)v(t-\mathrm{\τ})d_{\mathrm{\τ}}$

Obtain w (t)=u (t) * v (t)

Formula w (t)=u (t) * v (t) is expressed as at Fourier-domain:

Wherein, w (ω), u (ω), v (ω) is respectively w (t), u (t), the expression formula of v (t) Fourier-domain;

Be respectively w (t), u (t), the phase spectrum of v (t);

Formula

Logarithmic spectrum be expressed as:

With formula

Being converted to linear formula is:

To formula

The substitution Fourier inversion is about to its substitution inversefouriertransform formula:

$x_t={\∫}_{-\∞}^{+\∞}{X}_{\mathrm{\ω}}{e}^{2\mathrm{\πj\ωt}}{d}_{\mathrm{\ω}}$

Obtain formula: $\hat{w}\left(t\right)=\hat{u}\left(t\right)+\hat{v}\left(t\right)$

Wherein

Be the intermediary heat spectrum of wavelet amplitude, symmetry appears on the positive and negative axle of intermediary heat spectrum,

Be the intermediary heat spectrum of the minimum component spectral amplitude of wavelet,

Be the intermediary heat spectrum of wavelet largest component spectral amplitude,

Appear at respectively on the positive axis and negative axle of intermediary heat spectrum;

According to formula

Obtain:

Wherein,

It is the intermediary heat spectrum of zero phase spectral amplitude.