CN105259579A - A high-amplitude shielding layer rejecting method based on seismic data instantaneous attributes - Google Patents

Abstract

The invention relates to a high-amplitude shielding layer rejecting method based on seismic data instantaneous attributes. The method is characterized by comprising the following steps: 1), fine interpretation of a high-amplitude shielding layer is carried out in terms of data after stack or offset; 2), the interpreted high-amplitude shielding layer is regarded as a center; a time window is designed, and seismic data in the time window is intercepted; time and amplitude information of the interpreted high-amplitude shielding layer is obtained, and the seismic data in the time window is subjected to Hilbert conversion to obtain frequencies and phases forming wavelets of the high-amplitude shielding layer; average wavelets are obtained through well seismic calibration; according to correlation coefficients between the average wavelets and different scale parameter theoretical wavelets, the scale parameters of the average wavelets are determined; Morlet wavelets approximating the high-amplitude shielding layer is constructed one by one; and 4) differences between a data body of the 1) step and the Morlet wavelets obtained in the 3) step are calculated one by one to obtain seismic records in which the high-amplitude shielding layer is rejected. In the invention, influences by the high-amplitude shielding layer in a seismic profile on the processed data can be effectively eliminated.

Description

A kind of strong amplitude screen layer elimination method based on geological data instantaneous attribute

Technical field

The invention belongs to seismic data analysis and treament field in oil-gas exploration, relate to a kind of seismic data processing technique, specifically, is about a kind of strong amplitude screen layer elimination method based on geological data instantaneous attribute.

Background technology

Strong reflection axle is often there is in actual seismic section, as strong biolithite reflects, strong coal layer reflection etc., they are the wave impedance difference excessive formation due to upper and lower stratum, reflection horizon, and due to the amplitude of these strong amplitude inphase axles excessive, below it, lineups energy will die down relatively comparatively speaking, and Here it is strong amplitude energy lineups are to the shielding action of the weak energy width lineups that shake.In seismic data interpretation, below traditional description strong amplitude screen layer, the method for thin reservoir is that window carries out attributes extraction when thin Reservoir Section is chosen, thus directly carry out layer description and prediction, but due to the covering effect of strong screen layer, the explanation results of classic method can not give prominence to the weak reflective information that underlies, and the effect of reservoir prediction can be subject to larger impact.Extract someway if strong reflection amplitude axle can be utilized, in the residue seismic section so after rejecting strong reflection amplitude axle, the energy of weak amplitude reflection axle will obtain relative enhancing.

Existing for the method rejecting strong amplitude shielding axle is at present all based on multiple wavelet resolution theory, method used in common seismic signal transacting is all hypothesis seismic wavelet is single fixing, this theory hypothesis and actual conditions have a long way to go, and often inevitable problem served by band: the effective information that the seismologic record based on this hypothesis may make some energy more weak is lost; Simultaneously in traditional filtering method because the frequency band of interference wave and significant wave has lap, while filtering undesired signal, useful signal also can be subject to decay in various degree.Multiple wavelet decomposition method can resolve into seismic trace the wavelet set of different dominant frequency, different time, therefore the decomposition of seismic trace in time-frequency domain can be realized, based on decomposing the wavelet obtained, for different geologic bodies, the single seismic wavelet of different frequency or the wavelet collection of a certain frequency range can be selected to carry out geological data reconstruct, thus obtain the rear new seismic section of reconstruct and data volume.

At present, existing multiple method can realize the operation of multiple wavelet decomposition and reconstruction, and main method has Short Time Fourier Transform, wavelet transformation, S-transformation, Hilbert-Huang conversion, match tracing etc.Fourier transform utilizes signal in the information of time domain to study the spectrum signature of signal, but strict upper says, Fourier transform is only applicable to stationary signal, inapplicable to the so a kind of non-stationary signal of seismic signal.Wavelet transformation overcomes Fourier transform does not have resolving power limitation in time domain, inherit the characteristic that Short Time Fourier Transform has localization simultaneously, it has good local character in time domain and frequency field, can the attributes such as the amplitude of signal, phase place, frequency be portrayed out within the selected period, from 20 time Mos, wavelet transformation is widely used in the process of seismic signal.The Wavelet Frames that Daubechies (1990) proposes is theoretical, the people such as Zhu Guangming utilize wavelet transformation to carry out one-dimensional filtering, wavelet transformation road is done interpolation by WangZhengli etc., the people such as Gao Jinghuai utilize wavelet transformation to extract the temporal characteristics of signal, Li Shuguang etc. utilize frequency field wavelet transformation that seismic signal is decomposed into the Morlet wavelet of a series of different frequency, realize the multiple wavelet decomposition and reconstruction of signal, and computing velocity is very fast, obtain higher resolution, decomposed and reconstituted result can be carried out the fine geologies such as high-precision reservoir prediction and fluid identification and be explained task.Mallat etc. (1993) propose matching pursuit algorithm first, this algorithm is at first based on Gabor time-frequency atom storehouse, can iteration choose time-frequency atom thus signal is carried out multiple wavelet decomposition from redundancy atom, seismic trace can be resolved into dominant frequency difference, time shift is different, phase place is different and yardstick is different wavelet set by matching pursuit algorithm, thus can realize the finer decomposition of seismic trace in time-frequency domain.

According to the definition of multiple wavelet decomposition and reconstruction, the wavelet of strong amplitude screen layer can be rejected from the wavelet set after multiple wavelet decomposition if known, wavelet be concentrated remaining wavelet to be reconstructed and can obtain the seismologic record of rejecting after strong amplitude screen layer.Multiple wavelet based on wavelet transformation decomposes, and utilizes wavelet transformation theory, and its positive inverse transformation is inherently a kind of convolution operation, and therefore based on the multiple wavelet decomposition algorithm of small echo, the seismologic record of its reconstruct and original earthquake data can exist must error; Based on match tracing multiple wavelet decomposition algorithm, seismic trace can be resolved into dominant frequency difference, time shift is different, phase place is different and yardstick is different wavelet set, match tracing is the process of a redundancy iteration in essence, and its huge calculated amount is a major reason of this algorithm development of restriction all the time.Though said method all will shield by force axle by multiple wavelet decomposition and reconstruct out, if but only above-mentioned algorithm is introduced in the rejecting of strong amplitude shielding axle, then it does not make full use of strong amplitude shielding axle energy by force, and the feature that section is easily differentiated, counting yield is also lower simultaneously.

Summary of the invention

Based on the above-mentioned problems in the prior art, the object of the present invention is to provide a kind of strong amplitude screen layer elimination method based on geological data instantaneous attribute.

For achieving the above object, present invention employs following technical scheme: a kind of strong amplitude screen layer elimination method based on geological data instantaneous attribute, described method is characterized in that, comprises the following steps:

1) after poststack or skew, after superposition, data carry out Fine structural interpretation to strong amplitude screen layer lineups;

2) after poststack or skew after superposition in data by step 1) centered by the shielding axle explained, window during design, geological data during intercepting in window;

3) by step 1) the strong amplitude screen layer explained, obtain time and the amplitude information of strong amplitude screen layer, to step 2) geological data after the poststack that intercepts or migration stack carries out Hilbert conversion, obtain by road and form the sub-wave frequency of strong amplitude screen layer and phase place, the width of average wavelet is extracted by meticulous well shake staking-out work, the basis of Morlet wavelet combines the strong amplitude screen layer energy explained, builds the wavelet being similar to strong amplitude screen layer by road;

4) by superpose or after migration stack data by road and the 3rd) the Morlet wavelet that obtains of step does difference, and difference is exported the result after as the strong amplitude screen layer of rejecting by road.

Described step 3) in, the Morlet small echo of structure approximate strong amplitude shielding axle, concrete steps comprise:

①Zhu road is to by step 2) superposition that intercepts or migration stack data, carry out Hilbert conversion, Hilbert conversion is carried out to jth road geological data, build complex seismic trace s _j(t)

$s_j\left(t\right)=x_j\left(t\right)+i{\tilde{x}}_j\left(t\right)$

In formula, x _jt () is jth road geological data (j=1,2...N), for x _jthe Hilbert transformation results of (t);

②Zhu road obtaining step 1) in the strong amplitude explained shield time and the amplitude of axle, jth road earthquake data amplitudes value a _j0as the sub-wave amplitude of the strong amplitude screen layer of structure, with u _j0as shift time when building the center of strong amplitude screen layer wavelet;

3. s is passed through _jt (), obtains instantaneous frequency and the instantaneous phase of jth road seismic signal, and records u _j0the instantaneous frequency at place and instantaneous phase

${\mathrm{\ω}}_{j0}=\frac{d}{dt}\left(\arctan \frac{{\tilde{x}}_j\left(t\right)}{x_j\left(t\right)}\right),t=u_{j0}$

In formula for instantaneous phase, ω _j0for instantaneous frequency;

4. in conjunction with well-log information, carry out well shake and demarcate, and extract average wavelet, according to the related coefficient of average wavelet and different scale Morlet small echo, determine σ further ₀;

Shift time u when 5. utilizing the center of acquisition _j0and u _j0instantaneous frequency ω corresponding to position _j0and instantaneous phase build the Morlet wavelet of strong amplitude screen layer position, jth road, its expression formula is

6. by step 3) the amplitude a that obtains ₀5. walk the Morlet small echo obtained be multiplied with the, the approximate strong amplitude obtaining jth road shields roller ripple

p _j(t)＝a _j0×m _j(t)

Described step 4) in, obtain the data D after rejecting strong amplitude screen layer, concrete steps are:

$D\left(t\right)=\underset{j=1}{\overset{N}{\Σ}}{x}_j\left(t\right)-p_j\left(t\right)$

The present invention is owing to taking above technical scheme, it has the following advantages: 1, implementation method of the present invention is simple, be easy to operation, on the basis carefully analyzing match tracing multiple wavelet decomposition principle, improve in each iteration the method constructing best Morlet wavelet, strong in conjunction with strong amplitude shielding axle energy in superposition or the rear stacked section of skew, the feature of easy pickup, the time of the strong amplitude screen layer explained and amplitude energy are incorporated the present invention as the constraint condition reconstructing strong amplitude screen layer wavelet, therefore the present invention can obtain the strong sub-wave amplitude of amplitude screen layer and center time-shifted positions accurately from seismic section more easily, further avoid pickup when seeking energy maximum wavelet inaccurate, the problem of calculation of complex, 2, the present invention avoids the complicated calculations method that multiple wavelet decomposes acquisition strong shielding roller ripple, demarcates the average wavelet of acquisition, determine average wavelet width cs from well shake ₀, therefore the present invention fully in conjunction with log data, can improve the efficiency determining strong amplitude shielding roller ripple, 3, the present invention adopts Morlet small echo, and Morlet small echo is the multiple Sine Modulated high bass wave of a kind of single-frequency, and its time-frequency domain all has good locality.Based on above advantage, the present invention can make full use of well-shooting data, interpretation work is incorporated in post-stack data processing work, effectively can reject the interference of strong amplitude screen layer on seismic section, make the weak signal energy below strong amplitude screen layer obtain strengthening, contribute to the prediction of thin reservoir.

Accompanying drawing explanation

Fig. 1 is schematic flow sheet of the present invention;

Fig. 2 is the different scale parameter wavelet waveforms figure that the present invention draws for relation between Research scale parameter and wavelet breadth;

Fig. 3 is the average wavelet used of well shake timing signal that the present invention extracts;

Fig. 4 is that the actual wavelet of extraction and the small echo of different scale parameter are carried out the result of cross-correlation by the present invention;

Fig. 5 is the present invention's actual seismic section after Fine structural interpretation to be dealt with;

Fig. 6 is the seismic section after the present invention rejects strong amplitude screen layer;

Fig. 7 is the strong amplitude screen layer that the present invention reconstructs on the basis of the layer position that Fig. 5 has explained;

Fig. 8 (a) is the single-channel seismic record at the present invention labeling position place in Figure 5;

Fig. 8 (b) is the single-channel seismic record at the present invention labeling position place in figure 6;

Fig. 9 (a) is the time frequency analysis result that the present invention carries out single-channel seismic data in Fig. 8 (a);

Fig. 9 (b) is the time frequency analysis result that the present invention carries out single-channel seismic data in Fig. 8 (b).

Embodiment

Below in conjunction with accompanying drawing and example, the present invention is described in detail.

The seismologic record that the present invention obtains from field acquisition, superposes geological data after becoming post-stack seismic data or skew, need process according to the inventive method from Interpretation of profile and single track process two aspect to geological data after pre-service.

Fig. 1 illustrates the flow process of the strong amplitude screen layer elimination method that the present invention is based on geological data instantaneous attribute, comprises the following steps:

1) after poststack or skew, after superposition, data carry out Fine structural interpretation to strong amplitude screen layer lineups;

2) after poststack or skew after superposition in data by step 1) centered by the shielding axle explained, window during design, geological data during intercepting in window;

3) by step 1) the strong amplitude screen layer explained, obtain time and the amplitude information of strong amplitude screen layer, to step 2) geological data after the poststack that intercepts or migration stack carries out Hilbert conversion, obtain by road and form the sub-wave frequency of strong amplitude screen layer and phase place, extracted the width of average wavelet by meticulous well shake staking-out work, build in the basic Shang Zhu road of Morlet wavelet the wavelet being similar to strong amplitude screen layer

Morlet small echo is the multiple Sine Modulated high bass wave of a kind of single-frequency, and be also the most frequently used complex scalar wavelet, its time-frequency domain all has good locality.The formation of Morlet small echo depends on amplitude, phase place, frequency, center time shift, scale parameter, the Morlet small echo of structure approximate strong amplitude shielding axle, and concrete steps comprise:

1. to by step 2) superpose geological data after the poststack that intercepts or skew, carry out Hilbert conversion by road, Hilbert conversion is carried out to jth road geological data, build complex seismic trace s _j(t)

$s_j\left(t\right)=x_j\left(t\right)+i{\tilde{x}}_j\left(t\right)$

In formula, x _jt () is jth road geological data (j=1,2...N), for x _jthe Hilbert transformation results of (t);

②Zhu road obtaining step 1) in the strong amplitude explained shield time and the amplitude of axle, jth road earthquake data amplitudes value a _j0as the sub-wave amplitude of the strong amplitude screen layer of structure, with u _j0as shift time when building the center of strong amplitude screen layer wavelet; Due to strong amplitude screen layer after earthquake poststack or migration stack on section energy pick up by force, easily, if the explanation results of strong amplitude screen layer therefore can be utilized, multiple wavelet can be avoided to decompose the complex calculation that will carry out

3. s is passed through _jt (), obtains instantaneous frequency and the instantaneous phase of jth road seismic signal, and records u _j0the instantaneous frequency at place and instantaneous phase

${\mathrm{\ω}}_{j0}=\frac{d}{dt}\left(\arctan \frac{{\tilde{x}}_j\left(t\right)}{x_j\left(t\right)}\right),t=u_{j0}$

In formula for instantaneous phase, ω _j0for instantaneous frequency;

4. in conjunction with well-log information, carry out well shake and demarcate, and extract average wavelet, the Morlet small echo of average wavelet and different scale is carried out cross-correlation, and determines σ further ₀;

Shift time u when 5. utilizing acquisition center _j0and u _j0instantaneous frequency ω corresponding to position _j0and instantaneous phase build Morlet wavelet, the expression formula of Morlet small echo is

6. by step 3) the amplitude a that obtains _j05. walk the Morlet small echo obtained be multiplied with the, the approximate strong amplitude obtaining jth road shields roller ripple

p _j(t)＝a _j0×m _j(t)

4) by superpose or after migration stack data by road and the 3rd) the Morlet wavelet that obtains of step does difference, and difference D is exported the result after as the strong amplitude screen layer of rejecting by road

$D\left(t\right)=\underset{j=1}{\overset{N}{\Σ}}{x}_j\left(t\right)-p_j\left(t\right)$

Fig. 2 gives the form of the Morlet wavelet corresponding to different scale parameter, in order to the relation of scale parameter and Morlet wavelet to be described, and sapphirine σ ∈ [0.1,0.5]; Blue σ ∈ [0.6,1.0]; Red σ ∈ [1.1,1.5]; Green σ ∈ [1.6,2.0]; Pink colour σ ∈ [2.1,2.5]; Black σ ∈ [2.6,3.0]; Visible scale parameter is mainly that near 1.0,1.5,2.0,2.5,3.0, scale parameter often increases by 0.5 at scale parameter on the impact of Morlet small echo form, and its Morlet wavelet can increase an obvious secondary lobe;

Fig. 3 gives the average wavelet extracted after well shake is demarcated;

Fig. 4 gives after in Fig. 3 and Fig. 2, each wavelet carries out cross-correlation, the graph of a relation of its related coefficient and scale parameter;

Fig. 5 gives the section of the actual seismic after Fine structural interpretation, and interpretation horizon position is the position of strong amplitude screen layer;

Fig. 6 gives the seismic section after rejecting strong amplitude screen layer, comparison diagram 5 and Fig. 6 visible, reject the seismic section after strong amplitude screen layer, the more original seismic section of lineups energy below former strong amplitude screen layer position strengthens to some extent, and in seismic section, lineups form is without exception compared with original seismic data.

Fig. 7 gives the strong amplitude screen layer that the basis based on Fig. 5 interpretation horizon reconstructs, the energy of visible wavelet changes with the energy of amplitude screen layer strong on original actual seismic section, and the strong amplitude screen layer wavelet reconstructed can realize mating preferably with amplitude screen layer strong in original actual seismic section;

Fig. 8 gives in Fig. 5, Fig. 6 the single-channel seismic record marking position, and Fig. 8 (a) is the one-channel record at labeling position place of institute in original seismic section; B () is the one-channel record at labeling position place of institute in the actual seismic section after rejecting strong amplitude screen layer, comparison diagram 8 (a) is visible with (b), near 3200ms, the inventive method effectively can weaken the energy of strong amplitude screen layer, highlight the energy of effective weak signal below strong amplitude screen layer, and impact be there is no on the energy of all the other positions of seismologic record;

Fig. 9 gives the time-frequency spectrum of Fig. 8 (a), Fig. 8 (b), and Fig. 9 (a) is the time-frequency spectrum corresponding to Fig. 8 (a); Fig. 9 (b) is the time-frequency spectrum corresponding to Fig. 8 (b), comparison diagram 9 (a) and Fig. 9 (b) reject the seismic trace after strong amplitude screen layer as seen, below original strong amplitude screen layer position, the energy of (near 3200ms) strengthens to some extent, and near 3200ms, former strong amplitude screen layer position frequency resolution increases.

Claims (3)

1., based on a strong amplitude screen layer elimination method for geological data instantaneous attribute, described method is characterized in that, comprises the following steps:

1) after poststack or skew, after superposition, data carry out Fine structural interpretation to strong amplitude screen layer lineups;

2) after poststack or skew after superposition in data by step 1) centered by the shielding axle explained, window during design, geological data during intercepting in window;

3) the 1st) on the step basis of strong amplitude screen layer of explaining, obtain centre time information and the amplitude information of strong amplitude screen layer, to the 2nd) step intercept poststack or migration stack after geological data carry out Hilbert conversion, obtain by road and form the sub-wave frequency of strong amplitude screen layer and phase place, extracted the width of average wavelet by meticulous well shake staking-out work, build in the basic Shang Zhu road of Morlet wavelet the wavelet being similar to strong amplitude screen layer;

4) by the geological data after poststack or migration stack by road and the 3rd) the Morlet wavelet that obtains of step does difference, and difference is exported the result after as the strong amplitude screen layer of rejecting by road.

2. the strong amplitude screen layer elimination method based on geological data instantaneous attribute according to claim 1, described step 3) in, the Morlet small echo of structure approximate strong amplitude shielding axle, concrete steps comprise:

1. to by step 2) geological data of superposition carries out Hilbert conversion by road after the superposition that intercepts or skew, and Hilbert conversion is carried out to jth road geological data, builds complex seismic trace s _j(t)

In formula, x _jt () is jth road geological data (j=1,2 ... N), for x _jthe Hilbert transformation results of (t);

②Zhu road obtaining step 1) in the strong amplitude explained shield time and the amplitude of axle, jth road earthquake data amplitudes value a _j0as the sub-wave amplitude of the strong amplitude screen layer of structure, u _j0as shift time when building the center of strong amplitude screen layer wavelet;

3. s is passed through _jt (), obtains instantaneous frequency and the instantaneous phase of jth road seismic signal, and records u _j0the instantaneous frequency at place and instantaneous phase

In formula for instantaneous phase, ω _j0for instantaneous frequency;

4. in conjunction with well-log information, carry out well shake and demarcate, and extract average wavelet, according to the related coefficient of average wavelet and different scale Morlet small echo, determine σ further ₀;

Shift time u when 5. utilizing acquisition center _j0and u _j0the instantaneous frequency ω that position is corresponding _j0and instantaneous phase build Morlet wavelet, the expression formula of Morlet small echo is

6. by step 3) the amplitude a that obtains _j05. walk the Morlet small echo obtained be multiplied with the, the approximate strong amplitude obtaining jth road shields roller ripple

p _j(t)＝a _j0×m _j(t)。

3. the strong amplitude screen layer elimination method based on geological data instantaneous attribute according to claim 1, described step 4) in, obtain the data D after rejecting strong amplitude screen layer, concrete steps comprise:

。