CN106873038A - A kind of method that Depth Domain seismic wavelet is extracted in the geological data from Depth Domain - Google Patents

Abstract

The present invention realizes a method for extracting depth-domain seismic wavelets from depth-domain seismic data by utilizing the ridge regression method, which includes the following steps: 1) obtaining depth, velocity and density information from the logging data of a certain well, From this, the corresponding reflection coefficient r is calculated; 2) Extract the side-well seismic gather s of the well from the pre-stack depth migration seismic data, and select a constant velocity v _c as the standard velocity. Set s to transform the velocity and depth parameters, so that it conforms to the linear time-invariant condition, and obtain the transformed side-hole seismic gather s'; 3) Map the reflection coefficient r to the transformed depth position to become r'; 4 ) select the appropriate ridge parameter α, and use the ridge regression method to extract the seismic wavelet. The method of the present invention directly uses the depth-domain seismic data to extract the depth-domain seismic wavelet, and the extracted depth-domain seismic wavelet has high precision, without the mutual conversion of the depth-domain seismic data from time to depth domain and from depth to time domain .

Description

A Method for Extracting Depth-Domain Seismic Wavelets from Depth-Domain Seismic Data

technical field

The invention relates to the field of petroleum seismic exploration data processing and interpretation, in particular to a method for extracting depth-domain seismic wavelets from depth-domain seismic data.

Background technique

Prestack depth migration technology has been successfully applied in actual seismic exploration, and prestack depth migration has a greater advantage in imaging quality than prestack time migration. In order to obtain depth from prestack depth migration To invert the elastic parameters of formations from seismic data in the deep domain, it is necessary to directly use the logging data in the depth domain and seismic wavelets in the depth domain to generate synthetic seismic records in the depth domain, and use the synthetic seismic records in the depth domain to calibrate the seismic data in the depth domain, so as to carry out reservoir prediction, etc. . The extraction of depth-domain seismic wavelets is a very critical part of the processing work such as depth-domain seismic parameter inversion, deconvolution, and seismic forward modeling. The quality of depth-domain seismic wavelet extraction is directly related to the quality of depth-domain seismic data. availability and value.

The traditional seismic wavelet extraction algorithm is mainly to extract the time-domain seismic wavelet from the time-domain seismic data, usually based on the convolution model. The basic assumption of the convolution model is linear time invariant, that is, the wavelet in the propagation process It is stable and invariant, therefore, the conditions of linear time-invariant system must be satisfied in order to perform convolution operation. In the depth domain, the propagation velocity of seismic waves in different spaces and depths of the underground is different, and the seismic waveform will inevitably change, and the wave number of the seismic wavelet is inversely proportional to the propagation velocity of the seismic wave. Therefore, the seismic wave field in the depth domain is not satisfied. Therefore, the traditional seismic wavelet extraction algorithm does not meet the convolution operation conditions in the depth domain, and it is impossible to directly extract the depth domain seismic wavelet from the depth domain seismic data.

The traditional time-domain seismic wavelet extraction methods can be divided into two categories: one is the deterministic method, that is, using the logging data to calculate the reflection coefficient, and then combining the seismic traces beside the well to obtain the wavelet; the other is the statistical method, that is, using Statistical principle, making certain assumptions about wavelets, and extracting wavelets using seismic trace signals. The two types of methods have their own advantages and disadvantages. The advantage of the deterministic method is that it can extract more accurate wavelets without making any assumptions about the formation impulse response. The disadvantage is that it is greatly affected by the logging data; In the case of well logging data, wavelets can also be extracted by directly using the statistical properties of seismic trace signals. The disadvantage is that some statistical assumptions about the formation impulse response need to be made.

Contents of the invention

In view of the above problems, the purpose of the present invention is to provide a method based on ridge regression, which can directly extract depth-domain seismic wavelets from depth-domain seismic data without the need for time-to-depth and depth-to-time conversions.

To achieve the above object, the present invention adopts the following technical solutions: a method for extracting depth-domain seismic wavelets from depth-domain seismic data, which includes the following steps: (1) obtaining depth, velocity and density information from certain well logging data , so as to calculate the corresponding reflection coefficient r; (2) Select the wellside seismic gather s of this well from the pre-stack depth migration seismic data, and select a constant velocity v _c at the same time, and take this constant velocity as the standard velocity, Transform the velocity and depth parameters of the selected side-hole seismic gather s to make it conform to the linear time-invariant condition, and obtain the transformed side-hole seismic gather s'; (3) map the reflection coefficient r to the transformed depth The position becomes r'; (4) select the appropriate ridge parameter α, and use the ridge regression method to extract the seismic wavelet in the depth domain.

The above step (2) is to transform the velocity and depth of the side-hole seismic trace in the depth domain according to the following formula, so that it satisfies the linear time-invariant condition:

In the formula, d is the depth sampling interval of the logging data, d _c is the depth value after d transformation, v _c is the standard constant velocity, and v _max is the maximum velocity recorded in the logging velocity data. Then, the downhole seismic gather s is _resampled with the transformed sampling interval dc, thereby transforming s into s'.

The realization of the above step (3) is the depth corresponding to the reflection coefficient calculated in step (1):

The depth after step (2) transformation is:

In the formula, n is the number of depth sampling points of well logging data, h is the depth position of well logging data record, and h _c is the depth position after transformation. When the reflection coefficient r is mapped to the transformed depth position, the value of the reflection coefficient remains unchanged, that is, r=r'.

In the above step (4), the transformed depth-domain seismic convolution model is expressed in the following vector form:

S=RW

In the formula, S is a column vector constructed from the transformed side-hole seismic gather s', R is the Toeplitz matrix constructed from the depth-transformed reflection coefficient r', and W is the depth domain seismic wavelet vector to be obtained.

In order to obtain the unique solution of W in the above formula, the method of the present invention adopts the method of ridge regression, promptly optimizes the unconstrained minimization problem of following formula:

min||S-RW|| ² +α||W ² ||

In the formula, α is the ridge parameter, α>0.

In actual calculation, the analytical solution W of the minimization problem of the above formula can be solved by using the following formula by selecting an appropriate value of α:

W＝(RR ^T +αI) ^-1 R ^T S

Due to the adoption of the above technical scheme, the present invention has the advantage that it can directly use the depth domain seismic data to extract the depth domain seismic wavelet.

Description of drawings

Figure 1 is a synthetic depth-domain geological model and depth-domain seismic records, in which Figure 1a is a depth-domain velocity model containing multiple formations, the abscissa is the P-wave velocity, the unit is m/s, the ordinate is the depth, the unit is m, and the depth The sampling interval is 1 meter; Fig. 1b is the depth-domain synthetic seismic record corresponding to Fig. 1a, and the ordinate is depth, and the unit is meter.

Fig. 2 is the result of extracting depth-domain seismic wavelets from the depth-domain synthetic seismic records in Fig. 1 . Wherein, Fig. 2 a compares the depth-domain seismic wavelet (shown as a solid line) extracted by the method of the present invention and the original depth-domain seismic wavelet (shown as a dotted line) used in the synthetic depth-domain seismic record, the abscissa is depth, and the unit is meter, and the ordinate is the amplitude; Fig. 2 b compares the depth domain seismic wavelet (shown as a solid line) extracted by the method of the present invention and the original depth domain seismic wavelet (shown as a dotted line) used in the synthetic depth domain seismic record Wavenumber spectrum, the abscissa is the wavenumber, the unit is one centimeter, and the ordinate is the amplitude.

Fig. 3 is the result of using the method of the present invention to extract the depth domain seismic wavelet from the depth domain angle gather seismic data in a certain area, wherein Fig. 3a is the pre-stack depth domain angle gather seismic data in this area, and the ordinate is depth , the depth range is 3550 meters to 3975 meters, the depth sampling interval is 5m, the abscissa is the angle, and the unit is degree. Fig. 3b is a depth-domain seismic wavelet extracted from the data in Fig. 3a by using the method of the present invention, the abscissa is the depth, the unit is meter, and the ordinate is the amplitude.

detailed description

The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

A method of extracting depth-domain seismic wavelets from depth-domain seismic data of the present invention comprises the following steps:

(1) Using the depth, velocity and density information of the processed logging data of a certain well, calculate the reflection coefficient according to the following formula:

In the formula, r _i is the depth-domain reflection coefficient of the interface between the i-th layer and the i+1-th layer, ρ _i is the density of the i-th layer, and v _i is the velocity of the i-th layer.

(2) Select the wellside seismic gathers of this well from the pre-stack depth migration seismic data, and set a constant velocity as the standard velocity. According to the following formula, the velocity and depth parameters of the depth domain sidehole seismic gathers are transformed, so that It satisfies the linear time invariant condition:

In the formula, d is the depth sampling interval of the logging data, d _c is the depth value after d transformation, v _c is the standard constant velocity, and v _max is the maximum velocity recorded in the logging velocity data. Then, the downhole seismic gather s is _resampled with the transformed sampling interval dc, thereby transforming s into s'.

(3) The depth corresponding to the reflection coefficient in step (1) is:

The depth after step (2) transformation is:

In the formula, n is the number of depth sampling points of well logging data, h is the depth position of well logging data record, and h _c is the depth position after transformation. When the reflection coefficient r is mapped to the transformed depth position, the value of the reflection coefficient remains unchanged, that is, r=r'.

(4) The transformed seismic convolution model in the depth domain can be expressed in the form of vectors as:

S=RW

In the formula, S is a column vector constructed from the transformed side-hole seismic gather s', R is the Toeplitz matrix constructed from the depth-transformed reflection coefficient r', and W is the depth domain seismic wavelet vector to be obtained.

In order to obtain the unique solution of W in the above formula, the method of the present invention adopts the method based on ridge regression, promptly optimizes the unconstrained minimization problem of following formula:

min||S-RW|| ² +α||W ² ||

In the formula, α is the ridge parameter, α>0.

In actual calculation, the analytical solution W of the minimization problem of the above formula can be solved by using the following formula by selecting an appropriate value of α:

W＝(RR ^T +αI) ^-1 R ^T S

A method for extracting depth-domain seismic wavelets from depth-domain seismic data according to the present invention will be further described below through specific embodiments.

Figure 1a shows the artificially synthesized multilayer velocity model in the depth domain. The minimum layer velocity is 2000 m/s, the maximum layer velocity is 4200 m/s, the depth direction is 440 meters, and the depth sampling interval is 1 meter. Fig. 1b is the depth-domain synthetic seismic record corresponding to Fig. 1a. It can be seen from Fig. 1b that in the depth domain, the side lobes of seismic reflection wavelets on both sides of the reflection interface are asymmetrical, and they are different from the velocity of the formation on both sides of the interface It is proportional to the size, that is, the greater the formation velocity, the wider the side lobe of the seismic reflection wavelet. Therefore, the depth-domain seismic reflection waveform will broaden as the formation velocity increases.

Figure 2 shows the result of using the method of the present invention to extract the depth-domain seismic wavelet (indicated by the solid line in the figure) from the depth-domain synthetic seismic record in Figure 1b, and compares it with the depth-domain original earthquake used in the synthetic depth-domain seismic record subwaves (indicated by dashed lines in the figure) were compared. In Fig. 2a, the correlation coefficient between the depth domain seismic wavelet (indicated by solid line) extracted by the method of the present invention and the original seismic wavelet in depth domain (indicated by dotted line) has reached 0.9963; in addition, as can be seen from Fig. 2b, the method of the present invention The wavenumber spectrum (represented by the solid line) of the extracted depth-domain seismic wavelet is very close to the spectral distribution characteristics of the wavenumber spectrum (represented by the dotted line) of the original seismic wavelet in the depth domain, indicating that the depth-domain seismic wavelet extracted by the method of the present invention has very high precision.

Fig. 3 is the result of using the method of the present invention to extract the depth domain seismic wavelet from the depth domain angle gather seismic data in a certain area. As can be seen from Fig. 3b, the depth domain seismic wavelet extracted by the method of the present invention from the actual depth domain seismic data The wave quality is very high.

The above-mentioned embodiments are only used to illustrate the present invention, and the various implementation steps of the method etc. all can be changed to some extent, and all equivalent transformations and improvements carried out on the basis of the technical solution of the present invention should not be excluded from the scope of the present invention. outside the scope of protection.

Claims (5)

1. a kind of method that Depth Domain seismic wavelet is extracted in geological data from Depth Domain, it is comprised the following steps：

1) depth, speed and density information are obtained from certain mouthful of borehole logging tool data, corresponding reflectance factor r is thus calculated；

2) this mouthful of seismic trace near well collection s of well is selected from pre-stack depth migration geological data, while choosing a constant velocity v_c, And with the constant velocity as standard speed, the seismic trace near well collection s to choosing carries out the conversion of speed, depth parameter, complies with The condition of LTI, the seismic trace near well collection s' after being converted；

3) being mapped to reflectance factor r turns into r' on the depth location after conversion；

4) suitable ridge parameter α is chosen, Depth Domain seismic wavelet is extracted with Ridge Regression Modeling Method.

2. the method that Depth Domain seismic wavelet is extracted in a kind of geological data from Depth Domain as claimed in claim 1, its feature It is：It is that Depth Domain seismic wavelet is directly extracted from pre-stack depth migration geological data, without to Depth Domain earthquake number According to the time of carrying out to Depth Domain, the mutual conversion of depth to time-domain.

3. the method that Depth Domain seismic wavelet is extracted in a kind of geological data from Depth Domain as claimed in claim 1, its feature It is：The step 2) in, as one constant velocity v of selection_cAs after standard speed, it is necessary to according to the following formula to choose well side ground Shake the conversion of the speed, depth parameter of road s：

In formula, d is the depth sampling interval of log data, d_cIt is the depth value after d conversion, v_cIt is standard constant velocity, v_maxIt is to survey The maximal rate that be recorded in well speed data.Then, with the sampling interval d after conversion_cSeismic trace near well collection s is carried out again Sampling, so as to s is transformed into s'.

4. the method that Depth Domain seismic wavelet is extracted in a kind of geological data from Depth Domain as described in claim 1 and 3, it is special Levy and be：The step 3) in, it is necessary to according to below equation, by reflectance factor r from the depth in log data：

It is converted into the r' at depth below position：

In formula, n is the depth-sampling points of log data, and h is the depth location of log data record, h_cIt is the depth after conversion Position.When reflectance factor r is mapped into the depth location after conversion, the value of reflectance factor is constant, i.e. r=r'.

5. the method that Depth Domain seismic wavelet is extracted in a kind of geological data from Depth Domain as claimed in claim 1, its feature It is：The step 4) in, extract Depth Domain seismic wavelet using Ridge Regression Modeling Method and realize according to the following procedure：

First, will can be in vector form expressed as by the seismic convolution model of the Depth Domain after conversion：

S=RW

In formula, S be by converting after seismic trace near well collection s' build column vector, R is by the reflectance factor r' after depth conversion The Toeplitz matrixes of structure, W is Depth Domain seismic wavelet vector to be asked for.

In order to obtain the unique solution of W in above formula, present invention employs the method for ridge regression, i.e., to following formula unconstrained minimization problem Optimize：

min||S-RW||²+α||W²||

In formula, α is ridge parameter, α>0.

The analytic solutions W of above formula minimization problem can be solved using following formula by selecting suitable α values in actually calculating：

W=(RR^T+αI)^-1R^TS。