A method for strong reflection stripping and weak signal recovery of seismic data

Abstract

The application discloses a method for stripping strong reflection and recovering weak signal of seismic data, and steps are as follows: obtaining time-depth of strong reflection; extracting seismic wavelet; calculating wave impedance data and carrying out square wave processing to obtain logging reflection coefficient; determining maximum and minimum of top interface and bottom interface reflection coefficient of strong reflection formation and maximum and minimum of formation time thickness; giving reflection coefficient increment and time thickness increment, and carrying out discrete sampling on top interface and bottom interface reflection coefficient and formation time thickness; calculating reflection structure characteristic element on each discrete point; calculating projection of seismic record on each reflection structure characteristic element; determining reflection structure characteristic element corresponding to maximum projection value from the projection; subtracting the corresponding reflection structure characteristic element from original seismic record to obtain seismic record after strong reflection stripping. The application effectively enhances resolution ability of seismic data to underground structure.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of seismic data processing in oil and gas geophysical exploration, and more particularly, to a method for strong reflection stripping and weak signal recovery of seismic data. BACKGROUND

[0002] Seismic record is the seismic response of subsurface structure, which can be approximately expressed as the convolution of seismic wavelet and reflection coefficient. That is, the number of seismic wavelet in seismic record is equal to the number of subsurface reflection interface, the time of seismic wavelet appearance is equal to the reflection time of subsurface interface, and the amplitude of seismic wavelet is equal to the reflection coefficient of subsurface interface. Seismic wavelet has a certain duration, when the duration is greater than the difference of travel time of seismic wave at different interfaces, the seismic wavelets of different interfaces interfere with each other, which increases the difficulty of using seismic record to interpret subsurface structure. Coal seam, igneous rock and buried hill structure have large difference in wave impedance with surrounding strata, which produces strong seismic reflection in seismic record, and seriously interferes and shields the weak reflection signal near the strong reflection, reducing the accuracy of horizon interpretation and reservoir prediction of geological structure near the strong reflection.

[0003] The duration of seismic wavelet can be compressed by deconvolution technology to a certain extent, which can weaken the shielding effect of strong reflection stratum on weak signal. However, the compression degree of deconvolution on seismic wavelet depends on the effective frequency band of original seismic data, and it is difficult to completely suppress the shielding effect of strong reflection by deconvolution technology for band-limited seismic record. In addition, the high frequency end of actual seismic record is often occupied by noise, and deconvolution processing will amplify the energy of high frequency noise, reducing the signal-to-noise ratio of seismic record.

[0004] Another method to eliminate the shielding effect of strong reflection is to detect and strip the strong reflection signal from seismic record, and the core idea of this method is the matching pursuit technology based on multi-scale analysis. This method realizes the sparse decomposition of seismic record by constructing an overcomplete atom library, and finds the signal component most matched with strong reflection. However, since the atom library of this method is constructed by stretching and compressing a certain mathematical signal, the atom itself is difficult to simulate the waveform characteristics and frequency characteristics of actual strong reflection signal.

[0005] In fact, if the seismic wavelet can be extracted from the seismic record, the interference effect of the strong reflection formation is completely dependent on the three basic elements of the top interface reflection coefficient, the bottom interface reflection coefficient and the formation time thickness. The reflection structure characteristic elements describing the strong reflection interference effect are constructed in the above three dimensions, and the strong reflection signal is detected and stripped from the actual seismic record by the projection of the actual seismic record on different structure elements, so that the shielding effect of the strong reflection formation can be better eliminated. Therefore, based on the above basic idea, a strong reflection stripping and weak signal recovery method based on reflection structure projection is desirable. SUMMARY

[0006] The purpose of the present application is to overcome the shortcomings of the prior art, provide a strong reflection stripping and weak signal recovery method for seismic data, eliminate the interference and shielding effect of the strong reflection formation on the weak reflection, and recover and reconstruct the weak reflection signal.

[0007] The technical scheme adopted by the present application is as follows:

[0008] According to an aspect of the present application, a strong reflection stripping and weak signal recovery method for seismic data is provided, comprising the following steps:

[0009] 1) obtaining the time depth τ0 of the strong reflection;

[0010] 2) extracting the seismic wavelet w(t);

[0011] 3) calculating the wave impedance data and performing square wave processing to obtain the logging reflection coefficient r0(t);

[0012] 4) statistically analyzing the amplitude and time thickness of the logging reflection coefficient r0(t) near the strong reflection to determine the minimum value a min and the maximum value a max of the top interface reflection coefficient a of the strong reflection formation, the minimum value b min and the maximum value b max of the bottom interface reflection coefficient b of the strong reflection formation, and the minimum thickness h min and the maximum thickness h max of the time thickness h of the strong reflection formation;

[0013] 5) given the reflection coefficient increment Δα and the time thickness increment Δh, discretely sampling the top interface reflection coefficient a of the strong reflection formation, the bottom interface reflection coefficient b of the strong reflection formation and the time thickness h of the strong reflection formation within the value range determined in step 4);

[0014] 6) calculating the reflection structure characteristic element c i,j,k (t) on each discrete point in the three-dimensional space composed of the top interface reflection coefficient a of the strong reflection formation, the bottom interface reflection coefficient b of the strong reflection formation and the time thickness h of the strong reflection formation;

[0015] 7) In the vicinity of time depth τ0, calculate the projection p(i,j,k) of the seismic record on each reflection structure characteristic element c i,j,k (t);

[0016] 8) Determine the reflection structure characteristic element c max (t) corresponding to the maximum projection value from the projection p(i,j,k);

[0017] 9) Subtract the reflection structure characteristic element c max (t) corresponding to the maximum projection value from the original seismic record, to obtain the seismic record after strong reflection stripping.

[0018] In one embodiment of the present application, in step 1), the time depth τ0 of the strong reflection is obtained by horizon interpretation on the three-dimensional seismic record.

[0019] In one embodiment of the present application, in step 2), the seismic wavelet w(t) is extracted from the seismic record in the vicinity of the interpreted horizon. Preferably, the seismic wavelet w(t) is a Ricker wavelet with a main frequency of 30 Hz.

[0020] In one embodiment of the present application, in step 3), acoustic logging data and density logging data are obtained, and wave impedance data are calculated using the acoustic logging data and the density logging data.

[0021] In one embodiment of the present application, in step 4), preferably, a min = 0.1, a max = 0.2, b min = -0.2, b max = -0.1, h min = 2 ms, h max = 8 ms.

[0022] In one embodiment of the present application, in step 5), preferably, Δα = 0.01, Δh = 1 ms.

[0023] In one embodiment of the present application, in step 5):

[0024] The sampling range of the reflection coefficient a of the top boundary of the strong reflection stratum is 0 to m a , the sampling range of the reflection coefficient b of the bottom boundary of the strong reflection stratum is 0 to m b , and the sampling range of the time thickness h of the strong reflection stratum is 0 to m h ; preferably, m a = 10, m b = 10, and m h = 8.

[0025] In one embodiment of the present application, in step 6), the following is performed:

[0026] The reflection structure feature element c on each discrete point is calculated by the following calculation formula i,j,k (t):

[0027] c i,j,k (t)=(a min +iΔα)w(t)+(b min +iΔα)w(h min -kΔh)。

[0028] In one embodiment of the present application, in step 8), the following is performed:

[0029] Preferably, the number of projections p(i,j,k) is (m a +1)×(m b +1)×(m h +1)=11×11×9.

[0030] With the above technical solution, the present application has at least the following beneficial effects:

[0031] The present application provides a method for improving seismic data resolution, which effectively enhances the resolution capability of seismic data to underground structure. The present application is stable and effective, easy to use, and provides technical support for high-resolution seismic data processing. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required by the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0033] Figure 1 A flowchart of the method for stripping strong reflection and recovering weak signal of seismic data provided by the present application is shown;

[0034] Figure 2 A geological model containing strong wave impedance interface is shown;

[0035] Figure 3 A synthetic seismic record of the geological model shown in Figure 2 is shown;

[0036] Figure 4 The result after strong reflection stripping of the synthetic seismic record in Figure 3 is shown;

[0037] Figure 5 A seismic record of an oilfield in an embodiment of the present application is shown;

[0038] Figure 6 The seismic record of the oilfield after strong reflection stripping in the embodiment of the present application is shown. DETAILED DESCRIPTION

[0039] To make the objects, technical solutions and advantages of the present application clearer, the embodiments of the present application are further described in detail below with reference to the drawings.

[0040] In the present application, the model data is taken as an example to further describe and explain the present application. As shown in Figure 2 , Figure 2 The geological model containing a strong shielding stratum is shown, and there are three unconnected sand bodies, i.e. No. 1 sand body, No. 2 sand body and No. 3 sand body, near the lower part of the strong shielding stratum. As shown in Figure 3 , Figure 3 The seismic record synthesized by using the 30Hz Ricker wavelet is shown, and due to the interference effect of the overlying strong reflection stratum, the underlying sand bodies cannot be distinguished and identified on the synthesized seismic record. Thus, the present application provides a method for strong reflection stripping of the model, as shown in Figure 1 , the specific implementation process of the method is as follows:

[0041] Step S101: obtaining the time depth τ0 of strong reflection. Preferably, the time depth τ0 of strong reflection is obtained by horizon interpretation on the three-dimensional seismic record.

[0042] Step S102: extracting the seismic wavelet w(t). The seismic wavelet w(t) is extracted from the seismic record near the interpreted horizon by using a conventional method. In the present application, preferably, the seismic wavelet w(t) is the Ricker wavelet with a main frequency of 30Hz.

[0043] Step S103: obtaining the sonic logging data and the density logging data, and calculating the wave impedance data by using the sonic logging data and the density logging data, and performing square wave processing to obtain the logging reflection coefficient r0(t).

[0044] Step S104: statistically analyzing the amplitude and time thickness of the logging reflection coefficient r0(t) near the strong reflection to determine the minimum value a min and the maximum value a max of the top interface reflection coefficient a of the strong reflection stratum, the minimum value b min and the maximum value b max of the bottom interface reflection coefficient b of the strong reflection stratum, and the minimum thickness h min and the maximum thickness h max of the time thickness h of the strong reflection stratum. In the present application, preferably, a min = 0.1, a max = 0.2, b min=-0.2, b max =-0.1, h min =2ms,h max =8ms.

[0045] Step S105: Given the reflection coefficient increment Δα and the formation time thickness increment Δh, within the value range determined in step S104, perform discrete sampling of the top interface reflection coefficient a, the bottom interface reflection coefficient b, and the formation time thickness h. The sampling range of the top interface reflection coefficient a is from 0 to m. a The sampling range of the bottom interface reflection coefficient b is from 0 to m. b The sampling range for the formation time thickness h is 0 to m. h In this invention, preferably, Δα = 0.01, Δh = 1ms, m a =10,m b =10,m h =8.

[0046] Step S106: In the three-dimensional space consisting of the top interface reflection coefficient a, the bottom interface reflection coefficient b, and the formation time thickness h, calculate the reflection structure characteristic element c at each discrete point according to the following formula. i,j,k (t),

[0047] c i,j,k (t)=(a min +iΔα)w(t)+(b min +iΔα)w(h min -kΔh).

[0048] Step S107: Near the time depth τ0, calculate the seismic record for each reflection structure characteristic element c. i,j,k The projection p(i,j,k) on (t).

[0049] Step S108: From (m a +1)×(m b +1)×(m h Determine the reflection structure feature element c corresponding to the maximum projection value among the +1) projection elements p(i,j,k). max (t). In this invention, (m) a +1)×(m b +1)×(m h +1)=11×11×9.

[0050] Step S109: Subtract the reflection structure feature element c corresponding to the maximum projection value from the original seismic record. max (t) yields the seismic record after strong reflection stripping.

[0051] Through such Figure 1The method is used for processing Figure 3 The processed seismic record is shown in Fig. 4. Figure 4 The result of the strong reflection stripping of the synthetic seismic record is shown in Fig. 5. Figure 3 It can be seen that the strong reflection of the seismic data is effectively stripped by the method of the present application. Figure 4

[0052] Example

[0053] The present embodiment is an application example of a buried hill oilfield.

[0054] The input seismic data of the application example is shown in Fig. 6. Figure 5 The strong reflection events related to the top surface of the buried hill are indicated by the arrows in the figure. Figure 5 The strong reflection events related to the top surface of the buried hill are indicated by the arrows in the figure.

[0055] The seismic data of the buried hill oilfield is processed by the method of the present application, and the result is shown in Fig. 7. Figure 6 The strong reflection events related to the top surface of the buried hill are indicated by the arrows in the figure. Figure 6 The strong reflection events related to the top surface of the buried hill are indicated by the arrows in the figure.

[0056] Therefore, the method of the present application eliminates the interference and shielding effect of the strong reflection layer on the weak reflection, and can restore and reconstruct the weak reflection signal. The present application effectively enhances the resolution of the seismic data to the underground structure.

[0057] The above description is only a preferred embodiment of the present application, and is not intended to limit the scope of the present application; if the present application is modified or replaced without departing from the spirit and scope of the present application, it should be covered in the protection scope of the claims of the present application.​

Claims

1. A method for seismic data strong reflection stripping and weak signal recovery, characterized in that, The method comprises the following steps: 1) obtaining time depth τ0 of strong reflection; 2) extracting seismic wavelet w(t); 3) calculating wave impedance data and carrying out square wave processing to obtain logging reflection coefficient r0(t); 4) Statistical analysis was performed on the amplitude and time thickness of the logging reflection coefficient r0(t) near strong reflection to determine the minimum value a of the reflection coefficient a at the top interface of the strong reflection formation. min and maximum value a max The minimum value of the reflection coefficient b at the bottom interface of a strongly reflective stratum. min and maximum value b max And the minimum thickness h of the time thickness h of the strongly reflective strata. min and maximum thickness h max ; 5) given reflection coefficient increment Δα and time thickness increment Δh, within the value range determined in step 4), the reflection coefficient a of the top interface of the strong reflection formation, the reflection coefficient b of the bottom interface of the strong reflection formation and the time thickness h of the strong reflection formation are discretely sampled; 6) In the three-dimensional space composed of the strong reflection stratum top interface reflection coefficient a, the strong reflection stratum bottom interface reflection coefficient b and the strong reflection stratum time thickness h, the reflection structure characteristic element c on each discrete point is calculated i,j,k (t); 7) Near the time depth τ0, calculate the projection p(i,j,k) of the seismic record on each reflection structure characteristic element c i,j,k (t). 8) determining the reflected structure feature element c corresponding to the maximum projection value from the projections p(i,j,k) max (t); 9) subtracting from the original seismic record the reflection structure characteristic element c corresponding to the maximum projection value max (t), obtaining the seismic record after the strong reflection stripping.

2. The method for seismic data strong reflection stripping and weak signal recovery according to claim 1, characterized in that, In the step 1), the time depth τ0 of strong reflection is obtained by horizon interpretation on the three-dimensional seismic record.

3. The method of seismic data strong reflection stripping and weak signal recovery of claim 2, wherein, In the step 2), the seismic wavelet w(t) is extracted from the seismic record near the interpreted horizon.

4. The method for seismic data strong reflection stripping and weak signal recovery of claim 1, wherein, In the step 3), the acoustic logging data and the density logging data are obtained, and the wave impedance data are calculated by using the acoustic logging data and the density logging data.

5. The method for seismic data strong reflection stripping and weak signal recovery of claim 1, wherein, In the step 6): The reflectance structure feature element c at each discrete point is calculated by the following calculation formula i,j,k (t): c i,j,k (t) = (a min +iΔα)w(t)+(b min +iΔα)w(h min -kΔh).

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