Multidirectional earthquake river channel sand body prediction method

Abstract

The invention discloses a multidirectional earthquake river channel sand body prediction method. The problems that in the prior art, due to the fact that full-superposition earthquakes are adopted, signals are covered due to superposition, the distinguishing capacity is insufficient, and the prediction precision of narrow and small river channels is low are solved. The method comprises the following steps: S1, obtaining pre-stack seismic trace gather data and a sound wave impedance logging curve; s2, performing statistics to obtain the azimuth angle range of the pre-stack seismic gather as theta1-theta2; s3, acquiring a plurality of seismic bodies with different azimuth angles; s4, obtaining seismic bodies of a plurality of azimuth angles after normalization; s5, obtaining a synthetic seismic data volume; s6, acquiring a plurality of correlation coefficient data volumes; s7, obtaining a fusion seismic body; and S8, based on the obtained fused seismic body, extracting plane amplitude attributes of a target stratum, and realizing river channel sand body prediction. According to the multidirectional earthquake channel sand body prediction method, azimuth angle information of the pre-stack earthquake channel set is comprehensively utilized, the channel sand body prediction precision is improved, and the oil field exploration and development effects are improved.

Description

Technical Field:

[0001] The present invention relates to the technical field of geophysical exploration, and particularly relates to a method for predicting multi-azimuth seismic channel sand bodies. Background Art:

[0002] Seismic data is a commonly used data for studying the prediction of channel sand bodies, which can improve the prediction accuracy of channel sand bodies and is beneficial to the accurate exploration and efficient development of oil fields in China.

[0003] Currently, the commonly used seismic data is mainly full-stack seismic, that is, seismic traces in different azimuths are fully stacked to form full-stack seismic. Due to the stacking, the signals of full-stack seismic are masked and the resolution ability is insufficient, resulting in a low prediction accuracy for narrow channels. Summary of the Invention:

[0004] The present invention aims at the problems in the background art that in the existing technology, due to the stacking of full-stack seismic, the signals are masked, the resolution ability is insufficient, and the prediction accuracy for narrow channels is low, and provides a method for predicting multi-azimuth seismic channel sand bodies. This method for predicting multi-azimuth seismic channel sand bodies comprehensively utilizes the azimuth angle information of pre-stack seismic trace gathers to improve the prediction accuracy of channel sand bodies and enhance the exploration and development effects of oil fields.

[0005] The present invention can achieve the following technical solutions to solve its problems: This method for predicting multi-azimuth seismic channel sand bodies includes the following steps:

[0006] S1. Obtain pre-stack seismic trace gather data and acoustic impedance logging curves. The seismic traces at each spatial grid point contain azimuth angle information;

[0007] S2. Based on the azimuth angle information contained in the obtained seismic traces, statistically obtain the azimuth angle range of the pre-stack seismic trace gather as θ1 to θ2;

[0008] S3. Stack and calculate the seismic traces at each spatial grid point at azimuth angle intervals to obtain several seismic volumes with different azimuth angles;

[0009] S4. Respectively perform normalization calculations on the obtained several seismic volumes with different azimuth angles to obtain several normalized seismic volumes with different azimuth angles;

[0010] S5. Use the acoustic impedance logging curves and seismic wavelets to obtain a synthetic seismic data volume;

[0011] S6. Based on the obtained synthetic seismic data volume and the several normalized seismic volumes with different azimuth angles, obtain several correlation coefficient data volumes;

[0012] S7. Using several correlation coefficient data volumes as constraints, perform multiple regression fusion calculations on the seismic volumes with different azimuth angles after normalization to obtain a fused seismic volume;

[0013] S8. Based on the obtained fused seismic volume, extract the plane amplitude attributes of the target layer to achieve the prediction of channel sand bodies.

[0014] Preferably, obtain pre-stack seismic trace gather data through seismic acquisition; obtain acoustic impedance logging curves through logging.

[0015] Preferably, the seismic traces at each spatial grid point in step S3 are stacked and calculated at an azimuth interval of m; k seismic volumes with different azimuth angles are obtained, where k is the integer part of (θ1~θ2) / m.

[0016] Preferably, the azimuth interval m is 20~400.

[0017] Preferably, the azimuth interval m is 300.

[0018] Preferably, the method for normalizing the k seismic volumes with different azimuth angles in step S4 is: divide the amplitude value of each spatial grid point of each data volume by the maximum amplitude value of the data volume, and after normalization, obtain the normalized seismic volumes Fn(x, y, t) of k azimuth angles; where: n = 1, 2,..., k; x, y are plane coordinates, and t is the seismic time depth.

[0019] Preferably, the method for synthesizing the seismic data volume in step 5 is: perform Kriging interpolation calculation using the obtained acoustic impedance logging curve to obtain an acoustic impedance data volume, and perform convolution calculation on the acoustic impedance data volume and the seismic wavelet to obtain the synthetic seismic data volume H(x, y, t); where: the grid size and total number used in the Kriging interpolation operation are the same as those of the seismic data volume obtained in step 4, the seismic wavelet uses a Ricker wavelet, and the main frequency of the Ricker wavelet is the same as the seismic data obtained in step 4.

[0020] Preferably, the method for obtaining several correlation coefficient data volumes in step S6 based on the obtained synthetic seismic data volume and the normalized seismic volumes of several azimuth angles is:

[0021] Perform correlation coefficient calculation on the synthetic seismic data volume H(x, y, t) and the normalized seismic volumes Fn(x, y, t) of several azimuth angles respectively to obtain the correlation coefficient data volume Rn(x, y, t).

[0022] Preferably, the formula for calculating the correlation coefficient data volume Rn(x, y, t) by performing correlation coefficient calculation on the synthetic seismic data volume H(x, y, t) and Fn(x, y, t) respectively is:

[0023]

[0024] Wherein: the function Cov is the covariance, and the function D is the variance.

[0025] Preferably, in step S7, using a plurality of correlation coefficient data volumes as constraints, the normalized seismic bodies with different azimuth angles are subjected to multiple regression fusion calculation to obtain a fused seismic body, and its formula is:

[0026] Z(x, y, t) = R1(x, y, t)F1(x, y, t) + R2(x, y, t)F2(x, y, t) + … + R k

[0027] (x, y, t)F k (x, y, t);

[0028] Wherein: F n (x, y, t) is the normalized seismic body with different azimuth angles; Z(x, y, t) is the fused seismic body; R n (x, y, t) is a plurality of correlation coefficient data volumes, n = 1, 2, …, k; x and y are plane coordinates, and t is the time depth of the earthquake.

[0029] The present invention may have the following beneficial effects compared with the above background art:

[0030] The multi-azimuth seismic channel sand body prediction method of the present invention comprehensively utilizes the azimuth angle information of the pre-stack seismic trace gather, improves the prediction accuracy of the channel sand body, is beneficial to searching for oil and gas resources existing in the channel sand body, thereby guiding the accurate development of drilling and various measures, and has important significance for improving the exploration and development effects of oil fields. This method can be applied to the prediction of reservoir sand bodies in different types of oil fields, and the calculation process is clear, the result is reasonable, and the accuracy is relatively high. Brief Description of the Drawings:

[0031] Figure 1 is the flow chart of the multi-azimuth seismic channel sand body prediction method of the present invention;

[0032] Figure 2 is the schematic diagram of the seismic bodies with 6 azimuth angles in the BBL block of the embodiment of the present invention;

[0033] Figure 3 is the schematic diagram of the synthetic seismic data volume in the BBL block of the embodiment of the present invention;

[0034] Figure 4 is the fused seismic body in the BBL block of the embodiment of the present invention;

[0035] Figure 5 is the fused seismic amplitude plan view of the target layer in the BBL block of the embodiment of the present invention. Specific implementation manner:

[0036] To make the objectives, technical solutions and advantages of the present invention clearer, the following will further describe the embodiments of the present invention in detail with reference to the accompanying drawings.

[0037] As Figure 1 shown, a multi-directional seismic channel sand body prediction method includes the following steps:

[0038] S1. Obtain pre-stack seismic trace gather data through seismic acquisition, and the seismic traces at each spatial grid point contain azimuth information; obtain acoustic impedance logging curves through logging.

[0039] S2. Based on the azimuth information contained in the obtained seismic traces, statistically obtain that the azimuth range of the pre-stack seismic trace gather is θ1 to θ2;

[0040] S3. Superpose and calculate the seismic traces at each spatial grid point at an azimuth interval of m to obtain k seismic volumes with different azimuths, where k is the integer part of (θ1 to θ2) / m.

[0041] The azimuth interval m is preferably 20 - 40 0 ; more preferably, the azimuth interval m is 30 0 .

[0042] S4. Respectively perform normalization calculations on the obtained seismic volumes with different azimuths to obtain the normalized seismic volumes with different azimuths; the specific method includes:

[0043] Divide the amplitude value of each spatial grid point of each data volume by the maximum amplitude value of the data volume, and obtain the normalized k azimuth seismic volumes F n (x, y, t); where: n = 1, 2,..., k; x, y are plane coordinates, and t is the seismic time depth.

[0044] S5. Use the acoustic impedance logging curve to perform Kriging interpolation calculation to obtain an acoustic impedance data volume; convolve the acoustic impedance data volume with a seismic wavelet to obtain a synthetic seismic data volume H(x, y, t); the specific method includes:

[0045] Use the obtained acoustic impedance logging curve to perform Kriging interpolation calculation to obtain an acoustic impedance data volume;

[0046] And convolve the acoustic impedance data volume with a seismic wavelet to obtain a synthetic seismic data volume H(x, y, t);

[0047] Wherein: the grid size and total number used in the Kriging interpolation operation are consistent with the seismic data volume obtained in step 4, the seismic wavelet uses a Ricker wavelet, and the main frequency of the Ricker wavelet is consistent with the seismic data obtained in step 4.

[0048] S6. Based on the obtained synthetic seismic data volume and the seismic volumes at several azimuth angles after normalization, several correlation coefficient data volumes are obtained; the specific method includes:

[0049] The synthetic seismic data volume H(x, y, t) is respectively subjected to correlation coefficient calculation with the seismic volumes at several azimuth angles after normalization, F n (x, y, t), and the correlation coefficient data volume R n (x, y, t) is obtained.

[0050] The formula for the correlation coefficient data volume R n (x, y, t) is:

[0051]

[0052] Wherein: the function Cov is the covariance, and the function D is the variance.

[0053] S7. Using several correlation coefficient data volumes as constraints, the seismic volumes at different azimuth angles after normalization are subjected to multiple regression fusion calculation to obtain a fused seismic volume Z(x, y, t), and its formula is:

[0054] Z(x, y, t) = R1(x, y, t)F1(x, y, t) + R2(x, y, t)F2(x, y, t) + … + R k

[0055] (x, y, t)F k (x, y, t);

[0056] Wherein: F n (x, y, t) is the seismic volume at different azimuth angles after normalization; Z(x, y, t) is the fused seismic volume; R n (x, y, t) are several correlation coefficient data volumes, n = 1, 2, …, k; x and y are plane coordinates, and t is the time depth of the earthquake.

[0057] S8. Based on the obtained fused seismic volume, the plane amplitude attribute of the target layer is extracted to realize the prediction of channel sand bodies.

[0058] Example 1

[0059] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings by taking the BBL block of the Daqing Oilfield as an example.

[0060] Step 1: In the BBL block of the Daqing Oilfield, pre-stack seismic gather data are obtained through seismic acquisition, and each seismic trace contains azimuth information; acoustic impedance logging curves are obtained through logging.

[0061] Step 2: It is statistically obtained that the azimuth range of the pre-stack seismic gathers in the BBL block is 0 0 ~180 0 .

[0062] Step 3: The seismic traces at each spatial grid point in the BBL block are stacked and calculated at azimuth intervals of 30 0 to obtain 6 seismic volumes with different azimuths. Figure 2 These are the 6 seismic volumes with different azimuths. Among them, azimuth 1 - azimuth 6 are seismic volumes with azimuths of 0 0 , 30 0 , 60 0 , 90 0 , 120 0 , 150 0 , 180 0 respectively; as can be seen from the figures of azimuth 1 - azimuth 6 in Figure 2 , the overall trends among the seismic volumes are consistent, but there are local differences, and the 6 seismic volumes with different azimuths have relatively rich information.

[0063] Step 4: Normalization calculations are respectively performed on the 6 seismic volumes with different azimuths to obtain 6 normalized seismic volumes with different azimuths.

[0064] Step 5: Kriging interpolation calculation is performed using the acoustic impedance logging curves to obtain an acoustic impedance data volume; the acoustic impedance data volume is convolved with the seismic wavelet to obtain a synthetic seismic data volume H(x, y, t). Figure 3 This is the synthetic seismic data volume of the BBL block, which is overall consistent with the 6 seismic volumes with different azimuths in Figure 2 azimuth 1 - azimuth 6, indicating that the synthetic seismic data volume is reliable and reasonable.

[0065] Step 6: The correlation coefficient calculation is respectively performed between the synthetic seismic data volume H(x, y, t) and F n (x, y, t) to obtain a correlation coefficient data volume R n (x, y, t).

[0066] Step 7: Using R n (x, y, t) as a constraint, the multivariate regression fusion calculation is performed on F n (x, y, t) to obtain a fused seismic volume Z(x, y, t). Figure 4 This is the fused seismic volume of the BBL block. It can be seen that the overall signal is strong and the lateral distribution characteristics are relatively clear, providing relatively accurate seismic data for subsequent prediction of channel sand bodies.

[0067] Step 8: Extract the planar amplitude attribute of the target layer using the fused seismic volume R(x, y, t) to achieve the prediction of channel sand bodies. Figure 5 It is the planar fused seismic amplitude map of the target layer in the BBL block. Five narrow channel sand body features can be seen from the map, and there are typical channel sand body bifurcation phenomena. The channel sand bodies trend north-south, which is consistent with the geological understanding of this area.

[0068] Those of ordinary skill in the art will realize that the embodiments described herein are for helping readers understand the implementation methods of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention based on these technical revelations disclosed in the present invention, and these deformations and combinations are still within the protection scope of the present invention.

Claims

1. A multi-directional seismic channel sand body prediction method, characterized in that: Including the following steps: S1. Obtain pre-stack seismic trace gather data and acoustic impedance logging curves, where the seismic traces at each spatial grid point contain azimuth information; S2. Based on the azimuth information contained in the obtained seismic traces, statistically obtain that the azimuth range of the pre-stack seismic trace gather is θ1 to θ2; S3. Stack and calculate the seismic traces at each spatial grid point at azimuth intervals to obtain several seismic volumes with different azimuths; S4. Respectively perform normalization calculations on the obtained several seismic volumes with different azimuths to obtain the normalized seismic volumes of several azimuths; S5. Use the acoustic impedance logging curve and seismic wavelet to obtain a synthetic seismic data volume; S6. Based on the obtained synthetic seismic data volume and the normalized seismic volumes of several azimuths, obtain several correlation coefficient data volumes; S7. Using several correlation coefficient data volumes as constraints, perform multiple regression fusion calculations on the normalized seismic volumes of different azimuths to obtain a fused seismic volume; S8. Based on the obtained fused seismic volume, extract the plane amplitude attribute of the target layer to achieve the prediction of channel sand bodies.

2. The multi-directional seismic channel sand body prediction method according to claim 1, characterized in that: Obtain pre-stack seismic trace gather data through seismic acquisition; obtain acoustic impedance logging curves through logging.

3. The multi-directional seismic channel sand body prediction method according to claim 1, characterized in that: In step S3, the seismic traces at each spatial grid point are stacked and calculated at an azimuth interval m; k seismic volumes with different azimuths are obtained; where k is the integer part of (θ1 - θ2) / m.

4. The multi-directional seismic channel sand body prediction method according to claim 3, characterized in that: The azimuth interval m is 20 - 40 0 .

5. The multi-directional seismic channel sand body prediction method according to claim 4, characterized in that: The azimuth interval m is 30 0 .

6. The multi-directional seismic channel sand body prediction method according to claim 3, characterized in that: The method for performing normalization calculations on the seismic bodies at k different azimuth angles in step S4 is as follows: divide the amplitude value of each spatial grid point of each data body by the maximum amplitude value of the data body, and obtain the seismic bodies F at k azimuth angles after normalization n (x, y, t); where: n = 1, 2, …, k; x and y are planar coordinates, and t is the time depth of the earthquake.

7. The multi-directional seismic channel sand body prediction method according to claim 6, characterized in that: The method for obtaining the synthetic seismic data volume in step 5 includes: Use the acoustic impedance logging curve and seismic wavelet to obtain a synthetic seismic data volume; Perform Kriging interpolation calculation using the obtained acoustic impedance logging curve to obtain an acoustic impedance data volume; And perform convolution calculation on the acoustic impedance data volume and the seismic wavelet to obtain the synthetic seismic data volume H(x, y, t); Where: The grid size and total number used in the Kriging interpolation operation are consistent with the seismic data volume obtained in step 4, the seismic wavelet uses a Ricker wavelet, and the main frequency of the Ricker wavelet is consistent with the seismic data obtained in step 4.

8. The multi-directional seismic channel sand body prediction method according to claim 7, characterized in that: The method for obtaining several correlation coefficient data volumes in step S6 based on the obtained synthetic seismic data volume and the normalized seismic volumes of several azimuths is: The synthetic seismic data volume H(x, y, t) is respectively correlated with the seismic volumes F n (x, y, t) at several azimuths after normalization to obtain the correlation coefficient data volume R n (x, y, t).

9. The multi-directional seismic channel sand body prediction method according to claim 8, characterized in that: The synthetic seismic data volume H(x, y, t) is respectively correlated with F n (x, y, t) to calculate the correlation coefficient data volume R n (x, y, t) is given by the formula: Where: The function Cov is the covariance, and the function D is the variance.

10. The multi-directional seismic channel sand body prediction method according to claim 9, characterized in that: In step S7, using several correlation coefficient data volumes as constraints, perform multiple regression fusion calculations on the normalized seismic volumes of different azimuths to obtain a fused seismic volume, and its formula is: Z(x,y,t) = R1(x,y,t)F1(x,y,t) + R2(x,y,t)F2(x,y,t) + … + R k (x,y,t)F k (x,y,t); where: F n (x, y, t) is the seismic volume with different azimuths after normalization; Z(x, y, t) is the fused seismic volume; R n (x, y, t) A number of correlation coefficient data volumes, where n = 1, 2, …, k; x and y are plane coordinates, and t is the seismic time depth.

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