Amplitude anomaly extraction method and device based on stratum energy gradient

Abstract

The invention provides an amplitude anomaly extraction method and device based on a stratum energy gradient, and belongs to the field of geophysical exploration, and the method comprises the steps: carrying out the resampling of post-stack three-dimensional seismic data; amplitude envelope extraction is carried out on the resampled three-dimensional data; extracting stratum reflection time difference from the amplitude envelope; extracting a trend energy gradient of each sampling point in the resampled three-dimensional data, and constructing a tensor matrix of the trend energy gradients; smoothing the tensor matrix, and calculating at least one characteristic value of the tensor matrix after smoothing; and under the condition that the at least one characteristic value does not meet the preset condition, determining that the amplitude of the post-stack three-dimensional seismic data is abnormal. The device comprises a data acquisition module, a data resampling module, an envelope extraction module, a reflection time difference extraction module, a tensor matrix construction module, a feature value calculation module and an amplitude anomaly detection module. Compared with a traditional method, the amplitude abnormity can be detected, and the precision of energy difference description is improved.

Description

Technical Field

[0001] The present application belongs to the field of geophysical exploration, and specifically relates to a method and device for extracting amplitude anomaly based on formation energy gradient. Background Art

[0002] During seismic acquisition, the excited seismic waves propagate from the surface to the underground. When the seismic waves propagate underground, they will be transmitted and reflected when they encounter the interface of stratum impedance difference. When the seismic waves pass through special geological bodies such as caves, rivers or volcanic rocks, the large impedance difference between strata will produce strong seismic reflections, which usually appear as strong energy clusters on the seismic profile, and there is a large energy difference with the surrounding seismic traces. Amplitude attributes can usually be used to extract the torsion, peak state and instantaneous amplitude of the stratum to characterize energy anomalies. However, the attribute bodies obtained by this method not only contain energy anomalies, but also the reflection characteristics of the stratum, which is not conducive to the carving of special geological bodies. In addition, amplitude differences, structural tensors or coherent energy gradients can also be used to characterize amplitude anomalies. However, there are two problems in the traditional structural tensor characterization of energy anomalies. One is that the amplitude anomaly characterized is usually the boundary feature of a special geological body, rather than the geological body itself, which is not conducive to the spatial carving of three-dimensional geological bodies either vertically or horizontally. The second is that the energy anomaly characterized in areas with large stratum inclination will be affected by the stratum tilt, resulting in inaccurate energy anomalies. There are many false anomalies caused by stratum tilt, which do not utilize the interpretation of special geological bodies. Summary of the invention

[0003] Based on the above technical problems, the present application proposes a method and device for extracting amplitude anomalies based on formation energy gradient, which are used to identify or detect amplitude anomalies in seismic profiles and improve the ability to identify special geological bodies.

[0004] In the first aspect, the present application proposes a method for extracting amplitude anomaly based on formation energy gradient, comprising:

[0005] Acquire post-stack 3D seismic data;

[0006] Resampling the post-stack three-dimensional seismic data to obtain resampled three-dimensional data;

[0007] extracting an amplitude envelope from the resampled three-dimensional data;

[0008] extracting formation reflection time difference from the amplitude envelope;

[0009] Extracting the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and constructing a tensor matrix of the strike energy gradient;

[0010] Performing smoothing on the tensor matrix, and calculating at least one eigenvalue of the smoothed tensor matrix;

[0011] When the at least one characteristic value does not meet the predetermined condition, it is determined that there is an amplitude anomaly in the post-stack three-dimensional seismic data.

[0012] The resampling of the post-stack three-dimensional seismic data to obtain the resampled three-dimensional data includes: resampling the post-stack three-dimensional seismic data using a piecewise cubic Hermite interpolation method to obtain the resampled three-dimensional data.

[0013] The step of extracting an amplitude envelope from the resampled three-dimensional data comprises:

[0014] The imaginary part of the resampled three-dimensional data is calculated using the Hilbert transform, and the amplitude envelope is obtained using the following calculation formula:

[0015]

[0016] Where InsAMP is the amplitude envelope, C re is the three-dimensional data after resampling, C im is the imaginary part of the resampled 3D data.

[0017] The step of extracting formation reflection time difference from the amplitude envelope comprises: using a cross-correlation function to respectively extract the seismic event strike time difference in the direction of the amplitude envelope main survey line and the seismic event strike time difference in the direction of the amplitude envelope contact survey line.

[0018] The step of extracting the strike energy gradient of each sample point in the resampled three-dimensional data comprises:

[0019] According to the strike time difference of the seismic phase axis in the direction of the amplitude envelope main survey line and the strike time difference of the seismic phase axis in the direction of the amplitude envelope contact survey line, the partial derivative of each sample point in the resampled three-dimensional data is calculated;

[0020] The partial derivative of each sample point in the resampled three-dimensional data is used to construct the strike energy gradient of each sample point.

[0021] The energy gradient of each sample point is constructed as follows:

[0022]

[0023] Among them, G is the trend energy gradient, C(x,y,z) is the sample point in the three-dimensional data after resampling, is the partial derivative of the main survey line direction calculated according to the time difference of the seismic event axis in the main survey line direction of the amplitude envelope, and Abbreviated as g x , is the partial derivative of the tie line direction calculated according to the time difference of the seismic event strike in the tie line direction of the amplitude envelope, and Abbreviated as g y , is the partial derivative in the time direction, and Abbreviated as g z .

[0024] The tensor matrix of the energy gradient is constructed as follows:

[0025]

[0026] Among them, TST is the tensor matrix of the strike energy gradient, G is the strike energy gradient, G T is the transpose of the energy gradient, g x is the partial derivative in the direction of the main survey line calculated based on the time difference of the seismic event strike in the direction of the main survey line of the amplitude envelope, g y is the partial derivative of the connection line direction calculated based on the time difference of the seismic event strike in the connection line direction of the amplitude envelope, g z is the partial derivative in the time direction.

[0027] The smoothing process for the tensor matrix is ​​to use a Gaussian weighted average method to smooth the tensor matrix.

[0028] The calculating at least one eigenvalue of the smoothed tensor matrix includes: using Jacobi iteration method to calculate at least one eigenvalue of the smoothed tensor matrix.

[0029] In the second aspect, the present application proposes an amplitude anomaly extraction device based on formation energy gradient, comprising:

[0030] A data acquisition module, used for acquiring post-stack three-dimensional seismic data;

[0031] A data resampling module, used for resampling the post-stack three-dimensional seismic data to obtain resampled three-dimensional data;

[0032] An envelope extraction module, used for extracting an amplitude envelope from the resampled three-dimensional data;

[0033] A reflection time difference extraction module, used for extracting the formation reflection time difference from the amplitude envelope;

[0034] A tensor matrix construction module is used to extract the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and construct a tensor matrix of the strike energy gradient;

[0035] an eigenvalue calculation module, used for smoothing the tensor matrix and calculating at least one eigenvalue of the smoothed tensor matrix;

[0036] The amplitude anomaly detection module is used to determine that the post-stack three-dimensional seismic data has an amplitude anomaly when the at least one characteristic value does not meet a predetermined condition.

[0037] In a third aspect, the present application proposes an electronic device, comprising: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the amplitude anomaly extraction method based on formation energy gradient is executed.

[0038] In a fourth aspect, the present application proposes a computer-readable storage medium storing executable instructions, which, when executed, enable a processor to execute the amplitude anomaly extraction method based on formation energy gradient.

[0039] Beneficial technical effects:

[0040] The present application proposes a method and device for extracting amplitude anomalies based on formation energy gradient. Compared with traditional methods, it can detect amplitude anomalies and improve the accuracy of energy difference characterization. At the same time, the energy anomaly characterized is the geological body itself, which is more conducive to three-dimensional space carving or reserve calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of a method for extracting amplitude anomaly based on formation energy gradient according to an embodiment of the present application;

[0042] Figure 2 A schematic diagram showing a comparison of resampling effects in an embodiment of the present application;

[0043] Figure 3 A schematic diagram showing the comparison of amplitude envelope effects of an embodiment of the present application;

[0044] Figure 4 A schematic diagram showing a comparison of the formation reflection time difference effect in an embodiment of the present application;

[0045] Figure 5 A schematic diagram showing comparison of amplitude abnormality results in an embodiment of the present application;

[0046] Figure 6 This is a principle block diagram of an amplitude anomaly extraction device based on formation energy gradient according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] The present disclosure is further described below in conjunction with the embodiments shown in the accompanying drawings.

[0048] In the prior art, the torsion, peak state and instantaneous amplitude of the formation are usually extracted by amplitude attributes to characterize energy anomalies. However, the attribute body obtained by this method not only contains energy anomalies, but also contains the reflection characteristics of the formation, which is not conducive to the carving of special geological bodies. In addition, amplitude differences, structural tensors or coherent energy gradients can also be used to characterize amplitude anomalies. However, the traditional structural tensor characterization of energy anomalies is not conducive to the spatial carving of three-dimensional geological bodies. The energy anomalies are not accurate, there are many false anomalies caused by the inclination of the formation, and the interpretation of special geological bodies is not utilized.

[0049] The present application proposes a method and device for extracting amplitude anomalies based on stratum energy gradient, which fully considers the influence of stratum tilt and the problem of carving the spatial contour of geological bodies. First, the three-dimensional seismic data is resampled, and the resampled seismic data is conducive to the extraction of stratum tilt time difference; secondly, the amplitude envelope is introduced as the input data for the extraction of gradient attributes, which is conducive to the carving of special geological bodies in three-dimensional space. The present application can eliminate false energy anomalies caused by stratum tilt and improve the accuracy of energy difference characterization; at the same time, the energy anomaly depicted is the geological body itself, which is more conducive to three-dimensional space carving or reserve calculation.

[0050] Embodiment 1

[0051] This embodiment proposes a method for extracting amplitude anomalies based on formation energy gradient, such as Figure 1 As shown, including:

[0052] Step S1: Acquire post-stack 3D seismic data;

[0053] In this embodiment, the seismic signals received by the shot detection are processed by dynamic correction and static correction stacking to form a two-dimensional data volume or a three-dimensional data volume. The data before stacking is called pre-stack seismic data, and the data after stacking is called post-stack seismic data. This embodiment is only applicable to three-dimensional seismic data.

[0054] Step S2: resampling the post-stack three-dimensional seismic data to obtain resampled three-dimensional data;

[0055] In this embodiment, resampling the post-stack 3D seismic data to obtain resampled 3D data includes: resampling the post-stack 3D seismic data using a piecewise cubic Hermite interpolation method to obtain resampled 3D data.

[0056] Step S3: extracting the amplitude envelope of the resampled three-dimensional data;

[0057] In this embodiment, the imaginary part of the resampled three-dimensional data is calculated using the Hilbert transform, and the amplitude envelope is obtained using the following calculation formula:

[0058]

[0059] Where InsAMP is the amplitude envelope, C re is the three-dimensional data after resampling, C im is the imaginary part of the resampled 3D data.

[0060] Step S4: extracting formation reflection time difference from the amplitude envelope;

[0061] In this embodiment, extracting the formation reflection time difference from the amplitude envelope includes: using a cross-correlation function to respectively extract the seismic event strike time difference DeltaInline in the direction of the amplitude envelope InsAMP main survey line and the seismic event strike time difference DeltaXline in the direction of the amplitude envelope InsAMP connecting survey line.

[0062] Step S5: extracting the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and constructing a tensor matrix of the strike energy gradient;

[0063] In this embodiment, extracting the strike energy gradient of each sample point in the resampled three-dimensional data includes:

[0064] According to the time difference of the seismic event strike in the direction of the amplitude envelope main survey line and the time difference of the seismic event strike in the direction of the amplitude envelope contact survey line, the partial derivative of each sample point in the resampled three-dimensional data is calculated, specifically:

[0065] Calculate partial derivatives of the main survey line direction based on post-stack 3D seismic data in small bins and DeltaInline Calculate the partial derivative of the tie line direction based on post-stack 3D seismic data in a small bin and DeltaXline

[0066] The partial derivative of each sample point in the resampled three-dimensional data is used to construct the strike energy gradient of each sample point.

[0067] The energy gradient of each sample point is constructed as follows:

[0068]

[0069] Among them, G is the trend energy gradient, C(x,y,z) is the sample point in the three-dimensional data after resampling, is the partial derivative of the main survey line direction calculated according to the time difference of the seismic event axis in the main survey line direction of the amplitude envelope, and Abbreviated as g x , is the partial derivative of the tie line direction calculated according to the time difference of the seismic event strike in the tie line direction of the amplitude envelope, and Abbreviated as gy , is the partial derivative in the time direction, and Abbreviated as g z .

[0070] The tensor matrix of the energy gradient is constructed as follows:

[0071]

[0072] Among them, TST is the tensor matrix of the strike energy gradient, G is the strike energy gradient, G T is the transpose of the energy gradient, g x is the partial derivative in the direction of the main survey line calculated based on the time difference of the seismic event strike in the direction of the main survey line of the amplitude envelope, g y is the partial derivative of the connection line direction calculated based on the time difference of the seismic event strike in the connection line direction of the amplitude envelope, g z is the partial derivative in the time direction.

[0073] Step S6: performing smoothing on the tensor matrix, and calculating at least one eigenvalue of the smoothed tensor matrix;

[0074] In this embodiment, the tensor matrix is ​​smoothed by using a Gaussian weighted average method, and at least one eigenvalue of the smoothed tensor matrix is ​​calculated, including: using a Jacobi iteration method to calculate at least one eigenvalue of the smoothed tensor matrix. By using any eigenvalue of the at least one eigenvalue or the combination of at least two eigenvalues, the amplitude anomaly in the seismic profile can be characterized.

[0075] Step S7: when the at least one characteristic value does not meet the predetermined condition, determining that there is an amplitude anomaly in the post-stack 3D seismic data.

[0076] In a specific implementation, as long as the characteristic value is obtained, it can be determined whether there is an amplitude anomaly in the post-stack 3D seismic data through certain predetermined conditions. This step is a well-known technology for those skilled in the art and will not be described in detail in this application.

[0077] The present application proposes an amplitude anomaly extraction method based on formation energy gradient. First, the post-stack three-dimensional seismic data is resampled to obtain the resampled three-dimensional data; the amplitude envelope is extracted from the resampled three-dimensional data, and the formation reflection time difference is extracted from the amplitude envelope; then, according to the formation reflection time difference, the strike energy gradient of each sample point in the resampled three-dimensional data is extracted, and a tensor matrix of the strike energy gradient is constructed; finally, the tensor matrix is ​​smoothed, and at least one eigenvalue of the smoothed tensor matrix is ​​calculated; when at least one eigenvalue does not meet the predetermined condition, it is determined that the post-stack three-dimensional seismic data has an amplitude anomaly. This embodiment introduces the amplitude envelope as the input data for extracting the gradient attribute, which is conducive to the carving of the three-dimensional space of special geological bodies, can eliminate the false energy anomaly caused by the formation tilt, and improve the accuracy of the energy difference characterization; at the same time, the energy anomaly depicted as the geological body itself is more conducive to three-dimensional space carving or reserve calculation.

[0078] Embodiment 2

[0079] This embodiment is a specific example of the first embodiment, and describes in detail a method for extracting amplitude anomalies based on formation energy gradient, and uses specific data and simulation results to prove the effectiveness of the method described in this embodiment.

[0080] A method for extracting amplitude anomalies based on formation energy gradient, such as Figure 1 As shown, including:

[0081] Step S1: Acquire post-stack 3D seismic data;

[0082] In this embodiment, the seismic signals received by the shot detection are processed by dynamic correction and static correction stacking to form a two-dimensional data volume or a three-dimensional data volume. The data before stacking is called pre-stack seismic data, and the data after stacking is called post-stack seismic data. This embodiment is only applicable to three-dimensional seismic data.

[0083] Step S2: resampling the post-stack three-dimensional seismic data to obtain resampled three-dimensional data;

[0084] In this embodiment, the input three-dimensional post-stack seismic data volume C is resampled using piecewise cubic Hermite interpolation to obtain the resampled three-dimensional data C re .

[0085] For each seismic signal f(x), the piecewise cubic Hermite interpolation algorithm is used for interpolation, and the calculation formula is as follows:

[0086] H3(x)=f k-1 α k-1 (x)+f k α k (x)+f' k-1 β k-1(x)+f' k β k (x)

[0087] Among them, H3(x) is the interpolation result, f k is f(x) at point x k The value at f' k f k The first derivative of k-1 is f(x) at point x k-1 The value at f' k-1 f k-1 The first derivative of

[0088]

[0089]

[0090] Finally, all interpolation results of all channels constitute the resampled three-dimensional data C re .

[0091] like Figure 2 As shown, the seismic profile encrypted by the piecewise cubic Hermite interpolation algorithm is compared with the original seismic profile (the post-stack 3D seismic data obtained in step S1), wherein the lower one is the original seismic profile with a sampling interval of 4ms; the upper one is the seismic profile sampled at 1ms after the piecewise cubic Hermite interpolation; from the profile comparison, it can be seen that the piecewise cubic Hermite interpolation can well maintain the characteristics of the original seismic signal, and the waveform change characteristics do not change at all. After the interpolation, the sampling interval of the seismic signal becomes smaller and the number of discrete points increases, which is beneficial to improve the extraction accuracy of the time difference between inclined strata.

[0092] Step S3: extracting the amplitude envelope of the resampled three-dimensional data;

[0093] In this embodiment, the imaginary part of the resampled three-dimensional data is calculated using the Hilbert transform, and the amplitude envelope is obtained using the following calculation formula:

[0094]

[0095] Where InsAMP is the amplitude envelope, C re is the three-dimensional data after resampling, C im is the imaginary part of the three-dimensional data after resampling.

[0096] like Figure 3 As shown, the amplitude envelope properties are extracted from the encrypted seismic signal using the Hilbert transform.

[0097] Step S4: extracting formation reflection time difference from the amplitude envelope;

[0098] In this embodiment, extracting the formation reflection time difference from the amplitude envelope includes: using a cross-correlation function to respectively extract the seismic event strike time difference DeltaInline in the direction of the amplitude envelope InsAMP main survey line and the seismic event strike time difference DeltaXline in the direction of the amplitude envelope InsAMP connecting survey line.

[0099] like Figure 4 As shown in the figure, the strike time difference DeltaInline in the main side line direction extracted from the amplitude envelope attribute data volume, when the stratum tilts upward, the time difference is negative and displayed in white; when the stratum tilts downward, the time difference is positive and displayed in black.

[0100] Step S5: extracting the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and constructing a tensor matrix of the strike energy gradient;

[0101] In this embodiment, extracting the strike energy gradient of each sample point in the resampled three-dimensional data includes:

[0102] According to the time difference of the seismic event strike in the direction of the amplitude envelope main survey line and the time difference of the seismic event strike in the direction of the amplitude envelope contact survey line, the partial derivative of each sample point in the resampled three-dimensional data is calculated, specifically:

[0103] Calculate partial derivatives of the main survey line direction based on post-stack 3D seismic data in small bins and DeltaInline Calculate the partial derivative of the tie line direction based on post-stack 3D seismic data in a small bin and DeltaXline

[0104] Take the extraction of the strike time difference DeltaInline of the seismic event axis in the direction of the main lateral line as an example: for a certain sample point on a profile of the resampled three-dimensional data, it is defined as the center point, and the cross-correlation time window N and the maximum scanning time window M are set. The seismic signal S with a length of N centered on the center point is intercepted, and the cross-correlation coefficient is calculated by scanning the seismic signal S and the adjacent seismic traces from top to bottom starting from the maximum scanning time window M. The difference between the position with the largest cross-correlation coefficient and the center point position is the strike time difference of DeltaInline at the center point.

[0105] The partial derivative of each sample point in the resampled three-dimensional data is used to construct the strike energy gradient of each sample point.

[0106] The energy gradient of each sample point is constructed as follows:

[0107]

[0108] Among them, G is the trend energy gradient, C(x,y,z) is the sample point in the three-dimensional data after resampling, is the partial derivative of the main survey line direction calculated according to the time difference of the seismic event axis in the main survey line direction of the amplitude envelope, and Abbreviated as g x , is the partial derivative of the tie line direction calculated according to the time difference of the seismic event strike in the tie line direction of the amplitude envelope, and Abbreviated as g y , is the partial derivative in the time direction, and Abbreviated as g z .

[0109] Taking the partial derivative of the seismic signal along the strike of the seismic event axis can eliminate the influence of stratum tilt and help highlight the energy anomalies hidden in the tilted strata.

[0110] The tensor matrix of the energy gradient is constructed as follows:

[0111]

[0112] Among them, TST is the tensor matrix of the strike energy gradient, G is the strike energy gradient, G T is the transpose of the energy gradient, g x is the partial derivative in the direction of the main survey line calculated based on the time difference of the seismic event strike in the direction of the main survey line of the amplitude envelope, g y is the partial derivative of the connection line direction calculated based on the time difference of the seismic event strike in the connection line direction of the amplitude envelope, g z is the partial derivative in the time direction.

[0113] Step S6: performing smoothing on the tensor matrix, and calculating at least one eigenvalue of the smoothed tensor matrix;

[0114] In this embodiment, a Gaussian weighted average method is used to smooth the tensor matrix, and at least one eigenvalue of the smoothed tensor matrix is ​​calculated, including: using a Jacobi iteration method to calculate at least one eigenvalue of the smoothed tensor matrix.

[0115]

[0116] Among them, η i =E{g i}, η i is the g in the three-dimensional hour window i The mean value, η j =E{g j}, η j is the g in the three-dimensional hour window j The mean of , the Gaussian window function is as follows:

[0117]

[0118] Among them, TST sm is the smoothed tensor matrix, ∑TST ij (x, y, z) is the Gaussian weighted sum of the tensor matrix of the i-th sample point and the tensor matrix of the j-th sample point, g i (x+Δx,y+Δy,z+Δz) is the gradient of the ith sample point, g j (x+Δx,y+Δy,z+Δz) is the gradient of the jth sample point, σ x is the variance of x, σ y is the variance of y, σ z is the variance of z.

[0119] Step S7: when the at least one characteristic value does not meet the predetermined condition, determining that there is an amplitude anomaly in the post-stack 3D seismic data.

[0120] In this embodiment, the Jacobi iteration method is used to obtain the smoothed trend energy gradient tensor matrix TST. sm The characteristic values ​​λ1, λ2 and λ3 are used, through certain predetermined conditions, to determine whether there is an amplitude anomaly in the post-stack 3D seismic data using one characteristic value or a combination of the characteristic values ​​λ1, λ2 and λ3. This step is a well-known technology for those skilled in the art and will not be described in detail in this application.

[0121] like Figure 5 As shown, the amplitude anomaly profile depicted by the eigenvalues ​​of the traditional structure tensor is compared with the amplitude anomaly profile depicted by the eigenvalues ​​obtained by the method described in this embodiment. The upper side is the original seismic profile, the middle side is the eigenvalue extracted by the traditional structure tensor, and the lower side is the eigenvalue extracted by this embodiment. By comparison, it can be seen that the eigenvalue extracted by this embodiment can well eliminate the influence of the formation tilt, and the amplitude anomaly depicted at the same time is the outline of the geological body, which is more conducive to the three-dimensional space carving of the geological body.

[0122] The amplitude anomaly extraction method based on formation energy gradient proposed in this embodiment, first, resample the post-stack three-dimensional seismic data to obtain resampled three-dimensional data; extract the amplitude envelope of the resampled three-dimensional data, and extract the formation reflection time difference from the amplitude envelope; then, extract the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and construct a tensor matrix of the strike energy gradient; finally, smooth the tensor matrix, and calculate at least one eigenvalue of the smoothed tensor matrix; when at least one eigenvalue does not meet the predetermined conditions, it is determined that the post-stack three-dimensional seismic data has an amplitude anomaly. The influence of formation tilt and the carving problem of the spatial contour of the geological body are fully considered, and the seismic signal encryption processing and amplitude envelope attributes are introduced into the interpretation process to improve the accuracy of amplitude anomaly characterization. The depicted energy anomaly eliminates the false anomaly caused by the uneven formation, highlights the contour of the geological body, and is more conducive to the carving of special geological bodies.

[0123] Embodiment 3

[0124] This embodiment proposes an amplitude anomaly extraction device based on formation energy gradient, such as Figure 6 As shown, it includes: a data acquisition module, a data resampling module, an envelope extraction module, a reflection time difference extraction module, a tensor matrix construction module, an eigenvalue calculation module and an amplitude anomaly detection module, the data acquisition module is connected to the data resampling module, the data resampling module is connected to the envelope extraction module, the envelope extraction module is connected to the reflection time difference extraction module, the reflection time difference extraction module is connected to the tensor matrix construction module, the tensor matrix construction module is connected to the eigenvalue calculation module, and the eigenvalue calculation module is connected to the amplitude anomaly detection module.

[0125] A data acquisition module, used for acquiring post-stack three-dimensional seismic data;

[0126] A data resampling module, used for resampling the post-stack three-dimensional seismic data to obtain resampled three-dimensional data;

[0127] An envelope extraction module, used for extracting an amplitude envelope from the resampled three-dimensional data;

[0128] In this embodiment, the imaginary part of the resampled three-dimensional data is calculated using the Hilbert transform, and the amplitude envelope is obtained using the following calculation formula:

[0129]

[0130] Where InsAMP is the amplitude envelope, C re is the three-dimensional data after resampling, C im is the imaginary part of the three-dimensional data after resampling.

[0131] A reflection time difference extraction module, used for extracting the formation reflection time difference from the amplitude envelope;

[0132] In this embodiment, the cross-correlation function is used to extract the seismic event strike time difference DeltaInline in the direction of the amplitude envelope InsAMP main survey line and the seismic event strike time difference DeltaXline in the direction of the amplitude envelope InsAMP contact survey line.

[0133] A tensor matrix construction module is used to extract the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and construct a tensor matrix of the strike energy gradient;

[0134] Extract the strike energy gradient of each sample point in the resampled 3D data, including:

[0135] According to the strike time difference of the seismic phase axis in the direction of the amplitude envelope main survey line and the strike time difference of the seismic phase axis in the direction of the amplitude envelope contact survey line, the partial derivative of each sample point in the resampled three-dimensional data is calculated;

[0136] The partial derivative of each sample point in the resampled three-dimensional data is used to construct the strike energy gradient of each sample point.

[0137] The energy gradient of each sample point is constructed as follows:

[0138]

[0139] Among them, G is the trend energy gradient, C(x,y,z) is the sample point in the three-dimensional data after resampling, is the partial derivative of the main survey line direction calculated according to the time difference of the seismic event axis in the main survey line direction of the amplitude envelope, and Abbreviated as g x , is the partial derivative of the tie line direction calculated according to the time difference of the seismic event strike in the tie line direction of the amplitude envelope, and Abbreviated as g y , is the partial derivative in the time direction, and Abbreviated as g z .

[0140] The tensor matrix of the energy gradient is constructed as follows:

[0141]

[0142] Among them, TST is the tensor matrix of the strike energy gradient, G is the strike energy gradient, G T is the transpose of the energy gradient, g xis the partial derivative in the direction of the main survey line calculated based on the time difference of the seismic event strike in the direction of the main survey line of the amplitude envelope, g y is the partial derivative of the connection line direction calculated based on the time difference of the seismic event strike in the connection line direction of the amplitude envelope, g z is the partial derivative in the time direction.

[0143] an eigenvalue calculation module, used for smoothing the tensor matrix and calculating at least one eigenvalue of the smoothed tensor matrix;

[0144] The amplitude anomaly detection module is used to determine that the post-stack three-dimensional seismic data has an amplitude anomaly when the at least one characteristic value does not meet a predetermined condition.

[0145] The present application proposes an amplitude anomaly extraction device based on formation energy gradient, comprising: using a data resampling module to resample the post-stack three-dimensional seismic data to obtain resampled three-dimensional data, using an envelope extraction module to extract the amplitude envelope of the resampled three-dimensional data, using a reflection time difference extraction module to extract the formation reflection time difference from the amplitude envelope, using a tensor matrix construction module to construct a tensor matrix of the strike energy gradient, using an eigenvalue calculation module to smooth the tensor matrix, and calculate at least one eigenvalue of the smoothed tensor matrix; finally, using an amplitude anomaly detection module, when the at least one eigenvalue does not meet the predetermined conditions, it is determined that the post-stack three-dimensional seismic data has an amplitude anomaly. The device of this embodiment can eliminate the false energy anomaly caused by the formation tilt and improve the accuracy of energy difference characterization; at the same time, the energy anomaly characterized as the geological body itself is more conducive to three-dimensional space carving or reserve calculation.

[0146] Embodiment 4:

[0147] This embodiment provides an electronic device, including: a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the amplitude anomaly extraction method based on formation energy gradient is executed.

[0148] The electronic device may be a mobile phone, a computer or a tablet computer, etc., including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the amplitude anomaly extraction method based on formation energy gradient as described in the embodiment is implemented. It is understood that the electronic device may also include an input / output (I / O) interface and a communication component.

[0149] The processor is used to execute all or part of the steps in the amplitude anomaly extraction method based on formation energy gradient as described in the above embodiment. The memory is used to store various types of data, which may include instructions of any application or method in the electronic device, as well as data related to the application.

[0150] The processor can be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is used to execute the amplitude anomaly extraction method based on formation energy gradient described in the above embodiments.

[0151] Embodiment 5

[0152] This embodiment provides a computer-readable storage medium storing executable instructions, which, when executed, enable a processor to execute the amplitude anomaly extraction method based on formation energy gradient.

[0153] If implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0154] Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the amplitude anomaly extraction method based on formation energy gradient described in each embodiment of the present application.

[0155] The aforementioned storage media include: flash memory, hard disk, multimedia card, card-type memory (for example, SD (Secure Digital Memory Card) or DX (Memory Data Register, MDR abbreviation, memory data register) memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, CD, server, APP (Application, abbreviation of application software) application store and other media that can store program verification codes, on which computer programs are stored. When the computer program is executed by the processor, the various steps of the amplitude anomaly extraction method based on formation energy gradient described above can be implemented.

[0156] The various embodiments in the present disclosure are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0157] The protection scope of the present disclosure is not limited to the above-mentioned embodiments. Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the scope and spirit of the present disclosure. If these changes and modifications fall within the scope of the claims of the present disclosure and their equivalents, the intention of the present disclosure also includes these changes and modifications.

Claims

1. A method for extracting amplitude anomaly based on formation energy gradient, characterized in that: include: Acquire post-stack 3D seismic data; Resampling the post-stack three-dimensional seismic data to obtain resampled three-dimensional data; extracting an amplitude envelope from the resampled three-dimensional data; extracting formation reflection time difference from the amplitude envelope; Extracting the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and constructing a tensor matrix of the strike energy gradient; Performing smoothing on the tensor matrix, and calculating at least one eigenvalue of the smoothed tensor matrix; When the at least one characteristic value does not meet the predetermined condition, it is determined that there is an amplitude anomaly in the post-stack three-dimensional seismic data.

2. The amplitude anomaly extraction method based on formation energy gradient according to claim 1 is characterized in that: The resampling of the post-stack three-dimensional seismic data to obtain the resampled three-dimensional data includes: resampling the post-stack three-dimensional seismic data using a piecewise cubic Hermite interpolation method to obtain the resampled three-dimensional data.

3. The amplitude anomaly extraction method based on formation energy gradient according to claim 1 is characterized in that: The step of extracting an amplitude envelope from the resampled three-dimensional data comprises: The imaginary part of the resampled three-dimensional data is calculated using the Hilbert transform, and the amplitude envelope is obtained using the following calculation formula: Where InsAMP is the amplitude envelope, C re is the resampled three-dimensional data, C im is the imaginary part of the three-dimensional data after resampling.

4. The amplitude anomaly extraction method based on formation energy gradient according to claim 1 is characterized in that: The step of extracting formation reflection time difference from the amplitude envelope comprises: using a cross-correlation function to respectively extract the seismic event strike time difference in the direction of the amplitude envelope main survey line and the seismic event strike time difference in the direction of the amplitude envelope contact survey line.

5. The amplitude anomaly extraction method based on formation energy gradient according to claim 4 is characterized in that: The step of extracting the strike energy gradient of each sample point in the resampled three-dimensional data comprises: According to the strike time difference of the seismic phase axis in the direction of the amplitude envelope main survey line and the strike time difference of the seismic phase axis in the direction of the amplitude envelope contact survey line, the partial derivative of each sample point in the resampled three-dimensional data is calculated; The partial derivative of each sample point in the resampled three-dimensional data is used to construct the strike energy gradient of each sample point.

6. The amplitude anomaly extraction method based on formation energy gradient according to claim 5 is characterized in that: The energy gradient of each sample point is constructed as follows: Among them, G is the trend energy gradient, C(x,y,z) is the sample point in the three-dimensional data after resampling, is the partial derivative of the main survey line direction calculated according to the time difference of the seismic event axis in the main survey line direction of the amplitude envelope, and Abbreviated as g x , is the partial derivative of the tie line direction calculated according to the time difference of the seismic event strike in the tie line direction of the amplitude envelope, and Abbreviated as g y , is the partial derivative in the time direction, and Abbreviated as g z .

7. The amplitude anomaly extraction method based on formation energy gradient according to claim 1 is characterized in that: The tensor matrix of the energy gradient is constructed as follows: Among them, TST is the tensor matrix of the strike energy gradient, G is the strike energy gradient, G T is the transpose of the energy gradient, g x is the partial derivative in the direction of the main survey line calculated based on the time difference of the seismic event strike in the direction of the main survey line of the amplitude envelope, g y is the partial derivative of the connection line direction calculated based on the time difference of the seismic event strike in the connection line direction of the amplitude envelope, g z is the partial derivative in the time direction.

8. The amplitude anomaly extraction method based on formation energy gradient according to claim 1 is characterized in that: The smoothing process for the tensor matrix is ​​to use a Gaussian weighted average method to smooth the tensor matrix.

9. The amplitude anomaly extraction method based on formation energy gradient according to claim 1 is characterized in that: The calculating at least one eigenvalue of the smoothed tensor matrix includes: using Jacobi iteration method to calculate at least one eigenvalue of the smoothed tensor matrix.

10. An amplitude anomaly extraction device based on formation energy gradient, characterized in that: include: A data acquisition module, used for acquiring post-stack three-dimensional seismic data; A data resampling module, used for resampling the post-stack three-dimensional seismic data to obtain resampled three-dimensional data; An envelope extraction module, used for extracting an amplitude envelope from the resampled three-dimensional data; A reflection time difference extraction module, used for extracting the formation reflection time difference from the amplitude envelope; A tensor matrix construction module is used to extract the strike energy gradient of each sample point in the resampled three-dimensional data according to the formation reflection time difference, and construct a tensor matrix of the strike energy gradient; an eigenvalue calculation module, used for smoothing the tensor matrix and calculating at least one eigenvalue of the smoothed tensor matrix; The amplitude anomaly detection module is used to determine that the post-stack three-dimensional seismic data has an amplitude anomaly when the at least one characteristic value does not meet a predetermined condition.

11. An electronic device, characterized in that: include: A memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the amplitude anomaly extraction method based on formation energy gradient according to any one of claims 1 to 9 is executed.

12. A computer-readable storage medium, characterized in that: It stores executable instructions, which, when executed, enable the processor to execute the amplitude anomaly extraction method based on formation energy gradient as described in any one of claims 1-9.

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