Earthquake surface wave attenuation method

Abstract

The invention relates to the technical field of seismic dispersion surface wave attenuation, in particular to a seismic surface wave attenuation method. The seismic surface wave attenuation method comprises the following steps: firstly, establishing a surface gradient model according to surface elevation information after smoothing processing; secondly, according to the change relation between the earth surface gradient model and the surface wave dispersion, surface wave dispersion characteristics are counted; thirdly, establishing a frequency dispersion surface wave model according to surface wave frequency dispersion characteristics; then, matching the frequency dispersion surface wave model with actual seismic data to obtain surface wave information in the actual seismic data; and finally, separating the surface waves through a subtraction method on the basis of the surface wave information. According to the method, surface waves are effectively attenuated on the premise of ensuring that effective reflection is not lost, and the purpose of high-fidelity noise attenuation is achieved.

Description

Technical Field

[0001] This invention relates to the field of seismic dispersion surface wave attenuation technology, and particularly to a seismic surface wave attenuation method. Background Technology

[0002] In terrestrial seismic exploration, surface waves are a major type of regular noise, characterized by high energy and generally frequencies below 20Hz. In areas with significant topographic relief, they easily cause surface wave dispersion, severely impacting the signal-to-noise ratio of seismic data. Incomplete surface wave attenuation can lead to poor migration imaging, creating false bright spot anomalies. This poses a significant threat to the detailed description of bright spot reflection characteristics of dense terrestrial sand bodies in the general exploration area. Therefore, effectively eliminating the impact of surface wave interference on seismic data is of paramount importance.

[0003] Seismic waves are divided into longitudinal (P) waves and transverse (S) waves. S wave is a wave in which the direction of particle vibration is perpendicular to the direction of wave propagation, while P wave is a wave in which the direction of particle vibration is parallel to the direction of wave propagation. These two types of waves interact, intersecting or superimposing at the Earth's surface to produce a rolling wave, also known as a surface wave, that propagates along the surface. The flatter the Earth's surface, the simpler its dispersion characteristics; however, surface waves exhibit more severe and complex dispersion phenomena when encountering surface undulations.

[0004] Surface waves are a special type of Rayleigh wave, originating in the low-velocity zone near the Earth's surface and characterized by low frequency, low velocity, strong amplitude, and dispersion. Due to their dispersion characteristics, surface waves often exhibit a near-linear, "broom-like" distribution in seismic records. This type of surface wave interference is characterized by complex and variable dispersion regions, weak linearity, rapid apparent velocity changes, and significant attenuation challenges. Currently, experts both domestically and internationally have conducted numerous attempts to attenuate dispersive surface waves, including frequency domain filtering, FK filtering, and Radon transform. Because surface waves and effective waves (reflected waves) are correlated, and the frequency bands of surface waves and the low-frequency portions of effective waves always overlap, frequency domain filtering or FK domain filtering will result in varying degrees of loss of the effective low-frequency signal. The Radon transform, based on the linearity of surface waves in seismic records, transforms the surface wave into an "energy point" in the Radon domain, thereby separating it from the effective signal. However, due to the end-point effect, the removal of the Radon domain will cause distortion of the effective signal. At the same time, the technique cannot accurately identify the area where surface wave dispersion occurs, and the Radon transform cannot completely suppress surface waves.

[0005] Chinese invention patent application CN2116068619A, published on May 5, 2023, discloses an adaptive multi-order dispersion surface wave suppression method, apparatus, and device. This method attenuates dispersion surface waves through multi-order surface wave attenuation technology. Based on the surface wave velocity changes caused by dispersion, the surface wave interference is subdivided into multiple data segments. Different apparent surface wave attenuation velocities are set for each data segment to predict the surface wave, thus achieving the goal of attenuating dispersion surface waves. Its advantage lies in the thorough attenuation of dispersion surface waves and high fidelity in the dispersion region. However, this method has inherent drawbacks: firstly, it cannot predict the surface wave dispersion region; secondly, it easily damages effective reflection in areas without surface wave dispersion, resulting in a lack of fidelity in the noise reduction process.

[0006] The paper "A Data-Driven Surface Wave Prediction and Adaptive Attenuation Method" presents a data-driven method for identifying dispersive surface waves. It predicts the occurrence region and dispersion characteristics of dispersive surface waves by using the time difference between the theoretical surface wave model and the actual surface waves generated by the shot-receiver distance prediction. A variable velocity adaptive surface wave attenuation technique is then employed to reduce noise, achieving the goal of attenuating dispersive surface waves. Its advantage lies in being purely data-driven, meeting the needs of massive data processing, and having relatively low effective reflection loss. However, while this method identifies dispersive surface wave characteristics and occurrence regions through data-driven methods, its accuracy is low, it is prone to surface wave dispersion artifacts, and the apparent velocity recognition of surface wave dispersion is low, significantly reducing the surface wave attenuation effect.

[0007] Currently, there is no systematic analysis and attenuation method for dispersive surface waves. However, dispersive surface waves are an important interference factor affecting seismic lithology exploration and need to be effectively removed. Therefore, it is necessary to fully study the formation mechanism of seismic dispersive surface waves and formulate practical attenuation schemes to support the progress of oilfield exploration and development. Summary of the Invention

[0008] The purpose of this invention is to provide a seismic surface wave attenuation method to solve the problem that existing technologies cannot effectively attenuate dispersive surface wave interference.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0010] A seismic surface wave attenuation method includes the following steps:

[0011] (1) Establish a surface gradient model based on the smoothed surface elevation information;

[0012] (2) Based on the relationship between the surface gradient model and surface wave dispersion, statistically analyze the surface wave dispersion characteristics;

[0013] (3) Establish a dispersion surface wave model based on the dispersion characteristics of surface waves;

[0014] (4) Match the dispersion surface wave model with the actual seismic data to obtain surface wave information in the actual seismic data;

[0015] (5) Surface waves are separated by subtraction based on surface wave information.

[0016] This invention is an improved version that utilizes the influence of changes in surface elevation on the dispersion intensity and apparent velocity of surface waves. It statistically analyzes surface wave dispersion characteristics, accurately locates the dispersion region, constructs a dispersion surface wave model, and matches it with actual seismic data to achieve precise signal-to-noise separation. While ensuring no loss of effective reflection, it effectively attenuates surface waves, achieving high-fidelity noise reduction. The technical solution of this invention is particularly suitable for environments with undulating terrain and complex conditions.

[0017] The technical solution of the present invention has the following advantages:

[0018] (1) Based on the relationship between surface wave dispersion and surface gradient change, the specific location of surface wave dispersion is determined, which solves the problem that conventional methods cannot accurately identify dispersive surface waves;

[0019] (2) The surface elevation change during the surface wave dispersion process fully considers the influence of the surface wave dispersion characteristics, namely the surface wave dispersion apparent velocity and dispersion intensity. The method of calculating the surface wave dispersion apparent velocity and dispersion intensity through the surface gradient solves the problem that conventional methods cannot accurately identify the surface wave dispersion apparent velocity and dispersion intensity. It accurately predicts the surface wave occurrence area and the variation characteristics of the surface wave dispersion apparent velocity and dispersion intensity, and effectively improves the dispersion surface wave attenuation effect.

[0020] (3) With the surface wave theory model as a reference, the surface wave attenuation effect is fully guaranteed without loss of effective reflection.

[0021] To accurately obtain the surface wave dispersion intensity, preferably, the surface wave dispersion characteristics in step (2) include dispersion intensity and dispersion apparent velocity, wherein the dispersion intensity is obtained from Equation 1:

[0022]

[0023] In Equation 1: v x v represents the surface wave velocity component in the direction parallel to the survey line. y t1 represents the surface wave velocity component in the direction perpendicular to the survey line; t1 is the start time of surface wave propagation between two elevation points, and t2 is the arrival time.

[0024] To accurately obtain the apparent dispersion velocity of the surface wave, preferably, the apparent dispersion velocity is obtained from Equation 2:

[0025]

[0026] In Equation 2: (x1,y1) and (x2,y2) are the coordinates of two adjacent grid points, and t2-t1 is the propagation time of the surface wave between the two elevation points;

[0027] Where t2-t1 is obtained from equation 3:

[0028]

[0029] In Equation 3: t1 is the start time of surface wave propagation between two elevation points, t2 is the arrival time, (x1, y1) and (x2, y2) are the coordinates of two adjacent grid points, and v x v represents the surface wave velocity component in the direction parallel to the survey line. y This represents the surface wave velocity component perpendicular to the survey line.

[0030] To accurately represent surface elevation information, preferably, the surface elevation information in step (1) includes elevation point coordinates and mountain height. An irregular grid is formed using the elevation point coordinates, and the topographic gradient between adjacent grid points is calculated to establish a surface gradient model. The topographic gradient between adjacent grid points is obtained from formula 4.

[0031]

[0032] In Equation 4: h1 and h2 are the heights of the mountain between two adjacent grid points, and (x1, y1) and (x2, y2) are the coordinates of two adjacent grid points.

[0033] To improve the accuracy of identifying the dispersion region of surface waves, preferably, the establishment of the dispersion surface wave model in step (3) is based on the elastic wave equation in a two-dimensional spatial homogeneous medium, which is Equation 5:

[0034]

[0035] In the formula: u represents the displacement field, x and z are spatial coordinates, t is time, ρ is the density of the medium, λ and μ are Lamé parameters characterizing the elastic properties of the medium, and p(x,z,t) is the source.

[0036] To improve the matching degree between the dispersion surface wave model and actual seismic data, and to obtain surface wave information in the actual seismic data more accurately, preferably, there is a matching error in the matching of the dispersion surface wave model and the actual seismic data in step (4). The matching error is characterized by the L2 norm error, which is obtained from Equation 6:

[0037]

[0038] In the formula: f(lΔt) represents the actual seismic data; u(lΔt) represents the dispersion surface wave model; l represents the number of seismic data points in the comparison area; Δt represents the time span of a single data point. Attached Figure Description

[0039] Figure 1 This is a flowchart of the seismic surface wave attenuation processing according to Embodiment 1 of the present invention;

[0040] Figure 2 This is a surface elevation map of the Puguang exploration area in the seismic surface wave attenuation method of Embodiment 1 of the present invention;

[0041] Figure 3 This is a surface gradient map of the general exploration area in the seismic surface wave attenuation method of Embodiment 1 of the present invention;

[0042] Figure 4 This is a graph showing the relationship between wave dispersion intensity and topographic gradient in the seismic surface wave attenuation method of Embodiment 1 of the present invention;

[0043] Figure 5 This is a surface wave dispersion intensity diagram in the seismic surface wave attenuation method of Embodiment 1 of the present invention;

[0044] Figure 6 This is a full-area dispersion surface wave model diagram in the seismic surface wave attenuation method of Embodiment 1 of the present invention;

[0045] Figure 7 This is a model diagram of seismic data containing surface waves in the seismic surface wave attenuation method of Embodiment 1 of the present invention;

[0046] Figure 8 This is a diagram showing the attenuation effect of dispersion surface waves in the Puguang exploration area in the seismic surface wave attenuation method of Embodiment 1 of the present invention;

[0047] Figure 9 This is a comparison diagram of the surface wave attenuation effect of the Puguang exploration area dispersion surface wave attenuation method in the seismic surface wave attenuation method of Embodiment 1 of the present invention and the surface wave attenuation effect of the conventional surface wave attenuation method.

[0048] Figure 10 This is an image of the formation imaging effect after surface wave attenuation in the general exploration area and after surface wave attenuation without considering dispersion, followed by migration imaging processing, in the seismic surface wave attenuation method of Embodiment 1 of the present invention. Detailed Implementation

[0049] As cited in the background section, existing technologies cannot effectively attenuate dispersive surface wave interference. Therefore, this invention proposes a seismic surface wave attenuation method, comprising the following steps:

[0050] (1) Establish a surface gradient model based on the smoothed surface elevation information;

[0051] (2) Based on the relationship between the surface gradient model and surface wave dispersion, statistically analyze the surface wave dispersion characteristics;

[0052] (3) Establish a dispersion surface wave model based on the dispersion characteristics of surface waves;

[0053] (4) Match the dispersion surface wave model with the actual seismic data to obtain surface wave information in the actual seismic data;

[0054] (5) Surface waves are separated by subtraction based on surface wave information.

[0055] The technical concept of this invention is as follows: First, a surface gradient model of the general exploration area is established based on the smoothed surface elevation information to characterize changes in surface elevation information. Second, based on the relationship between the surface gradient model and surface wave dispersion, surface wave dispersion characteristics are statistically analyzed to accurately identify surface wave dispersion intensity and apparent velocity, and accurately locate the area where surface wave dispersion occurs. Next, a dispersive surface wave model is established and matched with actual seismic data. Seismic information with high consistency between actual seismic data and the surface wave model is sought to obtain surface wave information from the actual seismic data and achieve precise signal-to-noise separation. This is achieved by using a subtraction method to effectively attenuate surface waves while ensuring that effective reflection is not lost, thus achieving high-fidelity noise attenuation. The technical solution of this invention is particularly suitable for environments with undulating terrain and complex environments, solving the problem of the difficulty in attenuating dispersive surface waves and effectively improving the attenuation effect.

[0056] The following example uses actual 3D seismic data from a certain work area in Puguang to illustrate the specific implementation process of this method.

[0057] Specific embodiment 1 of the seismic surface wave attenuation method of the present invention:

[0058] In this embodiment, as Figure 1 As shown, the seismic surface wave attenuation method is as follows:

[0059] First, the surface elevation information is smoothed, that is,... Figure 2 The elevation information in the surface elevation map of the Puguang exploration area shown is smoothed to remove extremely subtle elevation changes, and information such as surface topographic dip angle, elevation point coordinates, and mountain height is obtained.

[0060] Secondly, a surface gradient model of the Puguang exploration area was established. This involved using elevation point coordinates to form an irregular grid, calculating the topographic gradient between adjacent grid points, and then constructing the surface gradient model of the Puguang exploration area, as shown below. Figure 3 The surface gradient map of the Puguang exploration area shown lays the foundation for statistical surface wave dispersion characteristics. The topographic gradient between two adjacent grid points is calculated according to Formula 4:

[0061]

[0062] In Equation 4: h1 and h2 are the heights of the mountain between two adjacent grid points, and (x1, y1) and (x2, y2) are the coordinates of two adjacent grid points.

[0063] Next, gradient decomposition is performed, and the surface wave dispersion intensity and apparent dispersion velocity are statistically analyzed. Based on the terrain gradient, the surface wave propagation time between two elevation points is calculated, as shown in Formula 3:

[0064]

[0065] In Equation 3: t1 is the start time of surface wave propagation between two elevation points, t2 is the arrival time, (x1, y1) and (x2, y2) are the coordinates of two adjacent grid points, and v x and v y These are the surface wave velocity components in two coordinate directions. The surface wave waveform lies within the time interval t1, t2, where the interval length is slightly longer than the surface wave waveform length.

[0066] Then, the surface wave dispersion intensity E is calculated according to Formula 1:

[0067]

[0068] In Equation 1: v x v represents the surface wave velocity component in the direction parallel to the survey line. y t1 represents the surface wave velocity component in the direction perpendicular to the survey line; t1 is the start time of surface wave propagation between two elevation points, and t2 is the arrival time.

[0069] The apparent velocity v0 of the surface wave is calculated using the terrain gradient and propagation time, as shown in Equation 2:

[0070]

[0071] In Equation 2: (x1,y1) and (x2,y2) are the coordinates of two adjacent grid points, and t2-t1 is the propagation time of the surface wave between the two elevation points;

[0072] The surface wave dispersion intensity and apparent dispersion velocity under different topographic gradients were statistically analyzed to obtain the following results: Figure 4 The diagram shown illustrates the relationship between surface wave dispersion intensity and topographic gradient, where the surface wave dispersion intensity diagram is as follows: Figure 5 As shown.

[0073] Then, combining surface wave dispersion intensity and apparent dispersion velocity data, a full-area dispersion surface wave model is established, such as... Figure 6 As shown, the elastic wave equation in a two-dimensional homogeneous medium is Equation 5:

[0074]

[0075] In the formula: u represents the displacement field, x and z are spatial coordinates, t is time, ρ is the density of the medium, λ and μ are Lamé parameters characterizing the elastic properties of the medium, and p(x,z,t) is the source.

[0076] Next, guided by the dispersion surface wave model, the dispersion surface wave model was matched with actual seismic data to obtain, as shown below. Figure 7 The diagram showing the seismic data model containing surface waves uses the L2 norm error to characterize the matching error between the actual seismic data and the dispersion surface wave model. This method identifies seismic information with high consistency between the actual seismic data and the dispersion surface wave model, accurately identifies surface wave interference within the actual seismic data, and obtains surface wave information from the actual seismic data. The L2 norm error is obtained from Equation 6:

[0077]

[0078] In Equation 6: f(lΔt) represents the actual seismic data; u(lΔt) represents the surface wave model; l represents the number of seismic data points in the comparison area; Δt represents the time span of a single data point.

[0079] Finally, based on the surface wave information obtained from actual seismic data, signal-to-noise separation is performed, that is, surface waves are separated by subtraction to achieve the purpose of attenuating dispersive surface waves, resulting in, as shown in the figure. Figure 8 The diagram shows the attenuation effect of dispersion surface waves in the Puguang exploration area.

[0080] Meanwhile, a comparison was made with conventional surface wave attenuation methods. Conventional surface wave attenuation methods, which are designed for surface wave noise without dispersion, attenuate it by setting a single surface wave apparent velocity, such as... Figure 9 , Figure 10 As shown, conventional surface wave attenuation methods often result in incomplete attenuation of dispersive surface waves, leading to geological defects. The seismic surface wave attenuation method provided in this invention first establishes a surface gradient model of the exploration area based on smoothed surface elevation information to characterize changes in surface elevation. Secondly, based on the relationship between the surface gradient model and surface wave dispersion, surface wave dispersion characteristics are statistically analyzed to accurately identify surface wave dispersion intensity and apparent velocity, thus accurately locating the area where surface wave dispersion occurs. Next, a dispersive surface wave model is established and matched with actual seismic data. Seismic information with high consistency between the actual seismic data and the surface wave model is identified, obtaining surface wave information from the actual seismic data and achieving precise signal-to-noise separation. This is achieved using a subtraction method, ensuring that effective reflection is not lost while effectively attenuating the dispersive surface waves in the actual seismic data. The attenuation process effectively protects seismic reflection information, resulting in thorough surface wave attenuation, effective reflection, and high-fidelity noise reduction.

[0081] The technical solution of this invention is particularly suitable for environments with undulating terrain and complex environments, solving the problem of the difficulty in attenuating dispersive surface waves and effectively improving the attenuation effect. This method overcomes the shortcomings of conventional surface wave attenuation methods, which cannot accurately identify the location of surface wave dispersion, the change in apparent velocity of dispersive surface waves, and the frequency characteristics of dispersive surface waves. It has important theoretical and practical significance for subsequent amplitude-preserving and fidelity-preserving processing research.

[0082] The above is a detailed description of the embodiments, but it is not intended to limit the technical solutions of the present invention. Those skilled in the art should understand that any modifications, partial substitutions, and variations can be made to the above embodiments within the scope of the present invention, and all such modifications and variations should be covered within the scope of the present invention.

Claims

1. A seismic surface wave attenuation method, characterized by, The method comprises the following steps: (1) establishing a surface gradient model according to the smoothed surface elevation information; (2) statistically analyzing the surface wave dispersion characteristics according to the change relationship between the surface gradient model and the surface wave dispersion; (3) establishing a dispersion surface wave model according to the surface wave dispersion characteristics; (4) matching the dispersion surface wave model with the actual seismic data to obtain the surface wave information in the actual seismic data; (5) separating the surface wave by subtracting method based on the surface wave information.

2. The seismic surface wave attenuation method of claim 1, wherein, In the step (2), the surface wave dispersion characteristics include dispersion intensity and apparent velocity, and the dispersion intensity is obtained by formula 1. In formula 1: v x is the parallel profile direction surface wave velocity component, v y is the perpendicular profile direction surface wave velocity component; t1 is the time when the surface wave waveform starts to propagate between two elevation points, and t2 is the time when it arrives.

3. The seismic surface wave attenuation method of claim 2, wherein, The apparent velocity is obtained by formula 2. In formula 2, (x1, y1) and (x2, y2) are the coordinates of adjacent two grid points, and t2-t1 is the surface wave waveform propagation time between two elevation points. Wherein t2-t1 is obtained by formula 3. In formula 3: t1 is the time when the wave form starts to propagate between two elevation points, t2 is the time when it arrives, (x1, y1) and (x2, y2) are the coordinates of two adjacent grid points, v x is the velocity component of the surface wave in the direction of the parallel survey line, y is the velocity component of the surface wave in the direction perpendicular to the survey line.

4. The seismic surface wave attenuation method of claim 1, wherein, In the step (1), the surface elevation information includes elevation point coordinates and mountain height, the elevation point coordinates are used to form irregular grids, the terrain gradient between adjacent two grid points is calculated to establish the surface gradient model, and the terrain gradient between adjacent two grid points is obtained by formula 4. In formula 4, h1 and h2 are the mountain heights of adjacent two grid points, and (x1, y1) and (x2, y2) are the coordinates of adjacent two grid points.

5. The seismic surface wave attenuation method of claim 1, wherein, In the step (3), the dispersion surface wave model is established according to the elastic wave equation in two-dimensional space uniform medium, and the elastic wave equation is formula 5. In formula 5, u represents displacement field, x and z are spatial coordinates, t is time, p is the density of medium, and p(x, z, t) is a seismic source.

6. The seismic surface wave attenuation method of claim 1, wherein, In the step (4), there is a matching error in matching the dispersion surface wave model with the actual seismic data, the matching error is characterized by L2 norm error, and the L2 norm error is obtained by formula 6. In formula 6, f(lΔt) is actual seismic data, u(lΔt) is dispersion surface wave model, l represents the number of seismic data in the comparison area, and Δt represents the time span of single data.

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