A far-field wavelet acquisition method and device, electronic equipment and storage medium

Abstract

The application discloses a far-field wavelet acquisition method and device, electronic equipment and a storage medium, and relates to the field of geophysical exploration. The method comprises the following steps: acquiring corresponding frequency domain detection data according to near-field detection data of a near-field detector; acquiring an imaginary wavelet of each frequency sampling point according to distances between a sub-source and each near-field detector, distances between a virtual source and each near-field detector, and the frequency domain detection data of the near-field detector; and acquiring a far-field wavelet of a target far-field point at each frequency sampling point according to distances between the sub-source and the target far-field point, distances between the virtual source and the target far-field point, and the imaginary wavelet of each frequency sampling point. The technical scheme of the embodiment of the application not only realizes the calculation and acquisition of the far-field wavelet, improves the accuracy of the calculation result, but also reduces the time consumption of the calculation of the far-field wavelet and improves the calculation efficiency of the far-field wavelet.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration, and more particularly to a method, apparatus, electronic device, and storage medium for acquiring far-field wavelets. Background Technology

[0002] Far-field wavelets are wavelets formed by the propagation of seismic waves generated by the earthquake source over long distances. As an important component of seismic signals, they play a vital role in marine seismic exploration.

[0003] Currently, the most commonly used excitation source in marine seismic data acquisition is the air gun array (i.e., gun array). Due to the widespread use of combined air gun arrays, the seismic source in marine seismic exploration is no longer a point source. In existing technologies, the acquisition of far-field wavelets is usually carried out under still water conditions, using forward modeling to obtain theoretical wavelets, or through seismic data-driven methods to extract wavelets from seismic data, thereby completing the acquisition of far-field wavelets.

[0004] However, wavelets under still water conditions differ significantly from those in the ocean, failing to accurately reflect the actual wavelets in the ocean. Seismic data-driven methods often mix multiple seismic waves, resulting in poor wavelet extraction. Furthermore, their multi-track statistical approach also leads to significant differences in spatially varied wavelets, making it difficult to meet the requirements of practical track-by-track processing. Summary of the Invention

[0005] This invention provides a method, apparatus, electronic device, and storage medium for acquiring far-field wavelets, in order to solve the problem of low computational efficiency of far-field wavelets.

[0006] According to one aspect of the present invention, a method for acquiring far-field wavelet is provided, comprising:

[0007] Based on the near-field detection data of each near-field detector, obtain the corresponding frequency domain detection data;

[0008] Based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector, the hypothetical wavelet at each frequency sampling point is obtained.

[0009] Based on the distances between each sub-source of the gun array and the far-field point of the target, the distances between each virtual source of the gun array and the far-field point of the target, and the hypothetical wavelets at each frequency sampling point, the far-field wavelets of the target far-field point at each frequency sampling point are obtained.

[0010] The step of obtaining the hypothetical wavelet at each frequency sampling point based on the distance between each sub-source of the gun array and each near-field detector, the distance between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector includes: obtaining the hypothetical wavelet at each frequency sampling point through the conjugate gradient method based on the distance between each sub-source of the gun array and each near-field detector, the distance between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector.

[0011] The step of obtaining the far-field wavelet of the target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point includes: obtaining the coordinate information of the target far-field point based on the pre-configured depth, emission angle, and azimuth angle of the far-field point; obtaining the distances between each sub-source of the gun array and the target far-field point, and the distances between each near-virtual source of the gun array and the target far-field point based on the coordinate information of the target far-field point; and obtaining the far-field wavelet of the target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point.

[0012] The step of obtaining the far-field wavelet of the target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point further includes: obtaining the coordinate information of all target far-field points in three-dimensional space based on the depth, emission angle range and angle step size, and azimuth angle range and angle step size of the pre-configured far-field point element; obtaining the distances between each sub-source of the gun array and each target far-field point, and the distances between each virtual source of the gun array and each target far-field point based on the coordinate information of each target far-field point; and obtaining the far-field wavelet of each target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and each target far-field point, the distances between each virtual source of the gun array and each target far-field point, and the hypothetical wavelet of each frequency sampling point.

[0013] The process of obtaining hypothetical wavelets at each frequency sampling point based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector includes: obtaining the velocity difference between each sub-source and each near-field detector based on the water flow velocity, the mass and depth information of the sub-sources, and the mass and depth information of the near-field detectors; obtaining the distance between each sub-source and each near-field detector based on the position coordinates of each sub-source and each near-field detector, and the velocity difference between each sub-source and each near-field detector; and obtaining the distance between each virtual source and each near-field detector based on the position coordinates of each virtual source and each near-field detector, and the velocity difference between each virtual source and each near-field detector.

[0014] After acquiring the far-field wavelet of the target far-field point at each frequency sampling point, the method further includes: acquiring a matching waveform adjustment strategy based on the water flow velocity, the mass and depth information of the sub-source, and the mass and depth information of the near-field detector, and adjusting the waveform of the far-field wavelet of the target far-field point at each frequency sampling point according to the waveform adjustment strategy.

[0015] According to another aspect of the present invention, a far-field wavelet acquisition device is provided, comprising:

[0016] The frequency domain data acquisition module is used to acquire the corresponding frequency domain detection data based on the near-field detection data of each near-field detector;

[0017] The hypothetical wavelet acquisition module is used to acquire hypothetical wavelets at each frequency sampling point based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector.

[0018] The far-field wavelet acquisition module is used to acquire the far-field wavelet of the target far-field point at each frequency sampling point based on the distance between each sub-source of the gun array and the target far-field point, the distance between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point.

[0019] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0020] At least one processor; and

[0021] A memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the far-field wavelet acquisition method according to any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the far-field wavelet acquisition method according to any embodiment of the present invention.

[0024] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the far-field wavelet acquisition method described in any embodiment of the present invention.

[0025] The technical solution of this invention first obtains the hypothetical wavelet at each frequency sampling point based on the frequency domain detection data of the near-field detector and the coordinate information of the sub-source and the virtual source. Then, based on the coordinate information of the sub-source, the virtual source, and the target far-field point, as well as the hypothetical wavelet at each frequency sampling point, the far-field wavelet of the target far-field point at each frequency sampling point is obtained. This not only realizes the calculation and acquisition of the far-field wavelet and improves the accuracy of the calculation results, but also reduces the calculation time of the far-field wavelet, avoids the tedious process of interpolation calculation, and improves the calculation efficiency of the far-field wavelet.

[0026] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a flowchart of a far-field wavelet acquisition method provided in Embodiment 1 of the present invention;

[0029] Figure 2 This is a schematic diagram of the near-field detection data of the near-field detector provided in Embodiment 1 of the present invention;

[0030] Figure 3 This is a schematic diagram showing the positions of the sub-source and the virtual source according to Embodiment 1 of the present invention;

[0031] Figure 4 This is a flowchart of another far-field wavelet acquisition method provided in Embodiment 2 of the present invention;

[0032] Figure 5 It is a far-field wavelet of a target far-field point with a emission angle of 30 degrees, provided in Embodiment 2 of the present invention;

[0033] Figure 6 It is a far-field sub-wave of a target far-field point with a emission angle of 60 degrees, provided in Embodiment 2 of the present invention;

[0034] Figure 7 This is a flowchart of another far-field wavelet acquisition method provided in Embodiment 3 of the present invention;

[0035] Figure 8 This is a schematic diagram of a far-field wavelet acquisition device according to Embodiment 4 of the present invention;

[0036] Figure 9 This is a schematic diagram of the structure of an electronic device that implements the far-field wavelet acquisition method of this invention. Detailed Implementation

[0037] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0038] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] Example 1

[0040] Figure 1This is a flowchart of a far-field wavelet acquisition method provided in Embodiment 1 of the present invention. This embodiment is applicable to the case of calculating and acquiring a far-field wavelet based on near-field detection data from a near-field detector. This method can be executed by the far-field wavelet acquisition device in any embodiment of the present invention. The far-field wavelet acquisition device can be implemented in hardware and / or software, and can be configured in electronic devices such as servers. Figure 1 As shown, the method includes:

[0041] S101. Obtain the corresponding frequency domain detection data based on the near-field detection data of each near-field detector.

[0042] A detector is a device used to detect wave signals. In this embodiment of the invention, it is used to detect vibration signals emitted by a gun array. A gun array is an array of multiple air guns placed below the sea surface as a source of artificially induced seismic waves. Each point in the gun array is a sub-source, and each sub-source consists of one or more air guns clustered together. A near-field detector is a detector placed below the sea surface at a close distance to the source. The near-field detectors and sub-sources can be configured in a one-to-one matching relationship in terms of quantity and position. For example, the near-field detector is placed seven meters below the sea surface, while the sub-source is placed eight meters below the sea surface, directly below the corresponding near-field detector.

[0043] The near-field detection data of the near-field detector is represented in the time domain, that is, the time domain detection data, which is specifically represented by the following equation:

[0044] p i =(x i ,y i ,t i (h)) (Formula 1);

[0045] Where i is the near-field detector number, i = 1, 2, ..., m; m is the number of near-field detectors; x i ,y i Represent the x and y coordinates of the i-th near-field detector, respectively; t i (h) represents the travel time of the i-th near-field detector, t i (h) can be expressed by the following equation:

[0046] t i (h)=h*dt (Formula 2);

[0047] Where h represents the number of the time sampling point, h = 1, 2, ..., N; N is the number of time sampling points; dt is the sampling interval time, which can be pre-configured as needed, for example, it can be configured to 0.5 milliseconds, or 0.0005 seconds.

[0048] Perform a Fourier transform on the above time-domain data to obtain the matching frequency-domain data p. i =(x i ,y i ,f i (k)), f i (k) can be expressed by the following equation:

[0049] f i (k)=k*df (Formula 3);

[0050] Where k represents the number of the frequency sampling point, k = 1, 2, ..., M; M is the number of frequency sampling points; dt is the sampling interval frequency, which can be calculated by the following equation:

[0051]

[0052] like Figure 2 As shown, in a seismic source composed of 18 sub-gun arrays, each sub-gun array includes an air gun, while the near-field detector array consists of 18 near-field detectors. Figure 2 The data recorded includes near-field detection data from 18 near-field detectors.

[0053] S102. Based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector, obtain the hypothetical wavelet at each frequency sampling point.

[0054] After obtaining the position coordinates of each near-field detector and each sub-source based on the aforementioned near-field detection data, the distance r between each sub-source of the gun array and each near-field detector is determined. ij It can be obtained by calculating using the following equation:

[0055]

[0056] Where j is the sub-source number, j = 1, 2, ..., n; n is the number of sub-sources; x j ,y j ,z j Let x represent the x-coordinate, y-coordinate, and depth coordinates of the j-th sub-source, respectively; i ,y i ,z i Let x, y, and depth be the x, y, and depth coordinates of the i-th near-field detector, respectively.

[0057] like Figure 3As shown, the virtual source is the mirror image of the sub-sources about the sea surface. Based on the position coordinates of each sub-source, the position coordinates of the matching virtual source can be obtained. Therefore, the distance r between each virtual source in the gun array and each near-field detector is calculated. ij' g It can be obtained by calculating using the following equation:

[0058]

[0059] Where j' is the virtual source number, j' = 1, 2, ..., n; n is the number of virtual sources; x j' ,y j' ,z j' Let x represent the x-coordinate, y-coordinate, and depth coordinates of the j'-th virtual source, respectively. The x-coordinate of the virtual source is the same as that of the sub-source, the y-coordinate of the virtual source is the same as that of the sub-source, and the depth coordinates of the virtual source and the sub-source are opposites of each other. i ,y i ,z i Let x, y, and depth be the x, y, and depth coordinates of the i-th near-field detector, respectively.

[0060] For a near-field detector, the sampling frequency f k In other words, the hypothetical wavelet P is obtained by solving the following equation. i '(f k ):

[0061]

[0062] Where, r ij This represents the distance between the sub-source and the near-field detector, which can be calculated using Formula 5 above; r ij' g The distance between the virtual seismic source and the near-field detector can be calculated using Formula 6 above; v is the propagation speed of seismic waves in water, which can be pre-configured, for example, it can be configured to 1500 m / s; R is the reflection coefficient of the sea surface, which can also be pre-configured, for example, it can be configured to 1.0; k is the number of the frequency sampling point; P m (f k This means that the m-th near-field detector mentioned above operates at a sampling frequency f. k The frequency detection data below has been obtained by calculating using formulas one through four above.

[0063] By solving Formula 7 above, the hypothetical wavelet of each near-field detector at all frequency sampling points can be obtained. In the traditional technical solution, when calculating the desired wavelet under the time-domain detection data of each near-field detector, at non-integer sampling points, since there is no corresponding sampling data, it is necessary to use spline function or sinc function for interpolation calculation, and then substitute the predicted value of the interpolation calculation into the solution equation of the desired wavelet.

[0064] In this embodiment of the invention, under frequency domain detection data, the corresponding calculated value can be directly obtained at each frequency sampling point without the need to obtain the prediction result through interpolation or other calculation methods. Then, the actual calculation result (rather than the predicted calculation result) is substituted into the solution equation of the hypothetical wavelet to obtain the accurate hypothetical wavelet at each frequency sampling point. This not only greatly improves the accuracy of the expected wavelet calculation result, but also avoids the tedious process of interpolation calculation and improves the efficiency of obtaining the expected wavelet.

[0065] Optionally, in this embodiment of the invention, the step of obtaining the hypothetical wavelet at each frequency sampling point based on the distance between each sub-source of the gun array and each near-field detector, the distance between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector includes: obtaining the hypothetical wavelet at each frequency sampling point through the conjugate gradient method based on the distance between each sub-source of the gun array and each near-field detector, the distance between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector.

[0066] Specifically, the conjugate gradient method only needs to use the first derivative information to solve the linear equation system. It not only has the characteristics of step convergence and high stability, but also has a fast convergence speed and requires less intermediate storage. This not only improves the computational efficiency of the hypothetical wavelet, but also reduces the storage of temporary computation variables during the calculation process, thus reducing the occupation of storage space.

[0067] S103. Based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelets of each frequency sampling point, obtain the far-field wavelets of the target far-field point at each frequency sampling point.

[0068] Assuming the target far-field point's coordinates are (X, Y, Z), and its specific depth information is pre-set (e.g., the target far-field point is configured within a depth range of 3000-10000 meters, meaning the Z value is configured within this range); given that the coordinates of each sub-source of the seismic array have been obtained, the distance between each sub-source and the target far-field point is... It can be obtained by calculation using the following equation:

[0069]

[0070] Where j is the sub-source number, j = 1, 2, ..., n; n is the number of sub-sources; x j ,y j ,z j X, Y, and Z represent the x, y, and depth coordinates of the j-th earthquake source, respectively; X, Y, and Z represent the x, y, and depth coordinates of the far-field point of the target, respectively.

[0071] Similarly, given that the coordinates of each virtual source in the gun array have been obtained, the distance between each virtual source and the far-field point of the target is... It can be obtained by calculation using the following equation:

[0072]

[0073] Where j' is the virtual source number, j' = 1, 2, ..., n; n is the number of virtual sources; x j' ,y j' ,z j' X, Y, and Z represent the x, y, and depth coordinates of the j'th virtual source, respectively. The x and y coordinates of the virtual source are the same as those of the sub-source, the y coordinates of the virtual source are the same as those of the sub-source, and the depth coordinates of the virtual source and the sub-source are opposites of each other.

[0074] Therefore, based on the distances between each sub-source and the target far-field point... and the distances between each virtual seismic source and the far-field point of the target. and the expected wavelet P at each frequency sampling point i '(f k The far-field wavelet of the target far-field point at each frequency sampling point is obtained through the following equation. Since the number of near-field detectors, m, is equal to the number of sub-sources, n, the desired wavelet P can be... i '(f k ), i = 1, 2, ..., m, rewritten as P j '(f k ), j = 1, 2, ..., n; w represents the angular frequency, w = 2πf k .

[0075]

[0076] According to Formula 10, the far-field wavelet of the current frequency sampling point can be calculated. Then, by substituting all frequency sampling points into the formula, the far-field wavelet of the far-field point under all frequency sampling points can be obtained. After performing an inverse Fourier transform on the above far-field wavelet, the far-field wavelet in the time domain can be obtained.

[0077] Optionally, in this embodiment of the invention, the step of obtaining the far-field wavelet of the target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point includes: obtaining the coordinate information of the target far-field point based on the pre-configured depth, emission angle, and azimuth angle of the far-field point; obtaining the distances between each sub-source of the gun array and the target far-field point, and the distances between each near-virtual source of the gun array and the target far-field point based on the coordinate information of the target far-field point; and obtaining the far-field wavelet of the target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point.

[0078] Specifically, the position of the target's far-field point on the depth plane can be determined based on the emission angle θ and azimuth angle. The surface is divided into elements based on the pre-configured emission angle θ and azimuth angle. Given the specific numerical values ​​and the depth coordinate Z of the target's far-field point, calculate the x-coordinate X and y-coordinate Y of the target's far-field point:

[0079]

[0080] Then, based on the coordinate information of the target far-field point, the far-field wavelet of the target far-field point at each frequency sampling point can be obtained through Formulas 8 to 10 above. This greatly expands the acquisition range of the far-field wavelet and ensures the diversity of the far-field wavelet.

[0081] The technical solution of this invention first obtains the hypothetical wavelet at each frequency sampling point based on the frequency domain detection data of the near-field detector and the coordinate information of the sub-source and the virtual source. Then, based on the coordinate information of the sub-source, the virtual source, and the target far-field point, as well as the hypothetical wavelet at each frequency sampling point, the far-field wavelet of the target far-field point at each frequency sampling point is obtained. This not only realizes the calculation and acquisition of the far-field wavelet and improves the accuracy of the calculation results, but also reduces the calculation time of the far-field wavelet, avoids the tedious process of interpolation calculation, and improves the calculation efficiency of the far-field wavelet.

[0082] Example 2

[0083] Figure 4This is a flowchart of a far-field wavelet acquisition method provided in Embodiment 2 of the present invention. The relationship between this embodiment and the above embodiments is that, based on the angle range and angle step size of the emission angle and azimuth angle, a complete surface element division is performed on the depth plane where the target far-field point is located. Figure 4 As shown, the method includes:

[0084] S201. Based on the near-field detection data of each near-field detector, obtain the matching frequency domain detection data.

[0085] S202. Based on the distances between each sub-source and each near-field detector, the distances between each virtual source and each near-field detector, and the frequency domain detection data of each near-field detector, obtain the expected wavelet at each frequency sampling point.

[0086] S203. Based on the distances between each sub-source and the target far-field point, the distances between each virtual source and the target far-field point, and the expected wavelet of each frequency sampling point, obtain the far-field wavelet of the target far-field point at each frequency sampling point.

[0087] S204. Based on the pre-configured angle range and angle step size of the emission angle, as well as the angle range and angle step size of the azimuth angle, obtain the coordinate information of all target far-field points in three-dimensional space.

[0088] Corresponding angle ranges can be configured for the emission angle and azimuth angle, representing the minimum and maximum values ​​that the emission angle and azimuth angle can reach, respectively. For example, the angle ranges for both the emission angle and azimuth angle can be configured to be from 0 to 90 degrees. At the same time, corresponding step ranges can also be configured for the emission angle and azimuth angle, representing the specific angle change value of the emission angle and azimuth angle for each step. For example, the step size of the angle ranges for both the emission angle and azimuth angle can be configured to be 1 degree. In this way, a total of 8100 target far-field points related to the target far-field point in three-dimensional space can be obtained. According to the above formulas eleven and twelve, the coordinate information of all target far-field points can be calculated and obtained.

[0089] S205. Based on the coordinate information of each target far-field point, obtain the distance between each sub-source and each target far-field point, and the distance between each virtual source and each target far-field point.

[0090] By substituting the coordinates of the target far-field point into Formulas 8 and 9 above, the distances between each sub-source and each target far-field point, as well as the distances between each virtual source and each target far-field point, can be calculated.

[0091] S206. Based on the distance between each sub-source and each target far-field point, the distance between each virtual source and each target far-field point, and the expected wavelet of each frequency sampling point, obtain the far-field wavelet of each target far-field point at each frequency sampling point.

[0092] Substituting the calculated distances between each sub-source and each target far-field point, the distances between each virtual source and each target far-field point, and the expected wavelet at each frequency sampling point into Formula 10 above, the far-field wavelet at each target far-field point at each frequency sampling point can be calculated. This achieves the calculation and acquisition of all far-field wavelets in three-dimensional space, thereby greatly expanding the acquisition range of far-field wavelets and ensuring the diversity and integrity of far-field wavelets in three-dimensional space. Figure 5 As shown, it is the far-field wavelet of the target far-field point with a departure angle of 30 degrees; as Figure 6 As shown, it is the far-field sub-wave of the target far-field point with an emission angle of 60 degrees.

[0093] The technical solution of this invention first obtains the coordinate information of all target far-field points in three-dimensional space based on the pre-configured angle range and angle step size of the emission angle and the angle range and angle step size of the azimuth angle. Then, based on the coordinate information of each target far-field point, sub-source, and virtual source, and the expected wavelet of each frequency sampling point, the far-field wavelet of each target far-field point at each frequency sampling point is obtained. This achieves the calculation and acquisition of all far-field wavelets in three-dimensional space, thereby greatly expanding the acquisition range of far-field wavelets and ensuring the diversity and integrity of far-field wavelets in three-dimensional space.

[0094] Example 3

[0095] Figure 7 This is a flowchart of a far-field wavelet acquisition method provided in Embodiment 3 of the present invention. The relationship between this embodiment and the above embodiments is that the distance values ​​between the sub-source and the near-field detector, and between the virtual source and the near-field detector, are corrected based on the water flow velocity, the mass and depth information of the sub-source, and the mass and depth information of the near-field detector. Figure 7 As shown, the method includes:

[0096] S301. Obtain matching frequency domain detection data based on the near-field detection data of each near-field detector.

[0097] S302. Based on the water flow velocity, the mass and depth information of the sub-sources, and the mass and depth information of the near-field detectors, obtain the velocity difference between each sub-source and each near-field detector.

[0098] In the ocean, the seismic source and the geophone will shift positionally due to the water flow. Because the seismic source and the geophone have different masses and are located at different depths, they will move at different speeds, resulting in different positional shifts and relative deviations. Different water flow speeds will also lead to different relative shifts. Since the sub-seismic sources have the same mass and are located at the same depth, and the geophones also have the same mass and are located at the same depth, the velocity difference between each sub-seismic source and each near-field geophone is the same.

[0099] Based on the water flow velocity, the mass and depth information of the sub-source, and the mass and depth information of the near-field detector, the matching velocity difference can be obtained by querying the difference mapping table. The difference mapping table is pre-configured based on empirical or experimental values ​​and records the velocity difference between the sub-source and the detector under different scenario parameters.

[0100] S303. Based on the position coordinates of each sub-source and each near-field detector, and the velocity difference between each sub-source and each near-field detector, obtain the distance between each sub-source and each near-field detector.

[0101] The distance r between each sub-source and each near-field detector ij Specifically, it can be calculated using the following equation:

[0102]

[0103] Where j is the sub-source number, j = 1, 2, ..., n; n is the number of sub-sources; v x ,v y ,v z These represent the velocity differences between the sub-source and the near-field detector in the horizontal, vertical, and depth directions, respectively; t h Indicates when traveling.

[0104] Similarly, the distance r between each virtual source and each near-field detector ij' g Specifically, it can be calculated using the following equation:

[0105]

[0106] Where j' is the virtual source number, j' = 1, 2, ..., n; n is the number of virtual sources; v x' ,v y' ,v z'These represent the velocity differences between the virtual source and the near-field detector in the horizontal, vertical, and depth directions, respectively. Since the virtual source is the mirror image of the sub-source, the velocity difference between the sub-source and the near-field detector is equal to the velocity difference between the virtual source and the near-field detector, i.e., v0. x =v x' ,v y =v y' ,v z =v z' .

[0107] S304. Based on the position coordinates of each virtual source and each near-field detector, as well as the velocity difference between each virtual source and each near-field detector, obtain the distance between each virtual source and each near-field detector.

[0108] S305. Based on the distances between each sub-source and each near-field detector, the distances between each virtual source and each near-field detector, and the frequency domain detection data of each near-field detector, obtain the expected wavelet at each frequency sampling point.

[0109] S306. Based on the distances between each sub-source and the target far-field point, the distances between each virtual source and the target far-field point, and the expected wavelet of each frequency sampling point, obtain the far-field wavelet of the target far-field point at each frequency sampling point.

[0110] Optionally, in this embodiment of the invention, after obtaining the far-field wavelet of the target far-field point at each frequency sampling point, the method further includes: obtaining a matching waveform adjustment strategy based on the water flow velocity, the mass and depth information of the sub-source, and the mass and depth information of the near-field detector, and adjusting the waveform of the far-field wavelet of the target far-field point at each frequency sampling point according to the waveform adjustment strategy.

[0111] Specifically, after calculating and obtaining the far-field wavelet of the target far-field point at various frequency sampling points, the matching waveform adjustment strategy can be obtained by querying the strategy mapping table based on the water flow velocity, the mass and depth information of the sub-source, and the mass and depth information of the near-field detector. The strategy mapping table records the waveform adjustment strategy of the far-field wavelet under different scene parameters. This reduces the computational complexity while ensuring the acquisition of accurate far-field wavelets and improving the computational efficiency of far-field wavelets.

[0112] The technical solution of this invention first obtains the velocity difference between each sub-source and each near-field detector based on the water flow velocity, the mass and depth information of the sub-sources, and the mass and depth information of the near-field detectors; then, based on the position coordinates of each sub-source and each near-field detector, and the velocity difference between each sub-source and each near-field detector, the distance between each sub-source and each near-field detector is obtained; thus, the actual distance between the sub-sources and the near-field detectors is obtained based on environmental factors, thereby improving the accuracy of the far-field wavelet calculation results.

[0113] Example 4

[0114] Figure 8 This is a structural block diagram of a far-field wavelet acquisition device provided in Embodiment 4 of the present invention. The device specifically includes:

[0115] The frequency domain data acquisition module 401 is used to acquire the corresponding frequency domain detection data based on the near-field detection data of each near-field detector;

[0116] The hypothetical wavelet acquisition module 402 is used to acquire the hypothetical wavelet at each frequency sampling point based on the distance between each sub-source of the gun array and each near-field detector, the distance between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector.

[0117] The far-field wavelet acquisition module 403 is used to acquire the far-field wavelet of the target far-field point at each frequency sampling point based on the distance between each sub-source of the gun array and the target far-field point, the distance between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point.

[0118] The technical solution of this invention first obtains the hypothetical wavelet at each frequency sampling point based on the frequency domain detection data of the near-field detector and the coordinate information of the sub-source and the virtual source. Then, based on the coordinate information of the sub-source, the virtual source, and the target far-field point, as well as the hypothetical wavelet at each frequency sampling point, the far-field wavelet of the target far-field point at each frequency sampling point is obtained. This not only realizes the calculation and acquisition of the far-field wavelet and improves the accuracy of the calculation results, but also reduces the calculation time of the far-field wavelet, avoids the tedious process of interpolation calculation, and improves the calculation efficiency of the far-field wavelet.

[0119] Optionally, the hypothetical wavelet acquisition module 402 is specifically used to acquire the hypothetical wavelet at each frequency sampling point through the conjugate gradient method based on the distance between each sub-source of the gun array and each near-field detector, the distance between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector.

[0120] Optionally, the far-field wavelet acquisition module 403 is specifically used to acquire the coordinate information of the target far-field point based on the pre-configured depth, emission angle, and azimuth angle of the far-field point; based on the coordinate information of the target far-field point, acquire the distance between each sub-source of the gun array and the target far-field point, and the distance between each near-virtual source of the gun array and the target far-field point; based on the distance between each sub-source of the gun array and the target far-field point, the distance between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point, acquire the far-field wavelet of the target far-field point at each frequency sampling point.

[0121] Optionally, the far-field wavelet acquisition module 403 is specifically used to acquire the coordinate information of all target far-field points in three-dimensional space based on the pre-configured depth, emission angle angle range and angle step size of the far-field points, and azimuth angle range and angle step size; based on the coordinate information of each target far-field point, acquire the distance between each sub-source of the gun array and each target far-field point, and the distance between each virtual source of the gun array and each target far-field point; based on the distance between each sub-source of the gun array and each target far-field point, the distance between each virtual source of the gun array and each target far-field point, and the hypothetical wavelet of each frequency sampling point, acquire the far-field wavelet of each target far-field point at each frequency sampling point.

[0122] Optionally, the hypothetical wavelet acquisition module 402 is specifically used to acquire the velocity difference between each sub-source and each near-field geophone based on the water flow velocity, the mass and depth information of the sub-sources, and the mass and depth information of the near-field geophones; to acquire the distance between each sub-source and each near-field geophone based on the position coordinates of each sub-source and each near-field geophone, as well as the velocity difference between each sub-source and each near-field geophone; and to acquire the distance between each virtual source and each near-field geophone based on the position coordinates of each virtual source and each near-field geophone, as well as the velocity difference between each virtual source and each near-field geophone.

[0123] Optionally, the far-field wavelet acquisition device is further configured to acquire a matching waveform adjustment strategy based on the water flow velocity, the mass and depth information of the sub-source, and the mass and depth information of the near-field detector, and to adjust the waveform of the far-field wavelet of the target far-field point at each frequency sampling point according to the waveform adjustment strategy.

[0124] The above-described apparatus can execute the far-field wavelet acquisition method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method. Technical details not described in detail in this embodiment can be found in the far-field wavelet acquisition method provided in any embodiment of the present invention.

[0125] Example 5

[0126] Figure 9 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, electronic devices, blade electronic devices, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0127] like Figure 9 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0128] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0129] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as far-field wavelet acquisition methods.

[0130] In some embodiments, the far-field wavelet acquisition method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on a heterogeneous hardware accelerator via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by a processor, one or more steps of the far-field wavelet acquisition method described above may be performed. Alternatively, in other embodiments, the processor may be configured to perform the far-field wavelet acquisition method by any other suitable means (e.g., by means of firmware).

[0131] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0132] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or electronic device.

[0133] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0134] To provide user interaction, the systems and techniques described herein can be implemented on a heterogeneous hardware accelerator, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the heterogeneous hardware accelerator. Other types of devices can also be used to provide user interaction; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or haptic feedback); and input from the user can be received in any form (including sound input, voice input, or haptic input).

[0135] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data electronic devices), or computing systems that include middleware components (e.g., application electronic devices), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0136] A computing system can include clients and electronic devices. Clients and electronic devices are generally geographically separated and typically interact via communication networks. The client-electronic device relationship is created by computer programs running on the respective computers and establishing a client-electronic device relationship between them. Electronic devices can be cloud electronic devices, also known as cloud computing electronic devices or cloud servers, which are hosting products within the cloud computing service ecosystem. These address the shortcomings of traditional physical hosting and VPS services, such as high management difficulty and weak business scalability.

[0137] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0138] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for obtaining a far-field wavelet, characterized by, include: Based on the near-field detection data of each near-field detector, obtain the corresponding frequency domain detection data; Based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector, the hypothetical wavelet at each frequency sampling point is obtained. Based on the distances between each sub-source of the gun array and the far-field point of the target, the distances between each virtual source of the gun array and the far-field point of the target, and the hypothetical wavelets at each frequency sampling point, the far-field wavelets of the target far-field point at each frequency sampling point are obtained.

2. The method of claim 1, wherein, The process of obtaining the hypothetical wavelet at each frequency sampling point based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector includes: Based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector, the hypothetical wavelet at each frequency sampling point is obtained through the conjugate gradient method.

3. The method of claim 1, wherein, The step of obtaining the far-field wavelet of the target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet at each frequency sampling point includes: Based on the pre-configured depth, emission angle, and azimuth of the far-field point, obtain the coordinate information of the target's far-field point; Based on the coordinate information of the target far-field point, the distances between each sub-source of the gun array and the target far-field point, as well as the distances between each near-virtual source of the gun array and the target far-field point, are obtained. Based on the distances between each sub-source of the gun array and the far-field point of the target, the distances between each virtual source of the gun array and the far-field point of the target, and the hypothetical wavelets at each frequency sampling point, the far-field wavelets of the target far-field point at each frequency sampling point are obtained.

4. The method of claim 1, wherein, The step of obtaining the far-field wavelet of the target far-field point at each frequency sampling point based on the distances between each sub-source of the gun array and the target far-field point, the distances between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet at each frequency sampling point further includes: Based on the pre-configured depth of the far-field point, the angle range and angle step of the emission angle, and the angle range and angle step of the azimuth angle, obtain the coordinate information of all target far-field points in three-dimensional space. Based on the coordinate information of each target far-field point, the distance between each sub-source of the gun array and each target far-field point, as well as the distance between each virtual source of the gun array and each target far-field point are obtained. Based on the distances between each sub-source of the gun array and each target far-field point, the distances between each virtual source of the gun array and each target far-field point, and the hypothetical wavelets at each frequency sampling point, the far-field wavelets of each target far-field point at each frequency sampling point are obtained.

5. The method of claim 1, wherein, The process of obtaining the hypothetical wavelet at each frequency sampling point based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector includes: Based on the water flow velocity, the mass and depth information of the sub-sources, and the mass and depth information of the near-field detectors, the velocity difference between each sub-source and each near-field detector is obtained. Based on the position coordinates of each sub-source and each near-field detector, as well as the velocity difference between each sub-source and each near-field detector, the distance between each sub-source and each near-field detector is obtained. Based on the position coordinates of each virtual source and each near-field detector, as well as the velocity difference between each virtual source and each near-field detector, the distance between each virtual source and each near-field detector is obtained.

6. The method of claim 1, wherein, After obtaining the far-field wavelet of the target far-field point at each frequency sampling point, the method further includes: Based on the water flow velocity, the mass and depth information of the sub-source, and the mass and depth information of the near-field detector, a matching waveform adjustment strategy is obtained, and the waveform of the far-field sub-wave at each frequency sampling point of the target far-field point is adjusted according to the waveform adjustment strategy.

7. A far-field wavelet acquisition apparatus, characterized by, include: The frequency domain data acquisition module is used to acquire the corresponding frequency domain detection data based on the near-field detection data of each near-field detector; The hypothetical wavelet acquisition module is used to acquire hypothetical wavelets at each frequency sampling point based on the distances between each sub-source of the gun array and each near-field detector, the distances between each virtual source of the gun array and each near-field detector, and the frequency domain detection data of each near-field detector. The far-field wavelet acquisition module is used to acquire the far-field wavelet of the target far-field point at each frequency sampling point based on the distance between each sub-source of the gun array and the target far-field point, the distance between each virtual source of the gun array and the target far-field point, and the hypothetical wavelet of each frequency sampling point.

8. An electronic device, comprising: The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the far-field wavelet acquisition method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the far-field wavelet acquisition method according to any one of claims 1-6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the far-field wavelet acquisition method according to any one of claims 1-6.

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