Method and terminal for obtaining far-field source wavelet using direct-arrival ocean earthquake wave data

Abstract

The present application relates to a method and terminal for obtaining far-field source wavelets using direct-arrival wave data of marine earthquakes. The original wavelet data of the source to be measured is obtained, and the original wavelet data is the direct-arrival wave data with source ghost waves in the offset seismic channel to be measured; the position information of the source to be measured is obtained, and the filter factor corresponding to the original wavelet data is selected according to the position information; the filter factor is a comprehensive factor of interference factors that reflects the difference between the wavelet data in the offset seismic channel to be measured and the known offset seismic channel; the interference factors include: offset, source depth in water, sinking depth of the detection point, sound wave velocity in water, and water surface reflection coefficient; the original wavelet data is corrected using the filter factor to obtain the far-field wavelet data of the source to be measured. The solution provided by the present application can obtain seismic wave data in the known offset seismic channel that can be regarded as far-field wavelet data through the correction of the filter factor. The obtained result is reliable and accurate, and the calculation is simple, the data is easy to obtain, and the survey cost is low.

Description

Technical Field

[0001] The present application relates to the field of marine seismic exploration technology, and in particular to a method and terminal for obtaining far-field source wavelets using direct marine seismic wave data. Background Art

[0002] In marine seismic exploration, earthquake source wavelets, often called "far-field wavelets," are essential input for seismic data signal processing. Accurate far-field wavelets facilitate the achievement of many signal processing objectives. However, accurate source wavelets are often difficult to obtain, making the extraction of far-field wavelet data and improving its estimation accuracy a key issue in seismic signal processing.

[0003] In the prior art, the main methods for obtaining far-field wavelets are:

[0004] First, direct on-site observation, but direct on-site observation of earthquake source wavelets is very costly;

[0005] Second, theoretical simulation is used. However, the method of theoretical simulation of wavelets is affected by factors such as theoretical model, source type, environmental parameters, and instrument equipment. There are large differences between the simulated wavelets and the actual wavelets.

[0006] 3. Extract from the reflection seismic data itself. However, since the reflection seismic data contains stratum information, the results of directly extracting far-field wavelet data will have large errors.

[0007] To address these issues, a prior art method for analyzing far-field wavelet data has been proposed. Based on bubble oscillation theory and combination theory, this method derives an analytical formula for calculating far-field wavelet data using direct waves in the frequency domain. However, this method has a complex theoretical basis and requires considering the combined effects of the source and receiving systems. Furthermore, obtaining far-field wavelet data requires solving a system of equations, making the algorithm complex and difficult to implement. Summary of the Invention

[0008] In order to overcome the problems existing in the related art, the present application provides a method for obtaining far-field source wavelets using direct ocean earthquake wave data, which can easily obtain far-field wavelet data from ocean earthquake wave data and reduce the cost of ocean earthquake surveys.

[0009] In a first aspect, the present application provides a method for obtaining far-field source wavelets using direct ocean earthquake wave data, comprising:

[0010] Acquire original wavelet data of the earthquake source to be measured, wherein the original wavelet data is direct wave data with earthquake source ghost waves in the earthquake trace at the offset to be measured;

[0011] Obtaining the location information of the earthquake source to be measured, and selecting a filter factor corresponding to the original wavelet data based on the location information; the filter factor is a comprehensive factor of interference factors that reflects the difference between the wavelet data in the earthquake trace with the offset to be measured and the earthquake trace with the known offset; the interference factors include: offset, depth of the earthquake source in water, depth of the receiver point, acoustic wave velocity in water, and water surface reflection coefficient;

[0012] The original wavelet data is corrected using the filter factor to obtain far-field wavelet data of the earthquake source to be measured.

[0013] In one embodiment, the obtaining of the position information of the earthquake source to be measured and the selecting of the filter factor corresponding to the original wavelet data according to the position information include:

[0014] The parameter conditions of the depth of the earthquake source in water, the speed of sound waves in water and the water surface reflection coefficient are set, the time difference effect between the direct wave and the earthquake source ghost wave is simulated, and the filtering factor corresponding to the parameter conditions is calculated.

[0015] In one embodiment, the simulation of the time difference effect between the direct wave and the source ghost wave to calculate the filter factor corresponding to the parameter condition includes:

[0016] According to the arrival time difference between the direct wave and the source ghost wave in the seismic trace of the offset distance to be measured, the first impulse response in the seismic trace of the offset distance to be measured is simulated;

[0017] According to the arrival time difference between the direct wave and the source ghost wave in the seismic trace with known offset, the second impulse response in the seismic trace with known offset is simulated;

[0018] The filter factor is determined based on the first impulse response and the second impulse response.

[0019] In one embodiment, it is characterized in that determining the filter factor based on the first impulse response and the second impulse response includes:

[0020] Converting the first impulse response and the second impulse response from the time domain to the frequency domain using Fourier transform;

[0021] The second impulse response converted to the frequency domain is divided by the first impulse response converted to the frequency domain to obtain a filter factor in the frequency domain;

[0022] Performing inverse Fourier transform on the filter factor in the frequency domain to obtain the filter factor.

[0023] In one embodiment, simulating the first impulse response in the seismic trace at the offset to be measured based on the arrival time difference between the direct wave and the source ghost wave in the seismic trace at the offset to be measured includes:

[0024] Construct the time-distance curve equation of the direct wave of the offset seismic trace to be measured;

[0025] Construct the time-distance curve equation of the source ghost wave of the offset seismic trace to be measured;

[0026] The first arrival time difference in the offset seismic trace to be measured is calculated based on the time-distance curve equation of the direct wave and the source ghost wave of the offset seismic trace to be measured;

[0027] Performing numerical simulation based on the first arrival time difference to obtain the first impulse response;

[0028] The method of simulating a second impulse response in a seismic trace with a known offset according to the arrival time difference between a direct wave and a source ghost wave in a seismic trace with a known offset includes:

[0029] Construct the time-distance curve equation of the direct wave of the seismic trace with known offset;

[0030] Construct the time-distance curve equation of the source ghost wave of the seismic trace with known offset distance;

[0031] The second arrival time difference in the known offset seismic trace is calculated based on the time-distance curve equation of the direct wave and the source ghost wave of the known offset seismic trace;

[0032] Numerical simulation is performed based on the second arrival time difference to obtain the second impulse response.

[0033] In one embodiment, the time-distance curve equation of the direct wave of the offset seismic trace to be measured is:

[0034]

[0035] Where t1 is the time it takes for the direct wave of the offset seismic trace to reach the detection point after it is sent out, d s1 is the first earthquake source sinking depth, d g is the depth of the receiver point, v is the speed of sound waves in water; offset1 is the offset distance to be measured, and the time-distance curve equation of the direct wave of the offset seismic trace to be measured takes the water surface reflection coefficient r as the boundary condition, r∈[-0.9,-1];

[0036] The time-distance curve equation of the source ghost wave of the offset seismic trace to be measured is:

[0037]

[0038] Where t1′ is the time it takes for the source ghost wave of the offset seismic trace to reach the detection point after it is emitted;

[0039] The step of calculating the first arrival time difference in the offset seismic trace to be measured based on the time-distance curve equation of the direct wave and the source ghost wave in the offset seismic trace to be measured comprises:

[0040] The first arrival time difference is calculated according to the following calculation formula:

[0041] Δt1=t1′-t1;

[0042] Wherein, Δt1 is the first arrival time difference.

[0043] The time-distance curve equation of the direct wave of the seismic trace with known offset is:

[0044]

[0045] Where t2 is the time it takes for the direct wave of the seismic trace with known offset to reach the detection point after it is sent out, d s2 is the depth of the second earthquake source, d g is the depth of the receiver point, v is the speed of sound waves in water; offset2 is the known offset distance, and the time-distance curve equation of the direct wave of the known offset seismic trace takes the water surface reflection coefficient r as the boundary condition, r∈[-0.9,-1];

[0046] The time-distance curve equation of the source ghost wave of the known offset seismic trace is:

[0047]

[0048] Where t2′ is the time it takes for the source ghost wave of a seismic trace with a known offset to arrive at the detection point;

[0049] The method of calculating the second time difference of arrival in the seismic trace with known offset based on the time distance curve equation of the direct wave and the ghost wave in the seismic trace with known offset includes:

[0050] The second arrival time difference is calculated according to the following calculation formula:

[0051] Δt2=t2′-t2;

[0052] Wherein, Δt2 is the second arrival time difference.

[0053] In one embodiment, after determining the filter factor based on the first impulse response and the second impulse response, the method further includes:

[0054] Calculating the matching accuracy between the seismic wave data obtained after correction by the filter factor and the actual far-field wavelet data;

[0055] Determine whether the matching accuracy reaches a preset matching threshold,

[0056] When the matching accuracy is lower than a preset matching threshold, adjusting the water surface reflection coefficient r and returning to the step of calculating the filter factor based on the time difference effect between the direct wave and the source ghost wave until the matching accuracy is higher than or equal to the preset matching threshold;

[0057] When the matching accuracy is higher than or equal to the preset matching threshold, the current filter factor is used as the corrected filter factor.

[0058] The technical solution provided by this application may have the following beneficial effects:

[0059] The direct wave is the waveform that propagates directly from the earthquake source to the receiving cable and is recorded. It only carries the velocity information of the shallowest layer and does not carry the information of the underground stratum interface. Therefore, the extraction of far-field wavelet data based on it can eliminate the interference of stratum information. When the earthquake source is located in the deep ocean, the incident angle of its reflected wave is extremely small and its offset distance is close to zero. Therefore, the direct wave emitted under deep ocean conditions has the shortest propagation path and often appears as the first arrival wave on most seismic traces. It is not interfered with by subsequent waves such as reflected waves, refracted waves, and surface waves. It is not only easy to identify, but its waveform can also be regarded as far-field wavelet data.

[0060] However, the seismic wave data in the seismic traces with known offsets are not easy to observe. The present application uses the seismic wave data in the seismic traces with non-zero offsets that are easy to observe as the basis, and corrects them through the filter factor. During the calculation process, it is only necessary to consider the time difference effect of the direct wave and the source ghost wave in the seismic traces with different offsets. Therefore, the seismic wave data in the seismic traces with known offsets obtained by correcting the filter factor eliminates the interference of subsequent waves such as reflected waves, refracted waves, and surface waves. That is, the seismic wave data in the seismic traces with known offsets that can be regarded as far-field wavelet data can be obtained through correction of the filter factor. The obtained results are reliable and accurate, the calculation is simple, the data is easy to obtain, and the survey cost is low.

[0061] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The above and other objects, features and advantages of the present application will become more apparent through a more detailed description of exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0063] Figure 1 1 is a flow chart of a method for obtaining far-field source wavelets using direct-arrival ocean earthquake wave data, as shown in an embodiment of the present application;

[0064] Figure 21 is a flow chart of a method for calculating a filter factor according to an embodiment of the present application;

[0065] Figure 3 1 is a flow chart of a method for correcting a filter factor according to an embodiment of the present application;

[0066] Figure 4 Schematic diagram of the locations of source ghost waves, virtual sources, and detection points shown in an embodiment of the present application;

[0067] Figure 5 Schematic diagram of the arrival time difference between the direct wave and the source ghost wave shown in the embodiment of the present application;

[0068] Figure 6 This is a waveform comparison diagram of the actual seismic data when converted to zero offset (offset 162m) shown in the embodiment of the present application;

[0069] Figure 7 This is a schematic diagram of data changes when an actual non-zero offset direct wave is converted to a zero offset direct wave (offset range: 162-387m) as shown in an embodiment of the present application. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Instead, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0071] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0072] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0073] Example 1

[0074] In existing technologies, direct on-site observation of far-field wavelet data is costly. Methods that use theoretical wavelet simulations are affected by factors such as the theoretical model, source type, environmental parameters, and instrumentation, resulting in significant discrepancies between the simulated and actual wavelets. Extracting far-field wavelet data from reflected seismic data itself results in significant errors due to the inclusion of stratigraphic information in reflected seismic data. Another analytical method for far-field wavelet data, based on bubble oscillation theory and combination theory, derives an analytical formula for calculating far-field wavelet data using direct waves in the frequency domain. However, this method has a complex theoretical basis, requiring consideration of the combined effects of the source and receiving systems. Furthermore, obtaining far-field wavelet data requires solving a system of equations, resulting in a complex algorithm and difficult implementation.

[0075] To address the above problems, an embodiment of the present application provides a method for obtaining far-field source wavelets using direct ocean earthquake wave data, which can easily obtain far-field wavelet data from ocean earthquake wave data and reduce the cost of ocean earthquake surveys.

[0076] See also Figure 4 , the reflected wave of the earthquake source energy on the water surface is called the earthquake source ghost wave, which can be regarded as a direct wave emitted from a virtual earthquake source (that is, the mirror image point of the earthquake source point on the water surface). S is the earthquake source, S' is the mirror image point of S, S' represents the virtual earthquake source, and G is the detection point. The actual direct wave of an ocean earthquake is a composite wave, which includes the earthquake source ghost wave and the direct wave. The time difference between the two is hereinafter referred to as "time difference", and the water surface reflection coefficient can be approximated to -1. The time difference is related to factors such as the offset distance, the depth of the earthquake source, the depth of the detection point, and the speed of sound waves propagating in water (such as Figure 4 As shown). When the offset is zero, the direct wave of the marine earthquake can be regarded as a far-field wavelet. However, in actual field acquisition, the offset is objectively present and cannot be avoided. The far-field wavelet is a special case of the direct wave of the marine earthquake (the direct wave at zero offset), which is essentially a directional wavelet with a large incident angle. The method of the present application uses the direct wave of a known offset to calculate the direct wave of a given offset. The technical solution of the embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0077] Figure 1 It is a flow chart of a method for obtaining far-field source wavelets using direct ocean earthquake wave data, as shown in an embodiment of the present application.

[0078] See also Figure 1 The method for obtaining far-field source wavelets using direct ocean earthquake wave data comprises:

[0079] 101. Obtaining original wavelet data of the earthquake source to be measured;

[0080] The original wavelet data of the earthquake source to be measured is obtained. The original wavelet data is the direct wave data with the earthquake source ghost wave in the earthquake trace with the offset distance to be measured.

[0081] In actual applications, seismic wave data from the offset seismic trace to be measured can be observed and the survey cost is low; however, the observation cost of seismic wave data from the zero-offset seismic trace is high and difficult.

[0082] 102. Acquire the position information of the earthquake source to be measured, and select a filter factor corresponding to the original wavelet data according to the position information;

[0083] The filtering factor is a comprehensive factor reflecting the interference factors of the difference between the wavelet data in the seismic trace with the measured offset and the seismic trace with the known offset; the interference factors include: offset, water depth of the earthquake source, the placement depth of the detection point, the water sound wave velocity and the water surface reflection coefficient.

[0084] In practical applications, different earthquake sources have different location information (such as depth in water, sound wave velocity in water, and water surface reflection coefficient), and the resulting filtering factors are also different. Therefore, it is necessary to determine the corresponding filtering factor based on the location information of the earthquake source to be measured.

[0085] The filter factors include at least two groups, and different filter factors correspond to different interference factors (at least one of the conditions such as underwater depth, underwater sound wave speed and water surface reflection coefficient is different).

[0086] 103. Use the filter factor to modify the original wavelet data to obtain far-field wavelet data of the earthquake source to be measured.

[0087] In the embodiment of the present application, the offset distance represents the horizontal distance between the earthquake source and the detection point; the known offset distance seismic trace is the propagation path of the seismic wave emitted by the earthquake source at an ocean depth greater than D. In actual application, the specific value of D can be selected according to actual conditions. The larger the value of D, the closer the calculated seismic wave data of the known offset distance seismic trace is to the actual far-field sub-wave data.

[0088] When the earthquake source is located deep in the ocean, the incident angle of its reflected wave is extremely small. Therefore, the offset distance of the seismic trace of the seismic wave generated by the earthquake source in the deep sea is approximately zero. That is, the direct wave emitted under deep ocean conditions has the shortest propagation path and often appears first as the first arrival wave on most seismic traces. It is not subject to interference from subsequent waves such as reflected waves, refracted waves, and surface waves. It is not only easy to identify, but its waveform can also be regarded as far-field wavelet data.

[0089] However, since the seismic wave data of the seismic channels corresponding to deep-sea earthquake sources are not easy to observe, it is often necessary to use the seismic wave data in the seismic channels corresponding to non-zero offset distances to approximate the far-field wavelet data, but this model often has large errors; or use the seismic wave data in the seismic channels corresponding to non-zero offset distances to directly extract and calculate the far-field wavelet data, which is computationally intensive and complex.

[0090] Therefore, based on the seismic wave data of the seismic trace corresponding to the non-zero offset distance that is easily observable, the filter factor is used to correct it and the seismic wave data of the seismic trace with a known offset distance is calculated, which can greatly reduce the difficulty and cost of the survey. Moreover, since the filter factor has been determined, the seismic wave data in the seismic trace with a known offset distance that can be regarded as far-field wavelet data can be obtained after correction using the filter factor. The calculation is simple and reliable.

[0091] Example 2

[0092] In the method for obtaining far-field source wavelets using direct ocean earthquake wave data as shown in the first embodiment, before the original wavelet data is corrected using the filter factor, the filter factor must be calculated based on the time difference effect between the direct wave and the source ghost wave.

[0093] In the embodiment of the present application, the parameter conditions of the depth of the earthquake source in water, the sinking depth of the detection point, the speed of sound waves in water and the water surface reflection coefficient are set by means of simulation, the time difference effect of the direct wave and the source ghost wave is simulated, and the filtering factor corresponding to the parameter conditions is calculated.

[0094] The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0095] Figure 2 It is a flowchart of a method for calculating a filter factor according to an embodiment of the present application.

[0096] See also Figure 2 , the calculation method of the filtering factor includes:

[0097] 201. According to the arrival time difference between the direct wave and the source ghost wave in the seismic trace at the offset distance to be measured, simulate and obtain the first impulse response in the seismic trace at the offset distance to be measured;

[0098] Exemplary:

[0099] Construct the time-distance curve equation of the direct wave of the offset seismic trace to be measured:

[0100]

[0101] Where t1 is the time it takes for the direct wave of the offset seismic trace to reach the detection point after it is sent out, d s1 is the first earthquake source sinking depth, d gis the depth of the receiver point, v is the speed of sound waves in water; offset1 is the offset to be measured, and the time-distance curve equation of the direct wave of the offset seismic trace to be measured takes the water surface reflection coefficient r as the boundary condition, r∈[-0.9,-1].

[0102] Construct the time-distance curve equation of the source ghost wave of the offset seismic trace to be measured:

[0103]

[0104] Wherein, t1′ is the time taken for the source ghost wave of the offset seismic trace to arrive at the detection point after it is emitted.

[0105] The first arrival time difference Δt1 in the offset seismic trace to be measured is calculated based on the time-distance curve equation of the direct wave of the offset seismic trace to be measured and the source ghost wave of the offset seismic trace to be measured:

[0106] Δt1=t1′-t1;

[0107] Numerical simulation is performed based on the first arrival time difference to obtain the first impulse response x1(t).

[0108] In the embodiment of the present application, the first source sinking depth d s1 Smaller than D.

[0109] 202. According to the arrival time difference between the direct wave and the source ghost wave in the seismic trace with known offset, the second impulse response in the seismic trace with known offset is simulated;

[0110] Exemplary:

[0111] Construct the time-distance curve equation of the direct wave of the seismic trace with known offset:

[0112]

[0113] Where t2 is the time it takes for the direct wave of the seismic trace with known offset to reach the detection point after it is sent out, d s2 is the depth of the second earthquake source, d g is the depth of the receiver point, v is the speed of sound waves in water; offset2 is the known offset distance, and the time-distance curve equation of the direct wave of the known offset seismic trace takes the water surface reflection coefficient r as the boundary condition, r∈[-0.9,-1].

[0114] Construct the time-distance curve equation of the source ghost wave of the seismic trace with known offset distance:

[0115]

[0116] Where t2′ is the time it takes for the source ghost wave of a seismic trace with a known offset to arrive at the detection point after it is emitted.

[0117] The second arrival time difference Δt2 in the known offset seismic trace is calculated based on the time-distance curve equation of the direct wave and the source ghost wave of the known offset seismic trace:

[0118] Δt2=t2′-t2;

[0119] Numerical simulation is performed based on the second arrival time difference to obtain the second impulse response x2(t).

[0120] In the embodiment of the present application, the second source sinking depth d s2 Greater than or equal to D.

[0121] It should be noted that the deeper the source is placed, the smaller the incident angle of the reflected wave from the source is, that is, the propagation path of the seismic wave emitted by the source is closer to the zero offset distance. Therefore, the second source placement depth d s2 The larger the value of , the stronger the calculated filter factor's ability to resist interference from subsequent waves such as reflected waves, refracted waves, and surface waves.

[0122] In the embodiment of the present application, the water surface reflection coefficient r is -1.

[0123] It should be noted that in actual applications, due to the influence of factors such as wind and waves, the sea surface during actual survey is uneven. Therefore, in addition to reflection, seismic waves will also be scattered on the rough sea surface. Only a part of the scattered wave field is coherently superimposed with the reflected wave field, resulting in the absolute value of the actual water surface reflection coefficient being less than 1. Therefore, in actual applications, the initial value of the water surface reflection coefficient can also be set to -1. After the filter factor is calculated, the water surface reflection coefficient is adjusted according to the correction effect of the filter factor to improve the accuracy of the filter factor correction result.

[0124] 203. Determine a filter factor based on the first impulse response and the second impulse response.

[0125] like Figure 5 As shown in the figure, based on the time-distance curve equation of the direct wave and the source ghost wave, the arrival time differences Δt1 and Δt2 of the direct wave and the source ghost wave at offset 1 and offset 2 are calculated. Based on these time differences, the direct wave impulse responses with the source ghost wave at offset 1 and offset 2 are simulated and recorded as x1(t) and x2(t), respectively. Through Fourier transform, the impulse responses x1(t) and x2(t) are transformed into the frequency domain X1(f) and X2(f), respectively. The filter factor can be obtained from either the time domain or the frequency domain, and the effect is similar. The calculation formula is as follows:

[0126] Frequency domain filter factor: δ(f) = X2(f) / X1(f).

[0127] ② Time domain filtering factor: δ(t) = x2(t) / x1(t).

[0128] The direct wave at offset 1 to be measured is y1(t), and the direct wave at offset 2 is y2(t). Through Fourier transform, y1(t) is transformed into the frequency domain Y1(f). The calculation formula for the direct wave y2(t) is as follows:

[0129] ① Apply the frequency domain filter factor: y2(t)=ifft[Y1(f)δ(f)].

[0130] ② Apply the time domain filter factor: y2(t) = y1(t)δ(t).

[0131] When offset2=0, y2(t) can be regarded as a far-field wavelet.

[0132] For ease of understanding, the present application embodiment provides a waveform comparison diagram of actual seismic data converted to zero offset (offset 162m), please refer to Figure 6 , where 6-(a) is the waveform of the direct arrival of the earthquake source ghost wave at an offset distance of 162 m, and 6-(b) is the waveform of the direct arrival of the earthquake source ghost wave at a zero offset distance.

[0133] In addition, the present embodiment also provides the data change process of converting the actual non-zero offset direct wave to the zero offset direct wave (offset range: 162-387m), please refer to Figure 7 , where 7-(a) is the original direct wave gather with source ghost waves, 7-(b) is the direct wave gather with source ghost waves after dynamic correction, 7-(c) is the direct wave gather with source ghost waves after spherical diffusion compensation, and 7-(d) is the direct wave gather with source ghost waves after conversion to zero offset.

[0134] In an embodiment of the present application, a method for calculating a filter factor based on the time difference effect between a direct wave and a source ghost wave is provided. The first pulse response of the original wavelet data in the seismic trace corresponding to the non-zero offset is numerically simulated by the arrival time difference of the direct wave and the source ghost wave in the seismic trace corresponding to the non-zero offset. The second pulse response in the seismic trace with a known offset is obtained with reference to the above numerical simulation method. Since the observed seismic wave data is in the time domain, in order to facilitate the separation of the wave field, it is necessary to convert the first pulse response and the second pulse response to the frequency domain through Fourier transform, divide the first pulse response and the second pulse response in the frequency domain, and calculate the deviation formed by the seismic wave data in the seismic trace corresponding to the non-zero offset and the seismic trace with a known offset, that is, the filter factor in the frequency domain. The filter factor in the frequency domain is converted to the time domain through inverse Fourier transform so that it can be directly used to process the observed seismic wave data in the time domain, thereby calculating the far-field wavelet data.

[0135] Example 3

[0136] Based on the calculation method of the filter factor in the second embodiment above, due to the influence of factors such as wind and waves, the sea surface during actual survey is uneven. Therefore, the actual water surface reflection coefficient is often not equal to the ideal value of -1, and its absolute value is often less than 1. To solve the above problem, the embodiment of the present application proposes a correction method for the filter factor.

[0137] The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0138] Figure 3 It is a flowchart of a method for correcting a filter factor according to an embodiment of the present application.

[0139] See also Figure 3 , the method for correcting the filter factor includes:

[0140] 301. Calculate the filter factor based on the time difference effect between the direct wave and the source ghost wave;

[0141] In the embodiment of the present application, the content of step 301 has been described in detail in embodiment 2 and will not be repeated here.

[0142] 302. Calculate the matching accuracy between the seismic wave data obtained after filter factor correction and the actual far-field wavelet data;

[0143] In an embodiment of the present application, the matching accuracy between seismic wave data and actual far-field wavelet data can be determined by a waveform matching algorithm or by calculating the similarity of the waveforms; wherein, the actual far-field wavelet data can be obtained by analyzing the relationship between the direct wave and the far-field wavelet based on bubble oscillation theory and combination theory, or by direct survey.

[0144] 303. Determine whether the matching accuracy reaches a preset matching threshold;

[0145] When the matching accuracy is lower than the preset matching threshold, execute step 304 and return to step 301;

[0146] When the matching accuracy is higher than or equal to the preset matching threshold, step 305 is executed.

[0147] In the embodiment of the present application, the preset matching threshold can be set or adjusted according to actual needs and is not limited here.

[0148] 304. Adjust the water surface reflection coefficient;

[0149] In the embodiment of the present application, since the absolute value of the actual water surface reflection coefficient is often less than 1, in step 304, the water surface reflection coefficient can be increased step by step on the basis of the initial value to obtain an updated water surface reflection coefficient; in the above adjustment process, the adjustment can be made with a fixed adjustment amplitude, for example, based on the initial value of the water surface reflection coefficient, it can be increased by 0.01 step by step.

[0150] It should be noted that the above description of adjusting the water surface reflection coefficient in step 304 is only an example in the embodiment of the present application and should not be regarded as the sole limitation of the present application. In actual application, step 304 can also be performed by gradually increasing by 0.05 or adjusting with a non-fixed adjustment range.

[0151] 305. Use the current filter factor as the corrected filter factor.

[0152] After the filter factor is calculated by the filter factor calculation method shown in Example 2, the embodiment of the present application adjusts the water surface reflection coefficient r through the matching results of the corrected seismic wave data and the actual far-field wavelet data to make it closer to the actual water surface reflection coefficient, thereby making the pulse response of the seismic waves in the seismic traces corresponding to the non-zero offset distance and the seismic traces with known offset distance closer to the actual one, and thus the calculated filter factor is more accurate.

[0153] An embodiment of the present application also includes a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, the method of obtaining far-field source sub-waves using direct wave data of marine earthquakes as described is implemented.

[0154] The scheme of the present application has been described in detail above with reference to the accompanying drawings. In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. Those skilled in the art should also be aware that the actions and modules involved in the description are not necessarily required for this application. In addition, it is understood that the steps in the method of the embodiment of the present application can be adjusted in sequence, merged and deleted according to actual needs, and the modules in the device of the embodiment of the present application can be merged, divided and deleted according to actual needs.

[0155] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0156] Alternatively, the present application can also be implemented as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) on which executable code (or computer program, or computer instruction code) is stored. When the executable code (or computer program, or computer instruction code) is executed by a processor of an electronic device (or electronic device, server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0157] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the application herein may be implemented as electronic hardware, computer software, or combinations of both.

[0158] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems and methods according to multiple embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a part of a module, program segment or code, and the part of the module, program segment or code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0159] The embodiments of the present application have been described above. The above description is illustrative and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or improvements to the technology in the market, or to enable other persons skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for obtaining far-field source wavelets using direct-arrival ocean earthquake wave data, characterized in that: include: Acquire original wavelet data of the earthquake source to be measured, wherein the original wavelet data is direct wave data with earthquake source ghost waves in the earthquake trace at the offset to be measured; Set the parameters of the source depth in water, the depth of the receiver, the speed of sound waves in water, and the water surface reflection coefficient, simulate the time difference effect between the direct wave and the source ghost wave, and calculate the filter factor corresponding to the parameter conditions; including: According to the arrival time difference between the direct wave and the source ghost wave in the seismic trace of the offset distance to be measured, the first impulse response in the seismic trace of the offset distance to be measured is simulated; According to the arrival time difference between the direct wave and the source ghost wave in the seismic trace with known offset, the second impulse response in the seismic trace with known offset is simulated; Determining the filter factor based on the first impulse response and the second impulse response; comprising: Converting the first impulse response and the second impulse response from the time domain to the frequency domain using Fourier transform; The second impulse response converted to the frequency domain is divided by the first impulse response converted to the frequency domain to obtain a filter factor in the frequency domain; Performing an inverse Fourier transform on the filter factor in the frequency domain to obtain the filter factor; Obtaining the location information of the earthquake source to be measured, and selecting a filter factor corresponding to the original wavelet data based on the location information; the filter factor is a comprehensive factor of interference factors that reflects the difference between the wavelet data in the earthquake trace with the offset to be measured and the earthquake trace with the known offset; the interference factors include: offset, depth of the earthquake source in water, depth of the receiver point, acoustic wave velocity in water, and water surface reflection coefficient; The original wavelet data is corrected using the filter factor to obtain far-field wavelet data of the earthquake source to be measured.

2. The method for obtaining far-field source wavelet using direct ocean earthquake wave data according to claim 1, characterized in that: The method of simulating a first impulse response in a seismic trace at the offset to be measured based on the arrival time difference between a direct wave and a source ghost wave in the seismic trace at the offset to be measured comprises: Construct the time-distance curve equation of the direct wave of the offset seismic trace to be measured; Construct the time-distance curve equation of the source ghost wave of the offset seismic trace to be measured; The first arrival time difference in the offset seismic trace to be measured is calculated based on the time-distance curve equation of the direct wave and the source ghost wave of the offset seismic trace to be measured; Numerical simulation is performed based on the first arrival time difference to obtain the first impulse response.

3. The method for obtaining far-field source wavelet using direct ocean earthquake wave data according to claim 1, characterized in that: The method of simulating a second impulse response in a seismic trace with a known offset according to the arrival time difference between a direct wave and a source ghost wave in a seismic trace with a known offset includes: Construct the time-distance curve equation of the direct wave of the seismic trace with known offset; Construct the time-distance curve equation of the source ghost wave of the seismic trace with known offset distance; The second arrival time difference in the known offset seismic trace is calculated based on the time-distance curve equation of the direct wave and the source ghost wave of the known offset seismic trace; Numerical simulation is performed based on the second arrival time difference to obtain the second impulse response.

4. The method for obtaining far-field source wavelets using direct ocean earthquake wave data according to claim 2, wherein: The time-distance curve equation of the direct wave of the offset seismic trace to be measured is: Where t1 is the time it takes for the direct wave of the offset seismic trace to reach the detection point after it is sent out, d s1 is the first earthquake source sinking depth, d g is the depth of the receiver point, v is the speed of sound waves in water; offset1 is the offset distance to be measured, and the time-distance curve equation of the direct wave of the offset seismic trace to be measured takes the water surface reflection coefficient r as the boundary condition, r∈[-0.9,-1]; The time-distance curve equation of the source ghost wave of the offset seismic trace to be measured is: Where t1′ is the time it takes for the source ghost wave of the offset seismic trace to reach the detection point after it is emitted; The step of calculating the first arrival time difference in the offset seismic trace to be measured based on the time-distance curve equation of the direct wave and the source ghost wave in the offset seismic trace to be measured comprises: The first arrival time difference is calculated according to the following calculation formula: △t1=t1′-t1; Wherein, Δt1 is the first arrival time difference.

5. The method for obtaining far-field source wavelet using direct ocean earthquake wave data according to claim 3, characterized in that: The time-distance curve equation of the direct wave of the seismic trace with known offset is: Where t2 is the time it takes for the direct wave of the seismic trace with known offset to reach the detection point after it is sent out, d s2 is the depth of the second earthquake source, d g is the depth of the receiver point, v is the speed of sound waves in water; offset2 is the known offset distance, and the time-distance curve equation of the direct wave of the known offset seismic trace takes the water surface reflection coefficient r as the boundary condition, r∈[-0.9,-1]; The time-distance curve equation of the source ghost wave of the known offset seismic trace is: Where t2′ is the time it takes for the source ghost wave of a seismic trace with a known offset to arrive at the detection point; The method of calculating the second arrival time difference in the known offset seismic trace based on the time-distance curve equation of the direct wave and the source ghost wave of the known offset seismic trace comprises: The second arrival time difference is calculated according to the following calculation formula: △t2=t2′-t2; Wherein, Δt2 is the second arrival time difference.

6. The method for obtaining far-field source wavelet using direct ocean earthquake wave data according to claim 1, characterized in that: After determining the filter factor based on the first impulse response and the second impulse response, the method further includes: Calculating the matching accuracy between the seismic wave data obtained after correction by the filter factor and the actual far-field wavelet data; Determine whether the matching accuracy reaches a preset matching threshold, When the matching accuracy is lower than a preset matching threshold, adjusting the water surface reflection coefficient r and returning to the step of calculating the filter factor based on the time difference effect between the direct wave and the source ghost wave until the matching accuracy is higher than or equal to the preset matching threshold; When the matching accuracy is higher than or equal to the preset matching threshold, the current filter factor is used as the corrected filter factor.

7. A terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for obtaining far-field source wavelets using direct-arrival ocean earthquake wave data as described in any one of claims 1 to 6 is implemented.

Images