A Method and System for Correcting Moving Internal Waves Based on Seawater Acoustic Imaging

Abstract

This invention provides a method and system for correcting moving internal waves based on seawater acoustic imaging, relating to the field of seismic oceanography. The method includes: Step S1: acquiring raw seismic exploration data of internal waves in the water body; Step S2: obtaining received signals through simulation calculations using the raw data, and performing moving internal wave acoustic imaging of the water body using the received signals; Step S3: extracting characteristic parameters of internal waves in the water; Step S4: correcting the moving internal wave acoustic imaging of the water body based on the characteristic parameters. This invention enables the acquisition of the wave velocity of internal wave groups over long distances using high-sensitivity medium-resolution optical images, correcting the moving internal wave sea acoustic imaging method, and extracting true characteristic information such as the wavelength, width, and amplitude of internal waves.

Description

Technical Field

[0001] This invention relates to the field of seismic oceanography, specifically to a method for extracting characteristic parameters of moving internal waves in seismic reflection exploration and correcting internal wave imaging, and more particularly to a method and system for correcting moving internal waves based on seawater acoustic imaging. Background Technology

[0002] The technical method involved in this invention is based on seismic oceanography theory. Holbrook, in processing seismic exploration data from seawater areas exhibiting marine dynamics, observed superimposed reflection wave profiles of seawater mass structures, and further inverted these profiles to obtain the spatial distribution of seawater temperature and density. The nonlinear resonance of internal waves results in large amplitudes perpendicular to the sea surface. However, when using seismic reflection technology to monitor time-varying marine dynamic processes such as internal waves, the difference between the wave velocity of internal waves and the travel speed of the experimental exploration vessel causes image shifts in the seismic imaging profile, similar to the Doppler effect. This leads to errors in extracting internal wave characteristic parameters from the phase axis of the seawater imaging profile. Furthermore, seismic images are instantaneous, and existing seismic imaging procedures and methods are not conducive to observing the motion of solitary internal waves. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a method and system for correcting moving internal waves based on seawater acoustic imaging.

[0004] According to the present invention, a moving internal wave correction method and system based on seawater acoustic imaging is provided, the scheme of which is as follows:

[0005] In a first aspect, a moving internal wave correction method based on seawater acoustic imaging is provided, the method comprising:

[0006] Step S1: Obtain raw seismic exploration data of water body waves;

[0007] Step S2: Obtain the received signal through simulation calculation using the original data, and perform moving internal wave acoustic imaging of the water body using the received signal;

[0008] Step S3: Extract the characteristic parameters of internal waves in the water;

[0009] Step S4: Correct the moving internal wave water acoustic imaging according to the characteristic parameters.

[0010] Preferably, step S1 includes:

[0011] The soliton internal wave velocity and characteristic width of the two-layer seawater model are expressed as follows:

[0012]

[0013]

[0014] Where h1 and h2 are the depths of the two seawater layers, Δρ is the change in seawater density, η0 is the vertical displacement of the soliton internal wave, and g is the gravitational acceleration; the spatial sound velocity distribution of the soliton internal wave group is simulated based on the wave velocity and characteristic width of the soliton internal wave.

[0015] Preferably, step S2 includes:

[0016] Step S2.1: Remove the influence of direct waves with a sound speed of 1480m / s;

[0017] Step S2.2: Referring to the seismic reflection wave method in seismic exploration technology, the acquired received signal is subjected to pre-stack time migration, the time domain waveform of the received signal at the common reflection location is extracted and accumulated, and then filtered after being sorted according to the location of the common reflection point;

[0018] Step S2.3: Finally, obtain the acoustic imaging results of the water body within the soliton's internal wave group structure.

[0019] Preferably, step S3 includes:

[0020] Step S3.1: Using image edge detection, extract similar in-phase axis structures in the acoustic imaging profile of the water body;

[0021] Step S3.2: Apply median filtering to the acoustic imaging profile of the water body using a 5×1 grid;

[0022] Step S3.3: The Sobel operator is used to further enhance the edges. The threshold for edge extraction is set as T' = 1.8·std(T) + mean(T), where T is the time-domain waveform of the original imaging profile. Discontinuous noise and abnormal false edge components are removed to obtain the phase axis of the water acoustic imaging profile of the soliton inner wave group. Relevant parameters, including the vertical displacement and characteristic width of the inner wave, are extracted from the phase axis.

[0023] Preferably, step S4 includes: during the extraction of the in-phase axis using the imaging profile, a velocity difference between the wave velocity of the internal wave and the travel speed of the exploration vessel will produce a Doppler-like effect; a formula is used to correct the characteristic width of the internal wave in the horizontal direction:

[0024]

[0025] Wherein, the horizontal speed of the ship is V ship ;

[0026] To extract accurate internal wave characteristic parameter information from the phase axis, an algorithm for common reflection point compensation is proposed during water acoustic imaging. The reordered common reflection point positions are as follows:

[0027]

[0028] Where, d T d represents the time interval for the air gun to fire its signal. offset denoted as , where is the distance from the air gun to the receiving array element, and n is the position number of the transmitted signal;

[0029] Using the corrected CMP coordinates, a corrected water body imaging profile is obtained, and relevant parameters, including the true internal wave vertical displacement and characteristic width, are extracted from the phase axis.

[0030] Secondly, a moving internal wave correction system based on seawater acoustic imaging is provided, the system comprising:

[0031] Module M1: Acquire raw seismic exploration data of water bodies;

[0032] Module M2: Obtains the received signal through simulation calculations using the original data, and performs acoustic imaging of the moving internal wave water body using the received signal;

[0033] Module M3: Extracts characteristic parameters of internal waves in water;

[0034] Module M4: Corrects the moving internal wave water acoustic imaging based on the characteristic parameters.

[0035] Preferably, the module M1 includes:

[0036] The soliton internal wave velocity and characteristic width of the two-layer seawater model are expressed as follows:

[0037]

[0038]

[0039] Where h1 and h2 are the depths of the two seawater layers, Δρ is the change in seawater density, η0 is the vertical displacement of the soliton internal wave, and g is the gravitational acceleration; the spatial sound velocity distribution of the soliton internal wave group is simulated based on the wave velocity and characteristic width of the soliton internal wave.

[0040] Preferably, the module M2 includes:

[0041] Module M2.1: Removes the influence of direct waves with a sound velocity of 1480m / s;

[0042] Module M2.2: Referring to the seismic reflection wave method in seismic exploration technology, the acquired received signal is subjected to pre-stack time migration, the time domain waveform of the received signal at the common reflection location is extracted and accumulated, and then filtered after being sorted according to the location of the common reflection point;

[0043] Module M2.3: Finally, obtain the acoustic imaging results of the water body within the soliton's internal wave group structure.

[0044] Preferably, the module M3 includes:

[0045] Module M3.1: Utilizes image edge detection to extract similar undulating in-phase axis structures in the acoustic imaging profile of water bodies;

[0046] Module M3.2: Median filtering of acoustic imaging profiles of water bodies using a 5×1 grid;

[0047] Module M3.3: The Sobel operator is used to further enhance the edges. The threshold for edge extraction is set as T' = 1.8·std(T) + mean(T), where T is the time-domain waveform of the original imaging profile. Discontinuous noise and abnormal false edge components are removed to obtain the phase axis of the water acoustic imaging profile of the soliton inner wave group. Relevant parameters, including the vertical displacement and characteristic width of the inner wave, are extracted from the phase axis.

[0048] Preferably, module M4 includes: during the extraction of the in-phase axis using imaging profiles, a velocity difference between the wave velocity of the internal wave and the travel speed of the exploration vessel will produce a Doppler-like effect; a formula is used to correct the characteristic width of the internal wave in the horizontal direction:

[0049]

[0050] Wherein, the horizontal speed of the ship is V ship ;

[0051] To extract accurate internal wave characteristic parameter information from the phase axis, an algorithm for common reflection point compensation is proposed during water acoustic imaging. The reordered common reflection point positions are as follows:

[0052]

[0053] Where, d T d represents the time interval for the air gun to fire its signal. offset denoted as , where is the distance from the air gun to the receiving array element, and n is the position number of the transmitted signal;

[0054] Using the corrected CMP coordinates, a corrected water body imaging profile is obtained, and relevant parameters, including the true internal wave vertical displacement and characteristic width, are extracted from the phase axis.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] This invention utilizes the finite-difference time-domain method to simulate the signal form received after the air gun's emitted signal passes through moving internal waves in the water body. It employs a modified seismic reflection imaging processing method to form a water body seismic imaging profile that eliminates the influence of internal wave velocity. This allows the acoustic imaging of seawater, which involves rapidly moving dynamic processes such as internal waves, to no longer be constrained by the speed of movement of ocean dynamic phenomena, thus achieving the correction of the acquisition of internal wave characteristic parameters.

[0057] Other beneficial effects of the present invention will be explained in detail through the introduction of specific technical features and technical solutions in specific embodiments. Those skilled in the art should be able to understand the beneficial technical effects brought about by these technical features and technical solutions through the introduction of these technical features and technical solutions. Attached Figure Description

[0058] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0059] Figure 1 This is an overall flowchart of the present invention;

[0060] Figure 2 This is a schematic diagram showing the direction of movement of the internal waves and the direction of navigation for exploration.

[0061] Figure 3 This is a schematic diagram of co-point compensation.

[0062] Figure 4 This represents the instantaneous vertical displacement of the wave group within the soliton;

[0063] Figure 5 The spatial distribution of seawater sound velocity for soliton internal wave group 1;

[0064] Figure 6 Received signals at different common reflection point (CMP) locations in a horizontally layered medium;

[0065] Figure 7 Hydraulic imaging simulation of soliton internal wave group 1 in water;

[0066] Figure 8 This is a schematic diagram of in-phase axis extraction after median filtering and edge enhancement.

[0067] Figure 9 Comparison of internal wave corrected imaging;

[0068] Figure 10 Acoustic correction imaging of water for soliton internal wave group 2. Detailed Implementation

[0069] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0070] This invention provides a moving internal wave correction method based on seawater acoustic imaging. The high spatial resolution and strong applicability of seismic reflection measurement methods to deep-sea exploration are beneficial for studying and monitoring the fine structure of small-scale soliton internal waves. The technical solution described in this invention establishes a process for satellite internal wave velocity estimation, seismic imaging correction, and internal wave characteristic parameter extraction.

[0071] Seismic images are instantaneous, and existing seismic imaging procedures and methods are not conducive to observing the motion of soliton internal waves. We improved the conventional processing scheme for seismic exploration data and used internal wave velocity obtained from satellite optical images to correct the acoustic imaging profile of the water body. In this way, characteristic parameters such as the true width, characteristic width, and amplitude of soliton internal waves during motion can be extracted from the seawater acoustic imaging profile. The internal wave characteristic parameters extracted using the improved scheme show good agreement with the preset internal wave characteristic parameters in numerical simulation, demonstrating the effectiveness of the processing scheme and correction in this invention. This improved scheme can not only study moving soliton internal waves but also has great potential for studying other ocean dynamics. (Refer to...) Figure 1 As shown, the method specifically includes:

[0072] Step S1: Obtain raw data of seismic exploration of water bodies.

[0073] The soliton internal wave is assumed to move in the same direction as the offshore seismic exploration experimental vessel. Figure 2 As shown, the horizontal velocity V of the soliton internal wave moving from the common center point CMP to CMP' is... wave Represented as:

[0074]

[0075] The internal wave moves at the same speed as the ship, and the horizontal speed of the air gun moving from point S to S' is V. ship The energy generated by the two air guns is reflected in the inner wave trough and finally received by the two hydrophones R and R'.

[0076] Step S2: Obtain the received signal through simulation calculation using the original data, and perform moving internal wave acoustic imaging of the water body using the received signal.

[0077] The experimental vessel conducted multiple airgun experiments at a relative initial position, emitting airgun signals at horizontal intervals of 37.5m, which were received by the ship's horizontally towed array. Using conventional underwater acoustic imaging processing procedures, the superimposed profiles of these received signals, after suppressing surface reflections and noise, were first processed. When imaging the seawater, the influence of direct waves with a sound velocity of 1480m / s was first removed. Then, referring to the seismic reflection wave method in seismic exploration technology, the acquired time-domain signals were pre-stacked, and the time-domain waveforms of the received signals at common reflection locations were extracted and accumulated. After sorting by the common reflection point locations, the signals were filtered. Finally, the underwater acoustic imaging results of the wave group structure within the soliton were obtained.

[0078] Step S3: Extract the characteristic parameters of internal waves in the water.

[0079] Image edge detection is used to extract the similar undulating phase axis structure in the acoustic imaging profile of water bodies. A 5×1 grid is used for median filtering of the acoustic imaging profile of water bodies. Since the phase axis has a horizontal strip-like structure, the Sobel operator is used to further enhance the edges. The threshold for edge extraction is set as T' = 1.8·std(T) + mean(T), where T is the time-domain waveform of the original imaging profile. Finally, after removing discontinuous noise and anomalous false edge components, the phase axis of the acoustic imaging profile of the soliton inner wave group is obtained. From the phase axis, parameters such as the vertical displacement and characteristic width of the inner wave can be extracted.

[0080] Step S4: Correct the moving internal wave water acoustic imaging according to the characteristic parameters.

[0081] In the process of extracting the phase axis using imaging profiles, a velocity difference between the internal wave velocity and the exploration vessel's travel speed will produce a Doppler-like effect, where the internal wave velocity information V... wave Internal waves can be observed using the MODIS satellite. However, due to the velocity difference between the internal wave and the ship's speed, the dynamic hydrological environment during acoustic imaging at the common reflection point causes a horizontal shift in the sound wave path. This distortion at the reflection offset distance at the preset common reflection point results in the extracted feature width information being less accurate than the amplitude information of the internal wave. The following method directly corrects the horizontal feature width of the internal wave:

[0082]

[0083] To extract accurate internal wave characteristic parameter information from the phase axis, an algorithm for common reflection point compensation is proposed during water acoustic imaging. This algorithm is based on the common center point compensation diagram. Figure 3 As shown, the reordered positions of the common reflection points are as follows:

[0084]

[0085] Where, dT d represents the time interval for the air gun to fire its signal. offset denoted as , where is the distance from the air gun to the receiving array element, and n is the position number of the transmitted signal.

[0086] By using the corrected CMP coordinates, a corrected water body imaging profile is obtained, which enables the extraction of parameters such as the true internal wave vertical displacement and characteristic width from the phase axis.

[0087] This invention also provides a moving internal wave correction system based on seawater acoustic imaging. This system can be implemented by executing the steps of the moving internal wave correction method based on seawater acoustic imaging. That is, those skilled in the art can understand the moving internal wave correction method based on seawater acoustic imaging as a preferred embodiment of the moving internal wave correction system based on seawater acoustic imaging. The system specifically includes:

[0088] Module M1: Acquire raw seismic exploration data of water bodies.

[0089] The soliton internal wave is assumed to move in the same direction as the offshore seismic exploration experimental vessel. Figure 2 As shown, the horizontal velocity V of the soliton internal wave moving from the common center point CMP to CMP' is... wave Represented as:

[0090]

[0091] The internal wave moves at the same speed as the ship, and the horizontal speed of the air gun moving from point S to S' is V. ship The energy generated by the two air guns is reflected in the inner wave trough and finally received by the two hydrophones R and R'.

[0092] Module M2: Obtains the received signal through simulation calculations using the original data, and performs moving internal wave acoustic imaging of the water body using the received signal.

[0093] The experimental vessel conducted multiple airgun experiments at a relative initial position, emitting airgun signals at horizontal intervals of 37.5m, which were received by the ship's horizontally towed array. Using conventional underwater acoustic imaging processing procedures, the superimposed profiles of these received signals, after suppressing surface reflections and noise, were first processed. When imaging the seawater, the influence of direct waves with a sound velocity of 1480m / s was first removed. Then, referring to the seismic reflection wave method in seismic exploration technology, the acquired time-domain signals were pre-stacked, and the time-domain waveforms of the received signals at common reflection locations were extracted and accumulated. After sorting by the common reflection point locations, the signals were filtered. Finally, the underwater acoustic imaging results of the wave group structure within the soliton were obtained.

[0094] Module M3: Extracts characteristic parameters of internal waves in water.

[0095] Image edge detection is used to extract the similar undulating phase axis structure in the acoustic imaging profile of water bodies. A 5×1 grid is used for median filtering of the acoustic imaging profile of water bodies. Since the phase axis has a horizontal strip-like structure, the Sobel operator is used to further enhance the edges. The threshold for edge extraction is set as T' = 1.8·std(T) + mean(T), where T is the time-domain waveform of the original imaging profile. Finally, after removing discontinuous noise and anomalous false edge components, the phase axis of the acoustic imaging profile of the soliton inner wave group is obtained. From the phase axis, parameters such as the vertical displacement and characteristic width of the inner wave can be extracted.

[0096] Module M4: Corrects the moving internal wave water acoustic imaging based on the characteristic parameters.

[0097] In the process of extracting the phase axis using imaging profiles, a velocity difference between the internal wave velocity and the exploration vessel's travel speed will produce a Doppler-like effect, where the internal wave velocity information V... wave Internal waves can be observed using the MODIS satellite. However, due to the velocity difference between the internal wave and the ship's speed, the dynamic hydrological environment during acoustic imaging at the common reflection point causes a horizontal shift in the sound wave path. This distortion at the reflection offset distance at the preset common reflection point results in the extracted feature width information being less accurate than the amplitude information of the internal wave. The following method directly corrects the horizontal feature width of the internal wave:

[0098]

[0099] To extract accurate internal wave characteristic parameter information from the phase axis, an algorithm for common reflection point compensation is proposed during water acoustic imaging. This algorithm is based on the common center point compensation diagram. Figure 3 As shown, the reordered positions of the common reflection points are as follows:

[0100]

[0101] Where, d T d represents the time interval for the air gun to fire its signal. offset denoted as , where is the distance from the air gun to the receiving array element, and n is the position number of the transmitted signal.

[0102] By using the corrected CMP coordinates, a corrected water body imaging profile is obtained, which enables the extraction of parameters such as the true internal wave vertical displacement and characteristic width from the phase axis.

[0103] The present invention will now be described in more detail.

[0104] This invention provides a method for correcting moving internal waves based on seawater acoustic imaging, comprising:

[0105] Step 1: Acquisition of raw data from seismic exploration within the water body (simulated seismic exploration results are used here).

[0106] The soliton internal wave velocity and characteristic width of the two-layer seawater model are expressed as follows:

[0107]

[0108]

[0109] Where h1 and h2 are the depths of the two layers of seawater, Δρ is the change in seawater density, η0 is the vertical displacement of the soliton internal wave, and g is the gravitational acceleration. Figure 4 The instantaneous vertical displacements of five independent soliton inner wave groups and eight mutually influential soliton inner wave groups are given. Figure 5 The spatial distribution of seawater sound velocity in soliton internal wave group 1 is given, and the characteristic parameters of the internal waves are: the maximum wave depth η of the internal waves. n and the position of the inner wave center R n The results are presented in Tables 1 and 2:

[0110] Table 1 Characteristic parameters of soliton inner wavegroup 1

[0111]

[0112] Table 2 Characteristic parameters of soliton inner group 2

[0113]

[0114] At a depth of 600m, the density of seawater is 1025 kg / m³ at a depth of 100m. 3 The linear increase to 1035 kg / m at a depth of 350 m 3 Under the background hydrological conditions, simulation results of the spatial sound velocity distribution of the soliton internal wave group are constructed. To observe the changes in reflection characteristics caused by internal waves, the hydrological environment in the presence of internal waves is constructed based on the moving velocity and characteristic parameters of the soliton internal waves. Figure 2 As shown, a dynamic finite-difference sound field model that considers the sound reflection effect between water layers is used to simulate the time-domain waveform of sound waves propagating in the inner wave, accurately simulating the arrival structure of the low-frequency near-field sound field. Figure 6 The received signal forms of different horizontally layered environments are described in the figure, among which Figure 6 (a) shows the time-domain signal of the pulse signal received within a 2km range from the sound source, unaffected by internal waves. Figure 6 (b) represents the time-domain signal received after the pulse passes through the center of the first soliton internal wave packet. Because the descending soliton internal wave causes the upper low-density water to sink, the sound velocity profile exhibits a spatially distance-dependent variation in the vertical direction due to the influence of the soliton internal wave, as reflected in… Figure 6 (b) characterizes the reflected wave compared to Figure 6 (a) The hyperbolic stripes shifted downwards as a whole.

[0115] Step Two: Acoustic Imaging of Moving Internal Waves in the Water. The propagation direction of the internal waves is the same as the direction of the ship's movement. The experimental ship emits an airgun signal every 37.5m horizontally, for a total of 500 airgun signals (Recker wavelets). The sound field excited by the airgun propagates through the channel and is received by the towed horizontal array accompanying the ship. The received signals can be simulated using the finite-difference time-domain method in Step One. Seawater imaging is performed on these 500 received signals. First, the influence of the direct wave with a sound velocity of 1480m / s is removed. Then, referring to the seismic reflection wave method in seismic exploration technology, the acquired time-domain signal is pre-stacked, and the time-domain waveforms of the received signals at common reflection locations are extracted and accumulated. After sorting by the common reflection point location and filtering, the final acoustic imaging results of the soliton internal wave group structure are obtained as follows: Figure 7 As shown.

[0116] Step 3: Extraction of internal wave characteristic parameters in water. Using image edge detection methods, extract in-phase axis structures with similar undulations from the acoustic imaging profile of the water body. A 5×1 grid is used. Figure 7 Median filtering is applied, and the Sobel operator is used to further enhance the edges due to the horizontal strip-like structure of the in-phase axis. The threshold for edge extraction is set to T' = 1.8·std(T) + mean(T), where T is the time-domain waveform of the original imaging profile. Finally, after removing discontinuous noise and anomalous false edge components, the in-phase axis of the water acoustic imaging profile of the soliton inner wave group is obtained. Figure 8 (As shown). Parameters such as the vertical displacement and characteristic width of the internal wave can be extracted from the phase axis.

[0117] Step 4: Correction of internal wave acoustic imaging of water. During the extraction of the in-phase axis using the imaging profile, a Doppler-like effect occurs due to the velocity difference between the internal wave velocity and the exploration vessel's travel speed. A formula is used to correct the characteristic width of the internal wave in the horizontal direction.

[0118]

[0119] As shown in Table 3, the extracted feature width information is less accurate than the amplitude information of the internal wave. This is because there is a velocity difference between the internal wave velocity and the ship's speed. During acoustic imaging at the common reflection point in water, the sound wave path deviates horizontally due to the dynamic hydrological environment, resulting in distortion of the reflection offset distance at the preset common reflection point. Therefore, to extract accurate internal wave feature parameter information from the phase axis, an algorithm for common reflection point compensation is proposed during acoustic imaging of water. The compensation diagram for the common center point is shown below. Figure 3 As shown.

[0120] Table 3 Extraction of Internal Wave Characteristic Parameters

[0121]

[0122]

[0123] The above formula represents the reordered positions of the common reflection points, where d T d represents the time interval for the air gun to fire its signal. offset Let n be the distance between the air gun and the receiving array element, and n be the position number of the transmitted signal. The imaging results before and after correction are as follows: Figure 9 As shown.

[0124] The finite-difference time-domain (FDTD) algorithm was used to simulate the time-domain signal of sound waves passing through mutually influencing solitary internal wave groups. The resulting time-domain signal was then used to construct a seawater imaging profile. The total water depth was 600m, with CMP1000-CMP4000 corresponding to eight solitary internal waves, the depth of which ranged from 100 to 350m. The strongest reflection was observed at the horizontal sedimentary layer interface. At other locations, the downflow of internal waves caused thin-layer reflections between water layers, exhibiting continuity and a distinct layered structure. Figure 10 The eight solitary internal wave groups shown form an acoustic imaging profile structure that influences each other. It can be seen that the mutually influencing internal wave groups can also be used to perform correct acoustic imaging of water bodies through this modified algorithm.

[0125] This invention provides a method and system for correcting moving internal waves based on seawater acoustic imaging. It obtains the wave velocity of the internal wave group from a distance using high-sensitivity medium-resolution optical images, corrects the moving internal wave sea acoustic imaging method, and can extract the true internal wave wavelength, width, amplitude and other characteristic information.

[0126] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0127] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for correcting moving internal waves based on seawater acoustic imaging, characterized in that, include: Step S1: Obtain raw seismic exploration data of water body waves; Step S2: Obtain the received signal through simulation calculation using the original data, and perform moving internal wave acoustic imaging of the water body using the received signal; Step S3: Extract the characteristic parameters of internal waves in the water; Step S4: Correct the moving internal wave water acoustic imaging according to the characteristic parameters; Step S4 includes: during the extraction of the phase axis using the imaging profile, a velocity difference between the internal wave velocity and the exploration vessel's travel speed will produce a Doppler-like effect. A formula is used to correct the characteristic width of the internal wave in the horizontal direction. Wherein, the horizontal speed of the ship is V ship ; To extract accurate internal wave characteristic parameter information from the phase axis, an algorithm for common reflection point compensation is proposed during water acoustic imaging. The reordered common reflection point positions are as follows: Where, d T d represents the time interval for the air gun to fire its signal. offset denoted as , where is the distance from the air gun to the receiving array element, and n is the position number of the transmitted signal; Using the corrected CMP coordinates, a corrected water body imaging profile is obtained, and relevant parameters, including the true internal wave vertical displacement and characteristic width, are extracted from the phase axis.

2. The method for correcting moving internal waves based on seawater acoustic imaging according to claim 1, characterized in that, Step S1 includes: The soliton internal wave velocity and characteristic width of the two-layer seawater model are expressed as follows: Where h1 and h2 are the depths of the two seawater layers, Δρ is the change in seawater density, η0 is the vertical displacement of the soliton internal wave, and g is the gravitational acceleration; the spatial sound velocity distribution of the soliton internal wave group is simulated based on the wave velocity and characteristic width of the soliton internal wave.

3. The method for correcting moving internal waves based on seawater acoustic imaging according to claim 1, characterized in that, Step S2 includes: Step S2.1: Remove the influence of direct waves with a sound speed of 1480m / s; Step S2.2: Referring to the seismic reflection wave method in seismic exploration technology, the acquired received signal is subjected to pre-stack time migration, the time domain waveform of the received signal at the common reflection location is extracted and accumulated, and then filtered after being sorted according to the location of the common reflection point; Step S2.3: Finally, obtain the acoustic imaging results of the water body within the soliton's internal wave group structure.

4. The method for correcting moving internal waves based on seawater acoustic imaging according to claim 1, characterized in that, Step S3 includes: Step S3.1: Using image edge detection, extract similar in-phase axis structures in the acoustic imaging profile of the water body; Step S3.2: Apply median filtering to the acoustic imaging profile of the water body using a 5×1 grid; Step S3.3: The Sobel operator is used to further enhance the edges. The threshold for edge extraction is set as T' = 1.8·std(T) + mean(T), where T is the time-domain waveform of the original imaging profile. Discontinuous noise and abnormal false edge components are removed to obtain the phase axis of the water acoustic imaging profile of the soliton inner wave group. Relevant parameters, including the vertical displacement and characteristic width of the inner wave, are extracted from the phase axis.

5. A moving internal wave correction system based on seawater acoustic imaging, characterized in that, include: Module M1: Acquire raw seismic exploration data of water bodies; Module M2: Obtains the received signal through simulation calculations using the original data, and performs acoustic imaging of the moving internal wave water body using the received signal; Module M3: Extracts characteristic parameters of internal waves in water; Module M4: Corrects the moving internal wave water acoustic imaging based on the aforementioned characteristic parameters; The module M4 includes: during the extraction of the in-phase axis using imaging profiles, a velocity difference between the internal wave velocity and the exploration vessel's travel speed will produce a Doppler-like effect; a formula is used to correct the characteristic width of the internal wave in the horizontal direction: Wherein, the horizontal speed of the ship is V ship ; To extract accurate internal wave characteristic parameter information from the phase axis, an algorithm for common reflection point compensation is proposed during water acoustic imaging. The reordered common reflection point positions are as follows: Where, d T d represents the time interval for the air gun to fire its signal. offset denoted as , where is the distance from the air gun to the receiving array element, and n is the position number of the transmitted signal; Using the corrected CMP coordinates, a corrected water body imaging profile is obtained, and relevant parameters, including the true internal wave vertical displacement and characteristic width, are extracted from the phase axis.

6. The moving internal wave correction system based on seawater acoustic imaging according to claim 5, characterized in that, The module M1 includes: The soliton internal wave velocity and characteristic width of the two-layer seawater model are expressed as follows: Where h1 and h2 are the depths of the two seawater layers, Δρ is the change in seawater density, η0 is the vertical displacement of the soliton internal wave, and g is the gravitational acceleration; the spatial sound velocity distribution of the soliton internal wave group is simulated based on the wave velocity and characteristic width of the soliton internal wave.

7. The moving internal wave correction system based on seawater acoustic imaging according to claim 5, characterized in that, The module M2 includes: Module M2.1: Removes the influence of direct waves with a sound velocity of 1480m / s; Module M2.2: Referring to the seismic reflection wave method in seismic exploration technology, the acquired received signal is subjected to pre-stack time migration, the time domain waveform of the received signal at the common reflection location is extracted and accumulated, and then filtered after being sorted according to the location of the common reflection point; Module M2.3: Finally, obtain the acoustic imaging results of the water body within the soliton's internal wave group structure.

8. The moving internal wave correction system based on seawater acoustic imaging according to claim 5, characterized in that, The module M3 includes: Module M3.1: Utilizes image edge detection to extract similar undulating in-phase axis structures in the acoustic imaging profile of water bodies; Module M3.2: Median filtering of acoustic imaging profiles of water bodies using a 5×1 grid; Module M3.3: The Sobel operator is used to further enhance the edges. The threshold for edge extraction is set as T' = 1.8·std(T) + mean(T), where T is the time-domain waveform of the original imaging profile. Discontinuous noise and abnormal false edge components are removed to obtain the phase axis of the water acoustic imaging profile of the soliton inner wave group. Relevant parameters, including the vertical displacement and characteristic width of the inner wave, are extracted from the phase axis.

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