Ocean engineering underwater geomagnetic anomaly joint inversion surveying and mapping method and system

Abstract

The invention provides an ocean engineering underwater geomagnetic anomaly joint inversion surveying and mapping method and system. The method comprises the following steps: acquiring geomagnetic anomaly data of multiple data sources; preprocessing the geomagnetic anomaly data, and unifying the geomagnetic anomaly data of different data sources to the same coordinate system; carrying out fusion processing on the plurality of preprocessed geomagnetic anomaly data to obtain fused geomagnetic anomaly data; establishing a geomagnetic anomaly inversion model according to the geological features of the ocean area and the prior information of the target object; and according to the fused geomagnetic anomaly data and the geomagnetic anomaly inversion model, performing combined inversion calculation to solve magnetic parameters. According to the method, abundant data sources are adopted, the sampling interval is dynamically adjusted, it is ensured that all-directional geomagnetic anomaly information of the ocean area can be obtained, and data redundancy or missing is avoided; the advantages of different data sources are fully integrated, fusion algorithm parameters are dynamically adjusted or an algorithm is replaced, the integrity, consistency and accuracy of data are enhanced, and a solid foundation is laid for accurate inversion.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of ocean engineering, and in particular, relates to a marine engineering underwater geomagnetic anomaly joint inversion surveying and mapping method and system. BACKGROUND

[0002] In the field of ocean engineering, underwater geomagnetic surveying and mapping is of great significance for detecting underground geological bodies and identifying target objects. However, traditional underwater geomagnetic measurement methods have many limitations.

[0003] Unlike the relatively static and stable spatial distribution of conductive properties in underground environments, the underwater environment is mainly composed of seawater, which directly interferes with the propagation of geomagnetic signals due to its conductivity and fluidity. Dynamic factors such as ocean currents and waves exist, leading to unstable measurement device posture and introducing additional noise. The Earth's main magnetic field, the magnetic field of the seabed magnetic geological body, and the interference of ship metal components need to be considered simultaneously.

[0004] On the one hand, underwater exploration needs to cover different depths (from the sea surface to the seabed) and horizontal positions, but the data sources obtained by a single measurement device are limited. Shipborne magnetometers have a wide coverage range, but their ability to detect deep sea areas is insufficient. Underwater autonomous vehicles with magnetometers have high flexibility, but they have shortcomings in endurance and stability. Due to the limitations of endurance and communication, it is difficult to achieve long-term continuous measurement. Fixed seabed magnetometers can monitor fixed areas for a long time, but they are difficult to achieve rapid measurement in a large area, resulting in incomplete data and an inability to accurately reflect the underwater geomagnetic anomaly situation.

[0005] On the other hand, the positioning of underwater devices is affected by ocean current drift and water pressure, resulting in low coordinate accuracy. The data collected by different measurement devices often has noise and errors, and the coordinate systems are inconsistent, making data preprocessing difficult. It is difficult to directly calibrate using GPS or total station, and the coordinate systems need to be unified through complex conversion. At the same time, underwater geomagnetic data noise includes device motion noise and electromagnetic interference, which requires specific denoising algorithms such as wavelet transform and Kalman filtering. Existing inversion models cannot fully consider the complex environmental factors of the ocean and the multiple parameters of underground geological bodies and target objects, and the optimization algorithm efficiency and accuracy of inversion calculation are not satisfactory, resulting in low reliability of the inversion results and difficulty in meeting the high-precision surveying and mapping needs of ocean engineering.

[0006] The patent document "Ocean Controlled Source Electromagnetic and Magnetotelluric Joint Inversion Method Based on Product Function" (CN112578470A) discloses simultaneously inverting the anisotropic resistivity and thickness of the seabed stratum, combining the high resolution of ocean controlled source electromagnetic data for shallow strata and the detection ability of magnetotelluric data for deep structures, resulting in higher inversion efficiency and better results. The proposed joint inversion method has wider applicability, but the inversion calculation is complex and the data sources are relatively single.

[0007] Therefore, a marine engineering underwater geomagnetic anomaly joint inversion mapping method is proposed, which can guarantee the reliability, integrity, consistency and accuracy of data processing, and provide a high-quality data basis for subsequent processing. SUMMARY

[0008] In view of the defects in the prior art, the purpose of the present application is to provide a marine engineering underwater geomagnetic anomaly joint inversion mapping method and system.

[0009] According to the marine engineering underwater geomagnetic anomaly joint inversion mapping method provided by the present application, the following steps are included:

[0010] The data acquisition step, the geomagnetic data of the marine area is collected by using a plurality of underwater geomagnetic measuring devices, and the geomagnetic anomaly data of a plurality of data sources is obtained;

[0011] The data preprocessing step, the geomagnetic anomaly data is preprocessed, and the geomagnetic anomaly data of different data sources is unified to the same coordinate system;

[0012] The data fusion step, the preprocessed multiple geomagnetic anomaly data is fused to obtain the fused geomagnetic anomaly data;

[0013] The inversion model establishment step, according to the geological characteristics of the marine area and the prior information of the target object, the geomagnetic anomaly inversion model is established;

[0014] The inversion calculation step, according to the fused geomagnetic anomaly data and the geomagnetic anomaly inversion model, the joint inversion calculation is performed to solve the magnetic parameters.

[0015] Preferably, the underwater geomagnetic measuring device includes a shipborne magnetometer, an underwater autonomous vehicle-mounted magnetometer and a seabed fixed magnetometer.

[0016] The geomagnetic data acquisition is carried out at multiple positions and multiple depths in the marine area.

[0017] The preprocessing includes data cleaning, denoising and coordinate conversion, the denoising adopts wavelet transform denoising algorithm, Kalman filter algorithm and / or adaptive filter algorithm.

[0018] The data fusion adopts weighted average, Kalman filter and / or neural network fusion algorithm.

[0019] The data fusion step further includes: quality evaluation is performed on the fused geomagnetic anomaly data, if the evaluation index is greater than or equal to the preset threshold, the inversion calculation step is executed, if the evaluation index is lower than the preset threshold, the parameters of the data fusion algorithm are adjusted or the data fusion algorithm is replaced to perform data fusion again.

[0020] The evaluation index includes the integrity, consistency and accuracy of the data.

[0021] Preferably, in the geomagnetic data acquisition, the sampling interval of the shipborne magnetometer is dynamically adjusted according to the ship navigation speed and the geomagnetic gradient variation of the measured sea area:

[0022]

[0023] where Δs represents the sampling interval;

[0024] υ represents the ship navigation speed;

[0025] G represents the geomagnetic gradient of the measured sea area;

[0026] k represents an empirical coefficient, and the value range is 1-5.

[0027] Preferably, in the inversion model establishment step, the model parameters are set according to the shape, size, buried depth, magnetization intensity parameters of the underground geological body or target object, the conductivity of seawater and / or the ocean flow field.

[0028] Suppose that the underground geological body is composed of a plurality of simple-shaped magnetic bodies, for a single regular magnetic body:

[0029]

[0030] where ∝ represents a proportional relationship;

[0031] ΔT represents the generated geomagnetic anomaly;

[0032] M represents the magnetization intensity of the magnetic body;

[0033] V represents the volume;

[0034] r represents the distance from the magnetic body to the observation point.

[0035] The geomagnetic anomaly inversion model is obtained by superimposing the geomagnetic anomalies generated by the magnetic bodies.

[0036] The inversion calculation utilizes an optimization algorithm, including a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm and / or a conjugate gradient method.

[0037] A relationship model is established to separate the interference of the main geomagnetic field and the measurement noise:

[0038] T obs = T0+ ΔT+ ε

[0039] where ε represents the measurement noise, and is subject to a normal distribution with a mean of zero and a variance of σ 2 ;

[0040] The value T obs represents the actual geomagnetic anomaly measurement at the observation point P;

[0041] ΔT represents the generated magnetic anomaly;

[0042] T0 represents the main magnetic field of the earth.

[0043] Preferably, it further comprises a result analysis and evaluation step:

[0044] The magnetic parameters obtained by solving are analyzed and quantitatively evaluated by using the root mean square error and the correlation coefficient, and are compared with known geological data and actual measurement data to verify the accuracy of the results;

[0045] According to the accuracy of the verification result, the data source, the magnetic anomaly inversion model and / or the algorithm of pre-processing, data fusion and / or inversion calculation are optimized.

[0046] According to the application, a marine engineering underwater magnetic anomaly joint inversion surveying and mapping system is provided, comprising:

[0047] The data acquisition module uses various underwater magnetic measurement devices to acquire magnetic data of the marine area and obtain magnetic anomaly data of various data sources;

[0048] The data preprocessing module preprocesses the magnetic anomaly data and unifies the magnetic anomaly data of different data sources to the same coordinate system;

[0049] The data fusion module fuses the preprocessed magnetic anomaly data to obtain fused magnetic anomaly data;

[0050] The inversion model establishment module establishes a magnetic anomaly inversion model according to the geological characteristics of the marine area and the prior information of the target object;

[0051] The inversion calculation module jointly calculates the magnetic parameters according to the fused magnetic anomaly data and the magnetic anomaly inversion model.

[0052] Preferably, the underwater magnetic measurement device comprises a shipborne magnetometer, an underwater autonomous vehicle-mounted magnetometer and a seabed fixed magnetometer.

[0053] The magnetic data acquisition is carried out at multiple positions and depths in the marine area.

[0054] The preprocessing includes data cleaning, denoising and coordinate conversion, and the denoising uses wavelet transform denoising algorithm, Kalman filtering algorithm and / or adaptive filtering algorithm.

[0055] The data fusion uses weighted average, Kalman filtering and / or neural network fusion algorithm.

[0056] The data fusion module further comprises: quality evaluation of the fused geomagnetic anomaly data, if the evaluation index is greater than or equal to a preset threshold, performing the inversion calculation step, if the evaluation index is lower than the preset threshold, adjusting the parameters of the data fusion algorithm or replacing the data fusion algorithm to perform data fusion again.

[0057] The evaluation index comprises data integrity, consistency and accuracy.

[0058] Preferably, in the geomagnetic data acquisition, according to the ship sailing speed, the geomagnetic gradient change of the measured sea area, the sampling interval of the shipborne magnetometer is dynamically adjusted:

[0059]

[0060] Where Δs represents the sampling interval;

[0061] υ represents the ship sailing speed;

[0062] G represents the geomagnetic gradient of the measured sea area;

[0063] k represents an empirical coefficient, and the value range is 1-5.

[0064] Preferably, in the inversion model establishment module, according to the shape, size, buried depth, magnetization intensity parameter of the underground geological body or target object, the conductivity of seawater and / or the ocean flow field, the model parameters are set.

[0065] Suppose that the underground geological body is composed of a plurality of simple-shaped magnetic bodies, for a single regular magnetic body:

[0066]

[0067] Where ∝ represents a proportional relationship;

[0068] ΔT represents the generated geomagnetic anomaly;

[0069] M represents the magnetization intensity of the magnetic body;

[0070] V represents the volume;

[0071] r represents the distance from the magnetic body to the observation point.

[0072] The geomagnetic anomaly inversion model is obtained by superimposing the geomagnetic anomalies generated by the magnetic bodies.

[0073] The inversion calculation utilizes an optimization algorithm, including a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm and / or a conjugate gradient method.

[0074] A relationship model is established to separate the interference of the main geomagnetic field and the measurement noise:

[0075] T obs= T0 + ΔT + ε

[0076] wherein ε represents measurement noise, obeying normal distribution with mean zero and variance σ 2

[0077] value T obs represents the actual geomagnetic anomaly measurement at observation point P;

[0078] ΔT represents the generated geomagnetic anomaly;

[0079] T0 represents the earth's main magnetic field.

[0080] Preferably, it further comprises a result analysis and evaluation module:

[0081] The magnetic parameters obtained by solving are analyzed and quantitatively evaluated by using root mean square error and correlation coefficient, and are compared with known geological data and actual measurement data to verify the accuracy of the results;

[0082] According to the accuracy of the verification results, the data source, the geomagnetic anomaly inversion model and / or the algorithm of pre-processing, data fusion and / or inversion calculation are optimized.

[0083] Compared with the prior art, the present application has the following beneficial effects:

[0084] 1. The present application collects data at different positions and depths, greatly enriches the data source, and ensures that the geomagnetic anomaly information of the marine area can be obtained in all directions.

[0085] 2. The present application dynamically adjusts the sampling interval according to the ship's sailing speed and the geomagnetic gradient of the measured sea area, effectively improves the pertinence and effectiveness of data collection, avoids data redundancy or loss, and provides a high-quality data basis for subsequent processing.

[0086] 3. The present application fully integrates the advantages of different data sources, enhances the integrity, consistency and accuracy of the data, dynamically adjusts the fusion algorithm parameters or replaces the algorithm according to the evaluation results, and further ensures the reliability of data processing.

[0087] 4. The inversion model of the present application can more realistically describe the relationship between the magnetic parameters of the underground geological body or target object and the geomagnetic anomaly data, and lay a solid foundation for accurate inversion. BRIEF DESCRIPTION OF DRAWINGS

[0088] Other features, objects and advantages of the present application will become more apparent through reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0089] Figure 1 is a flowchart of the marine engineering underwater geomagnetic anomaly joint inversion surveying method of the present application. DETAILED DESCRIPTION ​

[0090] The application will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the application, but do not limit the application in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the application. These are within the scope of protection of the application.

[0091] The marine engineering underwater geomagnetic anomaly joint inversion mapping method provided by the application greatly enriches the data source, ensures that the geomagnetic anomaly information of the marine area can be obtained in all directions, effectively improves the pertinence and effectiveness of data acquisition, avoids data redundancy or loss, and provides a high-quality data basis for subsequent processing.

[0092] For example, using a shipborne magnetometer, an underwater autonomous vehicle-mounted magnetometer, a seabed fixed magnetometer and other devices, data is collected at different positions and depths. For the shipborne magnetometer, the sampling interval is dynamically adjusted according to the ship speed and the geomagnetic gradient of the measured sea area. Specifically, it includes: Figure 1 Data collection: using various underwater geomagnetic measurement devices, including shipborne magnetometers, underwater autonomous vehicle-mounted magnetometers, and seabed fixed magnetometers, geomagnetic data is collected in different positions and depths in the marine area to obtain geomagnetic anomaly data from multiple data sources.

[0093] Different types of measurement devices are suitable for different marine environments and measurement needs. Shipborne magnetometers can quickly measure large areas of the sea, underwater autonomous vehicle-mounted magnetometers can penetrate complex sea areas, and seabed fixed magnetometers can stably monitor specific areas for a long time. The multi-device, multi-position and multi-depth data collection method avoids data bias and omission that may exist in single devices or single measurement points, thereby more completely reflecting the geomagnetic anomaly characteristics of the marine area.

[0094] In more preferred examples, in the data collection step, for the shipborne magnetometer, the sampling interval is dynamically adjusted according to the ship speed and the geomagnetic gradient variation of the measured sea area. The sampling interval adjustment formula is:

[0095]

[0096] Where Δs is the sampling interval, υ is the ship speed, G is the geomagnetic gradient of the measured sea area, and k is an empirical coefficient with a value range of 1-5.

[0097]

[0098] ​The ship navigation speed and the measurement of the geomagnetic gradient variation in the sea area will affect the collection effect of the geomagnetic anomaly data. If the sampling interval is fixed, in the area where the ship navigation speed is fast or the geomagnetic gradient variation is large, data may be missed, and the geomagnetic anomaly situation cannot be accurately reflected. In the area where the ship navigation speed is slow or the geomagnetic gradient variation is small, data redundancy may be generated, and the data processing burden is increased. Through the above sampling interval adjustment formula, the sampling interval is dynamically adjusted according to the actual situation, the number of sampling points can be reasonably controlled under different navigation conditions and sea area environments, and it is ensured that the collected data can accurately reflect the geomagnetic anomaly variation. At the same time, the data collection efficiency is improved, the problems of data redundancy or missing caused by traditional fixed interval sampling are solved, and it is especially suitable for complex sea areas.

[0099] Data preprocessing: The collected various geomagnetic anomaly data are preprocessed, including data cleaning, denoising and coordinate conversion, so as to eliminate the noise and error in the data, and unify the data of different data sources to the same coordinate system.

[0100] In the data collection process, various noise and error will be inevitably introduced, such as environmental interference, equipment self-error, etc. The data cleaning and denoising operation can remove these interference factors, so that the data can more truly reflect the geomagnetic anomaly situation. The data of different data sources may adopt different coordinate systems, and the coordinate conversion can unify them, so as to ensure the consistency and comparability of the data in the subsequent processing, avoid the data confusion and error analysis caused by the difference of coordinate systems, and improve the data quality.

[0101] Specifically, at least one of the wavelet transform denoising algorithm, the Kalman filter algorithm or the adaptive filter algorithm is used in the denoising operation in the data preprocessing. Different denoising algorithms have different characteristics and application ranges. The wavelet transform denoising algorithm is suitable for processing noise with sudden signal, the Kalman filter algorithm is suitable for processing noise in dynamic system, and the adaptive filter algorithm can automatically adjust the parameters for denoising according to the noise variation.

[0102] According to the specific situation of the data, the appropriate algorithm or a combination of multiple algorithms is selected, and the data cleaning and coordinate conversion are combined, so as to more accurately remove the noise and error, retain the effective information in the data, improve the signal-to-noise ratio of the data, and further improve the accuracy of the subsequent data fusion, inversion calculation and other steps.

[0103] Data fusion: The data fusion algorithm is used to fuse and process the preprocessed various geomagnetic anomaly data, and the fused geomagnetic anomaly data are obtained.

[0104] The advantages of integrating multiple data sources are combined, the effective information of each data is fully utilized, the shortcomings of single data source are made up, the precision and reliability of the data are improved, better data input is provided for the inversion model, and the accuracy of the inversion result is improved.

[0105] Specifically, the data fusion algorithm adopts at least one of a weighted average fusion algorithm, a Kalman filter fusion algorithm, or a neural network fusion algorithm, integrates multi-source data such as shipborne, underwater robots, and seabed fixed stations, and overcomes the short board of a single device in coverage (such as shipborne) or deep-sea detection capability (such as underwater robots). Different data fusion algorithms have different focuses and methods when fusing data. The weighted average fusion algorithm is simple and intuitive, and is suitable for cases where the reliability of data is known to some extent; the Kalman filter fusion algorithm can effectively process dynamic data; and the neural network fusion algorithm has strong learning and adaptation capabilities. According to the type of data, noise conditions, relationships between data, and other factors, selecting the appropriate algorithm can better integrate data information, improve the accuracy and reliability of data fusion, enhance the integrity, consistency, and accuracy of data, and thus improve the accuracy of the inversion result.

[0106] In more preferred examples, after the data fusion step, the quality of the fused geomagnetic anomaly data is evaluated, and when the evaluation index is lower than the preset threshold, the parameters of the data fusion algorithm are adjusted or the data fusion algorithm is replaced. The quality evaluation index includes the integrity, consistency, and accuracy of the data.

[0107] The quality of data fusion directly affects the accuracy of the inversion result. By evaluating the integrity, consistency, and accuracy of the data, it can be determined whether the fused data meets the requirements of the inversion calculation. If it does not meet the requirements, the fusion algorithm parameters are dynamically adjusted, forming a full-process optimization mechanism of "collection-preprocessing-fusion-evaluation", to ensure the reliability of the inversion result. If the evaluation index is lower than the preset threshold, it indicates that the data fusion effect is not good, and there may be problems such as data loss, data contradiction, or inaccurate data. At this time, the parameters of the data fusion algorithm are adjusted or the algorithm is replaced, which can optimize the data fusion process, improve the quality of the fused data, provide better data for subsequent inversion calculation, and thus improve the accuracy and reliability of the inversion result.

[0108] Establishing an inversion model: according to the geological characteristics of the marine engineering area and the prior information of the target object, an appropriate geomagnetic anomaly inversion model for the corresponding area is established, which describes the mathematical relationship between the magnetic parameters of the underground geological body or the target object and the geomagnetic anomaly data.

[0109] The geological characteristics and target objects of different marine engineering areas are different. Based on the geological characteristics and prior information of the target object of a specific area, the model can take into account the influence of actual geological structure, target object characteristics, and other factors on the inversion result. For example, by understanding the approximate shape and position of the target object, the parameters in the model can be set more reasonably, making the model more accurately reflect the actual situation and thus improve the accuracy of the inversion calculation.

[0110] Specifically, when establishing the geomagnetic anomaly inversion model, the marine environmental impact factors (such as seawater conductivity, the main magnetic field T0 of the earth) are explicitly introduced, and the shape, size, burial depth, and magnetization intensity parameters of the underground geological body or target object and the influence factors of the marine environment on the geomagnetic anomaly are considered. The shape, size, burial depth, and magnetization intensity of the underground geological body or target object directly affect the distribution and intensity of the geomagnetic anomaly, and marine environmental factors such as seawater conductivity and ocean current field also have an impact on the geomagnetic measurement. Fully considering these factors when establishing the inversion model can more accurately describe the mechanism of the generation of the geomagnetic anomaly, make the model more consistent with the actual situation, and thus improve the accuracy of the magnetic parameters obtained by inversion calculation, providing a reliable basis for the planning and decision-making of marine engineering.

[0111] When establishing the inversion model, it is assumed that the underground geological body is composed of several simple-shaped magnetic bodies. For a single regular magnetic body (such as a sphere or a cuboid), the geomagnetic anomaly ΔT it produces at an observation point is related to the magnetization intensity M of the magnetic body, the volume V of the magnetic body, and the distance r from the magnetic body to the observation point, and the calculation formula is:

[0112]

[0113] where ∝ represents a proportional relationship. This can better reflect the basic relationship between the geomagnetic anomaly and the magnetic parameters and spatial position of the magnetic body. The total geomagnetic anomaly produced by the entire underground geological body at the observation point is the superposition of the geomagnetic anomalies produced by each magnetic body.

[0114] The shape and structure of the underground geological body are usually very complex, and it is difficult to model and perform inversion calculation directly. By assuming that it is a combination of simple-shaped magnetic bodies, the geomagnetic anomaly calculation formula of the known simple-shaped magnetic bodies can be used to simplify the model establishment process, and the geomagnetic anomaly of the entire underground geological body can be approximately obtained by superimposing the geomagnetic anomalies produced by each magnetic body. This method not only reduces the calculation complexity, but also accurately reflects the geomagnetic anomaly situation of the actual geological body to some extent, making the inversion calculation more feasible and accurate.

[0115] Inversion calculation: Using an optimization algorithm, combined with the fused geomagnetic anomaly data and the established inversion model, the geomagnetic anomaly is jointly inverted and calculated to solve the magnetic parameters of the underground geological body or target object.

[0116] Optimization algorithms have strong search and optimization capabilities. For example, genetic algorithms find the optimal solution by simulating the biological evolution process, and particle swarm optimization algorithms find the optimal solution by information sharing and cooperation between particles. These algorithms can quickly find the magnetic parameter values that make the model calculation results best match the actual geomagnetic anomaly data in a complex inversion model, thereby improving the efficiency and accuracy of the inversion calculation and providing valuable geological parameters for marine engineering.

[0117] In particular, the optimization algorithm employs at least one of a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm, or a conjugate gradient method. Different optimization algorithms have different search strategies and computational efficiency, the genetic algorithm is suitable for processing complex nonlinear problems, the particle swarm optimization algorithm has fast convergence speed, the simulated annealing algorithm can avoid falling into a local optimal solution, and the conjugate gradient method is suitable for solving large-scale linear equations. According to the complexity of the inversion model, the amount of calculation, whether there is a local optimum, and other problems, select the appropriate algorithm, combine the fused magnetic anomaly data and the scientific inversion model for joint inversion calculation, which can fully play the advantages of the algorithm, quickly and accurately solve the magnetic parameters of the underground geological body or target object, improve the efficiency and accuracy of the inversion calculation, and quickly obtain reliable inversion results.

[0118] In more preferred examples, when considering the influence of the magnetic anomaly, the noise is separated from the geological body anomaly signal, and the inversion accuracy in a complex electromagnetic environment is improved. The actual magnetic anomaly measurement value T at the observation point P obs The relationship between the magnetic anomaly AT generated by the underground geological body and the main magnetic field TO of the earth is:

[0119] T obs = TO + AT + ε

[0120] Where ε is the measurement noise, which is subject to a normal distribution with a mean of zero and a variance of σ 2 .

[0121] In actual measurement, the magnetic anomaly measurement value of the observation point is jointly affected by the main magnetic field of the earth, the magnetic anomaly generated by the underground geological body, and the measurement noise. By establishing the above mathematical relationship, the magnetic anomaly generated by the underground geological body can be more accurately separated in the inversion calculation process, and the interference of the main magnetic field of the earth and the measurement noise can be removed, so that more accurate magnetic parameters of the underground geological body are obtained, and the accuracy of the inversion result is improved.

[0122] Result analysis and evaluation: analyze and evaluate the results obtained by inversion calculation, and compare them with known geological data and actual measurement data to verify whether the inversion results are accurate.

[0123] Comparing the inversion results with known geological data and actual measurement data is an effective method to test the accuracy of the inversion results; if there is a large deviation between the inversion results and the known information, it indicates that there may be problems in the inversion process, such as incomplete data collection, unreasonable model establishment, improper algorithm selection, etc. By analyzing these deviations, the relevant steps can be improved and optimized to improve the quality of the surveying and mapping results.

[0124] Specifically, in the result analysis and evaluation process, the root mean square error and the correlation coefficient are used to quantitatively evaluate the inversion results. The root mean square error can measure the average error degree between the inversion results and the actual values, and the smaller the value is, the closer the inversion results are to the actual values. The correlation coefficient can reflect the linear correlation degree between the inversion results and the actual values, and the closer the value is to 1, the stronger the correlation between the two is. Using these two quantitative indicators, the inversion results can be evaluated from different angles, avoiding the limitations of subjective judgment, making the evaluation results more objective and accurate, and thus providing a scientific basis for the optimization and improvement of the inversion method.

[0125] The application also provides a marine engineering underwater geomagnetic anomaly joint inversion mapping system, which can be realized by performing the process steps of the marine engineering underwater geomagnetic anomaly joint inversion mapping method, i.e., the marine engineering underwater geomagnetic anomaly joint inversion mapping method can be understood by those skilled in the art as the preferred embodiment of the marine engineering underwater geomagnetic anomaly joint inversion mapping system.

[0126] According to the marine engineering underwater geomagnetic anomaly joint inversion mapping system provided by the application, the marine engineering underwater geomagnetic anomaly joint inversion mapping system comprises:

[0127] The data acquisition module acquires geomagnetic data of the marine area by using various underwater geomagnetic measurement devices to obtain geomagnetic anomaly data of various data sources;

[0128] The data preprocessing module preprocesses the geomagnetic anomaly data and unifies the geomagnetic anomaly data of different data sources to the same coordinate system;

[0129] The data fusion module fuses and processes the preprocessed various geomagnetic anomaly data to obtain fused geomagnetic anomaly data;

[0130] The inversion model establishment module establishes a geomagnetic anomaly inversion model according to the geological characteristics of the marine area and the prior information of the target object;

[0131] The inversion calculation module jointly calculates and solves the magnetic parameters according to the fused geomagnetic anomaly data and the geomagnetic anomaly inversion model.

[0132] In more preferred examples, the underwater geomagnetic measurement device comprises a shipborne magnetometer, a magnetometer carried by an underwater autonomous vehicle, and a seabed fixed magnetometer.

[0133] The geomagnetic data acquisition is performed at multiple positions and depths in the marine area.

[0134] The preprocessing includes data cleaning, denoising, and coordinate conversion, and the denoising adopts a wavelet transform denoising algorithm, a Kalman filter algorithm, and / or an adaptive filter algorithm.

[0135] The data fusion adopts weighted average, Kalman filtering and / or neural network fusion algorithm.

[0136] The data fusion module further comprises: quality evaluation of the fused geomagnetic anomaly data, if the evaluation index is greater than or equal to a preset threshold, the inversion calculation step is performed, if the evaluation index is lower than the preset threshold, the parameters of the data fusion algorithm are adjusted or the data fusion algorithm is replaced to perform data fusion again.

[0137] The evaluation index includes data integrity, consistency and accuracy.

[0138] In more preferred examples, in the geomagnetic data acquisition, according to the ship sailing speed, the geomagnetic gradient change of the measured sea area, the sampling interval of the shipborne magnetometer is dynamically adjusted:

[0139]

[0140] Where Δs represents the sampling interval;

[0141] υ represents the ship sailing speed;

[0142] G represents the geomagnetic gradient of the measured sea area;

[0143] k represents an empirical coefficient, and the value range is 1-5.

[0144] In more preferred examples, in the inversion model establishment module, according to the shape, size, buried depth, magnetization intensity parameter of the underground geological body or target object, the conductivity of seawater and / or ocean flow field, the model parameters are set.

[0145] Suppose that the underground geological body is composed of a plurality of simple-shaped magnetic bodies, for a single regular magnetic body:

[0146]

[0147] Where ∝ represents a proportional relationship;

[0148] ΔT represents the generated geomagnetic anomaly;

[0149] M represents the magnetization intensity of the magnetic body;

[0150] V represents the volume;

[0151] r represents the distance from the magnetic body to the observation point.

[0152] The geomagnetic anomaly inversion model is obtained by superimposing the geomagnetic anomaly generated by the magnetic body.

[0153] The inversion calculation utilizes an optimization algorithm, including genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm and / or conjugate gradient method.

[0154] The relationship model is established to separate the main earth magnetic field and the interference of the measurement noise:

[0155] T obs = T0+ ΔT + ε

[0156] wherein, ε represents the measurement noise, obeying normal distribution with mean of zero and variance of σ 2 ;

[0157] T obs represents the actual geomagnetic anomaly measurement at the observation point P;

[0158] ΔT represents the generated geomagnetic anomaly;

[0159] T0 represents the main earth magnetic field.

[0160] In more preferred examples, a result analysis and evaluation module is further included:

[0161] The magnetic parameters obtained by solving are analyzed and quantitatively evaluated by using the root mean square error and the correlation coefficient, and are compared with the known geological data and the actual measurement data to verify the accuracy of the results;

[0162] According to the accuracy of the verification results, the data source, the geomagnetic anomaly inversion model and / or the algorithm of the preprocessing, data fusion and / or inversion calculation are optimized.

[0163] Those skilled in the art know that, in addition to implementing the system provided by the present application and each device, module and unit thereof in the form of pure computer readable program code, the system provided by the present application and each device, module and unit thereof can also be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers and embedded microcontrollers to achieve the same functions by logically programming the method steps. Therefore, the system provided by the present application and each device, module and unit thereof can be considered as a hardware component, and the devices, modules and units included therein for achieving various functions can also be considered as structures within the hardware component; the devices, modules and units for achieving various functions can also be considered as both software modules for implementing the method and structures within the hardware component.

[0164] The specific embodiments of the present application are described above. It needs to be understood that the present application is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essential content of the present application. In the case of no conflict, the embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other.

Claims

1. A method for joint inversion mapping of underwater geomagnetic anomalies in marine engineering, characterized by: include: Data collection steps: using a variety of underwater geomagnetic measurement equipment to collect geomagnetic data in the ocean area and obtain geomagnetic anomaly data from multiple data sources; Data preprocessing step: preprocessing the geomagnetic anomaly data to unify the geomagnetic anomaly data from different data sources into the same coordinate system; Data fusion step, fusing the pre-processed multiple geomagnetic anomaly data to obtain fused geomagnetic anomaly data; Inversion model establishment steps, based on the geological characteristics of the ocean area and the prior information of the target object, establish a geomagnetic anomaly inversion model; Inversion calculation steps: Based on the fused geomagnetic anomaly data and the geomagnetic anomaly inversion model, a joint inversion calculation is performed to solve the magnetic parameters.

2. The method for joint inversion mapping of underwater geomagnetic anomalies in marine engineering according to claim 1, characterized in that: The underwater geomagnetic measurement equipment includes ship-borne magnetometers, magnetometers carried by underwater autonomous vehicles, and seabed fixed magnetometers; The geomagnetic data collection is performed at multiple locations and multiple depths in the ocean area; The preprocessing includes data cleaning, denoising and coordinate transformation, wherein the denoising adopts a wavelet transform denoising algorithm, a Kalman filter algorithm and / or an adaptive filter algorithm; The data fusion adopts weighted average, Kalman filter and / or neural network fusion algorithm; The data fusion step further includes: performing a quality assessment on the fused geomagnetic anomaly data, and if the assessment index is greater than or equal to a preset threshold, performing an inversion calculation step; if the assessment index is lower than the preset threshold, adjusting the parameters of the data fusion algorithm or replacing the data fusion algorithm to perform data fusion again; The evaluation indicators include data completeness, consistency and accuracy.

3. The method for joint inversion mapping of underwater geomagnetic anomalies in marine engineering according to claim 2, characterized in that: During the geomagnetic data collection, the sampling interval of the shipboard magnetometer is dynamically adjusted according to the ship's navigation speed and the change of the geomagnetic gradient in the measurement sea area: Where, Δs represents the sampling interval; υ represents the ship's sailing speed; G represents the geomagnetic gradient of the measurement sea area; k represents the empirical coefficient, and its value range is 1-5.

4. The method for joint inversion mapping of underwater geomagnetic anomalies in marine engineering according to claim 1, characterized in that: In the inversion model establishment step, model parameters are set according to the shape, size, burial depth, magnetization parameters, seawater conductivity and / or ocean current field of the underground geological body or target object; Assume that the underground geological body is composed of several magnetic bodies of simple shapes. For a single regular magnetic body: Among them, ∝ indicates a proportional relationship; ΔT represents the generated geomagnetic anomaly; M represents the magnetization intensity of the magnetic body; V stands for volume; r represents the distance from the magnetic body to the observation point; Superimpose the geomagnetic anomaly produced by the magnetic body to obtain the geomagnetic anomaly inversion model; The inversion calculation utilizes an optimization algorithm, including a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm, and / or a conjugate gradient method; Establish a relationship model to separate the interference of the Earth's main magnetic field and measurement noise: T obs =T0+△T+ε Among them, ε represents the measurement noise, which has a mean of zero and a variance of σ 2 Normal distribution; Value T obs represents the actual geomagnetic anomaly measurement at the observation point P; ΔT represents the generated geomagnetic anomaly; T0 represents the Earth's main magnetic field.

5. The method for joint inversion mapping of underwater geomagnetic anomalies in marine engineering according to claim 1, characterized in that: It also includes the results analysis and evaluation steps: The root mean square error and correlation coefficient are used to analyze and quantitatively evaluate the magnetic parameters obtained, and compared with known geological data and actual measurement data to verify the accuracy of the results; Optimize the data source, geomagnetic anomaly inversion model and / or preprocessing, data fusion and / or inversion calculation algorithm based on the accuracy of the verification results.

6. A marine engineering underwater geomagnetic anomaly joint inversion mapping system, characterized by: include: The data acquisition module acquires geomagnetic anomaly data from multiple data sources obtained by collecting geomagnetic data of ocean areas using multiple underwater geomagnetic measurement equipment; Data preprocessing module, preprocesses geomagnetic anomaly data and unifies geomagnetic anomaly data from different data sources into the same coordinate system; The data fusion module fuses the pre-processed multiple geomagnetic anomaly data to obtain fused geomagnetic anomaly data; The inversion model building module builds a geomagnetic anomaly inversion model based on the geological characteristics of the ocean area and the prior information of the target object; The inversion calculation module performs joint inversion calculation based on the fused geomagnetic anomaly data and the geomagnetic anomaly inversion model to solve the magnetic parameters.

7. The marine engineering underwater geomagnetic anomaly joint inversion mapping system according to claim 6, characterized in that: The underwater geomagnetic measurement equipment includes ship-borne magnetometers, magnetometers carried by underwater autonomous vehicles, and seabed fixed magnetometers; The geomagnetic data collection is performed at multiple locations and multiple depths in the ocean area; The preprocessing includes data cleaning, denoising and coordinate transformation, wherein the denoising adopts a wavelet transform denoising algorithm, a Kalman filter algorithm and / or an adaptive filter algorithm; The data fusion adopts weighted average, Kalman filter and / or neural network fusion algorithm; The data fusion module further includes: performing a quality assessment on the fused geomagnetic anomaly data, and if the assessment index is greater than or equal to a preset threshold, performing an inversion calculation step; if the assessment index is lower than the preset threshold, adjusting the parameters of the data fusion algorithm or replacing the data fusion algorithm to perform data fusion again; The evaluation indicators include data completeness, consistency and accuracy.

8. The marine engineering underwater geomagnetic anomaly joint inversion mapping system according to claim 7, characterized in that: During the geomagnetic data collection, the sampling interval of the shipboard magnetometer is dynamically adjusted according to the ship's navigation speed and the change of the geomagnetic gradient in the measurement sea area: Where, Δs represents the sampling interval; υ represents the ship's sailing speed; G represents the geomagnetic gradient of the measurement sea area; k represents the empirical coefficient, and its value range is 1-5.

9. The marine engineering underwater geomagnetic anomaly joint inversion mapping system according to claim 6, characterized in that: In the inversion model building module, model parameters are set according to the shape, size, burial depth, magnetization parameters, seawater conductivity and / or ocean current field of the underground geological body or target object; Assume that the underground geological body is composed of several magnetic bodies of simple shapes. For a single regular magnetic body: Among them, ∝ indicates a proportional relationship; ΔT represents the generated geomagnetic anomaly; M represents the magnetization intensity of the magnetic body; V stands for volume; r represents the distance from the magnetic body to the observation point; Superimpose the geomagnetic anomaly produced by the magnetic body to obtain the geomagnetic anomaly inversion model; The inversion calculation utilizes an optimization algorithm, including a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm, and / or a conjugate gradient method; Establish a relationship model to separate the interference of the Earth's main magnetic field and measurement noise: T obs =T0+△T+ε Among them, ε represents the measurement noise, which has a mean of zero and a variance of σ 2 Normal distribution; Value T obs represents the actual geomagnetic anomaly measurement at the observation point P; ΔT represents the generated geomagnetic anomaly; T0 represents the Earth's main magnetic field.

10. The marine engineering underwater geomagnetic anomaly joint inversion mapping system according to claim 6, characterized in that: Also includes result analysis and evaluation modules: The root mean square error and correlation coefficient are used to analyze and quantitatively evaluate the magnetic parameters obtained, and compared with known geological data and actual measurement data to verify the accuracy of the results; Optimize the data source, geomagnetic anomaly inversion model and / or preprocessing, data fusion and / or inversion calculation algorithm based on the accuracy of the verification results.

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