A method for analyzing active faults in marine areas based on fusion interpretation of acoustic stratigraphic data

Abstract

The present invention discloses a method for analyzing active faults in a sea area based on the fusion interpretation of acoustic stratigraphic data, which relates to the technical field of sea area data analysis, and collects acoustic data including seabed and shallow stratum profile data and multi-channel seismic data, and pre-processes the collected acoustic data; performs data registration on the pre-processed acoustic data, and aligns the data to the same reference plane by comparing and analyzing the horizons in different data sets; applies a data fusion strategy to fuse the seabed and shallow stratum profile data and multi-channel seismic data. The present invention extracts the activity characteristics of the fault zone, combines the regional geological background and geological structure information, calculates the geological risk coefficient, and divides different geological risk levels accordingly, which not only takes into account the activity of the fault zone itself, but also integrates the complexity of the regional geological environment, making the evaluation result more reliable, thereby providing a scientific basis for the prediction and prevention of geological disasters.

Description

Technical Field

[0001] The present invention relates to the technical field of marine data analysis, and in particular to a marine active fracture analysis method based on acoustic stratum data fusion interpretation. Background Art

[0002] Active marine faults refer to structures that have been active since the late Quaternary period 100,000 to 120,000 years ago, are currently active, and may still be active in a certain period of time in the future. They are closely related to the activity of submarine earthquakes, which often pose serious threats to human life and property as well as marine engineering facilities. Since the 21st century, the construction of marine engineering has increased. The safety evaluation of nuclear power plants, oil drilling platforms, cross-sea bridges and submarine tunnels is closely related to the active marine faults in the site selection area. The spatiotemporal characteristics of active marine faults have important indicative significance for the activity of active faults. The research results on the spatiotemporal characteristics of active marine faults can provide a scientific basis for the safety evaluation of marine engineering.

[0003] At present, high-resolution acoustic detection has become one of the main detection methods in the study of seafloor active fault detection. It has gradually developed from the initial single acoustic detection method to a combination of multiple acoustic detection methods to detect the structural characteristics of seafloor active faults. However, most studies simply combine various acoustic detection methods to identify seafloor fault characteristics. There is room for further improvement in the fusion and utilization of acoustic data, so as to improve the accuracy of depicting the spatiotemporal characteristics of seafloor active faults. Therefore, how to fuse shallow stratigraphic profiles and multi-channel seismic data to interpret the characteristics of seafloor active faults is a problem we need to solve. To this end, a method for analyzing active faults in the sea based on the fusion and interpretation of acoustic stratigraphic data is proposed. Summary of the invention

[0004] The present invention aims to provide a method for analyzing active faults in marine areas based on the fusion interpretation of acoustic stratigraphic data, so as to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for analyzing active faults in marine areas based on fusion interpretation of acoustic stratigraphic data comprises the following steps:

[0007] Step 1: Acquire acoustic data including seabed and shallow stratum profile data and multi-channel seismic data, and pre-process the acquired acoustic data, including filtering and denoising, to improve data quality and lay the foundation for subsequent analysis;

[0008] Step 2: perform data registration on the preprocessed acoustic data to ensure that they are in the same spatial and temporal frame, and align the data to the same reference plane by comparing and analyzing the layers in different data sets for subsequent data fusion;

[0009] Step 3, applying data fusion strategy to fuse the seabed and shallow stratum profile data and multi-channel seismic data to generate fused acoustic stratigraphic data;

[0010] Step 4: extract the characteristics of the seafloor active faults based on the fused acoustic stratigraphic data, and comprehensively analyze the characteristics of the seafloor active faults to identify the structural characteristics of the seafloor active faults;

[0011] Step 5: Based on the extracted and identified features, interpret the active seafloor faults to assess potential geological risks and conduct a comprehensive analysis of the interpretation results.

[0012] A further improvement of the technical solution of the present invention is that the acquisition and preprocessing process of the acoustic data is as follows:

[0013] A shallow layer profiler and a multi-channel seismic system are deployed in the target area to cover the entire target area to collect acoustic data of the seabed and shallow layer structure and multi-channel seismic signals. A signal conditioning front end and FPGA (field programmable gate array) are configured to adapt to seismic signals with extremely low signal response levels. The shallow layer profiler is then used to collect seabed and shallow layer profile data, record the reflected wave amplitude and frequency information, and use the signal conditioning front end and FPGA (field programmable gate array) technology to collect multi-channel seismic signals. Since the acoustic data of the seabed and shallow layer structure and multi-channel seismic signals are often weak and subject to noise interference, the signal conditioning front end can be used to pre-process the original signal, including amplification and filtering, to improve the signal-to-noise ratio and anti-interference ability of the signal. Wave processing, the signal conditioning front end can effectively improve the signal-to-noise ratio of the signal, provide high-quality input for subsequent data processing and analysis, and can filter out some noise interference, improve the stability and reliability of the signal. Since the shallow layer profiler and multi-channel seismic system need to process a large amount of acoustic data in real time, the real-time and parallel requirements of data processing are high. FPGA (field programmable gate array) technology is suitable for real-time processing of large-scale data with its high parallelism, high-speed processing capability and programmability. Through FPGA (field programmable gate array), multiple tasks can be processed in parallel, improving the efficiency of data processing and meeting real-time requirements. Compared with traditional processors, FPGA (field programmable gate array) has lower power consumption when implementing the same function, which is conducive to the long-term stable operation of the system;

[0014] The collected acoustic data are pre-processed by filtering, denoising and signal enhancement, wherein a bandpass filter is applied to the collected acoustic data to limit the frequency range of the signal to enhance the clarity of the signal and eliminate noise and unnecessary frequency components, and a wavelet transform denoising method is applied to improve the signal-to-noise ratio to ensure data quality, reduce random noise in the data, enhance seismic reflection signals, and make the characteristics of the reflection waves more obvious through signal enhancement, which is convenient for subsequent data processing and interpretation;

[0015] Normalize the preprocessed acoustic data to scale the data to the same level for easy comparison and analysis, and segment the continuous acoustic data to obtain individual acoustic data samples for further analysis;

[0016] The segmented individual acoustic data samples are labeled to identify their different geological features, and the pre-processed data are integrated and stored in the data warehouse for backup and archiving to facilitate future use and analysis.

[0017] A further improvement of the technical solution of the present invention is that the data registration and data alignment process of the acoustic data is as follows:

[0018] Collect high-precision acoustic data of the target area and organize them into acoustic data sets, which are used as reference data sets. The reference data sets include images, GPS, INS (inertial navigation system) data, and manually marked segmentation and tracking results. The INS (inertial navigation system) data is fused with the GPS data to further improve the accuracy and reliability of data fusion, and to improve the understanding of the seabed and shallow strata structure, so as to more accurately perform geological interpretation and risk assessment;

[0019] Use geographic information system (GIS) tools to convert the coordinates of all data to the WGS84 coordinate system and convert all timestamps to UTC time to unify the timestamp format;

[0020] Use seismic interpretation software (Petrel) to identify key geological horizon information, including but not limited to the amplitude, frequency, phase, etc. of the reflected wave, and compare horizons in different data to determine common geological features, and record the comparison results, including the description and location of key geological features such as reflection interfaces and fault zones;

[0021] Based on the results of geological feature comparison, select characteristic points with the same spatial position as control points in the data to be registered. It is necessary to ensure that the control points are representative and can accurately reflect the spatial relationship of the data. Then apply the registration algorithm to align the data to be registered to the reference data set through the control points, and calculate the root mean square error after registration to evaluate the accuracy of the registration. If the accuracy does not meet the requirements, further adjust the registration algorithm.

[0022] By comparing and analyzing the stratigraphic information of different data, the data are aligned to the same reference plane, and the aligned data are fused to form a unified acoustic feature data set.

[0023] A further improvement of the technical solution of the present invention is that the generation process of the fused acoustic formation data is as follows:

[0024] Extract seafloor and shallow-sediment profile data and multi-channel seismic data from the acoustic feature dataset, and build a variational assimilation model based on the observed data and prior information;

[0025] The variational assimilation model is used to comprehensively analyze the characteristics of seabed and shallow stratum profile data and multi-channel seismic data, estimate the stratum state, and continuously adjust the estimated value of the stratum state through an iterative optimization process until the optimal solution is reached. Based on the results of the assimilation model, acoustic stratigraphic data with spatial continuity are generated, which can accurately reflect the structure and characteristics of the seabed and shallow strata.

[0026] In the generated acoustic stratigraphic data, missing or sparse data points caused by observation condition limitations or errors in the data acquisition process are identified, and the values ​​of unknown data points are predicted based on the values ​​and positions of known data points using the Kriging interpolation method. The results of the Kriging interpolation method are then used to fill in the missing or sparse data points to obtain complete stratigraphic information, ensuring that the filled data are consistent and continuous with the original data in terms of space and value.

[0027] According to the characteristics of seabed and shallow stratum profile data and multi-channel seismic data, a statistical model is constructed, and the seabed and shallow stratum profile data and multi-channel seismic data are input into the statistical model for fusion processing. Through model calculation, the fused acoustic stratigraphic data is generated.

[0028] A further improvement of the technical solution of the present invention is that the identification process of the characteristics of the submarine active fault structure is as follows:

[0029] Perform feature analysis on the fused acoustic stratigraphic data to extract features related to active seafloor faults in the acoustic stratigraphic data. The features of active seafloor faults include reflection wave features, disturbance features, amplitude change features, and phase change features. The reflection wave features are obtained by observing the shape, intensity, and continuity of the reflection waves in the acoustic stratigraphic data to identify reflection anomalies caused by fault zones. The disturbance features are obtained by analyzing disturbance phenomena in the formation, such as formation faults and sequence disorder. The amplitude change features are obtained by measuring the amplitude changes of the reflection waves. A sudden increase or decrease in the amplitude may indicate the existence of a fault zone. The phase change features are obtained by analyzing the phase changes of the reflection waves. Discontinuity or mutation in the phase may indicate a fracture in the formation.

[0030] According to the distribution of reflected waves and disturbance characteristics, the geometric morphology of the fault zone is drawn, the extension direction of the fault zone is determined, and its relationship with the regional tectonic line is analyzed. In combination with geological knowledge, the fault properties of the fault zone are analyzed, the direction and displacement of the stratum fault are observed, and the movement direction of the fault is inferred;

[0031] Using the deformation and displacement data in the acoustic stratigraphic data, the fault activity value is calculated, the changing trend of the fault activity value is analyzed, and the activity trend of the fault zone is evaluated;

[0032] Combine the extracted active fault features with the regional geological background to analyze the causes of the fault zone, integrate the geometric morphology, fault properties, and activity trend data of the fault zone, and identify the structural characteristics of the fault zone;

[0033] Using geological modeling software, based on the activity trends and structural characteristic data of the fault zone, the evolution process of the fault is simulated, and the evolution characteristics and change trends of the fault zone in different periods are analyzed.

[0034] A further improvement of the technical solution of the present invention is that the calculation formula of the fracture activity value is:

[0035] ;

[0036] Where F is the fault activity value, is the average value of the reflected wave amplitude change, indicating the overall change of the reflected wave amplitude. It is the reference value of the reflected wave amplitude change, which is used to compare with the actual amplitude change. is the sensitivity factor of amplitude change, which is used to adjust the response speed of the exponential function. is the baseline value of the phase change characteristic, reflecting the overall level of phase change. It is the direction of stratum faulting and the maximum displacement, indicating the energy of fault activity. It is the benchmark threshold of stratum fault, which is used to determine whether the displacement exceeds the normal range. It is the limit value of stratum dislocation, indicating the maximum value that stratum dislocation may reach. It should be noted that the value range of F is between 0 and 1, where 1 indicates that the fault activity is at the highest level and 0 indicates that there is no fault activity.

[0037] A further improvement of the technical solution of the present invention is that the interpretation process of the active seafloor fault is:

[0038] Extract the activity trend data, structural characteristic data and geological information data of the fault zone, perform standardization processing, and use the regional geological background and geological structural line information to establish a geological framework model, including the distribution, thickness and lithology of the strata. Among them, the activity trend data of the fault zone includes the displacement rate, activity frequency and seismic activity of the fault zone. The structural characteristic data includes the geometric shape of the fault zone, the nature of the fault (normal fault, reverse fault, strike-slip fault), the dislocation of the strata and the distribution of lithology. The geological information data includes the regional geological background, geological structural line and stratigraphic sedimentary sequence.

[0039] Add the geometric shape and fault property data of the fault zone to the geological framework model to form a geological model that includes the fault zone, and compare the output of the geological model with the actual geological conditions to verify the accuracy of the model. According to the geometric shape, stratigraphic dislocation and lithology distribution information of the fault zone, analyze the properties of the fault, and determine the type of the fault zone in combination with the fault properties and regional geological background;

[0040] Conduct detailed analysis of the structural characteristics of different types of fault zones, including the width, depth, morphological changes, and degree of stratigraphic dislocation of the fault zones. Use the activity trend data of the fault zones to study the activity patterns of the fault zones, including activity cycles, activity intensity, and seismic activity.

[0041] Combined with the regional geological background and geological tectonic line information, the genesis mechanism of the fault zone, including crustal movement and plate tectonics, is clarified, and then the active seabed faults are interpreted, and a fault zone distribution map is drawn, with the type, location, and activity nature of the fault zone clearly marked on the map.

[0042] A further improvement of the technical solution of the present invention is that the evaluation process of the potential geological risk is as follows:

[0043] Calculate the geological risk factor of the submarine fault zone based on the interpretation results of the submarine active faults and the data in the fault zone distribution map;

[0044] According to the type of fault zone, the nature of activity and the regional geological background, analyze the relevant geological disaster types, such as submarine landslides, tsunamis, earthquakes, etc., and evaluate the severity of the geological disaster types. Combined with the geological risk coefficient, different geological risk levels are divided into low geological risk level, medium geological risk level and high geological risk level, and the corresponding evaluation thresholds are divided for each geological risk level to evaluate the potential geological risks;

[0045] Prepare a risk assessment report, including the interpretation results of the fault zone, the risk factor calculation process, the risk level classification results and the assessment results of potential geological hazards.

[0046] A further improvement of the technical solution of the present invention is that the calculation formula of the geological risk coefficient is:

[0047] ;

[0048] Among them, R is the geological risk factor, W is the width of the fault zone, and D is the depth of the fault zone. and It is the reference value of the fault zone width and fault zone depth, which can be set according to the regional geological background. is the activity period of the fault zone (in years), is the maximum possible value of the activity period, which can be set based on the historical data of the region. is the activity intensity of the fault zone (displacement rate, seismic moment, etc.), is the maximum possible value of activity intensity, is the degree of stratigraphic dislocation in the fault zone (fault displacement), is the baseline threshold of the degree of formation fault. When this value is exceeded, the risk is considered to increase significantly. k is an adjustment parameter used to control the sensitivity of the degree of formation fault to the risk. is the seismic activity energy of the fault zone (seismic moment release rate), is the maximum possible value of the energy of seismic activity.

[0049] A further improvement of the technical solution of the present invention is that: a plurality of the geological risk levels correspond to a plurality of the evaluation thresholds, wherein the evaluation thresholds include an upper threshold and a lower threshold;

[0050] The multiple geological risk levels and the multiple evaluation thresholds satisfy the following relationship:

[0051] Low geological risk level: ; It means that the probability of geological disasters in the area is low and the potential harm is small;

[0052] Medium geological risk level: ; The probability of geological disasters in this area is moderate, and the potential degree of harm is medium;

[0053] High geological risk level: ; It means that the probability of geological disasters in this area is high and the potential harm is serious;

[0054] Among them, R is the geological risk coefficient, is the lower threshold corresponding to the medium geological risk level and the upper threshold corresponding to the low geological risk level, is the lower threshold corresponding to the high geological risk level and the upper threshold corresponding to the medium geological risk level, , .

[0055] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0056] The present invention provides a method for analyzing active faults in marine areas based on the fusion interpretation of acoustic stratigraphic data. The method extracts the activity characteristics of the fault zone, combines the regional geological background and geological structure information, calculates the geological risk coefficient, and divides different geological risk levels accordingly. It not only takes into account the activity of the fault zone itself, but also incorporates the complexity of the regional geological environment, making the evaluation result more reliable, thereby providing a scientific basis for the prediction and prevention of geological disasters.

[0057] The present invention provides a method for analyzing active faults in marine areas based on the fusion interpretation of acoustic stratigraphic data. By adding the geometric morphology and fault property data of the fault zone to the geological framework model, a geological model including the fault zone is formed, which can more intuitively display the geological structure and characteristics. Moreover, by analyzing the geometric morphology, fault properties, stratigraphic dislocation and lithology distribution information of the fault zone, the type of the fault zone can be more accurately determined, which is helpful to understand the active nature of the fault zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0059] Figure 1 is a flow chart of the method of the present invention;

[0060] Figure 2 This is a flow chart for identifying the characteristics of active seafloor fault structures of the present invention;

[0061] Figure 3 This is a flow chart for interpreting active seafloor faults of the present invention;

[0062] Figure 4 This is a flow chart for assessing potential geological risks of the present invention. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] Embodiment 1, as Figure 1 , Figure 2As shown, the present invention provides a method for analyzing active faults in marine areas based on fusion interpretation of acoustic stratigraphic data, comprising the following steps:

[0065] Step 1: Collect acoustic data including seabed and shallow formation profile data and multi-channel seismic data, and pre-process the collected acoustic data, including filtering and denoising, to improve data quality and lay the foundation for subsequent analysis. Deploy a shallow formation profiler and a multi-channel seismic system in the target area to cover the entire target area to collect acoustic data of seabed and shallow formation structure and multi-channel seismic signals, and configure a signal conditioning front end and FPGA (field programmable gate array) to adapt to seismic signals with extremely low signal response levels. Then, use the shallow formation profiler to collect seabed and shallow formation profile data, record the amplitude and frequency information of the reflected wave, and use the signal conditioning front end and FPGA (field programmable gate array) to collect the seabed and shallow formation profile data. Array) technology is used to collect multi-channel seismic signals. Since the acoustic data of the seabed and shallow stratum structure and multi-channel seismic signals are often weak and there is noise interference, the signal conditioning front end can be used to pre-process the original signal, including amplification and filtering, to improve the signal-to-noise ratio and anti-interference ability of the signal. Through amplification and filtering, the signal conditioning front end can effectively improve the signal-to-noise ratio, provide high-quality input for subsequent data processing and analysis, and can filter out some noise interference, improve the stability and reliability of the signal. Since the shallow stratum profiler and multi-channel seismic system need to process a large amount of acoustic data in real time, the real-time and parallel requirements of data processing are high, FPGA (field Field Programmable Gate Array (FPGA) technology is suitable for real-time processing of large-scale data with its high parallelism, high-speed processing capability and programmability. FPGA (Field Programmable Gate Array) can process multiple tasks in parallel, improve the efficiency of data processing and meet real-time requirements. Compared with traditional processors, FPGA (Field Programmable Gate Array) has lower power consumption when implementing the same function, which is conducive to the long-term stable operation of the system. The collected acoustic data is pre-processed by filtering, denoising and signal enhancement. Among them, a bandpass filter is used to filter the collected acoustic data to limit the frequency range of the signal to enhance the clarity of the signal and eliminate noise and unnecessary frequency components. Use wavelet transform denoising method to improve the signal-to-noise ratio and ensure data quality, so as to reduce random noise in the data and enhance seismic reflection signals. Through signal enhancement, the characteristics of the reflection waves are more obvious, which is convenient for subsequent data processing and interpretation. Normalize the pre-processed acoustic data and scale the data to the same magnitude for comparison and analysis. Segment the continuous acoustic data to obtain individual acoustic data samples for further analysis. Label the segmented individual acoustic data samples to identify their different geological characteristics. Integrate the pre-processed data and store them in the data warehouse for backup and archiving for future use and analysis.

[0066] Step 2: Perform data registration on the preprocessed acoustic data to ensure that they are in the same spatial and temporal frame. By comparing and analyzing the layers in different data sets, the data are aligned to the same reference plane for subsequent data fusion. Collect high-precision acoustic data of the target area and organize them into an acoustic data set, which is used as a reference data set. The reference data set contains image, GPS, INS (inertial navigation system) data, and includes manually marked segmentation and tracking results. The INS (inertial navigation system) data is fused with the GPS data to further improve the accuracy and reliability of data fusion, improve the understanding of the seabed and shallow stratum structure, and thus more accurately perform geological interpretation and risk assessment. It is suitable for reference for acoustic data registration, and then check the preprocessed acoustic data to ensure data integrity and quality, confirm the timestamp and spatial coordinate information of each data for subsequent registration, and use geographic information system (GIS) tools to convert the coordinates of all data into Switch to the WGS84 coordinate system, convert all timestamps to UTC time, unify the timestamp format, use seismic interpretation software (Petrel) to identify the main geological layer information, including but not limited to the amplitude, frequency, phase, etc. of the reflection wave, and compare the layers in different data to determine the common geological features, record the comparison results, including the description and location of key geological features such as reflection interfaces and fault zones, and select characteristic points of the same spatial position as control points in the data to be registered based on the geological feature comparison results. It is necessary to ensure that the control points are representative and can accurately reflect the spatial relationship of the data, and apply the registration algorithm to align the data to be registered to the reference data set through the control points, calculate the root mean square error after registration, and evaluate the accuracy of the registration. If the accuracy does not meet the requirements, further adjust the registration algorithm, align the data to the same reference plane by comparing and analyzing the layer information of different data, and fuse the aligned data to form a unified acoustic feature data set;

[0067] Step 3: Apply the data fusion strategy to fuse the seabed and shallow layer profile data and multi-channel seismic data to generate fused acoustic stratigraphic data; extract the seabed and shallow layer profile data and multi-channel seismic data from the acoustic feature data set to ensure that the extracted data has sufficient resolution and signal-to-noise ratio to support subsequent data assimilation, interpolation and fusion processing; and construct a variational assimilation model based on the observed data and prior information; use the variational assimilation model to comprehensively analyze the characteristics of the seabed and shallow layer profile data and multi-channel seismic data to estimate the stratigraphic state; and continuously adjust the estimated value of the stratigraphic state through an iterative optimization process until the optimal solution is reached; and generate acoustic stratigraphic data with spatial continuity based on the results of the assimilation model to accurately Accurately reflect the structure and characteristics of the seabed and shallow strata, identify missing or sparse data points caused by observation condition restrictions or errors in the data acquisition process in the generated acoustic stratigraphic data, use the Kriging interpolation method to predict the values ​​of unknown data points based on the values ​​and positions of known data points, and use the results of the Kriging interpolation method to fill in the missing or sparse data points to obtain complete stratigraphic information, ensuring that the filled data is consistent and continuous with the original data in space and value, and construct a statistical model based on the characteristics of the seabed and shallow strata profile data and multi-channel seismic data, input the seabed and shallow strata profile data and multi-channel seismic data into the statistical model for fusion processing, and generate fused acoustic stratigraphic data through model calculation;

[0068] Step 4, based on the fused acoustic stratigraphic data, extract the characteristics of the seabed active faults, and comprehensively analyze the characteristics of the seabed active faults to identify the structural characteristics of the seabed active faults. Perform feature analysis on the fused acoustic stratigraphic data to extract the relevant characteristics of the seabed active faults in the acoustic stratigraphic data, wherein the seabed active fault characteristics include reflection wave characteristics, disturbance characteristics, amplitude change characteristics and phase change characteristics. The reflection wave characteristics are obtained by observing the shape, intensity and continuity of the reflection waves in the acoustic stratigraphic data to identify the reflection anomalies caused by the fault zone. The disturbance characteristics are obtained by analyzing the disturbance phenomena in the formation, such as formation faults, chaotic stratigraphic sequences, etc. The amplitude change characteristics are obtained by measuring the amplitude changes of the reflection waves. The sudden increase or decrease of the amplitude may indicate the existence of the fault zone. The phase change characteristics are obtained by analyzing the phase changes of the reflection waves. The inconsistency of the phase Continuous or sudden changes may indicate the fracture of the stratum. According to the distribution of reflected waves and disturbance characteristics, the geometric morphology of the fault zone is drawn, the extension direction of the fault zone is determined, and its relationship with the regional tectonic line is analyzed. In combination with geological knowledge, the fault properties of the fault zone are analyzed, the direction and displacement of the stratum fault are observed, and the movement direction of the fault is inferred. The deformation and displacement data in the acoustic stratigraphic data are used to calculate the fracture activity value, analyze the change trend of the fracture activity value, and evaluate the activity trend of the fracture zone. The extracted active fracture characteristics are combined with the regional geological background to analyze the cause of the fracture zone. The geometric morphology, fault properties, and activity trend data of the fracture zone are integrated to identify the structural characteristics of the fracture zone. The geological modeling software is used to simulate the evolution process of the fracture according to the activity trend and structural characteristic data of the fracture zone, and the evolution characteristics and change trend of the fracture zone in different periods are analyzed;

[0069] Furthermore, the calculation formula of the fracture activity value is:

[0070] ;

[0071] Where F is the fault activity value, is the average value of the reflected wave amplitude change, indicating the overall change of the reflected wave amplitude. It is the reference value of the reflected wave amplitude change, which is used to compare with the actual amplitude change. is the sensitivity factor of amplitude change, which is used to adjust the response speed of the exponential function. is the baseline value of the phase change characteristic, reflecting the overall level of phase change. It is the direction of stratum faulting and the maximum displacement, indicating the energy of fault activity. It is the benchmark threshold of stratum fault, which is used to determine whether the displacement exceeds the normal range. is the limit value of stratum dislocation, indicating the maximum value that stratum dislocation may reach. It should be noted that It is an exponential decay function, which is used to evaluate the deviation between the amplitude change and the reference value. When the amplitude change is close to the reference value, the term approaches 1. When the difference between the amplitude change and the reference value increases, the term decreases rapidly. is a root function, which is used to reflect the intensity of phase change. The root function can increase or decrease smoothly, making the impact of phase change more gentle. It is a limit function, which is used to evaluate whether the direction and displacement of the stratum fault are beyond the normal range. When the displacement is within the threshold range, the item is 1. When the displacement exceeds the limit value, the item decreases until it is 0. The value range of F is between 0 and 1, where 1 indicates that the fault activity is at the highest level and 0 indicates that there is no fault activity. As the fault activity value increases, the activity of the fault zone increases, which helps to evaluate the activity trend of the fault zone and the potential geological risks.

[0072] Step 5: Based on the extracted and identified features, interpret the active seafloor faults to assess potential geological risks and conduct a comprehensive analysis of the interpretation results.

[0073] Embodiment 2, as Figure 3 , Figure 4 As shown, based on Example 1, the present invention provides a technical solution: Preferably, the interpretation process of the seafloor active fault is:

[0074] The activity trend data, structural characteristic data and geological information data of the fault zone are extracted and standardized, and the regional geological background and geological structural line information are used to establish a geological framework model, including the distribution, thickness and lithology of the strata. Among them, the activity trend data of the fault zone include the displacement rate, activity frequency and seismic activity of the fault zone. The structural characteristic data include the geometric shape of the fault zone, the fault properties (normal fault, reverse fault, strike-slip fault), the stratum dislocation and lithology distribution. The geological information data include the regional geological background, geological structural line and stratigraphic sedimentary sequence. The geometric shape and fault property data of the fault zone are added to the geological framework model to form a geological model including the fault zone, and the output results of the geological model are compared with the actual geological situation. The accuracy of the model is verified by comparing the fault conditions. According to the geometric shape of the fault zone, the formation dislocation, and the lithology distribution information, the nature of the fault is analyzed. In combination with the fault properties and the regional geological background, the type of fault zone is determined. The structural characteristics of different types of fault zones are analyzed in detail, including the width, depth, morphological changes, and degree of formation dislocation of the fault zone. The activity trend data of the fault zone are used to study the activity laws of the fault zone, including the activity cycle, activity intensity, and seismic activity. In combination with the regional geological background and geological tectonic line information, the causes of the fault zone, including crustal movement and plate tectonics, are clarified. Then, the submarine active faults are interpreted, and a fault zone distribution map is drawn, in which the type, location, and activity nature of the fault zone are clearly marked.

[0075] Furthermore, the assessment process of potential geological risks is as follows:

[0076] Based on the interpretation results of submarine active faults and the data in the fault zone distribution map, the geological risk coefficient of the submarine fault zone is calculated. According to the type of fault zone, the nature of activity and the regional geological background, the relevant geological disaster types, such as submarine landslides, tsunamis, earthquakes, etc., are analyzed, and the severity of the geological disaster types is evaluated. In combination with the geological risk coefficient, different geological risk levels are divided into low geological risk level, medium geological risk level and high geological risk level, and corresponding evaluation thresholds are set for each geological risk level to evaluate potential geological risks. A risk assessment report is prepared, including the interpretation results of the fault zone, the risk coefficient calculation process, the risk level division results and the assessment results of potential geological disasters. The report should contain clear data charts and visual displays so that readers can intuitively understand the assessment process and results. The interpretation results are compared and verified with existing geological survey data, seismic monitoring data, etc., and the accuracy and reliability of the interpretation results are checked to ensure that there are no missed or misjudged fault zones.

[0077] Furthermore, the calculation formula of the geological risk factor is:

[0078] ;

[0079] Among them, R is the geological risk factor, W is the width of the fault zone, and D is the depth of the fault zone. and It is the reference value of the fault zone width and fault zone depth, which can be set according to the regional geological background. is the activity period of the fault zone (in years), is the maximum possible value of the activity period, which can be set based on the historical data of the region. is the activity intensity of the fault zone (displacement rate, seismic moment, etc.), is the maximum possible value of activity intensity, is the degree of stratigraphic dislocation in the fault zone (fault displacement), is the baseline threshold of the degree of formation fault. When this value is exceeded, the risk is considered to increase significantly. k is an adjustment parameter used to control the sensitivity of the degree of formation fault to the risk. is the seismic activity energy of the fault zone (seismic moment release rate), is the maximum possible value of seismic activity energy. It should be noted that the value range of R is between 0 and 1, and the larger the value, the higher the risk;

[0080] In addition, multiple geological risk levels correspond to multiple evaluation thresholds, where the evaluation thresholds include an upper threshold and a lower threshold;

[0081] Multiple geological risk levels and multiple evaluation thresholds satisfy the following relationship:

[0082] Low geological risk level: ; It means that the probability of geological disasters in the area is low and the potential harm is small;

[0083] Medium geological risk level: ; The probability of geological disasters in this area is moderate, and the potential degree of harm is medium;

[0084] High geological risk level: ; It means that the probability of geological disasters in this area is high and the potential harm is serious;

[0085] Among them, R is the geological risk coefficient, is the lower threshold corresponding to the medium geological risk level and the upper threshold corresponding to the low geological risk level, is the lower threshold corresponding to the high geological risk level and the upper threshold corresponding to the medium geological risk level, , .

[0086] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for analyzing active faults in marine areas based on fusion interpretation of acoustic stratigraphic data, characterized in that: The following steps are involved: Step 1, collecting acoustic data including seabed and shallow stratum profile data and multi-channel seismic data, and preprocessing the collected acoustic data; Step 2: perform data registration on the preprocessed acoustic data, and align the data to the same reference plane by comparing and analyzing the layers in different data sets. The data registration and data alignment process of the acoustic data is as follows: Collect high-precision acoustic data of the target area and organize them into an acoustic data set, which is used as a reference data set. The reference data set contains image, GPS, and INS data, and includes manually marked segmentation and tracking results, and fuses INS data with GPS data. Use geographic information system tools to convert the coordinates of all data to the WGS84 coordinate system and convert all timestamps to UTC time to unify the timestamp format; Use seismic interpretation software to identify the main geological horizon information, compare the horizons in different data, determine common geological features, and record the comparison results; Based on the geological feature comparison results, characteristic points with the same spatial position are selected as control points in the data to be registered, and the registration algorithm is applied to align the data to be registered to the reference data set through the control points. The root mean square error after registration is calculated to evaluate the accuracy of registration. By comparing and analyzing the layer information of different data, the data are aligned to the same reference plane, and the aligned data are fused to form a unified acoustic feature data set; Step 3, applying a data fusion strategy, fusing the seabed and shallow stratum profile data with the multi-channel seismic data to generate fused acoustic stratigraphic data. The generation process of the fused acoustic stratigraphic data is as follows: Extract seafloor and shallow-sediment profile data and multi-channel seismic data from the acoustic feature dataset, and build a variational assimilation model based on the observed data and prior information; The variational assimilation model is used to comprehensively analyze the characteristics of seabed and shallow stratigraphic profile data and multi-channel seismic data, estimate the stratigraphic state, and continuously adjust the estimated value of the stratigraphic state through an iterative optimization process until the optimal solution is reached. Based on the results of the assimilation model, acoustic stratigraphic data with spatial continuity are generated. In the generated acoustic stratigraphic data, missing or sparse data points caused by observation condition limitations or errors in the data acquisition process are identified, and the values ​​of unknown data points are predicted based on the values ​​and positions of known data points using the Kriging interpolation method. The results of the Kriging interpolation method are then used to fill in the missing or sparse data points to obtain complete stratigraphic information. According to the characteristics of seabed and shallow layer profile data and multi-channel seismic data, a statistical model is constructed, and the seabed and shallow layer profile data and multi-channel seismic data are input into the statistical model for fusion processing. Through model calculation, the fused acoustic stratigraphic data is generated; Step 4: extract the characteristics of the seafloor active faults based on the fused acoustic stratigraphic data, and comprehensively analyze the characteristics of the seafloor active faults to identify the structural characteristics of the seafloor active faults. The identification process of the structural characteristics of the seafloor active faults is as follows: Perform feature analysis on the fused acoustic stratigraphic data to extract the features related to the seafloor active faults in the acoustic stratigraphic data, where the features of the seafloor active faults include reflection wave features, disturbance features, amplitude change features, and phase change features; According to the distribution of reflected waves and disturbance characteristics, the geometric morphology of the fault zone is drawn, the extension direction of the fault zone is determined, and its relationship with the regional tectonic line is analyzed. In combination with geological knowledge, the fault properties of the fault zone are analyzed, the direction and displacement of the stratum fault are observed, and the movement direction of the fault is inferred; Using the deformation and displacement data in the acoustic stratigraphic data, the fault activity value is calculated, the changing trend of the fault activity value is analyzed, and the activity trend of the fault zone is evaluated; Combine the extracted active fault features with the regional geological background to analyze the causes of the fault zone, integrate the geometric morphology, fault properties, and activity trend data of the fault zone, and identify the structural characteristics of the fault zone; Using geological modeling software, based on the activity trend and structural characteristics of the fault zone, simulate the evolution of the fault and analyze the evolution characteristics and change trends of the fault zone in different periods; Step 5: Based on the extracted and identified features, interpret the active seafloor faults to assess potential geological risks and conduct a comprehensive analysis of the interpretation results.

2. The method for analyzing active faults in marine areas based on acoustic stratigraphic data fusion interpretation according to claim 1 is characterized by: The acquisition and preprocessing process of the acoustic data is as follows: Deploy a shallow layer profiler and a multi-channel seismic system in the target area, covering the entire target area to collect acoustic data of the seabed and shallow layer structure and multi-channel seismic signals, and configure a signal conditioning front end and a field programmable gate array, and then use the shallow layer profiler to collect seabed and shallow layer profile data, record the reflection wave amplitude and frequency information, and use the signal conditioning front end and field programmable gate array technology to collect multi-channel seismic signals; Perform pre-processing operations such as filtering, denoising and signal enhancement on the collected acoustic data; Normalize the preprocessed acoustic data, scale the data to the same level, and segment the continuous acoustic data to obtain individual acoustic data samples; The segmented individual acoustic data samples are labeled to identify their different geological features, and the pre-processed data are integrated and stored in the data warehouse for backup and archiving.

3. The method for analyzing active faults in marine areas based on acoustic stratigraphic data fusion interpretation according to claim 1 is characterized by: The calculation formula of the fracture activity value is: Among them, F is the fault activity value, F a is the average value of the reflected wave amplitude change, F B is the reference value of the reflected wave amplitude change, F M is the sensitivity factor of amplitude change, X B is the reference value of the phase change characteristic, D M is the direction of stratum faulting and the maximum displacement, D F is the benchmark threshold of stratum fault, D G is the limit value of stratum faulting. It should be noted that the value range of F is between 0 and 1, where 1 indicates that the fault activity is at the highest level and 0 indicates that there is no fault activity.

4. The method for analyzing active faults in marine areas based on acoustic stratigraphic data fusion interpretation according to claim 1 is characterized by: The interpretation process of the active seafloor fault is as follows: Extract the activity trend data, structural characteristic data and geological information data of the fault zone, perform standardization processing, and use the regional geological background and geological structural line information to establish a geological framework model, including the distribution, thickness and lithology of the strata. Among them, the activity trend data of the fault zone includes the displacement rate, activity frequency and seismic activity of the fault zone, the structural characteristic data includes the geometric shape of the fault zone, the nature of the fault, the dislocation of the strata and the distribution of lithology, and the geological information data includes the regional geological background, geological structural line and stratigraphic sedimentary sequence; Add the geometric shape and fault property data of the fault zone to the geological framework model to form a geological model that includes the fault zone, and compare the output of the geological model with the actual geological conditions to verify the accuracy of the model. According to the geometric shape, stratigraphic dislocation and lithology distribution information of the fault zone, analyze the properties of the fault, and determine the type of the fault zone in combination with the fault properties and regional geological background; Analyze the structural characteristics of different types of fault zones, including the width, depth, morphological changes, and degree of stratigraphic dislocation of the fault zones. Use the activity trend data of the fault zones to study the activity patterns of the fault zones, including activity cycles, activity intensity, and seismic activity. Combined with the regional geological background and geological tectonic line information, the genesis mechanism of the fault zone, including crustal movement and plate tectonics, is clarified, and then the active seabed faults are interpreted, and a fault zone distribution map is drawn, with the type, location, and activity nature of the fault zone clearly marked on the map.

5. The method for analyzing active faults in marine areas based on acoustic stratigraphic data fusion interpretation according to claim 4 is characterized by: The assessment process of potential geological risks is as follows: Calculate the geological risk factor of the submarine fault zone based on the interpretation results of the submarine active faults and the data in the fault zone distribution map; According to the type of fault zone, the nature of activity and the regional geological background, the relevant geological disaster types are analyzed and the severity of the geological disaster types is evaluated. Combined with the geological risk coefficient, different geological risk levels are divided into low geological risk level, medium geological risk level and high geological risk level, and corresponding evaluation thresholds are divided for each geological risk level to evaluate potential geological risks; Prepare a risk assessment report, including the interpretation results of the fault zone, the risk factor calculation process, the risk level classification results and the assessment results of potential geological hazards.

6. The method for analyzing active faults in marine areas based on acoustic stratigraphic data fusion interpretation according to claim 5 is characterized by: The calculation formula of the geological risk coefficient is: Among them, R is the geological risk factor, W is the width of the fault zone, D is the depth of the fault zone, and W r and D r is the reference value of the fault zone width and fault zone depth, A c is the activity period of the fault zone, A max is the maximum possible value of the activity period, I ac is the activity intensity of the fault zone, I max is the maximum possible value of activity intensity, S f is the degree of stratum dislocation in the fault zone, S t is the benchmark threshold of the formation fault degree, k is the adjustment parameter used to control the sensitivity of the formation fault degree to the risk impact, E se is the seismic activity energy of the fault zone, E max is the maximum possible value of the energy of seismic activity.

7. The method for analyzing active faults in marine areas based on acoustic stratigraphic data fusion interpretation according to claim 6 is characterized by: A plurality of the geological risk levels correspond to a plurality of the evaluation thresholds, wherein the evaluation thresholds include an upper threshold and a lower threshold; The multiple geological risk levels and the multiple evaluation thresholds satisfy the following relationship: Low geological risk level: 0 <R≤R T1 ; Medium geological risk level: R T1 <R≤R T2 ; High geological risk level: R T2 <R<1; Among them, R is the geological risk factor, R T1 is the lower threshold corresponding to the medium geological risk level and the upper threshold corresponding to the low geological risk level, R T2 is the lower threshold corresponding to the high geological risk level and the upper threshold corresponding to the medium geological risk level, R T1 =0.3, R T2 =0.7.

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