A method for identifying and predicting hydrate enrichment zones in a high fluid flux context and related devices

Abstract

The application discloses a hydrate enrichment area identification and prediction method under a high fluid flux background and related equipment, and the application constructs a stereoscopic data base covering a deep layer to a surface layer through multi-source research data; on the basis, deep fluid migration channels, middle layer geophysical anomalies, shallow geochemical parameters and surface micro-landform marks are extracted respectively, so that each layer identification mark can be matched, and thus the defects of traditional methods relying on a single means can be effectively overcome; finally, through spatial superposition analysis on deep, middle, shallow and surface layer result maps and output of a graded target area, a complete evidence chain from deep to shallow and layer by layer is formed, the misjudgment risk caused by the multi-solution of a single abnormal mark can be effectively reduced, and then the accuracy and reliability of the high fluid flux type hydrate enrichment area identification are significantly improved, and the application can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and related equipment for identifying and predicting hydrate enrichment areas under high fluid flux conditions. Background Technology

[0002] Natural gas hydrates, as an important new clean energy source, have become a cutting-edge field in global energy exploration. Based on differences in fluid supply intensity, natural gas hydrate systems can be divided into two end-member types: dispersed low-fluidity hydrates and concentrated high-fluidity hydrates. Among these, high-fluidity hydrate reservoirs, characterized by their large thickness and high saturation, are currently the key targets for hydrate resource exploration.

[0003] In existing technologies, seismic exploration techniques are the primary means of identifying and predicting natural gas hydrates. Among these, bottom-spot reflectors (BSRs), as classic markers for identifying the bottom boundary of hydrate stability domains, are widely used in exploration practice. Regarding the processing and interpretation of seismic data, the industry has developed various technical methods: improving data quality through high-resolution seismic acquisition systems; predicting hydrate-rich areas by fusing seismic attributes and elastic parameters; identifying hydrate-bearing layers and estimating saturation using P-wave and S-wave velocity increment cross-plots; classifying leakage types based on the relationship between submarine methane leakage characteristics and fluid migration channels; and determining BSR locations by calculating temperature and pressure matrices using numerical models.

[0004] However, the aforementioned technical methods mostly focus on a single discipline or a single identification marker, lacking a comprehensive understanding of the entire process of hydrate accumulation systems. When faced with complex hydrate accumulation systems under high fluid flux conditions, the limitations of existing technical methods and relatively singular indicators become increasingly apparent, making it difficult to meet the current demand for cross-verification of multiple evidence chains in fine exploration. Summary of the Invention

[0005] The main objective of this invention is to provide a method, apparatus, electronic device, storage medium, and program product for identifying and predicting hydrate enrichment regions under high fluid flux conditions, aiming to solve at least one problem of the prior art.

[0006] To achieve the above objectives, one aspect of this invention proposes a method for identifying and predicting hydrate enrichment regions under high fluid flux conditions, the method comprising: Acquire research data for the study area; including high-resolution 3D seismic data, seafloor topography data, underwater acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data. All data in the study area are pre-spatialized. Based on high-resolution 3D seismic data, the geometric morphology and attribute characteristics of deep fluid transport channels are extracted through seismic attribute analysis and structural interpretation, and a distribution map of deep fluid transport channels is generated. Based on the distribution map of deep fluid transport channels, geophysical anomaly markers coupled with channel space are extracted from the seismic data volume using high-resolution three-dimensional seismic data to generate a comprehensive map of mid-level geophysical anomaly responses. Based on sediment pore water samples and in-situ heat flow measurement data, geochemical parameters reflecting methane flux are obtained through quantitative geochemical analysis, and shallow geochemical anomaly zones are delineated to generate shallow geochemical constraint maps. Based on seabed topographic data, water acoustic data, and shallow seismic profile data, micro-topography and cold seep markers related to fluid activity are extracted, and then a comprehensive map of the surface micro-topography system is generated through credibility grading. Spatial overlay analysis was performed on the distribution map of deep fluid migration channels, the comprehensive map of geophysical anomaly response in the middle layer, the geochemical constraint map of the shallow layer, and the comprehensive map of the surface micro-geomorphic system to obtain exploration target areas at different levels.

[0007] In some implementations, acquiring research data for the study area includes the following steps: High-resolution 3D seismic data was acquired by towing a 3D seismic acquisition system using a geophysical exploration vessel. Simultaneously acquire seabed topographic data and underwater acoustic data using a multibeam bathymetry system; Shallow seismic profile data are obtained by using a shipborne or deep-towed shallow seismic profiler to emit sound pulses from a high-frequency sound source and receive the reflected signals from the shallow sedimentary layer on the seabed. Sediment pore water samples were obtained using a gravity sampler. In-situ heat flow measurement data are obtained using a heat flow probe; High-resolution 3D seismic data, seabed topographic data, water acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data were uniformly spatially registered and format converted to construct a standardized multi-source dataset as research data.

[0008] In some implementations, high-resolution 3D seismic data includes a 3D seismic data volume. Based on the high-resolution 3D seismic data, the geometric morphology and attribute characteristics of deep fluid migration channels are extracted through seismic attribute analysis and structural interpretation to generate a distribution map of deep fluid migration channels. This includes the following steps: By extracting coherence and variance seismic attributes from 3D seismic data volumes, candidate regions with low coherence and / or low variance in the study area that exhibit chaotic or blank internal reflections can be identified. Based on candidate regions, the channel morphology is identified through detailed interpretation of seismic profiles to obtain the corresponding channel set in the study area, and the spatial location of each channel in the channel set is determined; among them, the channel types corresponding to the channel morphology include gas chimneys, diapiric structures, structural faults and fluid conduits. Based on the three-dimensional seismic data volume, the planar distribution range, longitudinal extension length and top burial depth of each channel in the channel set are determined, and then the connectivity of each channel in the channel set with the deep gas source layer downward and with the shallow strata upward is calibrated as connectivity information. The distribution map of deep fluid transport channels is generated by using channel type, spatial location, connectivity information, and longitudinal extension range corresponding to longitudinal extension length as channel markers.

[0009] In some implementations, the distribution map of deep fluid migration channels is marked with the channel type, spatial location, longitudinal extension range, and connectivity information corresponding to each channel. Based on the distribution map of deep fluid migration channels, geophysical anomaly markers coupled with the channel space are extracted from the seismic data volume using high-resolution 3D seismic data to generate a comprehensive map of mid-level geophysical anomaly responses, including the following steps: Using the distribution map of deep fluid transport channels as a spatial constraint background, geophysical anomaly markers of the top of each channel and the adjacent area are extracted from the seismic data volume corresponding to the high-resolution three-dimensional seismic data. Among them, geophysical anomaly markers include: enhanced reflection, local bright spot reflection, and co-axial phase reversal features of atypical seafloor-like reflector layers and above them; and high-velocity anomalies above atypical seafloor-like reflector layers obtained by calibration of P-wave velocity fields obtained through pre-stack or full waveform inversion. By overlaying the spatial distribution range of various anomalies in the geophysical anomaly markers onto the deep fluid migration channel distribution map, and marking the spatial coupling relationship between various anomalies and each channel, a comprehensive map of the response to mid-level geophysical anomalies is generated.

[0010] In some implementations, based on sediment pore water samples and in-situ heat flow measurement data, geochemical parameters reflecting methane flux are obtained through quantitative geochemical analysis, thereby delineating shallow geochemical anomaly zones to generate shallow geochemical constraint maps. This includes the following steps: Sulfate ion concentration was extracted from sediment pore water samples, and then a decay profile of sulfate ion concentration as a function of depth was obtained by fitting the data. Based on the attenuation profile, the sulfate-methane interface is determined by linear or exponential fitting and extrapolation to the depth where the concentration is zero, and the interface contour lines are obtained. Among them, the depth of the sulfate-methane interface is negatively correlated with the methane flux; the shallower the sulfate-methane interface, the greater the methane flux. The sulfate concentration gradient is determined based on the attenuation profile. The preset porosity and diffusion coefficient are multiplied by the sulfate concentration gradient, and then the sulfate flux is obtained by taking the negative value. Based on the stoichiometry of the anaerobic oxidation reaction of methane, the methane flux is calculated by the sulfate flux, and flux is classified by a preset threshold. By comparing the in-situ heat flow measurement data with the corresponding regional background heat flow value of the study area, local heat flow anomaly areas can be identified. Shallow geochemical constraint maps are generated by using interface contour lines, flux classifications corresponding to each region, and local heat flow anomalies as chemical constraint markers.

[0011] In some implementations, based on seafloor topographic data, underwater acoustic data, and shallow seismic profile data, micro-topography and cold seep markers related to fluid activity are extracted. Then, a comprehensive surface micro-topography system map is generated through reliability grading, including the following steps: Water body acoustic data is processed by water body imaging to extract plume anomalies extending upward from the seabed. Transform seabed topographic data into a digital topographic model, and then extract the pockmarks of circular or elliptical negative topography through topographic analysis. Identify submarine mounds and carbonate crusts with strong reflective features from shallow seismic profile data; Feather flow anomalies, pit groups, submarine mounds, and carbonate crusts are used as geomorphic anomaly markers. Surface anomaly response zones are delineated in the study area, and the credibility is graded according to the degree of combination between geomorphic anomaly markers to generate a comprehensive map of the surface micro-geomorphic system. The confidence level classification includes: Level 1 confidence level, which includes multiple types of geomorphic anomaly markers and feather flow anomalies; Level 2 confidence level, which includes multiple types of geomorphic anomaly markers but does not include feather flow anomalies; and Level 3 confidence level, which includes only a single type of geomorphic anomaly marker.

[0012] In some implementations, the deep fluid migration channel distribution map is marked with channel markers, the intermediate geophysical anomaly response map is marked with geophysical anomaly markers, the shallow geochemical constraint map is marked with chemical constraint markers, and the surface micro-geomorphic system map is marked with geomorphic anomaly markers. The areas corresponding to the deep fluid migration channel distribution map, the intermediate geophysical anomaly response map, the shallow geochemical constraint map, and the surface micro-geomorphic system map are distributed longitudinally from deep to shallow in the study area. Spatial overlay analysis of the deep fluid migration channel distribution map, the intermediate geophysical anomaly response map, the shallow geochemical constraint map, and the surface micro-geomorphic system map is performed to obtain exploration target areas of different levels, including the following steps: The study area is traversed horizontally as the target area. If the target area has markings in the deep fluid transport channel distribution map, the comprehensive map of geophysical anomaly response in the middle layer, the shallow geochemical constraint map, and the comprehensive map of surface micro-geomorphic system corresponding to the deep, middle, shallow, and surface regions, the target area is determined to be a first-level target area. If the target area has markings in only three levels of regions in the deep fluid transport channel distribution map, the comprehensive map of intermediate geophysical anomaly response, the shallow geochemical constraint map, and the comprehensive map of surface micro-geomorphic system, the target area is determined to be a secondary target area. If the target area has markings in only two of the following layers: the deep fluid transport channel distribution map, the comprehensive map of intermediate geophysical anomaly response, the shallow geochemical constraint map, and the comprehensive map of surface micro-geomorphic system, then the target area is determined to be a level 3 target area. If the target area has a marked area in only one of the following layers: the deep fluid transport channel distribution map, the comprehensive map of intermediate geophysical anomaly response, the shallow geochemical constraint map, and the comprehensive map of surface micro-geomorphic system, then the target area is determined to be a level four target area.

[0013] To achieve the above objectives, another aspect of the present invention provides a device for identifying and predicting hydrate enrichment regions under high fluid flux conditions. The device includes: The first module is used to acquire research data for the study area. The research data includes high-resolution three-dimensional seismic data, seafloor topographic data, water acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data. The various data in the research data are pre-spatialized in the study area. The second module is used to extract the geometric morphology and attribute characteristics of deep fluid transport channels based on high-resolution three-dimensional seismic data through seismic attribute analysis and structural interpretation, and generate a distribution map of deep fluid transport channels. The third module is used to extract geophysical anomaly markers coupled with channel space from the seismic data volume based on the distribution map of deep fluid transport channels and high-resolution three-dimensional seismic data, and generate a comprehensive map of mid-level geophysical anomaly response. The fourth module is used to obtain geochemical parameters reflecting methane flux through quantitative geochemical analysis based on sediment pore water samples and in-situ heat flow measurement data, and then delineate shallow geochemical anomaly zones to generate shallow geochemical constraint maps. The fifth module is used to extract micro-topography and cold seep markers related to fluid activity based on seabed topography data, water acoustic data, and shallow seismic profile data, and then generate a comprehensive map of the surface micro-topography system through credibility grading. The sixth module is used to perform spatial overlay analysis on the distribution map of deep fluid migration channels, the comprehensive map of geophysical anomaly response in the middle layer, the geochemical constraint map of the shallow layer, and the comprehensive map of the surface micro-geomorphic system to obtain exploration target areas at different levels.

[0014] To achieve the above objectives, another aspect of the present invention provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned method.

[0015] To achieve the above objectives, another aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method.

[0016] To achieve the above objectives, another aspect of the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0017] The embodiments of this invention include at least the following beneficial effects: This invention provides a method, device, electronic device, storage medium, and program product for identifying and predicting hydrate enrichment areas under high fluid flux backgrounds. This scheme acquires research data from the study area; wherein the research data includes high-resolution 3D seismic data, seafloor topographic data, underwater acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data. Each data point in the research data is pre-registered spatially within the study area. Based on the high-resolution 3D seismic data, the geometric morphology and attribute characteristics of deep fluid transport channels are extracted through seismic attribute analysis and tectonic interpretation, generating a deep fluid transport channel distribution map. Based on the deep fluid transport channel distribution map, high-resolution 3D seismic data is used... Geophysical anomaly markers coupled with channel space are extracted from seismic data volumes to generate a comprehensive map of mid-level geophysical anomaly responses. Based on sediment pore water samples and in-situ heat flow measurements, geochemical parameters reflecting methane flux are obtained through quantitative geochemical analysis, thereby delineating shallow geochemical anomaly zones to generate shallow geochemical constraint maps. Based on seafloor topography data, water acoustic data, and shallow seismic profile data, micro-geomorphic features and cold seep markers related to fluid activity are extracted, and a comprehensive map of the surface micro-geomorphic system is generated through confidence grading. Spatial overlay analysis is performed on the deep fluid transport channel distribution map, the comprehensive map of mid-level geophysical anomaly responses, the shallow geochemical constraint map, and the comprehensive map of the surface micro-geomorphic system to obtain exploration target areas at different levels. This invention constructs a three-dimensional data foundation covering deep to surface layers using multi-source research data. Based on this, it extracts deep fluid transport channels, mid-layer geophysical anomalies, shallow geochemical parameters, and surface micro-geomorphic markers, enabling the matching of identification markers at each level. This effectively overcomes the shortcomings of traditional methods that rely on single methods. Finally, by spatially overlaying and analyzing the four-layer (deep, mid-layer, shallow, and surface) maps and outputting tiered target areas, a complete chain of evidence is formed, progressively confirming each layer from deep to shallow. This effectively reduces the risk of misjudgment due to the ambiguity of single anomaly markers, thus significantly improving the accuracy and reliability of identifying high-fluid-fluid-fluid hydrate-rich areas. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of an implementation environment for the method of identifying and predicting hydrate enrichment areas under high fluid flux conditions provided in this embodiment of the invention. Figure 2 This is a flowchart illustrating the method for identifying and predicting hydrate enrichment regions under high fluid flux conditions provided in this embodiment of the invention. Figure 3 This is a schematic diagram of the overall process of the hydrate enrichment region identification and prediction method under high fluid flux background provided in the embodiments of the present invention; Figure 4This is a schematic diagram illustrating an example of deep fluid transport channel identification provided in an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating an example of a mid-level geophysical anomaly response provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a shallow geochemical constraint example provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of an example of a surface micro-topography system provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of the hydrate enrichment region identification and prediction device under high fluid flux background provided in this embodiment of the invention; Figure 9 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of this invention; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this invention as detailed in the appended claims.

[0020] It is understood that the terms "first," "second," etc., used in this invention may be used to describe various concepts, but unless specifically stated otherwise, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of embodiments of this invention, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words "if" or "when" as used herein may be interpreted as "when," "in response to determination," or "in the event of a determination."

[0021] The terms “at least one,” “multiple,” “each,” “any,” etc., used in this invention, “at least one” includes one, two, or more than two; “multiple” includes two or more than two; “each” refers to each of the corresponding multiple; and “any” refers to any one of the multiple.

[0022] Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this invention is for descriptive purposes only and is not intended to limit the invention.

[0023] To facilitate understanding of the technical solution of this invention, the technical terms of the proprietary technical features that may be involved in the technical solution of this invention will first be explained: Natural gas hydrates are ice-like crystalline compounds formed by natural gas (mainly methane gas) and water molecules under low temperature and high pressure conditions on the seabed. They are widely found in seabed sediments and permafrost areas along continental margins and are a type of unconventional clean energy with huge resources.

[0024] High fluid flux refers to the large-scale, high-efficiency vertical migration of deep gas-bearing fluids into shallow strata along migration channels such as faults, gas chimneys, and fluid conduits. Under high fluid flux conditions, the fluid supply rate is significantly higher than the methane consumption rate of diffusion-type hydrates, which is conducive to the formation of highly saturated, thick-layered seepage-type hydrate reservoirs.

[0025] Leakage hydrates: closely related to deep fluid transport channels (gas chimneys, faults, fissures, etc.), hydrates formed by methane gas seeping upwards along the channels and under suitable internal temperature and pressure conditions. They often appear as massive, vein-like, or nodular formations, with high saturation. Traditional BSR identification markers are usually underdeveloped or atypical.

[0026] Seafloor reflection (BSR): A high-amplitude seismic reflection interface in marine seismic profiles that is approximately parallel to the seafloor, has a reflection polarity opposite to that of the seafloor, and can obliquely intersect sedimentary bedding. It is a key geophysical marker for the identification of traditional diffusion-type hydrates.

[0027] Blank reflections: These are vertical or near-vertical blank / chaotic reflections on seismic profiles, extending from deep to near the seabed. They are usually associated with gaseous fluid migration and the filling and enrichment of hydrates within the channels.

[0028] Gas chimneys: These are columnar strong amplitude anomalies that appear vertically or nearly vertically on seismic profiles. They indicate channels through which deep gas-bearing fluids migrate upwards along fracture or fissure systems and are one of the important types of deep fluid migration channels.

[0029] Dipirate structures are structural types formed by deep plastic materials (such as salt rock and mudstone) piercing or subcutaneously piercing through the overlying strata. The top is often mushroom-shaped and accompanied by radial fractures, which can provide favorable channels for fluid migration.

[0030] Fluid conduits: On seismic profiles, there are near-vertical tubular strong amplitude anomalies with small lateral diameters that extend longitudinally through shallow strata, indicating the path of deep fluids rapidly moving upward along tubular channels.

[0031] Submarine plumes: Echo anomalies appearing in the shape of plumes or bundles on the water profile indicate methane fluid leakage activity occurring on the seabed and are a direct indicator of the surface micro-geomorphic system.

[0032] Submarine pits: Negative topographic depressions on the seabed surface, formed by fluid leakage or gas escape after hydrate decomposition. They are often distributed in groups, indicating the history of shallow fluid activity and are one of the markers of the surface micro-geomorphic system.

[0033] Submarine mounds: Positive topographic uplifts on the seabed surface, usually caused by the growth of hydrates in the shallow layer or the formation of cold seeps in carbonate rocks. They often develop cold seep communities or carbonate crusts on their tops and are one of the markers of the surface micro-geomorphic system.

[0034] Sulfate-methane transition zone (SMTZ): The depth interface where the sulfate concentration in sediments approaches zero and methane begins to appear. Its depth variation can quantitatively reflect the amount of methane flux and the gas source conditions for hydrate accumulation, and is an important indicator of shallow geochemical constraints.

[0035] Methane flux: The amount of methane diffusion or seepage through a unit area of ​​sediment-water interface per unit time is a key parameter for evaluating the intensity of hydrate gas supply and belongs to the quantitative evaluation parameters of shallow geochemistry.

[0036] In related technologies, existing technologies mostly focus on a single discipline or a single identification marker, lacking a comprehensive understanding of the entire process of hydrate accumulation systems.

[0037] In view of this, this invention provides a method and related equipment for identifying and predicting hydrate enrichment areas under high fluid flux backgrounds. This method acquires research data from the study area, including high-resolution 3D seismic data, seafloor topography data, water acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data. Each data point in the research data is pre-registered spatially within the study area. Based on the high-resolution 3D seismic data, the geometric morphology and attribute characteristics of deep fluid transport channels are extracted through seismic attribute analysis and tectonic interpretation to generate a deep fluid transport channel distribution map. Based on the deep fluid transport channel distribution map, high-resolution 3D seismic data is used to extract and predict hydrate enrichment areas from the seismic data volume. Geophysical anomaly markers coupled with channel space are used to generate a comprehensive map of mid-level geophysical anomaly responses. Based on sediment pore water samples and in-situ heat flow measurements, geochemical parameters reflecting methane flux are obtained through quantitative geochemical analysis, thereby delineating shallow geochemical anomaly zones to generate shallow geochemical constraint maps. Based on seafloor topography data, water acoustic data, and shallow seismic profile data, micro-geomorphic features and cold seep markers related to fluid activity are extracted, and a comprehensive map of the surface micro-geomorphic system is generated through confidence grading. Spatial overlay analysis of the deep fluid transport channel distribution map, the comprehensive map of mid-level geophysical anomaly responses, the shallow geochemical constraint map, and the comprehensive map of the surface micro-geomorphic system is performed to obtain exploration target areas at different levels. This invention constructs a three-dimensional data foundation covering deep to surface layers using multi-source research data. Based on this, it extracts deep fluid transport channels, mid-layer geophysical anomalies, shallow geochemical parameters, and surface micro-geomorphic markers, enabling the matching of identification markers at each level. This effectively overcomes the shortcomings of traditional methods that rely on single methods. Finally, by spatially overlaying and analyzing the four-layer (deep, mid-layer, shallow, and surface) maps and outputting tiered target areas, a complete chain of evidence is formed, progressively confirming each layer from deep to shallow. This effectively reduces the risk of misjudgment due to the ambiguity of single anomaly markers, thus significantly improving the accuracy and reliability of identifying high-fluid-fluid-fluid hydrate-rich areas.

[0038] It is understood that the hydrate enrichment region identification and prediction method provided by this invention under high fluid flux backgrounds can be applied to any computer device with data processing and computing capabilities, and this computer device can be various types of terminals or servers. When the computer device in the embodiments is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal can be a smartphone, tablet, laptop, or desktop computer, but it is not limited to these.

[0039] like Figure 1 The diagram shown is a schematic representation of an implementation environment provided by an embodiment of the present invention. (Refer to...) Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected via a network, either wirelessly or via a wired connection, to complete data transmission and exchange.

[0040] Server 101 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0041] Additionally, server 101 can also be a node server in a blockchain network. Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms.

[0042] Terminal 102 can be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. Terminal 102 and server 101 can be directly or indirectly connected via wired or wireless communication, and this embodiment of the invention does not impose any limitations.

[0043] For example, based on Figure 1The implementation environment shown in this embodiment of the invention provides a method for identifying and predicting hydrate-rich regions under high fluid flux conditions. The following description uses the application of this method in server 101 as an example. It is understood that this method can also be applied in terminal 102.

[0044] Reference Figure 2 , Figure 2 This is an optional flowchart of the hydrate enrichment region identification and prediction method under high fluid flux background provided in the embodiments of the present invention. The execution subject of the hydrate enrichment region identification and prediction method under high fluid flux background can be any of the aforementioned computer devices (including servers or terminals). Figure 2 The method may include, but is not limited to, steps S100 to S600.

[0045] Step S100: Obtain research data for the study area; The research data includes high-resolution three-dimensional seismic data, seafloor topographic data, water acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data. All data in the research data were spatially registered in advance in the study area. It should be noted that in some embodiments, step S100 may include the following steps: acquiring high-resolution three-dimensional seismic data using a towed three-dimensional seismic acquisition system from a geophysical vessel; simultaneously acquiring seabed topographic data and water acoustic data using a multibeam echo sounder; obtaining shallow seismic profile data by emitting sound pulses with a high-frequency sound source and receiving reflected signals from shallow seabed sediments using a shipborne or deep-towed shallow seismic profiler; acquiring sediment pore water samples using a gravity sampler; acquiring in-situ heat flow measurement data using a heat flow probe; and uniformly performing spatial registration and format conversion on the high-resolution three-dimensional seismic data, seabed topographic data, water acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data to construct a standardized multi-source dataset as research data.

[0046] Step S200: Based on high-resolution three-dimensional seismic data, extract the geometric morphology and attribute characteristics of deep fluid transport channels through seismic attribute analysis and structural interpretation, and generate a distribution map of deep fluid transport channels; It should be noted that high-resolution 3D seismic data includes 3D seismic data volumes. In some embodiments, step S200 may include the following steps: extracting coherence and variance seismic attributes from the 3D seismic data volume to identify candidate areas in the study area with low coherence and / or low variance, exhibiting chaotic or blank internal reflections; based on the candidate areas, identifying channel morphology through fine interpretation of seismic profiles to obtain the corresponding channel set in the study area, and determining the spatial location of each channel in the channel set; wherein, the channel types corresponding to the channel morphology include gas chimneys, diapiric structures, structural faults, and fluid conduits; determining the planar distribution range, longitudinal extension length, and top burial depth of each channel in the channel set based on the 3D seismic data volume, and then calibrating the connectivity of each channel in the channel set downwards to the deep gas source layer and upwards to the shallow strata as connectivity information; and generating a deep fluid transport channel distribution map using the channel type, spatial location, connectivity information, and longitudinal extension range corresponding to the longitudinal extension length as channel markers.

[0047] For example, in some specific embodiments, fluid transport channel identification can be implemented as follows: 1. Gas Chimney Identification. Gas chimneys are mainly formed by the migration of deep gas-bearing fluids into shallow strata driven by overpressure. On seismic profiles, they appear as vertical or near-vertical columnar strong amplitude anomalies with chaotic or blank internal reflections, often accompanied by low-frequency reflections and reflection phase axis pull-down characteristics. They extend longitudinally and the top of the gas chimney is close to the seabed, indicating the channel for the vertical migration of deep gas-bearing fluids along the gas chimney and its internal fracture network system. In a specific embodiment, based on high-resolution 3D seismic data, seismic profiles are extracted along the direction perpendicular to the main seismic line to identify vertical columnar anomalies; combined with coherence analysis, the coherence value inside the gas chimney is significantly reduced; velocity spectra are extracted along the longitudinal direction of the gas chimney, typically showing low-velocity anomalies inside. The planar distribution range, longitudinal extension height, top burial depth, and connectivity with shallow faults of the gas chimney are recorded.

[0048] 2. Identification of Diapiric Structures. Diapiric structures are mainly formed by deep plastic materials (such as salt rock and mudstone) penetrating or subsurfacely penetrating the overlying strata. The top is often mushroom-shaped, accompanied by radial faults, and extends significantly longitudinally. The center of the diapir is relatively close to the seafloor, and diapiric activity can drive the upward migration of deep fluids. In specific embodiments, mushroom-shaped or dome-shaped structural morphology is identified on seismic profiles. The internal reflections of the diapir are chaotic or blank, and the surrounding strata show an upward contact relationship. Radial small faults develop at the top of the diapir; the thickness of the strata on both sides of the diapir changes significantly. The planar distribution, longitudinal extension depth, and top fault development characteristics of the diapir are recorded.

[0049] 3. Structural Fault Identification. Structural faults are mainly generated by tectonic tensile stress and often develop at the top of tectonic paleo-uplifts. They consist of multiple faults or fractures forming a banded structure. Individual faults are relatively long with significant displacement, while the distance between adjacent faults is small. The fault strike is often parallel to the tectonic ridge, forming a network of fluid transport channels. In specific embodiments, fault planes and the stratigraphic relationship between the two sides of the fault are identified on seismic profiles. On the fault plane, the fault extends in a banded pattern along the top of the tectonic ridge or paleo-uplift. The fault cuts downwards to deep strata and extends upwards to shallow layers or the seabed.

[0050] 4. Fluid Conduit Identification. Fluid conduits are primarily generated by formation rupture and fluid release driven by overpressured gas-bearing fluids. On seismic profiles, they appear as near-vertical tubular strong-amplitude anomalies with a small lateral diameter, extending longitudinally through shallow strata. Their internal reflection characteristics are similar to chimneys but more regular in shape, indicating the path of rapid upward migration of deep fluids along tubular channels. In specific embodiments, near-vertical tubular strong-amplitude anomalies are identified on seismic profiles, typically with a diameter of several hundred meters; the internal reflections of the conduit are chaotic or blank; the conduit connects downwards to chimneys or deep faults, and extends upwards to shallow strata or the seabed. The conduit diameter, longitudinal length, and connectivity with surrounding structures are measured.

[0051] Comprehensive identification: In a specific embodiment, if the study area has one or more of the following types of structures: gas chimneys, diapirs, tectonic faults, or fluid conduits, and the conduits extend downwards to deep gas source layers and upwards to shallow sedimentary layers or the seabed, then the area is determined to possess the geological conditions for high fluid flux and fluid transport. The identification results are output as a "Deep Fluid Transport Channel Distribution Map," which marks the channel type, spatial location, longitudinal extension range, and connectivity, serving as a background constraint map for mid-level geophysical anomaly responses.

[0052] Step S300: Based on the distribution map of deep fluid transport channels, geophysical anomaly markers coupled with channel space are extracted from the seismic data volume using high-resolution three-dimensional seismic data to generate a comprehensive map of mid-level geophysical anomaly response. It should be noted that the deep fluid transport channel distribution map is marked with the channel type, spatial location, longitudinal extension range and connectivity information corresponding to each channel. In some embodiments, step S300 may include the following steps: using the deep fluid transport channel distribution map as a spatial constraint background, extracting geophysical anomaly markers of the top and adjacent areas of each channel from the seismic data volume corresponding to the high-resolution three-dimensional seismic data; wherein, the geophysical anomaly markers include: enhanced reflection, local bright spot reflection and co-axial phase reversal features above the atypical seafloor-like reflector layer; high-velocity anomalies above the atypical seafloor-like reflector layer obtained by calibration using the P-wave velocity field obtained by pre-stack or full waveform inversion; superimposing the spatial distribution range of various anomalies in the geophysical anomaly markers on the deep fluid transport channel distribution map, and marking the spatial coupling relationship between various anomalies and each channel to generate a comprehensive map of mid-level geophysical anomaly response.

[0053] For example, in some specific implementations, geophysical anomaly extraction can be achieved as follows: 1. Identification of Atypical BSRs. These are typically characterized by BSR reflections that are approximately parallel to the seafloor topography, with discontinuous lateral extension and a discontinuous distribution, locally exhibiting beaded or bright spot reflections. At the corresponding locations of seepage channels, influenced by local thermal convection, the BSRs show localized upward pull, indicating a local uplift of the hydrate stability domain. In a specific embodiment, based on high-resolution 3D seismic profiles, strong reflection interfaces with polarity opposite to the seafloor are first identified; their lateral continuity is analyzed, and discontinuous or discontinuous distributions are marked; locally upward-pulling BSR segments are identified, and the magnitude of the upward pull is marked; the identification results are overlaid with the deep channel planar distribution map from step one, and the areas of BSR characteristic variation above the channels are marked.

[0054] 2. Enhanced Reflection Identification Above the BSR. Strong amplitude reflection features located above the BSR interface, exhibiting continuous or semi-continuous distribution and extending over a large lateral range, typically indicate the top interface of the hydrate layer. In a specific embodiment, on the seismic profile, the root mean square amplitude attribute is extracted within a 0-20 ms time window upwards from the BSR as the bottom boundary; the background amplitude value of the region is statistically analyzed, and areas with amplitude values ​​2-3 times higher than the background value are marked as enhanced reflection anomaly zones; the lateral extension length, longitudinal thickness, and contact relationship with the BSR of the enhanced reflection are analyzed.

[0055] 3. Bright Spot Reflection Identification. This manifests as a significant increase in local amplitude, with limited lateral extension compared to enhanced reflection. It typically presents as localized point-like or beaded distributions within seepage channels, usually indicating localized enrichment of highly saturated hydrates or cold seep carbonate formations. In a specific embodiment, localized strong-amplitude "bright spots" are identified on seismic profiles, typically less than 100m wide. The spatial relationship between these bright spots and deep channels is analyzed, and the number of bright spots developed at the top and periphery of the channels is counted. Combined with phase characteristics, the likelihood of the bright spots being hydrate layers (positive polarity) or free gas layers (negative polarity) is determined.

[0056] 4. Phase Reversal Identification. Phase reversal refers to the phenomenon of a significant polarity change between the seismic reflection phase axis and the surrounding strata. Under high fluid flux conditions, due to convective heat transfer, a central gas layer often forms on the plane, transitioning to hydrate layers on both sides, creating a mineral body distribution pattern. In this case, the boundary between the gas layer and the hydrate layer will show an inverse polarity reversal characteristic on the seismic reflection phase axis. Furthermore, under the influence of seepage fluid flux, gas enters the shallow seafloor. If the shallow sediments contain air bubbles, a polarity reversal characteristic will also appear, such as the negative polarity reflection generated after the air bubbles rise to the seafloor. The presence of a phase reversal on the seismic reflection phase axis on the seafloor usually indicates the presence of active cold seeps. In a specific embodiment, the polarity change of the reflection phase axis is traced along the vertical profile on the seismic profile, marking the location and spatial distribution characteristics of the polarity reversal from the BSR upwards to the seafloor, and then overlaid and matched with the deep channel plane projection from step one.

[0057] 5. Velocity Anomaly Certification. Based on the velocity field inversion results, high-velocity anomalies above the BSR are identified. Due to their high degree of consolidation and low porosity, hydrates exhibit significantly higher P-wave velocities than the surrounding rock strata. Velocity inversion can be used to infer hydrate-rich areas. In a specific embodiment, Gaussian beam inversion or full waveform inversion is used to obtain the shallow P-wave velocity field; a structurally stable, homogeneous region without anomalous reflections is selected to statistically analyze the background velocity; when the P-wave velocity of the strata is significantly higher than the background velocity (usually 30%~50% higher), and the anomalous region is located above the BSR, it is determined to be a velocity anomaly (hydrate indicator).

[0058] Comprehensive identification: The above-mentioned geophysical anomaly markers (atypical BSR, enhanced reflection, bright spot reflection, phase reversal, velocity anomaly) are spatially overlaid to mark the planar distribution range and vertical stratigraphic position of each anomaly. A "Comprehensive Map of Mid-Layer Geophysical Anomaly Responses" is output, highlighting anomaly areas with good spatial coupling to deep channels (i.e., areas with multiple anomalies developing at and around the channel tip), which serve as key target areas for shallow geochemical constraints.

[0059] Step S400: Based on sediment pore water samples and in-situ heat flow measurement data, geochemical parameters reflecting methane flux are obtained through quantitative geochemical analysis, and then shallow geochemical anomaly zones are delineated to generate shallow geochemical constraint maps. It should be noted that, in some embodiments, step S400 may include the following steps: extracting sulfate ion concentration from sediment pore water samples, and then fitting a decay profile of sulfate ion concentration with depth; based on the decay profile, using linear or exponential fitting and extrapolating to the depth where the concentration is zero, determining the sulfate-methane interface and converting it into interface contour lines; wherein, the depth of the sulfate-methane interface is negatively correlated with methane flux, the shallower the sulfate-methane interface, the greater the methane flux; determining the sulfate concentration gradient based on the decay profile, multiplying the preset porosity and diffusion coefficient with the sulfate concentration gradient, and then obtaining the sulfate flux by taking the negative value; based on the stoichiometric ratio of the methane anaerobic oxidation reaction, calculating the methane flux through the sulfate flux, and performing flux classification through a preset threshold; comparing the in-situ heat flux measurement data with the corresponding regional background heat flux value of the study area to identify local heat flux anomaly areas; and using the interface contour lines, the flux classification corresponding to each region, and the local heat flux anomaly areas as chemical constraint markers to generate a shallow geochemical constraint map.

[0060] For example, in some specific embodiments, shallow geochemical constraints can be achieved as follows: 1. Geochemical analysis of sediment pore water. Gravity columnar samples are collected within the target area, spaced at regular intervals (usually 20-50 cm), and pore water is extracted. Sulfate ion concentration (SO42-) is determined. 2- Dissolved inorganic carbon (DIC) and calcium ions (Ca) 2+ ), magnesium ions (Mg 2+ ), Strontium ion (Sr) 2+ ), chloride ions (Cl) - Concentrations of various ions were plotted. In a specific embodiment, a profile of the concentration of each ion as a function of depth was drawn. The sulfate concentration decreased linearly or exponentially with depth, indicating the intensity of the anaerobic oxidation of methane (AOM) process; the DIC concentration increased with depth, mirroring the decrease in sulfate concentration; calcium, magnesium, and strontium ions often exhibited anomalies (precipitation or release) near the SMTZ interface.

[0061] 2. SMTZ Interface Calculation and Identification. The SMTZ (sulfate-methane interface) refers to the depth interface in sediments where the sulfate concentration approaches zero and methane begins to appear. The SMTZ interface depth is negatively correlated with methane flux—the shallower the SMTZ interface, the greater the methane flux. In a specific embodiment, based on the pore water sulfate concentration profile, linear or exponential fitting is used to extrapolate to the depth where the sulfate concentration is zero, which is determined as the SMTZ interface depth. The SMTZ interface depth at each station is statistically analyzed, and SMTZ interface contour maps are plotted. An SMTZ interface shallower than 5 mbsf (meters below the seabed) indicates high fluid flux seepage activity, shallower than 10-20 mbsf indicates moderate flux, and deeper than 20 mbsf indicates a low flux background.

[0062] 3. Calculation of sulfate flux and methane flux. Sulfate flux (J_SO4) 2- Calculation formula: J_SO4 2- = -φ ×Ds × (dc / dz), where φ is porosity, Ds is diffusion coefficient, and dc / dz is sulfate concentration gradient. Methane flux (J_CH4) is based on the stoichiometric ratio of the AOM reaction (CH4 + SO42-). 2- → HCO3 - + HS - Based on the calculation using H2O, theoretically J_CH4 = J_SO4 2- In a specific embodiment, the sulfate flux at each station is calculated, and then the methane flux is estimated. Methane flux > 10 -2 mol / m 2 / a indicates high fluid flux leakage, 10 -3 ~10 -2 mol / m 2 / a indicates medium flux, <10 -3 mol / m 2 / a indicates a low flux background. The calculation results are plotted on the contour map of the SMTZ interface to identify areas of high fluid flux anomalies.

[0063] 4. In-situ heat flux measurement and stability zone calculation. The seafloor heat flux is measured in situ using a heat flux probe. Combined with parameters such as water depth, seafloor temperature, geothermal gradient, and pressure, the thickness and bottom boundary depth of the natural gas hydrate stability zone are calculated. In a specific embodiment, the measured heat flux values ​​are compared with the regional background heat flux values ​​to identify local heat flux anomalies (usually related to fluid activity). The suitability of the temperature and pressure conditions for hydrate accumulation within the hydrate stability zone is comprehensively analyzed, combining the SMTZ interface and methane flux calculation results.

[0064] Comprehensive identification: Based on geochemical indicators such as SMTZ interface depth, sulfate flux, methane flux, and heat flow anomalies, shallow geochemical anomaly zones are delineated. A "Shallow Geochemical Constraint Map" is output, marking SMTZ interface contour lines, methane flux classification zones, and heat flow anomaly zones. The geochemical anomaly zones identified in this step are spatially superimposed with those from Step 1 (deep fluid channels) and Step 2 (middle-layer geophysical anomalies). Areas with high overlap indicate high-probability areas of hydrate enrichment.

[0065] Step S500: Based on seabed topographic data, water acoustic data and shallow seismic profile data, micro-topography and cold seep markers related to fluid activity are extracted, and then a comprehensive map of the surface micro-topography system is generated through credibility grading. It should be noted that in some embodiments, step S500 may include the following steps: performing water body imaging processing on the acoustic data of the water body to extract the plume anomaly extending upward from the seabed; converting the seabed topography data into a digital topography model, and then extracting the pockmarked groups of circular or elliptical negative topography through topography analysis; identifying seabed mounds and carbonate crusts with strong reflective characteristics on the shallow seismic profile data; using the plume anomaly, pockmarked groups, seabed mounds, and carbonate crusts as geomorphic anomaly markers, delineating the surface anomaly response area in the study area, and classifying the credibility according to the degree of combination between geomorphic anomaly markers to generate a comprehensive map of the surface micro-geomorphic system; wherein, the credibility classification includes: Level 1 credibility of multiple types of geomorphic anomaly markers superimposed and including plume anomalies; Level 2 credibility of multiple types of geomorphic anomaly markers superimposed but not including plume anomalies; and Level 3 credibility of only including a single type of geomorphic anomaly marker.

[0066] For example, in some specific implementations, surface micro-topography system identification can be achieved as follows: 1. Plume Identification. Plumes are anomalous echoes formed by the leakage of active methane fluid into a water column, serving as direct evidence of an active hydrate system. In specific embodiments, plume echo anomalies in the water profile are extracted based on full-depth water body data from a multibeam echo system (such as the Kongsberg EM 302 multibeam bathymetry system) or high-frequency water imaging data from a fish finder. Plumes appear as bundles, feathers, or chimneys in the water profile, extending tens to hundreds of meters upwards from the seabed. The height, width, reflection intensity, and spatial location of the plume are measured.

[0067] 2. Pockmark Identification. Pockmarks are negative topographic depressions on the seabed surface, formed by fluid seepage or gas escape after hydrate decomposition. They often occur in clusters and are important indicators of shallow fluid activity history and seepage-type hydrate systems. In a specific embodiment, based on high-resolution multibeam bathymetry data, a digital topographic model (DTM, grid resolution typically ≤25m) is extracted from the seabed. Through topographic slope analysis, curvature analysis, and manual interpretation, circular, elliptical, or elongated negative topographic depressions are identified. The diameter (typically tens to hundreds of meters), depth (several meters to tens of meters), morphological characteristics, and spatial distribution patterns of the pockmarks are measured. The density of pockmarks is statistically analyzed; areas with clustered distributions and overlapping with deep channel projections are more indicative.

[0068] 3. Identification of Submarine Mounds. Submarine mounds are positive topographic elevations on the seabed surface, typically caused by the growth of hydrates in the shallow layer, cold seep carbonate formations, or mud volcano activity. They often feature cold seep communities or carbonate crusts at their top. In this specific embodiment, positive submarine topographic elevations are identified based on high-resolution multibeam bathymetry data and side-scan sonar images. Submarine mounds typically appear as areas of strong reflection and high backscattering intensity on side-scan sonar images. The height, base diameter, and top morphology of the mound are measured. Combined with seabed video or ROV surveys, it is confirmed whether cold seep organisms (clams, mussels, tube worms, etc.) or carbonate crusts are present at the top of the mound.

[0069] 4. Identification of Strong Seafloor Reflections. Cold seep carbonate rocks are products of anaerobic methane oxidation (AOM) processes, exhibiting strong seafloor reflections and high backscattering intensities in side-scan sonar and shallow seismic profiles, often associated with seafloor mounds. In specific embodiments, based on side-scan sonar data, areas of high backscattering intensity anomalies on the seafloor are identified, typically distributed in patchy, banded, or irregular shapes. Based on shallow seismic profiles, strong seafloor reflection interfaces are identified, often beneath which acoustic blanks or acoustic disturbances are frequently observed. Verification is then performed using seafloor video data to confirm the morphology of carbonate rock crusts, nodules, or massive formations.

[0070] Comprehensive identification: Based on the comprehensive identification of surface micro-geomorphic system markers such as plumes, pits, submarine mounds, and strong submarine reflections, delineate surface anomaly response areas. Output a "Comprehensive Map of Surface Micro-Geomorphic Systems," marking the spatial location, type, and confidence level of various responses (e.g., Level I – Multiple anomalies superimposed with plumes; Level II – Multiple anomalies superimposed but without plumes; Level III – Single anomaly marker). Spatially overlay the surface response areas with those from Step 1 (deep channels), Step 2 (middle-layer geophysical anomalies), and Step 3 (shallow geochemical constraints). Areas with high overlap among these four steps represent the highest probability target areas for hydrate enrichment.

[0071] Step S600: Spatial overlay analysis is performed on the distribution map of deep fluid migration channels, the comprehensive map of geophysical anomaly response in the middle layer, the geochemical constraint map of the shallow layer, and the comprehensive map of the surface micro-geomorphic system to obtain exploration target areas at different levels. It should be noted that the deep fluid migration channel distribution map is marked with channel markers, the intermediate geophysical anomaly response map is marked with geophysical anomaly markers, the shallow geochemical constraint map is marked with chemical constraint markers, and the surface micro-geomorphic system map is marked with geomorphic anomaly markers. The areas corresponding to the deep fluid migration channel distribution map, the intermediate geophysical anomaly response map, the shallow geochemical constraint map, and the surface micro-geomorphic system map are longitudinally distributed from deep to shallow within the study area. In some embodiments, step S600 may include the following steps: traversing each area of ​​the study area laterally as the target area; if the target area is located in the deep, intermediate, shallow, or deep regions corresponding to the deep fluid migration channel distribution map, the intermediate geophysical anomaly response map, the shallow geochemical constraint map, and the surface micro-geomorphic system map... If all areas in the surface region are marked, the target area is identified as a Level 1 target area. If only three levels of areas in the deep fluid migration channel distribution map, the comprehensive map of intermediate geophysical anomaly response, the shallow geochemical constraint map, and the comprehensive map of surface micro-geomorphic system are marked, the target area is identified as a Level 2 target area. If only two levels of areas in these maps are marked, the target area is identified as a Level 3 target area. If only one level of area in these maps is marked, the target area is identified as a Level 4 target area.

[0072] For example, in some specific embodiments, the three-dimensional detection comprehensive interpretation and target area selection can be achieved as follows: Objective and Significance: By integrating the identification results from Step 1 (deep fluid migration channels), Step 2 (middle-layer geophysical anomalies), Step 3 (shallow geochemical constraints), and Step 4 (surface micro-geomorphological systems), a comprehensive interpretation model of "deep-middle-shallow-surface" three-dimensional exploration is established. Through spatial superposition and cross-verification of the four-level spatial evidence chain, the ambiguity of single-level or single-method approaches is eliminated, enabling the scientific selection of target areas for hydrate enrichment under high fluid flux backgrounds.

[0073] In a specific embodiment, a spatial overlay of a four-level evidence chain is performed. The "Deep Fluid Migration Channel Distribution Map" output from step one, the "Middle Geophysical Anomaly Synthetic Map" output from step two, the "Shallow Geochemical Constraint Map" output from step three, and the "Surface Micro-Geomorphological System Synthetic Map" output from step four are spatially registered and overlaid.

[0074] The overlapping rules are as follows: (1) Target area of ​​level I (optimal): All four spatial layers are abnormally developed and their spatial locations are highly overlapping, namely: deep layer develops channels + middle layer develops multiple types of geophysical anomalies (BSR anomaly / bright spot / enhanced reflection / phase reversal, etc.) + shallow layer develops geochemical anomalies (SMTZ interface <10m, methane flux >10). - ² mol / m² / a) + The surface layer develops various micro-geomorphic systems (feather flow / pockmarks / submarine mounds, etc.).

[0075] (2) Level II target area (good): three levels of developmental abnormalities and spatial overlap, lacking evidence of one level.

[0076] (3) Level III target area (general): two levels of development are abnormal and spatially overlapping.

[0077] (4) Level IV (not considered): only single-level anomalies or anomalies at different levels have no spatial coupling relationship.

[0078] The core of this invention lies in establishing a four-layer three-dimensional detection architecture of "deep layer—middle layer—shallow layer—surface layer," and performing system coupling and spatial overlay analysis of multi-type identification markers at each layer. In some optional embodiments, based on the same inventive concept, the following alternative solutions can also achieve the objective of this invention: 1. Alternative Techniques: In identifying deep fluid transport channels, in addition to high-resolution 3D seismic data, comprehensive interpretation using seafloor electromagnetic exploration (CSEM) or gravity and magnetic data can improve the reliability of channel identification. In extracting mid-level geophysical anomalies, in addition to conventional seismic attribute analysis, pre-stack inversion, elastic impedance inversion, or dispersion attribute analysis can be used as alternatives or supplements. In shallow geochemical constraints, in addition to pore water geochemical analysis, in-situ sensors (such as methane sensors and pH sensors) can be used for real-time measurement, or combined with stable isotope analysis (δ¹⁸O₅). 13 C, δD) Improve the accuracy of methane flux estimation; In the identification of surface micro-topography systems, in addition to multibeam and side-scan sonar, unmanned surface vessels (USVs) equipped with shallow profiling or autonomous underwater vehicles (AUVs) can be used for high-resolution topographic surveying.

[0079] 2. Replacement and expansion of identification markers: In terms of mid-level geophysical anomalies, in addition to typical BSR, enhanced reflection, bright spot reflection, and phase reversal, markers such as low-frequency enhanced shadows, AVO anomalies, and P-wave / S-wave velocity ratio anomalies can be introduced; in terms of shallow geochemistry, in addition to SMTZ interfaces and methane flux, auxiliary indicators such as chloride ion dilution anomalies and strontium isotope anomalies in pore water can be combined; in terms of surface micro-geomorphology, in addition to plumes, pockmarks, and submarine mounds, the distribution of cold seep biological communities and the morphological classification of carbonate rock crusts (such as nodular, plate-like, and chimney-like) can be combined for more detailed identification.

[0080] 3. Alternatives to data fusion methods: In addition to spatial overlay and hierarchical identification, a quantitative weighting method can be used, assigning different weights to evidence at each level according to their importance (e.g., deep channels 0.3, mid-level anomalies 0.3, shallow geochemistry 0.2, surface micro-topography 0.2), calculating a comprehensive score and delineating the target area; alternatively, machine learning methods (e.g., random forests, support vector machines) can be used to train and predict the four-level multidimensional features of space, achieving semi-automatic or fully automatic target area selection.

[0081] 4. Alternative Implementation Process: This invention adopts a sequential progressive process of "deep → middle → shallow → surface". In practical applications, it can also be adjusted to a reverse tracing process of "surface → shallow → middle → deep" (i.e., starting from the surface micro-geomorphological response, tracing the shallow geochemical anomalies, middle geophysical responses and deep channels layer by layer), or a parallel implementation followed by comprehensive superposition. As long as the system coupling and spatial superposition analysis of the four-level spatial evidence chain are ultimately achieved, they are all alternative implementation schemes of this invention.

[0082] Therefore, alternative solutions based on similar multi-level coupling recognition principles, differing only in specific technical implementation details, are theoretically within the scope of protection of this invention.

[0083] To explain in detail the principle of the technical solution of the present invention, the overall process of the present invention will be described below with reference to some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and should not be regarded as a limitation of the present invention.

[0084] First, it should be noted that existing technologies generally lack a systematic understanding, often remaining at the level of identification using a single method or a single marker. Their common shortcomings are summarized below: (1) The methods are relatively simple and lack systematicity. Existing technologies are mostly based on single types of data (mainly seismic data) or single identification markers (such as BSR, gas chimneys), lacking a three-dimensional systematic thinking of "deep channels → mid-level response → shallow geochemistry → surface micro-geomorphology", and have not yet constructed a complete evaluation system from the perspective of gas source-sink relationship and the entire technical sequence of fluid transport.

[0085] (2) Insufficient coupling of geological systems. Existing technologies focus on geophysical signal processing or numerical calculations, and do not fully consider the systematic formation logic of hydrate reservoirs—that is, the "source (gas source)-migration (migration channel)-accumulation (accumulation space)" system, which leads to the need to improve the consistency between the identification results and the actual geological situation.

[0086] (3) There is a certain risk of misjudgment. Due to the lack of multiple evidence chains to corroborate each other, the multiple interpretations of a single geophysical anomaly (such as bright spot reflection, amplitude enhancement) are difficult to be effectively constrained, and the hydrate identification results may be at risk of misjudgment.

[0087] Therefore, the purpose of this invention is to: highlight the high fluid flux background, clearly define high fluid flux supply as the main controlling factor for hydrocarbon accumulation, establish a targeted hydrate resource exploration and evaluation method to compensate for the shortcomings of existing technologies in the evaluation of high fluid flux hydrates; construct a three-dimensional detection architecture of "deep-middle-shallow-surface" to achieve comprehensive detection of the entire technical sequence from deep (fluid migration channel identification) → middle (geophysical anomaly extraction) → shallow (geochemical quantitative constraints) → surface (micro-geomorphic system identification), establishing a systematic understanding from deep to shallow; establish a hierarchical identification marker system, so that each level has clear identification markers and corresponding technical means, forming a logical relationship of mutual verification and hierarchical constraints between levels, overcoming the shortcomings of relatively single technical means and indicator markers in existing technologies; integrate multiple methods and multiple evidence chains, organically integrating four independent methods of "deep structural geology, middle geophysics, shallow geochemistry, and surface micro-geomorphic structure" to establish a standardized and repeatable technical process for the exploration and evaluation of hydrates in the high fluid flux background, effectively reducing the risk of misjudgment caused by single means.

[0088] like Figure 3 The diagram illustrates an optional workflow example for identifying hydrate enrichment zones under high fluid flux conditions provided by an embodiment of the present invention. In some specific embodiments, the present invention addresses the problems of existing hydrate system identification technologies, such as relatively limited methods, limited geological understanding, and the need to strengthen the understanding of three-dimensional systems from deep to shallow. Based on high-resolution geophysical data, geochemical analysis, and micro-geomorphological survey data, it establishes a three-dimensional detection and evaluation system covering the "deep-middle-shallow-surface" layers, encompassing "fluid channel identification—geophysical anomaly extraction—geochemical constraints—micro-geomorphological system identification," thereby achieving efficient and standardized evaluation of hydrate enrichment and accumulation characteristics under high fluid flux conditions. Specifically, the embodiments of the present invention can be implemented through the following workflow steps: Step 1: Identification of fluid transport channels; Focus layer: Deep layer; Technical means: fine interpretation of high-resolution 3D seismic data, seismic attribute analysis (coherence volume, variance volume), velocity field analysis, and fine interpretation of seismic profiles; Identification features: chimneys, diapir structures, structural faults, fluid conduits; Objective and Significance: Starting from the hydrate "source-transport-accumulation" system of hydrocarbon accumulation, this step aims to identify deep-developed fluid migration channels. Deep fluid migration channels are crucial pathways for the vertical migration of gas-bearing fluids from deep to shallow formations under high fluid flux conditions, constituting the material supply prerequisite for hydrate enrichment and accumulation. This step aims to determine the channel types, spatial distribution, vertical extension scale, and connectivity with shallow strata.

[0089] like Figure 4 The image shows examples of identifying various channels for deep fluid transport. The specific implementation methods are as follows: 1. Gas Chimney Identification. Gas chimneys are mainly formed by the migration of deep gas-bearing fluids into shallow strata driven by overpressure. On seismic profiles, they appear as vertical or near-vertical columnar strong amplitude anomalies with chaotic or blank internal reflections, often accompanied by low-frequency reflections and reflection phase axis pull-down characteristics. They extend longitudinally and the top of the gas chimney is close to the seabed, indicating the channel for the vertical migration of deep gas-bearing fluids along the gas chimney and its internal fracture network system. In a specific embodiment, based on high-resolution 3D seismic data, seismic profiles are extracted along the direction perpendicular to the main seismic line to identify vertical columnar anomalies; combined with coherence analysis, the coherence value inside the gas chimney is significantly reduced; velocity spectra are extracted along the longitudinal direction of the gas chimney, typically showing low-velocity anomalies inside. The planar distribution range, longitudinal extension height, top burial depth, and connectivity with shallow faults of the gas chimney are recorded.

[0090] 2. Identification of Diapiric Structures. Diapiric structures are mainly formed by deep plastic materials (such as salt rock and mudstone) penetrating or subsurfacely penetrating the overlying strata. The top is often mushroom-shaped, accompanied by radial faults, and extends significantly longitudinally. The center of the diapir is relatively close to the seafloor, and diapiric activity can drive the upward migration of deep fluids. In specific embodiments, mushroom-shaped or dome-shaped structural morphology is identified on seismic profiles. The internal reflections of the diapir are chaotic or blank, and the surrounding strata show an upward contact relationship. Radial small faults develop at the top of the diapir; the thickness of the strata on both sides of the diapir changes significantly. The planar distribution, longitudinal extension depth, and top fault development characteristics of the diapir are recorded.

[0091] 3. Structural Fault Identification. Structural faults are mainly generated by tectonic tensile stress and often develop at the top of tectonic paleo-uplifts. They consist of multiple faults or fractures forming a banded structure. Individual faults are relatively long with significant displacement, while the distance between adjacent faults is small. The fault strike is often parallel to the tectonic ridge, forming a network of fluid transport channels. In specific embodiments, fault planes and the stratigraphic relationship between the two sides of the fault are identified on seismic profiles. On the fault plane, the fault extends in a banded pattern along the top of the tectonic ridge or paleo-uplift. The fault cuts downwards to deep strata and extends upwards to shallow layers or the seabed.

[0092] 4. Fluid Conduit Identification. Fluid conduits are primarily generated by formation rupture and fluid release driven by overpressured gas-bearing fluids. On seismic profiles, they appear as near-vertical tubular strong-amplitude anomalies with a small lateral diameter, extending longitudinally through shallow strata. Their internal reflection characteristics are similar to chimneys but more regular in shape, indicating the path of rapid upward migration of deep fluids along tubular channels. In specific embodiments, near-vertical tubular strong-amplitude anomalies are identified on seismic profiles, typically with a diameter of several hundred meters; the internal reflections of the conduit are chaotic or blank; the conduit connects downwards to chimneys or deep faults, and extends upwards to shallow strata or the seabed. The conduit diameter, longitudinal length, and connectivity with surrounding structures are measured.

[0093] Comprehensive identification: In a specific embodiment, if the study area has one or more of the following types of structures: gas chimneys, diapirs, tectonic faults, or fluid conduits, and the conduits extend downwards to deep gas source layers and upwards to shallow sedimentary layers or the seabed, then the area is determined to possess the geological conditions for high fluid flux and fluid transport. The identification results are output as a "Deep Fluid Transport Channel Distribution Map," which marks the channel type, spatial location, longitudinal extension range, and connectivity, serving as a background constraint map for mid-level geophysical anomaly responses.

[0094] Step 2: Geophysical anomaly extraction; Focus layer: Middle layer; Identification features: atypical BSR, enhanced reflection, bright spot reflection, phase reversal; Technical means: high-resolution 3D seismic fine interpretation, seismic attribute extraction (amplitude attribute, coherence attribute, frequency attribute), velocity field inversion, wave impedance inversion; Purpose and Significance: Under the constraints of the deep migration channels determined in Step 1, geophysical anomaly extraction is carried out in the middle layer (the hydrate stability domain and its vicinity). Middle-layer geophysical anomalies are direct geophysical manifestations of hydrate and free gas occurrence. By extracting various types of anomaly indicators and analyzing their spatial matching relationships with deep channels, geophysical evidence is provided for the delineation of hydrate-enriched areas.

[0095] like Figure 5 The image shows an example of a mid-level geophysical anomaly response, and the specific implementation method is as follows: 1. Identification of Atypical BSRs. These are typically characterized by BSR reflections that are approximately parallel to the seafloor topography, with discontinuous lateral extension and a discontinuous distribution, locally exhibiting beaded or bright spot reflections. At the corresponding locations of seepage channels, influenced by local thermal convection, the BSRs show localized upward pull, indicating a local uplift of the hydrate stability domain. In a specific embodiment, based on high-resolution 3D seismic profiles, strong reflection interfaces with polarity opposite to the seafloor are first identified; their lateral continuity is analyzed, and discontinuous or discontinuous distributions are marked; locally upward-pulling BSR segments are identified, and the magnitude of the upward pull is marked; the identification results are overlaid with the deep channel planar distribution map from step one, and the areas of BSR characteristic variation above the channels are marked.

[0096] 2. Enhanced Reflection Identification Above the BSR. Strong amplitude reflection features located above the BSR interface, exhibiting continuous or semi-continuous distribution and extending over a large lateral range, typically indicate the top interface of the hydrate layer. In a specific embodiment, on the seismic profile, the root mean square amplitude attribute is extracted within a 0-20 ms time window upwards from the BSR as the bottom boundary; the background amplitude value of the region is statistically analyzed, and areas with amplitude values ​​2-3 times higher than the background value are marked as enhanced reflection anomaly zones; the lateral extension length, longitudinal thickness, and contact relationship with the BSR of the enhanced reflection are analyzed.

[0097] 3. Bright Spot Reflection Identification. This manifests as a significant increase in local amplitude, with limited lateral extension compared to enhanced reflection. It typically presents as localized point-like or beaded distributions within seepage channels, usually indicating localized enrichment of highly saturated hydrates or cold seep carbonate formations. In a specific embodiment, localized strong-amplitude "bright spots" are identified on seismic profiles, typically less than 100m wide. The spatial relationship between these bright spots and deep channels is analyzed, and the number of bright spots developed at the top and periphery of the channels is counted. Combined with phase characteristics, the likelihood of the bright spots being hydrate layers (positive polarity) or free gas layers (negative polarity) is determined.

[0098] 4. Phase Reversal Identification. Phase reversal refers to the phenomenon of a significant polarity change between the seismic reflection phase axis and the surrounding strata. Under high fluid flux conditions, due to convective heat transfer, a central gas layer often forms on the plane, transitioning to hydrate layers on both sides, creating a mineral body distribution pattern. In this case, the boundary between the gas layer and the hydrate layer will show an inverse polarity reversal characteristic on the seismic reflection phase axis. Furthermore, under the influence of seepage fluid flux, gas enters the shallow seafloor. If the shallow sediments contain air bubbles, a polarity reversal characteristic will also appear, such as the negative polarity reflection generated after the air bubbles rise to the seafloor. The presence of a phase reversal on the seismic reflection phase axis on the seafloor usually indicates the presence of active cold seeps. In a specific embodiment, the polarity change of the reflection phase axis is traced along the vertical profile on the seismic profile, marking the location and spatial distribution characteristics of the polarity reversal from the BSR upwards to the seafloor, and then overlaid and matched with the deep channel plane projection from step one.

[0099] 5. Velocity Anomaly Certification. Based on the velocity field inversion results, high-velocity anomalies above the BSR are identified. Due to their high degree of consolidation and low porosity, hydrates exhibit significantly higher P-wave velocities than the surrounding rock strata. Velocity inversion can be used to infer hydrate-rich areas. In a specific embodiment, Gaussian beam inversion or full waveform inversion is used to obtain the shallow P-wave velocity field; a structurally stable, homogeneous region without anomalous reflections is selected to statistically analyze the background velocity; when the P-wave velocity of the strata is significantly higher than the background velocity (usually 30%~50% higher), and the anomalous region is located above the BSR, it is determined to be a velocity anomaly (hydrate indicator).

[0100] Comprehensive identification: The above-mentioned geophysical anomaly markers (atypical BSR, enhanced reflection, bright spot reflection, phase reversal, velocity anomaly) are spatially overlaid to mark the planar distribution range and vertical stratigraphic position of each anomaly. A "Comprehensive Map of Mid-Layer Geophysical Anomaly Responses" is output, highlighting anomaly areas with good spatial coupling to deep channels (i.e., areas with multiple anomalies developing at and around the channel tip), which serve as key target areas for shallow geochemical constraints.

[0101] Deep fluid channels are the material basis for hydrate accumulation; without channels, there's no point in proceeding. Similarly, even if a channel exists, if no decent geophysical anomalies (such as enhanced reflection or bright spots) can be found around it, the channel is considered "empty," and further geochemical and micro-topographic analysis is unnecessary. Therefore, if no valid anomalies are found in steps one (channel identification) and two (geophysical anomaly extraction), the process can be terminated directly; there's no need to force it further.

[0102] Step 3: Shallow geochemical constraints; Focused layer: shallow layer; Identification markers: SMTZ interface depth, methane flux, pore water geochemical anomaly, and heat flux value; Technical methods: pore water geochemical analysis, in-situ heat flux measurement, SMTZ depth estimation, and methane flux calculation; Purpose and Significance: Within the target areas delineated in Step 1 (deep fluid migration channels) and Step 2 (middle-layer geophysical anomalies), shallow geochemical constraints are established. Shallow geochemical parameters (SMTZ interface depth, sulfate flux, methane flux, etc.) can quantitatively reflect the magnitude of methane upward diffusion or leakage flux, and are key indicators for evaluating the intensity of gas supply for hydrate accumulation. This step provides geochemical evidence for hydrate-rich areas, effectively reducing the risk of misinterpretation of geological information using a single geophysical method.

[0103] like Figure 6 The image shows an example of shallow geochemical confinement, and the specific implementation method is as follows: 1. Geochemical analysis of sediment pore water. Gravity columnar samples are collected within the target area, spaced at regular intervals (usually 20-50 cm), and pore water is extracted. Sulfate ion concentration (SO42-) is determined. 2- Dissolved inorganic carbon (DIC), calcium ions (Ca) 2+ ), magnesium ions (Mg 2+ ), Strontium ion (Sr) 2+ ), chloride ions (Cl) - Concentrations of various ions were plotted. In a specific embodiment, a profile of the concentration of each ion as a function of depth was drawn. The sulfate concentration decreased linearly or exponentially with depth, indicating the intensity of the anaerobic oxidation of methane (AOM) process; the DIC concentration increased with depth, mirroring the decrease in sulfate concentration; calcium, magnesium, and strontium ions often exhibited anomalies (precipitation or release) near the SMTZ interface.

[0104] 2. SMTZ Interface Calculation and Identification. The SMTZ (sulfate-methane interface) refers to the depth interface in sediments where the sulfate concentration approaches zero and methane begins to appear. The SMTZ interface depth is negatively correlated with methane flux—the shallower the SMTZ interface, the greater the methane flux. In a specific embodiment, based on the pore water sulfate concentration profile, linear or exponential fitting is used to extrapolate to the depth where the sulfate concentration is zero, which is determined as the SMTZ interface depth. The SMTZ interface depth at each station is statistically analyzed, and SMTZ interface contour maps are plotted. An SMTZ interface shallower than 5 mbsf (meters below the seabed) indicates high fluid flux seepage activity, shallower than 10-20 mbsf indicates moderate flux, and deeper than 20 mbsf indicates a low flux background.

[0105] 3. Calculation of sulfate flux and methane flux. Sulfate flux (J_SO4) 2- Calculation formula: J_SO4 2- = -φ ×Ds × (dc / dz), where φ is porosity, Ds is diffusion coefficient, and dc / dz is sulfate concentration gradient. Methane flux (J_CH4) is based on the stoichiometric ratio of the AOM reaction (CH4 + SO42-). 2- → HCO3 - + HS - Based on the calculation using H2O, theoretically J_CH4 = J_SO4 2- In a specific embodiment, the sulfate flux at each station is calculated, and then the methane flux is estimated. Methane flux > 10 -2 mol / m 2 / a indicates high fluid flux leakage, 10 -3 ~10 -2 mol / m 2 / a indicates medium flux, <10 -3 mol / m 2 / a indicates a low flux background. The calculation results are plotted on the contour map of the SMTZ interface to identify areas of high fluid flux anomalies.

[0106] 4. In-situ heat flux measurement and stability zone calculation. The seafloor heat flux is measured in situ using a heat flux probe. Combined with parameters such as water depth, seafloor temperature, geothermal gradient, and pressure, the thickness and bottom boundary depth of the natural gas hydrate stability zone are calculated. In a specific embodiment, the measured heat flux values ​​are compared with the regional background heat flux values ​​to identify local heat flux anomalies (usually related to fluid activity). The suitability of the temperature and pressure conditions for hydrate accumulation within the hydrate stability zone is comprehensively analyzed, combining the SMTZ interface and methane flux calculation results.

[0107] Step 4: Identification of surface micro-topography systems; Focus layer: surface layer; Identification markers: plume-like currents, pockmarks, submarine mounds, strong submarine reflections, and cold seep biomes; Technical means: multibeam bathymetry, water imaging, side-scan sonar, shallow seismic profiling, seabed photography / ROV survey; Purpose and Significance: Within the deep-intermediate-shallow overlapping target area delineated in steps one through three, surface micro-topographic systems will be identified. Surface micro-topography is the most direct surface manifestation of high fluid flux-driven hydrate systems: plumes indicate ongoing fluid leakage, pockmarks indicate leakage history, submarine mounds indicate shallow hydrate growth or carbonate rock formation, and strong submarine reflections indicate cold seeps and carbonate crusts. This step provides direct observational evidence of the hydrate system at the outermost layer, forming a complete chain of evidence from source to sink with evidence from deep, intermediate, and shallow layers.

[0108] like Figure 7 The image shows an example of a surface micro-topography system, and the specific implementation method is as follows: 1. Plume Identification. Plumes are anomalous echoes formed by the leakage of active methane fluid into a water column, serving as direct evidence of an active hydrate system. In specific embodiments, plume echo anomalies in the water profile are extracted based on full-depth water body data from a multibeam echo system (such as the Kongsberg EM 302 multibeam bathymetry system) or high-frequency water imaging data from a fish finder. Plumes appear as bundles, feathers, or chimneys in the water profile, extending tens to hundreds of meters upwards from the seabed. The height, width, reflection intensity, and spatial location of the plume are measured.

[0109] 2. Pockmark Identification. Pockmarks are negative topographic depressions on the seabed surface, formed by fluid seepage or gas escape after hydrate decomposition. They often occur in clusters and are important indicators of shallow fluid activity history and seepage-type hydrate systems. In a specific embodiment, based on high-resolution multibeam bathymetry data, a digital topographic model (DTM, grid resolution typically ≤25m) is extracted from the seabed. Through topographic slope analysis, curvature analysis, and manual interpretation, circular, elliptical, or elongated negative topographic depressions are identified. The diameter (typically tens to hundreds of meters), depth (several meters to tens of meters), morphological characteristics, and spatial distribution patterns of the pockmarks are measured. The density of pockmarks is statistically analyzed; areas with clustered distributions and overlapping with deep channel projections are more indicative.

[0110] 3. Identification of Submarine Mounds. Submarine mounds are positive topographic elevations on the seabed surface, typically caused by the growth of hydrates in the shallow layer, cold seep carbonate formations, or mud volcano activity. They often feature cold seep communities or carbonate crusts at their top. In this specific embodiment, positive submarine topographic elevations are identified based on high-resolution multibeam bathymetry data and side-scan sonar images. Submarine mounds typically appear as areas of strong reflection and high backscattering intensity on side-scan sonar images. The height, base diameter, and top morphology of the mound are measured. Combined with seabed video or ROV surveys, it is confirmed whether cold seep organisms (clams, mussels, tube worms, etc.) or carbonate crusts are present at the top of the mound.

[0111] 4. Identification of Strong Seafloor Reflections. Cold seep carbonate rocks are products of anaerobic methane oxidation (AOM) processes, exhibiting strong seafloor reflections and high backscattering intensities in side-scan sonar and shallow seismic profiles, often associated with seafloor mounds. In specific embodiments, based on side-scan sonar data, areas of high backscattering intensity anomalies on the seafloor are identified, typically distributed in patchy, banded, or irregular shapes. Based on shallow seismic profiles, strong seafloor reflection interfaces are identified, often beneath which acoustic blanks or acoustic disturbances are frequently observed. Verification is then performed using seafloor video data to confirm the morphology of carbonate rock crusts, nodules, or massive formations.

[0112] Comprehensive identification: Based on the comprehensive identification of surface micro-geomorphic system markers such as plumes, pits, submarine mounds, and strong submarine reflections, delineate surface anomaly response areas. Output a "Comprehensive Map of Surface Micro-Geomorphic Systems," marking the spatial location, type, and confidence level of various responses (e.g., Level I – Multiple anomalies superimposed with plumes; Level II – Multiple anomalies superimposed but without plumes; Level III – Single anomaly marker). Spatially overlay the surface response areas with those from Step 1 (deep channels), Step 2 (middle-layer geophysical anomalies), and Step 3 (shallow geochemical constraints). Areas with high overlap among these four steps represent the highest probability target areas for hydrate enrichment.

[0113] Step 5: Comprehensive Interpretation of Three-Dimensional Detection and Target Area Selection Objective and Significance: By integrating the identification results from Step 1 (deep fluid migration channels), Step 2 (middle-layer geophysical anomalies), Step 3 (shallow geochemical constraints), and Step 4 (surface micro-geomorphological systems), a comprehensive interpretation model of "deep-middle-shallow-surface" three-dimensional exploration is established. Through spatial superposition and cross-verification of the four-level spatial evidence chain, the ambiguity of single-level or single-method approaches is eliminated, enabling the scientific selection of target areas for hydrate enrichment under high fluid flux backgrounds.

[0114] In a specific embodiment, a spatial overlay of a four-level evidence chain is performed. The "Deep Fluid Migration Channel Distribution Map" output from step one, the "Middle Geophysical Anomaly Synthetic Map" output from step two, the "Shallow Geochemical Constraint Map" output from step three, and the "Surface Micro-Geomorphological System Synthetic Map" output from step four are spatially registered and overlaid.

[0115] The overlapping rules are as follows: (1) Target area of ​​level I (optimal): All four spatial layers are abnormally developed and their spatial locations are highly overlapping, namely: deep layer develops channels + middle layer develops multiple types of geophysical anomalies (BSR anomaly / bright spot / enhanced reflection / phase reversal, etc.) + shallow layer develops geochemical anomalies (SMTZ interface <10m, methane flux >10). - ² mol / m² / a) + The surface layer develops various micro-geomorphic systems (feather flow / pockmarks / submarine mounds, etc.).

[0116] (2) Level II target area (good): three levels of developmental abnormalities and spatial overlap, lacking evidence of one level.

[0117] (3) Level III target area (general): two levels of development are abnormal and spatially overlapping.

[0118] (4) Level IV (not considered): only single-level anomalies or anomalies at different levels have no spatial coupling relationship.

[0119] The determination of high overlap can be achieved as follows: Specifically, the boundary of the deep channel can be used as a benchmark, with a buffer zone of 500 meters outward as the "primary correlation zone"—anomalies in the middle, shallow, and surface layers within this range are considered to be highly overlapped. The area 500 to 1500 meters outward is designated as the "secondary correlation zone," considered to be of medium overlap. Anomalies beyond 1500 meters are generally unrelated to the channel.

[0120] In summary, the evaluation of hydrate enrichment and accumulation under high fluid flux conditions is a cutting-edge direction in marine hydrate resource exploration, and its evaluation results directly affect resource estimation and drilling deployment. This invention addresses the bottlenecks of existing technologies, such as their relatively singular approach and insufficient systematic understanding. Based on the theory of hydrate system formation, it innovatively establishes a four-tiered comprehensive three-dimensional detection and evaluation system: "deep (fluid transport channels) – middle layer (geophysical anomaly response) – shallow layer (geochemical constraints) – surface layer (micro-geomorphic system)," achieving a technological evolution from single-marker identification to multi-level, multi-chain evidence system-wide comprehensive identification.

[0121] The key challenges of this invention lie in the standardized extraction of identification markers at each level, the superposition of the four-level spatial evidence chain, and the localized calibration of evaluation parameters under different geological backgrounds. This invention effectively solves these problems by introducing high-resolution three-dimensional seismic fine interpretation, multi-type seismic attribute analysis, quantitative calculation of pore water geochemistry, and three-dimensional fusion of multi-source acoustic data, combined with practical application verification in typical work areas, ensuring the reliability and practicality of the evaluation results. Specifically, this invention provides the following technical innovations: Innovation Point 1: Establishing a high-fluid-throughput hydrate enrichment and accumulation evaluation method based on a three-dimensional detection framework of "deep (fluid transport channels) – middle (geophysical anomaly response) – shallow (geochemical constraints) – surface (micro-geomorphic system)". This invention overcomes the limitations of existing technologies, which are relatively singular, lack systematicity, and have insufficient understanding of the three-dimensional system from deep to shallow. Starting from the theory of hydrate "source-transport-accumulation" system accumulation, it spatially couples deep channel identification, middle-layer geophysical anomaly extraction, shallow geochemical constraints, and surface micro-geomorphic system identification into a four-level system, forming a three-dimensional detection system that is progressively verified from deep to shallow and mutually constrained by multiple evidence chains. This effectively reduces the risk of multiple interpretations and misjudgments when using single methods for hydrate system identification.

[0122] Innovation Point Two: A standardized and comprehensive system for identifying anomalies at different spatial levels has been established. This invention clearly defines corresponding identification markers and technical methods for each of the "deep, middle, shallow, and surface" layers: For the deep layer, seismic data is used to identify gas chimneys, diapirs, faults, and fluid conduits; for the middle layer, high-resolution seismic data is used to identify atypical BSRs, enhanced reflections, bright spot reflections, and phase reversals; for the shallow layer, geochemical characterization is used to obtain SMTZ interfaces, sulfate flux, methane flux, and heat flow anomalies; and for the surface layer, multibeam sonar, water imaging, side-scan sonar, and shallow seismic profiling are used to identify plumes, pockmarks, submarine mounds, and strong submarine reflections. Each layer is mutually supportive and logically clear, forming a standardized and repeatable technical process system.

[0123] Innovation Point 3: A comprehensive identification rule for spatial overlap of a four-level evidence chain is constructed. This invention establishes a target differentiation grading standard based on the degree of spatial four-level abnormal overlap (Level I: four-level spatial overlap, Level II: three-level overlap, and Level III: two-level overlap), providing an operable identification basis for the quantitative evaluation and selection of hydrate enrichment areas.

[0124] Innovation Point Four: This invention enables low-cost, high-efficiency resource assessment of seepage hydrates in the absence of BSRs or in atypical BSR environments. It does not rely on typical BSR development and is particularly suitable for high-fluid-fluid-through-seepage hydrate systems. Based on conventional geophysical, geochemical, and micro-geomorphological survey data (at a cost far lower than drilling), a three-dimensional detection and evaluation system enables rapid regional-scale screening and target selection, effectively improving exploration efficiency, resource assessment accuracy, and economic viability.

[0125] Compared with the prior art, the present invention has at least the following beneficial effects: 1. Three-dimensional detection: Breaking through the limitations of single technical means, a three-dimensional detection system of "deep channel identification - middle geophysical response - shallow geochemical constraints - surface micro-geomorphic system" was constructed, realizing a systematic evaluation of the entire technical sequence of the "source-transport-accumulation" process of hydrate system.

[0126] 2. Advantages of multi-evidence chain coupling: By spatially superimposing and cross-validating four independent evidence chains of structural geology, geophysics, geochemistry and micro-geomorphology, the ambiguity of single anomaly markers (such as the difficulty of distinguishing between hydrates, free gas and carbonate rocks) is effectively reduced, and the risk of misjudgment is significantly reduced.

[0127] 3. Geological Systemicity: Unlike existing technologies that tend to focus on signal processing or numerical calculation, this invention is always guided by the geological theory of hydrate system formation, emphasizing the geological logic of "deep channels controlling migration, geophysical indicators of accumulation, geochemical reflections of seepage, and micro-geomorphological indicators of surface features", making the evaluation results more geologically reasonable.

[0128] 4. High efficiency and economic advantages: This method does not rely on high-cost drilling; rapid screening and target selection at the regional scale can be achieved based on conventional geophysical, geochemical, and micro-geomorphological surveys. Practical applications show that this method can effectively improve exploration efficiency and economy.

[0129] like Figure 8 As shown, this embodiment of the invention also provides a hydrate enrichment region identification and prediction device 900 under high fluid flux background, which can implement the above-mentioned method. The device may include: The first module 901 is used to acquire research data in the study area; the research data includes high-resolution three-dimensional seismic data, seafloor topographic data, water acoustic data, shallow seismic profile data, sediment pore water samples and in-situ heat flow measurement data, and each data in the research data is spatially registered in advance in the study area; The second module 902 is used to extract the geometric morphology and attribute characteristics of deep fluid transport channels based on high-resolution three-dimensional seismic data through seismic attribute analysis and structural interpretation, and generate a distribution map of deep fluid transport channels. The third module 903 is used to extract geophysical anomaly markers coupled with channel space from the seismic data volume based on the distribution map of deep fluid transport channels and to generate a comprehensive map of mid-level geophysical anomaly response. Module 4, 904, is used to obtain geochemical parameters reflecting methane flux through quantitative geochemical analysis based on sediment pore water samples and in-situ heat flow measurement data, and then delineate shallow geochemical anomaly zones to generate shallow geochemical constraint maps. The fifth module 905 is used to extract micro-topography and cold seep markers related to fluid activity based on seabed topography data, water acoustic data and shallow seismic profile data, and then generate a comprehensive map of the surface micro-topography system through credibility grading. Module 6, 906, is used to perform spatial overlay analysis on the distribution map of deep fluid migration channels, the comprehensive map of geophysical anomaly response in the middle layer, the geochemical constraint map of the shallow layer, and the comprehensive map of the surface micro-geomorphic system to obtain exploration target areas at different levels.

[0130] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0131] This invention also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0132] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0133] like Figure 9 As shown, Figure 9 The hardware structure of an electronic device 1000 according to another embodiment is illustrated. The electronic device 1000 includes: The processor 1001 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (aSIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention. The memory 1002 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RaM). The memory 1002 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called and executed by the processor 1001. Input / output interface 1003 is used to implement information input and output; The communication interface 1004 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 1005 transmits information between various components of the device (e.g., processor 1001, memory 1002, input / output interface 1003, and communication interface 1004); The processor 1001, memory 1002, input / output interface 1003 and communication interface 1004 are connected to each other within the device via bus 1005.

[0134] The electronic device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0135] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0136] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0137] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0138] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0139] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0140] The present invention provides a method, apparatus, electronic device, storage medium, and program product for identifying and predicting hydrate enrichment areas under high fluid flux backgrounds. This method acquires research data from a study area, including high-resolution 3D seismic data, seafloor topography data, underwater acoustic data, shallow seismic profile data, sediment pore water samples, and in-situ heat flow measurement data. Each data point in the study area is pre-registered spatially. Based on the high-resolution 3D seismic data, the geometric morphology and attribute characteristics of deep fluid transport channels are extracted through seismic attribute analysis and tectonic interpretation to generate a deep fluid transport channel distribution map. Based on the deep fluid transport channel distribution map, high-resolution 3D seismic data is used to extract... Geophysical anomaly markers coupled with channel space are used to generate a comprehensive map of mid-level geophysical anomaly responses. Based on sediment pore water samples and in-situ heat flow measurement data, geochemical parameters reflecting methane flux are obtained through quantitative geochemical analysis, thereby delineating shallow geochemical anomaly zones to generate shallow geochemical constraint maps. Based on seafloor topography data, water acoustic data, and shallow seismic profile data, micro-geomorphic features and cold seep markers related to fluid activity are extracted, and then a comprehensive map of the surface micro-geomorphic system is generated through confidence grading. Spatial overlay analysis is performed on the deep fluid transport channel distribution map, the comprehensive map of mid-level geophysical anomaly responses, the shallow geochemical constraint map, and the comprehensive map of the surface micro-geomorphic system to obtain exploration target areas at different levels. This invention constructs a three-dimensional data foundation covering deep to surface layers using multi-source research data. Based on this, it extracts deep fluid transport channels, mid-layer geophysical anomalies, shallow geochemical parameters, and surface micro-geomorphic markers, enabling the matching of identification markers at each level. This effectively overcomes the shortcomings of traditional methods that rely on single methods. Finally, by spatially overlaying and analyzing the four-layer (deep, mid-layer, shallow, and surface) maps and outputting tiered target areas, a complete chain of evidence is formed, progressively confirming each layer from deep to shallow. This effectively reduces the risk of misjudgment due to the ambiguity of single anomaly markers, thus significantly improving the accuracy and reliability of identifying high-fluid-fluid-fluid hydrate-rich areas.

[0141] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present invention, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0142] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0143] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0144] The preferred embodiments of the present invention have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and spirit of the present invention should be within the scope of the claims of the present invention.

Claims

1. A method for identifying and predicting hydrate enrichment regions under high fluid flux conditions, characterized in that, The method includes the following steps: Acquire research data for the study area; wherein, the research data includes high-resolution three-dimensional seismic data, seafloor topographic data, water acoustic data, shallow seismic profile data, sediment pore water samples and in-situ heat flow measurement data, and each data in the research data has been spatially registered in the study area in advance; Based on the high-resolution three-dimensional seismic data, the geometric morphology and attribute characteristics of deep fluid transport channels are extracted through seismic attribute analysis and structural interpretation, and a distribution map of deep fluid transport channels is generated. Based on the deep fluid transport channel distribution map, geophysical anomaly markers coupled with the channel space are extracted from the seismic data volume using the high-resolution three-dimensional seismic data to generate a comprehensive map of mid-level geophysical anomaly responses. Based on the sediment pore water samples and the in-situ heat flow measurement data, geochemical parameters reflecting methane flux are obtained through quantitative geochemical analysis, and shallow geochemical anomaly zones are delineated to generate shallow geochemical constraint maps. Based on the seabed topographic data, the water acoustic data, and the shallow seismic profile data, micro-topography and cold seep markers related to fluid activity are extracted, and then a comprehensive map of the surface micro-topography system is generated through credibility grading. Spatial overlay analysis was performed on the distribution map of deep fluid migration channels, the comprehensive map of geophysical anomalies in the middle layer, the comprehensive map of shallow geochemical constraints, and the comprehensive map of surface micro-geomorphic systems to obtain exploration target areas at different levels.

2. The method according to claim 1, characterized in that, The acquisition of research data for the study area includes the following steps: The high-resolution three-dimensional seismic data was acquired by a three-dimensional seismic acquisition system towed by a geophysical exploration vessel. The seabed topographic data and the water acoustic data are acquired simultaneously using a multibeam echo sounder system. The shallow seismic profile data is obtained by using a shipborne or deep-towed shallow seismic profiler to emit sound pulses from a high-frequency sound source and receive the reflected signals from the shallow sedimentary layer on the seabed. A pore water sample from the sediment was obtained using a gravity sampler. The in-situ heat flow measurement data is obtained using a heat flow probe; The high-resolution 3D seismic data, the seabed topographic data, the water acoustic data, the shallow seismic profile data, the sediment pore water samples, and the in-situ heat flow measurement data are uniformly spatially registered and format converted to construct a standardized multi-source dataset as the research data.

3. The method according to claim 1, characterized in that, The high-resolution 3D seismic data includes a 3D seismic data volume. Based on the high-resolution 3D seismic data, the geometric morphology and attribute characteristics of deep fluid migration channels are extracted through seismic attribute analysis and structural interpretation to generate a distribution map of deep fluid migration channels. This includes the following steps: By extracting coherence and variance seismic attributes from the three-dimensional seismic data volume, candidate regions with low coherence and / or low variance in the study area that exhibit chaotic or blank internal reflections are identified. Based on the candidate region, the channel morphology is identified through detailed interpretation of seismic profiles to obtain the corresponding channel set in the study area, and the spatial location of each channel in the channel set is determined; wherein, the channel types corresponding to the channel morphology include gas chimneys, diapiric structures, structural faults, and fluid conduits. Based on the three-dimensional seismic data volume, the planar distribution range, longitudinal extension length and top burial depth of each channel in the channel set are determined, and then the connectivity of each channel in the channel set with the deep gas source layer downward and with the shallow strata upward is calibrated as connectivity information. The deep fluid transport channel distribution map is generated by using the channel type, spatial location, connectivity information, and longitudinal extension range corresponding to the longitudinal extension length as channel markers.

4. The method according to claim 1, characterized in that, The deep fluid transport channel distribution map is marked with the channel type, spatial location, longitudinal extension range, and connectivity information corresponding to each channel. Based on the deep fluid transport channel distribution map, the high-resolution three-dimensional seismic data is used to extract geophysical anomaly markers spatially coupled with the channels from the seismic data volume to generate a comprehensive map of mid-level geophysical anomaly responses, including the following steps: Using the deep fluid transport channel distribution map as a spatial constraint background, geophysical anomaly markers of the top of each channel and the adjacent area are extracted from the seismic data volume corresponding to the high-resolution three-dimensional seismic data. Among them, the geophysical anomaly markers include: enhanced reflection, local bright spot reflection and co-axial phase reversal features above the atypical seafloor-like reflector layer; and high-velocity anomalies above the atypical seafloor-like reflector layer obtained by calibration using the P-wave velocity field obtained by pre-stack or full waveform inversion. The spatial distribution range of various anomalies in the geophysical anomaly markers is superimposed on the distribution map of deep fluid migration channels, and the spatial coupling relationship between various anomalies and each channel is marked to generate the comprehensive map of the response of the middle geophysical anomalies.

5. The method according to claim 1, characterized in that, The process of obtaining geochemical parameters reflecting methane flux through quantitative geochemical analysis based on the sediment pore water samples and in-situ heat flow measurement data, and then delineating shallow geochemical anomaly zones to generate shallow geochemical constraint maps, includes the following steps: The sulfate ion concentration was extracted from the sediment pore water sample, and then the attenuation profile of the sulfate ion concentration with depth was obtained by fitting. Based on the attenuation profile, the sulfate-methane interface is determined and converted into interface contour lines by linear or exponential fitting and extrapolation to the depth where the concentration is zero; wherein, the depth of the sulfate-methane interface is negatively correlated with the methane flux, and the shallower the sulfate-methane interface, the greater the methane flux. Based on the attenuation profile, the sulfate concentration gradient is determined. The preset porosity and diffusion coefficient are multiplied by the sulfate concentration gradient, and then the sulfate flux is obtained by taking the negative value. Based on the stoichiometric ratio of the anaerobic oxidation reaction of methane, the methane flux is calculated from the sulfate flux, and flux is classified by a preset threshold. By comparing the in-situ heat flow measurement data with the background heat flow value of the corresponding area in the study area, local heat flow anomaly areas are identified. The shallow geochemical constraint map is generated by using the interface contour lines, the flux classification corresponding to each region, and the local heat flow anomaly areas as chemical constraint markers.

6. The method according to claim 1, characterized in that, Based on the seabed topographic data, the water acoustic data, and the shallow seismic profile data, micro-topography and cold seep indicators related to fluid activity are extracted, and then a comprehensive surface micro-topography system map is generated through a reliability grading process, including the following steps: The acoustic data of the water body is processed by water imaging to extract the plume anomaly extending upward from the seabed. The seabed topography data is converted into a digital topography model, and then the pockmarks of circular or elliptical negative topography are extracted through topography analysis. Identify submarine mounds and carbonate crusts with strong reflective features on the shallow seismic profile data; The plume anomaly, the pit group, the submarine mound, and the carbonate rock crust are used as geomorphic anomaly markers. The surface anomaly response zone is delineated in the study area, and the credibility is graded according to the degree of combination between the geomorphic anomaly markers to generate a comprehensive map of the surface micro-geomorphic system. The confidence level is as follows: Level 1 confidence level, which includes multiple types of geomorphic anomaly markers superimposed and containing the plume anomaly; Level 2 confidence level, which includes multiple types of geomorphic anomaly markers superimposed but does not contain the plume anomaly; and Level 3 confidence level, which includes only a single type of geomorphic anomaly marker.

7. The method according to claim 1, characterized in that, The deep fluid migration channel distribution map is marked with channel markers, the intermediate geophysical anomaly response map is marked with geophysical anomaly markers, the shallow geochemical constraint map is marked with chemical constraint markers, and the surface micro-geomorphic system map is marked with geomorphic anomaly markers. The areas corresponding to the deep fluid migration channel distribution map, the intermediate geophysical anomaly response map, the shallow geochemical constraint map, and the surface micro-geomorphic system map are distributed longitudinally from deep to shallow in the study area. The spatial overlay analysis of the deep fluid migration channel distribution map, the intermediate geophysical anomaly response map, the shallow geochemical constraint map, and the surface micro-geomorphic system map to obtain exploration target areas of different levels includes the following steps: The study area is traversed horizontally to identify each region as the target area. If the target area is marked in the deep fluid transport channel distribution map, the comprehensive map of the intermediate geophysical anomaly response, the shallow geochemical constraint map, and the comprehensive map of the surface micro-geomorphic system, the target area is determined to be a first-level target area. If the target area has markings in only three of the following layers: the deep fluid transport channel distribution map, the intermediate geophysical anomaly response comprehensive map, the shallow geochemical constraint map, and the surface micro-geomorphic system comprehensive map, then the target area is determined to be a secondary target area. If the target area has markings in only two of the following maps: the deep fluid transport channel distribution map, the comprehensive map of the intermediate geophysical anomaly response, the shallow geochemical constraint map, and the comprehensive map of the surface micro-geomorphic system, then the target area is determined to be a level 3 target area. If the target area has a marked area in only one of the following three maps: the deep fluid transport channel distribution map, the intermediate geophysical anomaly response map, the shallow geochemical constraint map, and the surface micro-geomorphic system map, then the target area is determined to be a level four target area.

8. A device for identifying and predicting hydrate enrichment zones under high fluid flux conditions, characterized in that, The device includes: The first module is used to acquire research data in the study area; wherein, the research data includes high-resolution three-dimensional seismic data, seafloor topographic data, water acoustic data, shallow seismic profile data, sediment pore water samples and in-situ heat flow measurement data, and each data in the research data has been spatially registered in the study area in advance; The second module is used to extract the geometric morphology and attribute characteristics of deep fluid transport channels based on the high-resolution three-dimensional seismic data through seismic attribute analysis and structural interpretation, and generate a distribution map of deep fluid transport channels. The third module is used to extract geophysical anomaly markers coupled with the channel space from the seismic data volume based on the deep fluid transport channel distribution map and the high-resolution three-dimensional seismic data, and generate a comprehensive map of the mid-level geophysical anomaly response. The fourth module is used to obtain geochemical parameters reflecting methane flux through quantitative geochemical analysis based on the sediment pore water sample and the in-situ heat flow measurement data, and then delineate shallow geochemical anomaly zones to generate shallow geochemical constraint maps. The fifth module is used to extract micro-topography and cold seep markers related to fluid activity based on the seabed topography data, the water acoustic data, and the shallow seismic profile data, and then generate a comprehensive map of the surface micro-topography system through credibility grading. The sixth module is used to perform spatial overlay analysis on the distribution map of deep fluid migration channels, the comprehensive map of geophysical anomaly response in the middle layer, the geochemical constraint map of the shallow layer, and the comprehensive map of the surface micro-geomorphic system to obtain exploration target areas at different levels.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 7.

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