A method for identifying a seabed shallow hydrate system based on high-precision seismic data and related equipment

Abstract

The application discloses a kind of based on high-precision seismic data's seabed shallow hydrate system identification method and related equipment, and the present application is coupled with space preliminary by identifying tectonic geologic body and fluid transport channel, realize from " source-transport-concentrate " reservoir element and start to delineate potential favorable area;Through quantitative attribute extraction and abnormal body classification identification, shallow seismic anomaly identification can be from qualitative experience to quantitative standardization;In addition, by introducing regional background velocity trend surface to calibrate velocity anomaly high-speed body, and identifying non-typical BSR as stable domain constraint, it can realize the parameter conversion from velocity field to geological property;Finally, by coupling abnormal target body and high-speed anomaly body with space analysis and judging target area based on this, it can effectively exclude the multiple solutions of single anomaly, make the result more reliable, process can be repeated, can be widely applied in data processing technical field.

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 shallow seafloor hydrate systems based on high-precision seismic data. Background Technology

[0002] Natural gas hydrates are a new type of clean energy with enormous resource potential, and their exploration and identification mainly rely on seismic geophysical methods. Traditionally, seafloor reflectors (BSRs) on seismic profiles have been considered the core indicator for identifying hydrate occurrences. These reflectors typically correspond to the bottom boundary of the hydrate stability domain and exhibit seismic responses that are approximately parallel to the seafloor and have opposite reflection polarities. However, with the advancement of exploration practices, shallow seepage hydrates from the seafloor have gradually become a research focus. These hydrates often occur in massive or vein-like formations in shallow strata below the seafloor, lacking or only developing atypical BSRs, rendering the traditional method based on BSRs as the core criterion ineffective.

[0003] Current methods for identifying shallow hydrates largely rely on direct observation techniques such as drilling, well logging, and seabed photography. While these methods offer high accuracy, they suffer from drawbacks such as high cost per site, limited coverage, and long processing times, making them unsuitable for large-scale resource screening. Some seismic attribute-based methods attempt to infer hydrates from single anomaly markers like gas chimneys and bright spot reflections, but these methods lack quantification of identification criteria and fail to systematically couple hydrocarbon accumulation elements such as structure, fluid, anomalies, and velocity, leading to significant ambiguity and difficulty in reliably distinguishing hydrates from non-hydrate geological bodies such as free gas and carbonate rocks. Furthermore, existing technical processes suffer from low standardization, resulting in poor generalization ability and inconsistent results across different work areas. Summary of the Invention

[0004] The main objective of this invention is to propose a method, device, electronic device, storage medium, and program product for identifying shallow seafloor hydrate systems based on high-precision seismic data, aiming to solve at least one problem in the prior art.

[0005] To achieve the above objectives, one aspect of the present invention proposes a method for identifying shallow seafloor hydrate systems based on high-precision seismic data, the method comprising: Acquire seismic data volume for the target area; Based on seismic data volume identification, target geological bodies and fluid transport channels are identified, and then the target spatial range of potential favorable hydrate accumulation areas is delineated through preliminary spatial coupling. Based on the target spatial range and the predetermined range below the seabed, the quantitative attribute anomaly extraction and anomaly body classification of shallow seismic reflection are performed using seismic data volume to obtain seismic reflection anomaly target bodies. Based on the seismic data volume, the P-wave velocity field of shallow strata is obtained through constrained inversion. Based on the P-wave velocity field, the high-velocity velocity anomaly is identified by constructing a regional background velocity trend surface. Based on the seismic data volume, atypical seafloor-like reflector layers are identified by pre-defined markers. Using the atypical seafloor-like reflective layer as the bottom boundary constraint of the hydrate stability domain, spatial coupling analysis is performed on the seismic reflection anomaly target body and the velocity anomaly high-velocity body. Based on the results of the spatial coupling analysis, the favorable target area for hydrate development is determined.

[0006] In some preferred methods, target geological bodies and fluid transport channels are identified based on seismic data volumes, and then the target spatial extent of potential favorable hydrate accumulation areas is delineated through preliminary spatial coupling, including the following steps: On time-domain seismic profiles, ancient uplifts, tectonic ridges, and local tectonic high points are identified as target tectonic geological bodies for hydrate accumulation by interpreting the morphology of the same phase axis. Seismic phase and amplitude anomaly analysis identifies gas chimneys, diapiric structures, tectonic faults, and fluid conduits as fluid migration channels for the vertical migration of deep gas-bearing fluids to shallower layers. If there is at least one type of fluid transport channel on the upper part of a target geological structure, the interior and upper pre-defined area of ​​the corresponding fluid transport channel shall be delineated as the target spatial range of the potential favorable accumulation area of ​​hydrates.

[0007] In some preferred methods, the seismic reflection anomaly target body includes strong amplitude anomalies, bright spot reflections, and seismic uplift reflections. Based on the target spatial range and a predetermined range below the seabed, the seismic data volume is used to extract quantitative attribute anomalies of shallow seismic reflections and classify and identify anomalies to obtain the seismic reflection anomaly target body, including the following steps: The intersection of the target spatial range and the predetermined range below the seabed is processed to obtain the anomaly identification layer; Based on the seismic data volume, seismic reflection attributes are extracted along or between layers in the anomaly identification segment; among which, seismic reflection attributes include seismic amplitude value, regional background amplitude value, seismic reflection phase axis, regional reflection mean time, and stratum reflection time. If the earthquake amplitude value of a certain local area is greater than a preset multiple of the background amplitude value of the area, and the lateral extension length of the corresponding local area is less than the first length threshold, the corresponding local area will be marked as a bright spot reflection. If the earthquake amplitude value of a certain continuous area is greater than the background amplitude value of the area, and the lateral extension length of the corresponding continuous area is greater than the second length threshold, the corresponding continuous area will be marked as a strong amplitude anomaly. The region with upward bending deformation along the same phase of the seismic reflection is taken as the candidate anomaly region. If the time difference between the stratum reflection time and the average time of regional reflection in a certain candidate anomaly region is less than the time difference threshold, the corresponding candidate anomaly region is marked as seismic pull-up reflection. Based on the spatial location and marker type of all bright spot reflections, strong amplitude anomalies, and seismic uplift reflections, a seismic reflection anomaly target body is formed.

[0008] In some preferred methods, the high-velocity anomalous bodies are identified by constructing a regional background velocity trend surface based on the P-wave velocity field, including the following steps: A spatial sliding window is set at the initial position corresponding to the longitudinal wave velocity field; The trend surface background velocity of the region corresponding to the spatial sliding window is determined based on the median velocity value of the longitudinal wave velocity field at all spatial locations within the spatial sliding window. The velocity increment corresponding to each spatial location is obtained by calculating the difference between the velocity value of the longitudinal wave velocity field at each spatial location within the spatial sliding window and the background velocity of the trend surface. Slide the spatial sliding window one spatial position back along the space corresponding to the P-wave velocity field, and return to execute the step of calculating the median velocity value of all spatial positions within the spatial sliding window based on the P-wave velocity field, until the spatial sliding window reaches the termination position corresponding to the P-wave velocity field, and obtain the velocity increment of all spatial positions corresponding to the P-wave velocity field. If the velocity increment at each spatial location in a continuous region is greater than a preset velocity threshold, and the spatial continuous distribution scale of the corresponding continuous region is greater than a preset scale threshold, the corresponding continuous region will be marked as a high-speed body with abnormal velocity.

[0009] In some preferred methods, atypical seafloor-like reflective layers are identified based on seismic data volumes using preset markers, including the following steps: In the seismic data volume, in-phase axes that have a parallel spatial relationship with the seabed and have opposite amplitude polarities are matched as candidate reflector layers. Based on candidate reflective layers, atypical seabed-like reflective layers are identified by matching geometric features such as discontinuity, beading, and local uplift.

[0010] In some preferred methods, the seismic reflection anomaly target body includes strong amplitude anomalies and bright spot reflections. An atypical seafloor-like reflector layer is used as the bottom boundary constraint of the hydrate stability domain. Spatial coupling analysis is performed on the seismic reflection anomaly target body and the high-velocity velocity anomaly body. Based on the results of the spatial coupling analysis, the favorable target area for hydrate development is determined, including the following steps: Spatial coupling analysis was performed on the seismic reflection anomaly target body and the velocity anomaly high-speed body to obtain the spatial coupling degree; The expression for spatial coupling degree is: ; In the formula, Indicates spatial coupling degree; A represents a high-speed body with velocity anomalies; B represents a target body with seismic reflection anomalies. This indicates the spatial range quantized using the voxel accumulation method. This represents the intersection operation. This indicates the operation of finding the minimum value; If the spatial coupling degree is greater than or equal to the preset coupling ratio, and the corresponding coupling region is located within a preset range above the atypical seabed reflective layer, the corresponding coupling region is determined to be a hydrate favorable development target area. If a certain analysis region has at least one of strong amplitude anomalies or bright spot reflections, and there are no high-speed bodies with abnormal velocity in the corresponding analysis region, the corresponding analysis region is determined to be a free gas accumulation region. If a high-velocity body with an anomalous velocity exists in a certain analysis area, and the corresponding high-velocity body with an anomalous velocity is located below an atypical seafloor-like reflective layer, or if the spatial coupling degree of a certain analysis area is less than the preset coupling ratio, the corresponding analysis area is determined to be a non-hydrate high-velocity geological body area.

[0011] In some preferred embodiments, the method further includes the following steps: Obtain well logging data from adjacent areas of the target zone where hydrates are favorable for development; Extract high P-wave velocity and high resistivity logging response feature templates from well logging data to determine hydrate intervals; The burial depth and thickness information of the target area for favorable hydrate development are spatially superimposed and compared with the top and bottom interfaces of the hydrate layer; The identification and verification results of the favorable development target area of ​​hydrates were determined based on the spatial superposition and comparison results.

[0012] To achieve the above objectives, another aspect of the present invention proposes a device for identifying shallow seafloor hydrate systems based on high-precision seismic data, the device comprising: The first module is used to acquire seismic data volumes for the target area; The second module is used to identify target geological bodies and fluid transport channels based on seismic data volumes, and then to delineate the target spatial range of potential favorable hydrate accumulation areas through preliminary spatial coupling. The third module is used to extract quantitative attribute anomalies and classify and identify anomalies in shallow seismic reflections based on the target spatial range and a predetermined range below the seabed, thereby obtaining seismic reflection anomaly target bodies. The fourth module is used to obtain the P-wave velocity field of shallow strata through constrained inversion based on seismic data volume, and to identify the high-velocity velocity anomaly by constructing a regional background velocity trend surface based on the P-wave velocity field; and to identify atypical seafloor-like reflector layers based on seismic data volume through preset markers. The fifth module is used to use the atypical seafloor-like reflective layer as the bottom boundary constraint of the hydrate stability domain, to perform spatial coupling analysis on the seismic reflection anomaly target body and the velocity anomaly high-speed body, and to determine the favorable target area for hydrate development based on the results of the spatial coupling analysis.

[0013] In some preferred embodiments, the device further includes a sixth module for performing the following operations: Obtain well logging data from adjacent areas of the target zone where hydrates are favorable for development; Extract high P-wave velocity and high resistivity logging response feature templates from well logging data to determine hydrate intervals; The burial depth and thickness information of the target area for favorable hydrate development are spatially superimposed and compared with the top and bottom interfaces of the hydrate layer; The identification and verification results of the favorable development target area of ​​hydrates were determined based on the spatial superposition and comparison results.

[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 present invention includes at least the following beneficial effects: The present invention provides a method, apparatus, electronic device, storage medium, and program product for identifying shallow seafloor hydrate systems based on high-precision seismic data. This scheme acquires seismic data volumes of the target area; identifies target tectonic geological bodies and fluid transport channels based on the seismic data volumes, and then delineates the target spatial range of potential favorable hydrate accumulation areas through preliminary spatial coupling; based on the target spatial range and a predetermined range below the seafloor, it uses the seismic data volumes to extract quantitative attribute anomalies of shallow seismic reflections and classify and identify anomaly bodies to obtain seismic reflection anomaly target bodies; based on the seismic data volumes, it obtains the P-wave velocity field of shallow strata through constrained inversion, and calibrates the high-velocity velocity anomalies by constructing a regional background velocity trend surface based on the P-wave velocity field; based on the seismic data volumes, it identifies atypical seafloor-like reflection layers through preset markers; using the atypical seafloor-like reflection layers as the bottom boundary constraint of the hydrate stability domain, it performs spatial coupling analysis on the seismic reflection anomaly target bodies and the high-velocity velocity anomalies, and determines the favorable hydrate development target areas based on the results of the spatial coupling analysis. This invention identifies tectonic geological bodies and fluid migration channels and performs preliminary spatial coupling, enabling the delineation of potentially favorable areas based on the "source-migration-accumulation" hydrocarbon accumulation elements. This effectively overcomes the ambiguity of traditional methods that directly search for anomalies without considering the hydrocarbon accumulation background. Furthermore, through quantitative attribute extraction and anomaly classification, this invention enables shallow seismic anomaly identification to move from qualitative experience to quantitative standardization. In addition, by introducing regional background velocity trend surfaces to calibrate high-velocity velocity anomalies and identifying atypical BSRs as stability domain constraints, this invention achieves parameter transformation from velocity fields to geological attributes. Finally, by spatially coupling the target anomaly with high-velocity anomalies and using this as the basis for determining the target area, this invention effectively eliminates the ambiguity of single anomalies, making the results more reliable and the process repeatable. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of an implementation environment for a method for identifying shallow seafloor hydrate systems based on high-precision seismic data, as provided in an embodiment of the present invention. Figure 2 This is a flowchart illustrating the method for identifying shallow seafloor hydrate systems based on high-precision seismic data provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of the overall process of the method for identifying shallow seafloor hydrate systems based on high-precision seismic data provided in this embodiment of the invention; Figure 4 This is a schematic diagram of an example of structure-fluid activity feature recognition provided in an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating an example of shallow seafloor seismic reflection anomaly features provided in an embodiment of the present invention; Figure 6This is a schematic diagram illustrating an example of velocity field inversion and abnormal upward reflection characteristics within a fluid pipe, provided in an embodiment of the present invention. Figure 7 This is a schematic diagram illustrating an example of comprehensive verification of fluid leakage and hydrate drilling detection information provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of the seafloor shallow hydrate system identification device based on high-precision seismic data provided in an embodiment of the present 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 those of this invention; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this invention.

[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 a huge unconventional clean energy source and are widely found in seabed sediments and permafrost areas along continental margins.

[0024] Bottom Simulating Reflector (BSR): A high-amplitude seismic reflection interface in marine seismic profiles that is approximately parallel to the seabed, has a reflection polarity opposite to the seabed, and can obliquely intersect sedimentary bedding. This interface corresponds to the bottom boundary of the natural gas hydrate stability domain and is formed by the difference in wave impedance between the overlying hydrate-bearing sediments and the underlying free gas-bearing sediments. It is a traditional key geophysical marker for identifying marine natural gas hydrates.

[0025] Hydrate stability region: The spatial region in which natural gas hydrates can exist stably when conditions such as temperature, pressure, fluid composition, and formation medium meet the thermodynamic stability conditions. Its range is determined by the hydrate phase equilibrium conditions.

[0026] Leakage hydrates: These are closely associated with deep fluid transport channels (gas chimneys, faults, fissures, etc.). They are formed by methane gas (or other high-carbon gaseous alkanes) seeping upwards along these channels and forming hydrates under suitable internal temperature and pressure conditions. They often occur in massive, vein-like, or nodular forms. This type generally has high saturation (up to 90% or more) and enormous resource potential. Traditional BSR identification markers are usually underdeveloped or atypical.

[0027] Shallow hydrate systems: Natural gas hydrates located 0–100 m below the seabed, mainly including seepage hydrates and surface hydrates. This type of hydrate often occurs as near-seabed block fillings or fissure fillings, and is frequently accompanied by seabed plume-like fluid seepage.

[0028] Gas chimneys: Vertical or near-vertical columnar strong amplitude anomalies on seismic profiles, indicating channels for the upward migration of deep gas-bearing fluids along fracture or fissure systems, and are often closely related to the enrichment of shallow hydrates.

[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] Velocity anomaly: Due to their high degree of consolidation and low porosity, hydrates have significantly higher P-wave velocities than the surrounding rock formations. Velocity inversion can be used to infer hydrate enrichment zones.

[0031] Bright spot reflection: An anomalous feature of significantly enhanced local reflection amplitude on seismic profiles is an effective indicator of hydrate-rich layers.

[0032] Upward pulling of the reflection interface: Due to the presence of high-velocity anomalies (such as hydrate layers), the reflection time of the underlying strata is shortened, resulting in the seismic response characteristics of upward bending deformation along the same phase of the seismic reflection.

[0033] Among related technologies, existing technologies are difficult to achieve rapid and accurate identification of shallow seabed hydrates in areas without typical BSRs in an economical and efficient manner.

[0034] In view of this, this invention provides a method and related equipment for identifying shallow seafloor hydrate systems based on high-precision seismic data. This method involves acquiring seismic data volumes of the target area; identifying target geological structures and fluid transport channels based on the seismic data volumes; and then delineating the target spatial range of potential favorable hydrate accumulation areas through preliminary spatial coupling; based on the target spatial range and a predetermined range below the seafloor, extracting quantitative attribute anomalies and classifying anomalies from shallow seismic reflections using the seismic data volumes to obtain seismic reflection anomaly target bodies; obtaining the P-wave velocity field of shallow strata through constrained inversion based on the seismic data volumes; identifying high-velocity velocity anomalies by constructing a regional background velocity trend surface based on the P-wave velocity field; identifying atypical seafloor-like reflection layers using preset markers based on the seismic data volumes; using the atypical seafloor-like reflection layers as the bottom boundary constraint of the hydrate stability domain; performing spatial coupling analysis on the seismic reflection anomaly target bodies and high-velocity velocity anomalies; and determining favorable hydrate development target areas based on the results of the spatial coupling analysis. This invention, through identifying tectonic geological bodies and fluid migration channels and performing preliminary spatial coupling, enables the delineation of potentially favorable areas based on the "source-migration-accumulation" hydrocarbon accumulation elements, effectively overcoming the ambiguity of traditional methods that directly search for anomalies without considering the hydrocarbon accumulation background. Furthermore, this invention, through quantitative attribute extraction and anomaly body classification and identification, enables shallow seismic anomaly identification to move from qualitative experience to quantitative standardization. In addition, by introducing regional background velocity trend surfaces to calibrate high-velocity velocity anomalies and identifying atypical BSRs as stability domain constraints, this invention enables the parameter transformation from velocity fields to geological attributes. Finally, by performing spatial coupling analysis between the target anomaly body and high-velocity anomalies and using this as the basis for determining the target area, this invention effectively eliminates the ambiguity of single anomalies, making the results more reliable and the process repeatable.

[0035] It is understood that the method for identifying shallow seafloor hydrate systems based on high-precision seismic data provided by this invention 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] For example, based on Figure 1The implementation environment shown in this embodiment of the invention provides a method for identifying shallow seafloor hydrate systems based on high-precision seismic data. The following description uses the application of this method for identifying shallow seafloor hydrate systems based on high-precision seismic data in server 101 as an example. It can be understood that this method for identifying shallow seafloor hydrate systems based on high-precision seismic data can also be applied in terminal 102.

[0041] Reference Figure 2 , Figure 2 This is an optional flowchart of a method for identifying shallow seafloor hydrate systems based on high-precision seismic data provided in an embodiment of the present invention. The execution subject of this method for identifying shallow seafloor hydrate systems based on high-precision seismic data 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 S500.

[0042] Step S100: Obtain the seismic data volume of the target area; The seismic data volume includes, but is not limited to, time-domain high-resolution three-dimensional seismic profiles, regional geological background data, and seismic data.

[0043] Step S200: Based on the seismic data volume, identify the target geological structure and fluid transport channels, and then delineate the target spatial range of the potential favorable accumulation area of ​​hydrates through preliminary spatial coupling; It should be noted that, in some embodiments, step S200 may include the following steps: on the time-domain seismic profile, ancient uplifts, tectonic ridges and local tectonic high points are identified as target tectonic geological bodies for hydrate accumulation by interpreting the morphology of the same phase axis; gas chimneys, diapiric structures, tectonic faults and fluid conduits are identified as fluid migration channels for deep gas-bearing fluids to migrate vertically to shallow layers by analyzing seismic facies and amplitude anomalies; if at least one type of fluid migration channel exists above a target tectonic geological body, the interior and upper preset area of ​​the corresponding fluid migration channel are delineated as the target spatial range of a potential favorable accumulation area for hydrates.

[0044] For example, in some specific embodiments, the identification of the construction background and fluid channeling system can be achieved as follows: Purpose and significance: Starting from the hydrocarbon accumulation elements of the hydrate "source-transport-accumulation" system, this study aims to identify geological structural units and fluid conduction systems that are conducive to the accumulation of shallow hydrate systems. By analyzing the spatial coupling relationship between these two systems, favorable accumulation areas for shallow hydrates can be preliminarily determined, thus narrowing the scope of subsequent detailed identification and improving identification efficiency.

[0045] 1. Identification of tectonic geological bodies: Based on high-resolution three-dimensional seismic profiles in the time domain and combined with regional geological background data, three types of favorable geological structural units that play an important role in controlling the accumulation of shallow hydrate systems were identified.

[0046] (1) Paleo-uplift: a structural unit that is significantly uplifted relative to the surrounding strata. It is usually the result of deep geological activity, indicating a long-term stable structural high position, which is conducive to the convergence of deep fluids to higher positions, providing a fluid supply advantage for hydrate formation.

[0047] (2) Structural ridge: A regional uplift structure whose orientation is consistent with the regional tectonic orientation. The strata on both sides have obvious slope differences and bending deformation characteristics. The length and width reach a certain scale, providing favorable high-permeability channels for the lateral migration of fluids.

[0048] (3) Local structural high points: On the seismic profile, they are characterized by local uplift of the strata, forming a significant height difference with the surrounding strata. They are the dominant areas for vertical fluid transport and are often accompanied by the development of fluid transport channels such as tectonic faults.

[0049] 2. Fluid transport channel identification: We focused on identifying four types of fluid migration channels closely related to shallow hydrate migration and accumulation. These channels are key pathways for the migration of methane gas from formations to shallower layers and its accumulation in stable regions to form reservoirs. (1) Gas chimneys: These are mainly the result of deep gas-bearing fluids migrating to shallow strata under 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 relatively long longitudinally, with the top of the gas chimney 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.

[0050] (2) Diapiric structures: These are geological structures formed by deep plastic materials (such as salt rock and mudstone) piercing or piercing the overlying strata. The top is often mushroom-shaped, accompanied by radial fractures. They extend significantly in the longitudinal direction. The center of the diapiric structure is relatively close to the seabed. Diapiric activity can drive deep fluids to migrate upward.

[0051] (3) Structural faults: mainly generated by tectonic tensile stress, often developed at the top of tectonic ancient uplifts, are band-shaped structures composed of multiple faults or fissures. The length of a single fault is relatively large, the fault displacement is obvious, the distance between adjacent faults is small, and the fault strike is often parallel to the tectonic ridge strike, forming a network of fluid transport channels.

[0052] (4) Fluid conduits: mainly generated by the rupture of the formation and the release of fluid driven by overpressure gas-bearing fluid. On the seismic profile, they appear as nearly vertical tubular strong amplitude anomalies with a small lateral diameter and extend longitudinally through the shallow strata. The internal reflection characteristics are similar to those of a gas chimney but with a more regular shape, indicating the path of deep fluids rapidly moving upward along the tubular channels.

[0053] Based on the identification results of tectonic geological bodies and fluid transport channels using high-precision 3D seismic data, in a specific embodiment, if a region develops tectonic geological bodies and there are one or more types of fluid transport channels above them, it is determined that the geological environment has the potential to develop a shallow seafloor hydrate system. In particular, the area inside and above the fluid transport channels can be delineated as a potential favorable accumulation area for hydrates.

[0054] Step S300: Based on the target spatial range and the predetermined range below the seabed, the quantitative attribute anomaly extraction and anomaly body classification of shallow seismic reflection are performed using seismic data volume to obtain the seismic reflection anomaly target body. It should be noted that the seismic reflection anomaly target body includes strong amplitude anomalies, bright spot reflections, and seismic uplift reflections. In some embodiments, step S300 may include the following steps: performing intersection processing on the target spatial range and a predetermined range below the seabed to obtain anomaly identification segments; based on the seismic data volume, extracting seismic reflection attributes along or between layers of the anomaly identification segment; wherein, the seismic reflection attributes include seismic amplitude value, regional background amplitude value, seismic reflection phase axis, regional reflection average time, and stratum reflection time; if the seismic amplitude value of a certain local area is greater than a preset multiple of the regional background amplitude value, and the lateral extension length of the corresponding local area is small. At the first length threshold, the corresponding local area is marked as a bright spot reflection; if the seismic amplitude value of a certain continuous area is greater than the regional background amplitude value, and the lateral extension length of the corresponding continuous area is greater than the second length threshold, the corresponding continuous area is marked as a strong amplitude anomaly; areas with upward bending deformation along the seismic reflection phase axis are taken as candidate anomaly areas; if the time difference between the stratum reflection time of a candidate anomaly area and the regional reflection average time is less than the time difference threshold, the corresponding candidate anomaly area is marked as an earthquake pull-up reflection; based on the spatial location and marking type of all bright spot reflections, strong amplitude anomalies, and earthquake pull-up reflections, a seismic reflection anomaly target body is formed.

[0055] For example, in some specific embodiments, shallow seismic reflection anomaly extraction can be achieved as follows: Purpose and significance: Within the potential favorable accumulation zone of hydrates identified in the above steps, through detailed interpretation of seismic data, we can identify the seismic indication characteristics of shallow hydrate occurrence and extract seismic reflection anomalies.

[0056] For potential hydrate accumulation zones within the 0-100m range below the seabed, the following three types of shallow seismic reflection anomalies were identified through detailed interpretation of seismic data: 1. Strong amplitude anomaly: This is characterized by a seismic amplitude value that is significantly higher than the background amplitude value of the same area without anomaly reflection zones. It is distributed in a continuous strip shape, with a long horizontal extension and a large vertical thickness. This indicates that there is a significant difference in reflection characteristics between the hydrate layer or free gas and the surrounding rock. It is necessary to further determine its geological properties by combining the velocity field characteristics in subsequent steps.

[0057] 2. Bright spot reflection: It is characterized by a significant increase in local amplitude. Compared with strong amplitude anomalous reflection, its lateral extension is limited. It is usually distributed in local point-like or bead-like patterns within the seepage channel. It usually indicates gas-bearing layers or highly saturated hydrate accumulation. Its geological properties need to be further determined by combining the velocity field characteristics in subsequent steps.

[0058] Bright spot reflection is defined as having a lateral extension length of less than 200 meters and an amplitude anomaly value exceeding twice the background value; strong amplitude anomaly is defined as having a lateral extension length of more than 500 meters and being spatially continuous or quasi-continuous strip-like.

[0059] 3. Seismic uplift reflection: This is characterized by upward bending and deformation of the seismic reflection axis, with a significant upward pull (the time difference with the seabed topography is shortened by 5 milliseconds or more). This is caused by the presence of high-velocity anomalous geological bodies, which shortens the reflection time of the underlying strata. It is usually the result of hydrates filling the seepage channels.

[0060] Step S400: Based on the seismic data volume, the P-wave velocity field of the shallow strata is obtained through constrained inversion. Based on the P-wave velocity field, the high-velocity velocity anomaly is identified by constructing a regional background velocity trend surface. Based on the seismic data volume, atypical seafloor-like reflector layers are identified by preset markers. It should be noted that in some embodiments, identifying a high-velocity anomalous bodies by constructing a regional background velocity trend surface based on the P-wave velocity field may include the following steps: setting a spatial sliding window at the starting position corresponding to the P-wave velocity field; determining the background velocity of the trend surface of the region corresponding to the spatial sliding window based on the median of the velocity values ​​of the P-wave velocity field at all spatial positions within the spatial sliding window; performing a difference calculation between the velocity values ​​of the P-wave velocity field at each spatial position within the spatial sliding window and the background velocity of the trend surface to obtain the velocity increment corresponding to each spatial position; sliding the spatial sliding window one spatial position backward along the space corresponding to the P-wave velocity field, and returning to execute the step of determining the median of the velocity values ​​of the P-wave velocity field at all spatial positions within the spatial sliding window, until the spatial sliding window reaches the ending position corresponding to the P-wave velocity field, obtaining the velocity increment of all spatial positions corresponding to the P-wave velocity field; if the velocity increment of each spatial position in a certain continuous region is greater than a preset velocity threshold, and the spatial continuous distribution scale of the corresponding continuous region is greater than a preset scale threshold, the corresponding continuous region is marked as a high-velocity anomalous body.

[0061] For example, in some specific implementations, velocity field inversion and anomalous high-speed volume calibration can be achieved as follows: 1. Velocity field inversion: Stable and reliable inversion algorithms (such as Gaussian beam inversion, full waveform inversion, etc.) are adopted. Specifically, Gaussian beam inversion is used when the signal-to-noise ratio is ≤10dB; otherwise, full waveform inversion is used. The key inversion parameters are: inversion grid spacing not greater than 100 meters and the number of iterations is 3. The P-wave velocity field of shallow strata below the seabed is obtained by inversion based on multichannel seismic data. The inversion grid spacing meets the shallow resolution requirements. The hydrate stability domain is introduced to constrain the multiple solutions in the inversion process to ensure the reliability of the velocity field.

[0062] In some alternative implementations, the velocity field inversion conditional branch is as follows: If the average signal-to-noise ratio within the work area is ≤10dB, Gaussian beam tomography inversion is used. This method is more adaptable to low signal-to-noise ratio data, and simulates wave propagation by decomposing the wave field into Gaussian beams to invert the macroscopic velocity structure.

[0063] Otherwise, full waveform inversion is used. This method utilizes complete waveform information (amplitude, phase, etc.) to iteratively update the velocity model, achieving extremely high resolution.

[0064] The core principle and objective function of full waveform inversion are as follows: The goal is to find a subsurface velocity model that minimizes the discrepancy between the seismic data simulated by the model and the actual field observations. The most commonly used objective function is the L2 norm. Specifically, the gradient of the objective function with respect to the model parameters can be calculated using the adjoint state method, and then the model can be iteratively updated using methods such as gradient descent or conjugate gradient until the required number of iterations (e.g., 3) is met. During velocity inversion, the inversion grid spacing should be set to no more than 100 meters (the preset spacing can be adjusted according to actual needs, e.g., 80 to 120 meters) to ensure that thin layers of shallow hydrates can be distinguished.

[0065] 2. Speed ​​anomaly calibration: (1) Background velocity calculation: Based on the velocity field inversion results, a homogeneous region with stable structure and no abnormal reflections is selected, and its velocity distribution is statistically analyzed as a background velocity reference. Specifically, the sliding window statistical method is used to calculate the trend surface of the entire velocity field, and the trend surface is used as the background velocity. Regions that deviate significantly from the trend surface are considered as anomalies.

[0066] (2) Velocity anomaly determination: When the longitudinal wave velocity of the stratum is significantly higher than that of the background velocity field, and the longitudinal thickness of the anomalous area is large and has a certain lateral extension scale, it is determined to be a velocity anomaly, indicating the high-speed characteristics of the hydrate layer (the longitudinal wave velocity of hydrate is significantly higher than that of the surrounding rock due to its high degree of consolidation and low porosity).

[0067] It should be noted that, in some embodiments, the identification of atypical seafloor-like reflective layers based on seismic data volumes and by using preset identifiers may include the following steps: matching in-phase axes in the seismic data volumes that have a parallel spatial relationship with the seafloor and have opposite amplitude polarities as candidate reflective layers; and identifying atypical seafloor-like reflective layers based on the candidate reflective layers by matching geometric features such as discontinuity, beading, and local upward pull.

[0068] For example, in some specific implementations, atypical BSR identification can be achieved as follows: Atypical BSR characteristics are characterized by BSR reflections that are approximately parallel to the seabed topography, with discontinuous lateral extension and a discontinuous distribution, locally exhibiting beaded or bright spot reflections. At the corresponding locations of leakage channels, influenced by local thermal convection, the BSR shows localized upward pull, indicating a local uplift of the hydrate stability domain. These discontinuous, beaded, and locally upward pull features are extracted as identification markers for atypical BSRs and superimposed on high-velocity anomalies identified through velocity field inversion to constrain the favorable spatial distribution of leakage-type hydrates.

[0069] Step S500: Using the atypical seafloor-like reflective layer as the bottom boundary constraint of the hydrate stability domain, a spatial coupling analysis is performed on the seismic reflection anomaly target body and the velocity anomaly high-speed body, and the favorable target area for hydrate development is determined based on the results of the spatial coupling analysis. It should be noted that the seismic reflection anomaly target body includes strong amplitude anomalies and bright spot reflections. In some embodiments, step S500 may include the following steps: performing spatial coupling analysis on the seismic reflection anomaly target body and the velocity anomaly high-velocity body to obtain the spatial coupling degree; if the spatial coupling degree is greater than or equal to a preset coupling ratio, and the corresponding coupling region is located within a preset range above the atypical seafloor-like reflection layer, the corresponding coupling region is determined to be a hydrate-favorable development target area; if at least one of strong amplitude anomalies or bright spot reflections exists in a certain analysis area, and the corresponding analysis area does not have a velocity anomaly high-velocity body, the corresponding analysis area is determined to be a free gas accumulation area; if a certain analysis area has a velocity anomaly high-velocity body, and the corresponding velocity anomaly high-velocity body is located below the atypical seafloor-like reflection layer, or if the spatial coupling degree of a certain analysis area is less than the preset coupling ratio, the corresponding analysis area is determined to be a non-hydrate high-velocity geological body area.

[0070] The expression for spatial coupling degree is: ; In the formula, Indicates spatial coupling degree; A represents a high-speed body with velocity anomalies; B represents a target body with seismic reflection anomalies. This indicates the spatial range quantized using the voxel accumulation method. This represents the intersection operation. This indicates the operation of finding the minimum value; Specifically, Volume refers to the operation of calculating the volume (or area) occupied by an anomaly in three-dimensional space. In a three-dimensional seismic data volume, since the identified "strong amplitude anomalies" or "velocity anomalies" are not single points, but rather irregularly shaped spatial regions composed of numerous three-dimensional grid points, the Volume operation calculates the size of the area encompassed by these regions in three-dimensional space. For example, Volume(A) calculates the connected volume of geological body A in the three-dimensional data volume. In practical calculations, the voxel accumulation method can be used. Discretize the three-dimensional space into regular small cubes (i.e., voxels), assuming the volume of each voxel is... For geological body A (such as the envelope of a high-velocity anomaly), it contains For a voxel that meets the identification criteria (e.g., velocity anomaly exceeding the background value by 5%), its volume is calculated as follows:

[0071] For example, in some specific implementations, multi-condition comprehensive identification and target area determination can be achieved as follows: Objective and Significance: To establish a coupled identification system for hydrate enrichment under multiple geological constraints by integrating seismic anomaly reflections and velocity field characteristics. By comprehensively comparing and eliminating the multiple solutions of a single geophysical anomaly, favorable shallow hydrate enrichment areas can be effectively delineated, realizing the transformation from "anomaly identification" to "target evaluation".

[0072] Using the atypical BSR identified in the aforementioned steps as the thermodynamic constraint of the bottom boundary of the hydrate stability domain (BGHSZ), the strong amplitude / bright spot anomaly extracted in step two is spatially superimposed with the high-velocity anomaly inverted in step three. Based on the spatial coupling analysis of "seismic reflection-velocity anomaly-stability domain" (when the overlap between the spatial range (or envelope) of the high-velocity anomaly and the spatial range (or envelope) of the strong amplitude / bright spot reflection reaches more than 70%, and the overlapping area is located within 50 meters above the atypical BSR interface, it is judged as 'highly coupled'), the following three types of identification operations are performed: Scenario 1: Inferred to be a hydrate region; By superimposing strong amplitude anomalies, bright spot reflections, and high-velocity anomalies, anomalous units located above atypical BSRs and exhibiting high spatial coupling between seismic reflection and velocity anomalies were identified. These regions possess triple indicative evidence of "strong reflection + high velocity + occurrence within a stable domain," thus qualifying them as reliable areas of seepage-type shallow hydrate development.

[0073] Scenario 2: Inferred to be a free gas region; By superimposing strong amplitude anomalies, bright spot reflections, and velocity fields, anomalous units with seismic reflection anomalies but without matching high-velocity anomalies (manifesting as low velocity or background velocity) were identified. These anomalies conform to the geophysical characteristics of "strong reflection + low velocity" of free gas and were determined to be free gas accumulation areas.

[0074] Scenario 3: Inferred to be a high-velocity geological body such as carbonate rock; Superimposed seismic reflection anomalies, high-velocity anomalies, and atypical BSRs are analyzed. High-velocity anomaly units located below atypical BSRs or with poor spatial coupling to the bottom boundary of the stable domain are excluded, suggesting they may be non-hydrate high-velocity geological bodies such as carbonate rocks, siliceous cemented layers, or other authigenic minerals. It should be noted that authigenic carbonate rocks may also form above BSRs and within hydrate stable domains. In this case, a comprehensive differentiation is needed based on their seismic reflection characteristics (such as strong amplitude, low frequency, and continuous plate-like structure) and spatial morphology (crust-like rather than layered / massive).

[0075] It should be noted that, in some embodiments, the method may further include the following steps: acquiring well logging data of adjacent areas of the hydrate favorable development target area; extracting high P-wave velocity and high resistivity well logging response feature templates from the well logging data to determine the hydrate interval; spatially superimposing and comparing the burial depth and thickness information corresponding to the hydrate favorable development target area with the top and bottom interfaces corresponding to the hydrate interval; and determining the identification and verification results of the hydrate favorable development target area based on the results of the spatial superimposition and comparison.

[0076] For example, in some specific implementations, the integrated verification of seismic-adjacent drilling and logging information can be achieved as follows: Purpose and Significance: Based on the identification system constructed in steps S100 to S500 and the hydrate development zone delineated in step S500, existing drilling data from neighboring areas can be further introduced for cross-validation. Through spatial matching analysis between "seismic prediction results" and "drilling verification in neighboring areas," the effectiveness and reliability of the method of this invention under similar geological backgrounds are verified, forming a complete technical closed loop from "theoretical identification" to "empirical verification." Specifically, this can be achieved as follows: Collect drilling data from neighboring areas, extract logging curve characteristics of hydrate-bearing strata encountered during drilling (such as sudden increases in P-wave velocity and abnormal increases in resistivity), and establish geological and geophysical response standards. Spatially overlay and compare the hydrate-favorable areas and atypical BSR distribution maps identified in step four with the hydrate top and bottom boundary depths and stratigraphic levels revealed by drilling in neighboring areas. If the hydrate development areas delineated in step four spatially match the hydrate strata depths revealed by drilling in neighboring areas, and the seismic reflection characteristics (strong amplitude, bright spots) correspond one-to-one with high-velocity logging anomalies, then the identification method is deemed scientifically sound and practical, and the identification results are reliable. If there are discrepancies between the identification results in step four and the drilling data from neighboring areas in spatial distribution or stratigraphic correspondence, then conduct differentiated geological genetic analysis, focusing on whether these discrepancies are due to local structural fracturing, errors in atypical BSR identification, or differences in fluid migration paths in neighboring areas. Based on this, improve the geological understanding of hydrate accumulation patterns under complex geological conditions and provide a basis for correction in subsequent regional resource assessments.

[0077] 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.

[0078] First, it should be noted that current shallow hydrate identification mainly relies on direct observation methods such as drilling, well logging, and seabed photography. While these methods offer high accuracy, they suffer from drawbacks such as high cost (single well drilling cost ≥ 15 million RMB), long cycle time, and limited coverage, making it impossible to achieve rapid screening and evaluation of large-scale hydrate-rich areas. Furthermore, existing seismic identification technologies often rely on relatively singular seismic or geological anomaly markers (such as identifying only single features like gas chimneys, bright spot reflections, or reflection pull-up), lacking a comprehensive hydrate system identification technology sequence encompassing the multi-level coupling of "tectonic-fluid-seismic anomaly-velocity field." This results in highly ambiguous identification results, making it difficult to meet the economical and efficient geological exploration needs of shallow seabed hydrate systems.

[0079] Specifically, the existing technology has the following disadvantages: (1) Limited identification targets: Traditional BSR identification mode cannot cover shallow seepage hydrate systems.

[0080] Existing technologies are mostly limited to identifying deep diffuse hydrate systems characterized by BSR reflection features. Although some technologies have improved shallow imaging accuracy by using long-short cable combinations, their solutions have not established an identification mechanism for hydrates without BSR features. They rely on deep learning model training, and the training of these models does not adequately consider the coupling relationship between seismic attributes and geological conditions, meaning they lack specific identification logic for seepage hydrates without typical BSR features.

[0081] (2) The identification logic is fragmented and lacks a systematic identification technology sequence of multi-level coupling of "structure-fluid-seismic anomaly-velocity field".

[0082] Existing technologies and methods suffer from fragmented identification logic and lack a systematic identification sequence involving multi-level coupling of "structure-fluid-seismic anomalies-velocity fields". They focus only on classifying the causes of leakage without considering the coupling relationship between seismic response characteristics (such as amplitude anomalies and velocity anomalies) and fluid transport channels, resulting in low matching degree between classification results and actual seismic exploration data. Furthermore, they only rely on the single indicator of BSR (Body Slip Reduction) and fail to integrate multi-dimensional seismic anomaly information such as gas chimneys and fluid channels, leading to multiple interpretations in the analysis results.

[0083] (3) Insufficient standardization of methods, lack of convenient and efficient standardized technical implementation process.

[0084] Existing technologies and methods have low standardization and lack repeatable process-based identification steps. In related technologies, the selection of training samples, label construction, and transfer learning parameter settings for deep learning models lack unified standards under geological constraints, and the generalization ability of models in different work areas is not strong. Furthermore, the regional applicability standards for the P-wave and S-wave velocity difference threshold curves are not clearly defined, and there are errors in the matching between the theoretical porosity line and the actual strata.

[0085] (4) The high dependence on drilling means that regional resource assessment is limited by high cost and low efficiency.

[0086] Existing technologies and methods are heavily reliant on drilling, resulting in high costs, low efficiency, and difficulty in achieving rapid regional screening. While related technologies have improved data acquisition accuracy, their technical solutions have not formed an independent identification technology sequence based on high-precision seismic data. They still rely on direct verification methods such as drilling and well logging (with a single well costing over 15 million yuan), making it difficult to achieve rapid pre-identification over a large area. They can only determine the presence or absence of BSRs, but cannot provide key information such as the degree of hydrate enrichment and distribution range. Essentially, they still require drilling verification, which restricts exploration effectiveness and resource assessment progress.

[0087] In view of this, this invention addresses a series of problems existing in hydrate identification technologies, such as strong dependence on seafloor shale seismic (BSR) data, insufficient ability to identify shallow hydrate ore bodies, lack of systematic coupling in geological systems, low standardization, and high drilling costs. The aim is to establish a rapid identification method and technical process for seafloor shallow hydrate systems based on high-precision seismic data. The main objective of this invention is to break through the traditional hydrate ore body identification model that relies on BSR as the core criterion. By innovatively establishing a multi-level coupled identification technology sequence of "tectonic-fluid identification—seismic anomaly extraction—velocity field calibration—multi-condition comprehensive discrimination," a standardized and streamlined technical sequence is constructed. This enables economical and efficient identification of seafloor shallow hydrates in atypical BSR areas, providing scientific and reliable technical support for hydrate resource evaluation, drilling target area selection, and geological risk prevention and control.

[0088] Specifically, this invention addresses the problems of existing natural gas hydrate identification technologies, such as their reliance on BSR indicator markers, insufficient ability to identify shallow seafloor hydrate systems based on high-precision seismic data, and lack of a systematic coupling identification technology sequence. It aims to achieve economical, efficient, and standardized identification of shallow seafloor hydrate systems based on high-resolution seismic data by establishing a complete technical sequence of "tectonic-fluid identification—seismic anomaly extraction—velocity field calibration—multi-condition comprehensive discrimination." For example... Figure 3 As shown, the technical solution of the present invention can be achieved as follows: Step 1: Constructing the background and identifying the fluid transport system; Purpose and significance: Starting from the hydrocarbon accumulation elements of the hydrate "source-transport-accumulation" system, this study aims to identify geological structural units and fluid conduction systems that are conducive to the accumulation of shallow hydrate systems. By analyzing the spatial coupling relationship between these two systems, favorable accumulation areas for shallow hydrates can be preliminarily determined, thus narrowing the scope of subsequent detailed identification and improving identification efficiency.

[0089] 1. Identification of tectonic geological bodies: Based on high-resolution three-dimensional seismic profiles in the time domain and combined with regional geological background data, three types of favorable geological structural units that play an important role in controlling the accumulation of shallow hydrate systems were identified.

[0090] (1) Paleo-uplift: a structural unit that is significantly uplifted relative to the surrounding strata. It is usually the result of deep geological activity, indicating a long-term stable structural high position, which is conducive to the convergence of deep fluids to higher positions, providing a fluid supply advantage for hydrate formation.

[0091] (2) Structural ridge: A regional uplift structure whose orientation is consistent with the regional tectonic orientation. The strata on both sides have obvious slope differences and bending deformation characteristics. The length and width reach a certain scale, providing favorable high-permeability channels for the lateral migration of fluids.

[0092] (3) Local structural high points: On the seismic profile, they are characterized by local uplift of the strata, forming a significant height difference with the surrounding strata. They are the dominant areas for vertical fluid transport and are often accompanied by the development of fluid transport channels such as tectonic faults.

[0093] 2. Fluid transport channel identification: We focused on identifying four types of fluid migration channels closely related to shallow hydrate migration and accumulation. These channels are key pathways for the migration of methane gas from formations to shallower layers and its accumulation in stable regions to form reservoirs. (1) Gas chimneys: These are mainly the result of deep gas-bearing fluids migrating to shallow strata under 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 relatively long longitudinally, with the top of the gas chimney 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.

[0094] (2) Diapiric structures: These are geological structures formed by deep plastic materials (such as salt rock and mudstone) piercing or piercing the overlying strata. The top is often mushroom-shaped, accompanied by radial fractures. They extend significantly in the longitudinal direction. The center of the diapiric structure is relatively close to the seabed. Diapiric activity can drive deep fluids to migrate upward.

[0095] (3) Structural faults: mainly generated by tectonic tensile stress, often developed at the top of tectonic ancient uplifts, are band-shaped structures composed of multiple faults or fissures. The length of a single fault is relatively large, the fault displacement is obvious, the distance between adjacent faults is small, and the fault strike is often parallel to the tectonic ridge strike, forming a network of fluid transport channels.

[0096] (4) Fluid conduits: mainly generated by the rupture of the formation and the release of fluid driven by overpressure gas-bearing fluid. On the seismic profile, they appear as nearly vertical tubular strong amplitude anomalies with a small lateral diameter and extend longitudinally through the shallow strata. The internal reflection characteristics are similar to those of a gas chimney but with a more regular shape, indicating the path of deep fluids rapidly moving upward along the tubular channels.

[0097] Based on the identification results of tectonic geological bodies and fluid transport channels using high-precision 3D seismic data, in a specific embodiment, if a region develops tectonic geological bodies and there are one or more types of fluid transport channels above them, it is determined that the geological environment has the potential to develop a shallow seafloor hydrate system. In particular, the area inside and above the fluid transport channels can be delineated as a potential favorable accumulation area for hydrates.

[0098] Step 2: Extraction of shallow seismic reflection anomalies; Purpose and significance: Within the potential favorable accumulation zone of hydrates identified in the above steps, through detailed interpretation of seismic data, we can identify the seismic indication characteristics of shallow hydrate occurrence and extract seismic reflection anomalies.

[0099] For potential hydrate accumulation zones within the 0-100m range below the seabed, the following three types of shallow seismic reflection anomalies were identified through detailed interpretation of seismic data: 1. Strong amplitude anomaly: This is characterized by a seismic amplitude value that is significantly higher than the background amplitude value of the same area without anomaly reflection zones. It is distributed in a continuous strip shape, with a long horizontal extension and a large vertical thickness. This indicates that there is a significant difference in reflection characteristics between the hydrate layer or free gas and the surrounding rock. It is necessary to further determine its geological attributes by combining the velocity field characteristics in step three.

[0100] 2. Bright spot reflection: It is characterized by a significant increase in local amplitude. Compared with strong amplitude anomalous reflection, its lateral extension is limited. It is usually distributed in local point-like or bead-like patterns within the seepage channel. It usually indicates gas-bearing layers or high-saturation hydrate accumulation. It is necessary to combine the velocity field characteristics in step three to further determine its geological attributes.

[0101] Bright spot reflection is defined as having a lateral extension length of less than 200 meters and an amplitude anomaly value exceeding twice the background value; strong amplitude anomaly is defined as having a lateral extension length of more than 500 meters and being spatially continuous or quasi-continuous strip-like.

[0102] 3. Seismic uplift reflection: This is characterized by upward bending and deformation of the seismic reflection axis, with a significant upward pull (the time difference with the seabed topography is shortened by 5 milliseconds or more). This is caused by the presence of high-velocity anomalous geological bodies, which shortens the reflection time of the underlying strata. It is usually the result of hydrates filling the seepage channels.

[0103] Step 3: Velocity field inversion and calibration of anomalous high-speed bodies; Purpose and significance: To obtain the P-wave velocity distribution of shallow strata through seismic velocity field inversion, and to provide quantitative parameter constraints for hydrate identification by combining velocity anomaly calibration and atypical BSR reflection identification, thereby reducing ambiguity.

[0104] 1. Velocity field inversion: Stable and reliable inversion algorithms (such as Gaussian beam inversion, full waveform inversion, etc.) are adopted. Specifically, Gaussian beam inversion is used when the signal-to-noise ratio is ≤10dB; otherwise, full waveform inversion is used. The key inversion parameters are: inversion grid spacing not greater than 100 meters and the number of iterations is 3. The P-wave velocity field of shallow strata below the seabed is obtained by inversion based on multichannel seismic data. The inversion grid spacing meets the shallow resolution requirements. The hydrate stability domain is introduced to constrain the multiple solutions in the inversion process to ensure the reliability of the velocity field.

[0105] 2. Speed ​​anomaly calibration: (1) Background velocity calculation: Based on the velocity field inversion results, a homogeneous region with stable structure and no abnormal reflections is selected, and its velocity distribution is statistically analyzed as a background velocity reference. Specifically, the sliding window statistical method is used to calculate the trend surface of the entire velocity field, and the trend surface is used as the background velocity. Regions that deviate significantly from the trend surface are considered as anomalies.

[0106] (2) Velocity anomaly determination: When the longitudinal wave velocity of the stratum is significantly higher than that of the background velocity field, and the longitudinal thickness of the anomalous area is large and has a certain lateral extension scale, it is determined to be a velocity anomaly, indicating the high-speed characteristics of the hydrate layer (the longitudinal wave velocity of hydrate is significantly higher than that of the surrounding rock due to its high degree of consolidation and low porosity).

[0107] 3. Identification of atypical BSRs: Atypical BSR characteristics are characterized by BSR reflections that are approximately parallel to the seabed topography, with discontinuous lateral extension and a discontinuous distribution, locally exhibiting beaded or bright spot reflections. At the corresponding locations of leakage channels, influenced by local thermal convection, the BSR shows localized upward pull, indicating a local uplift of the hydrate stability domain. These discontinuous, beaded, and locally upward pull features are extracted as identification markers for atypical BSRs and superimposed on high-velocity anomalies identified through velocity field inversion to constrain the favorable spatial distribution of leakage-type hydrates.

[0108] Step 4: Multi-condition comprehensive identification and target area determination; Objective and Significance: To establish a coupled identification system for hydrate enrichment under multiple geological constraints by integrating seismic anomaly reflections and velocity field characteristics. By comprehensively comparing and eliminating the multiple solutions of a single geophysical anomaly, favorable shallow hydrate enrichment areas can be effectively delineated, realizing the transformation from "anomaly identification" to "target evaluation".

[0109] Using the atypical BSR identified in step three as the thermodynamic constraint of the bottom boundary of the hydrate stability domain (BGHSZ), the strong amplitude / bright spot anomaly extracted in step two is spatially superimposed with the high-velocity anomaly inverted in step three. Based on the spatial coupling analysis of "seismic reflection-velocity anomaly-stability domain" (when the overlap between the spatial range (or envelope) of the high-velocity anomaly and the spatial range (or envelope) of the strong amplitude / bright spot reflection reaches more than 70%, and the overlapping area is located within 50 meters above the atypical BSR interface, it is judged as 'highly coupled'), the following three types of identification operations are performed: Scenario 1: Inferred to be a hydrate region; By superimposing strong amplitude anomalies, bright spot reflections, and high-velocity anomalies, anomalous units located above atypical BSRs and exhibiting high spatial coupling between seismic reflection and velocity anomalies were identified. These regions possess triple indicative evidence of "strong reflection + high velocity + occurrence within a stable domain," thus qualifying them as reliable areas of seepage-type shallow hydrate development.

[0110] Scenario 2: Inferred to be a free gas region; By superimposing strong amplitude anomalies, bright spot reflections, and velocity fields, anomalous units with seismic reflection anomalies but without matching high-velocity anomalies (manifesting as low velocity or background velocity) were identified. These anomalies conform to the geophysical characteristics of "strong reflection + low velocity" of free gas and were determined to be free gas accumulation areas.

[0111] Scenario 3: Inferred to be a high-velocity geological body such as carbonate rock; Superimposed seismic reflection anomalies, high-velocity anomalies, and atypical BSRs are analyzed. High-velocity anomaly units located below atypical BSRs or with poor spatial coupling to the bottom boundary of the stable domain are excluded, suggesting they may be non-hydrate high-velocity geological bodies such as carbonate rocks, siliceous cemented layers, or other authigenic minerals. It should be noted that authigenic carbonate rocks may also form above BSRs and within hydrate stable domains. In this case, a comprehensive differentiation is needed based on their seismic reflection characteristics (such as strong amplitude, low frequency, and continuous plate-like structure) and spatial morphology (crust-like rather than layered / massive).

[0112] Step 5: Comprehensive verification of earthquake and adjacent drilling and logging information; Purpose and Significance: Based on the identification system constructed in steps one through four and the hydrate development zone delineated in step four, existing drilling data from neighboring areas are introduced for cross-validation. Through spatial matching analysis between "seismic prediction results" and "drilling data from neighboring areas," the effectiveness and reliability of the method of this invention are verified under similar geological backgrounds, forming a complete technical closed loop from "theoretical identification" to "empirical verification."

[0113] Collect drilling data from neighboring areas, extract logging curve characteristics of hydrate-bearing strata encountered during drilling (such as sudden increases in P-wave velocity and abnormal increases in resistivity), and establish geological and geophysical response standards. Spatially overlay and compare the hydrate-favorable areas and atypical BSR distribution maps identified in step four with the hydrate top and bottom boundary depths and stratigraphic levels revealed by drilling in neighboring areas. If the hydrate development areas delineated in step four spatially match the hydrate strata depths revealed by drilling in neighboring areas, and the seismic reflection characteristics (strong amplitude, bright spots) correspond one-to-one with high-velocity logging anomalies, then the identification method is deemed scientifically sound and practical, and the identification results are reliable. If there are discrepancies between the identification results in step four and the drilling data from neighboring areas in spatial distribution or stratigraphic correspondence, then conduct differentiated geological genetic analysis, focusing on whether these discrepancies are due to local structural fracturing, errors in atypical BSR identification, or differences in fluid migration paths in neighboring areas. Based on this, improve the geological understanding of hydrate accumulation patterns under complex geological conditions and provide a basis for correction in subsequent regional resource assessments.

[0114] The seismic methods based on steps one through four have formed a comprehensive logical closed loop. The key lies in steps one through four; step five is merely a verification process under certain conditions.

[0115] To more clearly illustrate the specific implementation process of the technical solution of this invention, this invention uses a key sea area as a case study area, and combines the actual geological and geophysical data of the area to demonstrate and explain the complete operation steps of the method (e.g. Figure 3 (As shown). This embodiment aims to verify the feasibility and operability of the method of the present invention in practical applications by identifying shallow hydrate systems in this sea area based on high-resolution seismic data. Specifically, it can be implemented as follows: Step 1: Constructing the background and identifying the fluid transport system; Purpose and significance: Starting from the hydrocarbon accumulation elements of the hydrate "source-transport-accumulation" system, this study aims to identify geological structural units and fluid conduction systems that are conducive to the accumulation of shallow hydrate systems. By analyzing the spatial coupling relationship between these two systems, potential shallow hydrate accumulation areas can be preliminarily determined, thus narrowing the scope of subsequent detailed identification and improving identification efficiency.

[0116] In a specific embodiment, such as Figure 4 As shown, the study area is located in a key sea area, and in terms of regional tectonic units, it is located in the Lingnan Low Uplift area of ​​the Qiongdongnan Basin.

[0117] 1. Identification of ancient uplift structures: In this specific embodiment, the background is mainly based on the ancient uplift, and the study area is located in the Lingnan low uplift area of ​​the Qiongdongnan Basin.

[0118] The Lingnan Low Uplift area exhibits significant paleobasement uplift structural features, with strong amplitude reflection interfaces and associated unconformities at the top of the uplift, and extensional faults at the apex. Depressions develop on both sides of the paleouplift, forming an overall alternating uplift and depression structural pattern. The top of the Lingnan Low Uplift is a typical favorable area for deep fluid activity and hydrocarbon accumulation.

[0119] 2. Identification of Fluid Transport Channels: The study area, based on the Lingnan Low Uplift background, features superimposed gas chimneys and shallow fluid channels, forming a vertical transport system from the deep paleo-uplift, through the middle gas chimneys, to the shallow fluid channels. Through seismic data interpretation, a typical gas chimney structure was identified at the top of the Lingnan Low Uplift. Based on the corresponding stratigraphic velocity data, the vertical height of this gas chimney is estimated to be approximately 850 meters. A vertical tubular fluid channel further develops at the top of the gas chimney, extending to the seabed, with a calculated vertical height of approximately 450 meters. The gas chimneys are concentrated within a local structural high point on the Lingnan Low Uplift, with a lateral width of approximately 6 kilometers and a main body width of approximately 4 kilometers. The upward-extending tubular channel gradually narrows from bottom to top, reaching a maximum width of approximately 800 meters.

[0120] In summary, the spatial geographical pattern of the study area conforms to the expected tectonic geological background, with well-developed fluid transport elements, and possesses excellent geological conditions for fluid migration and shallow hydrate accumulation.

[0121] Step 2: Extraction of shallow seismic reflection anomalies; Purpose and significance: Within the potential favorable accumulation zone of hydrates identified in the above steps, through detailed interpretation of seismic data, we can identify the seismic indication characteristics of shallow hydrate occurrence and extract seismic reflection anomalies.

[0122] In a specific embodiment, based on step one, such as Figure 5 As shown, a detailed identification of shallow seepage channels on the seabed is carried out.

[0123] 1. Channel Response Identification: Seismic data interpretation revealed that the leakage channels in the area directly connect to the seabed. At the seabed location, the seismic reflection phase axis is discontinuous, accompanied by local phase reversal characteristics, indicating a clear seabed fluid leakage response.

[0124] 2. Shallow anomaly extraction: Small-scale enhanced reflection features are developed in the shallow seabed, with a certain lateral extension range, which may indicate the accumulation characteristics of shallow hydrates in favorable reservoirs; below the enhanced reflection, the seismic reflection phase axis is observed to be pulled up, which may reflect the accumulation of seepage hydrates in fluid conduits.

[0125] In summary, the shallow seismic reflection anomalies in the study area are clear and typical, and the seismic anomaly indicators are very significant. Based on step one, we further focused on and locked down the favorable distribution range of shallow hydrates.

[0126] Step 3: Velocity field inversion and calibration of anomalous high-speed bodies; Purpose and significance: To obtain the P-wave velocity distribution of shallow strata through seismic velocity field inversion, and to provide quantitative parameter constraints for hydrate identification by combining velocity anomaly calibration and atypical BSR reflection identification, thereby reducing the ambiguity of seismic data.

[0127] In a specific embodiment, such as Figure 6 As shown, its velocity field inversion profile can clearly reflect the velocity field characteristics inside the seepage channel and the underlying strata of the BSR.

[0128] 1. Identification of Atypical BSRs: Through detailed interpretation of seismic data, it was identified that the BSR reflection polarity in the study area is opposite to that of the seafloor (blue seismic reflection phase axis at the seafloor, red seismic reflection phase axis at the BSR). Specifically, the identified BSR reflections are roughly parallel to the seafloor topography, and the BSRs as a whole exhibit atypical continuous development characteristics, with small-scale strong amplitude reflections, possibly indicating small-scale accumulation of highly saturated hydrates. At the locations of seepage channels, the BSR reflection phase axis shows local upward pull characteristics, mainly due to thermal convection activity triggered by the seepage of deep gas-bearing fluids, causing local formation temperature increases and uplift of the bottom boundary of the stable domain.

[0129] 2. Velocity anomaly calibration: A distinct low-velocity anomaly zone is developed below the BSR, indicating shallow free gas accumulation; within the fluid leakage channel above the BSR, affected by the high-velocity anomaly of the geological body, the reflected phase axis shows obvious distortion and upward pull characteristics, which is inferred to be caused by the high-velocity strata formed by hydrate accumulation in the leakage channel.

[0130] Step 4: Multi-condition comprehensive identification and target area determination; Objective and Significance: To establish a coupled identification system for hydrate enrichment under multiple geological constraints by integrating seismic anomaly reflections and velocity field characteristics. Through comprehensive comparative analysis, the ambiguity of single geophysical anomalies is eliminated, further identifying favorable shallow hydrate enrichment areas and realizing the transformation from "anomaly identification" to "target evaluation".

[0131] In specific embodiments, as can be seen from the analysis of the aforementioned examples, under the tectonic background of the Lingnan low uplift in the Qiongdongnan Basin, the gas chimney activity and fluid pipeline-controlled gas-bearing fluid migration create favorable geological and fluid migration conditions for hydrate accumulation and enrichment.

[0132] 1. Spatial coupling analysis: such as Figure 5 As shown, the leakage channel exhibits local bright spot reflections and seismic reflection pull-up characteristics; combined with... Figure 6 The velocity field analysis results show that the seismic anomaly responses, such as enhanced reflection, bright spot reflection, and velocity anomaly pull-up, are well matched with the spatial distribution of seepage channels and the spatial development location of BSR.

[0133] 2. Target Area Determination: Various geological, geophysical, and velocity field anomalies are concentrated in the upper stable domain of atypical BSRs, primarily within seepage channels. Anomalies such as velocity distortion are closely spatially coupled with high-velocity geological bodies and are uniformly controlled by the paleo-uplift pattern and fluid transport system described in Step 1. Considering the regional geological background, seismic reflection response, velocity field characteristics, and multiple geological information constraints from hydrate stable domains, the geological indications of various identification indicators show a high degree of consistency, essentially confirming that the series of anomalies within the seepage channels in the study area are caused by shallow hydrate enrichment.

[0134] Step 5: Comprehensive verification of earthquake and adjacent drilling and logging information; Purpose and Significance: Based on the identification system constructed in steps one through four and the hydrate development zone delineated in step four, existing drilling data from adjacent areas are introduced for cross-validation. Through spatial matching analysis between "seismic-geological prediction results" and "drilling verification," the effectiveness and reliability of this method under similar geological backgrounds are verified, forming a complete technical closed loop from "theoretical identification" to "empirical verification."

[0135] In a specific embodiment, such as Figure 7 As shown, based on the hydrate favorable areas identified in steps one to four, a comparative analysis will be conducted with the measured drilling data of hydrates in neighboring areas with similar geological backgrounds.

[0136] 1. Well logging response characteristics: A comprehensive comparison with drilling and logging information from neighboring areas shows that the seismic anomaly response characteristics of this area are highly consistent with the actual drilling and logging results of neighboring areas. Specifically, the resistivity logging curves deviate significantly from the resistivity background baseline value, showing a significant positive anomaly; within the imaging logging profile, hydrate-developed layers exhibit clear high-brightness reflection characteristics, while only the locations of locally developed interlayers are non-hydrate-developed layers.

[0137] 2. Comprehensive Analysis of Results: The empirical logging results from neighboring areas with similar geological backgrounds show a good match in terms of spatial distribution characteristics and response patterns with the shallow seepage-type hydrate system predicted in this study based on tectonic geological conditions, seismic anomaly indicators, velocity field analysis, and stability domain constraints. The overall logging data provides significant corroboration. Although non-hydrated interlayers exist in some local sections, the main seepage channels exhibit hydrate enrichment responses, forming a complete deep fluid migration-shallow seepage-type hydrate enrichment system. Cross-validation with measured data from neighboring areas fully verifies the feasibility, accuracy, and scientific validity of this identification method.

[0138] In summary, this invention relates to the field of marine natural gas hydrate geological exploration, and particularly to a rapid identification method for shallow seafloor hydrate systems based on high-resolution seismic data. By breaking through the traditional identification model of deep seafloor (~200m) diffuse hydrates using BSR (subsurface reflector) as the core marker, this invention establishes a multi-level coupled technical sequence for identifying shallow seafloor hydrate systems based on high-precision seismic data, encompassing "tectonic-fluid identification—seismic anomaly extraction—velocity field calibration—multi-condition comprehensive discrimination." This enables rapid and accurate identification of shallow seafloor hydrate systems (0-100m) in the absence of typical BSRs, providing technical support for marine hydrate resource exploration and evaluation, and drilling target area selection. Specifically, this invention is based on the core principle of identifying shallow hydrate systems using high-resolution seismic data. By establishing a multi-level coupled technical sequence of "tectonic-fluid identification—seismic anomaly extraction—velocity field calibration—multi-condition comprehensive discrimination," it achieves comprehensive discrimination of the occurrence conditions and enrichment areas of shallow seafloor hydrate systems. Its innovation lies in the construction of a systematic identification logic and the formulation of standardized discrimination rules, specifically achieved through techniques such as structure-fluid coupling discrimination, comprehensive identification of shallow anomalies, and velocity field inversion calibration. Specifically, the technical solution of this invention proposes the following technical innovations: Innovation Point 1: Establishing a series of shallow hydrate system identification technologies based on multi-level coupling of "structure-fluid identification, seismic anomaly extraction, velocity field calibration, and multi-condition comprehensive judgment".

[0139] This invention breaks through the existing single identification mode of hydrates that often uses BSR as the core marker. Starting from the "source-transport-accumulation" system of hydrates, it organically couples the optimization of tectonic background, identification of fluid migration channels, extraction of seismic reflection anomalies, and calibration of velocity field characteristics to form a progressive and systematic identification logic. This enables the delineation of favorable accumulation areas of shallow hydrates, effectively improving the identification accuracy and reducing the ambiguity of solutions.

[0140] Innovation Point Two: A programmed rule for identifying shallow seismic reflection anomalies and a multi-condition integrated discrimination rule was constructed.

[0141] This invention, based on the "source-transport-accumulation" system theory of hydrate formation, constructs a progressive, multi-element coupled identification technology sequence, overcoming the limitations of existing technologies that rely solely on BSR or empirical qualitative identification. Through a logically rigorous sequence of technical steps—"structural-fluid identification—seismic anomaly extraction—velocity field calibration—multi-condition comprehensive discrimination"—it achieves layer-by-layer focusing of the identification range and mutual verification of multi-parameter responses. Furthermore, by utilizing standardized discrimination rules to replace subjective identification, it ensures the proceduralization, standardization, and geological rationality of the shallow hydrate identification process.

[0142] Innovation Point 3: It enables economical and efficient identification of shallow seabed hydrates in atypical BSR development areas within the region.

[0143] This invention overcomes the technical bottlenecks of traditional drilling, which is heavily reliant on it and costly. Based on high-resolution seismic data, it employs a multi-level coupled identification process—"structure-fluid identification—seismic anomaly extraction—velocity field calibration—multi-condition comprehensive discrimination"—to achieve rapid screening and target delineation of shallow hydrates without drilling verification. This method boasts wide coverage (hundreds of square kilometers in a single seismic survey), low cost (one order of magnitude lower than drilling costs), and high efficiency (short data processing and interpretation cycle), providing an effective technical path for rapid hydrate resource evaluation and drilling deployment.

[0144] To address the problems of existing natural gas hydrate identification technologies, such as reliance on BSR markers, insufficient ability to identify shallow hydrates, lack of systematically coupled identification technology sequences, and high drilling costs, this invention proposes a rapid identification method for seafloor shallow hydrate systems based on high-resolution seismic data. Compared to existing technologies, the embodiments of this invention have at least the following beneficial effects: Compared with traditional BSR identification methods, the significant advantages of this invention are: it breaks through the single identification mode centered on BSR and establishes a systematic identification technology sequence with multi-level coupling of "tectonic-fluid identification—seismic anomaly extraction—velocity field calibration—multi-condition comprehensive discrimination". By introducing the comprehensive identification of favorable tectonic units and fluid migration channels, it achieves the delineation of favorable shallow hydrate areas starting from the "source-migration-accumulation" hydrocarbon accumulation elements. By constructing quantitative identification standards for three types of shallow seismic reflection anomalies and multi-condition comprehensive discrimination rules, it achieves standardized and procedural identification of hydrates under conditions without typical BSRs. This method not only solves the problem of insufficient identification capability of traditional methods for shallow seeping / massive hydrates, but also achieves large-scale, low-cost, and rapid screening and target area locking of shallow hydrates through the application of high-resolution seismic data. It can effectively improve the efficiency of hydrate resource evaluation and drilling success rate, and overcome the inherent limitations of traditional methods in terms of shallow identification, systematicness, timeliness, and economy.

[0145] Identification of shallow seabed natural gas hydrate (BSR) systems is a crucial aspect of marine natural gas hydrate system exploration, and its effectiveness directly impacts the accuracy of resource assessment and the scientific basis of drilling deployment. This invention addresses the technical challenges of atypical BSR characteristics and the failure of traditional identification methods. Based on the "source-transport-accumulation" systemic accumulation theory, it establishes a multi-level coupled identification method using high-resolution seismic data, achieving a technological shift from single-marker identification to comprehensive system identification.

[0146] This invention overcomes the shortcomings of traditional techniques, such as strong reliance on BSR (Biological Seismic Response) data, insufficient shallow hydrate identification capabilities, lack of systematic coupling, and low standardization. Based on the advantages of high-resolution seismic data acquisition and processing, and taking tectonic-fluid background coupling as a macroscopic constraint and shallow seismic anomalies and velocity characteristics as specific identification criteria, it forms a relatively scientific, efficient, and highly operable method for identifying shallow hydrate systems. This provides an effective technical approach for the exploration, resource evaluation, and future development and deployment of highly enriched shallow hydrate systems.

[0147] The technical challenge of this invention lies in the precise identification of shallow seismic reflection anomalies and the optimization of multi-condition comprehensive judgment rules. By introducing techniques such as seismic attribute analysis, velocity field inversion, and phase balance calculation, combined with regional geological background and drilling verification feedback, the above problems are effectively solved, ensuring the reliability and practicality of the identification results.

[0148] like Figure 8 As shown, this embodiment of the invention also provides a device 900 for identifying shallow seafloor hydrate systems based on high-precision seismic data, which can implement the above-mentioned method. This device may include: The first module 901 is used to acquire the seismic data volume of the target area; The second module 902 is used to identify target geological bodies and fluid transport channels based on seismic data volumes, and then to delineate the target spatial range of potential favorable hydrate accumulation areas through preliminary spatial coupling. The third module 903 is used to extract quantitative attribute anomalies and classify and identify anomalies in shallow seismic reflections based on the target spatial range and a predetermined range below the seabed, using seismic data volumes to obtain seismic reflection anomaly target bodies. The fourth module, 904, is used to obtain the P-wave velocity field of shallow strata through constrained inversion based on seismic data volumes, and to identify high-velocity velocity anomalies by constructing a regional background velocity trend surface based on the P-wave velocity field; and to identify atypical seafloor-like reflector layers based on seismic data volumes through preset markers. Module 5, 905, is used to use the atypical seafloor-like reflective layer as the bottom boundary constraint of the hydrate stability domain, to perform spatial coupling analysis on the seismic reflection anomaly target body and the velocity anomaly high-speed body, and to determine the favorable target area for hydrate development based on the results of the spatial coupling analysis.

[0149] In some embodiments, the apparatus may further include a sixth module for performing the following operations: Obtain well logging data from adjacent areas of the target zone where hydrates are favorable for development; Extract high P-wave velocity and high resistivity logging response feature templates from well logging data to determine hydrate intervals; The burial depth and thickness information of the target area for favorable hydrate development are spatially superimposed and compared with the top and bottom interfaces of the hydrate layer; The identification and verification results of the favorable development target area of ​​hydrates were determined based on the spatial superposition and comparison results.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] like Figure 9 As shown, Figure 9The 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.

[0154] 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.

[0155] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0156] 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.

[0157] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0158] 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.

[0159] 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.

[0160] The present invention provides a method, apparatus, electronic device, storage medium, and program product for identifying shallow seafloor hydrate systems based on high-precision seismic data. This method acquires seismic data volumes of a target area; identifies target geological structures and fluid transport channels based on the seismic data volumes; and then delineates the target spatial range of potential favorable hydrate accumulation areas through preliminary spatial coupling. Based on the target spatial range and a predetermined range below the seafloor, it uses the seismic data volumes to extract quantitative attribute anomalies of shallow seismic reflections and classify and identify anomaly targets, obtaining seismic reflection anomaly targets. Based on the seismic data volumes, it obtains the P-wave velocity field of shallow strata through constrained inversion, and calibrates high-velocity velocity anomalies by constructing a regional background velocity trend surface based on the P-wave velocity field. Based on the seismic data volumes, it identifies atypical seafloor-like reflection layers using preset markers; it uses the atypical seafloor-like reflection layers as the bottom boundary constraint of the hydrate stability domain, and performs spatial coupling analysis on the seismic reflection anomaly targets and high-velocity velocity anomalies, determining favorable hydrate development target areas based on the results of the spatial coupling analysis. This invention, through identifying tectonic geological bodies and fluid migration channels and performing preliminary spatial coupling, can delineate potentially favorable areas based on the "source-migration-accumulation" hydrocarbon accumulation elements, effectively overcoming the ambiguity of traditional methods that directly search for anomalies without considering the hydrocarbon accumulation background. Furthermore, this invention, through quantitative attribute extraction and anomaly classification, enables shallow seismic anomaly identification to move from qualitative experience to quantitative standardization. In addition, by introducing regional background velocity trend surfaces to calibrate high-velocity velocity anomalies and identifying atypical BSRs as stability domain constraints, this invention achieves parameter transformation from velocity fields to geological attributes. Finally, by spatially coupling the target anomaly with high-velocity anomalies and using this as the basis for determining the target area, this invention effectively eliminates the ambiguity of single anomalies, making the results more reliable and the process repeatable. The embodiments described in this invention are for the purpose of more clearly illustrating the technical solutions of this invention and do not constitute a limitation on the technical solutions provided by this invention. Those skilled in the art will understand that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by this invention are also applicable to similar technical problems.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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 shallow seafloor hydrate systems based on high-precision seismic data, characterized in that, The method includes the following steps: Acquire seismic data volume for the target area; Based on the seismic data volume, the target geological body and fluid transport channels are identified, and then the target spatial range of the potential favorable accumulation area of ​​hydrates is delineated through preliminary spatial coupling. Based on the target spatial range and the predetermined range below the seabed, the seismic data volume is used to extract the quantitative attribute anomalies of shallow seismic reflections and classify and identify the anomalies to obtain the seismic reflection anomaly target bodies. Based on the seismic data volume, the P-wave velocity field of shallow strata is obtained through constrained inversion. Based on the P-wave velocity field, a high-velocity velocity anomaly is identified by constructing a regional background velocity trend surface. Based on the seismic data volume, an atypical seafloor-like reflection layer is identified by preset markers. The atypical seafloor-like reflection layer is characterized by a phase axis that has a parallel spatial relationship with the seafloor and opposite amplitude polarity. This phase axis has discontinuous, beaded, and locally uplifted geometric features. Using the atypical seafloor-like reflective layer as the bottom boundary constraint of the hydrate stability domain, a spatial coupling analysis is performed on the seismic reflection anomaly target body and the velocity anomaly high-speed body, and the favorable target area for hydrate development is determined based on the results of the spatial coupling analysis. The seismic reflection anomaly target body includes strong amplitude anomalies and bright spot reflections. The atypical seafloor-like reflection layer is used as the bottom boundary constraint of the hydrate stability domain. Spatial coupling analysis is performed on the seismic reflection anomaly target body and the velocity anomaly high-velocity body. Based on the results of the spatial coupling analysis, the favorable hydrate development target area is determined, including the following steps: Spatial coupling analysis is performed on the seismic reflection anomaly target body and the velocity anomaly high-speed body to obtain the spatial coupling degree; The expression for the spatial coupling degree is: ； In the formula, Indicates spatial coupling degree; A represents a high-speed body with velocity anomalies; B represents a target body with seismic reflection anomalies. This represents the spatial range quantized using the voxel accumulation method. This spatial range is obtained by discretizing the three-dimensional space into regular voxels and then statistically analyzing the total volume of voxels that meet the recognition criteria. This represents the intersection operation. This indicates the operation of finding the minimum value; If the spatial coupling degree is greater than or equal to the preset coupling ratio, and the corresponding coupling region is located within a preset range above the atypical seabed reflective layer, the corresponding coupling region is determined to be a hydrate favorable development target area. If at least one of the strong amplitude anomalies or bright spot reflections exists in a certain analysis area, and there is no high-speed body with abnormal velocity in the corresponding analysis area, the corresponding analysis area is determined to be a free gas accumulation area. If a high-velocity anomalous body exists in a certain analysis area, and the corresponding high-velocity anomalous body is located below the atypical seafloor reflection layer, or if the spatial coupling degree of a certain analysis area is less than the preset coupling ratio, the corresponding analysis area is determined to be a non-hydrate high-velocity geological body area.

2. The method according to claim 1, characterized in that, The process of identifying target geological structures and fluid transport channels based on the seismic data volume, and then delineating the target spatial range of potential favorable hydrate accumulation areas through preliminary spatial coupling, includes the following steps: On time-domain seismic profiles, ancient uplifts, tectonic ridges, and local tectonic high points are identified as target tectonic geological bodies for hydrate accumulation by interpreting the morphology of the same phase axis. Seismic phase and amplitude anomaly analysis identifies gas chimneys, diapiric structures, tectonic faults, and fluid conduits as fluid migration channels for the vertical migration of deep gas-bearing fluids to shallower layers. If at least one type of fluid transport channel exists on the upper part of a certain target geological structure, the interior and upper preset area of ​​the corresponding fluid transport channel are delineated as the target spatial range of a potential favorable accumulation area for hydrates.

3. The method according to claim 1, characterized in that, The seismic reflection anomaly target body includes strong amplitude anomalies, bright spot reflections, and seismic uplift reflections. Based on the target spatial range and a predetermined range below the seabed, the seismic data volume is used to extract quantitative attribute anomalies of shallow seismic reflections and classify and identify anomalies to obtain the seismic reflection anomaly target body. This includes the following steps: The intersection of the target spatial range and the predetermined range below the seabed is processed to obtain the anomaly identification layer; Based on the earthquake data volume, seismic reflection attributes are extracted along or between the anomaly identification layers; wherein, the seismic reflection attributes include earthquake amplitude value, regional background amplitude value, seismic reflection phase axis, regional reflection mean time, and stratum reflection time; If the earthquake amplitude value in a certain local area is greater than a preset multiple of the background amplitude value of the area, and the lateral extension length of the corresponding local area is less than a first length threshold, the corresponding local area is marked as the bright spot reflection; wherein, the preset multiple represents 2 times; If the earthquake amplitude value of a certain continuous area is greater than the background amplitude value of the area, and the lateral extension length of the corresponding continuous area is greater than the second length threshold, the corresponding continuous area is marked as the strong amplitude anomaly. The region where the seismic reflection phase axis bends upward is taken as a candidate anomaly region. If the time difference between the stratum reflection time and the average reflection time of the region in a candidate anomaly region is less than the time difference threshold, the corresponding candidate anomaly region is marked as the seismic uplift reflection. Based on the spatial location and marker type of all the bright spot reflections, strong amplitude anomalies, and earthquake uplift reflections, the earthquake reflection anomaly target body is formed.

4. The method according to claim 1, characterized in that, The process of identifying the high-speed anomalous body based on the longitudinal wave velocity field by constructing a regional background velocity trend surface includes the following steps: A spatial sliding window is set at the starting position corresponding to the longitudinal wave velocity field; Based on the median of the velocity values ​​of the longitudinal wave velocity field at all spatial locations within the spatial sliding window, determine the trend surface background velocity of the region corresponding to the spatial sliding window. The velocity increment corresponding to each spatial position is obtained by calculating the difference between the velocity value of the longitudinal wave velocity field at each spatial position within the spatial sliding window and the background velocity of the trend surface. Slide the spatial sliding window one spatial position along the space corresponding to the longitudinal wave velocity field, and return to execute the step of calculating the median velocity value of all spatial positions within the spatial sliding window based on the longitudinal wave velocity field, until the spatial sliding window reaches the termination position corresponding to the longitudinal wave velocity field, and obtain the velocity increment of all spatial positions corresponding to the longitudinal wave velocity field. If the velocity increment at each spatial location in a continuous region is greater than a preset velocity threshold, and the spatial continuous distribution scale of the corresponding continuous region is greater than a preset scale threshold, the corresponding continuous region is marked as a high-speed body with abnormal velocity.

5. The method according to claim 1, characterized in that, The process of identifying atypical seafloor-like reflective layers based on the seismic data volume using preset identifiers includes the following steps: In the seismic data volume, in-phase axes that have a parallel spatial relationship with the seabed and have opposite amplitude polarities are matched as candidate reflector layers; Based on the candidate reflective layers, the atypical seabed-like reflective layers are identified by matching geometric features such as discontinuity, beading, and localized upward pull.

6. The method according to claim 1, characterized in that, The method further includes the following steps: Obtain well logging data from adjacent areas of the target zone where hydrates are favorable for development; High P-wave velocity and high resistivity logging response feature templates are extracted from the logging data to determine hydrate intervals; The burial depth and thickness information corresponding to the hydrate favorable development target area are spatially superimposed and compared with the top and bottom interfaces corresponding to the hydrate segment; The identification and verification results of the hydrate favorable development target area are determined based on the spatial superposition and comparison results.

7. A device for identifying shallow seafloor hydrate systems based on high-precision seismic data, characterized in that, The device includes: The first module is used to acquire seismic data volumes for the target area; The second module is used to identify target geological bodies and fluid transport channels based on the seismic data volume, and then to delineate the target spatial range of potential favorable hydrate accumulation areas through preliminary spatial coupling. The third module is used to extract quantitative attribute anomalies and classify and identify anomalies in shallow seismic reflections based on the target spatial range and a predetermined range below the seabed, using the seismic data volume to obtain seismic reflection anomaly target bodies. The fourth module is used to obtain the P-wave velocity field of shallow strata through constrained inversion based on the seismic data volume, and to identify the high-velocity velocity anomaly by constructing a regional background velocity trend surface based on the P-wave velocity field; and to identify atypical seafloor-like reflector layers based on the seismic data volume through preset markers. The fifth module is used to use the atypical seafloor-like reflective layer as the bottom boundary constraint of the hydrate stability domain, to perform spatial coupling analysis on the seismic reflection anomaly target body and the velocity anomaly high-speed body, and to determine the hydrate favorable development target area based on the results of the spatial coupling analysis. The seismic reflection anomaly target body includes strong amplitude anomalies and bright spot reflections. The atypical seafloor-like reflection layer is used as the bottom boundary constraint of the hydrate stability domain. Spatial coupling analysis is performed on the seismic reflection anomaly target body and the velocity anomaly high-velocity body. Based on the results of the spatial coupling analysis, the favorable hydrate development target area is determined, including the following steps: Spatial coupling analysis is performed on the seismic reflection anomaly target body and the velocity anomaly high-speed body to obtain the spatial coupling degree; The expression for the spatial coupling degree is: ； In the formula, Indicates spatial coupling degree; A represents a high-speed body with velocity anomalies; B represents a target body with seismic reflection anomalies. This represents the spatial range quantized using the voxel accumulation method. This spatial range is obtained by discretizing the three-dimensional space into regular voxels and then statistically analyzing the total volume of voxels that meet the recognition criteria. This represents the intersection operation. This indicates the operation of finding the minimum value; If the spatial coupling degree is greater than or equal to the preset coupling ratio, and the corresponding coupling region is located within a preset range above the atypical seabed reflective layer, the corresponding coupling region is determined to be a hydrate favorable development target area. If at least one of the strong amplitude anomalies or bright spot reflections exists in a certain analysis area, and there is no high-speed body with abnormal velocity in the corresponding analysis area, the corresponding analysis area is determined to be a free gas accumulation area. If a high-velocity anomalous body exists in a certain analysis area, and the corresponding high-velocity anomalous body is located below the atypical seafloor reflection layer, or if the spatial coupling degree of a certain analysis area is less than the preset coupling ratio, the corresponding analysis area is determined to be a non-hydrate high-velocity geological body area.

8. 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 6.

9. 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 6.

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