Marine unconsolidated natural gas hydrate reservoir resource quantity evaluation method

Abstract

The invention discloses an ocean unconsolidated natural gas hydrate reservoir resource quantity evaluation method, which comprises the following steps of: predicting the bottom boundary depth of a hydrate stable zone by comprehensively utilizing logging, three-dimensional earthquake and geological data, identifying a hydrate plane distribution range, and carrying out earthquake inversion to obtain a wave impedance data volume; a relation model of wave impedance, porosity and saturation is established, three-dimensional fine description of the hydrate ore body is achieved, and the resource quantity is calculated through hexahedron unit subdivision and a volumetric method. According to the method, parameter estimation precision and resource quantity calculation reliability are remarkably improved, and a scientific basis is provided for exploration and development of marine natural gas hydrates.

Description

Technical Field

[0001] This invention belongs to the field of marine geological technology, and in particular relates to a method for evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs. Background Technology

[0002] Accurately assessing the scale and resource potential of natural gas hydrate deposits by comprehensively utilizing information from seismic, geological, drilling, and well logging data is a crucial issue currently facing my country's natural gas hydrate resource survey and evaluation. Establishing a systematic and effective method for evaluating natural gas hydrate resources is of great significance for reducing exploration risks, lowering exploration costs, and making development decisions.

[0003] Natural gas hydrate resources refer to the total amount of natural gas after the decomposition of hydrates, which can be estimated by combining geological, geophysical, and geochemical data. Depending on the exploration stage and the level of data granularity, resources can be categorized into predicted resources, controlled resources, and proven resources. Estimating reasonable hydrate resources at different exploration stages is crucial for selecting optimal hydrate development areas and formulating reasonable development strategies.

[0004] Based on the different main principles and parameter selection methods used, the current methods for evaluating hydrate resources both domestically and internationally mainly include the area method, volume method, probability and statistics method, and material balance method. (1) Analogy The analogy method primarily relies on analogical (inference) analysis to estimate and analyze resource quantities within a single geological body. It is applicable to different exploration and evaluation stages and objectives. Key methods include resource abundance analogy and prospective trap distribution analogy. The accuracy of the evaluation results depends heavily on the correct selection of volumetric parameters and analogy objects. While applicable to resource evaluation at different stages, it is more effective for calculating early-stage resource quantities in basins.

[0005] (2) Volumetric method The theoretical basis for calculating resource quantity using the volumetric method is to directly calculate the natural gas hydrate resource quantity from the reservoir space. This is achieved by establishing the relationship between the hydrate ore body resource quantity and the ore body volume, porosity, and hydrate resource density per unit volume, and then summing these relationships to obtain the total resource quantity. The volumetric method is simple and intuitive, and the estimation results are relatively reliable.

[0006] (3) Probability and statistics method This method utilizes exploration data and employs mathematical statistical analysis to fit historical data into a trend-based growth curve for resource reserves. It effectively extrapolates past exploration results to future or exhaustive states, thereby summing up the total resource amount. Compared to the volumetric method, this method incorporates probability distribution patterns and reduces some uncertainties, and is now widely used in the South China Sea.

[0007] (4) Material balance method The organic carbon mass balance method is a material balance method. Based on identifying the main potential source rock strata of natural gas hydrates, this method obtains the area of ​​the source rock strata, calculates the mass of the source rock by using the cumulative thickness of the source rock measured by actual profiles and the average density of the source rock, and then calculates the gas production per unit mass of source rock by using the corresponding sample gas production rate value obtained from thermal simulation hydrocarbon generation experiments and the total organic carbon (TOC) test value. Finally, by combining the transport and accumulation coefficient, the geological resources of natural gas hydrates in the area can be preliminarily determined, that is, the maximum amount of hydrocarbon gas that can be provided for the formation of natural gas hydrates from the perspective of hydrocarbon generation.

[0008] Currently, the exploration and development of marine natural gas hydrates is at a low level, and the technology for evaluating the quantity of natural gas hydrate resources is not yet mature. This has hindered the pace of exploration and development of marine natural gas hydrate resources to some extent. Therefore, it is necessary to conduct research on the evaluation methods of marine natural gas hydrate resources, so as to provide important guidance for the selection of sweet spots for marine natural gas hydrate resources. Summary of the Invention

[0009] To address the aforementioned technical problems, this invention proposes a method for evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs, which significantly improves the accuracy and reliability of resource quantity calculation.

[0010] To achieve the above objectives, this invention provides a method for evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs, comprising the following steps: S1. Based on the gas component test data and geothermal gradient data of natural gas hydrates, the depth of the bottom boundary of the hydrate stability zone is predicted by phase equilibrium calculation. S2. Using the seafloor-like reflection features in 3D seismic data, identify the hydrate layer and the underlying free gas layer to determine the planar distribution range of the hydrate ore body; S3. Preprocess the 3D seismic data and well logging data, extract the seismic wavelet and perform well-seismic calibration, and obtain the 3D data volume of formation impedance through seismic inversion; S4. Using resistivity, density, and sonic logging curves, estimate formation porosity, hydrate saturation, and effective hydrate layer thickness. S5. Based on indoor rock physics experiments and well logging results, establish a relationship model between wave impedance and formation porosity and hydrate saturation, and apply the relationship model to the three-dimensional wave impedance data volume to obtain the three-dimensional data volume of formation porosity and the three-dimensional data volume of hydrate saturation. S6. Perform time-depth conversion on the three-dimensional wave impedance data volume to obtain the depth domain wave impedance data volume; S7. Use hexahedral elements to perform three-dimensional subdivision of the hydrate ore body and determine the volume, porosity and saturation of each hexahedral element; S8. For each hexahedral cell, calculate the natural gas reserves using the volumetric method, and sum the reserves of all cells to obtain the total resource.

[0011] Optionally, the predicted depth of the hydrate stability zone bottom boundary in S1 specifically includes: The gas composition of the natural gas hydrate sample was tested; geothermal gradient data and seafloor temperature of the study area were obtained; the bottom boundary depth of the hydrate stability zone was calculated using the hydrate phase equilibrium calculation software CSMGEM based on the gas composition, geothermal gradient data and seafloor temperature; the bottom boundary depth was confirmed by the intersection of the geothermal curve and the phase equilibrium curve.

[0012] Optionally, identifying the planar distribution range of hydrate ore bodies in S2 specifically includes: processing post-stack 3D seismic data; identifying seafloor-like reflection features on seismic profiles, wherein the seafloor-like reflection features have the characteristics of opposite polarity and strong amplitude to seafloor reflections; and delineating the planar distribution area of ​​hydrate layers based on the relationship between the seafloor-like reflection features and stratigraphic interfaces.

[0013] Optionally, obtaining the three-dimensional data volume of formation wave impedance through seismic inversion in S3 specifically includes: obtaining high signal-to-noise ratio, high fidelity, and zero-phase seismic data through three-dimensional seismic data processing; calculating wave impedance using sonic transit time logging curves and density logging curves; converting depth domain logging data to the time domain; extracting statistical wavelets using the least squares method based on the reflection coefficient sequence calculated from the well-side seismic traces and wells; obtaining the three-dimensional data volume of formation wave impedance using well-constrained sparse pulse inversion or fractal inversion methods; and obtaining the full-band absolute wave impedance through trace merging.

[0014] Optionally, the specific steps in S5 to establish the relationship model between wave impedance and formation porosity and hydrate saturation include: establishing the relationship between wave impedance and P-wave velocity using the Gardner formula, wherein the relationship is determined by power series fitting; drawing a cross-plot of porosity-wave impedance relationship using well logging interpretation results of density, sonic transit time and porosity, and obtaining the relationship between porosity and wave impedance by power series fitting; and selecting an equivalent medium model as the hydrate saturation prediction model.

[0015] Optionally, the time-depth conversion of the three-dimensional wave impedance data volume in S6 includes: establishing a velocity model based on the velocity data volume obtained by well logging constrained sparse pulse inversion; using the velocity model to perform time-depth conversion on the three-dimensional wave impedance data volume, converting the time-domain wave impedance data volume into a depth-domain wave impedance data volume; and using the time-depth relationship determined by well-seismic calibration during the conversion process.

[0016] Optionally, the three-dimensional subdivision of the hydrate ore body using hexahedral elements in S7 includes: based on depth domain impedance data, hydrate saturation data, and porosity data; writing a program to perform volume subdivision of the hydrate three-dimensional ore body sculpting model using hexahedral elements; determining the volume, porosity, and saturation of each basic hexahedral element within the hydrate ore body; the size of the hexahedral element is determined based on the seismic grid and sampling interval.

[0017] Optionally, the calculation of natural gas reserves using the volumetric method in S8 includes: estimating the natural gas reserves in the hydrate using the volumetric method for each hexahedral unit; and superimposing the natural gas reserves of all hexahedral units to obtain the total resource amount of the entire natural gas hydrate ore body.

[0018] Technical advantages of this invention: This invention discloses a method for evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs. By comprehensively utilizing well logging, 3D seismic, and geological data, a systematic method for describing the parameters and quantitatively evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs is established. This invention effectively integrates multi-source data, overcomes the limitations of single data sources, and improves the spatial prediction accuracy of key parameters such as formation porosity and hydrate saturation. Through the combination of seismic inversion and rock physics models, a detailed 3D characterization of hydrate ore bodies is achieved. The use of hexahedral element subdivision and element volume superposition significantly improves the precision and reliability of resource quantity calculation. This method provides an effective technical means for the accurate evaluation of marine natural gas hydrate resource potential and provides a scientific basis for the selection of exploration targets and development decisions. Attached Figure Description

[0019] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic flowchart of a method for evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the calculation results of the bottom boundary of the natural gas hydrate stability zone in a well on the southeastern continental slope of Qiongdong, according to an embodiment of the present invention. Figure 3 This is a cross-plot of wave impedance and longitudinal wave velocity according to an embodiment of the present invention; Figure 4 This is a cross-plot of wave impedance and longitudinal wave velocity according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the hydrate saturation of an example well predicted using the time-averaged equation model in an embodiment of the present invention. Figure 6 This is a schematic diagram of the hydrate saturation of an example well predicted using the Wood equation model in an embodiment of the present invention; Figure 7 This is a schematic diagram of the hydrate saturation of an example well predicted using the Lee weighted equation model in an embodiment of the present invention. Figure 8 This is a schematic diagram of the hydrate saturation of an example well predicted using the improved Biot-Gaussmann equation model in an embodiment of the present invention. Figure 9 This is a schematic diagram of the hydrate saturation of an example well predicted using the equivalent medium model (Model A) in an embodiment of the present invention; Figure 10 This is a schematic diagram of the hydrate saturation of an example well predicted using the equivalent medium model (Model B) in an embodiment of the present invention. Figure 11 This is a waveform impedance inversion profile diagram according to an embodiment of the present invention; Figure 12 This is a cross-sectional view of formation porosity according to an embodiment of the present invention; Figure 13 This is a cross-sectional view of the hydrate saturation in an embodiment of the present invention. Detailed Implementation

[0020] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0021] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0022] like Figure 1 As shown in the figure, this embodiment provides a method for evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs, including the following steps: S1. Based on the gas component test data and geothermal gradient data of natural gas hydrates, the depth of the bottom boundary of the hydrate stability zone is predicted by phase equilibrium calculation. S2. Using the seafloor-like reflection features in 3D seismic data, identify the hydrate layer and the underlying free gas layer to determine the planar distribution range of the hydrate ore body; S3. Preprocess the 3D seismic data and well logging data, extract the seismic wavelet and perform well-seismic calibration, and obtain the 3D data volume of formation impedance through seismic inversion; S4. Using resistivity, density, and sonic logging curves, estimate formation porosity, hydrate saturation, and effective hydrate layer thickness. S5. Based on indoor rock physics experiments and well logging results, establish a relationship model between wave impedance and formation porosity and hydrate saturation, and apply the relationship model to the three-dimensional wave impedance data volume to obtain the three-dimensional data volume of formation porosity and the three-dimensional data volume of hydrate saturation. S6. Perform time-depth conversion on the three-dimensional wave impedance data volume to obtain the depth domain wave impedance data volume; S7. Use hexahedral elements to perform three-dimensional subdivision of the hydrate ore body and determine the volume, porosity and saturation of each hexahedral element; S8. For each hexahedral cell, calculate the natural gas reserves using the volumetric method, and sum the reserves of all cells to obtain the total resource.

[0023] Furthermore, the predicted depth of the bottom boundary of the hydrate stability zone in S1 specifically includes: The gas composition of the natural gas hydrate sample was tested; geothermal gradient data and seafloor temperature of the study area were obtained; the bottom boundary depth of the hydrate stability zone was calculated using the hydrate phase equilibrium calculation software CSMGEM based on the gas composition, geothermal gradient data and seafloor temperature; the bottom boundary depth was confirmed by the intersection of the geothermal curve and the phase equilibrium curve.

[0024] Furthermore, the identification of the planar distribution range of hydrate ore bodies in S2 specifically includes: processing post-stack 3D seismic data; identifying seafloor-like reflection features on seismic profiles, wherein the seafloor-like reflection features have the characteristics of opposite polarity and strong amplitude to seafloor reflections; and delineating the planar distribution area of ​​hydrate layers based on the relationship between the seafloor-like reflection features and stratigraphic interfaces.

[0025] Furthermore, the specific steps in S3 for obtaining the three-dimensional data volume of formation wave impedance through seismic inversion include: obtaining high signal-to-noise ratio, high fidelity, and zero-phase seismic data through three-dimensional seismic data processing; calculating wave impedance using sonic transit time logging curves and density logging curves; converting depth-domain logging data to the time domain; extracting statistical wavelets using the least squares method based on the reflection coefficient sequence calculated from the well-side seismic traces and wells; obtaining the three-dimensional data volume of formation wave impedance using well-constrained sparse pulse inversion or fractal inversion methods; and obtaining the full-band absolute wave impedance through trace merging.

[0026] Specifically, the implementation process of this embodiment includes: Explanation of the lower boundary of the natural gas hydrate stability zone: The bottom boundary of the stable zone of natural gas hydrates can be identified using pseudo-seafloor reflections. Pseudo-seafloor reflections are reflection interfaces on seismic profiles that are approximately parallel to the seabed and can cut through all planes or faults. They have the characteristics of opposite polarity and strong amplitude compared to seafloor reflection interfaces. The specific steps are as follows: 1) Prepare post-stack 3D seismic data, natural gas hydrate sample test data, and geothermal gradient data for the study area; 2) For natural gas hydrates in the continental slope area, the seafloor reflections are obliquely intersecting with the bottom sediment interface. In this case, the bottom boundary of the stable zone of natural gas hydrates can be directly identified by the aforementioned seafloor reflection characteristics. 3) When the apparent seafloor reflection does not intersect the strata at a significant angle, it is necessary to statistically analyze the gas composition of natural gas hydrates to determine the hydrate type (Type SI and Type SII) at different stations. Then, based on the measured seafloor temperature and geothermal gradient, the depth of the bottom boundary of the hydrate stability zone under a specific gas composition is calculated using CSMGEM software. The accurate calculation of the BSR depth in the Qiongdongnan Basin is achieved by using the intersection of the geothermal curve and the phase equilibrium curve. Figure 2 As shown; 4) Based on the interpretation results of the apparent seabed reflection, the planar distribution range of natural gas hydrates can be obtained. In this embodiment, the distribution area of ​​natural gas hydrates is 32.8 km². 2 .

[0027] Furthermore, the specific steps in S5 to establish the relationship model between wave impedance and formation porosity and hydrate saturation include: establishing the relationship between wave impedance and P-wave velocity using the Gardner formula, which is determined by power series fitting; drawing a cross-plot of porosity-wave impedance relationship using well logging interpretation results of density, sonic transit time, and porosity, and obtaining the relationship between porosity and wave impedance through power series fitting; and selecting an equivalent medium model as the hydrate saturation prediction model.

[0028] Specifically, the implementation process of this embodiment includes: A detailed characterization of hydrate reservoirs was conducted using well logging curves based on resistivity, density, natural gamma, and acoustic logging. Parameters such as formation porosity, hydrate saturation, and effective hydrate layer thickness were estimated. Then, a model relating wave impedance / velocity to reservoir properties was established using laboratory rock physics experiments and well logging results. The specific steps are as follows: The wave impedance-longitudinal wave velocity relationship is established using Gardner's formula, and the calculation formula is as follows: (2); In the formula, For the density of the formation, For the longitudinal wave velocity of the formation, and These are constants obtained by fitting data from well logging or laboratory tests.

[0029] Using equation (2), the wave impedance is obtained. With longitudinal wave velocity The relationship is: (3); In the formula, For the ground wave impedance, and This is the constant after the formula conversion.

[0030] Using the logging density and sonic transit time logging interpretation results, a cross-plot of wave impedance and P-wave velocity is obtained, as shown below. Figure 3 As shown. In this embodiment, power series fitting is used to obtain the relationship between wave impedance and P-wave velocity as follows: (4); Using the logging interpretation results of density, sonic transit time, and porosity, a cross-plot of the porosity-wave impedance relationship is drawn, such as... Figure 4 As shown. In this embodiment, power series fitting is used to obtain the relationship between porosity and wave impedance as follows: (5).

[0031] Preferred sound velocity model for hydrate-bearing formations: Sound velocity models for hydrate-bearing formations are fundamental for predicting hydrate saturation using data from well logging and seismic analysis. Selecting a sound velocity model suitable for marine undiagenetic hydrate-bearing sediments is crucial for accurate hydrate saturation prediction. This study calculated natural gas hydrate saturation using various methods, including the time-averaged equation, the Wood equation, the Lee weighted equation, the improved Biot-Gassmann model, and the equivalent medium model. The results were compared with hydrate saturation predicted by chloride ion concentration anomalies. The sound velocity model for hydrate-bearing formations with the highest prediction accuracy was determined through this comparison.

[0032] When performing calculations using the improved Biot-Gaussmann model and the equivalent medium model, the mineral composition of the stratigraphic framework should first be obtained through experiments. In this embodiment, the stratigraphic framework is mainly composed of quartz, clay and calcite, accounting for 65.7%, 20% and 14.3% respectively.

[0033] Figures 5-10 The hydrate saturation of example wells predicted using the time-averaged equation, the Wood equation, the Lee weighted equation, the improved Biot-Gaussmann equation, and the equivalent medium model (modes A and B) are respectively.

[0034] In this embodiment, the equivalent medium model (B) is selected as the hydrate saturation prediction model.

[0035] Furthermore, the time-depth conversion of the three-dimensional wave impedance data volume in S6 includes: establishing a velocity model based on the velocity data volume obtained by well logging constrained sparse pulse inversion; using the velocity model to perform time-depth conversion on the three-dimensional wave impedance data volume, converting the time-domain wave impedance data volume into the depth-domain wave impedance data volume; and using the time-depth relationship determined by well-seismic calibration during the conversion process.

[0036] Specifically, the implementation process of this embodiment includes: By leveraging the high vertical resolution of well logging information and the lateral continuity of seismic data, broadband constrained inversion processing is performed on seismic profiles to obtain wave impedance profiles, which can reflect the lateral and vertical distribution of hydrates and provide important fundamental parameters for hydrate saturation prediction. The specific steps are as follows: 1) High signal-to-noise ratio, high fidelity, and zero-phase seismic data are obtained through 3D seismic data processing; 2) Calculate wave impedance using sonic time-of-flight logging curves and density logging curves. Use the time-depth relationship generated by the seismic traces near the well to convert the logging data in the depth domain to the time domain. Then, based on the reflection coefficient sequence calculated from the seismic traces near the well and the well, extract a statistical wavelet using methods such as the least squares method. 3) Within the work area, a three-dimensional low-frequency model is established by well point interpolation or by modeling along the sequence framework. In this embodiment, the low-frequency model is constructed by modeling along the sequence framework. 4) By minimizing the objective function and using maximum likelihood deconvolution, a sparse reflection coefficient sequence is obtained, and then the broadband wave impedance is derived; through channel combining, a full-bandwidth absolute wave impedance is obtained. The wave impedance inversion profile is shown below. Figure 11 As shown.

[0037] Further, reservoir parameter prediction: Using the obtained wave impedance-porosity relationship model, the wave impedance data volume obtained from constrained sparse pulse seismic inversion is converted into a porosity data volume, such as... Figure 12 As shown; The seismic wave impedance is converted into velocity data using the obtained wave impedance-P-wave velocity model, and then the spatial distribution of hydrate saturation is obtained from the equivalent medium equation, such as... Figure 13 As shown.

[0038] Furthermore, the three-dimensional subdivision of the hydrate ore body using hexahedral elements in S7 includes: based on depth domain impedance data, hydrate saturation data, and porosity data; writing a program to perform volume subdivision of the hydrate three-dimensional ore body sculpting model using hexahedral elements; determining the volume, porosity, and saturation of each basic hexahedral element within the hydrate ore body; the size of the hexahedral element is determined based on the seismic grid and sampling interval.

[0039] Furthermore, the calculation of natural gas reserves using the volumetric method in S8 includes: estimating the natural gas reserves in the hydrate using the volumetric method for each hexahedral unit; and superimposing the natural gas reserves of all hexahedral units to obtain the total resource amount of the entire natural gas hydrate ore body.

[0040] Specifically, the implementation process of this embodiment includes: Based on the velocity model, the three-dimensional wave impedance data volume is converted from time-domain to depth-domain data. Using the velocity data volume, hydrate saturation volume, and porosity volume obtained from well-logging constrained sparse pulse inversion as a basis, hexahedral elements are used to volumetrically partition the hydrate three-dimensional ore body model. The volume, porosity, and saturation of each basic hexahedral element within the hydrate ore body are determined. The natural gas reserves within each hexahedral element are estimated using the volumetric method. Then, the elements are stacked to obtain the total resource quantity of the entire natural gas hydrate ore body. The volumetric method formula for calculating the hydrate resource quantity is as follows: (6); In the formula, Natural gas reserves, It is the gas expansion factor. This is the standard ground temperature, usually taken as 293.15 K (20°C) or 288.15 K (15°C), depending on the national standard. This is the standard ground pressure, typically taken as 0.101325 MPa (1 standard atmosphere). For the first Formation pressure of a hexahedral unit, It is the gas compressibility factor. For the first The number of hexahedral units within the hydrate mineral body. For the first The volume of a hexahedral unit cell For the first Formation porosity of a hexahedral unit For the first Natural gas hydrate saturation of a hexahedral unit.

[0041] In this embodiment, each hexahedral grid is 25 m × 25 m × 2 ms in size. Using an average formation velocity of 1800 m / s and a gas volume expansion factor of 160, the calculated natural hydrate resource quantity in the study area is approximately 30.5 × 10⁻⁶ m / s. 8 m 3 .

[0042] Due to the limited well constraint data, the hydrate saturation obtained from seismic inversion has insufficient lateral constraints, which may lead to errors in resource quantity calculation.

[0043] Using natural gas reserve abundance as an evaluation index, that is, the geological reserves of natural gas per unit gas-bearing area, it is expressed as: (7); In the formula, For natural gas reserves abundance, 10 8 m 3 / km 2 ; For the geological reserves of natural gas in hydrate reservoirs, 10 8 m 3 ; For air-bearing area, km 2 .

[0044] The distribution area of ​​natural gas hydrates is 32.8 km². 2 As the distribution area of ​​hydrate reservoirs, the abundance of natural gas reserves is calculated to be 0.93 according to equation (7).

[0045] This invention discloses a method for evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs. By comprehensively utilizing well logging, 3D seismic, and geological data, a systematic method for describing the parameters and quantitatively evaluating the resource quantity of unconsolidated marine natural gas hydrate reservoirs is established. This invention effectively integrates multi-source data, overcomes the limitations of single data sources, and improves the spatial prediction accuracy of key parameters such as formation porosity and hydrate saturation. Through the combination of seismic inversion and rock physics models, a detailed 3D characterization of hydrate ore bodies is achieved. The use of hexahedral element subdivision and element volume superposition significantly improves the precision and reliability of resource quantity calculation. This method provides an effective technical means for the accurate evaluation of marine natural gas hydrate resource potential and provides a scientific basis for the selection of exploration targets and development decisions.

[0046] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea, characterized by, The method comprises the following steps: S1, predicting the bottom depth of the hydrate stability zone based on the gas component test data of the natural gas hydrate and the geothermal gradient data through phase equilibrium calculation; S2, identifying the hydrate layer and the underlying free gas layer by using the sea bottom reflection characteristics in the three-dimensional seismic data, and determining the planar distribution range of the hydrate ore body; S3, pre-processing the three-dimensional seismic data and the logging data, extracting the seismic wavelet and calibrating the well-seismic, obtaining the stratum wave impedance three-dimensional data body through seismic inversion; S4, estimating the stratum porosity, hydrate saturation and effective thickness of the hydrate layer by using the resistivity, density and acoustic logging curves; S5, based on the indoor rock physical experiment and the logging result, establishing the relationship model of the wave impedance and the stratum porosity and the hydrate saturation, and applying the relationship model to the wave impedance three-dimensional data body to obtain the stratum porosity three-dimensional data body and the hydrate saturation three-dimensional data body; S6, converting the wave impedance three-dimensional data body to the depth domain to obtain the depth domain wave impedance data body; S7, using the hexahedral unit to three-dimensionally subdivide the hydrate ore body, and determining the volume, porosity and saturation of each hexahedral unit; S8, for each hexahedral unit, calculating the natural gas reserves by using the volume method, and collecting the reserves of all units to obtain the total resource amount.

2. The method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea according to claim 1, characterized by, The S1 specifically comprises the following steps: testing the gas component of the natural gas hydrate sample; obtaining the geothermal gradient data and the sea bottom temperature of the research area; using the hydrate phase equilibrium calculation software CSMGEM, calculating the bottom depth of the hydrate stability zone based on the gas component, the geothermal gradient data and the sea bottom temperature; and confirming the bottom depth by the intersection point of the geothermal curve and the phase equilibrium curve.

3. The method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea according to Claim 1, wherein The S2 specifically comprises the following steps: processing the post-stack three-dimensional seismic data; identifying the sea bottom reflection characteristics on the seismic profile, the sea bottom reflection characteristics having the characteristics of opposite polarity and strong amplitude to the sea bottom reflection; and based on the relationship between the sea bottom reflection characteristics and the stratum interface, delineating the planar distribution area of the hydrate layer.

4. The method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea according to Claim 1, wherein The S3 specifically comprises the following steps: obtaining the seismic data with high signal-to-noise ratio, high fidelity and zero phase through three-dimensional seismic data processing; calculating the wave impedance by using the acoustic travel time logging curve and the density logging curve; converting the depth domain logging data to the time domain; based on the well seismic trace and the calculated reflection coefficient sequence, extracting the statistical wavelet by using the least square method; obtaining the stratum wave impedance three-dimensional data body by using the well-constrained sparse pulse inversion or fractal inversion method; and obtaining the full-band absolute wave impedance through trace merging.

5. The method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea according to Claim 1, wherein The S5 specifically comprises the following steps: establishing the relationship between the wave impedance and the stratum porosity and the hydrate saturation by using the Gardner formula to establish the relationship between the wave impedance and the P-wave velocity, and determining the relationship by power series fitting; drawing the porosity-wave impedance relationship crossplot by using the density, acoustic travel time and porosity logging interpretation results, and obtaining the relationship between the porosity and the wave impedance by power series fitting; and selecting the equivalent medium model as the hydrate saturation prediction model.

6. The method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea according to Claim 1, wherein The time-depth conversion of the wave impedance three-dimensional data body in S6 comprises: establishing a velocity model based on velocity data obtained by well-constrained sparse pulse inversion; using the velocity model to perform time-depth conversion on the wave impedance three-dimensional data body, so as to convert the time-domain wave impedance data body into a depth-domain wave impedance data body; and using a time-depth relationship determined by well-to-seismic calibration in the conversion process.

7. The method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea according to Claim 1, wherein The three-dimensional sectioning of the hydrate ore body by using hexahedral units in S7 comprises: taking the depth-domain wave impedance data body, the hydrate saturation data body and the porosity data body as the basis; writing a program to perform volume sectioning on the hydrate three-dimensional ore body sculpture model by using hexahedral units; determining the volume, porosity and saturation of each basic hexahedral unit in the hydrate ore body; and the size of the hexahedral unit is determined according to the seismic grid and the sampling interval.

8. The method for evaluating the resource amount of an unconsolidated natural gas hydrate reservoir in the sea according to Claim 1, wherein The volume method is used to calculate the natural gas reserves in S8, which comprises: for each hexahedral unit, the volume method is used to estimate the natural gas reserves in the hydrate; and the natural gas reserves of all the hexahedral units are superimposed to obtain the total resource quantity of the entire natural gas hydrate ore body.

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