A method, device and medium for identifying natural gas hydrates and conventional free gas

Abstract

The present invention discloses a method, device and medium for identifying natural gas hydrates and conventional free gas. The present invention establishes a rock physics model for natural gas hydrates and conventional free gas through a variety of parameter combinations to achieve simulation and prediction of the seismic response of natural gas hydrates; moreover, the present invention uses spectral decomposition technology to analyze seismic data, which helps to identify specific frequency characteristics related to natural gas hydrates; at the same time, by comparing the measured seismic data with the synthetic seismic data, the presence and characteristics of natural gas hydrates and related free gas can be identified. The objective of the present invention is to improve the success rate and efficiency of natural gas hydrate exploration through more precise identification and quantification methods. The present invention develops new exploration and characterization methods for the challenges in natural gas hydrate exploration to achieve the effective utilization of this potential energy resource. The present invention can be widely applied to the field of data processing technology.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a method, device, and medium for identifying natural gas hydrates and conventional free gas. Background Art

[0002] With the growth of global energy demand, the exploration of new energy resources has become particularly important. As a potential energy resource, natural gas hydrates have received great attention. The exploration of natural gas hydrates faces many challenges, including their uneven distribution underground, low density, and characteristics that are difficult to directly observe. Traditional exploration methods, such as logging and seismic exploration, although able to provide information about underground structures and rock physical properties, have limitations in directly detecting and quantifying natural gas hydrates. Summary of the Invention

[0003] The present invention aims to solve the problems of related technical limitations to at least a certain extent. For this purpose, the present invention provides a method, device, and medium for identifying natural gas hydrates and conventional free gas, which can conveniently identify natural gas hydrates and conventional free gas.

[0004] On the one hand, an embodiment of the present invention provides a method for identifying natural gas hydrates and conventional free gas, including the following steps:

[0005] Obtain logging data and measured seismic data of the target exploration area;

[0006] Based on the logging data, construct a rock physics model through a preset layered structure; wherein, the layered structure includes a background clay layer and a target sand body layer; the rock physics model includes a hydrate wedge model and a conventional gas wedge model; various parameter combinations of natural gas hydrates are preset in the target sand body layer of the hydrate wedge model, and various parameter combinations of conventional free gas are preset in the target sand body layer of the conventional gas wedge model;

[0007] Generate synthetic seismic data based on the rock physics model; the synthetic seismic data includes first synthetic seismic data corresponding to the hydrate wedge model and second synthetic seismic data corresponding to the conventional gas wedge model;

[0008] Perform spectral decomposition on the measured seismic data and the synthetic seismic data in sequence, and correspondingly obtain measured low-frequency data and synthetic low-frequency data; the synthetic low-frequency data includes first synthetic low-frequency data corresponding to the hydrate wedge model and second synthetic low-frequency data corresponding to the conventional gas wedge model;

[0009] Extract the amplitudes of the positive and negative phases of the measured low-frequency data to obtain the forward amplitude and the reverse amplitude; extract the amplitudes of the first synthetic low-frequency data and the second synthetic low-frequency data in sequence, and correspondingly obtain the hydrate amplitude and the conventional gas amplitude;

[0010] Compare and identify the forward amplitude with the hydrate amplitude, and the reverse amplitude with the conventional gas amplitude in sequence to obtain the identification results of natural gas hydrates and conventional free gas in the target exploration area.

[0011] Optionally, obtaining the logging data and measured seismic data of the target exploration area includes the following steps:

[0012] Deploy a logging system in the target exploration area and obtain the logging data of the target exploration area through the logging system; the logging data includes resistivity data, acoustic velocity data, radioactive data, electromagnetic data, and nuclear magnetic resonance data;

[0013] Arrange a seismic source in the target exploration area, emit seismic waves through the seismic source, and then use a geophone to record the reflection and refraction information of the seismic waves in the target exploration area to obtain the measured seismic data.

[0014] Optionally, the logging data includes resistivity data, acoustic velocity data, radioactive data, electromagnetic data, and nuclear magnetic resonance data; based on the logging data, a petrophysical model is constructed through a preset layered structure, including the following steps:

[0015] Determine the properties and distribution information of the underground rocks in the target exploration area based on the logging data;

[0016] Among them, the properties and distribution information include: water content and mineral type determined based on resistivity data; porosity, lithology, and pressure determined based on acoustic velocity data; shale content determined based on radioactive data; porosity and fluid type determined based on electromagnetic data; dynamic information of the fluid in the pores determined based on nuclear magnetic resonance data;

[0017] According to the properties and distribution information and the preset natural gas hydrates and conventional free gas with various parameter combinations, a petrophysical model is constructed based on the layered structure through a preset quantitative theory method.

[0018] Optionally, generating synthetic seismic data based on the petrophysical model includes the following steps:

[0019] Generate preliminary synthetic seismic data based on the petrophysical model using three-dimensional geological modeling technology;

[0020] Match and adjust the frequency content of the preliminary synthetic seismic data according to the main frequency of the measured seismic data using spectral analysis and frequency band extension technology to obtain the synthetic seismic data.

[0021] Optionally, extracting the amplitudes of the positive and negative phases from the measured low-frequency data to obtain the forward amplitude and the reverse amplitude includes the following steps:

[0022] Extract amplitude data from measured low-frequency data using a phase scanning method, and then identify the positive and negative phase characteristics of the amplitude in the amplitude data and their corresponding dominant positions to obtain the forward amplitude and the reverse amplitude.

[0023] Optionally, the multiple parameter combinations include combinations of thickness and saturation in multiple numerical ranges for natural gas hydrates and combinations of distribution and content in multiple numerical ranges for conventional free gas; compare and identify the forward amplitude with the hydrate amplitude, and the reverse amplitude with the conventional gas amplitude in sequence to obtain the identification results of natural gas hydrates and conventional free gas in the target exploration area, including the following steps:

[0024] Perform a first comparison and identification between the forward amplitude and the hydrate amplitude of the hydrate wedge model corresponding to the thickness and saturation in each numerical range to obtain the first identification results of the thickness and saturation of natural gas hydrates;

[0025] Perform a second comparison and identification between the reverse amplitude and the conventional gas amplitude of the conventional gas wedge model corresponding to the distribution and content in each numerical range to obtain the second identification results of the distribution and content of conventional free gas.

[0026] Optionally, the method further includes the following steps:

[0027] Obtain sampling data of the target exploration area; the sampling data is collected based on the sidewall coring technology;

[0028] Verify the identification results based on the sampling data, and adjust the parameters of the rock physics model according to the results of the verification process.

[0029] On the other hand, an embodiment of the present invention provides an identification device for natural gas hydrates and conventional free gas, including:

[0030] A first module for obtaining well logging data and measured seismic data of the target exploration area;

[0031] A second module for constructing a rock physics model based on the well logging data through a preset layered structure; wherein, the layered structure includes a background clay layer and a target sand body layer; the rock physics model includes a hydrate wedge model and a conventional gas wedge model; the target sand body layer of the hydrate wedge model is preset with multiple parameter combinations of natural gas hydrates, and the target sand body layer of the conventional gas wedge model is preset with multiple parameter combinations of conventional free gas;

[0032] A third module for generating synthetic seismic data based on the rock physics model; the synthetic seismic data includes first synthetic seismic data corresponding to the hydrate wedge model and second synthetic seismic data corresponding to the conventional gas wedge model;

[0033] The fourth module is used to perform spectral decomposition on the measured seismic data and the synthetic seismic data in sequence, and correspondingly obtain the measured low-frequency data and the synthetic low-frequency data; the synthetic low-frequency data includes the first synthetic low-frequency data corresponding to the hydrate wedge model and the second synthetic low-frequency data corresponding to the conventional gas wedge model.

[0034] The fifth module is used to extract the amplitudes of the positive and negative phases of the measured low-frequency data to obtain the forward amplitude and the reverse amplitude; the amplitudes of the first synthetic low-frequency data and the second synthetic low-frequency data are sequentially extracted to correspondingly obtain the hydrate amplitude and the conventional gas amplitude.

[0035] The sixth module is used to sequentially compare and identify the forward amplitude with the hydrate amplitude, and the reverse amplitude with the conventional gas amplitude, and obtain the identification results of natural gas hydrates and conventional free gas in the target exploration area.

[0036] Optionally, the device further includes:

[0037] The seventh module is used to obtain the sampling data of the target exploration area; the sampling data is collected based on the sidewall coring technology.

[0038] The eighth module is used to perform verification processing on the identification results based on the sampling data, and adjust the parameters of the rock physics model according to the results of the verification processing.

[0039] On the other hand, an embodiment of the present invention provides an electronic device, including: a processor and a memory; the memory is used to store a program; the processor executes the program to implement the above-mentioned identification method for natural gas hydrates and conventional free gas.

[0040] On the other hand, an embodiment of the present invention provides a computer storage medium, in which a program executable by a processor is stored, and the program executable by the processor is used to implement the above-mentioned identification method for natural gas hydrates and conventional free gas when executed by the processor.

[0041] In an embodiment of the present invention, logging data and measured seismic data of a target exploration area are obtained; based on the logging data, a rock physics model is constructed through a preset layered structure; wherein, the layered structure includes a background clay layer and a target sand body layer; the rock physics model includes a gas hydrate wedge model and a conventional gas wedge model; various parameter combinations of natural gas hydrates are preset in the target sand body layer of the gas hydrate wedge model, and various parameter combinations of conventional free gas are preset in the target sand body layer of the conventional gas wedge model; synthetic seismic data is generated based on the rock physics model; the synthetic seismic data includes first synthetic seismic data corresponding to the gas hydrate wedge model and second synthetic seismic data corresponding to the conventional gas wedge model; the measured seismic data and the synthetic seismic data are sequentially subjected to spectral decomposition to obtain measured low-frequency data and synthetic low-frequency data correspondingly; the synthetic low-frequency data includes first synthetic low-frequency data corresponding to the gas hydrate wedge model and second synthetic low-frequency data corresponding to the conventional gas wedge model; the amplitudes of the positive and negative phases of the measured low-frequency data are extracted to obtain a positive amplitude and a negative amplitude; the amplitudes of the first synthetic low-frequency data and the second synthetic low-frequency data are sequentially extracted to obtain a gas hydrate amplitude and a conventional gas amplitude correspondingly; the positive amplitude is compared and identified with the gas hydrate amplitude, and the negative amplitude is compared and identified with the conventional gas amplitude to obtain the identification results of natural gas hydrates and conventional free gas in the target exploration area. The present invention establishes a rock physics model with various parameter combinations of natural gas hydrates and conventional free gas to simulate and predict the seismic response of natural gas hydrates; moreover, the present invention uses spectral decomposition technology to analyze seismic data, which helps to identify specific frequency characteristics related to natural gas hydrates; meanwhile, by comparing the measured seismic data with the synthetic seismic data, the presence and characteristics of natural gas hydrates and related free gas can be identified. The goal of the present invention is to improve the success rate and efficiency of natural gas hydrate exploration through more accurate identification and quantification methods. The present invention develops new exploration and characterization methods for the challenges in natural gas hydrate exploration to achieve the effective utilization of this potential energy resource. Description of the Drawings

[0042] The drawings are used to provide a further understanding of the technical solutions of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation to the technical solutions of the present invention.

[0043] Figure 1 It is a schematic diagram of an implementation environment for identifying natural gas hydrates and conventional free gas provided by an embodiment of the present invention;

[0044] Figure 2 It is a schematic flowchart of a method for identifying natural gas hydrates and conventional free gas provided by an embodiment of the present invention;

[0045] Figure 3It is a schematic diagram of the expanded process of step S100 provided by an embodiment of the present invention;

[0046] Figure 4 It is a schematic diagram of the expanded process of step S200 provided by an embodiment of the present invention;

[0047] Figure 5 It is a schematic diagram of an exemplary structure of the rock physics model provided by an embodiment of the present invention;

[0048] Figure 6 It is a schematic diagram of another exemplary structure of the rock physics model provided by an embodiment of the present invention;

[0049] Figure 7 It is a schematic diagram of the expanded process of step S300 provided by an embodiment of the present invention;

[0050] Figure 8 It is a schematic diagram of the overall process of a method for identifying natural gas hydrates and conventional free gas provided by an embodiment of the present invention;

[0051] Figure 9 It is a schematic diagram of the structure of a device for identifying natural gas hydrates and conventional free gas provided by an embodiment of the present invention;

[0052] Figure 10 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0053] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present 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 only used to explain the present invention, and are not used to limit the present invention.

[0054] It should be noted that although functional module division is performed in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the system or the order in the flowchart. Terms such as "first / S100", "second / S200", etc. in the specification, claims and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence.

[0055] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appears in various positions in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0056] It can be understood that the method for identifying natural gas hydrates and conventional free gas provided by the embodiments of the present 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 embodiment 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 communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal is a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto.

[0057] For the convenience of understanding the technical solution of the present invention, first, the technical feature proper nouns that may appear in the embodiments of the present invention are explained:

[0058] As Figure 1 shown, it is a schematic diagram of an implementation environment provided by the embodiments of the invention. Referring to Figure 1 , this implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be network-connected by wireless or wired means to complete data transmission and exchange.

[0059] The server 101 can be 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 communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0060] In addition, the server 101 can also be a node server in a blockchain network. Among them, the blockchain is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithm.

[0061] The terminal 102 can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited thereto. The terminal 102 and the server 101 can be directly or indirectly connected by wired or wireless communication means, and the embodiments of the present invention do not limit this here.

[0062] Exemplarily based on Figure 1In the implementation environment shown, an embodiment of the present invention provides a method for identifying natural gas hydrates and conventional free gas. Taking the application of this method for identifying natural gas hydrates and conventional free gas in server 101 as an example for illustration, it can be understood that this method for identifying natural gas hydrates and conventional free gas can also be applied to terminal 102.

[0063] Referring to Figure 2 , Figure 2 is a flowchart of the method for identifying natural gas hydrates and conventional free gas applied to a server provided by an embodiment of the present invention. The execution subject of this method for identifying natural gas hydrates and conventional free gas can be any of the aforementioned computer devices (including servers or terminals). Referring to Figure 2 , this method includes the following steps:

[0064] S100. Obtain well logging data and measured seismic data of the target exploration area;

[0065] It should be noted that in some embodiments, as Figure 3 shown, step S100 may include the following steps:

[0066] S101. Deploy a well logging system in the target exploration area, and obtain well logging data of the target exploration area through the well logging system; the well logging data includes resistivity data, acoustic velocity data, radioactive data, electromagnetic data, and nuclear magnetic resonance data;

[0067] Exemplarily, in some specific implementation manners, a well logging system can be deployed on an offshore platform. This system lowers well logging instruments into the oil well through a cable, and uses a variety of sensors to record the physical properties of the rock. These instruments can measure the resistivity, acoustic velocity, radioactive intensity, electromagnetic characteristics, and nuclear magnetic resonance characteristics of the rock, so as to obtain detailed information about the rock and the rock-filled fluid.

[0068] S102. Arrange a seismic source in the target exploration area, emit seismic waves through the seismic source, and then use geophones to record the reflection and refraction information of the seismic waves in the target exploration area to obtain measured seismic data.

[0069] Exemplarily, in some specific implementation manners, multiple geophones and seismic sources can be arranged on site to collect 3D seismic data. These data help generate a three-dimensional image of the underground structure by recording the reflection and refraction information of seismic waves underground, and play an important role in identifying geological structures, faults, and hydrocarbon reservoir boundaries, etc.

[0070] Among them, during the logging process, the following key parameter data will be collected: resistivity data is used to judge the water content and mineral type of rock formations; acoustic velocity data is used to infer the porosity, lithology, and pressure of the formation; radioactive data is used to determine the shale content of the formation; electromagnetic data is used to infer the porosity and fluid type of rocks; nuclear magnetic resonance data is used to obtain the dynamic information of fluids in rock pores. These data are crucial for understanding the properties and distribution of subsurface rocks.

[0071] S200. Based on the logging data, a rock physics model is constructed through a preset layered structure;

[0072] Among them, the layered structure includes a background clay layer and a target sand body layer; the rock physics model includes a hydrate wedge model and a conventional gas wedge model; the target sand body layer of the hydrate wedge model is preset with various parameter combinations of natural gas hydrates, and the target sand body layer of the conventional gas wedge model is preset with various parameter combinations of conventional free gas;

[0073] It should be noted that the logging data includes resistivity data, acoustic velocity data, radioactive data, electromagnetic data, and nuclear magnetic resonance data; in some embodiments, as Figure 4 shown, step S200 may include the following steps: S201. Determine the properties and distribution information of the subsurface rocks in the target exploration area based on the logging data; among them, the properties and distribution information includes: water content and mineral type determined based on resistivity data; porosity, lithology, and pressure determined based on acoustic velocity data; shale content determined based on radioactive data; porosity and fluid type determined based on electromagnetic data; dynamic information of fluids in voids determined based on nuclear magnetic resonance data; S202. According to the properties and distribution information and various preset parameter combinations of natural gas hydrates and conventional free gas, construct a rock physics model based on the layered structure through a preset quantitative theory method.

[0074] Exemplarily, in some specific embodiments, a velocity-density-thickness model can be established using logging data. Determine the physical parameters of the background clay layer and the target sand body layer.

[0075] Assume that the target sand body layer is filled with water and use the physical parameters of water as the basis. When establishing the velocity-density-thickness model and determining the physical parameters of the background clay layer and the target sand body layer, it is mainly based on the following theories and empirical formulas:

[0076] Biot theory: This is a theory that describes the propagation of elastic waves in saturated porous media. In the interpretation of logging data, the Biot theory is used to explain the propagation characteristics of acoustic waves in fluid-bearing rocks, especially in the three-phase medium (rock skeleton, hydrate, pore fluid) when considering the presence of natural gas hydrates.

[0077]

[0078]

[0079]

[0080]

[0081] Among them, are the velocities of the fast compressional wave and the slow compressional wave, are the attenuation coefficients of the fast compressional wave and the slow compressional wave, is the velocity of the shear wave, is the attenuation coefficient of the shear wave, is the angular frequency, and respectively represent the real part and the imaginary part of the complex number.

[0082] Gassmann equation: This is an empirical formula used to describe the change in wave velocity in fluid-saturated rocks. It can be used to calculate the elastic parameters of rocks after fluid replacement, such as the compressional wave velocity and the shear wave velocity. The Gassmann equation is used to describe the change in elastic parameters of rocks after fluid replacement, and its basic form is:

[0083]

[0084] Among them, is the bulk modulus of the dry rock, is the bulk modulus of the fluid-saturated rock, is the bulk modulus of the fluid, Porosity.

[0085] Equivalent medium theory: This theory is used to describe the macroscopic physical properties of multiphase media, such as resistivity and elastic wave velocity, by treating the multiphase medium as a single equivalent medium to simplify calculations.

[0086] Through these theories and methods, the effects of natural gas hydrates and conventional free gas on the petrophysical properties under different saturation conditions can be quantitatively analyzed and predicted, providing a scientific basis for geological exploration and resource assessment.

[0087] Furthermore, the following can be achieved by constructing two models in the petrophysical model:

[0088] Model A: Assume that there are natural gas hydrates with different contents (thickness and saturation) in the target sandstone layer. As Figure 5 shown, it is a schematic diagram of the structure example of Model A ( Figure 5 illustrated by the percentage content of hydrates, which can be adjusted according to needs in actual applications).

[0089] Model B: Assume that there is conventional free gas with different contents (distribution and content) in the target sand body layer. As Figure 6 shown, it is a schematic diagram of the structural example of Model B ( Figure 6 illustrated by the percentage content of conventional gas in the figure, which can be adjusted according to requirements in actual applications).

[0090] When constructing Model A and Model B, the influence of different saturations of natural gas hydrate and conventional free gas on rock physical properties is mainly considered in the following ways:

[0091] Model A (natural gas hydrate saturation model, i.e., hydrate wedge model): In this model, the influence of the morphology, distribution, and saturation of hydrate on rock physical properties is considered. The presence of hydrate will affect the elastic properties and fluid flow properties of the rock, and these effects are quantified through Biot theory and equivalent medium theory.

[0092] Model B (conventional free gas saturation model, i.e., conventional gas wedge model): In this model, the influence of the presence and saturation of conventional free gas on rock physical properties is considered. Free gas will affect the porosity, permeability, and elastic wave velocity of the rock, and these effects are described through Gassmann equation and equivalent medium theory.

[0093] S300. Generate synthetic seismic data based on the rock physical model;

[0094] Among them, the synthetic seismic data includes the first synthetic seismic data corresponding to the hydrate wedge model and the second synthetic seismic data corresponding to the conventional gas wedge model;

[0095] It should be noted that in some embodiments, as Figure 7 shown, step S300 may include the following steps: S301. Generate preliminary synthetic seismic data based on the rock physical model using 3D geological modeling technology; S302. Match and adjust the frequency content of the preliminary synthetic seismic data according to the main frequency of the measured seismic data using spectral analysis and frequency band extension technology to obtain the synthetic seismic data.

[0096] Exemplarily, in some specific embodiments, first, the KL-3DGeoModeler 3D geological modeling technology can be used to generate synthetic seismic data. This technology takes the construction of non-topological consistent blocks as the core, supports the fusion modeling of profile data, scatter point data, theoretical geometric bodies, and external surface data, effectively improving the success rate of block construction and shortening the modeling cycle.

[0097] Furthermore, based on the changes in the sand layer thickness, hydrate saturation, and conventional free gas volume in Model A and Model B, the frequency content of the synthetic seismic data can be adjusted to ensure its matching with the main frequency of the measured seismic data. Through the spectral analysis and frequency band extension technology of the seismic data, the frequency response of the synthetic seismic data is ensured to match the measured data, thereby generating synthetic seismic data that conforms to the geological actual situation. This process involves a detailed analysis of the seismic data spectrum and necessary frequency band extension of the synthetic seismic data to achieve the matching with the main frequency of the measured seismic data.

[0098] S400. Perform spectral decomposition on the measured seismic data and the synthetic seismic data in sequence, and correspondingly obtain the measured low-frequency data and the synthetic low-frequency data.

[0099] Among them, the synthetic low-frequency data includes the first synthetic low-frequency data corresponding to the hydrate wedge model and the second synthetic low-frequency data corresponding to the conventional gas wedge model; specifically, the spectral decomposition is realized through discrete Fourier transform based on a preset main analysis frequency.

[0100] Exemplarily, in some specific embodiments, the application of spectral decomposition can achieve the following:

[0101] 1) In this step, perform spectral decomposition on the measured seismic data set and the synthetic seismic data set. For example, 15 Hz can be selected as the main analysis frequency, and this selection is based on the spectral parameters of the seismic data, where the main frequency is the frequency corresponding to the maximum value of the spectrum, and 15 Hz can provide a good balance point to ensure appropriate anti-aliasing and avoid information redundancy at the high-frequency end.

[0102] 2) Use spectral decomposition technology to extract low-frequency narrowband data. This technology is based on the discrete Fourier transform (DFT), which converts the seismic signal from the time domain to the frequency domain to generate a high-resolution seismic image and identify the lateral distribution of medium properties.

[0103] S500. Extract the amplitudes of the positive and negative phases of the measured low-frequency data to obtain the forward amplitude and the reverse amplitude; perform amplitude extraction on the first synthetic low-frequency data and the second synthetic low-frequency data in sequence, and correspondingly obtain the hydrate amplitude and the conventional gas amplitude.

[0104] It should be noted that in some embodiments, step S500 may include the following steps: use the phase scanning method to extract amplitude data from the measured low-frequency data, and then identify the positive and negative phase characteristics of the amplitude in the amplitude data and their corresponding dominant positions to obtain the forward amplitude and the reverse amplitude.

[0105] Exemplarily, in some specific embodiments, the amplitude can be extracted from the measured low-frequency data, and the positive and negative phase characteristics of the amplitude and their dominant positions can be identified. This process can be achieved by a phase scanning method, which determines the polarity of the seismic profile by comparing the correlation between the well impedance and the relative impedance inverted from the near-well trace, as well as the phase of the seismic profile. In addition, the amplitude extraction for hydrate amplitude and conventional gas amplitude can be achieved by conventional amplitude extraction methods, which will not be elaborated here.

[0106] S600. Compare and identify the positive amplitude with the hydrate amplitude, and the negative amplitude with the conventional gas amplitude in sequence to obtain the identification results of natural gas hydrates and conventional free gas in the target exploration area.

[0107] It should be noted that the multiple parameter combinations include the combinations of the thickness and saturation of multiple numerical ranges for natural gas hydrates and the combinations of the distribution and content of multiple numerical ranges for conventional free gas; in some embodiments, step S600 may include the following steps: perform a first comparison and identification between the positive amplitude and the hydrate amplitude of the hydrate wedge model corresponding to the thickness and saturation of each numerical range to obtain the first identification results of the thickness and saturation of natural gas hydrates; perform a second comparison and identification between the negative amplitude and the conventional gas amplitude of the conventional gas wedge model corresponding to the distribution and content of each numerical range to obtain the second identification results of the distribution and content of conventional free gas.

[0108] Exemplarily, in some specific embodiments, the extracted amplitude is compared with the amplitude data corresponding to the synthetic seismic data. For the area dominated by positive amplitude (i.e., the forward amplitude), it is compared with the amplitude data corresponding to the synthetic seismic data of model A; for the area dominated by negative amplitude (i.e., the reverse amplitude), it is compared with the amplitude data corresponding to the synthetic seismic data of model B. This comparison helps to verify the accuracy of the geological model and identify possible geological anomalies or features. Furthermore, based on the comparison results, the presence of natural gas hydrates and free gas and their data conditions are identified. Specifically, taking Figure 5 the shown model A as an example, the similarity determination is respectively performed between the positive amplitude and the amplitude data corresponding to the synthetic seismic data obtained with different hydrate contents in model A, and then the identification result of the natural gas hydrates in the target exploration area is determined according to the hydrate content corresponding to the highest similarity.

[0109] It should also be noted that in some embodiments, the method may further include the following steps: obtaining the sampling data of the target exploration area; the sampling data is collected based on the sidewall coring technology; verifying the identification results based on the sampling data, and adjusting the parameters of the rock physics model according to the results of the verification process.

[0110] Exemplarily, in some specific embodiments, if the gap between the sampled data and the recognition result is too large (e.g., greater than a preset threshold), the distribution density of the data range of various parameter combinations set in the rock physics model can be adjusted accordingly according to the verified gap size (the larger the gap, the larger the distribution density setting).

[0111] In some specific application scenarios, verification and adjustment can be achieved as follows:

[0112] 1) Verify the exploration results. During the process of verifying the exploration results, the sidewall coring technique is used to obtain core samples. In the coring operation, by using a sidewall coring tool, it is possible to accurately judge whether the coring is successful and measure the length of the core taken. Between cores, spacers can be inserted to accurately distinguish the horizons of the cores. This technique allows adjusting the key parameters of the instrument according to the formation characteristics, effectively improving the coring efficiency and coring success rate. The sidewall coring tool adopts a modular structure, which is convenient for the maintenance and repair of the instrument.

[0113] 2) Adjust the rock physics model and exploration parameters. According to the core samples obtained from sidewall coring and the verification results, the rock physics model and exploration parameters are adjusted. This process involves a detailed analysis of the core samples, including the physical properties of the cores such as porosity, permeability, and the elastic parameters of the rock. These parameters will be compared with seismic data to verify and adjust the rock physics model. The adjustment strategy includes re-evaluating the physical properties of the rock based on the core analysis results and their correlation with seismic data. By this method, it can be ensured that the adjusted model is more accurate and reliable, providing a scientific basis for the adjustment of exploration parameters. Such adjustment helps to optimize the exploration strategy and improve the success rate and efficiency of exploration.

[0114] To explain the principle of the technical solution of the present invention in detail, the overall process of the present invention will be described below in conjunction with 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.

[0115] First of all, it should be noted that the exploration of natural gas hydrates can be achieved by the following steps in the present invention:

[0116] 1) Establish a rock physics model:

[0117] Use well logging data (such as gamma ray, resistivity, acoustic velocity, and density) to establish a velocity-density-thickness model of background clay and target sand bodies, so as to accurately simulate the geological structure.

[0118] 2) Generate synthetic seismic data:

[0119] Generate two sets of synthetic seismic data based on the geological model, one set representing pure gas hydrate and the other representing free gas beneath the gas hydrate. Generate the synthetic seismic data by simulating different geological conditions (such as changes in sand layer thickness, hydrate saturation, and free gas volume).

[0120] 3) Apply spectral decomposition:

[0121] Perform spectral decomposition on the measured seismic data and the synthetic seismic data to extract low-frequency narrowband data, in order to highlight specific seismic features related to gas hydrate and free gas.

[0122] 4) Amplitude extraction and comparison:

[0123] Extract the amplitude from the measured seismic data and compare it with the synthetic seismic data. This includes identifying the positive and negative phase characteristics of the amplitude and their dominance to distinguish different types of geological structures.

[0124] As Figure 8 shown, the method of the present invention may specifically include the following steps:

[0125] Step 1: Data collection:

[0126] 1) Offshore platform logging system:

[0127] Deploy a logging system on the offshore platform. This system lowers logging instruments into the oil well through a cable and uses various sensors to record the physical properties of the rock. These instruments can measure the resistivity, acoustic velocity, radioactivity intensity, electromagnetic characteristics, and nuclear magnetic resonance characteristics of the rock, thereby obtaining detailed information about the rock and the rock-filled fluid.

[0128] 2) Collect logging data:

[0129] During logging, the following key parameter data will be collected: Resistivity data is used to judge the water content and mineral type of the rock formation; Acoustic velocity data is used to infer the porosity, lithology, and pressure of the formation; Radioactivity data is used to determine the shale content of the formation; Electromagnetic data is used to infer the porosity and fluid type of the rock; Nuclear magnetic resonance data is used to obtain dynamic information about the fluid in the rock pores. These data are crucial for understanding the properties and distribution of underground rocks.

[0130] 3) Collect measured seismic data sets:

[0131] On-site, collect 3D seismic data by arranging multiple geophones and sources. These data help generate a three-dimensional image of the underground structure by recording the reflection and refraction information of seismic waves underground, and are important for identifying geological structures, faults, and hydrocarbon reservoir boundaries, etc.

[0132] Among them, the technical requirements and operation specifications are as follows:

[0133] During the data collection process, strict technical requirements and operating specifications will be followed, including selecting appropriate instrument equipment and conducting regular calibration to ensure the accuracy and reliability of data collection. At the same time, various index data will be accurately collected, and attention will be paid to the consistency of time and space to ensure the continuity and integrity of the data. In addition, the geological structure, landform, soil quality, etc. of the target area will be detailedly recorded and observed, and information such as sample numbers, sampling depths, and sampling horizons will be properly preserved. Data processing will include data sorting, data analysis, and data interpretation, etc., to ensure the reliability and effectiveness of exploration results. All personnel engaged in geological exploration work must receive safety awareness education and training, understand relevant safety regulations, be familiar with operating procedures, and master necessary safety skills.

[0134] Step 2: Establish a rock physics model

[0135] 1) Use logging data to establish a velocity-density-thickness model. Determine the physical parameters of the background clay layer and the target sand body layer.

[0136] Assume that the target sand body layer is filled with water and use the physical parameters of water as the basis. When establishing the velocity-density-thickness model and determining the physical parameters of the background clay layer and the target sand body layer, it is mainly based on Biot theory, Gassmann equation, and equivalent medium theory (the specific principle logic refers to the content of the foregoing specific implementation manners and will not be elaborated here).

[0137] Through these theories and methods, the effects of natural gas hydrates and conventional free gas on rock physical properties under different saturation conditions can be quantitatively analyzed and predicted, providing a scientific basis for geological exploration and resource assessment.

[0138] 2) Construct two models:

[0139] Model A: Assume that there are natural gas hydrates with different thicknesses and saturations in the target sand body layer.

[0140] Model B: Assume that there are conventional free gases with different distributions and contents in the target sand body layer.

[0141] When constructing Model A and Model B, the effects of different saturations of natural gas hydrates and conventional free gas on rock physical properties are considered mainly in the following ways:

[0142] Model A (natural gas hydrate saturation model): In this model, the effects of the morphology, distribution, and saturation of hydrates on rock physical properties are considered. The presence of hydrates will affect the elastic properties and fluid flow properties of rocks, and these effects are quantified through Biot theory and equivalent medium theory.

[0143] Model B (Conventional Free Gas Saturation Model): In this model, the presence of conventional free gas and the influence of its saturation on rock physical properties are considered. Free gas affects the porosity, permeability, and elastic wave velocity of rocks, and these effects are described by the Gassmann equation and the equivalent medium theory.

[0144] Step 3: Generate synthetic seismic data:

[0145] Generate two sets of synthetic seismic data according to Model A and Model B.

[0146] 1) In this step, the KL-3DGeoModeler 3D geological modeling technology is used to generate synthetic seismic data. This technology takes non-topological consistent block construction as the core, supports the fusion modeling of profile data, scatter point data, theoretical geometric bodies, and external surface data, effectively improving the success rate of block construction and shortening the modeling cycle.

[0147] 2) According to the changes in sand layer thickness, hydrate saturation, and conventional free gas volume in Model A and Model B, adjust the frequency content of the synthetic seismic data to ensure its matching with the main frequency of the measured seismic data. Through the spectral analysis and frequency band extension technology of seismic data, ensure that the frequency response of the synthetic seismic data matches the measured data, so as to generate synthetic seismic data that conforms to the geological actual situation. This process involves a detailed analysis of the seismic data spectrum and necessary frequency band extension of the synthetic seismic data to achieve the matching with the main frequency of the measured seismic data.

[0148] Step 4: Apply spectral decomposition:

[0149] 1) In this step, perform spectral decomposition on the measured seismic data set and the synthetic seismic data set. Select 15 Hz as the main analysis frequency. This selection is based on the spectral parameters of the seismic data, where the main frequency is the frequency corresponding to the maximum value of the spectrum, and 15 Hz can provide a good balance point to ensure appropriate anti-aliasing while avoiding information redundancy at the high-frequency end.

[0150] 2) Use spectral decomposition technology to extract low-frequency narrow-band data. This technology is based on the discrete Fourier transform (DFT), which converts the seismic signal from the time domain to the frequency domain to generate high-resolution seismic images and identify the lateral distribution of medium properties.

[0151] Step 5: Amplitude extraction and comparison:

[0152] 1) Extract the amplitude from the measured low-frequency data and identify the positive and negative phase characteristics of the amplitude and their dominant positions. This process can be achieved through the phase scanning method, which judges the polarity of the seismic profile by comparing the correlation between the well impedance and the relative impedance inverted from the well-side trace, as well as the phase of the seismic profile.

[0153] 2) Compare the extracted amplitude with the low-frequency data corresponding to the synthetic seismic data. For the regions dominated by positive amplitudes, compare with the synthetic seismic data of Model A; for the regions dominated by negative amplitudes, compare with the synthetic seismic data of Model B. This comparison helps to verify the accuracy of the geological model and identify possible geological anomalies or features.

[0154] Step 6: Identification and Interpretation:

[0155] 1) Identify the presence of gas hydrates and free gas based on the comparison results.

[0156] 2) Determine the saturation and thickness of gas hydrates.

[0157] 3) Determine the distribution and content of conventional free gas.

[0158] Step 7: Verification and Adjustment:

[0159] 1) Verify the exploration results. During the process of verifying the exploration results, the sidewall coring technique is used to obtain core samples. In the coring operation, by using a sidewall corer, it is possible to accurately judge whether the coring is successful and measure the length of the core taken. Between cores, spacers can be inserted to accurately distinguish the horizons of the cores. This technique allows adjusting the key parameters of the instrument according to the formation characteristics, effectively improving the coring efficiency and coring success rate. The sidewall corer adopts a modular structure, facilitating the maintenance and repair of the instrument.

[0160] 2) Adjust the rock physics model and exploration parameters. Based on the core samples obtained from sidewall coring and the verification results, adjust the rock physics model and exploration parameters. This process involves a detailed analysis of the core samples, including the physical properties of the cores such as porosity, permeability, and the elastic parameters of the rock. These parameters will be compared with the seismic data to verify and adjust the rock physics model. The adjustment strategy includes re-evaluating the physical properties of the rock and their correlation with the seismic data according to the core analysis results. By this method, it can be ensured that the adjusted model is more accurate and reliable, providing a scientific basis for the adjustment of exploration parameters. Such adjustments help to optimize the exploration strategy and improve the success rate and efficiency of exploration.

[0161] In summary, the present invention proposes to use a rock physics model to simulate and predict the seismic response of natural gas hydrates. This method can help to more accurately identify and quantify the distribution of natural gas hydrates. By establishing a geological model and a physical parameter model, synthetic seismic data can be generated, which are used to simulate the response of natural gas hydrates that may appear in actual seismic data. The invention mentions the use of spectral decomposition technology to analyze seismic data, which helps to identify specific frequency characteristics related to natural gas hydrates. By comparing the measured seismic data with the synthetic seismic data, the presence and characteristics of natural gas hydrates and associated free gas can be identified. The goal of this technology is to improve the success rate and efficiency of natural gas hydrate exploration through more precise identification and quantification methods. Generally speaking, the background of this technology is to develop new exploration and characterization methods in the context of global energy demand to address the challenges in natural gas hydrate exploration and achieve the effective utilization of this potential energy resource.

[0162] Compared with the prior art, the present invention has at least the following beneficial effects:

[0163] 1) Improving the accuracy of resource assessment: More accurately identifying the presence of natural gas hydrates and conventional free gas improves the accuracy of resource assessment.

[0164] 2) Reducing exploration risks: By improving exploration accuracy, the present invention helps to reduce drilling risks and costs.

[0165] 3) Reducing environmental impact: Through more precise exploration methods, the interference and damage to the environment are reduced.

[0166] 4) Improving exploration efficiency: Utilizing computer simulation and automated analysis improves the efficiency of the exploration process.

[0167] 5) Supporting sustainable development: Helping to discover new energy resources and supporting the sustainable development of energy.

[0168] 6) Flexibility of technology application: The method of the present invention can adapt to different geological conditions and exploration environments, and has high flexibility.

[0169] Through its innovative methods and technologies, the present invention not only improves the accuracy and efficiency of natural gas hydrate exploration, but also helps to reduce exploration risks and environmental impact, bringing significant beneficial effects to the field of energy exploration.

[0170] On the other hand, as Figure 9 shown, an identification device 900 for natural gas hydrates and conventional free gas provided by an embodiment of the present invention may include:

[0171] A first module 901, configured to obtain well logging data and measured seismic data of a target exploration area;

[0172] The second module 902 is configured to construct a petrophysical model based on well logging data through a preset layered structure. The layered structure includes a background clay layer and a target sand body layer. The petrophysical model includes a hydrate wedge model and a conventional gas wedge model. A variety of parameter combinations of natural gas hydrates are preset in the target sand body layer of the hydrate wedge model, and a variety of parameter combinations of conventional free gas are preset in the target sand body layer of the conventional gas wedge model.

[0173] The third module 903 is configured to generate synthetic seismic data based on the petrophysical model. The synthetic seismic data includes first synthetic seismic data corresponding to the hydrate wedge model and second synthetic seismic data corresponding to the conventional gas wedge model.

[0174] The fourth module 904 is configured to perform spectral decomposition on the measured seismic data and the synthetic seismic data in sequence to obtain measured low-frequency data and synthetic low-frequency data respectively. The synthetic low-frequency data includes first synthetic low-frequency data corresponding to the hydrate wedge model and second synthetic low-frequency data corresponding to the conventional gas wedge model.

[0175] The fifth module 905 is configured to extract the amplitudes of positive and negative phases from the measured low-frequency data to obtain a positive amplitude and a negative amplitude. The amplitudes are extracted from the first synthetic low-frequency data and the second synthetic low-frequency data in sequence to obtain a hydrate amplitude and a conventional gas amplitude respectively.

[0176] The sixth module 906 is configured to compare and identify the positive amplitude with the hydrate amplitude, and the negative amplitude with the conventional gas amplitude in sequence to obtain the identification results of natural gas hydrates and conventional free gas in the target exploration area.

[0177] In some embodiments, the device may further include:

[0178] A seventh module, configured to obtain sampling data of the target exploration area. The sampling data is collected based on the sidewall coring technology.

[0179] An eighth module, configured to verify the identification results based on the sampling data and adjust the parameters of the petrophysical model according to the results of the verification process.

[0180] The content of the method embodiments of the present invention is applicable to the device embodiments of the present invention. The functions specifically implemented by the device embodiments of the present invention are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above methods.

[0181] On the other hand, the embodiments of the present invention further provide an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the above method for identifying natural gas hydrates and conventional free gas. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0182] It is understandable that the content in the above method embodiments is applicable to the device embodiments herein. The functions specifically implemented by the device embodiments are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0183] As Figure 10 shown, Figure 10 FIG. schematically shows the hardware structure of an electronic device 1000 according to another embodiment. The electronic device 1000 includes:

[0184] A processor 1001, which can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided by the embodiments of the present invention;

[0185] A memory 1002, which can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The memory 1002 can store an operating system and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 1002 and are called by the processor 1001 to execute the network node population optimization method of the embodiments of the present invention;

[0186] An input / output interface 1003, which is used to implement information input and output;

[0187] A communication interface 1004, which is used to implement communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or through wireless means (such as mobile network, WIFI, Bluetooth, etc.);

[0188] A bus 1005, which transmits information between various components of the device (such as the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004);

[0189] Among them, the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004 are communicatively connected to each other inside the device through the bus 1005.

[0190] The embodiments of the electronic device described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0191] The content of the method embodiments of the present invention is applicable to the embodiments of this electronic device. The functions specifically implemented by the embodiments of this electronic device are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method.

[0192] Another aspect of the embodiments of the present invention further provides a computer-readable storage medium. The storage medium stores a program, and the program is executed by a processor to implement the foregoing method.

[0193] It should be noted that the computer-readable medium shown in the embodiments of the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0194] The content of the method embodiments of the present invention is applicable to the embodiments of this computer-readable storage medium. The functions specifically implemented by the embodiments of this computer-readable storage medium are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method.

[0195] The embodiments of the present invention also disclose a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above method.

[0196] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0197] It should be noted that although several modules of devices for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present invention, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0198] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described here can be implemented by software, or can be implemented by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, and the software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on the network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present invention.

[0199] In some alternative embodiments, the functions / operations recited in the block diagrams may not occur in the order presented in the operational illustrations. For example, depending on the functions / operations involved, two blocks shown in succession may actually be executed substantially simultaneously or the blocks may sometimes be executed in reverse order. Additionally, the embodiments presented and described in the flowcharts of the present invention are provided by way of example for the purpose of providing a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are contemplated in which the order of various operations is altered and in which sub-operations described as part of a larger operation are performed independently.

[0200] Furthermore, although the present invention has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It should also be understood that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present invention. Rather, given the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skill of an engineer. Thus, those skilled in the art can implement the present invention as set forth in the claims without undue experimentation. It should also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0201] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention, in essence or the part that contributes to the prior art or part of this technical solution, may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0202] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered as a definable sequence list of executable instructions for implementing logical functions, which can be specifically implemented in any computer-readable medium for use by an instruction execution apparatus, apparatus, or device (such as a computer-based device, a device including a processor, or other devices that can fetch and execute instructions from the instruction execution apparatus, apparatus, or device), or used in combination with these instruction execution apparatuses, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution apparatus, apparatus, or device.

[0203] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, a computer-readable medium can even be paper or other suitable media on which a program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or, if necessary, other suitable processing, and then stored in a computer memory.

[0204] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution apparatus. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0205] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc., means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0206] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the claims and their equivalents.

[0207] The above has specifically described the preferred embodiments of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present invention.

Claims

1. A method for identifying natural gas hydrates and conventional free gas, characterized in that: The following steps are involved: Acquire well logging data and measured seismic data in the target exploration area; the well logging data includes resistivity data, acoustic wave velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data; Based on the logging data, a rock physics model is obtained by constructing a preset layered structure; wherein the layered structure includes a background clay layer and a target sand body layer; the rock physics model includes a hydrate wedge model and a conventional gas wedge model; the target sand body layer of the hydrate wedge model presets natural gas hydrates with multiple parameter combinations, and the target sand body layer of the conventional gas wedge model presets conventional free gas with multiple parameter combinations; Generate synthetic seismic data based on the rock physics model; the synthetic seismic data includes first synthetic seismic data corresponding to the hydrate wedge model and second synthetic seismic data corresponding to the conventional gas wedge model; Performing spectral decomposition on the measured seismic data and the synthetic seismic data in sequence to obtain measured low-frequency data and synthetic low-frequency data correspondingly; the synthetic low-frequency data includes first synthetic low-frequency data corresponding to the hydrate wedge model and second synthetic low-frequency data corresponding to the conventional gas wedge model; Perform amplitude extraction of positive and negative phases on the measured low-frequency data to obtain a positive amplitude and a reverse amplitude; perform amplitude extraction on the first synthetic low-frequency data and the second synthetic low-frequency data in sequence to obtain a hydrate amplitude and a conventional gas amplitude respectively; The forward amplitude and the hydrate amplitude, as well as the reverse amplitude and the conventional gas amplitude are compared and identified in turn to obtain identification results of the natural gas hydrate and conventional free gas in the target exploration area.

2. The method for identifying natural gas hydrate and conventional free gas according to claim 1, characterized in that: The step of obtaining the well logging data and measured seismic data of the target exploration area comprises the following steps: Deploy a well logging system in the target exploration area, and obtain the well logging data of the target exploration area through the well logging system; A seismic source is arranged in the target exploration area, seismic waves are emitted by the seismic source, and then reflection and refraction information of the seismic waves in the target exploration area are recorded by a geophone to obtain the measured seismic data.

3. The method for identifying natural gas hydrate and conventional free gas according to claim 1, characterized in that: The logging data includes resistivity data, acoustic wave velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data; the rock physics model is obtained based on the logging data through a preset layered structure, including the following steps: Determine the properties and distribution information of underground rocks in the target exploration area based on the well logging data; The property and distribution information includes: water content and mineral type determined based on the resistivity data; porosity, lithology and pressure determined based on the acoustic wave velocity data; mud content determined based on the radioactivity data; porosity and fluid type determined based on the electromagnetic data; dynamic information of fluid in the void determined based on the nuclear magnetic resonance data; According to the properties and distribution information and the preset multiple parameter combinations of the natural gas hydrate and the conventional free gas, the rock physics model is constructed based on the layered structure through a preset quantitative theoretical method.

4. The method for identifying natural gas hydrate and conventional free gas according to claim 1, characterized in that: The generating of synthetic seismic data based on the rock physics model comprises the following steps: Based on the rock physics model, generating preliminary synthetic seismic data using three-dimensional geological modeling technology; According to the main frequency of the measured seismic data, the frequency content of the preliminary synthetic seismic data is matched and adjusted by using spectrum analysis and frequency band extension technology to obtain the synthetic seismic data.

5. The method for identifying natural gas hydrate and conventional free gas according to claim 1, characterized in that: The step of extracting the amplitude of the positive and negative phases of the measured low-frequency data to obtain the positive amplitude and the reverse amplitude comprises the following steps: Amplitude data is extracted from the measured low-frequency data using a phase scanning method, and then the positive and negative phase characteristics of the amplitude in the amplitude data and their corresponding dominant positions are identified to obtain the positive amplitude and the reverse amplitude.

6. The method for identifying natural gas hydrate and conventional free gas according to claim 1, characterized in that: The plurality of parameter combinations include a combination of thickness and saturation in a plurality of numerical ranges for the natural gas hydrate and a combination of distribution and content in a plurality of numerical ranges for the conventional free gas; the forward amplitude and the hydrate amplitude, and the reverse amplitude and the conventional gas amplitude are sequentially compared and identified to obtain the identification results of the natural gas hydrate and the conventional free gas in the target exploration area, including the following steps: Performing a first comparison and identification on the forward amplitude and the hydrate amplitude of the hydrate wedge model corresponding to the thickness and saturation in each numerical range, to obtain a first identification result of the thickness and saturation of the natural gas hydrate; A second comparison and identification is performed on the reverse amplitude and the conventional gas amplitude of the conventional gas wedge model corresponding to the distribution and content of each numerical range to obtain a second identification result of the distribution and content of the conventional free gas.

7. The method for identifying natural gas hydrate and conventional free gas according to claim 1, characterized in that: The method further comprises the following steps: Acquiring sampling data of the target exploration area; the sampling data is collected based on the well wall coring technology; The identification result is verified based on the sampling data, and parameters of the rock physics model are adjusted according to the result of the verification.

8. A device for identifying natural gas hydrates and conventional free gas, characterized in that: include: The first module is used to obtain well logging data and measured seismic data in the target exploration area; The logging data includes resistivity data, acoustic wave velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data; The second module is used to obtain a rock physical model based on the logging data through a preset layered structure; wherein the layered structure includes a background clay layer and a target sand body layer; the rock physical model includes a hydrate wedge model and a conventional gas wedge model; the target sand body layer of the hydrate wedge model presets a natural gas hydrate with a plurality of parameter combinations, and the target sand body layer of the conventional gas wedge model presets a conventional free gas with a plurality of parameter combinations; A third module is used to generate synthetic seismic data based on the rock physics model; the synthetic seismic data includes first synthetic seismic data corresponding to the hydrate wedge model and second synthetic seismic data corresponding to the conventional gas wedge model; A fourth module is used to perform spectral decomposition on the measured seismic data and the synthetic seismic data in sequence, and obtain measured low-frequency data and synthetic low-frequency data correspondingly; the synthetic low-frequency data includes first synthetic low-frequency data corresponding to the hydrate wedge model and second synthetic low-frequency data corresponding to the conventional gas wedge model; The fifth module is used to extract the amplitude of the positive and negative phases of the measured low-frequency data to obtain the positive amplitude and the reverse amplitude; perform amplitude extraction on the first synthetic low-frequency data and the second synthetic low-frequency data in sequence to obtain the hydrate amplitude and the conventional gas amplitude respectively; The sixth module is used to compare and identify the forward amplitude and the hydrate amplitude, and the reverse amplitude and the conventional gas amplitude in turn, to obtain the identification results of the natural gas hydrate and conventional free gas in the target exploration area.

9. An electronic device, characterized in that: including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method according to any one of claims 1 to 7.

10. A computer storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

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