CN119667785B

CN119667785B - A method, device and medium for identifying natural gas hydrate and conventional free gas

Info

Publication number: CN119667785B
Application number: CN202510199600.3A
Authority: CN
Inventors: 刘金霖; 吴时国; 万武波; 王昊寅; 任传真
Original assignee: Yazhouwan Innovation Research Institute Of Hainan Institute Of Tropical Oceanography
Current assignee: Yazhouwan Innovation Research Institute Of Hainan Institute Of Tropical Oceanography
Priority date: 2025-02-24
Filing date: 2025-02-24
Publication date: 2025-07-01
Anticipated expiration: 2045-02-24
Also published as: CN119667785A

Abstract

The invention discloses a method, a device and a medium for identifying natural gas hydrate and conventional free gas, which are used for establishing a petrophysical model through the natural gas hydrate and the conventional free gas with various parameter combinations so as to simulate and predict the earthquake response of the natural gas hydrate. The invention aims to improve the success rate and efficiency of natural gas hydrate exploration through a more accurate identification and quantification method, and develops a novel exploration and characterization method aiming at challenges in natural gas hydrate exploration so as to realize effective utilization of potential energy resources.

Description

Method, device and medium for identifying natural gas hydrate and conventional free gas

Technical Field

The invention relates to the technical field of data processing, in particular to a method, a device and a medium for identifying natural gas hydrate and conventional free gas.

Background

With the growth of global energy demand, exploration for new energy resources has become particularly important. Natural gas hydrates have received great attention as a potential energy source. The exploration of natural gas hydrates faces many challenges including its heterogeneous distribution in the subsurface, low density, and difficult to directly observe properties. Traditional exploration methods, such as well logging and seismic exploration, while capable of providing information about subsurface structures and petrophysical properties, have limitations with respect to the direct detection and quantification of natural gas hydrates.

Disclosure of Invention

The present invention aims to solve the problems of the limitations of the related art at least to some extent. Therefore, the invention provides a method, a device and a medium for identifying natural gas hydrate and conventional free gas, which can conveniently identify the natural gas hydrate and the conventional free gas.

In one aspect, the embodiment of the invention provides a method for identifying natural gas hydrate and conventional free gas, which comprises the following steps:

acquiring logging data and actual measurement seismic data of a target exploration area;

The method comprises the steps of obtaining a petrophysical model through construction of a preset lamellar structure based on logging data, wherein the lamellar structure comprises a background clay layer and a target sand layer, the petrophysical model comprises a hydrate wedge-shaped model and a conventional gas wedge-shaped model, the target sand layer of the hydrate wedge-shaped model is preset with natural gas hydrate with various parameter combinations, and the target sand layer of the conventional gas wedge-shaped model is preset with conventional free gas with various parameter combinations;

generating synthetic seismic data based on the petrophysical model, wherein the synthetic seismic data comprises first synthetic seismic data corresponding to a hydrate wedge model and second synthetic seismic data corresponding to a conventional gas wedge model;

sequentially performing frequency spectrum decomposition on the actually measured seismic data and the synthesized seismic data to correspondingly obtain actually measured low-frequency data and synthesized low-frequency data, wherein the synthesized low-frequency data comprises first synthesized low-frequency data corresponding to a hydrate wedge-shaped model and second synthesized low-frequency data corresponding to a conventional gas wedge-shaped model;

the method comprises the steps of carrying out amplitude extraction of positive and negative phases on measured low frequency data to obtain forward amplitude and reverse amplitude, and carrying out amplitude extraction on first synthesized low frequency data and second synthesized low frequency data in sequence to correspondingly obtain hydrate amplitude and conventional gas amplitude;

And sequentially comparing and identifying the forward amplitude with the hydrate amplitude and the reverse amplitude with the conventional gas amplitude to obtain the identification results of natural gas hydrate and conventional free gas in the target exploration area.

Optionally, acquiring logging data and measured seismic data of the target exploration area includes the steps of:

Deploying a logging system in a target exploration area, and acquiring logging data of the target exploration area through the logging system, wherein the logging data comprises resistivity data, sonic velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data;

Arranging a seismic source in a target exploration area, sending out seismic waves through the seismic source, and further recording reflection and refraction information of the seismic waves in the target exploration area by utilizing a detector to obtain actual measurement seismic data.

Optionally, the logging data comprises resistivity data, sonic velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data, and the petrophysical model is constructed by a preset lamellar structure based on the logging data, and comprises the following steps of:

Determining properties and distribution information of subsurface rock of the target exploration area based on the logging data;

wherein the property and distribution information includes water content and mineral type determined based on resistivity data, porosity, lithology and pressure determined based on sonic velocity data, clay content determined based on radioactivity data, porosity and fluid type determined based on electromagnetic data, dynamic information of fluid in the void determined based on nuclear magnetic resonance data;

According to the nature and distribution information and the preset natural gas hydrate and conventional free gas with various parameter combinations, a rock physical model is obtained through a preset quantitative theoretical method based on layered construction.

Optionally, generating synthetic seismic data based on the petrophysical model comprises the steps of:

Based on the petrophysical model, generating preliminary synthetic seismic data by utilizing a three-dimensional geological modeling technology;

And according to the main frequency of the actually measured seismic data, matching and adjusting the frequency content of the primary synthetic seismic data by utilizing a frequency spectrum analysis and frequency band expansion technology to obtain the synthetic seismic data.

Optionally, the method includes the steps of extracting positive and negative phases of amplitude of the actually measured low frequency data to obtain a forward amplitude and a reverse amplitude, and the method includes the following steps:

and extracting amplitude data from the actually measured low-frequency data by using a phase scanning method, and further identifying positive and negative phase characteristics of the amplitude in the amplitude data and corresponding dominant positions of the positive and negative phase characteristics to obtain forward amplitude and reverse amplitude.

Optionally, the multiple parameter combinations comprise the combination of thickness and saturation of a plurality of numerical ranges for the natural gas hydrate and the combination of distribution and content of a plurality of numerical ranges for the conventional free gas, and 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 result of the natural gas hydrate and the conventional free gas of the target exploration area, and the method comprises the following steps:

Performing first comparison and identification on the forward amplitude and the hydrate amplitude of the hydrate wedge-shaped model corresponding to the thickness and the saturation of each numerical range to obtain a first identification result of the thickness and the saturation of the natural gas hydrate;

And performing second comparison and identification on the conventional gas amplitude of the conventional gas wedge-shaped model corresponding to the distribution and the content of each numerical range of the reverse amplitude to obtain a second identification result of the distribution and the content of the conventional free gas.

Optionally, the method further comprises the steps of:

Acquiring sampling data of a target exploration area, wherein the sampling data is acquired based on a side-wall coring technology;

And verifying the identification result based on the sampling data, and adjusting parameters of the petrophysical model according to the verification result.

In another aspect, an embodiment of the present invention provides a device for identifying natural gas hydrate and conventional free gas, including:

the first module is used for acquiring logging data and actual measurement seismic data of a target exploration area;

The system comprises a first module, a second module, a third module, a fourth module, a fifth module, a sixth module and a seventh module, wherein the first module is used for obtaining a petrophysical model through construction of a preset layered structure based on logging data, the layered structure comprises a background clay layer and a target sand layer, the petrophysical model comprises a hydrate wedge model and a conventional gas wedge model, the target sand layer of the hydrate wedge model is preset with natural gas hydrate with various parameter combinations, and the target sand layer of the conventional gas wedge model is preset with conventional free gas with various parameter combinations;

The third module is used for generating synthetic seismic data based on the petrophysical model, wherein the synthetic seismic data comprises first synthetic seismic data corresponding to the hydrate wedge-shaped model and second synthetic seismic data corresponding to the conventional gas wedge-shaped model;

The fourth module is used for sequentially carrying out frequency spectrum decomposition on the actually measured seismic data and the synthesized seismic data to correspondingly obtain actually measured low-frequency data and synthesized low-frequency data, wherein the synthesized low-frequency data comprises first synthesized low-frequency data corresponding to a hydrate wedge-shaped model and second synthesized low-frequency data corresponding to a conventional gas wedge-shaped model;

The fifth module is used for extracting positive and negative phases of amplitude of the actually measured low frequency data to obtain forward amplitude and reverse amplitude, and sequentially extracting the amplitude of the first synthesized low frequency data and the second synthesized low frequency data to correspondingly obtain hydrate amplitude and normal gas amplitude;

and the sixth module is used for sequentially comparing and identifying the forward amplitude with the hydrate amplitude and the reverse amplitude with the conventional gas amplitude to obtain the identification results of the natural gas hydrate and the conventional free gas of the target exploration area.

Optionally, the apparatus further comprises:

The seventh module is used for acquiring sampling data of the target exploration area, wherein the sampling data is acquired based on a side-wall coring technology;

And an eighth module, configured to perform verification processing on the identification result based on the sampling data, and perform parameter adjustment on the petrophysical model according to the result of the verification processing.

On the other hand, the embodiment of the invention provides electronic equipment which comprises a processor and a memory, wherein the memory is used for storing a program, and the processor executes the program to realize the identification method of the natural gas hydrate and the conventional free gas.

In another aspect, embodiments of the present invention provide a computer storage medium in which a processor-executable program is stored, which when executed by a processor is configured to implement the above-described method for identifying natural gas hydrates and conventional free gas.

According to the embodiment of the invention, a petrophysical model is built by acquiring logging data and actual measurement seismic data of a target exploration area and through a preset layered structure based on the logging data, the layered structure comprises a background clay layer and a target sand layer, the petrophysical model comprises a hydrate wedge-shaped model and a conventional gas wedge-shaped model, the target sand layer of the hydrate wedge-shaped model is preset with natural gas hydrate with various parameter combinations, the target sand layer of the conventional gas wedge-shaped model is preset with conventional free gas with various parameter combinations, synthetic seismic data are generated based on the petrophysical model, the synthetic seismic data comprise first synthetic seismic data corresponding to the hydrate wedge-shaped model and second synthetic seismic data corresponding to the conventional gas wedge-shaped model, the actual measurement seismic data and the synthetic seismic data are subjected to frequency spectrum decomposition in sequence, the first synthetic low frequency data corresponding to the hydrate wedge-shaped model and the second synthetic low frequency data corresponding to the conventional gas wedge-shaped model are correspondingly obtained, the synthetic low frequency data comprises the first synthetic low frequency data corresponding to the hydrate wedge-shaped model and the second synthetic low frequency data corresponding to the conventional gas wedge-shaped model, positive and negative amplitude of amplitude is extracted to obtain positive amplitude and negative amplitude, the synthetic low frequency data is obtained, the first amplitude and the reverse amplitude is obtained, the first synthetic low frequency data and the conventional amplitude is sequentially compared with the conventional amplitude, and the natural gas is obtained, and the positive amplitude and negative amplitude is obtained. The invention establishes a petrophysical model through the natural gas hydrate and the conventional free gas with various parameter combinations to realize the simulation and prediction of the seismic response of the natural gas hydrate, analyzes the seismic data by using a frequency spectrum decomposition technology, is favorable for identifying specific frequency characteristics related to the natural gas hydrate, and can identify the existence and the characteristics of the natural gas hydrate and the related free gas by comparing the actual measurement seismic data with the synthetic seismic data. The invention aims to improve the success rate and efficiency of natural gas hydrate exploration through a more accurate identification and quantification method, and develops a new exploration and characterization method aiming at challenges in natural gas hydrate exploration so as to realize effective utilization of potential energy resources.

Drawings

The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate and do not limit the invention.

FIG. 1 is a schematic illustration of one implementation environment for carrying out the identification of natural gas hydrates and conventional free gases provided by an embodiment of the present invention;

FIG. 2 is a schematic flow chart of a method for identifying natural gas hydrate and conventional free gas according to an embodiment of the present invention;

Fig. 3 is a schematic diagram of an unfolding process of step S100 according to an embodiment of the present invention;

fig. 4 is a schematic diagram of an unfolding process of step S200 according to an embodiment of the present invention;

FIG. 5 is a schematic illustration of an example construction of a petrophysical model provided by an embodiment of the present invention;

FIG. 6 is a schematic illustration of another example construction of a petrophysical model provided by an embodiment of the present invention;

fig. 7 is a schematic diagram of an unfolding process of step S300 according to an embodiment of the present invention;

FIG. 8 is a schematic general flow chart of a method for identifying natural gas hydrate and conventional free gas according to an embodiment of the present invention;

FIG. 9 is a schematic structural diagram of a device for identifying natural gas hydrate and conventional free gas according to an embodiment of the present invention;

Fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

It should be noted that although functional block diagrams are depicted as block diagrams, and logical sequences are shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the block diagrams in the system. The terms first/S100, second/S200, and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

It can be understood that the method for identifying natural gas hydrate and conventional free gas provided by the embodiment of the invention can be applied to any computer equipment with data processing and calculating capabilities, and the computer equipment can be various 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 a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs (Content Delivery Network, content distribution networks), basic cloud computing services such as big data and artificial intelligence platforms, and the like. Alternatively, the terminal is a smart phone, a tablet computer, a notebook computer, a desktop computer, or the like, but is not limited thereto.

In order to facilitate understanding of the technical solution of the present invention, first, technical feature proper nouns that may occur in the embodiments of the present invention are explained:

FIG. 1 is a schematic view of an embodiment of the invention. Referring to fig. 1, the implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected through a network in a wireless or wired mode to complete data transmission and exchange.

The server 101 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs (Content Delivery Network, content delivery networks), basic cloud computing services such as big data and artificial intelligent platforms, and the like.

In addition, server 101 may also be a node server in a blockchain network. The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like.

The terminal 102 may be, but is not limited to, a smart phone, tablet, notebook, desktop, smart box, smart watch, etc. The terminal 102 and the server 101 may be directly or indirectly connected through wired or wireless communication, which is not limited in this embodiment of the present invention.

The embodiment of the present invention provides a method for identifying natural gas hydrate and conventional free gas, which is described below by taking an example that the method for identifying natural gas hydrate and conventional free gas is applied to the server 101, based on the implementation environment shown in fig. 1, it will be understood that the method for identifying natural gas hydrate and conventional free gas may also be applied to the terminal 102.

Referring to fig. 2, fig. 2 is a flowchart of a method for identifying a natural gas hydrate and a conventional free gas applied to a server according to an embodiment of the present invention, where an execution body of the method for identifying a natural gas hydrate and a conventional free gas may be any one of the foregoing computer devices (including a server or a terminal). Referring to fig. 2, the method includes the steps of:

S100, acquiring logging data and actual measurement seismic data of a target exploration area;

It should be noted that, in some embodiments, as shown in fig. 3, the step S100 may include the following steps:

s101, deploying a logging system in a target exploration area, and acquiring logging data of the target exploration area through the logging system, wherein the logging data comprise resistivity data, sonic velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data;

For example, in some embodiments, a logging system may be deployed at an offshore platform that lowers a logging instrument into a well via a wireline, recording physical properties of rock with various sensors. These instruments are capable of measuring the resistivity, sonic velocity, radioactivity, electromagnetic properties, and nuclear magnetic resonance properties of the rock to obtain detailed information about the rock and the rock-fill fluid.

S102, arranging a seismic source in a target exploration area, and sending out seismic waves through the seismic source, and further recording reflection and refraction information of the seismic waves in the target exploration area by utilizing a detector to obtain actual measurement seismic data.

Illustratively, in some embodiments, 3D seismic data may be collected in the field by arranging a plurality of detectors and sources. The data helps to generate three-dimensional images of subsurface structures by recording reflection and refraction information of seismic waves in the subsurface, and plays an important role in identifying geologic structures, faults, hydrocarbon reservoir boundaries and the like.

In the well logging process, the following key parameter data are collected, wherein the resistivity data are used for judging the water content and the mineral type of a rock stratum, the sound wave speed data are used for estimating the porosity, lithology and pressure of the stratum, the radioactivity data are used for determining the clay content of the stratum, the electromagnetic data are used for deducing the porosity and the fluid type of the rock, and the nuclear magnetic resonance data are used for acquiring dynamic information of the fluid in the pores of the rock. These data are critical to understanding the nature and distribution of subsurface rock.

S200, constructing and obtaining a petrophysical model through a preset layered structure based on logging data;

The rock physical model comprises a hydrate wedge-shaped model and a conventional gas wedge-shaped model, wherein the target sand layer of the hydrate wedge-shaped model is preset with natural gas hydrate with various parameter combinations, and the target sand layer of the conventional gas wedge-shaped model is preset with conventional free gas with various parameter combinations;

It should be noted that the logging data includes resistivity data, sonic velocity data, radioactivity data, electromagnetic data, and nuclear magnetic resonance data, and in some embodiments, as shown in fig. 4, step S200 may include determining properties and distribution information of the subsurface rock of the target exploration area based on the logging data, where the properties and distribution information includes water content and mineral type determined based on the resistivity data, porosity, lithology, and pressure determined based on the sonic velocity data, clay content determined based on the radioactivity data, porosity and fluid type determined based on the electromagnetic data, dynamic information of the fluid in the void determined based on the nuclear magnetic resonance data, and constructing a petrophysical model based on the layered structure by a preset quantization theory method according to the properties and distribution information and a preset natural gas hydrate and a preset various parameter combination, and a conventional free gas, S202.

For example, in some embodiments, the velocity-density-thickness model may be built using logging data. Physical parameters of the background clay layer and the target sand layer are determined.

It is assumed that the target sand layer is filled with water, based on physical parameters of the water. In establishing the velocity-density-thickness model and determining the physical parameters of the background clay layer and the target sand layer, the following theoretical and empirical formulas are mainly based:

biot theory, a theory describing elastic wave propagation in saturated porous media. In the interpretation of well logging data, the Biot theory is used to explain the propagation characteristics of acoustic waves in fluid-containing rock, especially in three-phase media (rock framework, hydrate, pore fluids) when the presence of natural gas hydrate is considered.

Wherein, the Is the velocity of the fast and slow longitudinal waves,Is the attenuation coefficient of the fast longitudinal wave and the slow longitudinal wave,Is the velocity of the transverse wave and,Is the attenuation coefficient of the transverse wave,Is the angular frequency of the wave form,AndRepresenting the real and imaginary parts of the complex numbers, respectively.

Gassmann equation, an empirical formula used to describe the change in wave velocity in fluid saturated rock. It can be used to calculate elastic parameters of the rock after fluid replacement, such as longitudinal and transverse wave velocities. The Gassmann equation is used to describe the change in elastic parameters of rock after fluid substitution, and its basic form is:

wherein, the Is the bulk modulus of the dry rock,Is the bulk modulus of the fluid-containing rock,Is the bulk modulus of the fluid and,Porosity.

Equivalent media theory this theory is used to describe the macroscopic physical properties of the multiphase media, such as resistivity and elastic wave velocity, simplifying the calculation by treating the multiphase media as a single equivalent medium.

Through the theory and the method, the influence of natural gas hydrate and conventional free gas on the physical properties of rock under different saturation conditions can be quantitatively analyzed and predicted, so that scientific basis is provided for geological exploration and resource evaluation.

Further, constructing two of the petrophysical models can be accomplished as follows:

Model a assuming different levels (thickness and saturation) of natural gas hydrate in the target sand layer. As shown in fig. 5, a schematic diagram of a construction example of the model a is shown (the example is shown in fig. 5 by the percentage content of hydrate, and the model a can be adjusted according to the requirement in practical application).

Model B assuming different levels (distribution and content) of conventional free gas in the target sand layer. As shown in fig. 6, a schematic diagram of a construction example of the model B is shown (the conventional gas percentage content is shown in fig. 6, and the model B can be adjusted according to the requirement in practical application).

In constructing models a and B, the effect of different saturations of natural gas hydrate and conventional free gas on petrophysical properties is considered mainly by:

model a (natural gas hydrate saturation model, i.e., hydrate wedge model) in which the effect of hydrate morphology, distribution and saturation on petrophysical properties is taken into account. The presence of hydrates affects the elastic properties and fluid flow properties of rock, as quantified by the Biot theory and equivalent media theory.

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 the petrophysical properties is taken into account. Free gas affects the porosity, permeability and elastic wave velocity of the rock, which are described by the Gassmann equation and equivalent media theory.

S300, generating synthetic seismic data based on a petrophysical model;

The synthetic seismic data comprises first synthetic seismic data corresponding to a hydrate wedge-shaped model and second synthetic seismic data corresponding to a conventional gas wedge-shaped model;

It should be noted that, in some embodiments, as shown in fig. 7, step S300 may include the steps of generating preliminary synthetic seismic data by using a three-dimensional geologic modeling technique based on a petrophysical model, and performing matching adjustment on frequency content of the preliminary synthetic seismic data by using a spectrum analysis and a band expansion technique according to a main frequency of the measured seismic data, to obtain the synthetic seismic data, in S301.

Illustratively, in some embodiments, first, the KL-3DGeoModeler three-dimensional geologic modeling technique may be utilized to generate synthetic seismic data. The technology takes the non-topological consistency block construction as a core, supports the fusion modeling of the section data, the scattered point data, the theoretical geometry and the external layer data, effectively improves the block construction success rate and shortens the modeling period.

Furthermore, the frequency content of the synthetic seismic data can be adjusted according to the thickness of the sand layer, the saturation of the hydrate and the change of the conventional free air quantity in the model A and the model B so as to ensure that the frequency content is matched with the main frequency of the measured seismic data. Through the spectrum analysis and the frequency band expansion technology of the seismic data, the frequency response of the synthetic seismic data is ensured to be matched with the measured data, so that the synthetic seismic data which accords with the actual geological situation is generated. This process involves detailed analysis of the spectrum of the seismic data and the necessary band expansion of the synthetic seismic data to achieve a match with the dominant frequency of the measured seismic data.

S400, sequentially performing spectrum decomposition on the actually measured seismic data and the synthesized seismic data to correspondingly obtain actually measured low-frequency data and synthesized low-frequency data;

The synthesized low frequency data comprises first synthesized low frequency data corresponding to a hydrate wedge-shaped model and second synthesized low frequency data corresponding to a conventional gas wedge-shaped model, and specifically, the spectrum decomposition is realized through discrete Fourier transform based on a preset main analysis frequency;

Illustratively, in some embodiments, applying spectral decomposition may be accomplished as follows:

1) In this step, spectral decomposition is performed on the measured seismic dataset and the synthetic seismic dataset. For example, 15Hz may be chosen as the primary analysis frequency, this choice being based on the spectral parameters of the seismic data, where the primary frequency is the frequency corresponding to the spectral maxima, and 15Hz can provide a good balance point, ensuring proper anti-aliasing while avoiding information redundancy at the high frequency side.

2) The low frequency narrowband data is extracted using spectral decomposition techniques. This technique is based on Discrete Fourier Transforms (DFT) that convert the seismic signals from the time domain to the frequency domain to generate a high resolution seismic image and identify the lateral distribution of the media properties.

S500, carrying out positive and negative phase amplitude extraction on the actually measured low frequency data to obtain a forward amplitude and a reverse amplitude;

It should be noted that, in some embodiments, the step S500 may include the steps of extracting the amplitude data from the actually measured low frequency data by using a phase scanning method, so as to identify positive and negative phase characteristics of the amplitude in the amplitude data and corresponding dominant positions thereof, and obtain the forward amplitude and the reverse amplitude.

For example, in some embodiments, the amplitude may be extracted from the measured low frequency data, identifying the positive and negative phase characteristics of the amplitude and its dominance. This can be accomplished by a phase sweep method that determines the polarity of the seismic profile by comparing the correlation of the well impedance with the relative impedance of the well bypass inversion, and the phase of the seismic profile. In addition, the amplitude extraction for the hydrate amplitude and the conventional gas amplitude can be implemented by adopting a conventional amplitude extraction mode, and a detailed description is omitted here.

S600, sequentially comparing and identifying the forward amplitude with the hydrate amplitude and the reverse amplitude with the conventional gas amplitude to obtain the identification results of the natural gas hydrate and the conventional free gas of the target exploration area.

It should be noted that the various parameter combinations include a combination of thickness and saturation of a plurality of numerical ranges for the natural gas hydrate and a combination of distribution and content of a plurality of numerical ranges for the conventional free gas, and in some embodiments, the step S600 may include a step of performing a first comparison and identification of the forward amplitude and the hydrate amplitude of the hydrate wedge model corresponding to the thickness and saturation of each numerical range to obtain a first identification result of the thickness and saturation of the natural gas hydrate, and a step of performing a second comparison and identification of 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.

Illustratively, in some embodiments, the extracted amplitude is compared to amplitude data corresponding to synthetic seismic data. For the region where positive amplitude (i.e., positive amplitude) is dominant, amplitude data corresponding to the synthetic seismic data of model a is compared, and for the region where negative amplitude (i.e., negative amplitude) is dominant, amplitude data corresponding to the synthetic seismic data of model B is compared. Such comparison helps to verify the accuracy of the geologic model and identify possible geologic anomalies or features. Further, the presence of natural gas hydrate and free gas and the data thereof are identified based on the comparison result. Specifically, taking the model a shown in fig. 5 as an example, similarity determination is performed on amplitude data corresponding to synthetic seismic data obtained by different hydrate contents in the model a, so as to determine a recognition result of the natural gas hydrate in the target exploration area according to the hydrate content corresponding to the highest similarity.

In some embodiments, the method may further include the steps of obtaining sample data of the target exploration area, the sample data being obtained based on a side-wall coring technique, validating the identification based on the sample data, and parameter adjusting the petrophysical model based on the validation.

Illustratively, in some embodiments, assuming that 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 the plurality of parameter combinations of the setting of the petrophysical model may be correspondingly adjusted according to the verified gap size (the greater the gap, the greater the distribution density setting).

In some specific application scenarios, the verification and adjustment may be implemented as follows:

1) And verifying the exploration result. In validating the exploration results, a side-wall coring technique is used to obtain core samples. In the coring operation, whether coring is successful or not can be accurately judged by using a sidewall coring device, and the length of the obtained core is measured. Spacer can be inserted between the cores to accurately distinguish the horizons of the cores. The technique allows the key parameters of the instrument to be adjusted according to the stratum characteristics, and effectively improves the coring efficiency and the coring success rate. The side-wall coring device adopts a modularized structure, thereby being convenient for the maintenance of the instrument.

2) And adjusting the petrophysical model and the exploration parameters. And adjusting the rock physical model and the exploration parameters according to the core sample obtained by the side-wall coring and the verification result. This process involves detailed analysis of the core sample, including physical properties of the core such as porosity, permeability and elastic parameters of the rock. These parameters will be compared to the seismic data to verify and adjust the petrophysical model. The adjustment strategy includes re-evaluating the physical properties of the rock, and their correlation with the seismic data, based on the core analysis results. By the method, the adjusted model can be ensured to be more accurate and reliable, and scientific basis is provided for adjustment of exploration parameters. Such adjustment helps to optimize the exploration strategy and improve the success rate and efficiency of exploration.

For the purpose of illustrating the principles of the present invention in detail, the following general flow chart of the present invention is described in connection with certain specific embodiments, and it is to be understood that the following is illustrative of the principles of the present invention and is not to be construed as limiting the present invention.

Firstly, the invention can realize the exploration of the natural gas hydrate by the following steps:

1) Building a petrophysical model:

The velocity-density-thickness model of the background clay and target sand is built using well log data (such as gamma rays, resistivity, sonic velocity and density) to accurately model the geologic structure.

2) Generating synthetic seismic data:

Two sets of combined seismic data are generated according to the geological model, wherein one set represents pure natural gas hydrate, and the other set represents free gas under the natural gas hydrate. Synthetic seismic data is generated by simulating different geological conditions (such as changes in sand thickness, hydrate saturation and free gas content).

3) Spectral decomposition is applied:

The measured seismic data and the synthetic seismic data are subjected to frequency spectrum decomposition, and low-frequency narrow-band data are extracted to highlight specific seismic characteristics related to natural gas hydrate and free gas.

4) Amplitude extraction and comparison:

Amplitude is extracted from the measured seismic data and compared to the synthetic seismic data. Including identifying positive and negative phase characteristics of the amplitude and its dominance to distinguish between different types of geologic structures.

As shown in fig. 8, the method of the present invention specifically may include the following steps:

step 1, data collection:

1) Offshore platform logging system:

A logging system is deployed on an offshore platform that lowers the logging instrument into the well via a cable, recording the physical properties of the rock using a variety of sensors. These instruments are capable of measuring the resistivity, sonic velocity, radioactivity, electromagnetic properties, and nuclear magnetic resonance properties of the rock to obtain detailed information about the rock and the rock-fill fluid.

2) Collecting logging data:

During the well logging process, the following key parameter data are collected, namely resistivity data are used for judging the water content and mineral type of the rock stratum, sonic velocity data are used for estimating the porosity, lithology and pressure of the stratum, radioactivity data are used for determining the clay content of the stratum, electromagnetic data are used for deducing the porosity and fluid type of the rock, and nuclear magnetic resonance data are used for acquiring dynamic information of fluid in the pores of the rock. These data are critical to understanding the nature and distribution of subsurface rock.

3) Collecting a measured seismic dataset:

in the field, 3D seismic data is collected by arranging a plurality of detectors and sources. The data helps to generate three-dimensional images of subsurface structures by recording reflection and refraction information of seismic waves in the subsurface, and plays an important role in identifying geologic structures, faults, hydrocarbon reservoir boundaries and the like.

Wherein, the technical requirements and operation specifications are as follows:

During data collection, stringent specifications and operating specifications will be followed, including selection of appropriate instrumentation and periodic calibration to ensure accuracy and reliability of data acquisition. Meanwhile, various index data are accurately collected, the consistency of time and space is noted, and the continuity and the integrity of the data are ensured. In addition, the geological structure, the landform, the soil property and the like of the target area are recorded and observed in detail, and the information of the sample number, the sampling depth, the sampling horizon and the like is well saved. The data processing comprises links such as data arrangement, data analysis, data interpretation and the like so as to ensure the reliability and the effectiveness of the exploration result. All personnel engaged in geological exploration work must be educated and trained through safety consciousness, know relevant safety regulations, familiarize with operating regulations and master necessary safety skills.

Step 2, building a rock physical model

1) A velocity-density-thickness model is built using the log data. Physical parameters of the background clay layer and the target sand layer are determined.

It is assumed that the target sand layer is filled with water, based on physical parameters of the water. The physical parameters of the background clay layer and the target sand layer are mainly based on the Biot theory, gassmann equation and equivalent medium theory (the specific principle logic refers to the foregoing detailed description and is not repeated here) when the speed-density-thickness model is established and the physical parameters of the background clay layer and the target sand layer are determined.

2) Two models were constructed:

model a assuming the presence of natural gas hydrates of different thickness and saturation in the target sand layer.

Model B assuming different distributions and contents of conventional free gas in the target sand layer.

Model a (natural gas hydrate saturation model) in which the effect of hydrate morphology, distribution and saturation on petrophysical properties is taken into account. The presence of hydrates affects the elastic properties and fluid flow properties of rock, as quantified by the Biot theory and equivalent media theory.

Model B (conventional free gas saturation model) in this model the effect of the presence and saturation of conventional free gas on petrophysical properties is taken into account. Free gas affects the porosity, permeability and elastic wave velocity of the rock, which are described by the Gassmann equation and equivalent media theory.

Step 3, generating synthetic seismic data:

and generating two groups of combined seismic data according to the model A and the model B.

1) In this step, the synthetic seismic data is generated using a KL-3DGeoModeler three-dimensional geologic modeling technique. The technology takes the non-topological consistency block construction as a core, supports the fusion modeling of the section data, the scattered point data, the theoretical geometry and the external layer data, effectively improves the block construction success rate and shortens the modeling period.

2) And adjusting the frequency content of the synthetic seismic data according to the thickness of the sand layer, the saturation of the hydrate and the change of the conventional free air quantity in the model A and the model B so as to ensure that the frequency content of the synthetic seismic data is matched with the main frequency of the measured seismic data. Through the spectrum analysis and the frequency band expansion technology of the seismic data, the frequency response of the synthetic seismic data is ensured to be matched with the measured data, so that the synthetic seismic data which accords with the actual geological situation is generated. This process involves detailed analysis of the spectrum of the seismic data and the necessary band expansion of the synthetic seismic data to achieve a match with the dominant frequency of the measured seismic data.

And 4, applying spectrum decomposition:

1) In this step, spectral decomposition is performed on the measured seismic dataset and the synthetic seismic dataset. 15 Hz is selected as the primary analysis frequency, which is based on the spectral parameters of the seismic data, where the primary frequency is the frequency corresponding to the spectral maxima, while 15 Hz provides a good balance point, ensuring proper anti-aliasing while avoiding information redundancy at the high frequency side.

And 5, amplitude extraction and comparison:

1) And extracting the amplitude from the actually measured low-frequency data, and identifying positive and negative phase characteristics and dominant positions of the amplitude. This can be accomplished by a phase sweep method that determines the polarity of the seismic profile by comparing the correlation of the well impedance with the relative impedance of the well bypass inversion, and the phase of the seismic profile.

2) The extracted amplitude is compared with low frequency data corresponding to the synthetic seismic data. For the region with dominant positive amplitude, it is compared with the synthetic seismic data of model a, and for the region with dominant negative amplitude, it is compared with the synthetic seismic data of model B. Such comparison helps to verify the accuracy of the geologic model and identify possible geologic anomalies or features.

Step 6, identifying and explaining:

1) Based on the comparison, the presence of natural gas hydrates and free gas is identified.

2) The saturation and thickness of the natural gas hydrate are determined.

3) The distribution and content of conventional free gas was determined.

And 7, verifying and adjusting:

In summary, the present invention proposes the use of petrophysical models to simulate and predict the seismic response of natural gas hydrates. This approach may help to more accurately identify and quantify the distribution of natural gas hydrates. By modeling geologic and physical parameters, synthetic seismic data may be generated that is used to simulate the response of natural gas hydrates that may occur in actual seismic data. The invention mentions the use of spectral decomposition techniques to analyze seismic data, which helps identify specific frequency characteristics associated with natural gas hydrates. By comparing the measured seismic data with the synthetic seismic data, the presence and nature of natural gas hydrates and associated free gases can be identified. The aim of the technology is to improve the success rate and efficiency of natural gas hydrate exploration through a more accurate identification and quantification method. In general, the background of this technology is the development of new exploration and characterization methods for challenges in natural gas hydrate exploration in the context of global energy demand to achieve efficient utilization of such potential energy resources.

Compared with the prior art, the invention at least has the following beneficial effects:

1) The method improves the accuracy of resource assessment, namely more accurately identifies the existence of natural gas hydrate and conventional free gas, and improves the accuracy of resource assessment.

2) The invention helps to reduce drilling risk and cost by improving exploration accuracy.

3) Reduction of environmental impact by more accurate exploration methods, interference and damage to the environment is reduced.

4) The exploration efficiency is improved by utilizing computer simulation and automatic analysis.

5) Support sustainable development, help discover new energy resources, support sustainable development of energy.

6) Flexibility of technical application the method of the invention can be adapted to different geological conditions and exploration environments, and has high flexibility.

The method and the technology of the invention not only improve the accuracy and the efficiency of natural gas hydrate exploration, but also help to reduce the exploration risk and the environmental impact, and bring remarkable beneficial effects to the field of energy exploration.

In another aspect, as shown in fig. 9, an embodiment of the present invention provides a device 900 for identifying natural gas hydrate and conventional free gas, which may include:

a first module 901, configured to acquire logging data and measured seismic data of a target exploration area;

A second module 902, configured to construct a petrophysical model through a preset layered structure based on the logging data; the rock physical model comprises a hydrate wedge-shaped model and a conventional gas wedge-shaped model, wherein the target sand layer of the hydrate wedge-shaped model is preset with natural gas hydrate with various parameter combinations, and the target sand layer of the conventional gas wedge-shaped model is preset with conventional free gas with various parameter combinations;

A third module 903 for generating synthetic seismic data based on the petrophysical model, the synthetic seismic data including 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 904, configured to sequentially perform spectral decomposition on the actually measured seismic data and the synthesized seismic data to correspondingly obtain actually measured low frequency data and synthesized low frequency data, where the synthesized low frequency data includes first synthesized low frequency data corresponding to a hydrate wedge model and second synthesized low frequency data corresponding to a conventional gas wedge model;

A fifth module 905, configured to perform positive and negative phase amplitude extraction on the actually measured low frequency data to obtain a forward amplitude and a reverse amplitude;

And a sixth module 906, configured to sequentially compare and identify the forward amplitude with the hydrate amplitude, and the reverse amplitude with the regular gas amplitude, so as to obtain an identification result of natural gas hydrate and regular free gas in the target exploration area.

In some embodiments, the apparatus may further include:

The content of the method embodiment of the invention is suitable for the device embodiment, the specific function of the device embodiment is the same as that of the method embodiment, and the achieved beneficial effects are the same as those of the method.

On the other hand, the embodiment of the invention also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the identification method of the natural gas hydrate and the conventional free gas when executing the computer program. The electronic equipment can be any intelligent terminal including a tablet personal computer, a vehicle-mounted computer and the like.

It can be understood that the content in the above method embodiment is applicable to the embodiment of the present apparatus, and the specific functions implemented by the embodiment of the present apparatus are the same as those of the embodiment of the above method, and the achieved beneficial effects are the same as those of the embodiment of the above method.

As shown in fig. 10, fig. 10 illustrates a hardware structure of an electronic device 1000 of another embodiment, and the electronic device 1000 includes:

The processor 1001 may be implemented by using a general purpose CPU (Central Processing Unit ), a microprocessor, an application specific integrated Circuit (application SPECIFIC INTEGRATED Circuit, aSIC), or one or more integrated circuits, etc. to execute related programs to implement the technical solutions provided by the embodiments of the present invention;

The Memory 1002 may be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a random access Memory (Random access Memory, raM). The memory 1002 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present disclosure are implemented by software or firmware, relevant program codes are stored in the memory 1002, and the processor 1001 invokes a network node population optimization method for executing the embodiments of the present disclosure;

an input/output interface 1003 for implementing information input and output;

The communication interface 1004 is configured to implement communication interaction between the present device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.);

A bus 1005 for transferring information between the various components of the device (e.g., the processor 1001, memory 1002, input/output interface 1003, and communication interface 1004);

Wherein the processor 1001, the memory 1002, the input/output interface 1003, and the communication interface 1004 realize communication connection between each other inside the device through the bus 1005.

The above described embodiments of the electronic device are merely illustrative, wherein the units described as separate components may or may not be physically separate, i.e. may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The content of the method embodiment of the invention is suitable for the electronic equipment embodiment, the functions of the electronic equipment embodiment are the same as those of the method embodiment, and the achieved beneficial effects are the same as those of the method.

Another aspect of the embodiments of the present invention also provides a computer-readable storage medium storing a program that is executed by a processor to implement the foregoing method.

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. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), a flash Memory, an optical fiber, a portable compact disc read-Only Memory (Compact Disc Read to Only Memory, CD to ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, etc., or any suitable combination of the foregoing.

The content of the method embodiment of the invention is applicable to the computer readable storage medium embodiment, the functions of the computer readable storage medium embodiment are the same as those of the method embodiment, and the achieved beneficial effects are the same as those of the method.

Embodiments of the present invention also disclose a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions may be read from a computer-readable storage medium by a processor of a computer device, and executed by the processor, to cause the computer device to perform the foregoing method.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations 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 diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It should be noted that although in the above detailed description several modules of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the invention. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.

From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present invention may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD to ROM, a U-disc, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the method according to the embodiments of the present invention.

In some alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed, and in which sub-operations described as part of a larger operation are performed independently.

Furthermore, while the invention is described in the context of functional modules, it should be appreciated that, unless otherwise indicated, one or more of the functions and/or features may be integrated in a single physical device and/or software module or may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be apparent to those skilled in the art from consideration of their attributes, functions and internal relationships. Accordingly, one of ordinary skill in the art can implement the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative and are not intended to be limiting upon the scope of the invention, which is to be defined in the appended claims and their full scope of equivalents.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present invention. The storage medium includes a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random-access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes.

Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution apparatus, device, or apparatus, such as a computer-based apparatus, processor-containing apparatus, or other apparatus that can fetch the instructions from the instruction execution apparatus, device, or apparatus and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution apparatus, device, or apparatus.

More specific examples (a non-exhaustive list) of the computer-readable medium would include an electrical connection (an electronic device) having one or more wires, a portable computer diskette (a 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, the computer-readable medium may even be paper or other suitable medium upon which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of techniques known in the art, discrete logic circuits with logic gates for implementing logic functions on data signals, application specific integrated circuits with appropriate combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the spirit and scope of the invention as defined by the appended claims and their equivalents.

While the preferred embodiment of the present invention has been described in detail, the present invention is not limited to the embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and the equivalent modifications or substitutions are intended to be included in the scope of the present invention as defined in the appended claims.

Claims

1. A method for identifying natural gas hydrate and conventional free gas, comprising the steps of:

Logging data and measured seismic data of a target exploration area are obtained, wherein the logging data comprise resistivity data, sonic velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data;

The method comprises the steps of obtaining logging data, constructing a petrophysical model through a preset lamellar structure based on the logging data, wherein the lamellar structure comprises a background clay layer and a target sand layer, the petrophysical model comprises a hydrate wedge-shaped model and a conventional gas wedge-shaped model, the target sand layer of the hydrate wedge-shaped model is preset with natural gas hydrate with various parameter combinations, and the target sand layer of the conventional gas wedge-shaped model is preset with conventional free gas with various parameter combinations;

Generating synthetic seismic data based on the petrophysical model, wherein the synthetic seismic data comprises first synthetic seismic data corresponding to the hydrate wedge model and second synthetic seismic data corresponding to the conventional gas wedge model;

Sequentially performing frequency spectrum decomposition on the actually measured seismic data and the synthesized seismic data to correspondingly obtain actually measured low-frequency data and synthesized low-frequency data, wherein the synthesized low-frequency data comprises first synthesized low-frequency data corresponding to the hydrate wedge-shaped model and second synthesized low-frequency data corresponding to the conventional gas wedge-shaped model;

The amplitude extraction of the positive phase and the negative phase is carried out on the actually measured low frequency data to obtain a forward amplitude and a reverse amplitude;

and comparing and identifying the forward amplitude with the hydrate amplitude and the reverse amplitude with the conventional gas amplitude in sequence to obtain the identification result of the natural gas hydrate and the conventional free gas of the target exploration area.

2. The method for identifying natural gas hydrates and conventional free gas as claimed in claim 1, wherein the acquiring of logging data and measured seismic data of a target exploration area comprises the steps of:

deploying a logging system in the target exploration area, and acquiring logging data of the target exploration area through the logging system;

Arranging a seismic source in the target exploration area, sending out seismic waves through the seismic source, and further recording reflection and refraction information of the seismic waves in the target exploration area by using a detector to obtain the actually measured seismic data.

3. The method for identifying natural gas hydrate and conventional free gas according to claim 1, wherein the logging data comprises resistivity data, sonic velocity data, radioactivity data, electromagnetic data and nuclear magnetic resonance data, and the rock physical model is constructed by a preset lamellar structure based on the logging data, and comprises the following steps:

determining properties and distribution information of subsurface rock of the target survey area based on the well log data;

wherein 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 sonic velocity data, clay 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;

And constructing the petrophysical model based on the layered structure through a preset quantitative theoretical method according to the property and distribution information and the preset natural gas hydrate and the conventional free gas of the various parameter combinations.

4. The method of identifying natural gas hydrates and conventional free gas as set forth in claim 1, wherein the generating synthetic seismic data based on the petrophysical model comprises the steps of:

5. The method for identifying natural gas hydrate and conventional free gas according to claim 1, wherein the step of extracting positive and negative phase amplitudes of the measured low frequency data to obtain a forward amplitude and a reverse amplitude comprises the steps of:

And extracting amplitude data from the actually measured low-frequency data by using a phase scanning method, and further identifying positive and negative phase characteristics of the amplitude in the amplitude data and corresponding predominance thereof to obtain the forward amplitude and the reverse amplitude.

6. The method for identifying natural gas hydrate and conventional free gas according to claim 1, wherein the plurality of parameter combinations include combinations of thickness and saturation for a plurality of numerical ranges of the natural gas hydrate and combinations of distribution and content for a plurality of numerical ranges of the conventional free gas, and wherein the sequentially comparing and identifying the forward amplitude with the hydrate amplitude and the reverse amplitude with the conventional gas amplitude results in identification of natural gas hydrate and conventional free gas for the target exploration area comprises the following steps:

7. The method of identifying natural gas hydrates and conventional free gas of claim 1, further comprising the steps of:

acquiring sampling data of the target exploration area, wherein the sampling data is acquired based on a side-wall coring technology;

And verifying the identification result based on the sampling data, and performing parameter adjustment on the petrophysical model according to the result of the verification process.

8. A natural gas hydrate and conventional free gas identification device, comprising:

the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring logging data and measured seismic data of a target exploration area, and the logging data comprise resistivity data, sound wave speed data, radioactivity data, electromagnetic data and nuclear magnetic resonance data;

The system comprises a logging module, a second module, a first module, a second module, a third module, a fourth module, a fifth module and a sixth module, wherein the logging module is used for acquiring a petrophysical model through a preset lamellar structure based on the logging data, the lamellar structure comprises a background clay layer and a target sand layer, the petrophysical model comprises a hydrate wedge-shaped model and a conventional gas wedge-shaped model, the target sand layer of the hydrate wedge-shaped model is preset with natural gas hydrate with various parameter combinations, and the target sand layer of the conventional gas wedge-shaped model is preset with conventional free gas with various parameter combinations;

the fourth module is used for sequentially carrying out frequency spectrum decomposition on the actually measured seismic data and the synthesized seismic data to correspondingly obtain actually measured low-frequency data and synthesized low-frequency data, wherein the synthesized low-frequency data comprises first synthesized low-frequency data corresponding to the hydrate wedge-shaped model and second synthesized low-frequency data corresponding to the conventional gas wedge-shaped model;

The fifth module is used for extracting positive and negative phases of amplitude of the actually measured low-frequency data to obtain forward amplitude and reverse amplitude, and sequentially extracting the amplitude of the first synthesized low-frequency data and the second synthesized low-frequency data to correspondingly obtain hydrate amplitude and normal gas amplitude;

and a sixth module, configured to sequentially compare and identify the forward amplitude with the hydrate amplitude, and the reverse amplitude with the regular gas amplitude, so as to obtain an identification result of natural gas hydrate and regular free gas in the target exploration area.

9. An electronic device comprising a processor and a memory;

The memory is used for storing programs;

The processor executing the program implements the method of any one of claims 1 to 7.

10. A computer storage medium in which a processor executable program is stored, characterized in that the processor executable program is for implementing the method according to any one of claims 1 to 7 when being executed by the processor.