Ultra-deep geological structure recognition method, device and equipment and storage medium

Abstract

The invention provides a recognition method, device and equipment for an ultra-deep geological structure and a storage medium, and belongs to the technical field of oil-gas exploration, and the recognition method comprises the steps: obtaining active source seismic record data and passive source seismic record data of a target block; performing imaging processing on the active source seismic record data to obtain an active seismic source signal imaging data body; performing imaging processing on the passive source seismic record data to obtain a passive source signal imaging data body; and based on the active seismic source signal imaging data volume and the passive seismic source signal imaging data volume, carrying out joint identification on the ultra-deep geological structure to obtain an identification result of the ultra-deep geological structure. Through the method provided by the invention, multiplicity of solutions generated when the ultra-deep geologic body is identified based on the active source exploration data can be reduced, and the ultra-deep geologic structure can be effectively identified.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration technology, specifically to a method for identifying ultra-deep geological structures, a device for identifying ultra-deep geological structures, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Seismic exploration is one of the most important means of achieving large-scale discoveries of oil and gas resources. With the advancement of seismic exploration technology, the exploration targets of oil and gas reservoirs are rapidly moving towards the deep and ultra-deep realms, which poses a severe challenge to seismic exploration technology.

[0003] Currently, oil and gas reservoir exploration mainly relies on artificial active source seismic exploration technology. This involves surveying subsurface targets, recording signals, and processing images to ultimately obtain information on the subsurface distribution of oil and gas. However, due to the limited explosive energy generated by active source seismic events, the wavefield analysis during signal processing becomes increasingly complex and the ambiguity increases with deeper strata, making it difficult to effectively identify ultra-deep geological structures.

[0004] Although there are a large number of passive source seismic signals in nature that can acquire information about large-scale underground structures, these passive source seismic signals mainly come from natural earthquakes, environmental noise, and traffic noise. They often lack the low-frequency information required for high-precision modeling and cannot achieve high-resolution imaging effects and oil and gas reservoir exploration targets.

[0005] This shows that the data generated by single-source earthquakes are limited in terms of quality and frequency band, which restricts the technical advantages that seismic exploration should have in detecting ultra-deep underground structures. Summary of the Invention

[0006] To address the technical problem that the data excited by a single type of seismic source in the existing technology is limited in terms of quality and frequency band, which restricts the prediction accuracy and precision of ultra-deep (e.g., depths above 5000m) underground structures, this invention provides a method for identifying ultra-deep geological structures. This method can reduce the ambiguity generated when identifying ultra-deep geological bodies based on active source exploration data and effectively identify ultra-deep geological structures.

[0007] To achieve the above objectives, the first aspect of the present invention provides a method for identifying ultra-deep geological structures. The method includes the following steps: acquiring active source seismic record data and passive source seismic record data of a target block; performing imaging processing on the active source seismic record data to obtain an active source signal imaging data volume; performing imaging processing on the passive source seismic record data to obtain a passive source signal imaging data volume; and jointly identifying the ultra-deep geological structure based on the active source signal imaging data volume and the passive source signal imaging data volume to obtain the identification result of the ultra-deep geological structure.

[0008] In an exemplary embodiment of the present invention, the joint identification of ultra-deep geological structures based on active source signal imaging data and passive source signal imaging data to obtain identification results of ultra-deep geological structures may include: using active source signal imaging data and passive source signal imaging data to compare and interpret ultra-deep geological structures and identify the boundaries of ultra-deep geological structures; and identifying the internal detailed structure of ultra-deep geological structures based on active source signal imaging data.

[0009] In an exemplary embodiment of the present invention, the step of comparing and interpreting ultra-deep geological structures using active source signal imaging data and passive source signal imaging data to identify the boundaries of ultra-deep geological structures may include: interpreting multiple waves appearing in the active source signal imaging data to obtain a first stratigraphic boundary interpretation result; interpreting the passive source signal imaging data at a specified spatial location to obtain a second stratigraphic boundary interpretation result, wherein the specified spatial location is the spatial location corresponding to the multiple waves appearing in the active source signal imaging data; determining whether the first stratigraphic boundary interpretation result is the same as the second stratigraphic boundary interpretation result; and, if it is determined that the first stratigraphic boundary interpretation result is the same as the second stratigraphic boundary interpretation result, outputting the first stratigraphic boundary interpretation result as the boundary identification result of the ultra-deep geological structure.

[0010] In an exemplary embodiment of the present invention, the step of imaging processing of passive source seismic record data to obtain passive source signal imaging data volume may include: performing cross-correlation calculation on continuous-time signals between different stations to obtain a background noise cross-correlation signal; using a double-beam imaging method to superimpose the energy coherence portion of the background noise cross-correlation signal to obtain a superimposed seismic wave signal; extracting an empirical Green's function based on the superimposed seismic wave signal; and using the extracted empirical Green's function to perform imaging processing on the subsurface medium structure to obtain a passive source signal imaging data volume.

[0011] In an exemplary embodiment of the present invention, the step of performing imaging processing on passive source seismic record data to obtain passive source signal imaging data volume may further include: preprocessing the passive source seismic record data before performing cross-correlation calculation to obtain preprocessed passive source seismic record data.

[0012] In an exemplary embodiment of the present invention, the preprocessing may include at least one of noise interference removal processing, time-domain normalization, and frequency-domain normalization.

[0013] In an exemplary embodiment of the present invention, the acquisition path of the active source seismic record data may be the same as that of the passive source seismic record data.

[0014] In an exemplary embodiment of the present invention, the detection depth of the ultra-deep geological structure is 5000m or more.

[0015] A second aspect of the present invention provides an identification device for ultra-deep geological structures. The identification device includes: an acquisition unit for acquiring active-source seismic record data and passive-source seismic record data of a target block; an active-source imaging unit for performing imaging processing on the active-source seismic record data to obtain an active-source signal imaging data volume; a passive-source imaging unit for performing imaging processing on the passive-source seismic record data to obtain a passive-source signal imaging data volume; and a joint identification unit for jointly identifying ultra-deep geological structures based on the active-source signal imaging data volume and the passive-source signal imaging data volume to obtain the identification result of the ultra-deep geological structure.

[0016] In another exemplary embodiment of the present invention, the joint identification unit may include: a boundary identification module, used to compare and interpret the ultra-deep geological structure using active source signal imaging data and passive source signal imaging data to identify the boundary of the ultra-deep geological structure; and an internal identification module, used to identify the internal detailed structure of the ultra-deep geological structure based on the active source signal imaging data.

[0017] In another exemplary embodiment of the present invention, the boundary identification module may include: a first interpretation submodule, used to interpret multiple waves appearing in the active source signal imaging data volume to obtain a first stratigraphic boundary interpretation result; a second interpretation submodule, used to interpret a passive source signal imaging data volume at a specified spatial location to obtain a second stratigraphic boundary interpretation result, wherein the specified spatial location is the spatial location corresponding to the multiple waves appearing in the active source signal imaging data volume; a judgment submodule, used to determine whether the first stratigraphic boundary interpretation result and the second stratigraphic boundary interpretation result are the same; and an output submodule, used to output the first stratigraphic boundary interpretation result as the boundary identification result of the ultra-deep geological structure when it is determined that the first stratigraphic boundary interpretation result and the second stratigraphic boundary interpretation result are the same.

[0018] In another exemplary embodiment of the present invention, the passive source imaging unit may include: a cross-correlation processing module for performing cross-correlation calculations on continuous-time signals between different stations to obtain a background noise cross-correlation signal; a superposition processing module for superimposing the energy coherence portion of the background noise cross-correlation signal using a dual-beam imaging method to obtain a superimposed seismic wave signal; a Green's function extraction module for extracting an empirical Green's function based on the superimposed seismic wave signal; and a seismic imaging processing module for performing imaging processing of the subsurface medium structure using the extracted empirical Green's function to obtain a passive source signal imaging data volume.

[0019] In another exemplary embodiment of the present invention, the passive source imaging unit may further include: a preprocessing module, used to preprocess the passive source seismic record data before performing cross-correlation calculations to obtain preprocessed passive source seismic record data.

[0020] A third aspect of the present invention provides an electronic device comprising a processor and a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by one or more processors to cause the processors to perform the ultra-deep geological structure identification method as described above.

[0021] A fourth aspect of the present invention provides a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to enable a computer to perform the method for identifying ultra-deep geological structures as described above.

[0022] The present invention has at least the following technical effects through the technical solution provided by the present invention:

[0023] (1) The method for identifying ultra-deep geological structures in this invention breaks through the incompleteness of single-source seismic data and the inherent technical bottleneck of exploration methods. By fully exploring the hidden correlation between passive source seismic data and active source seismic data, the passive source seismic data and active source seismic data are integrated and fused under certain conditions to improve the quality of active source seismic data and broaden its frequency band, thereby significantly improving the detection accuracy and resolution of ultra-deep structures.

[0024] (2) This invention solves the technical problems faced in ultra-deep artificial active source seismic exploration, such as difficulty in identifying effective signals and susceptibility to interference signal suppression, and reduces the ambiguity of seismic identification of ultra-deep geological bodies, thereby enabling effective identification of ultra-deep geological structures.

[0025] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0026] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0027] Figure 1 A flowchart illustrating the method for identifying ultra-deep geological structures provided in an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram showing the distribution of two-dimensional seismic survey lines in a basin, provided in an embodiment of the present invention.

[0029] Figure 3 This is an image of a natural earthquake and background noise provided in an embodiment of the present invention;

[0030] Figure 4 A structural block diagram of the ultra-deep geological structure identification device provided in this embodiment of the invention;

[0031] Figure 5 This is a structural block diagram of an electronic device provided in an embodiment of the present invention.

[0032] Explanation of reference numerals in the attached figures

[0033] 101-Acquisition unit, 102-Active source imaging unit, 103-Passive source imaging unit, 104-Joint identification unit, 201-Processor, 202-Memory. Detailed Implementation

[0034] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0035] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0036] In this invention, terms such as "first" and "second" are used merely for ease of description and distinction, and should not be construed as indicating or implying relative importance.

[0037] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integrated connection; they can refer to a direct connection or an indirect connection; they can refer to a wired connection or a wireless connection. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0038] In existing technologies, artificially induced earthquakes (or active-source earthquakes) are generally used to detect designated underground targets. After the earthquake, the artificially induced earthquake generates a signal that is transmitted underground. This signal produces different reflections when it encounters different strata. Once the surface receives this reflection information, the time and energy intensity of the reflection can be used to image the underground structure, thereby obtaining information on the underground distribution of oil and gas. However, because the explosive energy generated by artificially induced earthquakes is relatively limited, as the depth of the strata increases, the ability of the explosive energy to transmit to deeper strata weakens and the signal reflection path becomes longer, leading to the problem of multiple resolutions in deep layers, resulting in "false strata" reflections. Furthermore, although some scholars have proposed using data from natural earthquakes (or passive-source earthquakes) for inversion imaging of stratigraphic structures, natural earthquake data often lacks the low-frequency information required for high-precision modeling, failing to achieve the high-resolution imaging results needed for oil and gas reservoir exploration.

[0039] To address the technical limitations of existing technologies that rely on single-source seismic data for effectively identifying ultra-deep subsurface structures, this invention provides a method for identifying ultra-deep geological structures. This method integrates passive-source seismic data with active-source seismic data, using passive-source data to identify the boundaries of specific geological bodies and active-source data to depict the detailed internal structure of these bodies. This achieves joint geological interpretation of passive and active source imaging. Compared to existing geological structure identification methods, this invention significantly improves the accuracy of identifying ultra-deep geological structures, which is of great significance for oil and gas reservoir exploration. In practical implementation, the method can be executed by electronic devices, such as servers or terminals, that possess processing capabilities.

[0040] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings and embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0041] like Figure 1 As shown in the figure, this invention provides a method for identifying ultra-deep geological structures, which includes the following steps:

[0042] Step S101: Obtain active source seismic record data and passive source seismic record data of the target block.

[0043] It is important to clarify here that active source seismic record data refers to seismic wave signals generated on or beneath the Earth's surface by artificial or man-made sources (such as seismographs, explosive sources, or vibrators). These signals are the raw waveform data recorded by seismic sensors after the vibrations excited by the seismic source propagate to the Earth's surface. Active source seismic record data is usually stored in digital form and includes parameters such as amplitude, displacement, velocity, and acceleration, recording signal data from different channels.

[0044] Passive source seismic records refer to seismic wave signals generated by seismic sources in natural geological processes (such as seismic activity, wind, and ocean waves). These signals are usually background noise or natural vibrations originating from the Earth's interior. The signals received by ground-based detectors or detector arrays are amplified and recorded by a recorder to obtain a seismic waveform record. The recorder discretely samples the amplified electrical signal at certain time intervals and records it digitally on magnetic tape.

[0045] After obtaining active source seismic record data by setting up artificial seismic sources in the target block, a passive signal recording array is deployed according to the observation system consistent with the two-dimensional or three-dimensional grid of the active source seismic record data, and effective signals such as natural earthquake signals and background noise in the field are collected. This allows the acquisition of passive source seismic record data with a monitoring range roughly the same as that of the active source seismic record data.

[0046] Step S102: Perform imaging processing on the active source seismic record data to obtain active source signal imaging data volume.

[0047] It should be noted that after acquiring the original acquisition shot gather, velocity field and other data required for active source seismic imaging, the dispersion curves of active source surface waves can be extracted by methods such as steady-state method, transient surface wave spectrum analysis (SASW), and multichannel transient surface wave analysis (MASW). Then, S-wave velocity structure inversion is performed based on the dispersion curves of active source surface waves to obtain the active source signal imaging data volume.

[0048] Step S103: Perform imaging processing on the passive source seismic record data to obtain passive source signal imaging data volume.

[0049] It should be noted that after acquiring effective signals such as natural earthquake signals and background noise in the field, the dispersion curve of the passive source surface wave can be extracted by methods such as spatial autocorrelation (SPAC), high-resolution frequency wavenumber (HRFK), and background noise cross-correlation (NCF). Then, S-wave velocity structure inversion is performed based on the dispersion curve of the passive source surface wave to obtain the passive source signal imaging data volume.

[0050] Step S104: Based on the active source signal imaging data volume and the passive source signal imaging data volume, the ultra-deep geological structure is jointly identified to obtain the identification result of the ultra-deep geological structure.

[0051] It should be noted that the inventors have discovered through research that both active source seismic record data and passive source seismic record data describe the elastic dynamics of the Earth's medium and have very similar physical characteristics. They also have good complementarity in terms of signal frequency band and imaging scale. Under certain conditions, integrating and fusing active source seismic record data and passive source seismic record data can improve the quality of active source seismic record data and broaden its frequency band.

[0052] Specifically, active-source seismic records typically provide higher resolution and depth of penetration regarding subsurface structures. However, when used alone for seismic imaging, they only yield good interpretation results for shallow strata. For deeper strata (e.g., below 8000 km in basins), the energy transmitted from active-source earthquakes weakens and is suppressed by numerous interference signals, leading to increased ambiguity in deep multiples and resulting in many "false strata" interpretations. Passive-source seismic records, on the other hand, are helpful in obtaining real subsurface structure information over a large area (e.g., below 10 km in basins). However, their resolution is too low. When used alone for seismic imaging, passive-source seismic records can only identify geological structures over a large scale, not specific geological structure types, thus failing to meet the needs of oil and gas exploration.

[0053] It can be seen that active source seismic record data and passive source seismic record data actually have complementary advantages and disadvantages. If the seismic imaging profiles at the same underground location are compared and interpreted by the two types of seismic record data under different illumination methods in the ultra-deep layers, the real underground structural information transmitted by the passive source seismic record data can be used to verify the identification results of active source seismic record data for special geological bodies (such as rifts, intrusive rocks, etc.) in the ultra-deep layers on a large scale. This reduces the ambiguity of seismic identification of ultra-deep geological bodies and effectively identifies ultra-deep geological structures.

[0054] For example, when using active source signal imaging data for geological interpretation alone, if many layered reflections (i.e., multiples) are found in the active source imaging profile and the interpretation result is a "depression structure", in order to verify whether the "depression structure" is a true solution, it can be checked whether the passive source imaging profile also shows a corresponding "depression structure" at the same spatial location. If so, the above "depression structure" is considered to be a true solution; otherwise, the above "depression structure" is considered to be a "false stratum" reflection.

[0055] Furthermore, in one possible implementation, in step S101, when acquiring active source seismic record data and passive source seismic record data, it should be ensured that the acquisition path of the active source seismic record data is the same as that of the passive source seismic record data, so as to ensure that the subsurface velocity results constructed from the two types of seismic data belong to the same range.

[0056] For example, before acquiring passive source seismic record data, the geodetic coordinates of the geological target to be explored can be determined based on the acquisition path of the active source seismic record data. The acquisition points of the field instruments for natural seismic signals can then be arranged according to the determined geodetic coordinates of the geological target to be explored, so as to obtain passive source seismic record data that is consistent with the acquisition path of the active source seismic record data.

[0057] Specifically, one can first select the corresponding two-dimensional seismic survey line from the already deployed two-dimensional survey line database, based on the geological target to be surveyed, and obtain the corresponding geodetic coordinates. For example, Figure 2 This shows the location distribution of some two-dimensional seismic survey lines in a basin. We can start from... Figure 2 Among the multiple two-dimensional seismic survey lines, the two-dimensional seismic survey line corresponding to the geological target is first determined. If the selected two-dimensional seismic survey line is a straight line, the geodetic coordinates of the starting point and the ending point of the survey line need to be determined. If the selected two-dimensional seismic survey line is a broken line, the geodetic coordinates of each turning point need to be obtained.

[0058] Then, based on the geodetic coordinates (such as starting point coordinates, ending point coordinates, turning point coordinates, etc.) corresponding to the selected two-dimensional seismic survey line, the deployment trajectory of the seismic survey line is determined in the field. Signal recorders for collecting natural earthquake signals and background noise are deployed according to the design requirements at intervals to obtain passive source seismic recording data. For example, the signal recorders for collecting natural earthquake signals and background noise can be set as EPS-type short-period seismographs (as shown in Table 1 below), with an interval of 500-800m between each signal recorder and an acquisition time of 60-90 days.

[0059] Table 1. Relevant parameters of EPS-type short-period seismographs

[0060] name parameter Instrument size 175×240mm Instrument weight 5.0kg Number of channels 3 Continuous working hours 45 days of continuous operation (200Hz sampling) bandwidth 20s~100Hz Dynamic range >120dB Sampling rate 50,100,200,250,500,1000 Storage capacity 32GB Data format Miniseed

[0061] Thus, by using the seismic survey line layout of active source seismic data as a benchmark, and deploying seismographs at the same seismic survey line locations to collect passive source seismic data, it can be ensured that the two types of seismic data express the underground structural information of the same spatial location within a small scale. This is conducive to the effective comparison and comprehensive analysis of the two types of seismic data in the future, thereby improving the accuracy of identifying ultra-deep geological structures.

[0062] Furthermore, in one possible implementation, taking multichannel transient surface wave analysis as an example, in step S102, the frequency wavenumber method in multichannel transient surface wave analysis can be used to image the active source seismic record data, thereby obtaining the active source signal imaging data volume.

[0063] The main processing steps of the frequency wavenumber method are as follows: First, the time-domain wave field is converted into the frequency-domain wave field through Fourier transform; then, the phase velocity at a specific frequency is calculated according to the wavenumber and frequency of the amplitude maximum. Repeating this calculation for multiple frequencies will yield the corresponding dispersion curve; finally, the dispersion curve is inverted to obtain the active source signal imaging data volume.

[0064] Of course, this invention is not limited to this; other methods can also be used to image active source seismic record data, such as the phase-shift method in multichannel transient surface wave analysis, to obtain the active source signal imaging data volume. The phase-shift method is an improvement on the frequency-wavenumber method. After transforming the record to the frequency domain, it is represented as the product of amplitude and phase terms, and the amplitude term is normalized to reduce the influence of attenuation, which can better extract the dispersion curve.

[0065] Furthermore, in one possible implementation, taking the background noise cross-correlation method as an example, in step S103, the process of obtaining the passive source signal imaging data volume based on imaging processing of the passive source seismic record data may include, but is not limited to, the following sub-steps S1031 to S1034.

[0066] Sub-step S1031: Perform cross-correlation calculation on the continuous-time signals between different stations to obtain the background noise cross-correlation signal.

[0067] It should be noted that background noise is a special type of wave from the Earth's interior, recorded by seismographs after being scattered by various underground media layers. Its sources are complex, and it is a wave not generated by a seismic source. The corresponding steps for cross-correlation calculation of continuous waveform records between any two stations can be as follows: first, perform a Fourier transform on the daily seismic background noise data to convert it to the frequency domain, and then perform cross-correlation calculation in the frequency domain; then, perform an inverse Fourier transform on the results of the cross-correlation calculation to obtain the time domain, and finally superimpose them to obtain the cross-correlation function of the long-term series.

[0068] Assume there are two stations, A and B, and the continuous signals recorded by stations A and B are f, respectively. A (t) and f B (t), then the background noise cross-correlation function of the two stations can be calculated using the following expression:

[0069]

[0070] Where τ represents time delay and t represents time.

[0071] It should be noted that cross-correlation calculations of any two time series yield a positive branch and a negative branch, representing two seismic waves propagating in opposite directions. When the noise source is uniformly distributed, the signals recorded by the positive and negative branches should be symmetrical. However, noise sources in field seismic data are often non-uniformly distributed, resulting in asymmetrical positive and negative branches after cross-correlation calculations. Therefore, it is necessary to reverse the order of the positive and negative branches before superimposing them to obtain symmetrical components. Furthermore, besides improving the signal-to-noise ratio (SNR) through reverse superposition of positive and negative branches, the SNR can also be improved by superimposing long-term data to approximate uniformity to a certain extent.

[0072] Sub-step S1032: The energy coherence components in the cross-correlation signal of the background noise are superimposed using the dual-beam imaging method to obtain the superimposed seismic wave signal.

[0073] It's important to note that the primary purpose of using double beamforming (DBF) to superimpose the energy coherence components of the environmental noise field is to improve the signal-to-noise ratio (SNR) of the seismic signal. DBF mainly utilizes the reciprocity between the cross-correlation imaging source and receiver in the background noise to reconstruct weak volume wave and surface wave signals. By superimposing the energy correlation components of the cross-correlation signals between two seismic arrays, it enhances signal correlation and extracts previously unclear weak signals. In other words, DBF acts as a spatial filter between the two seismic arrays.

[0074] Sub-step S1033: Extract the empirical Green's function based on the superimposed seismic wave signal.

[0075] It should be noted that calculating the cross-correlation of two time series will yield two positive and negative branches in opposite directions. The waveform generally contains signals of various frequencies, while the extracted Green's function is the result of the superposition of harmonics of different frequency signals.

[0076] Sub-step S1034: The extracted empirical Green's function is used to perform imaging processing of the underground medium structure to obtain passive source signal imaging data volume.

[0077] It should be noted that various seismic tomography methods can be used to study the structure of subsurface media, and the final passive source signal imaging data volume can be in two-dimensional or three-dimensional form.

[0078] For example, after obtaining the empirical Green's function, the dispersion curve can be obtained through time-frequency analysis to obtain the group velocity or phase velocity of each period. Then, the group velocity or phase velocity of each point can be obtained through inversion calculation, and finally, a velocity imaging map of the Earth's interior can be obtained.

[0079] In addition, in sub-step S1031, before performing cross-correlation calculations, the passive source seismic record data can be preprocessed to obtain preprocessed passive source seismic record data.

[0080] For example, the preprocessing of data from a single machine may include the following three steps:

[0081] (1) First, the station data that does not meet the format requirements is converted. Then, the converted data is processed to eliminate noise interference, such as detrending and demeaning, truncation and resampling, bandpass filtering, removal of instrument response, removal of wind noise and human interference, etc., to improve data quality.

[0082] (2) Time-domain normalization can suppress natural earthquake events in noise and remove abnormal signals caused by seismic instrument malfunctions, etc.

[0083] (3) Frequency domain normalization, this process is to suppress the influence of single-frequency signals.

[0084] It should be noted that single-station data preprocessing aims to remove the influence of natural earthquakes and anomalous signals inherent in the instrument, ultimately yielding background noise data. Time-domain normalization is the most crucial step in data preprocessing; the sliding absolute window method and the "one-bit" regularization method are the two most effective approaches, with the "one-bit" regularization method being the most commonly used. Generally, the frequency-domain sliding absolute value normalization method can be used for spectral whitening analysis. This not only effectively suppresses interference from site effects around the station and broadens the frequency band but also improves the signal-to-noise ratio of the long-term Green's function.

[0085] Furthermore, in one possible implementation, in step S104, the process of jointly identifying ultra-deep geological structures based on active source signal imaging data and passive source signal imaging data to obtain identification results of ultra-deep geological structures may include, but is not limited to, the following sub-steps S1041 to S1042.

[0086] Sub-step S1041 uses active source signal imaging data and passive source signal imaging data to compare and interpret ultra-deep geological structures and identify the boundaries of ultra-deep geological structures.

[0087] For example, the process of comparatively interpreting ultra-deep geological structures by combining active source signal imaging data and passive source signal imaging data may include the following five steps:

[0088] (1) Interpret the multiple waves appearing in the active source signal imaging data volume to obtain the interpretation results of the first stratum boundary;

[0089] (2) Interpret the passive source signal imaging data volume at a specified spatial location to obtain the interpretation result of the second stratum boundary. The specified spatial location refers to the spatial location corresponding to the multiple waves that appear in the active source signal imaging data volume.

[0090] (3) Determine whether the interpretation results of the first stratigraphic boundary are the same as those of the second stratigraphic boundary;

[0091] (4) If the interpretation result of the first stratigraphic boundary is the same as the interpretation result of the second stratigraphic boundary, then the interpretation result of the first stratigraphic boundary is considered to be the true stratigraphic identification result, and the interpretation result of the first stratigraphic boundary is output as the boundary identification result of the ultra-deep geological structure.

[0092] (5) If the interpretation results of the first stratigraphic boundary are different from those of the second stratigraphic boundary, the interpretation results of the first stratigraphic boundary are considered to be false stratigraphic identification results, and the interpretation results of the first stratigraphic boundary are discarded or deleted.

[0093] Sub-step S1042: Based on the active seismic source signal imaging data volume, identify the internal detailed structure of ultra-deep geological structures.

[0094] Thus, based on the complementary relationship between active source seismic record data and passive source seismic record data, the outline of ultra-deep special geological bodies identified by active source seismic record data can be verified on a large scale by first combining passive source seismic record data, and then the internal detailed structure of the geological body can be characterized by active source seismic record data. This can significantly improve the detection accuracy and resolution of ultra-deep geological structures.

[0095] Figure 3 An image of a natural earthquake and background noise is shown, such as... Figure 3 As shown, below the SF detector, the result of interpreting the velocity field of the artificial active source imaging is: there is a "depression groove" at the layer projection. This depression groove is consistent with the velocity field of the passive source imaging, indicating that the "depression groove" really exists.

[0096] Furthermore, the implementation environment of this embodiment includes at least one terminal and one server, and the method is executed on the terminal or the server respectively. The terminal and the server can establish a communication connection to achieve interactive information transmission.

[0097] The terminal can be any electronic product that can interact with the user through one or more methods such as keyboard, touchpad, touch screen, voice interaction, etc., such as PC (Personal Computer), PPC (Pocket Personal Computer), tablet computer, etc.

[0098] A server can be a single server, a server cluster consisting of multiple servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0099] like Figure 4 As shown, this embodiment of the invention also provides an identification device for ultra-deep geological structures, which includes an acquisition unit 101, an active seismic source imaging unit 102, a passive seismic source imaging unit 103, and a joint identification unit 104.

[0100] Acquisition unit 101 is used to acquire active source seismic record data and passive source seismic record data of the target block.

[0101] The active source imaging unit 102 is used to perform imaging processing on active source seismic record data to obtain active source signal imaging data volume.

[0102] The passive source imaging unit 103 is used to perform imaging processing on passive source seismic record data to obtain passive source signal imaging data volume.

[0103] The joint identification unit 104 is used to jointly identify ultra-deep geological structures based on active source signal imaging data and passive source signal imaging data, and obtain the identification results of ultra-deep geological structures.

[0104] Furthermore, in one possible implementation, the passive source imaging unit 103 may include a cross-correlation processing module, a stacking processing module, a Green's function extraction module, and a seismic imaging processing module.

[0105] Specifically, the cross-correlation processing module is used to perform cross-correlation calculations on continuous-time signals between different stations to obtain the cross-correlation signal of background noise.

[0106] The superposition processing module is used to superimpose the energy coherence components of the cross-correlation signal of the background noise using the dual-beam imaging method to obtain the superimposed seismic wave signal.

[0107] The Green's function extraction module is used to extract the empirical Green's function based on the superimposed seismic wave signal.

[0108] The seismic imaging processing module is used to perform imaging processing of the subsurface medium structure using the extracted empirical Green's function, and to obtain passive source signal imaging data.

[0109] Furthermore, in one possible implementation, the passive source imaging unit 103 may also include a preprocessing module.

[0110] The preprocessing module is used to preprocess the passive source seismic record data before performing cross-correlation calculations, so as to obtain preprocessed passive source seismic record data.

[0111] Furthermore, in one possible implementation, the joint identification unit 104 may include a boundary identification module and an internal identification module.

[0112] Specifically, the boundary recognition module is used to compare and interpret ultra-deep geological structures using active source signal imaging data and passive source signal imaging data to identify the boundaries of ultra-deep geological structures.

[0113] The internal identification module is used to identify the internal details of ultra-deep geological structures based on active seismic source signal imaging data.

[0114] Furthermore, in one possible implementation, the boundary recognition module may include: a first interpretation submodule, a second interpretation submodule, a judgment submodule, and an output submodule.

[0115] The first interpretation submodule is used to interpret the multiple waves appearing in the active source signal imaging data volume to obtain the interpretation results of the first stratigraphic boundary.

[0116] The second interpretation submodule is used to interpret the passive source signal imaging data volume at a specified spatial location to obtain the interpretation result of the second stratigraphic boundary. The specified spatial location is the spatial location corresponding to the multiple waves appearing in the active source signal imaging data volume.

[0117] The judgment submodule is used to determine whether the interpretation results of the first stratigraphic boundary are the same as those of the second stratigraphic boundary.

[0118] The output submodule is used to output the first stratigraphic boundary interpretation result as the boundary identification result of the ultra-deep geological structure when the interpretation results of the first stratigraphic boundary and the second stratigraphic boundary are the same.

[0119] It should be noted that the above-described device is only illustrated by the division of the functional modules described above. In practical applications, the functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the device and method provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0120] like Figure 5 As shown, this embodiment of the invention also provides an electronic device, which includes a processor 201 and a memory 202. The memory stores at least one computer program, which is loaded and executed by one or more processors to enable the processors to implement the ultra-deep geological structure identification method in the above embodiments.

[0121] Of course, the electronic device may also have wired or wireless network interfaces, keyboards, and input / output interfaces for input and output. The electronic device may also include other components for implementing the various functions of the device, which will not be elaborated here.

[0122] This invention also provides a computer-readable storage medium storing at least one piece of program code, which is loaded and executed by a processor to enable a computer to implement the method for identifying ultra-deep geological structures described in the above embodiments.

[0123] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, or an optical disc data storage device, etc. Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in each embodiment of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc.

[0124] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0125] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

[0126] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A method for identifying ultra-deep geological structures, characterized in that, The identification method includes: Obtain active source seismic record data and passive source seismic record data of the target block; Imaging processing is performed on active source seismic record data to obtain active source signal imaging data volume; Imaging processing is performed on passive source seismic record data to obtain passive source signal imaging data volume; The ultra-deep geological structure is jointly identified based on the active source signal imaging data and the passive source signal imaging data, and the identification results of the ultra-deep geological structure are obtained.

2. The method for identifying ultra-deep geological structures according to claim 1, characterized in that, The joint identification of ultra-deep geological structures based on active source signal imaging data and passive source signal imaging data yields the identification results of ultra-deep geological structures, including: By comparing and interpreting the imaging data volumes of active and passive seismic sources, the boundaries of ultra-deep geological structures can be identified. Based on active seismic source signal imaging data, we can identify the internal detailed structure of ultra-deep geological structures.

3. The method for identifying ultra-deep geological structures according to claim 2, characterized in that, The method of comparing and interpreting ultra-deep geological structures using active source signal imaging data and passive source signal imaging data to identify the boundaries of ultra-deep geological structures includes: The multiple waves appearing in the active source signal imaging data volume are interpreted to obtain the interpretation results of the first stratigraphic boundary. The passive source signal imaging data volume at a specified spatial location is interpreted to obtain the interpretation result of the second stratigraphic boundary. The specified spatial location is the spatial location corresponding to the multiple waves appearing in the active source signal imaging data volume. Determine whether the interpretation results of the first stratigraphic boundary are the same as those of the second stratigraphic boundary; If the interpretation results of the first stratigraphic boundary are the same as those of the second stratigraphic boundary, the interpretation result of the first stratigraphic boundary will be output as the boundary identification result of the ultra-deep geological structure.

4. The method for identifying ultra-deep geological structures according to claim 1, characterized in that, The imaging processing of passive source seismic record data to obtain passive source signal imaging data volume includes: Cross-correlation calculations are performed on continuous-time signals from different stations to obtain background noise cross-correlation signals; The energy coherence components of the cross-correlation signal of the background noise are superimposed using the dual-beam imaging method to obtain the superimposed seismic wave signal. Based on the superimposed seismic wave signals, an empirical Green's function is extracted; The extracted empirical Green's function is used to perform imaging processing of the underground medium structure to obtain passive source signal imaging data.

5. The method for identifying ultra-deep geological structures according to claim 1, characterized in that, The imaging processing of passive source seismic record data to obtain passive source signal imaging data volume further includes: Before performing cross-correlation calculations, the passive source seismic record data is preprocessed to obtain preprocessed passive source seismic record data.

6. The method for identifying ultra-deep geological structures according to claim 5, characterized in that, The preprocessing includes at least one of noise interference removal, time-domain normalization, and frequency-domain normalization.

7. The method for identifying ultra-deep geological structures according to claim 1, characterized in that, The acquisition path for the active source seismic record data is the same as that for the passive source seismic record data.

8. The method for identifying ultra-deep geological structures according to claim 1, characterized in that, The detection depth of the ultra-deep geological structure is over 5000m.

9. A device for identifying ultra-deep geological structures, characterized in that, The identification device includes: The acquisition unit is used to acquire active source seismic record data and passive source seismic record data of the target block; The active source imaging unit is used to perform imaging processing on active source seismic record data to obtain active source signal imaging data volume. The passive source imaging unit is used to perform imaging processing on passive source seismic record data to obtain passive source signal imaging data volume. The joint identification unit is used to jointly identify ultra-deep geological structures based on active source signal imaging data and passive source signal imaging data, and obtain the identification results of ultra-deep geological structures.

10. The device for identifying ultra-deep geological structures according to claim 9, characterized in that, The joint identification unit includes: The boundary recognition module is used to compare and interpret ultra-deep geological structures using active source signal imaging data and passive source signal imaging data to identify the boundaries of ultra-deep geological structures. The internal identification module is used to identify the internal details of ultra-deep geological structures based on active seismic source signal imaging data.

11. The device for identifying ultra-deep geological structures according to claim 10, characterized in that, The boundary recognition module includes: The first interpretation submodule is used to interpret the multiple waves appearing in the active source signal imaging data volume to obtain the interpretation results of the first stratigraphic boundary; The second interpretation submodule is used to interpret the passive source signal imaging data volume at a specified spatial location to obtain the interpretation result of the second stratigraphic boundary. The specified spatial location is the spatial location corresponding to the multiple waves appearing in the active source signal imaging data volume. The judgment submodule is used to determine whether the interpretation results of the first stratigraphic boundary and the interpretation results of the second stratigraphic boundary are the same. The output submodule is used to output the first stratigraphic boundary interpretation result as the boundary identification result of the ultra-deep geological structure when the interpretation results of the first stratigraphic boundary and the second stratigraphic boundary are the same.

12. The device for identifying ultra-deep geological structures according to claim 9, characterized in that, The passive seismic source imaging unit includes: The cross-correlation processing module is used to perform cross-correlation calculations on continuous-time signals between different stations to obtain background noise cross-correlation signals. The superposition processing module is used to superimpose the energy coherence components in the cross-correlation signal of the background noise using the dual-beam imaging method to obtain the superimposed seismic wave signal. The Green's function extraction module is used to extract the empirical Green's function based on the superimposed seismic wave signal; The seismic imaging processing module is used to perform imaging processing of the subsurface medium structure using the extracted empirical Green's function, and to obtain passive source signal imaging data.

13. The device for identifying ultra-deep geological structures according to claim 9, characterized in that, The passive seismic source imaging unit also includes: The preprocessing module is used to preprocess the passive source seismic record data before performing cross-correlation calculations, so as to obtain preprocessed passive source seismic record data.

14. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing at least one computer program, which is loaded and executed by one or more processors to enable the processors to perform the method for identifying ultra-deep geological structures as described in any one of claims 1 to 8.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to enable the computer to perform the method for identifying ultra-deep geological structures as described in any one of claims 1 to 8.

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