A method and device for identifying a volcanic mechanism period interface through earthquakes

Abstract

This application provides a method and apparatus for seismic identification of volcanic structure phase interfaces. The method includes: acquiring raw seismic data; calculating the dip angle and azimuth angle of the strata based on the raw seismic data; performing anisotropic diffusion filtering on the raw seismic data under the control of the dip angle and azimuth angle to obtain a structure-guided filtered data volume; extracting seismic reflection coefficient data from the structure-guided filtered data volume using inversion technology to obtain a seismic reflection coefficient data volume; and performing seismic identification and tracking interpretation of volcanic structures and phase interfaces based on the seismic reflection coefficient data volume. By performing structure-guided filtering and reflection coefficient inversion processing on the raw seismic data, the signal-to-noise ratio of seismic data of deep volcanic rocks is effectively improved. The resulting seismic reflection coefficient volume highlights the seismic reflection structural characteristics of volcanic structures, effectively improving the seismic identification capability and interpretation accuracy of deep volcanic structures and phase interfaces.

Description

Technical Field

[0001] This invention relates to the field of seismic data interpretation technology, and in particular to a method and apparatus for seismic identification of volcanic structure phase interfaces. Background Technology

[0002] The deep volcanic rock strata have a complex and intricate structure, with numerous volcanic structures intersecting and overlapping. These strata change rapidly in the lateral direction, exhibiting strong heterogeneity. In the vertical direction, the volcanic rocks often show characteristics of multiple eruptions and are buried at relatively deep locations.

[0003] Due to their great burial depth, the seismic reflection energy within volcanic rocks is extremely weak, resulting in a relatively low signal-to-noise ratio. On seismic profiles, these volcanic rocks typically exhibit a chaotic and weak reflection pattern, lacking clear and distinct seismic reflection interfaces. These characteristics make it exceptionally difficult to accurately identify volcanic structures and their internal phases using conventional seismic profiles.

[0004] This problem poses a serious challenge to volcanic rock oil and gas exploration. The inability to provide a detailed description of volcanic structures significantly impacts subsequent reservoir prediction and other related work. Therefore, accurately identifying the stratigraphic structure of deep volcanic rocks has always been a pressing issue in the field of volcanic rock oil and gas exploration, and its importance is self-evident. Summary of the Invention

[0005] This invention provides a seismic identification method and apparatus for volcanic structure phase interfaces, which is used to perform anisotropic diffusion filtering and reflection coefficient inversion on raw seismic data to achieve accurate seismic identification and tracking interpretation of volcanic structures and phase interfaces.

[0006] In a first aspect, the present invention provides a seismic identification method for the phase interface of a volcanic structure, comprising:

[0007] Obtain raw earthquake data;

[0008] Based on the original seismic data, calculate the dip angle and azimuth angle of the strata;

[0009] Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0010] Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques.

[0011] Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

[0012] Optionally, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0013] The seismic reflection coefficient data volume is then filtered.

[0014] Optionally, the seismic reflection coefficient data volume is filtered, including:

[0015] Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results;

[0016] Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0017] The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

[0018] Optionally, under the control of the stratum dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including:

[0019] Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed;

[0020] The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0021] Optionally, seismic reflection coefficient data can be obtained from the constructed guided filter data volume using inversion techniques, including:

[0022] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0023] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0024] Optionally, based on the constructed guided-filter data volume, a target function in the frequency domain is established, including:

[0025] The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components;

[0026] Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window;

[0027] The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

[0028] Secondly, the present invention provides an earthquake identification device for the interface of volcanic structure stages, comprising:

[0029] The acquisition module is used to acquire raw seismic data;

[0030] The calculation module is used to calculate the dip angle and azimuth angle of the strata based on the original seismic data;

[0031] The filtering module is used to perform anisotropic diffusion filtering on the original seismic data under the control of the dip angle and the azimuth angle to obtain the structurally guided filtered data volume.

[0032] The inversion module is used to extract the seismic reflection coefficient data from the constructed guided filter data volume using inversion technology.

[0033] The identification module is used to identify and track earthquakes at the volcanic structure and phase interface based on the earthquake reflection coefficient data.

[0034] Optionally, it also includes:

[0035] The filtering module is used to filter the seismic reflection coefficient data.

[0036] Optionally, the filtering module includes:

[0037] The well-seismic calibration result determination submodule is used to perform well-seismic calibration on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration result;

[0038] The bandpass filter coefficient determination submodule is used to determine the bandpass filter coefficient based on the well vibration calibration results.

[0039] The filtering submodule is used to apply the bandpass filter coefficients to filter the seismic reflection coefficient data volume.

[0040] Optionally, the filtering module includes:

[0041] The algorithm design submodule is used to design the anisotropic diffusion filter smoothing algorithm under the constraints of the dip angle and the azimuth angle of the strata;

[0042] The filtering submodule is used to apply the anisotropic diffusion filtering smoothing algorithm to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0043] Optionally, the inversion module includes:

[0044] The objective function establishment submodule is used to establish a frequency domain objective function based on the constructed guided filter data volume.

[0045] The data volume acquisition submodule is used to solve the objective function through optimization algorithms to obtain the seismic reflection coefficient data volume.

[0046] Optionally, the objective function establishment submodule includes:

[0047] The decomposition unit is used to perform parity decomposition on the constructed guided filter data volume to obtain odd components and even components.

[0048] The time-frequency analysis unit is used to perform time-frequency analysis on the constructed guided filter data volume to obtain the spectrum information within the hour window;

[0049] The function establishment unit is used to establish the objective function by combining the spectrum information, the odd component, and the even component.

[0050] Thirdly, the present invention provides an electronic device, including a processor and a memory, the memory storing computer-readable instructions, wherein when the computer-readable instructions are executed by the processor, the steps of the method provided in the first aspect above are performed, including:

[0051] Obtain raw earthquake data;

[0052] Based on the original seismic data, calculate the dip angle and azimuth angle of the strata;

[0053] Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0054] Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques.

[0055] Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

[0056] Optionally, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0057] The seismic reflection coefficient data volume is then filtered.

[0058] Optionally, the seismic reflection coefficient data volume is filtered, including:

[0059] Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results;

[0060] Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0061] The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

[0062] Optionally, under the control of the stratum dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including:

[0063] Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed;

[0064] The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0065] Optionally, seismic reflection coefficient data can be obtained from the constructed guided filter data volume using inversion techniques, including:

[0066] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0067] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0068] Optionally, based on the constructed guided-filter data volume, a target function in the frequency domain is established, including:

[0069] The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components;

[0070] Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window;

[0071] The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

[0072] Fourthly, the present invention provides a storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the method provided in the first aspect above, including:

[0073] Obtain raw earthquake data;

[0074] Based on the original seismic data, calculate the dip angle and azimuth angle of the strata;

[0075] Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0076] Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques.

[0077] Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

[0078] Optionally, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0079] The seismic reflection coefficient data volume is then filtered.

[0080] Optionally, the seismic reflection coefficient data volume is filtered, including:

[0081] Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results;

[0082] Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0083] The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

[0084] Optionally, under the control of the stratum dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including:

[0085] Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed;

[0086] The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0087] Optionally, seismic reflection coefficient data can be obtained from the constructed guided filter data volume using inversion techniques, including:

[0088] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0089] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0090] Optionally, based on the constructed guided-filter data volume, a target function in the frequency domain is established, including:

[0091] The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components;

[0092] Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window;

[0093] The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

[0094] Fifthly, the present invention provides a computer program product comprising a computer program, which, when executed by a processor, performs the steps of the method provided in the first aspect above, including:

[0095] Obtain raw earthquake data;

[0096] Based on the original seismic data, calculate the dip angle and azimuth angle of the strata;

[0097] Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0098] Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques.

[0099] Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

[0100] Optionally, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0101] The seismic reflection coefficient data volume is then filtered.

[0102] Optionally, the seismic reflection coefficient data volume is filtered, including:

[0103] Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results;

[0104] Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0105] The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

[0106] Optionally, under the control of the stratum dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including:

[0107] Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed;

[0108] The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0109] Optionally, seismic reflection coefficient data can be obtained from the constructed guided filter data volume using inversion techniques, including:

[0110] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0111] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0112] Optionally, based on the constructed guided-filter data volume, a target function in the frequency domain is established, including:

[0113] The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components;

[0114] Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window;

[0115] The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

[0116] As can be seen from the above technical solutions, the present invention has the following advantages:

[0117] This invention provides a method and apparatus for seismic identification of volcanic structure phase interfaces. The method includes: acquiring raw seismic data; calculating the dip angle and azimuth angle of the strata based on the raw seismic data; performing anisotropic diffusion filtering on the raw seismic data under the control of the dip angle and azimuth angle to obtain a structure-guided filtered data volume; extracting seismic reflection coefficient data from the structure-guided filtered data volume using inversion technology; and performing seismic identification and tracking interpretation of volcanic structures and phase interfaces based on the seismic reflection coefficient data volume. By performing structure-guided filtering and reflection coefficient inversion processing on the raw seismic data, the signal-to-noise ratio of seismic data for deep volcanic rocks is effectively improved. The resulting seismic reflection coefficient volume highlights the seismic reflection structural characteristics of volcanic structures, effectively improving the seismic identification capability and interpretation accuracy of deep volcanic structures and phase interfaces. Attached Figure Description

[0118] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0119] Figure 1 This is a flowchart illustrating the steps of a first embodiment of the seismic identification method for the volcanic structure phase interface of the present invention.

[0120] Figure 2 This is a flowchart illustrating the steps of a second embodiment of the seismic identification method for volcanic structure phase interfaces according to the present invention.

[0121] Figure 3 This is the original seismic profile of a second embodiment of the seismic identification method for the phase interface of a volcanic structure according to the present invention.

[0122] Figure 4 This is a schematic diagram of the data volume after construction-guided filtering in a second embodiment of the seismic identification method for the volcanic mechanism phase interface of the present invention.

[0123] Figure 5 This is a schematic diagram of the seismic reflection coefficient data volume of a second embodiment of the seismic identification method for the volcanic mechanism phase interface of the present invention;

[0124] Figure 6 This is a schematic diagram of the reflection interface data profile of a second embodiment of the seismic identification method for the volcanic structure phase interface of the present invention.

[0125] Figure 7 This is a structural block diagram of an embodiment of an earthquake identification device for a volcanic phase interface according to the present invention. Detailed Implementation

[0126] This invention provides a method and apparatus for seismic identification of volcanic structures and their phase interfaces, which is used to perform anisotropic diffusion filtering and reflection coefficient inversion on raw seismic data to achieve accurate seismic identification and tracking interpretation of volcanic structures and their phase interfaces.

[0127] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0128] Example 1, please refer to Figure 1 , Figure 1 This is a flowchart illustrating the steps of a seismic identification method for volcanic structure phase interfaces according to a first embodiment of the present invention. The method includes:

[0129] Step S101: Obtain raw seismic data;

[0130] It should be noted that raw seismic data is usually stored in the form of time-depth or time-distance, containing rich information about underground geological structures.

[0131] Step S102: Calculate the dip angle and azimuth angle of the strata based on the original seismic data;

[0132] In this embodiment, raw seismic data is used to estimate the dip and azimuth of subsurface strata. Methods for calculating the dip and azimuth may include analytical methods, numerical methods, or machine learning algorithms, depending on the data quality and required accuracy.

[0133] Step S103: Under the control of the dip angle and the azimuth angle of the strata, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0134] It should be noted that anisotropic diffusion filtering is an image processing technique that can smooth an image while preserving edge features.

[0135] In this embodiment, by combining information on stratum dip angle and azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering, which can diffuse along the direction of geological structure, thereby better protecting and enhancing the seismic response related to the structure.

[0136] Step S104: Using inversion technology, extract the seismic reflection coefficient data from the constructed guided filter data volume to obtain the seismic reflection coefficient data volume;

[0137] It should be noted that inversion technology is an important part of seismic data processing. Its purpose is to infer the physical properties of the subsurface medium, such as the reflection coefficient, from observational data.

[0138] In this embodiment of the application, the data volume after constructing the guided filter is used as input, and the reflection coefficient is estimated by establishing an appropriate mathematical model and optimization algorithm.

[0139] In an optional embodiment, seismic reflection coefficient data is obtained by extracting data from the structure-guided filter data volume using inversion techniques, including:

[0140] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0141] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0142] In this embodiment, the seismic data volume after guided filtering is converted to the frequency domain, and an objective function is established in the frequency domain. Subsequently, through iterative calculations, the model parameters are gradually adjusted so that the value of the objective function continuously decreases until the value of the objective function drops to a preset threshold, or the number of iterations reaches the upper limit, resulting in the final set of parameters, i.e., the seismic reflection coefficient data volume.

[0143] Step S105: Based on the earthquake reflection coefficient data volume, perform earthquake identification and tracking interpretation of volcanic structures and phase interfaces.

[0144] In the embodiments of this application, the obtained seismic reflection coefficient data volume can be used to perform detailed seismic interpretation work, including identifying volcanic structures and phase boundaries, thereby constructing a three-dimensional model of the underground geological structure, providing important information for volcanological research and resource exploration.

[0145] In an optional embodiment, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0146] The seismic reflection coefficient data volume is then filtered.

[0147] In the embodiments of this application, before performing earthquake identification and tracking interpretation of volcanic structures and phase interfaces, it may be necessary to further filter the seismic reflection coefficient data volume to improve the data quality and resolution.

[0148] This invention provides a seismic identification method for volcanic structure phase interfaces, comprising: acquiring raw seismic data; calculating the dip and azimuth of the strata based on the raw seismic data; performing anisotropic diffusion filtering on the raw seismic data under the control of the dip and azimuth to obtain a structure-guided filtered data volume; extracting seismic reflection coefficient data from the structure-guided filtered data volume using inversion technology; and performing seismic identification and tracking interpretation of volcanic structures and phase interfaces based on the seismic reflection coefficient data volume. By performing structure-guided filtering and reflection coefficient inversion processing on the raw seismic data, the signal-to-noise ratio of seismic data for deep volcanic rocks is effectively improved. The resulting seismic reflection coefficient volume highlights the seismic reflection structural characteristics of volcanic structures, effectively improving the seismic identification capability and interpretation accuracy of deep volcanic structures and phase interfaces.

[0149] Example 2, please refer to Figure 2 , Figure 2 This is a flowchart illustrating the steps of a second embodiment of the seismic identification method for volcanic structure phase interfaces according to the present invention. The steps include:

[0150] Step S201: Obtain raw seismic data;

[0151] In this embodiment of the application, seismic detectors are deployed on the surface or at sea, and seismic waves are artificially generated to record the propagation and reflection information of the seismic waves in the strata, thereby obtaining raw seismic data.

[0152] Please see Figure 3 , Figure 3This is the original seismic profile of a second embodiment of the seismic identification method for the phase interface of a volcanic structure according to the present invention. From the conventional seismic profile characteristics, the top surface of the volcanic rock shows strong wave peak reflection characteristics and forms an unconformity contact relationship with the overlying strata, making the seismic profile relatively easy to identify. However, the interior of the volcanic structure shows chaotic and discontinuous reflection characteristics, making it difficult to identify and trace the phase interfaces within the volcanic structure.

[0153] Step S202: Calculate the dip angle and azimuth angle of the strata based on the original seismic data;

[0154] Step S203: Under the constraints of the dip angle and the azimuth angle of the strata, design the anisotropic diffusion filter smoothing algorithm;

[0155] It should be noted that the anisotropic diffusion filtering smoothing algorithm only applies to information parallel to the seismic phase axis and not to the interface where seismic reflections terminate. This maximizes the protection of seismic information of faults and lithological boundaries. Compared with conventional filtering methods, it eliminates noise while maintaining the boundary information and texture features of the image, improving the signal-to-noise ratio and continuity of seismic data. The seismic phase axis features are more obvious, which is beneficial for subsequent interpretive processing.

[0156] Step S204: Apply the anisotropic diffusion filtering smoothing algorithm to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0157] In this embodiment, under the constraint of dip angle attribute volume, anisotropic diffusion filtering is performed on the original seismic data, and the profile processing effects corresponding to different parameters are compared to obtain... Figure 4 The structure-guided filtering data shown improves the signal-to-noise ratio and continuity of seismic data within the volcanic structure by processing the data volume, while protecting the seismic information of faults and lithological boundaries, and making the seismic phase axis characteristics more obvious.

[0158] Step S205: Based on the constructed guided filtering data volume, establish the objective function in the frequency domain;

[0159] In this embodiment, the odd-even decomposition is performed on the constructed guided filtering data volume to obtain odd and even components; time-frequency analysis is performed on the constructed guided filtering data volume to obtain spectral information within an hour window; and the objective function is established by combining the spectral information, the odd components, and the even components.

[0160] Step S206: Solve the objective function using an optimization algorithm to obtain the seismic reflection coefficient data volume;

[0161] In this embodiment, the seismic reflection coefficient data volume is constructed using seismic data volume after guided filtering, and a reflection coefficient inversion method based on parity decomposition is employed. This method establishes an objective function in the frequency domain and optimizes the inversion algorithm to invert the seismic reflection coefficients, such as... Figure 5 As shown.

[0162] The objective function is established by combining the spectral information within the hour window with the odd and even components of the data volume after the guided filter, similar to the principle of frequency domain convolution.

[0163] The objective function of spectral inversion (a method that transforms the seismic inversion problem from the time domain to the frequency domain) has better convergence and constraint capabilities compared to the convolutional residual objective function in the time domain, and it can reduce the problem of multiple solutions in seismic inversion. The odd and even components of the reflection coefficient play an important role in the identification of thin-layer reflection interfaces.

[0164] Step S207: Use the acquired well logging data to perform well-seismic calibration on the seismic reflection coefficient data volume to obtain the well-seismic calibration results;

[0165] In this embodiment, the impedance information of well logging data is converted into seismic response. Then, the converted well logging seismic response is compared with the actual seismic reflection coefficient data volume. Based on the comparison results, the calibration model parameters are adjusted to match the well logging data and the seismic reflection coefficient data volume, thus obtaining well-seismic calibration results including calibration coefficients, calibration model, and calibration error.

[0166] Step S208: Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0167] Based on the results of well seismic calibration, this application selects a frequency range that can highlight the geological strata interface, and calculates the filtering coefficients based on the determined frequency range.

[0168] Step S209: Apply the bandpass filter coefficients to filter the seismic reflection coefficient data volume;

[0169] In this embodiment, the seismic reflection coefficient data volume and bandpass filter coefficients are input, and digital signal processing technology is used to perform filtering to obtain the following result: Figure 6 The diagram shows a cross-sectional view of the reflective interface data.

[0170] Step S210: Based on the earthquake reflection coefficient data volume, perform earthquake identification and tracking interpretation of volcanic structures and phase interfaces.

[0171] This invention discloses a seismic identification method for volcanic structure phase interfaces, comprising: acquiring raw seismic data; calculating stratigraphic dip and azimuth based on the raw seismic data; performing anisotropic diffusion filtering on the raw seismic data under the control of the stratigraphic dip and azimuth to obtain a structurally guided filtered data volume; extracting seismic reflection coefficient data from the structurally guided filtered data volume using inversion technology; and performing seismic identification and tracking interpretation of volcanic structures and phase interfaces based on the seismic reflection coefficient data volume. By performing special processing on the raw seismic data such as structurally guided filtering, reflection coefficient inversion, and filtering, the signal-to-noise ratio of seismic data for deep volcanic rocks is effectively improved, the continuity characteristics of the strata within the volcanic structure are enhanced, and the obtained seismic reflection coefficient volume highlights the seismic reflection structural characteristics of the volcanic structure, effectively improving the seismic identification capability and interpretation accuracy of deep volcanic structures and their internal phase interfaces.

[0172] Example 3, please refer to Figure 7 , Figure 7 This is a structural block diagram of an embodiment of a seismic identification device for volcanic mechanism phase interfaces according to the present invention. The device includes:

[0173] Module 301 is used to acquire raw seismic data;

[0174] Calculation module 302 is used to calculate the dip angle and azimuth angle of the strata based on the original seismic data;

[0175] Filtering module 303 is used to perform anisotropic diffusion filtering on the original seismic data under the control of the dip angle and the azimuth angle to obtain the structurally guided filtered data volume;

[0176] The inversion module 304 is used to extract the seismic reflection coefficient data from the structured guided filter data volume through inversion technology.

[0177] The identification module 305 is used to identify and track earthquakes of volcanic structures and phase interfaces based on the earthquake reflection coefficient data volume.

[0178] In an optional embodiment, it further includes:

[0179] The filtering module is used to filter the seismic reflection coefficient data.

[0180] In an optional embodiment, the filtering module includes:

[0181] The well-seismic calibration result determination submodule is used to perform well-seismic calibration on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration result;

[0182] The bandpass filter coefficient determination submodule is used to determine the bandpass filter coefficient based on the well vibration calibration results.

[0183] The filtering submodule is used to apply the bandpass filter coefficients to filter the seismic reflection coefficient data volume.

[0184] In an optional implementation, the filtering module 303 includes:

[0185] The algorithm design submodule is used to design the anisotropic diffusion filter smoothing algorithm under the constraints of the dip angle and the azimuth angle of the strata;

[0186] The filtering submodule is used to apply the anisotropic diffusion filtering smoothing algorithm to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0187] In an optional embodiment, the inversion module 304 includes:

[0188] The objective function establishment submodule is used to establish a frequency domain objective function based on the constructed guided filter data volume.

[0189] The data volume acquisition submodule is used to solve the objective function through optimization algorithms to obtain the seismic reflection coefficient data volume.

[0190] In an optional embodiment, the objective function establishment submodule includes:

[0191] The decomposition unit is used to perform parity decomposition on the constructed guided filter data volume to obtain odd components and even components.

[0192] The time-frequency analysis unit is used to perform time-frequency analysis on the constructed guided filter data volume to obtain the spectrum information within the hour window;

[0193] The function establishment unit is used to establish the objective function by combining the spectrum information, the odd component, and the even component.

[0194] Example 4: This embodiment of the invention also provides an electronic device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of a seismic identification method for volcanic mechanism phase interfaces according to any embodiment, including:

[0195] Obtain raw earthquake data;

[0196] Based on the original seismic data, calculate the dip angle and azimuth angle of the strata;

[0197] Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0198] Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques.

[0199] Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

[0200] In an optional embodiment, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0201] The seismic reflection coefficient data volume is then filtered.

[0202] In an optional embodiment, filtering the seismic reflection coefficient data volume includes:

[0203] Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results;

[0204] Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0205] The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

[0206] In an optional embodiment, under the control of the stratum dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including:

[0207] Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed;

[0208] The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0209] In an optional embodiment, seismic reflection coefficient data is obtained by extracting data from the structure-guided filter data volume using inversion techniques, including:

[0210] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0211] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0212] In an optional embodiment, based on the constructed guided-filter data volume, a target function in the frequency domain is established, including:

[0213] The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components;

[0214] Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window;

[0215] The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

[0216] Example 5: This embodiment of the invention also provides a computer storage medium storing a computer program thereon. When the computer program is executed by the processor, it implements the steps of a seismic identification method for a volcanic mechanism phase interface according to any embodiment, including:

[0217] Obtain raw earthquake data;

[0218] Based on the original seismic data, calculate the dip angle and azimuth angle of the strata;

[0219] Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0220] Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques.

[0221] Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

[0222] In an optional embodiment, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0223] The seismic reflection coefficient data volume is then filtered.

[0224] In an optional embodiment, filtering the seismic reflection coefficient data volume includes:

[0225] Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results;

[0226] Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0227] The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

[0228] In an optional embodiment, under the control of the stratum dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including:

[0229] Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed;

[0230] The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0231] In an optional embodiment, seismic reflection coefficient data is obtained by extracting data from the structure-guided filter data volume using inversion techniques, including:

[0232] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0233] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0234] In an optional embodiment, based on the constructed guided-filter data volume, a target function in the frequency domain is established, including:

[0235] The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components;

[0236] Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window;

[0237] The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

[0238] Example 6: This embodiment of the invention also provides a computer program product, on which a computer program is stored. When the computer program is executed by the processor, it implements the steps of a seismic identification method for a volcanic mechanism phase interface according to any embodiment, including:

[0239] Obtain raw earthquake data;

[0240] Based on the original seismic data, calculate the dip angle and azimuth angle of the strata;

[0241] Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume.

[0242] Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques.

[0243] Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

[0244] In an optional embodiment, before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes:

[0245] The seismic reflection coefficient data volume is then filtered.

[0246] In an optional embodiment, filtering the seismic reflection coefficient data volume includes:

[0247] Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results;

[0248] Based on the well vibration calibration results, determine the bandpass filter coefficients;

[0249] The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

[0250] In an optional embodiment, under the control of the stratum dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including:

[0251] Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed;

[0252] The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

[0253] In an optional embodiment, seismic reflection coefficient data is obtained by extracting data from the structure-guided filter data volume using inversion techniques, including:

[0254] Based on the constructed guided filter data volume, a target function in the frequency domain is established;

[0255] The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

[0256] In an optional embodiment, based on the constructed guided-filter data volume, a target function in the frequency domain is established, including:

[0257] The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components;

[0258] Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window;

[0259] The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

[0260] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0261] In the several embodiments provided in this application, it should be understood that the methods, apparatuses, electronic devices, and storage media disclosed in this invention can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0262] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0263] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0264] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0265] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for seismic identification of volcanic structure phase interfaces, characterized in that, include: Obtain raw earthquake data; Based on the original seismic data, calculate the dip angle and azimuth angle of the strata; Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain the structurally guided filtered data volume. Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques. Based on the earthquake reflection coefficient data, earthquake identification and tracking interpretation of volcanic structures and phase interfaces are performed.

2. The seismic identification method for the volcanic structure phase interface according to claim 1, characterized in that, Before the step of identifying and tracking the seismic structure and phase interface based on the seismic reflection coefficient data volume, the method further includes: The seismic reflection coefficient data volume is then filtered.

3. The seismic identification method for the volcanic structure phase interface according to claim 2, characterized in that, The filtering process for the seismic reflection coefficient data volume includes: Well-seismic calibration was performed on the seismic reflection coefficient data volume using the acquired well logging data to obtain the well-seismic calibration results; Based on the well vibration calibration results, determine the bandpass filter coefficients; The bandpass filter coefficients are applied to filter the seismic reflection coefficient data.

4. The seismic identification method for the volcanic structure phase interface according to claim 2, characterized in that, Under the control of the dip angle and the azimuth angle, the original seismic data is subjected to anisotropic diffusion filtering to obtain a structure-guided filtered data volume, including: Under the constraints of the dip angle and the azimuth angle of the formation, the anisotropic diffusion filtering smoothing algorithm is designed; The anisotropic diffusion filtering smoothing algorithm is applied to filter the original seismic data volume to obtain the structure-guided filtered data volume.

5. The seismic identification method for the volcanic structure phase interface according to claim 1, characterized in that, Seismic reflection coefficient data volume is obtained by extracting data from the structured guided filter data volume using inversion techniques, including: Based on the constructed guided filter data volume, a target function in the frequency domain is established; The seismic reflection coefficient data volume is obtained by solving the objective function through an optimization algorithm.

6. The seismic identification method for the volcanic structure phase interface according to claim 5, characterized in that, Based on the constructed guided filter data volume, a target function in the frequency domain is established, including: The constructed guided filter data volume is subjected to parity decomposition to obtain odd components and even components; Time-frequency analysis is performed on the constructed guided filter data volume to obtain the spectral information within the hour window; The objective function is established by combining the spectral information, the odd-numbered components, and the even-numbered components.

7. A seismic identification device for the interface of volcanic structure stages, characterized in that, include: The acquisition module is used to acquire raw seismic data; The calculation module is used to calculate the dip angle and azimuth angle of the strata based on the original seismic data; The filtering module is used to perform anisotropic diffusion filtering on the original seismic data under the control of the dip angle and the azimuth angle to obtain the structurally guided filtered data volume. The inversion module is used to extract the seismic reflection coefficient data from the constructed guided filter data volume using inversion technology. The identification module is used to identify and track earthquakes at the volcanic structure and phase interface based on the earthquake reflection coefficient data.

8. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer-readable instructions that, when executed by the processor, perform the method as described in any one of claims 1-6.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it performs the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-6.

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