A true-surface seismic imaging method, device, equipment and medium

Abstract

Embodiments of the present application disclose a true surface seismic imaging method, device, equipment and medium. The method comprises: obtaining surface geological data; wherein the surface geological data comprises a lithology boundary and spatially discrete occurrence information; establishing a shallow surface layer velocity model according to the surface geological data; determining a seismic data correction amount, a migration imaging starting surface and a full-depth velocity model according to the shallow surface layer velocity model; and obtaining true surface seismic imaging based on the seismic data correction amount, the migration imaging starting surface and the full-depth velocity model. The technical solution can eliminate high-frequency jitter of seismic data, while retaining topography and near-surface velocity variation, realize depth domain pre-stack migration on a true surface migration surface, and thus improve the accuracy of true surface seismic imaging.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration technology, and in particular to a true surface seismic imaging method, apparatus, equipment, and medium. Background Technology

[0002] Depth migration originating from the true surface is a core technology for achieving accurate seismic depth domain imaging in complex regions. In complex mountainous areas, high-frequency jitter in seismic travel time caused by drastically undulating terrain, complex near-surface structures, and actual field measurement errors severely affects the accuracy of depth domain true surface migration and the focusing of the migration results.

[0003] Currently, in seismic depth migration in complex dual-region areas, a two-step method is commonly used to solve the problem of migration across undulating surfaces. First, a smooth undulating surface is determined, and the observation data is corrected to this surface. Then, velocity modeling and migration imaging processing are performed on this surface (Liu Dingjin et al., 2016). There are three commonly used methods for determining the undulating surface and correcting the data: ① Directly smoothing the static correction values ​​of the reference surface for time-domain stacking imaging, separating high and low frequencies, applying the high-frequency values ​​to the seismic data, and using replacement velocities for the low-frequency values ​​to transfer them to the depth domain as the migration starting surface (Zheng Hongming et al., 2005; Lin Boxiang et al., 2005; Wang Shengchun et al., 2018); ② Using a static correction method to address the seismic wave travel time distortion caused by changes in surface elevation and velocity variations in low-velocity zones in the time domain, and then selecting a suitable, generally relatively smooth, elevation surface to correct the data to. After smoothing the surface, migration velocity modeling is performed (Wang Huazhong et al., 2012; Liu Dingjin et al., 2016); ③ A small smooth surface approximating the real surface is established using smoothed surface elevation as the migration reference surface. In the literature, this is usually referred to as the pre-stack depth migration technique with approximate true surface elevation. Its data correction will spatially smooth the static correction amount applied to time-domain imaging, dividing it into low-wavenumber and high-wavenumber components. It is believed that the low-wavenumber component reflects the influence of the velocity and thickness of the low-velocity zone, while the high-wavenumber component reflects the influence of the difference between the shot and receiver within a small trend range (Liu Yuzhu et al., 2012; Guo Lei, 2020). All three methods are based on conventional time-domain static correction processing. Their function is to eliminate the influence of the inter-trace time difference caused by changes in surface elevation, low-velocity zone thickness, and low-velocity zone velocity on seismic imaging. This type of technique assumes that seismic waves propagate vertically in the near-surface medium, and the static correction amount does not change with the burial depth of the reflector layer and the shot-receiver distance. When applied, the seismic traces are shifted as a whole in time. In complex mountainous areas where topography and near-surface velocity fields change drastically, the time shift of data from this type of method manifests as an artificial distortion of the seismic wave travel time in depth migration. Using such data for depth domain velocity estimation results in biases starting from the shallow layer, leading to inaccurate positioning of mid-to-deep structural traps and making it impossible to achieve accurate imaging through true surface depth migration. Summary of the Invention

[0004] This invention provides a true surface seismic imaging method, apparatus, equipment, and medium that can eliminate high-frequency jitter in seismic data while preserving topographic and near-surface velocity variations. It enables depth-domain pre-stack migration on a true surface migration plane, thereby improving the accuracy of true surface seismic imaging.

[0005] According to one aspect of the present invention, a true surface seismic imaging method is provided, comprising:

[0006] Acquire surface geological data; wherein, the surface geological data includes stratigraphic lithological boundaries and spatially discrete occurrence information;

[0007] A shallow surface velocity model was established based on the aforementioned surface geological data.

[0008] Based on the shallow surface velocity model, the seismic data correction, the migration imaging starting surface, and the full-depth velocity model are determined.

[0009] True surface seismic imaging is obtained based on the seismic data correction, the migration imaging starting surface, and the full-depth velocity model.

[0010] Optionally, a shallow surface velocity model is established based on the aforementioned surface geological data, including:

[0011] A three-dimensional geological structure model is established based on the stratigraphic lithological boundary lines and spatially discrete occurrence information;

[0012] A shallow surface velocity model was established based on surface survey micrologging data and the aforementioned three-dimensional geological structure model.

[0013] Optionally, the seismic data correction amount is determined based on the shallow surface velocity model, including:

[0014] The lithological velocity variation characteristics were obtained using the shallow surface velocity model.

[0015] The velocity distribution region is determined based on the aforementioned lithological velocity variation characteristics;

[0016] The seismic data correction amount is determined based on the velocity distribution area; wherein the seismic data correction amount includes shot point and / or receiver point correction amount.

[0017] Optionally, determining the seismic data correction amount based on the velocity distribution region includes:

[0018] For the low-velocity layer velocity distribution area, the correction amount of the receiver point from the surface to the bottom interface of the low-velocity layer is determined using the shallow surface velocity model, and the receiver point correction amount is obtained; the correction amount of the shot point from the firing point to the bottom interface of the low-velocity layer is determined using the shallow surface velocity model, and the shot point correction amount is obtained.

[0019] For the high-velocity layer velocity distribution region, the detector point position remains unchanged. The correction amount from the excitation point position to the ground surface is determined using the shallow layer velocity model, and is used as the shot point correction amount.

[0020] Optionally, determining the migration imaging starting surface based on the shallow layer velocity model includes:

[0021] The lithological velocity variation characteristics were obtained using the shallow surface velocity model.

[0022] The velocity distribution region is determined based on the aforementioned lithological velocity variation characteristics;

[0023] If the velocity distribution area is a low-velocity layer distribution area, then the bottom interface of the low-velocity layer is selected as the starting surface for migration imaging.

[0024] If the velocity distribution area is a high-velocity layer distribution area, then the measurement elevation interface is selected as the starting surface for the migration imaging.

[0025] Optionally, determining the full-depth velocity model based on the shallow-layer velocity model includes:

[0026] The earthquake first arrival travel time is adjusted by using shot point and / or receiver point corrections to obtain the adjusted earthquake first arrival travel time.

[0027] The near-surface velocity model after tomographic inversion is obtained by performing tomographic inversion based on the adjusted earthquake first arrival travel time;

[0028] The near-surface velocity model and the mid-deep reflected wave velocity model are fused together to obtain the full-depth velocity model.

[0029] Optionally, a tomographic inversion model of near-surface velocity is obtained based on the adjusted earthquake first-arrival travel time, including:

[0030] The adjusted first-arrival travel time data were subjected to tomographic inversion using an adaptive weighted tomographic objective function to obtain the tomographically inverted near-surface velocity model.

[0031] Optionally, after obtaining the tomographically inverted near-surface velocity model based on the adjusted earthquake first-arrival travel time, the process also includes:

[0032] By correcting the surface consistency first-arrival residual, the predicted time and the adjusted earthquake first-arrival travel time residuals output by the near-surface velocity model after tomographic inversion are decomposed into surface consistency values ​​to obtain the high-frequency time difference corrections for shot and / or receiver points.

[0033] Optionally, the adaptive weighted tomography objective function is configured as follows:

[0034] J = ||W*(t) pick -tpred )||2

[0035]

[0036] Where J is the adaptive weighted tomography objective function, W is the adaptive weighting factor, and t pick For the corrected initial pickup time, t pred σ represents the initial arrival travel time in the forward modeling, offset represents the offset magnitude, σ represents the stability factor, and γ represents the weight calculation coefficient.

[0037] Optionally, a true surface seismic migration image is obtained based on the seismic data correction, the migration imaging starting surface, and the full-depth velocity model, including:

[0038] The correction values ​​for the shot point and receiver point are applied to the CMP gather or shot gather after wavefield preservation correction to obtain the data before migration.

[0039] The pre-migration data, the starting surface of the migration imaging, and the full-depth velocity model are used to perform migration imaging to obtain true surface seismic images.

[0040] According to another aspect of the present invention, a true surface seismic imaging apparatus is provided, comprising:

[0041] A geological data acquisition module is used to acquire surface geological data; wherein, the surface geological data includes stratigraphic lithological boundaries and spatially discrete occurrence information;

[0042] The model building module is used to build a shallow surface velocity model based on the surface geological data.

[0043] The data determination module is used to determine the seismic data correction, the migration imaging starting surface, and the full-depth velocity model based on the shallow surface velocity model.

[0044] The true surface seismic imaging acquisition module is used to obtain true surface seismic images based on the seismic data correction, the offset imaging starting surface, and the full-depth velocity model.

[0045] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0046] At least one processor; and

[0047] A memory communicatively connected to the at least one processor; wherein,

[0048] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the true surface seismic imaging method according to any embodiment of the present invention.

[0049] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the true surface seismic imaging method according to any embodiment of the present invention.

[0050] The technical solution of this invention involves acquiring surface geological data, including stratigraphic lithological boundaries and spatially discrete attitude information; establishing a shallow surface velocity model based on the surface geological data; determining seismic data correction, migration imaging starting surface, and full-depth velocity model based on the shallow surface velocity model; and obtaining a true surface seismic image based on the seismic data correction, migration imaging starting surface, and full-depth velocity model. This technical solution can eliminate high-frequency jitter in seismic data while preserving topographic and near-surface velocity variations, enabling depth-domain pre-stack migration on a true surface migration surface, thereby improving the accuracy of true surface seismic imaging. Attached Figure Description

[0051] Figure 1 This is a flowchart of a true surface seismic imaging method according to Embodiment 1 of the present invention;

[0052] Figure 2 This is a flowchart of a true surface seismic imaging method according to Embodiment 2 of the present invention;

[0053] Figure 3a This is an example diagram of a single gun provided according to Embodiment 2 of the present invention;

[0054] Figure 3b This is an example diagram of a single shot after wavefield preservation correction according to Embodiment 2 of the present invention;

[0055] Figure 4a This is an example diagram illustrating the existing small smooth surface offset effect provided in Embodiment 2 of the present invention.

[0056] Figure 4b This is an example diagram of the true surface imaging offset effect provided according to Embodiment 2 of the present invention;

[0057] Figure 5a This is an example diagram of an existing small smooth surface offset CRP gather provided according to Embodiment 2 of the present invention;

[0058] Figure 5b This is an example diagram of a true surface imaging migration CRP gather provided according to Embodiment 2 of the present invention;

[0059] Figure 6 This is a schematic diagram of the structure of a true surface seismic imaging device according to Embodiment 3 of the present invention;

[0060] Figure 7 This is a schematic diagram of the structure of an electronic device according to Embodiment 4 of the present invention. Detailed Implementation

[0061] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0062] Example 1

[0063] Figure 1 This is a flowchart of a true surface seismic imaging method provided in Embodiment 1 of the present invention. This embodiment is applicable to the case of pre-stack depth migration imaging of the true surface. The method can be executed by a true surface seismic imaging device, and specifically includes the following steps:

[0064] Step 110: Obtain relevant surface geological data.

[0065] Specifically, the surface geological data refers to surface geological data, including stratigraphic lithological boundaries and spatially discrete attitude information. In this embodiment, near-surface stratigraphic lithological boundaries and spatially discrete attitude information can be obtained using high-precision remote sensing data, surface geological survey data, and surface digital outcrops, or other surface geological data. High-precision remote sensing data can be satellite remote sensing imagery of the Earth's surface. Surface geological survey data can be geological survey data of the surface layer in each region, such as basic structural features like surface lithology and stratigraphic dip. Surface digital outcrop data can include information such as the thickness, lithology, and strike of surface digital outcrops. In this embodiment, near-surface stratigraphic lithological boundaries and spatially discrete attitude information can be obtained.

[0066] Step 120: Establish a shallow surface velocity model based on the aforementioned surface geological data.

[0067] The shallow velocity model can be understood as being used to determine correction information for seismic data and for velocity analysis. The shallow layer can be understood as the measurement depth range of micro-logging, roughly from the surface to a depth of ten to twenty meters. The near-surface layer has a relatively larger depth range, including not only low-velocity layers but also high-velocity layers within a certain depth range. The near-surface layer can be understood as the surface layer within a range of approximately five hundred or six hundred meters, or it can be set according to the actual area by surveying technicians.

[0068] The shallow surface velocity model can include features such as lithological velocity variations. In this embodiment, a shallow surface velocity model can be established based on near-surface lithological boundaries and spatially discrete attitude information.

[0069] In this embodiment, optionally, establishing a shallow surface velocity model based on the surface geological data includes: establishing a near-surface three-dimensional geological structure model based on the near-surface lithological boundary line and spatial discrete occurrence information; and establishing a shallow surface velocity model based on surface survey micrologging data and the three-dimensional geological structure model.

[0070] The three-dimensional geological structure model can be established based on the near-surface lithological boundaries and spatially discrete occurrence information. Surface survey micrologging data can be obtained through field surveys of the thickness and velocity of different distribution areas of the surface layer.

[0071] The shallow surface velocity model can be established based on surface survey micrologging data and a three-dimensional geological structure model. In this embodiment, the surface survey micrologging data can be directly obtained. Specifically, in this embodiment, the shallow surface velocity model can be obtained by interpolating the velocity information of different distribution areas in the surface survey micrologging data using a three-dimensional geological structure model. The interpolation method can be Kriging interpolation, or other interpolation methods.

[0072] In this embodiment, a near-surface three-dimensional geological structure model can be established based on the near-surface stratigraphic lithological boundaries and spatially discrete occurrence information. A shallow surface velocity model is then established based on surface survey micrologging data and the aforementioned three-dimensional geological structure model. This setup facilitates the subsequent calculation of seismic data corrections and other related tasks. Furthermore, this embodiment utilizes high-precision remote sensing data, surface geological survey data, and surface digital outcrops to constrain the surface survey micrologging data, establishing a high-precision shallow surface velocity model that is consistent with the actual near-surface geological structure and avoids the bullseye phenomenon that occurs with simple spatial interpolation.

[0073] Step 130: Determine the seismic data correction, migration imaging starting surface, and full-depth velocity model based on the shallow velocity model.

[0074] Seismic data correction can be understood as correcting the seismic imaging gather data used for seismic imaging. For example, the pre-migration seismic data can be corrected based on the low-velocity layer correction amount established by micrologging and the correction amount from the decomposition of the first arrival residual. The migration imaging starting surface can be understood as the starting surface of the seismic migration imaging, and different starting surfaces can be set according to different surface distribution areas. The full-depth velocity model can be used as the velocity model for pre-stack depth migration originating from the surface. In this embodiment, the full-depth velocity model can be determined based on the shallow surface velocity model. In this embodiment, the seismic data correction amount, the migration imaging starting surface, and the full-depth velocity model can be determined based on the shallow surface velocity model.

[0075] In this embodiment, optionally, determining the seismic data correction amount based on the shallow surface velocity model includes: obtaining lithological velocity variation characteristics through the shallow surface velocity model; determining the velocity distribution area based on the lithological velocity variation characteristics; and determining the seismic data correction amount based on the velocity distribution area; wherein the seismic data correction amount includes shot point and / or receiver point correction amounts.

[0076] The lithological velocity variation characteristics can be understood as the characteristic data of near-surface lithological velocity changes. In this embodiment, near-surface lithological velocity variation characteristics can be obtained through a shallow-layer velocity model. The distribution area can be determined based on the surface lithological velocity variation characteristics. The distribution area can include the distribution areas of low-velocity layers, decreasing-velocity layers, and high-velocity layers. For example, a low-velocity layer can refer to a velocity variation of less than or equal to 1 km / s; a decreasing-velocity layer can refer to a velocity variation of greater than 1 km / s to greater than or equal to 2 km / s; a high-velocity layer can refer to a velocity variation of greater than 2 km / s; a decreasing-velocity layer can be understood as a transition area between low-velocity and high-velocity layers. Seismic data corrections can include shot point corrections or receiver point corrections, or both. In this embodiment, seismic data corrections can be determined based on the different distribution areas of near-surface lithological velocity variation characteristics. This setting in this embodiment allows for the separate determination of shot point and / or receiver point corrections according to different surface distribution areas, which can eliminate the influence of local low-velocity anomalies on migration imaging.

[0077] In this embodiment, optionally, determining the seismic data correction amount based on the velocity distribution area includes: for the low-velocity layer velocity distribution area, using the shallow surface velocity model to determine the correction amount of the receiver point from the surface to the bottom interface of the low-velocity layer, obtaining the receiver point correction amount; using the shallow surface velocity model to determine the correction amount of the shot point from the current position to the bottom interface of the low-velocity layer, as the shot point correction amount; for the high-velocity layer velocity distribution area, using the shallow surface velocity model to determine the correction amount of the shot point from the current position to the surface, as the shot point correction amount. The receiver point correction amount and the shot point correction amount can be different depending on the distribution area. Both the receiver point correction amount and the shot point correction amount can be determined based on the shallow surface velocity model. In this embodiment, for the low-velocity layer velocity distribution area, the correction amount of the receiver point from the surface to the bottom interface of the low-velocity layer can be determined using the shallow surface velocity model, thus obtaining the receiver point correction amount; the correction amount of the shot point from the excitation point position to the bottom interface of the low-velocity layer can be determined using the shallow surface velocity model, as the shot point correction amount; for the high-velocity layer velocity distribution area, the receiver point position remains unchanged, and the correction amount of the shot point from the excitation point position to the surface can be determined using the shallow surface velocity model, as the shot point correction amount.

[0078] Specifically, when the surface is a low-velocity zone, the shallow surface velocity model can be used to calculate the model correction amount from the surface to the low-velocity layer bottom interface of the receiver point. If the shot point is located above the low-velocity bottom interface of the surface survey, the model correction amount from the shot point location to the low-velocity layer bottom interface is calculated and used as the shot point correction amount. If the shot point is located below the low-velocity bottom interface of the surface survey, the high-velocity layer velocity of the shallow surface velocity model is used to correct the shot point upwards to the low-velocity bottom interface of the surface survey, and this is used as the shot point correction amount. In this embodiment, when the receiver point is located in a high-velocity outcrop area, the original surface location of the data remains unchanged. The shot point uses the shallow surface velocity model and well depth to calculate the correction amount and corrects the shot point to the surface, which is used as the shot point correction amount. In this embodiment, the shallow surface velocity model determines the correction amount of the shot point and / or receiver point and corrects the data to the low-velocity bottom interface of the surface survey. This data correction amount can eliminate the influence of local low-velocity anomalies and keep the original surface location of the data unchanged in the high-velocity outcrop area.

[0079] In this embodiment, the correction amount of shot point and / or receiver point can be determined according to the different distribution areas of the ground surface, which can realize pre-stack data correction and facilitate true ground migration imaging.

[0080] In this embodiment, optionally, determining the migration imaging starting surface based on the shallow surface velocity model includes: obtaining lithological velocity variation characteristics through the shallow surface velocity model; determining the velocity distribution area based on the lithological velocity variation characteristics; if the velocity distribution area is a low-velocity layer distribution area, then selecting the bottom interface of the low-velocity layer as the migration imaging starting surface; if the velocity distribution area is a high-velocity layer distribution area, then selecting the measurement elevation interface as the migration imaging starting surface. The distribution area may include low-velocity layers, decreasing-velocity layers, and high-velocity layers. The migration imaging starting surface can be understood as the interface at which true surface seismic imaging begins. The migration imaging starting surface can be determined based on the distribution area where the near-surface lithological velocity variation characteristics are located. In this embodiment, the velocity distribution area can be determined based on the lithological velocity variation characteristics. Specifically, in this embodiment, the near-surface lithological velocity variation characteristics can be obtained based on the established shallow surface velocity model. Based on these lithological velocity variation characteristics, the velocity distribution area is determined. Then, if the surface velocity distribution area is a low-velocity layer distribution area, the bottom interface of the low-velocity zone is selected as the true surface migration imaging starting surface. If the velocity distribution area is a high-velocity layer distribution area, the measured elevation can be selected as the true surface migration imaging starting surface. Furthermore, a high-velocity outcrop area can be a type of high-velocity layer. In this embodiment, the migration imaging starting surface determined in this way is basically consistent with the actual surface elevation compared to a conventional migration surface generated based on a numerical smoothing algorithm.

[0081] Step 140: Obtain true surface seismic imaging based on the seismic data correction, the migration imaging starting surface, and the full-depth velocity model.

[0082] True surface seismic imaging, that is, real seismic imaging of the Earth's surface.

[0083] In this embodiment, true surface seismic imaging can be obtained based on seismic data correction, migration imaging starting surface, and full-depth velocity model.

[0084] Specifically, in this embodiment, the pre-migration data can be corrected based on the shot point and / or receiver point model correction and the first arrival tomography residual time difference decomposition. Then, true surface seismic imaging is obtained by migration method based on the corrected pre-migration seismic data, the migration imaging starting surface, and the full-depth velocity model.

[0085] The technical solution of this invention involves acquiring surface geological data, including stratigraphic lithological boundaries and spatially discrete attitude information; establishing a shallow surface velocity model based on the surface geological data; determining seismic data correction, migration imaging starting surface, and full-depth velocity model based on the shallow surface velocity model; and obtaining a true surface seismic image based on the seismic data correction, migration imaging starting surface, and full-depth velocity model. This technical solution can eliminate high-frequency jitter in seismic data while preserving topographic and near-surface velocity variations, enabling depth-domain pre-stack migration on a true surface migration surface, thereby improving the accuracy of true surface seismic imaging.

[0086] Example 2

[0087] Figure 2 This is a flowchart of a true surface seismic imaging method according to Embodiment 2 of the present invention. This embodiment is based on the above embodiment and optimized. Specifically, the optimization is as follows: determining the full-depth velocity model according to the shallow layer velocity model includes: adjusting the earthquake first arrival travel time using shot point and / or receiver point corrections to obtain the adjusted earthquake first arrival travel time; performing tomographic inversion based on the adjusted earthquake first arrival travel time to obtain the tomographically inverted near-surface velocity model; and fusing the tomographically inverted near-surface velocity model with the mid-deep reflected wave velocity model to obtain the full-depth velocity model.

[0088] Step 210: Obtain relevant surface geological data.

[0089] The surface geological data includes stratigraphic lithological boundaries and spatially discrete occurrence information;

[0090] Step 220: Establish a shallow surface velocity model based on the aforementioned surface geological data.

[0091] Step 230: Determine the seismic data correction amount and the migration imaging starting surface based on the shallow surface velocity model. The seismic data correction amount includes shot point and / or receiver point correction amounts.

[0092] Step 240: Adjust the earthquake first arrival travel time using shot point and / or receiver point corrections to obtain the adjusted earthquake first arrival travel time.

[0093] The first arrival travel time (FAT) of an earthquake can be understood as the time it takes for a seismic wave to travel from the excitation point through the near-surface medium to the receiver point, reflecting changes in the near-surface velocity structure characteristics. In this embodiment, the FAT can be adjusted using shot point and / or receiver point corrections to obtain an adjusted FAT.

[0094] For example, the effect of wavefield preservation correction application is as follows: Figure 3b As shown, where, Figure 3a This is an example diagram of the original single-gun design; Figure 3b This is an example diagram of a single shot with wavefield correction using seismic correction. In this embodiment, calibration is performed during the earthquake's first arrival travel time, which can largely eliminate the influence of local near-surface low-velocity layers, and the corrected position of the corresponding data obtained from the first correction data can be used as the starting position of the shot and / or receiver.

[0095] Step 250: Based on the adjusted earthquake first arrival travel time and the migration imaging starting surface, perform tomographic inversion to obtain the tomographically inverted near-surface velocity model.

[0096] In this context, tomographic inversion can be understood as performing tomographic inversion using an adaptive weighted tomographic objective function. In this embodiment, the adjusted first-arrival travel time and the migration imaging starting surface can be used as the tomographic shot-receiver starting surface to obtain the tomographically inverted near-surface velocity model. Alternatively, this embodiment can obtain the tomographically inverted near-surface velocity model by performing high-precision first-arrival travel time tomographic inversion.

[0097] In this embodiment, optionally, the near-surface velocity model after tomographic inversion is obtained based on the adjusted earthquake first-arrival travel time, including: performing tomographic inversion on the adjusted first-arrival travel time data using an adaptive weighted tomographic objective function to obtain the near-surface velocity model after tomographic inversion.

[0098] The adaptive weighted tomography objective function can be understood as adding an adaptive weight correction component to the iterative calculation formula for the grid slowness correction value, providing an objective function based on ray length correction for the grid slowness correction value. In this embodiment, the adaptive weighted tomography objective function can be used to perform tomographic inversion on the earthquake first-arrival travel time, thereby obtaining the tomographically inverted near-surface velocity model. The tomographically inverted near-surface velocity model can be a model with a deeper depth than the shallow surface velocity model.

[0099] This embodiment employs adaptive weighted first-arrival travel-time tomography, incorporating an adaptive weight correction component into the iterative calculation formula for the grid slowness correction value. This provides a ray length-based correction for the grid slowness correction value, resolving the issue of varying travel-time errors due to different ray lengths. In this embodiment, the seismic first-arrival travel-time tomography velocity inversion aims to better meet the requirements of full-depth velocity modeling, fully utilizing large-offset travel-time information to invert the deepest possible surface model.

[0100] In this embodiment, optionally, the adaptive weighted tomography objective function is configured as follows:

[0101] J = ||W*(t)pick -t pred )||2

[0102]

[0103] Where J is the adaptive weighted tomography objective function, W is the adaptive weighting factor, and t pick For the corrected initial pickup time, t pred Here, σ represents the initial travel time in the forward modeling, offset represents the offset magnitude, σ is the stability factor, and γ is the weight calculation coefficient. The stability factor can be set by technical personnel.

[0104] In this embodiment, the adaptive weighting factor can be automatically adjusted according to the ray length and ray density, overcoming the problem that traditional tomography techniques, when using large offset information, distribute deep errors to shallow layers, resulting in excessively high shallow velocities. This allows for the use of full offsets in seismic tomography inversion, enabling the inversion of deeper models with higher accuracy.

[0105] In this embodiment, optionally, after obtaining the near-surface velocity model after tomographic inversion based on the adjusted earthquake first arrival travel time, the method further includes: performing surface consistency decomposition on the prediction time output by the tomographic inversion near-surface velocity model and the adjusted earthquake first arrival travel time residual through surface consistency first arrival residual correction, and decomposing it to obtain the high-frequency time difference correction amount of shot and / or receiver points.

[0106] Furthermore, in this embodiment, the residual decomposition of the first-arrival tomography inversion can be performed. Through the surface consistency first-arrival residual correction, the prediction time and picking time residuals of the final model output obtained during the first-arrival travel time inversion are decomposed into surface consistency. The high-frequency time difference correction amount of the shot and / or receiver points is obtained, which can generate surface consistency travel time error between the obtained inversion model and the real model. This time difference is a high-frequency variation amount, which can eliminate the data mismatch problem caused by the high-frequency missingness of the velocity model to a certain extent.

[0107] Step 260: The near-surface velocity model obtained by tomographic inversion is fused with the mid-deep reflected wave velocity model to obtain the full-depth velocity model.

[0108] The fusion process can be understood as a weighted summation or averaging operation of the model parameters. The mid-deep reflected wave velocity model in this embodiment can be directly obtained and used. In this embodiment, the high-precision near-surface velocity model obtained from tomographic inversion can be weighted and summed or averaged with the mid-deep reflected wave velocity model to obtain a full-depth velocity model originating from the true surface.

[0109] Step 270: Obtain true surface seismic imaging based on the seismic data correction, the migration imaging starting surface, and the full-depth velocity model.

[0110] In this embodiment, optionally, obtaining true surface seismic migration imaging based on the seismic data corrections, the migration imaging starting surface, and the full-depth velocity model includes: applying the shot and receiver point corrections calculated based on the shallow surface model established by micrologging, and the high-frequency time difference corrections for shot and / or receiver points obtained from the first-arrival residual decomposition of tomographic inversion, to the pre-migration seismic data to obtain wavefield-preserving corrected CMP gathers or shot gathers, thus obtaining pre-migration data; and performing migration imaging using the pre-migration data, the migration imaging starting surface, and the full-depth velocity model to obtain true surface seismic imaging. The pre-migration data can be data obtained by applying the shot and receiver point corrections to the wavefield-preserving corrected CMP gathers or shot gathers. The migration method can be understood as a method for performing migration imaging; for example, the migration method in this embodiment can be a Kirchhoff migration, ray beam migration, or RTM depth migration method. Specifically, in this embodiment, the seismic data correction can be applied to the pre-migration data such as CMP gathers or shot gathers after wavefield preservation correction, and then the migration imaging starting surface and the full-depth velocity model are used to perform migration imaging to obtain true surface seismic imaging.

[0111] For example, a comparison of the profile effects of different offset methods is shown in the following figure. Figure 4a and Figure 4b As shown; where, Figure 4a This is an example image of the existing small smooth surface migration effect, which is an example image obtained by using a small smooth surface that approximates the real surface as the migration reference surface, which is usually referred to in the literature as the pre-stack depth migration technique of approximate real surface. Figure 4b This is an example diagram of the true surface imaging migration effect, which is an example diagram of the profile effect obtained by the true surface imaging migration in the technical solution of this embodiment.

[0112] For example, a comparison of the gather performance of different offset methods is shown in the following figure. Figure 5a and Figure 5b As shown; where Figure 5a Example diagram of existing small smooth surface offset CRP gather; Figure 5b Example image of a CRP gather for true surface imaging migration.

[0113] In this embodiment, the true surface migration surface is constructed starting from the original surface, with the interface of the low-velocity weathering layer used locally as the starting surface for depth migration. This eliminates the influence of local low-velocity anomalies on migration imaging. At the same time, the data correction satisfies the static correction vertical exit assumption, maintaining the travel time characteristics of the seismic wavefield. This achieves complete matching between the seismic data, velocity model, and migration starting surface. The wavefield fidelity correction is applied to the pre-migration data, thus correcting the seismic data onto the true surface migration surface that eliminates high-frequency jitter in surface elevation and preserves topography and near-surface changes. Secondly, a near-surface velocity model is established by inverting high-precision near-surface structures and fusing it with a mid-to-deep reflection wave velocity model to create a full-depth velocity model. This improves the modeling accuracy of shallow models and enhances the accuracy of depth migration imaging.

[0114] The technical solution of this invention involves acquiring surface geological data, including stratigraphic lithological boundaries and spatially discrete attitude information; establishing a shallow velocity model based on the surface geological data; determining seismic data corrections and a migration imaging starting surface based on the shallow velocity model; adjusting the seismic first arrival travel time using shot point and / or receiver point corrections to obtain an adjusted seismic first arrival travel time; performing tomographic inversion based on the adjusted seismic first arrival travel time and the new shot-receiver starting surface to obtain a tomographically inverted near-surface velocity model; fusing the tomographically inverted near-surface velocity model with a mid-deep reflected wave velocity model to obtain a full-depth velocity model; and obtaining a true surface seismic image based on the seismic data corrections, the migration imaging starting surface, and the full-depth velocity model. This technical solution can eliminate high-frequency jitter in seismic data while preserving topographic and near-surface velocity variations, achieving depth-domain pre-stack migration on a true surface migration surface, thereby improving the accuracy of true surface seismic imaging.

[0115] Example 3

[0116] Figure 6 This is a schematic diagram of a true surface seismic imaging device provided in Embodiment 3 of the present invention. This device can execute the real-time processing method for streaming data provided in any embodiment of the present invention, and possesses the corresponding functional modules and beneficial effects for executing the method. For example... Figure 6 As shown, the device includes:

[0117] The geological data acquisition module 610 is used to acquire surface geological data; wherein, the surface geological data includes stratigraphic lithological boundaries and spatial discrete occurrence information.

[0118] The model building module 620 is used to build a shallow surface velocity model based on the surface geological data.

[0119] The data determination module 630 is used to determine the seismic data correction amount, the migration imaging starting surface, and the full-depth velocity model based on the shallow velocity model.

[0120] The true surface seismic imaging acquisition module 640 is used to obtain true surface seismic images based on the seismic data correction, the offset imaging starting surface, and the full-depth velocity model.

[0121] Optional, model building module 620, specifically used for:

[0122] A three-dimensional geological structure model is established based on the stratigraphic lithological boundary lines and spatially discrete occurrence information;

[0123] A shallow surface velocity model was established based on surface survey micrologging data and the aforementioned three-dimensional geological structure model.

[0124] Optionally, the data determination module 630 includes:

[0125] The lithological velocity variation characteristic acquisition unit is used to acquire lithological velocity variation characteristics through the shallow surface velocity model;

[0126] A velocity distribution region determination unit is used to determine the velocity distribution region based on the lithological velocity variation characteristics.

[0127] The seismic data correction determination unit is used to determine the seismic data correction based on the velocity distribution area; wherein the seismic data correction includes shot point and / or receiver point correction.

[0128] Optional, seismic data correction determination unit, specifically used for:

[0129] For the low-velocity layer velocity distribution area, the correction amount of the receiver point from the surface to the bottom interface of the low-velocity layer is determined using the shallow surface velocity model, and the receiver point correction amount is obtained; the correction amount of the shot point from the firing point to the bottom interface of the low-velocity layer is determined using the shallow surface velocity model, and the shot point correction amount is obtained.

[0130] For the high-velocity layer velocity distribution region, the detector point position remains unchanged. The correction amount from the excitation point position to the ground surface is determined using the shallow layer velocity model, and is used as the shot point correction amount.

[0131] Optionally, the data determination module 630 is specifically used for:

[0132] The lithological velocity variation characteristics were obtained using the shallow surface velocity model.

[0133] The velocity distribution region is determined based on the aforementioned lithological velocity variation characteristics;

[0134] If the velocity distribution area is a low-velocity layer distribution area, then the bottom interface of the low-velocity layer is selected as the starting surface for migration imaging.

[0135] If the velocity distribution area is a high-velocity layer distribution area, then the measured elevation interface is selected as the starting surface for the migration imaging. Optionally, the data determination module 630 includes:

[0136] The data adjustment unit is used to adjust the earthquake first arrival travel time using shot point and / or receiver point corrections to obtain the adjusted earthquake first arrival travel time.

[0137] The tomographic inversion unit is used to perform tomographic inversion based on the adjusted earthquake first arrival travel time to obtain the tomographic inversion near-surface velocity model;

[0138] The model fusion processing unit is used to fuse the near-surface velocity model after tomographic inversion with the mid-deep reflected wave velocity model to obtain a full-depth velocity model.

[0139] Optional, tomographic inversion unit, specifically used for:

[0140] The adjusted first-arrival travel time data are subjected to tomographic inversion using an adaptive weighted tomographic objective function to obtain the tomographically inverted near-surface velocity model. Optionally, the apparatus further includes:

[0141] The data decomposition module is used to perform tomographic inversion based on the adjusted earthquake first arrival travel time to obtain the tomographically inverted near-surface velocity model. Then, through surface consistency first arrival residual correction, the predicted time output by the tomographically inverted near-surface velocity model and the adjusted earthquake first arrival travel time residual are decomposed into surface consistency to obtain the high-frequency time difference correction amount for shot and / or receiver points.

[0142] Optionally, the adaptive weighted tomography objective function is used in the following manner:

[0143] J = ||W*(t) pick -t pred )||2

[0144]

[0145] Where J is the adaptive weighted tomography objective function, W is the adaptive weighting factor, and t pick For the corrected initial pickup time, t pred σ represents the initial arrival travel time in the forward modeling, offset represents the offset magnitude, σ represents the stability factor, and γ represents the weight calculation coefficient.

[0146] Optional, the true surface seismic imaging acquisition module 640, specifically used for:

[0147] The corrections for shot points and receiver points calculated based on the shallow layer model established by micrologging, and the high-frequency time difference corrections for shot and / or receiver points from the first arrival residual decomposition of tomographic inversion, are applied to the pre-migration seismic data to obtain wavefield-preserving corrected CMP gathers or shot gathers, thus obtaining the pre-migration data.

[0148] The pre-migration data, the starting surface for migration imaging, and the full-depth velocity model are used to perform migration imaging to obtain a true surface seismic image. The above-described apparatus can execute the methods provided in all the foregoing embodiments of the present invention, possessing the corresponding functional modules and beneficial effects for executing the above methods. Technical details not described in detail in this embodiment can be found in the methods provided in all the foregoing embodiments of the present invention.

[0149] Example 4

[0150] Figure 7 This is a schematic diagram of an electronic device according to Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0151] like Figure 7 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0152] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0153] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as true surface seismic imaging methods.

[0154] In some embodiments, the true surface seismic imaging method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the true surface seismic imaging method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the true surface seismic imaging method by any other suitable means (e.g., by means of firmware).

[0155] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0156] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0157] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0158] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0159] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0160] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0161] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0162] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A true surface seismic imaging method, characterized in that, include: Acquire surface geological data; wherein, the surface geological data includes stratigraphic lithological boundaries and spatially discrete occurrence information; A shallow surface velocity model was established based on the aforementioned surface geological data. Based on the shallow surface velocity model, the seismic data correction, the migration imaging starting surface, and the full-depth velocity model are determined. True surface seismic imaging is obtained based on the seismic data correction, the migration imaging starting surface, and the full-depth velocity model. Determining the migration imaging starting surface based on the shallow surface velocity model includes: obtaining lithological velocity variation characteristics through the shallow surface velocity model; determining the velocity distribution area based on the lithological velocity variation characteristics; if the velocity distribution area is a low-velocity layer distribution area, then selecting the bottom interface of the low-velocity layer as the migration imaging starting surface; if the velocity distribution area is a high-velocity layer distribution area, then selecting the measurement elevation interface as the migration imaging starting surface. Determining the full-depth velocity model based on the shallow-surface velocity model includes: adjusting the earthquake first-arrival travel time using shot point and / or receiver point corrections to obtain the adjusted first-arrival travel time; performing tomographic inversion on the adjusted first-arrival travel time data using an adaptive weighted tomographic objective function to obtain the tomographically inverted near-surface velocity model; and fusing the near-surface velocity model with the mid-deep reflected wave velocity model to obtain the full-depth velocity model; the adaptive weighted tomographic objective function is performed as follows: ； ； Where J is the adaptive weighted tomography objective function, W is the adaptive weighting factor, and t pick For the corrected initial pickup time, t pred σ represents the initial arrival travel time in the forward modeling, offset represents the offset magnitude, σ represents the stability factor, and γ represents the weight calculation coefficient.

2. The method according to claim 1, characterized in that, A shallow surface velocity model is established based on the aforementioned surface geological data, including: A three-dimensional geological structure model is established based on the stratigraphic lithological boundary lines and spatially discrete occurrence information; A shallow surface velocity model was established based on surface survey micrologging data and the aforementioned three-dimensional geological structure model.

3. The method according to claim 1, characterized in that, The seismic data correction amount is determined based on the shallow surface velocity model, including: The lithological velocity variation characteristics were obtained using the shallow surface velocity model. The velocity distribution region is determined based on the aforementioned lithological velocity variation characteristics; The seismic data correction amount is determined based on the velocity distribution area; the shallow velocity model data correction amount includes shot point and / or receiver point correction amounts.

4. The method according to claim 3, characterized in that, Determining seismic data corrections based on the velocity distribution region includes: For the low-velocity layer velocity distribution area, the correction amount of the receiver point from the surface to the bottom interface of the low-velocity layer is determined using the shallow surface velocity model, and the receiver point correction amount is obtained; the correction amount of the shot point from the firing point to the bottom interface of the low-velocity layer is determined using the shallow surface velocity model, and the shot point correction amount is obtained. For the high-velocity layer velocity distribution region, the detector point position remains unchanged. The correction amount from the excitation point position to the ground surface is determined using the shallow layer velocity model, and is used as the shot point correction amount.

5. The method according to claim 1, characterized in that, After obtaining the tomographic inversion model of near-surface velocity based on the adjusted earthquake first-arrival travel time, the following steps are also included: By correcting the surface consistency first-arrival residual, the predicted time output by the near-surface velocity model after tomographic inversion and the adjusted earthquake first-arrival travel time residual are decomposed into surface consistency values ​​to obtain the high-frequency time difference correction values ​​for shot and / or receiver points.

6. The method according to claim 1, characterized in that, Based on the aforementioned seismic data corrections, the migration imaging starting surface, and the full-depth velocity model, a true surface seismic migration image is obtained, including: The correction values ​​for the shot point and receiver point are applied to the CMP gather or shot gather after wavefield preservation correction to obtain the data before migration. The pre-migration data, the starting surface of the migration imaging, and the full-depth velocity model are used to perform migration imaging to obtain true surface seismic images.

7. A true surface seismic imaging device, characterized in that, The apparatus is used to perform the true surface seismic imaging method according to claim 1, the apparatus comprising: A geological data acquisition module is used to acquire surface geological data; wherein, the surface geological data includes stratigraphic lithological boundaries and spatially discrete occurrence information; The model building module is used to build a shallow surface velocity model based on the surface geological data. The data determination module is used to determine the seismic data correction, the migration imaging starting surface, and the full-depth velocity model based on the shallow surface velocity model. The true surface seismic imaging acquisition module is used to obtain true surface seismic images based on the seismic data correction, the offset imaging starting surface, and the full-depth velocity model.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the true surface seismic imaging method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the true surface seismic imaging method according to any one of claims 1-6.

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