Ultra-shallow well control change grid modeling method and device

Abstract

The invention provides an ultra-shallow well control change grid modeling method and device, and belongs to the technical field of oilfield development. The ultra-shallow well control variable grid modeling method comprises the following steps: obtaining an overall initial model of a full imaging space according to logging information of twin-well micro-logging meeting a preset condition, and obtaining a first pre-stack data volume of the ultra-shallow layer according to the overall initial model of the full imaging space; processing the first ultra-shallow pre-stack data volume to obtain a second ultra-shallow pre-stack data volume, obtaining an ultra-shallow initial model according to the second ultra-shallow pre-stack data volume, and processing the ultra-shallow initial model and the second ultra-shallow pre-stack data volume to obtain a third ultra-shallow pre-stack data volume and an ultra-shallow depth domain initial model; performing iterative updating according to the third ultra-shallow layer pre-stack data volume and the ultra-shallow layer depth domain initial model to obtain an ultra-shallow layer depth domain precise model; and carrying out model fusion on the ultra-shallow layer depth domain accurate model and the full-imaging space overall initial model to obtain a full-space speed accurate model.

Description

Technical Field

[0001] The present invention relates to the technical field of oilfield development, and particularly to a modeling method for ultra-shallow well control variable grid and a device for ultra-shallow well control variable grid modeling. Background Art

[0002] In the development of conventional oil and gas reservoirs, unconventional oil and gas reservoirs, and new energy, modeling is an important means for fine reservoir description and real-time monitoring. With the continuous complexity of development targets, the accuracy requirements for ultra-shallow target modeling are constantly increasing. At the same time, 3D seismic technology is required for the modeling and imaging in the shallow layer with few wells. Usually, the initial model of the ultra-shallow layer can draw on the low-frequency model obtained by well-controlled tomography inversion, and the high-precision seismic imaging results can also verify the correctness of the model and whether it conforms to geological understanding. In complex ultra-shallow development application cases, accurate shallow imaging results are required as important basic data to support development research. However, when modeling, the real difficulty is not the imaging method itself, but whether a high-precision model can be obtained, especially for ultra-shallow models.

[0003] With the significant acceleration of new energy exploration and development, the accuracy requirements for ultra-shallow models are getting higher and higher. The initial model in the dense well pattern area comes from the construction of well information, and the initial model in the area with few wells comes from seismic data tomography inversion. However, due to the lack of effective seismic signals and available information in the shallow layer, the insufficient ray density in the unified grid shallow layer leads to the inability to establish an accurate model by conventional methods. Summary of the Invention

[0004] To solve the above technical defects, the present invention provides a modeling method and device for ultra-shallow well control variable grid. The modeling method for ultra-shallow well control variable grid performs initial modeling based on the logging data of dual-well micro-logging to obtain an overall initial model of the full imaging space. By intercepting the overall initial model of the full imaging space, a first ultra-shallow pre-stack data volume is obtained. After precision processing of the intercepted first ultra-shallow pre-stack data volume, tomography inversion is performed to obtain an initial model in the ultra-shallow depth domain. The initial model in the ultra-shallow depth domain is iteratively updated to solve the problem of low accuracy in shallow layer modeling of pre-stack depth migration, and to provide a high-precision velocity model for accurate seismic imaging of the ultra-shallow layer.

[0005] The first aspect of the embodiment of the present invention provides a modeling method for ultra-shallow well control variable grid, which is applied to conventional energy, unconventional energy, and new energy. The method includes:

[0006] Obtain the logging data of dual-well micro-logging that meet the preset conditions and 3D pre-stack seismic data within the target area;

[0007] Obtain an overall initial model of the full imaging space based on the logging data of dual-well micro-logging that meet the preset conditions, and obtain a first ultra-shallow pre-stack data volume based on the overall initial model of the full imaging space and the 3D pre-stack seismic data;

[0008] Perform precision processing on the first ultra-shallow pre-stack data volume to obtain a second ultra-shallow pre-stack data volume. Perform joint refraction and reflection tomography processing on the second ultra-shallow pre-stack data volume to obtain an initial ultra-shallow model. Process the depth unit of the initial ultra-shallow model and the depth unit of the second ultra-shallow pre-stack data volume to obtain a third ultra-shallow pre-stack data volume and an initial ultra-shallow depth domain model;

[0009] Perform iterative update based on the third ultra-shallow pre-stack data volume and the initial ultra-shallow depth domain model to obtain an updated ultra-shallow depth domain model. Perform precision processing on the updated ultra-shallow depth domain model to obtain an accurate ultra-shallow depth domain model;

[0010] Perform model fusion on the accurate ultra-shallow depth domain model and the overall initial full imaging space model to obtain an accurate full space velocity model.

[0011] In the embodiment of the present invention, obtaining the overall initial full imaging space model according to the logging data of the dual-well micro-logging that meets the preset conditions includes:

[0012] Perform surface layer modeling according to the logging data of the dual-well micro-logging that meets the preset conditions to obtain a surface layer model;

[0013] Combine the pre-obtained initial velocity model in the depth domain with the surface layer model to obtain the overall initial full imaging space model.

[0014] In the embodiment of the present invention, obtaining the first ultra-shallow pre-stack data volume according to the overall initial full imaging space model and the three-dimensional pre-stack seismic data includes:

[0015] Determine the top interface of the underground high-velocity layer according to the overall initial full imaging space model, and determine the shallow bottom surface according to the top interface of the underground high-velocity layer;

[0016] Obtain the first ultra-shallow pre-stack data volume according to the shallow bottom surface and the three-dimensional pre-stack seismic data.

[0017] In the embodiment of the present invention, performing precision processing on the first ultra-shallow pre-stack data volume to obtain a second ultra-shallow pre-stack data volume includes:

[0018] Perform upsampling on the first ultra-shallow pre-stack data volume at the first preset sampling interval to obtain the upsampled first ultra-shallow pre-stack data volume;

[0019] Update the original parameter values of the first seismic acquisition observation system according to the first preset sampling interval to obtain new parameter values and a second seismic acquisition observation system corresponding to the new parameter values;

[0020] In the second seismic acquisition observation system, matching pursuit interpolation processing is performed on the first ultra-shallow pre-stack data volume after upsampling to obtain a second ultra-shallow pre-stack data volume.

[0021] In an embodiment of the present invention, the refraction and reflection joint tomography processing of the second ultra-shallow pre-stack data volume to obtain an ultra-shallow initial model includes:

[0022] Performing refraction and reflection joint tomography processing on the second ultra-shallow pre-stack data volume to obtain an initial tomographic inversion model;

[0023] Calibrating the initial tomographic inversion model according to the overall initial model of the full imaging space to obtain an ultra-shallow initial model.

[0024] In an embodiment of the present invention, the processing of the depth unit of the ultra-shallow initial model and the depth unit of the second ultra-shallow pre-stack data volume to obtain a third ultra-shallow pre-stack data volume and an ultra-shallow depth domain initial model includes:

[0025] Reassigning the depth unit of the ultra-shallow initial model according to a preset multiple to obtain an ultra-shallow depth domain initial model;

[0026] Reassigning the depth unit of the second ultra-shallow pre-stack data volume according to the preset multiple to obtain a third ultra-shallow pre-stack data volume.

[0027] In an embodiment of the present invention, the precision processing of the ultra-shallow depth domain updated model to obtain an ultra-shallow depth domain precise model includes:

[0028] Performing downsampling on the ultra-shallow depth domain updated model according to a second preset sampling interval to obtain a reduced ultra-shallow depth domain updated model;

[0029] Performing quality control scanning on the reduced ultra-shallow depth domain updated model;

[0030] If the quality control scanning fails, then correcting the reduced ultra-shallow depth domain updated model to obtain a corrected ultra-shallow depth domain updated model, and performing bin thinning on the corrected ultra-shallow depth domain updated model to obtain an ultra-shallow depth domain precise model;

[0031] If the quality control scanning passes, then performing bin thinning on the reduced ultra-shallow depth domain updated model to obtain an ultra-shallow depth domain precise model.

[0032] In an embodiment of the present invention, the model fusion of the ultra-shallow depth domain precise model and the overall initial model of the full imaging space to obtain a full-space velocity precise model includes:

[0033] Taking the high - speed top interface as the demarcation line, excise the lower part of the ultra - shallow depth domain precise model to obtain the upper part of the ultra - shallow depth domain precise model;

[0034] Taking the high - speed top interface as the demarcation line, excise the upper part of the overall initial model of the full imaging space to obtain the lower part of the overall initial model of the full imaging space;

[0035] Fuse the upper part of the ultra - shallow depth domain precise model with the lower part of the overall initial model of the full imaging space to obtain the full - space velocity precise model.

[0036] In an embodiment of the present invention, the method further includes:

[0037] Perform quality control scanning on the full - space velocity precise model according to the geological information in the target area.

[0038] In an embodiment of the present invention, the performing quality control scanning on the full - space velocity precise model according to the geological information in the target area includes:

[0039] Pre - obtain the geological information in the target area;

[0040] Judge whether there are mutations in the full - space velocity precise model that do not conform to the geological information structure according to the geological information;

[0041] If there are, reconstruct the first ultra - shallow pre - stack data volume; perform precision processing on the first ultra - shallow pre - stack data volume to obtain the second ultra - shallow pre - stack data volume, perform joint refraction - reflection tomography processing on the second ultra - shallow pre - stack data volume to obtain the ultra - shallow initial model, process the depth unit of the ultra - shallow initial model and the depth unit of the second ultra - shallow pre - stack data volume to obtain the third ultra - shallow pre - stack data volume and the ultra - shallow depth domain initial model; perform iterative update according to the third ultra - shallow pre - stack data volume and the ultra - shallow depth domain initial model to obtain the ultra - shallow depth domain updated model, perform precision processing on the ultra - shallow depth domain updated model to obtain the ultra - shallow depth domain precise model; perform model fusion on the ultra - shallow depth domain precise model and the overall initial model of the full imaging space to obtain the full - space velocity precise model until there are no mutations in the full - space velocity precise model that do not conform to the geological information structure.

[0042] A second aspect of the embodiments of the present invention provides an ultra - shallow well - controlled variable - grid modeling device, which is applied to oil and gas reservoirs and new energy development. The device includes:

[0043] An ultra - shallow pre - stack data volume construction module, configured to obtain the overall initial model of the full imaging space according to the logging data of dual - well micro - log conforming to preset conditions, and obtain the first ultra - shallow pre - stack data volume according to the overall initial model of the full imaging space and the acquired three - dimensional pre - stack seismic data;

[0044] The ultra-shallow depth domain model construction module is used to perform precision processing on the first ultra-shallow pre-stack data volume to obtain a second ultra-shallow pre-stack data volume, perform refraction and reflection joint tomography processing on the second ultra-shallow pre-stack data volume to obtain an initial ultra-shallow model, and process the depth unit of the initial ultra-shallow model and the depth unit of the second ultra-shallow pre-stack data volume to obtain a third ultra-shallow pre-stack data volume and an initial ultra-shallow depth domain model;

[0045] The iterative update module is used to perform iterative update based on the third ultra-shallow pre-stack data volume and the initial ultra-shallow depth domain model to obtain an updated ultra-shallow depth domain model, and perform precision processing on the updated ultra-shallow depth domain model to obtain a precise ultra-shallow depth domain model;

[0046] The model fusion module performs model fusion on the precise ultra-shallow depth domain model and the overall initial model of the full imaging space to obtain a precise full-space velocity model.

[0047] The ultra-shallow well-controlled variable grid modeling method performs initial modeling based on the logging data of the dual-well micro-logging to obtain the overall initial model of the full imaging space, obtains the first ultra-shallow pre-stack data volume by intercepting the overall initial model of the full imaging space, performs precision processing on the intercepted first ultra-shallow pre-stack data volume, and then performs tomographic inversion to obtain the initial ultra-shallow depth domain model. By iteratively updating the initial ultra-shallow depth domain model, it solves the problem of low precision in shallow layer modeling of pre-stack depth migration and provides a high-precision velocity model for precise seismic imaging of the ultra-shallow layer.

[0048] Other features and advantages of the technical solution of the present invention will be described in detail in the following specific implementation part. Brief Description of the Drawings

[0049] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0050] Figure 1 is a flowchart of an ultra-shallow well-controlled variable grid modeling method provided by an embodiment of the present invention;

[0051] Figure 2 is a schematic structural diagram of an ultra-shallow well-controlled variable grid modeling system provided by an embodiment of the present invention. Detailed Description of the Invention

[0052] In order to make the technical solutions and advantages in the embodiments of the present invention clearer and more understandable, the exemplary embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than an exhaustive list of all embodiments. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0053] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention.

[0054] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0055] In the present invention, unless otherwise clearly specified and limited, terms such as "installation", "connection", "connection", "fixation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection, an electrical connection or can communicate with each other; it can be directly connected, or indirectly connected through an intermediate medium, and can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0056] In the process of implementing the present invention, the inventors found that modeling is an important means for fine reservoir description and real-time monitoring in conventional oil and gas reservoirs, unconventional oil and gas reservoirs, and new energy development. As the development targets become increasingly complex, the accuracy requirements for ultra-shallow target modeling are constantly increasing. At the same time, 3D seismic technology support is required for shallow modeling and imaging in areas with few wells. Usually, the initial ultra-shallow model can draw on the low-frequency model obtained by well-controlled tomography inversion, and the high-precision seismic imaging results can also verify the correctness of the model and whether it is consistent with geological understanding. In complex ultra-shallow development application cases, accurate shallow imaging results are required as important basic data to support development research. However, the real difficulty is not the imaging method itself, but whether a high-precision model can be obtained, especially an ultra-shallow model.

[0057] In the development practices for conventional, unconventional, and new energy sources, considerable potential has been seen in many basins in China. Technologies such as modeling, numerical simulation, integration, and well-seismic combination in fine reservoir description have achieved good results in application practices in many fields. In recent years, with the significant acceleration of new energy exploration and development, the requirements for the accuracy of ultra-shallow models have become increasingly high. The initial model in the dense well pattern area is constructed from well information, and the initial model in the sparse well area comes from seismic data tomographic inversion. However, due to the lack of effective seismic signals and available information in the shallow layer, the insufficient ray density in the shallow layer of the unified grid leads to the inability to establish an accurate model by conventional methods. There is an urgent need for a well-controlled ultra-shallow variable grid depth domain modeling method to support development, providing a high-precision model for accurate seismic imaging of ultra-shallow layers, thus comprehensively supporting the improvement of the compliance rate of fine description and prediction of conventional, unconventional, and new energy reservoirs, and accelerating the rapid increase in production of new energy targets in ultra-shallow layers.

[0058] In view of the above problems, an ultra-shallow well-controlled variable grid modeling method is provided in an embodiment of the present invention, which is applied to conventional energy, unconventional energy, and new energy. The method includes: S1. Obtaining well logging data of dual-well micro-logging that meet preset conditions and three-dimensional prestack seismic data in a target area; S2. Obtaining an overall initial model of the full imaging space based on the well logging data of dual-well micro-logging that meet preset conditions, and obtaining a first ultra-shallow prestack data volume based on the overall initial model of the full imaging space and the three-dimensional prestack seismic data; S3. Performing accuracy processing on the first ultra-shallow prestack data volume to obtain a second ultra-shallow prestack data volume, performing combined refraction and reflection tomography processing on the second ultra-shallow prestack data volume to obtain an ultra-shallow initial model, and processing the depth unit of the ultra-shallow initial model and the depth unit of the second ultra-shallow prestack data volume to obtain a third ultra-shallow prestack data volume and an ultra-shallow depth domain initial model; S4. Performing iterative update based on the third ultra-shallow prestack data volume and the ultra-shallow depth domain initial model to obtain an ultra-shallow depth domain updated model, and performing accuracy processing on the ultra-shallow depth domain updated model to obtain an ultra-shallow depth domain accurate model; S5. Performing model fusion on the ultra-shallow depth domain accurate model and the overall initial model of the full imaging space to obtain an accurate velocity model for the full space. The ultra-shallow well-controlled variable grid modeling method performs initial modeling based on the well logging data of dual-well micro-logging to obtain an overall initial model of the full imaging space, obtains a first ultra-shallow prestack data volume by intercepting the overall initial model of the full imaging space, performs accuracy processing on the intercepted first ultra-shallow prestack data volume, and then performs tomographic inversion to obtain an ultra-shallow depth domain initial model. Iterative update of the ultra-shallow depth domain initial model solves the problem of low accuracy in shallow layer modeling of prestack depth migration, providing a high-precision velocity model for accurate seismic imaging of ultra-shallow layers.

[0059] Figure 1 is a flowchart of an ultra-shallow well-controlled variable grid modeling method provided in an embodiment of the present invention. As Figure 1As shown in the figure, a super - shallow well - control variable - grid modeling method provided in this embodiment is applied to conventional energy, unconventional energy, and new energy. The method includes:

[0060] S1. Obtain the well - logging data of dual - well micro - logging and three - dimensional prestack seismic data that meet the preset conditions in the target area;

[0061] S2. Obtain the overall initial model of the full - imaging space based on the well - logging data of dual - well micro - logging that meet the preset conditions, and obtain the first super - shallow prestack data volume based on the overall initial model of the full - imaging space and the three - dimensional prestack seismic data;

[0062] S3. Perform precision processing on the first super - shallow prestack data volume to obtain the second super - shallow prestack data volume, perform combined refraction - reflection tomography processing on the second super - shallow prestack data volume to obtain the super - shallow initial model, and process the depth unit of the super - shallow initial model and the depth unit of the second super - shallow prestack data volume to obtain the third super - shallow prestack data volume and the initial model of the super - shallow depth domain;

[0063] S4. Perform iterative update based on the third super - shallow prestack data volume and the initial model of the super - shallow depth domain to obtain the updated model of the super - shallow depth domain, and perform precision processing on the updated model of the super - shallow depth domain to obtain the precise model of the super - shallow depth domain;

[0064] S5. Perform model fusion on the precise model of the super - shallow depth domain and the overall initial model of the full - imaging space to obtain the precise model of the full - space velocity.

[0065] In step S1, the dual - well micro - logging that meets the preset conditions is specifically: the density of the dual - well micro - logging is less than or equal to 1 km×1 km, and at the same time, there is three - dimensional prestack seismic data with a bin size less than one - fifth of the minimum well spacing.

[0066] If there is no dual - well micro - logging that meets the preset conditions in the target area, then perform densification construction on the dual - well micro - logging in the target area. That is, if the density of the dual - well micro - logging is greater than 1 km×1 km, then redeploy the dual - well micro - logging construction. If the density is less than 1 km×1 km, it is required that the dual - well micro - logging construction must drill through the top interface of the stable high - velocity layer. Obtain the well - logging data of the dual - well micro - logging that meets the preset conditions after densification construction and the three - dimensional prestack seismic data that meets the preset conditions.

[0067] If the well density of the dual - well micro - logging in the target area is less than or equal to 1 km×1 km, but the bin size of the three - dimensional seismic prestack data is greater than or equal to one - fifth of the minimum well spacing, then interpolation processing needs to be performed on the three - dimensional seismic prestack data in this area to obtain the three - dimensional prestack seismic data that meets the preset conditions.

[0068] When performing seismic excitation of the dual - well micro - logging, obtain the initial velocity model in the depth domain required in step S2.

[0069] In step S2, obtaining the overall initial model of the full imaging space according to the well logging data of the dual-well micro-logging that meets the preset conditions includes:

[0070] Performing surface layer modeling based on the well logging data of the dual-well micro-logging that meets the preset conditions to obtain a surface layer model;

[0071] Combining the initially obtained velocity model in the depth domain with the surface layer model to obtain the overall initial model of the full imaging space.

[0072] In step S2, obtaining the first ultra-shallow pre-stack data volume according to the overall initial model of the full imaging space and the three-dimensional pre-stack seismic data includes:

[0073] Determining the top interface of the underground high-velocity layer according to the overall initial model of the full imaging space, and determining the bottom surface of the shallow layer according to the top interface of the underground high-velocity layer;

[0074] Obtaining the first ultra-shallow pre-stack data volume according to the bottom surface of the shallow layer and the three-dimensional pre-stack seismic data.

[0075] Further, determining the bottom surface of the shallow layer according to the top interface of the underground high-velocity layer is specifically: in the vertical direction of the top interface of the high-velocity layer, deepening downward by a preset distance to obtain the bottom surface of the shallow layer. Further, the preset distance is 300 meters. The preset distance serves as a fusion buffer zone for subsequent model fusion to prevent mutations during model fusion.

[0076] In step S3, performing precision processing on the first ultra-shallow pre-stack data volume to obtain the second ultra-shallow pre-stack data volume includes:

[0077] Performing upsampling on the first ultra-shallow pre-stack data volume at a first preset sampling interval to obtain the upsampled first ultra-shallow pre-stack data volume;

[0078] Updating the original parameter values of the first seismic acquisition observation system according to the first preset sampling interval to obtain new parameter values and a second seismic acquisition observation system corresponding to the new parameter values;

[0079] Performing matching pursuit interpolation processing on the upsampled first ultra-shallow pre-stack data volume in the second seismic acquisition observation system to obtain the second ultra-shallow pre-stack data volume.

[0080] Specifically, the first preset sampling interval is one-tenth of the original sampling interval, and performing upsampling on the first ultra-shallow pre-stack data volume at the first preset sampling interval realizes vertical encryption of the first ultra-shallow pre-stack data.

[0081] Further, the original parameter values of the first seismic acquisition and observation system obtained in advance are: the parameter values of the seismic acquisition and observation system calculated according to the development geological design of the target area, and the first seismic acquisition and observation system is obtained.

[0082] The new small bin theoretical observation system established according to the first seismic acquisition and observation system after sampling is the second seismic acquisition and observation system, and the bin of the second seismic acquisition and observation system is one-tenth of the bin of the original seismic data.

[0083] In the second seismic acquisition and observation system, matching pursuit interpolation processing is performed on the first ultra-shallow prestack data volume after upsampling, so that there is one seismic trace in each bin of the new observation system for the first ultra-shallow prestack data volume, and the second ultra-shallow prestack data volume is obtained. The second ultra-shallow prestack data volume is a data volume with a very high density.

[0084] In step S3, the joint refraction and reflection tomography processing of the second ultra-shallow prestack data volume to obtain the ultra-shallow initial model includes:

[0085] Performing joint refraction and reflection tomography processing on the second ultra-shallow prestack data volume to obtain an initial tomographic inversion model;

[0086] Calibrating the initial tomographic inversion model according to the overall initial model of the full imaging space to obtain the ultra-shallow initial model.

[0087] In step S3, the processing of the depth unit of the ultra-shallow initial model and the depth unit of the second ultra-shallow prestack data volume to obtain the third ultra-shallow prestack data volume and the ultra-shallow depth domain initial model includes:

[0088] Reassigning the depth unit of the ultra-shallow initial model according to a preset multiple to obtain the ultra-shallow depth domain initial model;

[0089] Reassigning the depth unit of the second ultra-shallow prestack data volume according to the preset multiple to obtain the third ultra-shallow prestack data volume.

[0090] In this embodiment, the preset multiple is 10 times.

[0091] In step S4, iterative updating is performed according to the third ultra-shallow prestack data volume and the ultra-shallow depth domain initial model to obtain the ultra-shallow depth domain updated model. Specifically:

[0092] Performing 3-5 rounds of iterative updating according to the third ultra-shallow prestack data volume and the ultra-shallow depth domain initial model, recalculating travel time tomographic inversion, and after eliminating the residual moveout of the trace gather, performing model updating on the depth-expanded ten-fold resampled initial model and seismic data is to increase the ultra-shallow ray density. After the update is completed, the updated ultra-shallow depth domain updated model is output.

[0093] In step S4, the accuracy processing of the ultra-shallow depth domain update model to obtain the ultra-shallow depth domain accurate model includes:

[0094] Downsample the ultra-shallow depth domain update model downward at a second preset sampling interval to obtain a reduced ultra-shallow depth domain update model;

[0095] Perform quality control scanning on the reduced ultra-shallow depth domain update model;

[0096] If the quality control scanning fails, correct the reduced ultra-shallow depth domain update model to obtain a corrected ultra-shallow depth domain update model, and perform bin sparsification on the corrected ultra-shallow depth domain update model to obtain the ultra-shallow depth domain accurate model;

[0097] If the quality control scanning passes, perform bin sparsification on the reduced ultra-shallow depth domain update model to obtain the ultra-shallow depth domain accurate model.

[0098] In this embodiment, the method for judging outliers is:

[0099] Within the preset range of each formation in the ultra-shallow depth domain update model, if the outliers of each formation exceed 10% of the average value, it is judged that the quality control scanning fails.

[0100] The correction method is:

[0101] Perform smooth interpolation processing on the formation where the outliers exceed 10% of the average value.

[0102] Furthermore, performing bin sparsification on the reduced ultra-shallow depth domain update model to obtain the ultra-shallow depth domain accurate model specifically includes:

[0103] Perform re-meshing processing on the reduced ultra-shallow depth domain update model to make the spatial bins return to the original bin size, obtaining the ultra-shallow depth domain accurate model.

[0104] In step S5, the model fusion of the ultra-shallow depth domain accurate model and the overall initial model of the full imaging space to obtain the full-space velocity accurate model includes:

[0105] Using the high-velocity top interface as the demarcation line, cut off the lower part of the ultra-shallow depth domain accurate model to obtain the upper part of the ultra-shallow depth domain accurate model;

[0106] Using the high-velocity top interface as the demarcation line, cut off the upper part of the overall initial model of the full imaging space to obtain the lower part of the overall initial model of the full imaging space;

[0107] Fuse the upper part of the ultra-shallow depth domain precision model with the lower part of the overall initial model of the full imaging space to obtain the full-space velocity precision model.

[0108] Further, after fusing the upper part of the ultra-shallow depth domain precision model with the lower part of the overall initial model of the full imaging space, perform filtering and smoothing operations in sequence to obtain the full-space velocity precision model.

[0109] In this embodiment, the method further includes:

[0110] S6. Perform quality control scanning on the full-space velocity precision model according to the geological information in the target area.

[0111] In step S6, the performing quality control scanning on the full-space velocity precision model according to the geological information in the target area includes:

[0112] Pre-obtain the geological information in the target area;

[0113] Judge whether there are mutations in the full-space velocity precision model that do not conform to the geological information structure according to the geological information;

[0114] If so, repeat steps S1 - S5 until there are no mutations in the full-space velocity precision model that do not conform to the geological information structure.

[0115] Specifically, not conforming to the geological information structure includes: mutations not conforming to the stratigraphic structure or not conforming to the underground information revealed by the well.

[0116] The present invention takes the development of a certain oilfield as a specific example, and the specific method operation process is as follows:

[0117] In the development of the Changyuan area in the Daqing Oilfield, after determining a certain development research area, select the three-dimensional pre-stack seismic data of this research area, and find that the seismic work area of this research area belongs to the Changyuan 690 km 2For a 3D work area, if the density of dual-well micro-logging within the area is less than or equal to 1 km × 1 km and there is 3D seismic data with a bin size less than one-fifth of the minimum well spacing at the same time, the surface model is directly established; if the density of dual-well micro-logging within the area is greater than 1 km × 1 km, the construction of dual-well micro-logging is redeployed, and when the density is less than 1 km × 1 km, it is required that the construction of dual-well micro-logging must drill through the top interface of the stable high-velocity layer; if the bin size of the existing 3D seismic data is greater than or equal to one-fifth of the minimum well spacing, seismic data interpolation processing is required to obtain 3D pre-stack seismic data that meets the preset conditions. The surface model is established using the obtained dual-well micro-logging data, and then combined with the initial model in the depth domain to obtain the overall initial model of the full imaging space. The sampling interval in the depth domain of this model is 20 m. If the dual-well micro-logging in this study area can meet the application conditions of the present invention, there is no need to redeploy the encrypted dual-well micro-logging construction. The well spacing in this area is 150 m - 250 m, one-fifth of the well spacing is 30 m to 50 m, and the bin size of the 3D seismic data is 20 m × 20 m, which can meet the requirements of the present invention and no interpolation processing is required.

[0118] Estimate the parameters of the imaging observation system according to the geological design of conventional energy, unconventional energy, and new energy development, and determine that the minimum bin size for this application is 20 m × 20 m.

[0119] Use the overall initial model of the full imaging space to determine the top interface of the underground high-velocity layer within the development and research area. Take the maximum depth of the high-velocity layer top interface plus 300 m as the bottom surface of the shallow layer. The sampling interval in the data time domain is 1 ms, and intercept the overall initial model of the full imaging space to obtain the first ultra-shallow pre-stack data volume for the pre-stack data of the ultra-shallow layer tomography inversion model.

[0120] Resample the first ultra-shallow pre-stack data volume upward, with the sampling interval being 10 times the original sampling interval, to obtain the upward resampled first ultra-shallow pre-stack data volume, and the sampling interval comes to 0.1 ms.

[0121] According to the parameters of the first seismic acquisition observation system, establish a new small bin theoretical observation system after sampling, that is, the second seismic acquisition observation system. The bin size of the second seismic acquisition observation system is one-tenth of the bin size of the original seismic data, and the bin size of the newly established theoretical observation system is 2 m × 2 m.

[0122] Perform matching pursuit interpolation on the upward resampled first ultra-shallow pre-stack data volume within the second seismic acquisition observation system, so that there is one seismic trace in each bin of the new observation system for the upward resampled first ultra-shallow pre-stack data volume, and obtain the second ultra-shallow pre-stack data volume.

[0123] The model established by joint inversion of surface waves and refraction and reflection in the second ultra-shallow pre-stack data volume is used as the initial model obtained by inversion. Then, the above initial inversion model is calibrated and controlled using the overall initial model in the full imaging space. The depth unit of the updated ultra-shallow initial model is re-assigned, and each depth range is expanded ten times to obtain the initial model in the ultra-shallow depth domain, with a sampling interval of 2 m in the depth domain.

[0124] The depth unit of the second ultra-shallow pre-stack data volume is re-assigned and expanded ten times to obtain the third ultra-shallow pre-stack data volume. The actual sampling interval remains 0.1 ms, but the time domain unit of the data is replaced with 1 ms.

[0125] Using the initial model in the ultra-shallow depth domain and the third ultra-shallow pre-stack data volume, iterative model updating is carried out. After 3 - 5 rounds of recomputing travel time tomography inversion to eliminate the residual moveout in the gather, model updating is performed on the resampled initial model with a ten-fold depth expansion and the seismic data to increase the ray density in the ultra-shallow layer. After the update is completed, the updated ultra-shallow depth domain update model is output. Through this step, the original sampling interval and spatial grid were very sparse and insufficient to provide enough ray density for the establishment of an accurate ultra-shallow model. Now, the grid becomes 10×10×10×10 times that of the original data and model, which is sufficient for grid tomography of the ultra-shallow layer to invert an accurate model.

[0126] The updated model in the ultra-shallow depth domain is resampled downward with a sampling interval equal to that of the initial model in the ultra-shallow depth domain to obtain the reduced updated model in the ultra-shallow depth domain.

[0127] Perform vertical and horizontal quality control scans on the reduced updated model in the ultra-shallow depth domain to check if there are outliers in the shallow model. If there are outliers, perform smoothing interpolation to obtain the smoothed corrected updated model in the ultra-shallow depth domain, and repeat this step until passing the quality control; if there are no outliers, directly name the input model as the corrected updated model in the ultra-shallow depth domain.

[0128] Perform re-gridding processing on the accurate model in the ultra-shallow depth domain to make the spatial bin return to the original bin size, obtaining the accurate model in the ultra-shallow depth domain with sparse bins. The bin size returns to the original bin size.

[0129] Taking the top surface of the high-velocity layer as the dividing line, cut off the lower part of the accurate model in the ultra-shallow depth domain to obtain the upper part of the accurate model in the ultra-shallow depth domain, and cut off the overall initial model in the full imaging space to obtain the lower part of the overall initial model in the full imaging space.

[0130] Fuse and filter the upper part of the accurate model in the ultra-shallow depth domain and the lower part of the overall initial model in the full imaging space, and smooth to obtain the accurate velocity model in the full space.

[0131] For the all-space velocity precision model, perform quality control. If there are no mutations in the ultra-shallow layer that do not conform to the structure or do not conform to the underground information revealed by the well, output the model; if there are mutations in the ultra-shallow layer that do not conform to the structure or do not conform to the underground information revealed by the well, output the model and repeat steps S3 - S14 until the final all-space velocity precision model is output through the quality control of step S15. This final all-space velocity precision model can be used as the ultra-shallow layer model for reservoir fine description services or for pre-stack depth migration imaging of the ultra-shallow layer and deep layer. On the basis of accurately establishing the shallow layer model, the imaging accuracy of the middle and deep layers will also be greatly improved, which can comprehensively support the improvement of the compliance rate of fine description and prediction of conventional, unconventional, and new energy reservoirs, and accelerate the rapid production increase of new energy targets in the ultra-shallow layer.

[0132] Figure 2 It is a schematic structural diagram of an ultra-shallow layer well-controlled variable grid modeling system provided by an embodiment of the present invention, as Figure 2 shown: This embodiment provides an ultra-shallow layer well-controlled variable grid modeling device, which is applied to oil and gas reservoirs and new energy development. The device includes: an ultra-shallow layer pre-stack data volume construction module, which is used to obtain the overall initial model of the full imaging space according to the logging data of dual-well micro-logging that meets the preset conditions, and obtain the first ultra-shallow layer pre-stack data volume according to the overall initial model of the full imaging space and the acquired three-dimensional pre-stack seismic data; an ultra-shallow layer depth domain model construction module, which is used to perform accuracy processing on the first ultra-shallow layer pre-stack data volume to obtain the second ultra-shallow layer pre-stack data volume, perform refraction and reflection joint tomography processing on the second ultra-shallow layer pre-stack data volume to obtain the ultra-shallow layer initial model, process the depth unit of the ultra-shallow layer initial model and the depth unit of the second ultra-shallow layer pre-stack data volume to obtain the third ultra-shallow layer pre-stack data volume and the ultra-shallow layer depth domain initial model; an iterative update module, which is used to perform iterative update according to the third ultra-shallow layer pre-stack data volume and the ultra-shallow layer depth domain initial model to obtain the ultra-shallow layer depth domain updated model, and perform accuracy processing on the ultra-shallow layer depth domain updated model to obtain the ultra-shallow layer depth domain precision model; a model fusion module, which performs model fusion on the ultra-shallow layer depth domain precision model and the overall initial model of the full imaging space to obtain the all-space velocity precision model.

[0133] In this embodiment, the ultra-shallow layer pre-stack data volume construction module, which is used to obtain the overall initial model of the full imaging space according to the logging data of dual-well micro-logging that meets the preset conditions, and obtain the first ultra-shallow layer pre-stack data volume according to the overall initial model of the full imaging space and the acquired three-dimensional pre-stack seismic data, specifically:

[0134] Perform surface layer modeling according to the logging data of dual-well micro-logging that meets the preset conditions to obtain the surface layer model;

[0135] Combine the pre-acquired initial velocity model in the depth domain with the surface layer model to obtain the overall initial model of the full imaging space.

[0136] The obtaining of the first ultra-shallow pre-stack data volume based on the overall initial model of the full imaging space and the three-dimensional pre-stack seismic data includes:

[0137] Determine the top interface of the underground high-velocity layer according to the overall initial model of the full imaging space, and determine the bottom surface of the shallow layer according to the top interface of the underground high-velocity layer;

[0138] Obtain the first ultra-shallow pre-stack data volume according to the bottom surface of the shallow layer and the three-dimensional pre-stack seismic data.

[0139] Further, determining the bottom surface of the shallow layer according to the top interface of the underground high-velocity layer is specifically: in the vertical direction of the top interface of the high-velocity layer, deepen downward by a preset distance to obtain the bottom surface of the shallow layer. Further, the preset distance is 300 meters. The preset distance serves as a fusion buffer zone for subsequent model fusion to prevent mutations during model fusion.

[0140] The ultra-shallow depth domain model construction module is used to perform precision processing on the first ultra-shallow pre-stack data volume to obtain a second ultra-shallow pre-stack data volume, perform joint refraction and reflection tomography processing on the second ultra-shallow pre-stack data volume to obtain an initial ultra-shallow model, and process the depth unit of the initial ultra-shallow model and the depth unit of the second ultra-shallow pre-stack data volume to obtain a third ultra-shallow pre-stack data volume and an initial ultra-shallow depth domain model, specifically:

[0141] The performing of precision processing on the first ultra-shallow pre-stack data volume to obtain a second ultra-shallow pre-stack data volume includes:

[0142] Perform upsampling on the first ultra-shallow pre-stack data volume at a first preset sampling interval to obtain the upsampled first ultra-shallow pre-stack data volume;

[0143] Update the original parameter values of the first seismic acquisition observation system according to the first preset sampling interval to obtain new parameter values and a second seismic acquisition observation system corresponding to the new parameter values;

[0144] Perform matching pursuit interpolation processing on the upsampled first ultra-shallow pre-stack data volume in the second seismic acquisition observation system to obtain a second ultra-shallow pre-stack data volume.

[0145] Specifically, the first preset sampling interval is one-tenth of the original sampling interval, and performing upsampling on the first ultra-shallow pre-stack data volume at the first preset sampling interval realizes the vertical encryption of the first ultra-shallow pre-stack data.

[0146] Further, the original parameter values of the first seismic acquisition and observation system obtained in advance are: the parameter values of the seismic acquisition and observation system calculated according to the development geological design of the target area, and the first seismic acquisition and observation system is obtained.

[0147] The new small bin theoretical observation system established according to the first seismic acquisition and observation system after sampling is the second seismic acquisition and observation system, and the bin of the second seismic acquisition and observation system is one-tenth of the bin of the original seismic data.

[0148] In the second seismic acquisition and observation system, matching pursuit interpolation processing is performed on the first ultra-shallow prestack data volume after upsampling, so that there is a seismic trace in each bin of the new observation system for the first ultra-shallow prestack data volume, and the second ultra-shallow prestack data volume is obtained. The second ultra-shallow prestack data volume is a data volume with a very high density.

[0149] The refraction and reflection joint tomography processing of the second ultra-shallow prestack data volume to obtain the ultra-shallow initial model includes:

[0150] Performing refraction and reflection joint tomography processing on the second ultra-shallow prestack data volume to obtain the initial tomographic inversion model;

[0151] Calibrating the initial tomographic inversion model according to the overall initial model of the full imaging space to obtain the ultra-shallow initial model.

[0152] The processing of the depth unit of the ultra-shallow initial model and the depth unit of the second ultra-shallow prestack data volume to obtain the third ultra-shallow prestack data volume and the ultra-shallow depth domain initial model includes:

[0153] Reassigning the depth unit of the ultra-shallow initial model according to a preset multiple to obtain the ultra-shallow depth domain initial model;

[0154] Reassigning the depth unit of the second ultra-shallow prestack data volume according to the preset multiple to obtain the third ultra-shallow prestack data volume.

[0155] The preset multiple is 10 times.

[0156] The iterative update module is used to perform iterative update according to the third ultra-shallow prestack data volume and the ultra-shallow depth domain initial model to obtain the ultra-shallow depth domain updated model, and perform accuracy processing on the ultra-shallow depth domain updated model to obtain the ultra-shallow depth domain accurate model, specifically:

[0157] Performing iterative update according to the third ultra-shallow prestack data volume and the ultra-shallow depth domain initial model to obtain the ultra-shallow depth domain updated model, specifically:

[0158] Perform 3 - 5 rounds of iterative updates based on the third ultra - shallow prestack data volume and the initial model in the ultra - shallow depth domain. Recalculate the travel - time tomography inversion. After eliminating the residual moveout of the gather, perform model updates on the resampled initial model and seismic data with the depth enlarged by ten times to increase the ray density in the ultra - shallow layer. After the update is completed, output the updated ultra - shallow depth - domain updated model.

[0159] Performing precision processing on the updated ultra - shallow depth - domain model to obtain the accurate ultra - shallow depth - domain model includes:

[0160] Downsample the updated ultra - shallow depth - domain model according to the second preset sampling interval to obtain a reduced updated ultra - shallow depth - domain model;

[0161] Perform quality control scanning on the reduced updated ultra - shallow depth - domain model;

[0162] If the quality control scanning fails, correct the reduced updated ultra - shallow depth - domain model to obtain a corrected updated ultra - shallow depth - domain model, and perform bin thinning on the corrected updated ultra - shallow depth - domain model to obtain the accurate ultra - shallow depth - domain model;

[0163] If the quality control scanning passes, perform bin thinning on the reduced updated ultra - shallow depth - domain model to obtain the accurate ultra - shallow depth - domain model.

[0164] In this embodiment, the method for judging outliers is:

[0165] Within the preset range of each formation in the updated ultra - shallow depth - domain model, if the outliers of each formation exceed 10% of the average value, it is judged that the quality control scanning fails.

[0166] The correction method is:

[0167] Perform smooth interpolation on the formation where the outliers exceed 10% of the average value.

[0168] Furthermore, performing bin thinning on the reduced updated ultra - shallow depth - domain model to obtain the accurate ultra - shallow depth - domain model is specifically:

[0169] Perform re - gridding processing on the reduced updated ultra - shallow depth - domain model to make the spatial bin return to the original bin size, obtaining the accurate ultra - shallow depth - domain model.

[0170] The model fusion module is used to fuse the accurate ultra - shallow depth - domain model and the overall initial model of the full imaging space to obtain the accurate full - space velocity model, specifically:

[0171] The fusion of the accurate ultra - shallow depth - domain model and the overall initial model of the full imaging space to obtain the accurate full - space velocity model includes:

[0172] Taking the high-speed top interface as the demarcation line, the lower part of the ultra-shallow depth domain precise model is excised to obtain the upper part of the ultra-shallow depth domain precise model;

[0173] Taking the high-speed top interface as the demarcation line, the upper part of the overall initial model of the full imaging space is excised to obtain the lower part of the overall initial model of the full imaging space;

[0174] The upper part of the ultra-shallow depth domain precise model is fused with the lower part of the overall initial model of the full imaging space to obtain the full-space velocity precise model.

[0175] Furthermore, after the upper part of the ultra-shallow depth domain precise model is fused with the lower part of the overall initial model of the full imaging space, filtering and smoothing operations are sequentially performed to obtain the full-space velocity precise model.

[0176] An embodiment of the present invention also provides a computer device, including: a memory, a processor, and a computer program, where the computer program is stored in the memory and is configured to be executed by the processor to implement the above-mentioned ultra-shallow well control variable grid modeling method.

[0177] An embodiment of the present invention also provides a machine-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the above-mentioned ultra-shallow well control variable grid modeling method is implemented.

[0178] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented in various computer languages, for example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0179] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementation in the process Figure 1one or more processes and / or blocks Figure 1 means for the functions specified in one or more blocks

[0180] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions in the process Figure 1 one or more processes and / or blocks Figure 1 the functions specified in one or more blocks

[0181] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus, such that a series of operational steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions in the process Figure 1 one or more processes and / or blocks Figure 1 the steps of the functions specified in one or more blocks

[0182] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to cover the preferred embodiments as well as all changes and modifications falling within the scope of the present invention

[0183] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations

Claims

1. A super-shallow well control variable grid modeling method, which is applied to oil and gas reservoirs and new energy development, and is characterized in that, The method includes: Obtaining well logging data of dual-well micro-logging that meet preset conditions within a target area and three-dimensional prestack seismic data; Obtaining an overall initial model of the full imaging space based on the well logging data of dual-well micro-logging that meet preset conditions, and obtaining a first ultra-shallow prestack data volume based on the overall initial model of the full imaging space and the three-dimensional prestack seismic data; Performing precision processing on the first ultra-shallow prestack data volume to obtain a second ultra-shallow prestack data volume, performing combined refraction and reflection tomography processing on the second ultra-shallow prestack data volume to obtain an initial ultra-shallow model, and processing the depth unit of the initial ultra-shallow model and the depth unit of the second ultra-shallow prestack data volume to obtain a third ultra-shallow prestack data volume and an initial ultra-shallow depth domain model; Performing iterative update based on the third ultra-shallow prestack data volume and the initial ultra-shallow depth domain model to obtain an updated ultra-shallow depth domain model, and performing precision processing on the updated ultra-shallow depth domain model to obtain an accurate ultra-shallow depth domain model; Performing model fusion on the accurate ultra-shallow depth domain model and the overall initial model of the full imaging space to obtain an accurate full-space velocity model.

2. The super-shallow well control variable grid modeling method according to claim 1, characterized in that, The obtaining of the overall initial model of the full imaging space based on the well logging data of dual-well micro-logging that meet preset conditions includes: Performing surface layer modeling based on the well logging data of dual-well micro-logging that meet preset conditions to obtain a surface layer model; Combining the pre-obtained initial velocity model in the depth domain with the surface layer model to obtain the overall initial model of the full imaging space.

3. The super-shallow well control variable grid modeling method according to claim 1, characterized in that, The obtaining of the first ultra-shallow prestack data volume based on the overall initial model of the full imaging space and the three-dimensional prestack seismic data includes: Determining the top interface of the underground high-velocity layer based on the overall initial model of the full imaging space, and determining the bottom surface of the shallow layer based on the top interface of the underground high-velocity layer; Obtaining the first ultra-shallow prestack data volume based on the bottom surface of the shallow layer and the three-dimensional prestack seismic data.

4. The super-shallow well control variable grid modeling method according to claim 1, characterized in that, The performing of precision processing on the first ultra-shallow prestack data volume to obtain a second ultra-shallow prestack data volume includes: Performing upsampling on the first ultra-shallow prestack data volume at a first preset sampling interval to obtain the upsampled first ultra-shallow prestack data volume; Updating the original parameter values of the first seismic acquisition observation system according to the first preset sampling interval to obtain new parameter values and a second seismic acquisition observation system corresponding to the new parameter values; Performing matching pursuit interpolation processing on the upsampled first ultra-shallow prestack data volume in the second seismic acquisition observation system to obtain a second ultra-shallow prestack data volume.

5. The super-shallow well control variable grid modeling method according to claim 1, characterized in that, The performing of combined refraction and reflection tomography processing on the second ultra-shallow prestack data volume to obtain an initial ultra-shallow model includes: Performing combined refraction and reflection tomography processing on the second ultra-shallow prestack data volume to obtain an initial tomographic inversion model; Calibrating the initial tomographic inversion model according to the overall initial model of the full imaging space to obtain an initial ultra-shallow model.

6. The super-shallow well control variable grid modeling method according to claim 1, characterized in that, The processing of the depth unit of the initial ultra-shallow model and the depth unit of the second ultra-shallow prestack data volume to obtain a third ultra-shallow prestack data volume and an initial ultra-shallow depth domain model includes: Reassign the depth unit of the ultra-shallow initial model according to a preset multiple to obtain the ultra-shallow depth domain initial model; Reassign the depth unit of the second ultra-shallow pre-stack data volume according to the preset multiple to obtain the third ultra-shallow pre-stack data volume.

7. The super-shallow well control variable grid modeling method according to claim 1, characterized in that, The precision processing of the ultra-shallow depth domain updated model to obtain the ultra-shallow depth domain precise model includes: Downsample the ultra-shallow depth domain updated model according to a second preset sampling interval to obtain a reduced ultra-shallow depth domain updated model; Perform quality control scanning on the reduced ultra-shallow depth domain updated model; If the quality control scanning fails, correct the reduced ultra-shallow depth domain updated model to obtain a corrected ultra-shallow depth domain updated model, and perform bin sparsification on the corrected ultra-shallow depth domain updated model to obtain the ultra-shallow depth domain precise model; If the quality control scanning passes, perform bin sparsification on the reduced ultra-shallow depth domain updated model to obtain the ultra-shallow depth domain precise model.

8. The super-shallow well control variable grid modeling method according to claim 2, characterized in that, The model fusion of the ultra-shallow depth domain precise model and the whole imaging space overall initial model to obtain the whole space velocity precise model includes: Taking the high-speed top interface as the dividing line, excise the lower part of the ultra-shallow depth domain precise model to obtain the upper part of the ultra-shallow depth domain precise model; Taking the high-speed top interface as the dividing line, excise the upper part of the whole imaging space overall initial model to obtain the lower part of the whole imaging space overall initial model; Fuse the upper part of the ultra-shallow depth domain precise model with the lower part of the whole imaging space overall initial model to obtain the whole space velocity precise model.

9. The ultra-shallow well control variable grid modeling method according to claim 1, characterized in that The method further includes: Perform quality control scanning on the whole space velocity precise model according to the geological information in the target area.

10. The ultra-shallow well control variable grid modeling method according to claim 9, characterized in that The quality control scanning of the whole space velocity precise model according to the geological information in the target area includes: Pre-acquire the geological information in the target area; Judge whether there are mutations in the whole space velocity precise model that do not conform to the geological information structure according to the geological information; If so, reconstruct the first ultra-shallow pre-stack data volume; perform precision processing on the first ultra-shallow pre-stack data volume to obtain the second ultra-shallow pre-stack data volume, perform refraction and reflection joint tomography processing on the second ultra-shallow pre-stack data volume to obtain the ultra-shallow initial model, process the depth unit of the ultra-shallow initial model and the depth unit of the second ultra-shallow pre-stack data volume to obtain the third ultra-shallow pre-stack data volume and the ultra-shallow depth domain initial model; perform iterative update according to the third ultra-shallow pre-stack data volume and the ultra-shallow depth domain initial model to obtain the ultra-shallow depth domain updated model, perform precision processing on the ultra-shallow depth domain updated model to obtain the ultra-shallow depth domain precise model; perform model fusion on the ultra-shallow depth domain precise model and the whole imaging space overall initial model to obtain the whole space velocity precise model; until there are no mutations in the whole space velocity precise model that do not conform to the geological information structure.

11. An ultra-shallow well control variable grid modeling device, applied to oil and gas reservoirs and new energy development, characterized in that The device includes: The ultra-shallow pre-stack data volume construction module is used to obtain the overall initial model of the full imaging space according to the logging data of the cross-hole micro-logging that meets the preset conditions, and obtain the first ultra-shallow pre-stack data volume according to the overall initial model of the full imaging space and the acquired three-dimensional pre-stack seismic data; The ultra-shallow depth domain model construction module is used to perform precision processing on the first ultra-shallow pre-stack data volume to obtain the second ultra-shallow pre-stack data volume, perform joint refraction and reflection tomography processing on the second ultra-shallow pre-stack data volume to obtain the ultra-shallow initial model, and process the depth unit of the ultra-shallow initial model and the depth unit of the second ultra-shallow pre-stack data volume to obtain the third ultra-shallow pre-stack data volume and the ultra-shallow depth domain initial model; The iterative update module is used to perform iterative update according to the third ultra-shallow pre-stack data volume and the ultra-shallow depth domain initial model to obtain the ultra-shallow depth domain updated model, and perform precision processing on the ultra-shallow depth domain updated model to obtain the ultra-shallow depth domain accurate model; The model fusion module performs model fusion on the ultra-shallow depth domain accurate model and the overall initial model of the full imaging space to obtain the full-space velocity accurate model.

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