A method, system, and medium for high-resolution permafrost surface layer inversion velocity modeling

Abstract

This disclosure relates to tomographic inversion technology, and more particularly to a method, system, and medium for velocity modeling in tomographic inversion of permafrost surfaces in plateau regions. The method includes: constructing an initial surface model with velocity reversal characteristics based on micrologging information, drilling velocity information, and CMP first-arrival refraction stratification; performing velocity reversal processing on the initial surface model during tomographic inversion to obtain a velocity profile; identifying the permafrost floor reflection surface based on the stacked gather profile containing the velocity profile; and interpreting the permafrost layer velocity interface based on the shallow permafrost reflection surface within the permafrost floor reflection surface. This method establishes an accurate surface permafrost model, providing strong support for static correction calculations and pre-stack depth migration modeling of permafrost surfaces in plateau regions. It solves the problems of existing tomographic inversion methods failing to accurately reflect permafrost velocity reversal changes and the difficulty in determining the permafrost model floor boundary.

Description

Technical Field

[0001] This disclosure belongs to the field of petroleum geophysical exploration technology, and relates to tomographic inversion technology, and in particular to a method, system and medium for tomographic inversion velocity modeling of permafrost surface in plateau regions. Background Technology

[0002] With the continuous growth of global energy demand and the rapid development of new energy technologies, the permafrost zone, as a unique geographical environment, has attracted increasing attention for its energy exploration prospects. Currently, oil and gas exploration in the Tibetan Plateau is rapidly progressing, with the permafrost zone becoming a crucial exploration area. The widespread distribution of permafrost in the Qinghai-Tibet Plateau presents unique challenges to seismic exploration and development of oil and gas resources. Due to the presence of the permafrost layer, compared to the unfrozen surface, it is prone to higher velocities and velocity reversals. Seismic waves encounter energy shielding and velocity distortion during propagation, leading to a decrease in the imaging quality of seismic data. To overcome these problems, it is necessary to understand the velocity structure characteristics of the permafrost surface, perform static correction and pre-stack migration processing for velocity modeling, and improve the imaging quality and accuracy of seismic data. The velocity difference between the permafrost layer and the unfrozen soil is very large. This velocity contrast complicates the propagation path of seismic waves, making velocity reversals easy. The bottom boundary of the permafrost is difficult to distinguish from the surrounding strata, and conventional tomographic inversion methods cannot accurately reflect this velocity change, resulting in large errors in the permafrost inversion model.

[0003] Therefore, existing technologies need to be improved. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a method and system for velocity modeling based on tomographic inversion of permafrost surfaces in plateau regions. By constructing an initial surface model with velocity reversal characteristics, performing tomographic inversion velocity reversal processing, and interpreting the permafrost bottom interface model based on shallow reflective surfaces, an accurate surface permafrost model is established. This provides strong support for static correction calculations and pre-stack depth migration modeling of permafrost surfaces in plateau regions. It overcomes the problems of existing tomographic inversion methods failing to accurately reflect permafrost velocity reversal changes and the difficulty in determining the bottom boundary of the permafrost model.

[0005] According to one aspect of the present invention, a method for modeling inversion velocity in plateau permafrost surface tomography is provided, comprising:

[0006] S1. Utilize micrologging information, drilling velocity information, and CMP first arrival refraction stratification to establish an initial surface model including velocity reversal characteristics;

[0007] S2. Based on the initial surface model, velocity reversal processing is performed in tomographic inversion to obtain a velocity profile containing velocity reversal.

[0008] S3. Identify the permafrost bottom boundary reflection surface based on the superimposed gather profile containing velocity profile;

[0009] S4. Determine the velocity interface of the frozen soil layer based on the shallow frozen soil reflection surface in the frozen soil bottom boundary reflection surface.

[0010] In one embodiment of the present invention, S1 further includes: selecting a development zone based on the first arrival characteristics of a single shot, and selecting a corresponding position grid in the CMP domain to perform CMP first arrival refraction layering based on the single shot characteristics at different positions.

[0011] In one embodiment of the present invention, S1 further includes: using micrologging information, drilling velocity information and CMP first arrival refraction stratification as constraints to interpolate and establish an initial surface model.

[0012] In one embodiment of the present invention, S1 further includes interpolating based on the correlation between the frozen soil velocity inversion layer and its adjacent strata to establish an initial surface model.

[0013] In one embodiment of the present invention, S2 further includes: performing velocity reversal processing based on the surface initial model using an iterative algorithm.

[0014] In one embodiment of the present invention, the iterative algorithm includes a grid iterative algorithm.

[0015] In one embodiment of the present invention, S2 further includes: the longitudinal grid velocity change of the grid iteration algorithm is not performed in the forward velocity order and is reversed.

[0016] In one embodiment of the present invention, S3 includes: identifying the reflection phase axis of a superimposed gather with discontinuous reflection phase axis that has phase variation, is related to the surface morphology, and is not related to the attitude of shallow folded strata as the permafrost bottom boundary reflection surface.

[0017] In one embodiment of the present invention, S4 includes:

[0018] S41. Select different locations, pick up the time of the in-phase axis of the shallow frozen soil reflection, use the superposition speed to perform time-depth conversion, determine the depth of the shallow frozen soil reflection surface, and form depth control points.

[0019] S42. Overlay the depth information of the shallow frozen soil reflection surface at different depth control points onto the tomographic inversion velocity profile, and fit the depth surface of the control points according to the tomographic velocity variation characteristics to form the frozen soil velocity interface.

[0020] According to another aspect of the present invention, a system for modeling velocity inversion from surface tomography of permafrost in plateau regions is also provided, comprising:

[0021] The first module utilizes micrologging information, drilling velocity information, and CMP first arrival refraction stratification to establish an initial surface model including velocity reversal characteristics.

[0022] The second module performs velocity reversal processing in tomographic inversion based on the surface initial model to obtain a velocity profile containing velocity reversal.

[0023] The third module identifies the permafrost bottom boundary reflection surface based on the superimposed gather profile containing velocity profiles.

[0024] The fourth module determines the velocity interface of the frozen soil layer based on the shallow frozen soil reflection surface in the frozen soil bottom boundary reflection surface.

[0025] In one embodiment of the present invention, a fifth module is also included, which is used to output the velocity interface of the frozen soil layer for static correction calculation or for pre-stack depth migration modeling.

[0026] According to another aspect of the present invention, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, performs the steps of the method as described in any of the preceding embodiments.

[0027] The velocity modeling method for plateau permafrost surface tomography in this invention is suitable for establishing high-precision velocity fields in pre-stack depth migration processing of permafrost folded surfaces. It can be applied to areas with extremely low signal-to-noise ratios in permafrost surface development in western China, effectively improving the modeling accuracy of permafrost surfaces and enhancing imaging quality, with broad application prospects. Attached Figure Description

[0028] The above and other objects, features and advantages of this disclosure will become more apparent from the more detailed description of exemplary embodiments thereof taken in conjunction with the accompanying drawings, wherein like reference numerals generally denote like parts.

[0029] Figure 1 A flowchart of the modeling method of the present invention is shown;

[0030] Figure 2 A schematic diagram of the first-arrival refractive layering of the CMP of the present invention is shown;

[0031] Figure 3 A schematic diagram of the frozen soil bottom boundary reflective surface of the present invention is shown;

[0032] Figure 4 A schematic diagram of velocity reversal micrologging according to an embodiment of the present invention is shown;

[0033] Figure 5 A schematic diagram illustrating the micro-motion investigation reversal speed according to an embodiment of the present invention is shown;

[0034] Figure 6 An initial model schematic diagram of an embodiment of the present invention is shown;

[0035] Figure 7 A schematic diagram of velocity inversion processing according to an embodiment of the present invention is shown;

[0036] Figure 8 An inversion model for frozen soil velocity according to an embodiment of the present invention is shown. Detailed Implementation

[0037] It should be understood that the embodiments of the invention shown in the exemplary embodiments are merely illustrative. Although only a few embodiments have been described in detail in this invention, those skilled in the art will readily recognize that various modifications are possible without substantially departing from the teachings of the invention. Accordingly, all such modifications should be included within the scope of the invention. Other substitutions, modifications, variations, and deletions can be made to the design, operating conditions, and parameters of the following exemplary embodiments without departing from the spirit of the invention.

[0038] This invention discloses a method for modeling velocity inversion from surface tomography in plateau permafrost, such as... Figure 1 As shown, the method includes the following steps:

[0039] S1. Utilize micrologging information, drilling velocity information, and CMP first arrival refraction stratification to establish an initial surface model including velocity reversal characteristics;

[0040] S2. Based on the initial surface model, velocity reversal processing is performed in tomographic inversion to obtain a velocity profile containing velocity reversal.

[0041] S3. Identify the permafrost bottom boundary reflection surface based on the superimposed gather profile containing velocity profile;

[0042] S4. Determine the velocity interface of the frozen soil layer based on the shallow frozen soil reflection surface in the frozen soil bottom boundary reflection surface.

[0043] S5. Model Output. The obtained model can be used for static correction calculations or for pre-stack depth migration modeling.

[0044] In the above method, S1 also includes: selecting the development zone based on the first arrival characteristics of a single shot, and selecting the corresponding position grid in the CMP domain to perform CMP first arrival refraction layering based on the single shot characteristics at different positions.

[0045] In the above method, S1 also includes: using micrologging information, drilling velocity information and CMP first arrival refraction stratification as constraints to interpolate and establish an initial surface model.

[0046] In the above method, S1 also includes interpolating based on the correlation between the frozen soil velocity inversion layer and its adjacent strata to establish an initial surface model.

[0047] In the above method, S2 also includes: using an iterative algorithm to perform velocity reversal processing based on the surface initial model.

[0048] In the above methods, the iterative algorithm includes the grid iterative algorithm.

[0049] In the above method, S2 also includes: the vertical grid velocity change of the grid iteration algorithm is not performed according to the positive velocity sequence, but is reversed.

[0050] In the above method, S3 includes: identifying the reflection phase axis of the superimposed gather with high overlay of the small track spacing as the permafrost bottom boundary reflection surface, which has discontinuity, a phase change in the reflection phase axis, is related to the landform, and is not related to the attitude of shallow folded strata.

[0051] In the above method, S4 includes:

[0052] S41. Select different locations, pick up the time of the in-phase axis of the shallow frozen soil reflection, use the superposition speed to perform time-depth conversion, determine the depth of the shallow frozen soil reflection surface, and form depth control points.

[0053] S42. Overlay the depth information of the shallow frozen soil reflection surface at different depth control points onto the tomographic inversion velocity profile, and fit the depth surface of the control points according to the tomographic velocity variation characteristics to form the frozen soil velocity interface.

[0054] According to another embodiment of the present invention, a system for modeling velocity inversion from surface tomography of permafrost in plateau regions is also provided, comprising:

[0055] The first module utilizes micrologging information, drilling velocity information, and CMP first arrival refraction stratification to establish an initial surface model including velocity reversal characteristics.

[0056] The second module performs velocity reversal processing in tomographic inversion based on the surface initial model to obtain a velocity profile containing velocity reversal.

[0057] The third module identifies the permafrost bottom boundary reflection surface based on the superimposed gather profile containing velocity profiles.

[0058] The fourth module determines the velocity interface of the frozen soil layer based on the shallow frozen soil reflection surface in the frozen soil bottom boundary reflection surface.

[0059] The system also includes a fifth module, which is used to output the velocity interface of the frozen soil layer for static correction calculations or for pre-stack depth migration modeling.

[0060] According to another embodiment of the present invention, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, performs the steps of the method as described in any of the preceding embodiments.

[0061] To facilitate understanding of the solutions and effects of the embodiments of the present invention, specific implementation processes and application examples are given below. Those skilled in the art should understand that these examples are merely for the purpose of understanding the present invention, and any specific details therein are not intended to limit the present invention in any way.

[0062] Specific implementation process:

[0063] Step 1: Construct an initial surface model containing velocity reversal features using micrologging, drilling velocity information, and CMP first arrival stratification.

[0064] First, micrologging data and drilling velocity curves were collected, with particular attention paid to velocity reversal characteristics, i.e., the phenomenon where velocity initially increases and then decreases or initially decreases and then increases with depth. Then, based on the first arrival characteristics of individual shots, refraction stratification was performed in the developed areas. Because the permafrost layer has a higher velocity than the native strata, the permafrost developed areas exhibit high-velocity anomalies, resulting in severe first arrival attenuation of individual shots, exhibiting a "capped" phenomenon. Based on the "capped" characteristics of individual shots at different locations, corresponding grids were selected in the CMP domain for refraction stratification, such as... Figure 2 As shown, during stratification, the velocity fitting follows the principle of "higher rather than lower," forming refractive stratification control points. Finally, using micrologging, drilling velocity information, and CMP first-arrival refractive stratification control points as constraints, an initial model is established through interpolation. Considering the connection between the frozen soil velocity inversion layer and other strata, to ensure the integrity and continuity of the model, the inversion layer and the layers above and below it are interpolated according to a perfect similarity (similarity coefficient of 1) to construct the final initial model. CMP first-arrival refractive stratification, interpolation, and similarity coefficient settings can be implemented using specialized software.

[0065] Step 2: Perform velocity inversion processing during tomographic inversion.

[0066] Based on the initial model constraints, a suitable iterative algorithm is selected to handle velocity reversal. During the mesh velocity iteration process, the velocity changes within the vertical mesh do not completely follow the positive velocity sequence (the conventional tomographic inversion velocity model changes in a positive sequence). The above iterative changes only mean that after the initial model is meshed, the relative velocity levels of the velocity reversal mesh remain unchanged during the iteration process, and do not completely follow the positive velocity sequence iteration. This can be implemented by specialized software.

[0067] Step 3: Identification of the frozen soil bottom boundary reflection surface based on the superimposed gather profile.

[0068] There is a significant difference in wave impedance between the permafrost subsurface and the underlying strata, resulting in a reflection interface when superimposed with shallow layers. The velocities at the reflection interface may be positive or negative, leading to phase inconsistencies. Permafrost development is related to water content, and it is more developed in low-lying areas such as valleys, where the reflection interface is relatively more continuous. Figure 3 As shown, the reflective interface and the actual shallow folded strata interface have no similarity or continuity in their contact relationship.

[0069] On the small-spacing, high-coverage seismic overlay profile, shallow layers can be observed to have reflection axes with poor continuity (relatively continuous in river valley depressions), phase changes in the reflection axes, and correlation with surface morphology but not with the attitude of shallow folded strata. These are the reflection surfaces at the bottom of the permafrost.

[0070] Step 4: Interpret the interface of the frozen soil velocity model based on the shallow frozen soil reflection surface.

[0071] Selecting control points to determine the depth of the reflecting surface: Selecting different locations, picking the time of the same direction axis of shallow frozen soil reflection, using the superposition velocity to perform time-depth conversion, determining the approximate depth of the reflecting surface, and forming depth control points; Determining the interface of the frozen soil velocity model: Superimposing the depth information of control points at different locations onto the tomographic inversion velocity profile, referring to the tomographic velocity change characteristics, fitting the control point depth surface, and determining the interface of the frozen soil velocity model.

[0072] Step 5: Model Output

[0073] The resulting tomographic model output can be used for static correction calculations or for pre-stack depth migration modeling.

[0074] Application example:

[0075] This disclosure presents a method for modeling velocity inversion from surface assay in plateau permafrost, such as... Figures 4-8 As shown, this method has been practically applied in the processing of 2D seismic survey lines in the southwestern Qiangtang Basin and in the 2D seismic depth migration processing in the Qilian-Muli area of ​​the Qaidam Basin. In the Long'e'ni area of ​​the Qiangtang Basin, permafrost and shallow folds are well-developed, resulting in extremely low signal-to-noise ratios in seismic data. The application of this method improved the accuracy of pre-stack depth migration processing for shallow folds and small faults. In the 2D pre-stack depth migration processing in the Qilian-Muli area, the application of this method improved the modeling accuracy of permafrost surfaces and enhanced the imaging accuracy of structural components.

[0076] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Any modifications or equivalent substitutions made to the present invention without departing from the spirit and scope thereof should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for modeling inversion velocity from surface tomography in plateau permafrost, characterized in that, include: S1. Utilize micrologging information, drilling velocity information, and CMP first arrival refraction stratification to establish an initial surface model including velocity reversal characteristics; S2. Based on the initial surface model, velocity reversal processing is performed in tomographic inversion to obtain a velocity profile containing velocity reversal. S3. Identify the permafrost bottom boundary reflection surface based on the superimposed gather profile containing the velocity profile; S4. Determine the velocity interface of the frozen soil layer based on the shallow frozen soil reflection surface in the frozen soil bottom boundary reflection surface.

2. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 1, characterized in that, The S1 further includes: selecting a development zone based on the first arrival characteristics of a single shot, and selecting a corresponding position grid in the CMP domain based on the single shot characteristics at different positions to perform the CMP first arrival refraction layering.

3. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 2, characterized in that, S1 further includes: using the micrologging information, the drilling speed information and the CMP first arrival refraction stratification as constraints, interpolating to establish the initial surface model.

4. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 3, characterized in that, S1 further includes performing the interpolation based on the correlation between the frozen soil velocity inversion layer and its adjacent strata to establish the initial model of the surface layer.

5. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 1, characterized in that, S2 further includes: performing the velocity reversal process based on the initial surface model using an iterative algorithm.

6. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 5, characterized in that, The iterative algorithm includes a grid iterative algorithm.

7. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 6, characterized in that, S2 further includes: the vertical grid velocity change of the grid iteration algorithm is not performed according to the positive velocity change, and the velocity reversal process is performed.

8. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 1, characterized in that, S3 includes: identifying the reflection phase axis of the superimposed gather that has discontinuous reflection phase axis with phase change, is related to the landform, and is not related to the attitude of shallow folded strata as the permafrost bottom boundary reflection surface.

9. The method for modeling inversion velocity in plateau permafrost surface tomography according to claim 1, characterized in that, S4 includes: S41. Select different locations, pick up the in-phase time of shallow frozen soil reflection, use the superposition speed to perform time-depth conversion, determine the depth of the shallow frozen soil reflection surface, and form a depth control point. S42. The depth information of the shallow frozen soil reflection surface at different depth control points is superimposed on the tomographic inversion velocity profile. Based on the tomographic velocity profile variation characteristics, the depth surface of the control points is fitted to form the frozen soil velocity interface.

10. A system for modeling velocity inversion from surface tomography in plateau permafrost, characterized in that, include: The first module utilizes micrologging information, drilling velocity information, and CMP first arrival refraction stratification to establish an initial surface model including velocity reversal characteristics. The second module performs velocity reversal processing in tomographic inversion based on the surface initial model to obtain a velocity profile containing velocity reversal. The third module identifies the permafrost bottom boundary reflection surface based on the superimposed gather profile containing the velocity profile; The fourth module determines the frozen soil velocity interface based on the shallow frozen soil reflection surface in the frozen soil bottom boundary reflection surface.

11. The plateau permafrost surface tomography inversion velocity modeling system according to claim 8, characterized in that, Also includes: The fifth module is used to output the velocity interface of the frozen soil layer for static correction calculation or for pre-stack depth migration modeling.

12. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it performs the steps of the method as described in any one of claims 1-9.

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