Micro-motion H / V spectrum ratio method three-step stratum inversion method
By employing a three-step formation inversion method based on the micro-motion H/V spectral ratio, and optimizing the model parameter space using empirical formulas and H/V curve characteristics, the problem of relying on well logging data in existing technologies is solved, achieving more efficient and accurate subsurface structure inversion.
Patent Information
- Application Number
- CN202511266677.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-05
- Publication Date
- 2026-01-23
AI Technical Summary
Existing methods for imaging subsurface structures rely on well logging data and geological data. In particular, when conventional well logging data is lacking, it is difficult to determine the search range of the initial model, resulting in inaccurate inversion results.
A three-step stratigraphic inversion method using the micro-motion H/V spectral ratio is adopted. The empirical formula is used to initially estimate the stratigraphic position and velocity. The stratigraphic positions are merged by combining dual thresholds, and the search range is further narrowed by combining the characteristics of the H/V curve. The model parameter space is optimized, and low-velocity and high-velocity layers are automatically identified.
It improves the resolution and accuracy of inversion results, avoids local optima, is applicable to a wide range of underground structure studies, especially in areas lacking well logging data, and simplifies the operation process.
Smart Images
Figure CN121386004A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of geology, and in particular to a three-step stratigraphic inversion method based on micromotion H / V spectral ratio. Background Technology
[0002] Background noise-based imaging methods for subsurface structures have developed rapidly in recent years and are widely used in regional and local scale subsurface structure research. Among them, the micro-motion H / V spectral ratio method, as a typical passive source exploration technique, can effectively identify sedimentary layer thickness, VS30, site magnification factor, vulnerability factor, etc., by using information at the resonance frequency. It has shown unique advantages in shallow structure detection and has been widely used in research on sedimentary basins, permafrost layers, and even planetary exploration (such as Mars).
[0003] However, using only the resonant frequency and amplitude significantly ignores the information contained in other peaks and valleys of the H / V curve. Therefore, applying the entire H / V curve to invert the underground medium structure is a better approach, as it can obtain richer and more comprehensive information.
[0004] On the other hand, most current inversion work relies on prior information, derived from well logging data, geological data, etc., to determine the search space of the inversion model. However, during drilling operations, cement needs to be injected into the space between the wellbore and the casing to complete the cementing work. Shallow sections below 200 meters are mostly casing cementing sections, lacking conventional well logging data, making it difficult to determine the initial model search range. Summary of the Invention
[0005] The purpose of this invention is to provide a three-step stratigraphic inversion method based on the micromotion H / V spectral ratio method, in order to solve the problem that existing underground structure imaging methods rely on well logging data and geological data.
[0006] The above-mentioned objective of this application is achieved through the following technical solution: S1: Using empirical formulas, the average velocity of the S-wave in the peak layer and sedimentary layer is initially estimated, and the STEP1 average model is obtained by inversion. S2: By combining the two thresholds, the layers of the STEP1 average model are merged to obtain the STEP2 average model. S3: Further narrow the search range and invert the STEP2 average model to obtain the shallow shear wave velocity structure below a single station in the study area.
[0007] Optionally, step S1 includes: According to empirical formulas Preliminary estimates suggest that the peak value represents a specific stratum. Where 96 and -1.388 are empirical coefficients, It is the negative 1.388th power of the peak frequency.
[0008] Optionally, step S1 may further include: According to empirical formulas Determine the average velocity of S-waves in the sedimentary layer. ; Let the amplification factor at the resonant frequency of the H / V curve be... The impedance ratio between the bedrock and sedimentary layers is related to the following:
[0009] in, Indicates bedrock velocity; Indicates the density of bedrock; Indicates the density of the overlying sediments; let ,but ; The STEP1 average model is discretized into ten layers: the velocity and thickness of the first two layers are respectively determined by... and Confirmed; the last two layers are... Characterization; the velocity of the middle six layers in and The thickness varies between 5 and 40 meters.
[0010] Optionally, step S2 includes: Based on the STEP1 average model, a combination of fixed threshold and percentage threshold is set to dynamically determine the velocity, and adjacent layers with similar velocities are merged. The speed of the merged current layer is taken as the average value of the merged layers, and the thickness is taken as the sum of the values of the merged layers. Thin layers with a thickness less than a preset value are removed, and their thickness is evenly distributed to adjacent upper and lower layers to determine the final number of inverted layers.
[0011] Optionally, step S2 may further include: The search range for layer thickness is set to ±50% of the merged value, the initial velocity boundary is set to ±30%, and the velocity profile is monotonically increasing. By utilizing the minimum and second maximum values in the H / V curve, low-velocity and high-velocity layers are identified. Based on the corresponding layer information obtained from the STEP1 average model, the velocity search space is further constrained within a specific depth and velocity range.
[0012] Optionally, step S3 includes: Based on the STEP2 averaging model, for For the above layers, the search ranges for thickness and velocity are constrained to ±40% and ±20%, respectively; for For the following layers, the search ranges for thickness and velocity are constrained to ±50% and ±30%, respectively.
[0013] An electronic device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to enable the electronic device to perform a three-step stratigraphic inversion method based on micro-motion H / V spectral ratio.
[0014] A computer-readable storage medium storing instructions that, when executed, perform a three-step stratigraphic inversion method based on micro-motion H / V spectral ratio.
[0015] The beneficial effects of the technical solution provided in this application are: Based on empirical formulas and H / V curve resonance frequencies, the stratigraphic level and velocity range are rapidly estimated, thus establishing the initial model space for the first step. Utilizing dynamic layer merging and constraints based on the secondary peaks and valleys of the H / V curve, the locations of low- and high-velocity layers are automatically identified, and the number of model layers and parameter search range are optimized. Based on the results of the first two steps, the model space is further adjusted to make the inversion sampling more concentrated and efficient, thereby improving resolution and avoiding getting trapped in local optima. The shear wave velocity structure below 200 meters below a single station is obtained using a "three-step" inversion method. Compared to traditional inversion methods using well logging data, this method has wider applicability and is simpler to operate. Attached Figure Description
[0016] The present application will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a schematic diagram of parameter space adjustment in the embodiments of this application; Figure 2 This is a diagram of the shallow shear wave velocity structure in the embodiments of this application; Figure 3 This is a schematic diagram of the electronic device structure in the embodiments of this application. Detailed Implementation
[0017] To provide a clearer understanding of the technical features, objectives, and effects of this application, the specific embodiments of this application will now be described in detail with reference to the accompanying drawings.
[0018] The embodiments of this application provide a three-step stratigraphic inversion method based on the micro-motion H / V spectral ratio.
[0019] Please refer to Figure 1 , Figure 1 This is a schematic diagram of parameter space adjustment for a three-step stratigraphic inversion method based on the micro-motion H / V spectral ratio in an embodiment of this application, including: S1: Using empirical formulas, the average velocity of the S-wave in the peak layer and sedimentary layer is initially estimated, and the STEP1 average model is obtained by inversion. S2: By combining the two thresholds, the layers of the STEP1 average model are merged to obtain the STEP2 average model. S3: Further narrow the search range and invert the STEP2 average model to obtain the shallow shear wave velocity structure below a single station in the study area.
[0020] In one specific embodiment of this application, the present invention provides a three-step inversion technique based on the H / V curve morphology, which can be combined with a Markov chain-based Monte Carlo (MCMC) algorithm to improve sampling efficiency, obtain a more comprehensive and accurate inversion parameter space, and potentially escape local minima. This helps to construct more accurate and reliable shallow subsurface structures up to 200 meters deep, thereby guiding human survival and production activities. Our method can be widely applied in urban exploration and planning, oil and gas mineral development, and site selection for major engineering projects.
[0021] In one specific implementation of this application, the shear wave velocity structure below 200 meters below a single station is obtained by utilizing a "three-step" inversion method. For example... Figure 2 As shown, the blue solid line represents the theoretical model, the yellow solid line represents the average model obtained through inversion, and the white dashed line represents the model parameter space. Traditional inversion methods rely on prior information to obtain the white dashed line portion in the figure, while the "three-step" method can automatically identify and obtain the parameter space after calculating the H / V curve.
[0022] Step S1 includes: As one embodiment, this step yields the "STEP1" model space required by the method of the present invention. Preliminary estimates of shallow subsurface structure parameters are obtained based on empirical relationships.
[0023] According to empirical formulas Preliminary estimates suggest that the peak value represents a specific stratum. Where 96 and -1.388 are empirical coefficients, It is the negative 1.388th power of the peak frequency.
[0024] Step S1 also includes: According to empirical formulas Determine the average velocity of S-waves in the sedimentary layer. ; Let the amplification factor at the resonant frequency of the H / V curve be... The impedance ratio between the bedrock and sedimentary layers is related to the following:
[0025] in, Indicates bedrock velocity; Indicates the density of bedrock; Indicates the density of the overlying sediments; let ,but ; As one example, bedrock density With the density of overlying sediments Given equal density, the bedrock velocity is Due to bedrock density Typically greater than the density of the overlying sediments ,lead to It is overrated.
[0026] The STEP1 average model is discretized into ten layers: the velocity and thickness of the first two layers are respectively determined by... and Confirmed; the last two layers are... Characterization; the velocity of the middle six layers in and The thickness varies between 5 and 40 meters.
[0027] As one embodiment, the speed of the middle six layers is and The thickness varies between 5 and 40 meters, such as Figure 1 As shown in b.
[0028] Step S2 includes: Based on the STEP1 average model, a combination of fixed threshold and percentage threshold is set to dynamically determine the velocity, and adjacent layers with similar velocities are merged. The speed of the merged current layer is taken as the average value of the merged layers, and the thickness is taken as the sum of the values of the merged layers. Thin layers with a thickness less than a preset value are removed, and their thickness is evenly distributed to adjacent upper and lower layers to determine the final number of inverted layers.
[0029] Step S2 also includes: The search range for layer thickness is set to ±50% of the merged value, the initial velocity boundary is set to ±30%, and the velocity profile is monotonically increasing. By utilizing the minimum and second maximum values in the H / V curve, low-velocity and high-velocity layers are identified. Based on the corresponding layer information obtained from the STEP1 average model, the velocity search space is further constrained within a specific depth and velocity range.
[0030] As one example, the preliminary results of the STEP1 average model are used to guide the depth range of the target layer, such as... Figure 1 As shown in c.
[0031] Step S3 includes: Based on the STEP2 averaging model, for For the above layers, the search ranges for thickness and velocity are constrained to ±40% and ±20%, respectively; for For the following layers, the search ranges for thickness and velocity are constrained to ±50% and ±30%, respectively.
[0032] As one implementation, based on the STEP2 average model, the search range is further narrowed to improve resolution. This ensures more concentrated sampling in the model space and allows for adjustment of the model space, especially in cases where the actual parameters of some layers in the "STEP2 average model" may fall outside the set search range, such as... Figure 1 As shown in d. Using the technology of this invention, a three-step inversion is performed to obtain the shallow shear wave velocity structure below a single station in the study area.
[0033] This application also discloses an electronic device. (See reference...) Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 500 may include: at least one processor 501, at least one network interface 504, a user interface 503, a memory 505, and at least one communication bus 502.
[0034] The communication bus 502 is used to enable communication between these components.
[0035] The user interface 503 may include a display screen, and optionally, the user interface 503 may also include a standard wired interface or a wireless interface.
[0036] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).
[0037] This application also discloses a computer-readable storage medium storing multiple instructions adapted for loading by a processor to execute the above-described three-step stratigraphic inversion method using the micro-motion H / V spectral ratio method.
[0038] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure.
[0039] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.
Claims
1. A three-step stratigraphic inversion method based on micro-motion H / V spectral ratio, characterized in that, The method includes the following steps: S1: Using empirical formulas, the average velocity of the S-wave in the peak layer and sedimentary layer is initially estimated, and the STEP1 average model is obtained by inversion. S2: By combining the two thresholds, the layers of the STEP1 average model are merged to obtain the STEP2 average model. S3: Further narrow the search range and invert the STEP2 average model to obtain the shallow shear wave velocity structure below a single station in the study area.
2. The three-step stratigraphic inversion method based on micro-motion H / V spectral ratio as described in claim 1, characterized in that, Step S1 includes: According to empirical formulas Preliminary estimates suggest that the peak value represents a specific stratum. Where 96 and -1.388 are empirical coefficients, It is the negative 1.388th power of the peak frequency.
3. The three-step stratigraphic inversion method based on micro-motion H / V spectral ratio as described in claim 2, characterized in that, Step S1 also includes: According to empirical formulas Determine the average velocity of S-waves in the sedimentary layer. ; Let the amplification factor at the resonant frequency of the H / V curve be... The impedance ratio between the bedrock and sedimentary layers is related to the following: in, Indicates bedrock velocity; Indicates the density of bedrock; Indicates the density of the overlying sediments; let ,but ; The STEP1 average model is discretized into ten layers: the velocity and thickness of the first two layers are respectively determined by... and Confirmed; the last two floors are... Characterization; the velocity of the middle six layers in and The thickness varies between 5 and 40 meters.
4. The three-step stratigraphic inversion method based on micro-motion H / V spectral ratio as described in claim 3, characterized in that, Step S2 includes: Based on the STEP1 average model, a combination of fixed threshold and percentage threshold is set to dynamically determine the velocity, and adjacent layers with similar velocities are merged. The speed of the merged current layer is taken as the average value of the merged layers, and the thickness is taken as the sum of the values of the merged layers. Thin layers with a thickness less than a preset value are removed, and their thickness is evenly distributed to adjacent upper and lower layers to determine the final number of inverted layers.
5. The three-step stratigraphic inversion method based on micro-motion H / V spectral ratio as described in claim 4, characterized in that, Step S2 also includes: The search range for layer thickness is set to ±50% of the merged value, the initial velocity boundary is set to ±30%, and the velocity profile is monotonically increasing. By utilizing the minimum and second maximum values in the H / V curve, low-velocity and high-velocity layers are identified. Based on the corresponding layer information obtained from the STEP1 average model, the velocity search space is further constrained within a specific depth and velocity range.
6. The three-step stratigraphic inversion method based on micro-motion H / V spectral ratio as described in claim 5, characterized in that, Step S3 includes: Based on the STEP2 averaging model, for For the above layers, the search ranges for thickness and velocity are constrained to ±40% and ±20%, respectively; for For the following layers, the search ranges for thickness and velocity are constrained to ±50% and ±30%, respectively.
7. An electronic device, characterized in that, The device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-6.
8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed by a computer, perform the method as described in any one of claims 1-6.