DTCIG-based FWI speed inversion uncertainty analysis method and device
Through the DTCIG-based method, the delay deviation and amplitude in the seismic data are extracted and its uncertainty measurement is calculated, which solves the problem of inefficiency of the existing FWI velocity inversion uncertainty analysis method, and achieves more efficient uncertainty analysis.
Patent Information
- Application Number
- CN202311800591.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-12-25
- Publication Date
- 2025-06-27
AI Technical Summary
The existing FWI speed inversion uncertainty analysis methods are inefficient and cannot be effectively applied in production processes.
Using a DTCIG-based method, the forward propagation of seismic waves is performed through the preset velocity model, seismic data is obtained, and the DTCIG is obtained by reverse-time offset when introducing the delay time dimension. Then, the time dimension of DTCIG is interpolated and encrypted, the delay deviation and amplitude of the focus energy are picked up, its uncertainty measure is calculated, and the uncertainty interval of FWI speed inversion is finally calculated.
The efficiency of velocity inversion uncertainty analysis was significantly improved, and the delay deviation and amplitude were extracted from DTCIG for uncertainty analysis, avoiding the step of calculating the posterior distribution, and overcoming the inefficiency problem of existing methods.
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Figure CN120214904A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of oil and gas exploration, and particularly to a method and device for analyzing the uncertainty of FWI velocity inversion based on DTCIG. Background Art
[0002] Full-Waveform Inversion (FWI) is a geophysical imaging technology widely used in the fields of oil and gas exploration, seismic monitoring, etc. It reconstructs the subsurface structure by matching the full waveform information of seismic data with the predicted waveforms of the subsurface model, and velocity inversion is the core link. In understanding the FWI inversion results, it is crucial to analyze the uncertainty of the velocity update amount.
[0003] The analysis of the uncertainty of FWI velocity inversion is a frontier issue, and the current relevant research results are relatively limited. The existing analysis methods are mainly based on Bayesian theory. First, the posterior distribution is calculated using the Bayesian formula, and then sampling is performed from the posterior distribution for uncertainty analysis. However, the computational cost of the posterior distribution severely restricts the efficiency of the uncertainty analysis of FWI velocity inversion. Although the improvement of the sampling method slightly improves the efficiency of uncertainty analysis, the existing methods are still of low efficiency and cannot be effectively applied to the production process.
[0004] Based on this, there is an urgent need to provide a solution for a method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, so as to solve at least one of the above problems. Summary of the Invention
[0005] To have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important constituent elements or delineate the protection scope of these embodiments, but rather serves as a preface to the subsequent detailed description.
[0006] In view of the deficiencies of the prior art, the embodiments of the present disclosure provide a method for analyzing the uncertainty of FWI velocity inversion based on DTCIG to improve the efficiency of the uncertainty analysis of FWI velocity inversion.
[0007] In a first aspect, an embodiment of the present disclosure provides a method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, including: performing forward propagation of seismic waves through a preset velocity model to obtain seismic data; performing reverse time migration on the preset velocity model and the seismic data with the introduction of the delay time dimension to obtain DTCIG; interpolating and encrypting the time dimension of DTCIG and picking up the time delay deviation and amplitude of the focused energy on the encrypted DTCIG; calculating the uncertainty measures of the time delay deviation and amplitude respectively through the probability distributions of the time delay deviation and amplitude; calculating the uncertainty interval of FWI velocity inversion according to the uncertainty measures of the time delay deviation and amplitude.
[0008] In a preferred technical solution of the above method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, the performing forward propagation of seismic waves through a preset velocity model to obtain seismic data includes: setting a seismic source and arranging a plurality of receivers around the seismic source; the seismic source emits seismic waves, simulates the forward propagation of seismic waves according to the velocity model, and the receivers receive the turning waves and direct waves; obtaining seismic data according to the simulation results.
[0009] In a preferred technical solution of the above method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, the performing reverse time migration on the preset velocity model and the seismic data with the introduction of the delay time dimension to obtain DTCIG includes: stacking the image slices corresponding to each delay time to form DTCIG, where each pixel point in the formed DTCIG corresponds to a delay time and the spatial position of the corresponding receiver.
[0010] In a preferred technical solution of the above method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, the performing reverse time migration on the preset velocity model and the seismic data with the introduction of the delay time dimension to obtain DTCIG further includes: at the position of a near offset, where the turning wave covers a shallower position, DTCIG has a larger deviation at a shallower position.
[0011] In a preferred technical solution of the above method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, the performing reverse time migration on the preset velocity model and the seismic data with the introduction of the delay time dimension to obtain DTCIG further includes: at the position of a medium offset, where the turning wave covers a deeper position, DTCIG has a deviation at a deeper position.
[0012] In a preferred technical solution of the above method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, the performing reverse time migration on the preset velocity model and the seismic data with the introduction of the delay time dimension to obtain DTCIG further includes: at the position of a far offset, where the signal of the turning wave is weak, the information on DTCIG is inaccurate.
[0013] In the above preferred technical solution of the FWI velocity inversion uncertainty analysis method based on DTCIG, the interpolation encryption of the time dimension of DTCIG includes: interpolating and encrypting the time dimension of DTCIG, increasing the density of time sampling, and obtaining high time resolution and time information.
[0014] In the above preferred technical solution of the FWI velocity inversion uncertainty analysis method based on DTCIG, the picking of the time delay deviation and amplitude of the focused energy on the encrypted DTCIG further includes: using the semblance picking method to pick the time delay deviation and amplitude of the rotary wave focused energy at each imaging point on the encrypted DTCIG.
[0015] In the above preferred technical solution of the FWI velocity inversion uncertainty analysis method based on DTCIG, the calculation of the uncertainty measures of the time delay deviation and amplitude respectively through the probability distributions of the time delay deviation and amplitude further includes: According to the principle of semblance picking, when the time delay deviation follows a normal distribution, the uncertainty measure of the time delay deviation:
[0016]
[0017] When the amplitude follows a Rayleigh distribution, the uncertainty measure of the amplitude:
[0018]
[0019] where x is the independent variable of the normal distribution, y is the time delay deviation, z is the amplitude, and σ 2 is the variance.
[0020] In the above preferred technical solution of the FWI velocity inversion uncertainty analysis method based on DTCIG, the calculation of the uncertainty interval of the FWI velocity inversion according to the uncertainty measures of the time delay deviation and amplitude includes: when the uncertainty measure U1(y) of the time delay deviation and the uncertainty measure U2(z) of the amplitude are independent or weakly correlated, obtaining the lower bound I low = U1(y) × U2(z); when the uncertainty measure U1(y) of the time delay deviation and the uncertainty measure U2(z) of the amplitude are strongly correlated, obtaining the upper bound I up = min(U1(y), U2(z)).
[0021] In the above preferred technical solution of the FWI velocity inversion uncertainty analysis method based on DTCIG, if the calculated values of I low and I up are both 0, it is determined that the velocity update amount is not credible; if I low and I upIf the calculated values are all 1, the velocity update amount is determined to be credible; if I low and I up have different calculated values, it is determined that the velocity update amount is partially credible within the interval.
[0022] In a second aspect, an embodiment of the present disclosure provides a DTCIG-based FWI velocity inversion uncertainty analysis device. The DTCIG-based FWI velocity inversion uncertainty analysis device includes a data acquisition module, a DTCIG acquisition module, an encryption module, an uncertainty metric calculation module, and an uncertainty interval calculation module. The data acquisition module is configured to perform forward propagation of seismic waves through a preset velocity model to obtain seismic data; the DTCIG acquisition module is configured to perform reverse time migration on the preset velocity model and seismic data in the case of introducing a delay time dimension to obtain DTCIG; the encryption module is configured to interpolate and encrypt the time dimension of DTCIG and pick up the time delay deviation and amplitude of the focused energy on the encrypted DTCIG; the uncertainty metric calculation module is configured to calculate the uncertainty metrics of the time delay deviation and amplitude respectively through the probability distributions of the time delay deviation and amplitude; the uncertainty interval calculation module is configured to calculate the uncertainty interval of FWI velocity inversion according to the uncertainty metrics of the time delay deviation and amplitude.
[0023] The DTCIG-based FWI velocity inversion uncertainty analysis method and device provided by the embodiments of the present disclosure can achieve the following technical effects:
[0024] Extract the time delay deviation and amplitude from DTCIG for uncertainty analysis without calculating the posterior distribution, thereby overcoming the constraints faced by existing FWI velocity inversion uncertainty analysis methods. Significantly improve the efficiency of velocity inversion uncertainty analysis.
[0025] The above general description and the following description are only exemplary and explanatory and are not used to limit this application. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] One or more embodiments are exemplarily illustrated by corresponding drawings. These exemplary illustrations and the drawings do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation, and among them:
[0027] Figure 1 Shows a schematic flow chart of a DTCIG-based FWI velocity inversion uncertainty analysis method provided by the present invention;
[0028] Figure 2a Shows a schematic diagram of a preset velocity model provided by the present invention;
[0029] Figure 2bShows the seismic wave data under the preset velocity model provided by the present invention; Figure 2a Schematic diagram of seismic wave data under the preset velocity model;
[0030] Figure 3 Shows a schematic diagram of obtaining DTCIG by reverse time migration provided by the present invention;
[0031] Figure 4a Shows the Figure 3 Schematic diagram of the time slice before encryption at spatial position 401;
[0032] Figure 4b Shows the Figure 3 Schematic diagram of the time slice after encryption at spatial position 401;
[0033] Figure 5a Shows a schematic diagram of the picked time delay deviation provided by the present invention;
[0034] Figure 5b Shows a schematic diagram of the picked amplitude provided by the present invention;
[0035] Figure 6a Shows a schematic diagram of the uncertainty measure of the time delay deviation provided by the present invention;
[0036] Figure 6b Shows a schematic diagram of the uncertainty measure of the amplitude provided by the present invention;
[0037] Figure 7a Shows a schematic diagram of the lower bound of the uncertainty interval of velocity inversion provided by the present invention;
[0038] Figure 7b Shows a schematic diagram of the upper bound of the uncertainty interval of velocity inversion provided by the present invention;
[0039] Figure 7c Shows a schematic diagram of the difference between the upper and lower bounds of the uncertainty interval of velocity inversion provided by the present invention;
[0040] Figure 8 Shows a schematic diagram of a device for analyzing the uncertainty of FWI velocity inversion based on DTCIG provided by the present invention.
[0041] Reference numerals:
[0042] 11. Data acquisition module; 12. DTCIG acquisition module; 13. Encryption module; 14. Uncertainty measure calculation module; 15. Uncertainty interval calculation module. Detailed implementation manners
[0043] In order to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of explanation, numerous details are provided to give a thorough understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be shown in a simplified manner to simplify the drawings.
[0044] In the embodiments of the present disclosure, the terms "first", "second", etc. in the description and claims of the embodiments of the present disclosure and the above-mentioned accompanying drawings are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances so as to describe the embodiments of the present disclosure described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion.
[0045] In the embodiments of the present disclosure, the orientation or positional relationship indicated by the terms "upper", "lower", "inner", "middle", "outer", "front", "rear", etc. is based on the orientation or positional relationship shown in the accompanying drawings. These terms are mainly used to better describe the embodiments of the present disclosure and their embodiments, and are not used to limit that the indicated devices, elements or components must have a specific orientation or be constructed and operated in a specific orientation. And, in addition to being able to represent an orientation or positional relationship, some of the above terms may also be used to represent other meanings. For example, the term "upper" may also be used to represent a certain attachment relationship or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in the embodiments of the present disclosure can be understood according to specific circumstances.
[0046] In addition, the terms "arranged", "connected", "fixed" should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or there is internal communication between two devices, elements or components. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present disclosure can be understood according to specific circumstances.
[0047] Unless otherwise specified, the term "plurality" means two or more.
[0048] It should be noted that, without conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.
[0049] As Figure 1 shown, the embodiments of the present disclosure provide a control method for reducing copper embrittlement defects in hot-rolled weathering steel, including:
[0050] Step S1: Perform forward propagation of seismic waves through a preset velocity model to obtain seismic data;
[0051] Step S2: Perform reverse time migration on the preset velocity model and the seismic data by introducing a delay time dimension to obtain DTCIG;
[0052] Step S3: Interpolate and encrypt the time dimension of DTCIG, and pick up the time delay deviation and amplitude of the focused energy on the encrypted DTCIG;
[0053] Step S4: Calculate the uncertainty measures of the time delay deviation and the amplitude respectively through the probability distributions of the time delay deviation and the amplitude;
[0054] Step S5: Calculate the uncertainty interval of FWI velocity inversion according to the uncertainty measures of the time delay deviation and the amplitude.
[0055] Specifically, the preset velocity model is a conventional velocity model. Use this preset velocity model to simulate the forward propagation of seismic waves in a formation at a certain depth to obtain seismic data d. Combine the obtained seismic data d with the previous preset velocity model and add a delay time dimension, and combine with the reverse time migration technique to obtain DTCIG (Delay Time Common Image Gather). Increase the density of the time dimension of DTCIG to improve the picking accuracy. Pick up the points with the largest time delay deviation and amplitude values of the focused energy on the encrypted DTCIG. Calculate the uncertainty measures of the time delay deviation and the amplitude respectively according to the probability distributions that the time delay deviation and the amplitude follow, and finally calculate the uncertainty interval of FWI velocity inversion. Thus, the efficiency of velocity inversion uncertainty analysis is significantly improved. Extract the time delay deviation and the amplitude from DTCIG for uncertainty analysis without calculating the posterior distribution, thereby overcoming the constraints faced by the existing FWI velocity inversion uncertainty analysis methods.
[0056] As Figures 2a - 2b shown, in the preferred technical solution of the present application, performing forward propagation of seismic waves through a preset velocity model to obtain seismic data includes: setting a seismic source and arranging a plurality of receivers around the seismic source; the seismic source emits seismic waves, simulates the forward propagation of seismic waves according to the velocity model, and the receivers receive the converted waves and the direct waves; obtaining seismic data according to the simulation results.
[0057] Specifically, as Figure 2aAs shown in the figure, the red pentagram in the middle represents the seismic source, and the triangles on both sides represent the receivers. The receivers are the geophone points. The horizontal direction (XLINE_NO) is the spatial position of the seismic wave. On the left side of the vertical direction, the depth of the formation (depth) ranges from 0 to 10,000 meters, and on the right side of the vertical direction, it represents the propagation speed corresponding to the color in the figure. The unit of speed is m / s. The speed in the speed model increases linearly. The signals received by the receivers are the turning wave and the direct wave respectively. Figure 2b In the figure, the horizontal direction is the spatial position, and on the left side of the vertical direction, it represents the time (time) when the geophone point receives the seismic signal, and the unit is milliseconds. On the right side of the vertical direction, it represents the magnitude of the seismic signal corresponding to the color in the figure. Figure 2b The black solid line in the figure represents the time when the turning wave corresponding to each index is received at 0 polarization. In this speed model, d = Modeling(velocity, epsilon, delta, dip, azimuth) is used to obtain the seismic data d, where velocity, epsilon, delta, dip, and azimuth respectively correspond to the corresponding model data, velocity is the variable substituted, and the others are specified values.
[0058] In the preferred technical solution of the present application, the preset speed model and seismic data are subjected to reverse time migration in the case of introducing the delay time dimension to obtain DTCIG, including: stacking the image slices corresponding to each delay time to form DTCIG, where each pixel point in the formed DTCIG corresponds to a delay time and the spatial position of the corresponding receiver.
[0059] Specifically, as Figure 3 shown, the horizontal direction is the spatial position. On the left side of the vertical direction, it represents the depth in the formation ranging from 0 to 10,000 meters, and on the right side of the vertical direction, it represents the magnitude of DTCIG corresponding to the color in the figure. The figure shows the situation of the time-delay gather of the turning wave corresponding to multiple indexes, and the positions where the time-delay gather deviates are clearly indicated. By using the data d and models such as velocity, epsilon, delta, dip, and azimuth, combined with the reverse time migration (Reverse Time Migration) technology, and on this basis, introducing the delay time dimension, DTCIG is obtained. The specific model used is as follows, DTCIG = RTM(d, velocity, epsilon, delta, dip, azimuth, delay time). Stacking the image slices corresponding to each delay time forms DTCIG, and each of its pixel points corresponds to a specific delay time and the spatial position of the receiving point, thereby providing richer underground structure information.
[0060] In a preferred technical solution of the present application, inverse time migration is performed on the preset velocity model and seismic data with the introduction of the delay time dimension to obtain the DTCIG, and it further includes: at the position of a near offset, where the surface-related multiple coverage is relatively shallow, the DTCIG has a large deviation at a relatively shallow position.
[0061] Specifically, as Figure 3 shown, the position of the near offset refers to the lateral spatial position within the range of 700 - 900, such as at 701 or 801. The relatively shallow position refers to the depth range of 0 - 2500 meters. Since the propagation path of the surface-related multiple restricts its coverage range at deep positions, the surface-related multiple only covers relatively shallow positions, so the DTCIG already has a large deviation at relatively shallow positions.
[0062] In a preferred technical solution of the present application, inverse time migration is performed on the preset velocity model and seismic data with the introduction of the delay time dimension to obtain the DTCIG, and it further includes: at the position of a medium offset, where the surface-related multiple coverage is relatively deep, the DTCIG has a deviation at a relatively deep position.
[0063] Specifically, as Figure 3 shown, the position of the medium offset refers to the lateral spatial position within the ranges of 200 - 700 and 900 - 1400, such as at 301 or 401. The relatively deep position refers to the depth range of 2500 - 6500 meters. The surface-related multiple can cover relatively deep positions, and a deviation begins to appear in the DTCIG at approximately 6500 meters.
[0064] In a preferred technical solution of the present application, inverse time migration is performed on the preset velocity model and seismic data with the introduction of the delay time dimension to obtain the DTCIG, and it further includes: at the position of a far offset, the signal of the surface-related multiple is weak, and the information on the DTCIG is inaccurate.
[0065] Specifically, as Figure 3 shown, the position of the far offset refers to the lateral spatial position below 200 and above 1400. For example, at 1 and 101, due to factors such as propagation attenuation and interference, the signal of the surface-related multiple is relatively weak, which may result in inaccurate information on the DTCIG.
[0066] In a preferred technical solution of the present application, interpolating and densifying the time dimension of the DTCIG includes: interpolating and densifying the time dimension of the DTCIG to increase the density of time sampling and obtain high time resolution and time information. Picking the delay deviation and amplitude of the focused energy on the densified DTCIG further includes: using the semblance picking method to pick the delay deviation and amplitude of the focused energy of the surface-related multiple at each imaging point on the densified DTCIG.
[0067] Specifically, oversample is used to interpolate and encrypt the time dimension of DTCIG: oversampled_DTCIG = oversample(DTCIG); for the encrypted DTCIG, the time delay deviation and amplitude of the rotary wave focusing energy are picked at each imaging point. For example, the following formula is used: dt, Amp = picker(oversampled_DTCIG).
[0068] As Figures 4a - 4b shown, encryption is performed on the spatial position 401 in Figure 3 . Before encryption, there are 39 time slices, and after encryption, there are 761 time slices. Figure 4a And Figure 4b in, the horizontal direction represents the delay time (DELAY_T). The left side of the vertical direction represents the transmission depth of seismic waves in the formation, and the value range is 0 - 10,000 meters. The right side of the vertical direction represents the size of the time slice corresponding to the color in the figure. As Figures 5a to 5b shown, it can be seen from this that the time delay deviation and amplitude of the rotary wave focusing energy are picked at the imaging point using the semblance picking method. Among them, the horizontal direction is the spatial position, the left side of the vertical direction represents the depth in the formation, and the right side of the vertical direction represents the size of the time delay deviation and amplitude corresponding to the color in the figure.
[0069] In the preferred technical solution of the present application, the uncertainty measures of the time delay deviation and amplitude are calculated respectively through the probability distributions of the time delay deviation and amplitude, including: according to the principle of semblance picking, when the time delay deviation follows a normal distribution, the uncertainty measure of the time delay deviation:
[0070]
[0071] When the amplitude follows a Rayleigh distribution, the uncertainty measure of the amplitude:
[0072]
[0073] Among them, x is the independent variable of the normal distribution, y is the time delay deviation, z is the amplitude, and σ 2 is the variance.
[0074] Specifically, the uncertainty measures of the time delay deviation and amplitude represent the probability of accuracy. According to the principle of semblance picking, the picking result of the time delay deviation can reflect the accuracy of the model. A smaller time delay deviation indicates that the model is more accurate, while a larger time delay deviation indicates that there are larger errors in the model. For example, assume that the time delay deviation follows a normal distribution:
[0075]
[0076] The expected value of this normal distribution is 0, and the variance is σ 2 It is related to the frequency of reverse time migration. Then, the uncertainty measure U1(y) of the time delay deviation can be calculated by the following formula:
[0077]
[0078] Assume that the amplitude follows a Rayleigh distribution:
[0079]
[0080] Its parameter σ is related to the amplitude of DTCIG. Then, the uncertainty measure U 2 (z) can be calculated by the following formula:
[0081]
[0082] Where y represents the value of the time delay deviation, and z represents the value of the amplitude. For the picking result of the amplitude, a smaller or nearly 0 amplitude value indicates that there is no or only a small amount of turning wave passing through this position, thus indicating that the velocity inversion at this position may be incorrect. On the contrary, a larger amplitude value indicates that there is sufficient turning wave passing through, then the velocity inversion at this position may be correct. As Figures 6a to 6b shown Figure 6a shows the uncertainty measure of the time delay deviation. Among them, the horizontal direction is the spatial position, the left side of the vertical direction represents the depth in the formation, and the right side of the vertical direction represents the magnitude of the time delay deviation corresponding to the color in the figure. Figure 6b shows the uncertainty measure of the amplitude. Among them, the horizontal direction is the spatial position, the left side of the vertical direction represents the depth in the formation, and the right side of the vertical direction represents the magnitude of the amplitude uncertainty corresponding to the color in the figure.
[0083] In the preferred technical solution of this application, calculating the uncertainty interval of FWI velocity inversion according to the uncertainty measures of the time delay deviation and the amplitude includes: when the uncertainty measure U1(y) of the time delay deviation and the uncertainty measure U2(z) of the amplitude are independent or have weak correlation, obtaining the lower bound I low = U1(y) * U2(z); when the uncertainty measure U1(y) of the time delay deviation and the uncertainty measure U2(z) of the amplitude are strongly correlated, obtaining the upper bound I up = min(U1(y), U2(z)). If the calculated values of I low and I up are both 0, it is determined that the velocity update amount is not credible; if the calculated values of I low and I up are both 1, it is determined that the velocity update amount is credible; if the calculated values of I low and I up are different, it is determined that the velocity update amount is partially credible within the interval.
[0084] Specifically, calculate the uncertainty interval [I low , I up of FWI velocity inversion. Different from the existing velocity inversion uncertainty analysis methods, this paper provides the interval value of uncertainty. For example, assuming that the uncertainty measure U1(y) of time-delay deviation and the uncertainty measure U2(z) of amplitude are independent or weakly correlated, this paper gives the lower bound of the uncertainty interval: I low = U1(y) * U2(z); assuming that the uncertainty measure U1(y) of time-delay deviation and the uncertainty measure U2(z) of amplitude are strongly correlated, this paper gives the upper bound I of the uncertainty interval up = min(U1(y), U2(z)); through multiple examples, it is found that in most regions of the model, I low and I up have almost the same numerical values and are both 0 or 1 at the same time. Being both 0 indicates that in most regions of the model, the present invention can clearly and accurately judge that the velocity update amount is not credible. Being both 1 indicates that in most regions of the model, the present invention can clearly and accurately judge that the velocity update amount is credible. Only in a few regions, I low and I up have different numerical values. At this time, the interval [I low , I up evaluates the partial credibility of the velocity update amount in these regions. Figure 7a shows the lower bound of the uncertainty interval of velocity inversion. Among them, the horizontal axis is the spatial position, the left side of the vertical axis represents the depth in the formation, and the right side of the vertical axis represents the size of the uncertainty interval lower bound corresponding to the color in the figure. Figure 7b shows the upper bound of the uncertainty interval of velocity inversion. Among them, the horizontal axis is the spatial position, the left side of the vertical axis represents the depth in the formation, and the right side of the vertical axis represents the size of the uncertainty interval upper bound corresponding to the color in the figure. Figure 7c shows the uncertainty interval of velocity inversion. Among them, the horizontal axis is the spatial position, the left side of the vertical axis represents the depth in the formation, and the right side of the vertical axis represents the size of the uncertainty interval corresponding to the color in the figure.
[0085] An analysis method for the velocity inversion uncertainty of the converted-wave FWI based on DTCIG, which calculates the uncertainty by the time-delay deviation and amplitude of the converted-wave focusing energy picked up by DTCIG at each imaging point and according to their probability distributions, thus significantly improving the efficiency of analyzing the uncertainty of the velocity update amount.
[0086] Based on the probability distributions of the time-delay deviation and amplitude, this application directly calculates the uncertainties of the time-delay deviation and amplitude picked up in DTCIG, thus eliminating the need to calculate the Bayesian posterior distribution, thereby greatly reducing the computational amount of uncertainty analysis and improving the analysis efficiency.
[0087] The calculation result of this application is an interval of the uncertainty measure of FWI velocity inversion, rather than a single value. This makes the analysis result more comprehensive and reliable.
[0088] Through the above method, this application can improve the efficiency of uncertainty analysis while providing a more comprehensive and reliable measurement result of the uncertainty of FWI velocity inversion.
[0089] As Figure 8 shown, an embodiment of the present disclosure provides a DTCIG-based FWI velocity inversion uncertainty analysis device. The DTCIG-based FWI velocity inversion uncertainty analysis device includes a data acquisition module 11, a DTCIG acquisition module 12, an encryption module 13, an uncertainty measure calculation module 14, and an uncertainty interval calculation module 15. The data acquisition module 11 is configured to perform forward propagation of seismic waves through a preset velocity model to acquire seismic data; the DTCIG acquisition module 12 is configured to perform reverse time migration on the preset velocity model and seismic data with the introduction of a delay time dimension to obtain DTCIG; the encryption module 13 is configured to interpolate and encrypt the time dimension of DTCIG and pick up the time delay deviation and amplitude of the focused energy on the encrypted DTCIG; the uncertainty measure calculation module 14 is configured to calculate the uncertainty measures of the time delay deviation and amplitude respectively through the probability distributions of the time delay deviation and amplitude; the uncertainty interval calculation module 15 is configured to calculate the uncertainty interval of FWI velocity inversion according to the uncertainty measures of the time delay deviation and amplitude.
[0090] Specifically, the DTCIG-based FWI velocity inversion uncertainty analysis device of the present disclosure adopts the above-mentioned DTCIG-based FWI velocity inversion uncertainty analysis method. The data acquisition module 11 acquires seismic data by using the above method. The DTCIG acquisition module 12 obtains DTCIG through the preset velocity model and seismic data with the introduction of a delay time. The encryption module 13 interpolates and encrypts the acquired time dimension, and then picks up the time delay deviation and amplitude. The uncertainty measure calculation module 14 calculates the accuracy probabilities of the time delay deviation and amplitude. The uncertainty interval calculation module 15 calculates the uncertainty interval value. Thus, the efficiency of uncertainty analysis is improved without calculating the posterior distribution.
[0091] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure, enabling those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, process, and other changes. The embodiments only represent possible variations. Unless explicitly required, the individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terms used in this application are only for describing the embodiments and do not limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to also include the plural forms. Similarly, as used in this application, the term "and / or" refers to any and all possible combinations including one or more of the associated listed items. Additionally, when used in this application, the term "comprising" etc. means the presence of the stated features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or groups thereof. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, or apparatus comprising the element. Herein, what each embodiment focuses on may be the differences from other embodiments, and the same or similar parts among the embodiments may be referred to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, the relevant parts may refer to the description of the method part.
[0092] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner may depend on the specific application and design constraints of the technical solution. The skilled person may use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of the embodiments of the present disclosure. The skilled person can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.
[0093] In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units can be merely a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Additionally, the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms. The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to implement this embodiment. Additionally, in the embodiments of the present disclosure, the various functional units can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.
[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to the embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions marked in the blocks can occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, which can depend on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks can also occur in a different order than that disclosed in the description. Sometimes, there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, which can depend on the functions involved. Each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.
Claims
1. A method for analyzing the uncertainty of FWI velocity inversion based on DTCIG, characterized in that, Including the following steps: Performing forward propagation of seismic waves through a preset velocity model to obtain seismic data; Performing reverse time migration on the preset velocity model and seismic data with the introduction of a delay time dimension to obtain DTCIG; Interpolating and encrypting the time dimension of DTCIG and picking up the time delay deviation and amplitude of the focused energy on the encrypted DTCIG; Calculating the uncertainty measures of the time delay deviation and amplitude respectively through the probability distributions of the time delay deviation and amplitude; Calculating the uncertainty interval of FWI velocity inversion according to the uncertainty measures of the time delay deviation and amplitude.
2. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 1, wherein The performing forward propagation of seismic waves through a preset velocity model to obtain seismic data includes: Setting a seismic source and arranging a plurality of receivers around the seismic source; The seismic source emits seismic waves, simulates the forward propagation of seismic waves according to the velocity model, and the receivers receive the reflected waves and direct waves; Obtaining seismic data according to the simulation results.
3. The FWI velocity inversion uncertainty analysis method based on DTCIG according to claim 1, characterized in that The performing reverse time migration on the preset velocity model and seismic data with the introduction of a delay time dimension to obtain DTCIG includes: Stacking the image slices corresponding to each delay time to form DTCIG, where each pixel point in the formed DTCIG corresponds to a delay time and the spatial position of the corresponding receiver.
4. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 3, wherein The performing reverse time migration on the preset velocity model and seismic data with the introduction of a delay time dimension to obtain DTCIG includes: At the position of a near offset, the reflected wave covers a shallower position, and there is a large deviation in DTCIG at the shallower position.
5. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 3, wherein The performing reverse time migration on the preset velocity model and seismic data with the introduction of a delay time dimension to obtain DTCIG further includes: At the position of a medium offset, the reflected wave covers a deeper position, and there is a deviation in DTCIG at the deeper position.
6. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 3, wherein The performing reverse time migration on the preset velocity model and seismic data with the introduction of a delay time dimension to obtain DTCIG further includes: At the position of a far offset, the signal of the reflected wave is weak, and the information on DTCIG is inaccurate.
7. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 1, characterized in that The interpolating and encrypting the time dimension of DTCIG includes: Interpolating and encrypting the time dimension of DTCIG, increasing the density of time sampling, and obtaining high time resolution and time information.
8. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 7, wherein The picking up the time delay deviation and amplitude of the focused energy on the encrypted DTCIG includes: Adopting the semblance picking method to pick up the time delay deviation and amplitude of the reflected wave focused energy at each imaging point on the encrypted DTCIG.
9. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 1, wherein The calculating the uncertainty measures of the time delay deviation and amplitude respectively through the probability distributions of the time delay deviation and amplitude includes: According to the principle of semblance picking, when the time-delay deviation follows a normal distribution, the uncertainty measure of the time-delay deviation The uncertainty measure of the amplitude when the amplitude follows a Rayleigh distribution Among them, x is the independent variable of the normal distribution, y is the time delay deviation, z is the amplitude, and σ 2 is the variance.
10. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 9, wherein The calculating the uncertainty interval of FWI velocity inversion according to the uncertainty measures of the time delay deviation and amplitude includes: When the uncertainty measure U1(y) of the time delay deviation and the uncertainty measure U2(z) of the amplitude are independent or have weak correlation, obtain the lower bound I of the uncertainty interval low = U1(y) × U2(z); When the uncertainty measure U1(y) of the time delay deviation and the uncertainty measure U2(z) of the amplitude are strongly correlated, obtain the upper bound I of the uncertainty interval up = min(U1(y), U2(z)).
11. The method for analyzing the uncertainty of FWI velocity inversion based on DTCIG according to claim 10, characterized in that If I low and I up both have calculated values of 0, then it is determined that the speed update amount is not credible; If I low and I up both have calculated values of 1, then the speed update amount is determined to be credible; If I low and I up have different calculated values, it is determined that the partial speed update amount within the interval is credible.
12. An apparatus for analyzing the uncertainty of FWI velocity inversion based on DTCIG, characterized in that, Including: A data acquisition module configured to perform forward propagation of seismic waves through a preset velocity model to obtain seismic data; A DTCIG acquisition module configured to perform reverse time migration on the preset velocity model and seismic data with the introduction of a delay time dimension to obtain DTCIG; An encryption module configured to interpolate and encrypt the time dimension of DTCIG and pick up the time delay deviation and amplitude of the focused energy on the encrypted DTCIG; An uncertainty measure calculation module configured to calculate the uncertainty measures of the time delay deviation and amplitude respectively through the probability distributions of the time delay deviation and amplitude; An uncertainty interval calculation module configured to calculate the uncertainty interval of FWI velocity inversion based on the uncertainty measures of the time delay deviation and amplitude.