A method for constructing a seismic velocity model, an electronic device and a storage medium

Abstract

This invention relates to the field of seismic data processing technology, and discloses a method for constructing a seismic velocity model, an electronic device, and a storage medium. In this invention, geological stratigraphic data and time-velocity relationship pairs are loaded into a three-dimensional scene; a first interpolation smoothing operation is performed on the geological stratigraphic data to generate a geological stratigraphic sequence; a second interpolation smoothing and outlier removal operation is performed on the time-velocity relationship pairs to calculate and generate an initial seismic velocity model; based on the geological segments in the geological stratigraphic sequence data, the initial seismic velocity model is layered; a first interactive command input by the user is obtained, and a third interpolation smoothing operation is performed on the specified geological segments or inter-layers in the initial seismic velocity model according to the command to generate a final seismic velocity model. By constructing a seismic velocity model under the constraints of geological stratigraphic data and time-velocity relationship pairs, and through user interaction, the problem of insufficient detailed characterization and applicability of models in complex geological structures is solved.

Description

Technical Field

[0001] This invention relates to the field of earthquake data processing technology, and in particular to a method for constructing an earthquake velocity model, an electronic device, and a storage medium. Background Technology

[0002] Seismic imaging modeling technology is a core component of seismic exploration, spanning multiple stages including acquisition, processing, and interpretation. Its core task is to establish high-precision two-dimensional or three-dimensional seismic velocity models. These models provide crucial support for observation system design, imaging processing parameter optimization, and geological interpretation scheme verification. They also reflect the complex distribution characteristics of stratigraphic structure and properties, forming the basis for seismic imaging and numerical analysis. However, constructing seismic velocity models under complex geological conditions presents significant challenges, demanding higher levels of modeling accuracy and efficiency.

[0003] Currently, most interactive seismic modeling software develops seismic velocity models based on layered models. Layered models represent geological bodies by dividing strata into several relatively uniform velocity layers, where velocity values ​​remain consistent or exhibit simple variation patterns within each layer. This type of model has certain advantages when dealing with relatively simple geological structures, but its ability to accurately depict complex surfaces, fault blocks, and sand bodies—non-layered geological structures—is limited in terms of both detail and applicability. Therefore, a more efficient and flexible method for constructing seismic velocity models is urgently needed to reasonably address the modeling challenges of complex geological structures and achieve rapid and accurate seismic imaging. Summary of the Invention

[0004] The purpose of this invention is to provide a method for constructing a seismic velocity model, an electronic device, and a storage medium, so as to solve the problems of insufficient fine characterization capability and applicability of seismic velocity models under complex geological structures.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a method for constructing a seismic velocity model, comprising: loading geological stratigraphic data and time-velocity relationship data into a three-dimensional scene; performing a first interpolation smoothing operation on the geological stratigraphic data to generate a geological stratigraphic sequence data; performing a second interpolation smoothing operation and outlier removal operation on the time-velocity relationship data, and calculating and generating an initial seismic velocity model; performing layered processing on the initial seismic velocity model based on the geological strata in the geological stratigraphic sequence data; acquiring at least one first user-inputted interaction instruction, and performing a third interpolation smoothing operation on the corresponding geological strata in the initial seismic velocity model based on the first interaction instruction to obtain a final seismic velocity model; wherein the first interaction instruction includes the geological strata or inter-strata to be processed, and the third interpolation smoothing operation instruction.

[0006] Embodiments of the present invention also provide an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform a method for constructing a seismic velocity model as described above.

[0007] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for constructing an earthquake velocity model as described above.

[0008] In this embodiment of the invention, by fusing geological stratigraphic sequence data and time-velocity relationships as two constraints, and combining layered processing and interpolation smoothing operations, a precise velocity model is constructed, overcoming the limitations of traditional layered models in accurately depicting complex geological structures. Specifically, the geological stratigraphic sequence data, after interpolation smoothing optimization, provides continuous spatial distribution constraints of strata, ensuring the model accurately reflects complex geological structures. Local optimization of geological segments or inter-strata through user interaction commands enables model adjustments based on user prior knowledge, effectively addressing non-layered geological features such as faults and sand bodies, thus improving the applicability of the modeling.

[0009] Furthermore, in this embodiment of the invention, when the first interaction command is obtained more than once, the number of geological segments or inter-segmental areas to be processed is increased sequentially, and interpolation smoothing operations are performed step by step. This progressive modeling approach effectively avoids the error accumulation caused by global one-time processing, achieving layer-by-layer fine modeling. At the same time, by optimizing the speed model layer by layer through multiple interactions, the ability to depict complex geological structures is further improved, making the modeling process more efficient and controllable. Attached Figure Description

[0010] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0011] Figure 1 This is a schematic diagram of a seismic velocity model construction method provided in an embodiment of this application;

[0012] Figure 2 This is a comparison diagram of the effects of geological stratigraphic data processing before and after processing, provided in an embodiment of this application;

[0013] Figure 3 This is a comparison diagram of the effect of the earthquake velocity model before and after processing, provided in an embodiment of this application;

[0014] Figure 4 This is a comparison diagram of the effects of processing the seismic velocity model before and after processing, according to an embodiment of this application;

[0015] Figure 5 This is a diagram of an electronic device provided in another embodiment of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this application to help readers better understand this application. However, the technical solutions claimed in this application can be implemented even without these technical details and various changes and modifications based on the following embodiments. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.

[0017] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0018] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0019] Seismic imaging modeling technology is a core component of seismic exploration, spanning multiple stages including data acquisition, processing, and interpretation. Its core task is to establish high-precision two-dimensional or three-dimensional seismic velocity models to provide accurate input data for subsequent seismic imaging processing and geological analysis. These seismic velocity models not only provide crucial support for observation system design, imaging parameter optimization, and the verification of geological interpretation schemes, but also reflect the complex distribution characteristics of stratigraphic structure and properties, forming the foundation for seismic imaging and numerical analysis. An accurate seismic velocity model can effectively help researchers identify subsurface structures in seismic data, providing vital data support for resource exploration, geological hazard assessment, and engineering construction.

[0020] However, despite the crucial role of seismic velocity models in seismic exploration, constructing such models under complex geological conditions still faces many challenges. In particular, the presence of non-layered geological structures such as complex surfaces, fault blocks, sand bodies, and irregular geological strata makes traditional modeling methods inadequate. In traditional seismic modeling, many interactive seismic modeling software programs rely on layered models to develop seismic velocity models. Layered models divide the geological body into several relatively uniform velocity layers, with velocity values ​​in each layer remaining consistent or exhibiting simple variation patterns within their range. This modeling method is quite effective when dealing with areas with relatively simple geological structures, but for areas with complex structures and interlaced strata, the accuracy and applicability of layered models are quite limited.

[0021] The limitations of layered models are mainly reflected in the following aspects:

[0022] 1. Difficulty in accurately depicting complex geological features: For complex geological structures such as faults and sand bodies, layered models cannot effectively reflect their velocity changes and spatial distribution, resulting in the generated seismic velocity models failing to accurately reflect the actual underground conditions.

[0023] 2. Inability to handle non-layered geological structures: Most existing modeling methods are based on simple layered assumptions and cannot adapt to complex non-layered structures and highly heterogeneous geological bodies, especially in some complex seismic exploration environments.

[0024] Therefore, existing technologies urgently need innovative modeling methods to overcome these shortcomings, especially a modeling technique that can solve the problem of insufficient fine characterization and applicability of seismic velocity models under complex geological structures.

[0025] To address the aforementioned problems, this invention proposes a novel method for constructing seismic velocity models. Its innovation lies in integrating two key constraints: geological stratigraphic data and time-velocity pairs (TV pairs). By combining layered processing and interpolation smoothing operations, it overcomes the limitations of traditional layered models in complex geological structures. In this method, geological stratigraphic data provides constraints on the spatial distribution of strata, ensuring that the generated seismic velocity model accurately reflects the morphology of complex geological structures. Meanwhile, TV pairs provide constraints on velocity variations, making the seismic velocity model more accurate and consistent.

[0026] This invention's method can flexibly handle non-layered geological features, such as faults and sand bodies, improving the accuracy and efficiency of seismic velocity models. By introducing user-interactive commands, the model can be locally optimized and adjusted based on the user's prior knowledge, thus more flexibly addressing complex geological structures and generating higher-precision seismic velocity models. This method not only improves the applicability and efficiency of modeling but is also particularly suitable for the seismic imaging and data processing needs in complex geological environments.

[0027] Example 1:

[0028] Figure 1 This application provides a method for constructing an earthquake velocity model. For example... Figure 1 As shown, a method for constructing a seismic velocity model includes:

[0029] Step 101: Load geological stratigraphic data and time-velocity relationship data into the 3D scene.

[0030] The aforementioned geological stratigraphic data, generated through seismic exploration and geological interpretation, represents the spatial distribution and geometric morphology of subsurface strata. It is typically represented as a three-dimensional surface or layered structure, identifying the interfaces between strata and serving as one of the fundamental constraints for constructing velocity models. For example, geological stratigraphic data can indicate the distribution of complex structures such as subsurface faults and folds.

[0031] The aforementioned TV pairs (time-velocity pairs) record the variation of seismic wave propagation velocity over time at different underground locations. Extracted from seismic gathers (such as common midpoint gathers) through velocity analysis, they reflect the velocity characteristics at different depths or in different formations. TV pairs are crucial inputs for generating velocity fields and velocity models, providing support for formation thickness calculations and depth-domain velocity correction.

[0032] Specifically, geological stratigraphic data and TV pair data are loaded into the 3D scene. The geological stratigraphic data reflects the spatial distribution and geometry of the underground strata, while the TV pair data describes the velocity characteristics of seismic wave propagation. After loading, the 3D scene synchronously displays these two types of data and provides real-time quality control functions, allowing users to check the integrity and accuracy of the data, promptly identify potential anomalies or errors, and provide a reliable data foundation for subsequent modeling.

[0033] Step 102: Perform a first interpolation smoothing operation on the geological stratigraphic data to generate geological stratigraphic sequence data.

[0034] Specifically, for the loaded geological stratigraphic data (such as...) Figure 2 The first interpolation and smoothing operation is performed on the geological stratigraphic sequence data (e.g., in the 201 region of China), and the final generated geological stratigraphic sequence data is then obtained. Figure 2 The data from the 202 region accurately reflect the spatial distribution of underground strata, such as continuous stratigraphic boundaries or layer interfaces. These data provide crucial spatial distribution constraints for the construction of velocity models, ensuring that the models can reflect the true geological structure.

[0035] Step 103: Perform a second interpolation smoothing operation and outlier removal operation on the time-velocity relationship data, and calculate and generate an initial seismic velocity model.

[0036] Specifically, interpolation smoothing and outlier removal are performed on the TV data to generate a continuous velocity field. An initial seismic velocity model can then be calculated based on this continuous velocity field for further optimization.

[0037] Step 104: Based on the geological strata in the geological stratum sequence data, perform layered processing on the initial seismic velocity model.

[0038] Specifically, by utilizing geological stratum information from geological stratum sequence data, the initial seismic velocity model is processed in layers within each geological stratum, taking into account the spatial constraints of the geological stratum and the velocity distribution characteristics of the velocity field. This provides a basis for subsequent inter-segment interpolation smoothing.

[0039] Step 105: Obtain at least one first interaction instruction input by the user; based on the first interaction instruction, perform a third interpolation smoothing operation on the corresponding geological segment in the initial seismic velocity model to obtain the final seismic velocity model. The first interaction instruction includes the geological segment or inter-layer geological data to be processed, and the third interpolation smoothing operation instruction.

[0040] Specifically, by acquiring the user's initial interactive command, including the specified geological stratum or inter-stratum, and the corresponding interpolation smoothing algorithm and related parameters, the algorithm is applied to the specified area (e.g., Figure 3Area 301 and Figure 4 In region 402, a third interpolation smoothing operation is performed to finely optimize the local velocity model. Users can flexibly adjust interpolation parameters or redefine the processing area based on real-time feedback from the model, thereby achieving dynamic adjustment and optimization of complex geological structures. The final generated seismic velocity model, such as... Figure 3 Area 302 and Figure 4 As shown in region 403, the model not only possesses high precision but also accurately depicts complex geological features such as faults and sand bodies, significantly improving its applicability and reliability in practical applications. Furthermore, Figure 3 The 303 region in the image shows the difference in the model's cross-section before and after smoothing. The white area between the red and blue lines represents the key area for segment adjustment, visually reflecting the significant improvement in the model structure brought about by the optimization operation.

[0041] In this embodiment of the invention, by fusing geological stratigraphic sequence data and TV pair data as two constraints, and combining layered processing and interpolation smoothing operations, a precise velocity model is constructed, overcoming the limitations of traditional layered models in accurately depicting complex geological structures. Specifically, the geological stratigraphic sequence data, after interpolation smoothing optimization, provides continuous stratigraphic spatial distribution constraints, ensuring the model accurately reflects complex geological structures. Local optimization of geological segments or inter-segments through user interaction commands enables model adjustments based on user prior knowledge, effectively addressing non-layered geological features such as faults and sand bodies, thus improving the applicability of the modeling.

[0042] Example 2:

[0043] Based on the above embodiments, after step 101, that is, after loading geological stratigraphic data and time-velocity relationship data into the three-dimensional scene, the method further includes:

[0044] Obtain a second interactive instruction from the user regarding the geological stratigraphic data and the time-velocity relationship data; wherein the second interactive instruction is used to perform an outlier removal operation on the geological stratigraphic data and the time-velocity relationship data;

[0045] Based on the second interactive command, the geological stratigraphic data and time-velocity relationship data are edited.

[0046] Specifically, after loading geological stratigraphic data and TV pair data into the 3D scene, the system obtains the user's second interactive command through an interactive interface or command input function. Users can inspect the data distribution in the 3D visualization interface, mark outlier areas or specify operation ranges, and input specific removal commands through threshold settings, area selection, or point selection. The core function of this command is to identify and remove outliers in the geological stratigraphic data and TV pair data, such as extreme anomalies in velocity values, discontinuous geological stratigraphic data, or obvious human interpretation errors that deviate from geological patterns.

[0047] Then, based on the second interactive command input by the user, the system removes and edits the marked outlier areas or deviation data. For geological stratigraphic data, after removing outliers, local interpolation is performed using the geometric trends of the upper and lower stratigraphic layers to fill in missing areas, ensuring stratigraphic continuity and geological rationality. For TV pair data, after removing anomalous velocity values, a reasonable velocity distribution is regenerated using methods such as B-spline interpolation or kriging interpolation, making the local velocity field smoother and consistent with surrounding data. The entire editing process ensures that while removing unreasonable data, the overall coherence and reliability of the data are maintained.

[0048] In summary, outlier removal and data editing operations executed through user interaction commands significantly improved the quality of input data in the initial stage of modeling. This process avoided the negative impact of outlier data on subsequent interpolation and smoothing, ensuring that geological stratigraphic data and TV pairs more closely conformed to geological patterns, while providing a solid foundation for the generation of the initial seismic velocity model. The edited data was not only more accurate and consistent but also enhanced the flexibility and controllability of the modeling process, contributing to the generation of a high-precision seismic velocity model.

[0049] Example 3:

[0050] Based on the above embodiment, after step 103, that is, after generating the initial seismic velocity model, the method further includes:

[0051] The initial seismic velocity model is subjected to three-dimensional global smoothing and outlier removal operations.

[0052] Specifically, after generating the initial seismic velocity model, a three-dimensional global smoothing operation is performed, using Gaussian smoothing, mean smoothing, or other smoothing algorithms suitable for the velocity model to optimize the velocity field. By eliminating unreasonable local fluctuations or abrupt changes, the velocity values ​​become more consistent and smooth in three-dimensional space. Depending on the complexity of the geological structure, the smoothing factor can be flexibly adjusted; a larger smoothing parameter can be used in simple geological regions to improve overall homogeneity, while a smaller parameter is used in complex geological regions to preserve detailed features. Global smoothing ensures the overall stability of the velocity model, providing a more reliable data foundation for subsequent steps.

[0053] After global smoothing, outliers ("outliers") are checked in the velocity model. These outliers may originate from errors in the data itself, inaccuracies in the velocity analysis results, or limitations of the interpolation algorithm. Outlier removal involves two parts:

[0054] 1. Outlier Detection: Based on the statistical distribution of velocity values ​​and combined with geological background knowledge, a velocity range threshold is set to detect points in the velocity field that exceed the reasonable range (i.e., "outliers"). The following discrimination criteria can be used:

[0055]

[0056] Where v(x,y,z) is a specific point in the velocity model, v min and v max These are reasonable threshold ranges. All outliers that meet the above conditions are marked as points to be corrected.

[0057] 2. Outlier Correction: For detected outliers, the original values ​​are removed, and the velocity values ​​in the outlier region are recalculated using a local interpolation method. Sliding Kriging interpolation can be used as the interpolation method, and its formula is:

[0058]

[0059] Where, λ i The weights satisfy λ1 + λ2 + λ 3+…… +λ n =1, the weights are determined based on the semi-variogram, reflecting spatial autocorrelation. Z(x0) represents the interpolated value, Z(x i ) is the value of a known point.

[0060] Meanwhile, the outlier removal process can also incorporate geological stratigraphic constraints to ensure that the corrected velocity distribution remains consistent with geological structural features. The corrected velocity values ​​not only meet reasonable ranges but also align with the surrounding velocity field distribution. Outlier removal effectively avoids the negative impact of outliers on the overall accuracy of the model, further enhancing the reliability and geological plausibility of the velocity model.

[0061] Example 4:

[0062] Based on the above embodiment, after step 105, that is, after obtaining the final seismic velocity model, the method further includes:

[0063] Load seismic data into the three-dimensional scene;

[0064] Based on the final seismic velocity model and the seismic data, the migration imaging algorithm is invoked to generate imaging data volumes and imaging gathers.

[0065] Specifically, seismic data, including seismic reflection profiles, common center point gathers (CDPs), and pre-migrating stack gathers, is loaded into the 3D scene. This data records the propagation of seismic waves and provides crucial information such as the location of reflecting layers and the amplitude of reflected waves. The final construction of the seismic velocity model relies on this data loading, and a unified coordinate system ensures spatial consistency between the velocity model and seismic reflection characteristics. After loading, the data is displayed in real-time through the 3D scene, and quality control is performed to ensure the accuracy of the loaded seismic data. Users can further check and annotate the data based on seismic reflection characteristics, providing reliable input for subsequent modeling and imaging.

[0066] Then, using the final optimized seismic velocity model as input, it is combined with the quality-controlled seismic data, and a suitable migration imaging algorithm is invoked to generate high-precision imaging data volumes and imaging gathers. The migration imaging algorithm utilizes the high precision of the final seismic velocity model to accurately correct seismic wave propagation time, eliminating the influence of velocity variations on imaging, thereby improving the clarity and reliability of the imaging results.

[0067] Migration imaging algorithms include, but are not limited to, the following types:

[0068] 1. Pre-stack Depth Migration: For complex tectonic regions, this method directly images the geological structure in the depth domain based on wave equations or ray tracing methods, generating high-resolution 3D geological structure images. The algorithm corrects the seismic wave propagation time according to the depth velocity model at each point, ensuring accurate mapping of reflection events into the depth domain.

[0069] 2. Reverse Time Migration: By inverting and forward modeling seismic data using the wave equation, the reflection characteristics of complex tectonic regions such as faults and folds can be clearly depicted. The wave equation is as follows:

[0070]

[0071] Where P is the pressure fluctuation of the wave field, and v 2 (x,z) is the velocity field in the depth domain. It is the spatial derivative, which describes the propagation and inversion of the wave field. This algorithm allows seismic data to be converted into realistic subsurface reflection structures.

[0072] Based on the processing of a three-dimensional velocity model in the depth domain and seismic data, the migration imaging algorithm generates two main outputs: an imaging data volume and an imaging gather.

[0073] 1. Imaging Data Volume: The imaging data volume is a 3D reflection image generated by an offset algorithm. It consists of information such as reflection intensity and reflection time / depth, recording the reflection intensity at each volume element (a small unit in space). The reflection intensity reflects the physical characteristics of the subsurface strata and is closely related to the depth domain distribution of the velocity model. Reflection Intensity Formula:

[0074]

[0075] Where I(x,y,z) is the reflection intensity at each point in the depth domain, A(t) is the amplitude of the reflected wave, σ is the attenuation parameter, and t0 and t f It refers to the time window. This formula uses Gaussian attenuation to weight the reflected wave signal, helping to reduce the impact of noise and accurately calculate the reflection intensity.

[0076] 2. Imaging Gathers: Imaging gathers are a set of datasets processed from seismic imaging to describe the reflection characteristics of subsurface strata. They are typically extracted from reflected waves in seismic data. Unlike imaging data volumes, imaging gathers are usually presented as seismic traces, representing the waveform of reflected waves propagating from subsurface reflecting surfaces to the receiver. Each trace in an imaging gather represents the reflection amplitude of a seismic wave returning from a reflecting surface at a specific subsurface level; it is a combination of the time / depth and amplitude of the waveform received by the seismic receiver. Specifically, imaging gathers include the following elements:

[0077] a. Reflection Time / Depth: The reflection time (or depth) for each seismic trace represents the time (or depth) it takes for the seismic wave to travel from the reflecting surface. This information is typically used to locate the depth of the reflecting surface, helping geologists understand the depth structure of the strata.

[0078] b. Reflection Amplitude: The amplitude of the reflected wave is a measure of the intensity of the reflected seismic wave, and is usually related to the physical properties of the underground geological materials (such as density, velocity, elasticity, etc.). Each trace in the imaging gather reflects this, thus providing information about the properties of the underground reflecting layer.

[0079] c. Reflectance Coefficient: Imaging gathers can also represent the physical differences between formations using the reflection coefficient. The reflection coefficient is a measure of the intensity of reflection caused by differences in velocity or density between different formations, and is usually calculated using the following formula:

[0080]

[0081] Where R is the reflection coefficient, A reflected It is the amplitude of the reflected wave, A incident This is the amplitude of the incident wave. This coefficient reflects the interface characteristics between layers.

[0082] d. Reflection surface depth: In depth-domain migration imaging, the reflection surface depth refers to the depth at which the reflected wave returns from a certain underground reflection interface, reflecting the spatial location of the underground reflection interface.

[0083] By loading seismic data and combining it with the final seismic velocity model to invoke the migration imaging algorithm, the generated imaging data volume and imaging gather accurately depict the complex geological structure features, providing high-precision data support for subsequent geological interpretation and engineering design.

[0084] Example 5:

[0085] Based on the above embodiments, step 103, namely, performing a second interpolation smoothing operation and outlier removal operation on the time-velocity relationship data, and calculating and generating an initial seismic velocity model, specifically includes:

[0086] Perform a time-depth transformation on the time-velocity relationship data to obtain time-depth relationship data;

[0087] A second interpolation smoothing operation is performed on the time-depth relationship data to generate a continuous preliminary velocity field;

[0088] The preliminary velocity field is processed to remove outliers, and local interpolation is used to fill in the removed values.

[0089] The preliminary velocity field after the outlier removal process is then gridded to generate an initial seismic velocity model.

[0090] Specifically, TV converts the data from the time domain to the depth domain and calculates the depth using the following formula:

[0091]

[0092] Where Z represents the corresponding depth, and V(t′) is the velocity value at any time t′. During this process, the data is adjusted based on the nonlinear relationship between velocity and time, and the accuracy of the conversion is ensured by combining the loaded well location data or seismic velocity model. The time-depth pairs (TD pairs) generated by the time-depth conversion more closely match the actual depth distribution of the subsurface strata, providing reliable depth domain constraints for the subsequent generation of the velocity field.

[0093] Then, interpolation operations are performed on the TD data, using algorithms such as B-spline interpolation, kriging interpolation, or sliding kriging interpolation to expand the discrete velocity points into a continuous velocity field covering three-dimensional space. After interpolation, Gaussian smoothing or mean smoothing is applied to the velocity field to remove local noise or spikes, improving the overall continuity and smoothness of the velocity field. Interpolation and smoothing ensure that the generated preliminary velocity field has both high spatial resolution and reflects the actual characteristics of the geological structure.

[0094] Next, the preliminary velocity field undergoes outlier removal. A reasonable range for velocity values ​​is established through statistical analysis or geological background knowledge, and outliers exceeding this range are detected and eliminated. After outlier removal, local blank areas may appear. The system uses local interpolation algorithms (such as regional weighted interpolation or neighborhood average interpolation) to fill in these blank areas. This step not only removes outliers that negatively impact the accuracy of the velocity model but also ensures that the repaired velocity field possesses good continuity and rationality.

[0095] Finally, the preliminary velocity field, after outlier removal and completion processing, is mapped onto a 3D regular grid for gridded calculations to generate an initial seismic velocity model. During gridding, geological stratigraphic data is incorporated to spatially constrain the model, ensuring that the velocity model's distribution conforms to the spatial characteristics of geological structures and reflects the variation patterns of subsurface velocity. The resulting initial seismic velocity model is a 3D attribute data volume, providing high-quality foundational data for subsequent layered processing and optimization.

[0096] Example 6:

[0097] Based on the above embodiments, the number of times the first interaction instruction is obtained is greater than once, and the geological strata or geological strata to be processed in the first interaction instruction are increased sequentially.

[0098] The first interactive command mentioned above is input by the user to specify the geological segment or interlayer to be optimized. Each interactive command optimizes only a specific geological segment, ensuring that fine-grained local adjustments do not have unnecessary impacts on the global or other segments. The user selects the segment to be processed through a visual interactive interface, and the system performs interpolation and smoothing operations layer by layer according to the user's instructions.

[0099] Specifically, based on layered processing, users can input the first interactive command multiple times, each command corresponding to a geological segment or inter-layer structure to be processed. Users select specific geological segments layer by layer through the 3D visualization interface and specify the interpolation smoothing parameters and operation type for that segment. There is no limit to the number of times the first interactive command can be obtained; it can be increased progressively according to modeling needs. Each command optimizes only the specific geological segment, avoiding unnecessary impacts on local details from global adjustments.

[0100] Then, based on the user's input, the system processes geological segments or inter-segmental areas in an incremental order. First, starting with the shallowest layers, interpolation and smoothing operations are performed on the first geological segment to optimize the velocity distribution in the velocity model for that segment. Subsequently, similar operations are performed on the next adjacent segment, completing the processing layer by layer. The optimization of each layer is based on its specific geological characteristics, and after processing, the data of the previous layer is automatically locked to ensure that subsequent adjustments do not affect the already optimized area.

[0101] During this progressively increasing process, users can input different interpolation and smoothing parameters for different geological strata. For example, for strata with simple structures, a larger smoothing factor can be used to improve overall homogeneity; while for complex tectonic regions (such as faults, sand bodies, or folds), a higher resolution interpolation algorithm and a smaller smoothing factor can be selected to preserve geological feature details. By dynamically adjusting the parameters, the model can more accurately reflect the actual characteristics of different geological strata.

[0102] After each geological stratum undergoes interpolation and smoothing, the system generates an updated velocity model in real time and visualizes the processing results in a 3D scene. Users can review the current results and decide whether to further adjust or re-optimize the stratum based on the model's display. If necessary, users can immediately re-enter interactive commands to fine-tune the model parameters, enabling multiple rounds of iterative optimization until the user is satisfied with the accuracy and performance of the velocity model.

[0103] In this embodiment of the invention, when the first interaction command is obtained more than once, the geological strata or inter-strata to be processed are increased sequentially, and interpolation smoothing operations are performed step by step. This progressive modeling approach effectively avoids the error accumulation caused by global one-time processing, achieving layer-by-layer fine modeling. At the same time, by optimizing the speed model layer by layer through multiple interactions, the ability to depict complex geological structures is further improved, making the modeling process more efficient and controllable.

[0104] Example 7:

[0105] Based on the above embodiments, the first interpolation smoothing operation, the second interpolation smoothing operation, and the third interpolation smoothing operation are all performed based on at least one interpolation algorithm and at least one smoothing algorithm; wherein, the interpolation algorithm includes at least B-spline interpolation, Kriging interpolation, and sliding Kriging interpolation, and the smoothing algorithm includes at least Gaussian smoothing and mean smoothing.

[0106] Specifically, in the first, second, and third interpolation smoothing operations, interpolation algorithms are used to complete the data to generate continuous velocity fields or geological stratigraphic sequences. The interpolation algorithm is selected based on the processing requirements, and includes at least the following:

[0107] 1. B-spline interpolation: Suitable for smoothing geological horizons or velocity fields, it can generate data distributions with high continuity of curves or surfaces. Its mathematical expression is:

[0108]

[0109] Where S(x) is the interpolation curve, P i It is a control point, Ni,k (x) is the k-th order B-spline basis function at the i-th node.

[0110] 2. Kriging interpolation: Considering the spatial correlation of geological data, it is suitable for data interpolation in regions with complex geological structures. The generated results closely match the observed data while preserving spatial variability. The formula is as follows:

[0111]

[0112] Where, λ i The weights satisfy λ1 + λ2 + λ 3+…… +λ n =1, the weights are determined based on the semi-variogram, reflecting spatial autocorrelation. Z(x0) represents the interpolated value, Z(x i ) is the value of a known point.

[0113] 3. Sliding Kriging Interpolation: This method further optimizes Kriging interpolation by dynamically adjusting interpolation parameters within a local range to more accurately handle highly heterogeneous geological structures. The basic idea is to select known points within the neighborhood of each point to be estimated for Kriging interpolation calculations, thereby improving interpolation accuracy.

[0114] After interpolation, a smoothing algorithm is used to optimize the generated continuous data to eliminate noise and abnormal fluctuations, further improving the smoothness and consistency of the model. Furthermore, the smoothing algorithm parameters (such as Gaussian kernel size and moving window size) can be dynamically adjusted according to the complexity of the geological structure to ensure that the smoothed model has both good continuity and preserves the details of geological features. The smoothing algorithm should include at least the following:

[0115] 1. Gaussian smoothing: Reduces local noise points and anomalous fluctuations through weighted averaging. Suitable for global smoothing of velocity fields, it maintains the smoothing effect while preserving the overall characteristics of the geological structure. Its mathematical expression in the one-dimensional case is:

[0116]

[0117] Where S(x) is the smoothed function value, f(t) is the original function, and σ is the standard deviation, which determines the degree of smoothing.

[0118] 2. Mean Smoothing: This method averages the data within a specified region, making the velocity distribution more uniform in local areas of the model. It is suitable for smoothing simple regions. Its mathematical expression in the one-dimensional case is:

[0119]

[0120] Where S(x) is the smoothed function value, f(x+i) is the original function value at x+i, and k determines the size of the smoothing window.

[0121] In seismic data processing, selecting appropriate interpolation and smoothing algorithms and dynamically adjusting their parameters according to the complexity of geological structures can effectively improve the accuracy and reliability of the model.

[0122] Example 8:

[0123] Based on the above embodiments, step 102, namely, performing a first interpolation and smoothing operation on the geological stratigraphic data to generate geological stratigraphic sequence data, specifically includes:

[0124] The geological stratigraphic data is interpreted to generate interpreted stratigraphic data;

[0125] Based on the interpreted stratigraphic data, the interpolation algorithm in the first interpolation smoothing operation is invoked to perform interpolation calculations on the spatial data between geological layers, generating continuous geological stratigraphic data.

[0126] Based on the continuous geological stratigraphic data, the smoothing algorithm in the first interpolation and smoothing operation is invoked to smooth the geological strata and generate geological stratigraphic sequence data.

[0127] Specifically, first, the loaded original geological stratigraphic data (such as...) Figure 2 Stratigraphic interpretation is conducted in the Zhong 201 area, based on well location data, seismic reflection profiles, or other geological markers to clarify the boundaries and distribution characteristics of strata. Three-dimensional visualization tools are used to assist interpretation, marking geological stratigraphic data as interfaces between layers, and complex structural features such as faults and folds are interpreted manually or automatically.

[0128] Then, for the interpreted discrete stratigraphic data, algorithms such as B-spline interpolation, kriging interpolation, or sliding kriging interpolation are used to interpolate the spatial data between geological layers. During the interpolation process, the spatial distribution patterns of the stratigraphic data and the continuity and correlation of geological structures are considered, and missing areas are filled in to generate continuous geological stratigraphic data covering the entire three-dimensional space. The interpolation results not only preserve the spatial characteristics of geological structures but also eliminate the problem of incomplete stratigraphic layers caused by missing data.

[0129] Finally, the interpolated continuous geological stratigraphic data are further optimized using Gaussian smoothing or mean smoothing algorithms to obtain the following results: Figure 2 Results for region 202. Smoothing ensures the continuity and stability of geological stratigraphic data in three-dimensional space, while preserving key geological features, providing high-precision stratigraphic constraints for the construction of seismic velocity models.

[0130] Example 9:

[0131] Another embodiment of this application relates to an electronic device, such as... Figure 5 As shown, it includes: at least one 501 processor; and a 502 memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the following steps:

[0132] Load geological stratigraphic data and time-velocity pairs into a 3D scene;

[0133] The geological stratigraphic data are subjected to a first interpolation and smoothing operation to generate geological stratigraphic sequence data;

[0134] The time-velocity relationship data is subjected to a second interpolation smoothing operation and outlier removal operation, and an initial seismic velocity model is calculated and generated.

[0135] Based on the geological strata in the geological stratum sequence data, the initial seismic velocity model is processed into layers;

[0136] At least one user input first interaction command is obtained, and a third interpolation smoothing operation is performed on the geological segment corresponding to the initial seismic velocity model based on the first interaction command to obtain the final seismic velocity model;

[0137] The first interactive instruction includes the geological segment or inter-layer geological layer to be processed, and the third interpolation smoothing operation instruction.

[0138] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0139] Obtain a second interactive instruction from the user regarding the geological stratigraphic data and the time-velocity relationship data; wherein the second interactive instruction is used to perform an outlier removal operation on the geological stratigraphic data and the time-velocity relationship data;

[0140] Based on the second interactive command, the geological stratigraphic data and time-velocity relationship data are edited.

[0141] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0142] The initial seismic velocity model is subjected to three-dimensional global smoothing and outlier removal operations.

[0143] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0144] Load seismic data into the three-dimensional scene;

[0145] Based on the final seismic velocity model and the seismic data, the migration imaging algorithm is invoked to generate imaging data volumes and imaging gathers.

[0146] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0147] Perform a time-depth transformation on the time-velocity relationship data to obtain time-depth relationship data;

[0148] A second interpolation smoothing operation is performed on the time-depth relationship data to generate a continuous preliminary velocity field;

[0149] The preliminary velocity field is processed to remove outliers, and local interpolation is used to fill in the removed values.

[0150] The preliminary velocity field after the outlier removal process is then gridded to generate an initial seismic velocity model.

[0151] In one embodiment, the first interaction instruction is acquired more than once, and the geological strata to be processed or the geological strata between strata in the first interaction instruction are increased sequentially.

[0152] In one embodiment, the first interpolation smoothing operation, the second interpolation smoothing operation, and the third interpolation smoothing operation are all performed based on at least one interpolation algorithm and at least one smoothing algorithm; wherein the interpolation algorithm includes at least B-spline interpolation, Kriging interpolation, and sliding Kriging interpolation, and the smoothing algorithm includes at least Gaussian smoothing and mean smoothing.

[0153] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0154] The geological stratigraphic data is interpreted to generate interpreted stratigraphic data;

[0155] Based on the interpreted stratigraphic data, the interpolation algorithm in the first interpolation smoothing operation is invoked to perform interpolation calculations on the spatial data between geological layers, generating continuous geological stratigraphic data.

[0156] Based on the continuous geological stratigraphic data, the smoothing algorithm in the first interpolation and smoothing operation is invoked to smooth the geological strata and generate geological stratigraphic sequence data.

[0157] The memory and processor are connected via a bus, which can include any number of interconnecting buses and bridges, connecting various circuits of one or more processors and memories. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.

[0158] The processor manages the bus and general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory is used to store data used by the processor during operation.

[0159] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.

[0160] Example 10:

[0161] Another embodiment of this application relates to a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs the following steps:

[0162] Load geological stratigraphic data and time-velocity pairs into a 3D scene;

[0163] The geological stratigraphic data are subjected to a first interpolation and smoothing operation to generate geological stratigraphic sequence data;

[0164] The time-velocity relationship data is subjected to a second interpolation smoothing operation and outlier removal operation, and an initial seismic velocity model is calculated and generated.

[0165] Based on the geological strata in the geological stratum sequence data, the initial seismic velocity model is processed into layers;

[0166] At least one user input first interaction command is obtained, and a third interpolation smoothing operation is performed on the geological segment corresponding to the initial seismic velocity model based on the first interaction command to obtain the final seismic velocity model;

[0167] The first interactive instruction includes the geological segment or inter-layer geological layer to be processed, and the third interpolation smoothing operation instruction.

[0168] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0169] Obtain a second interactive instruction from the user regarding the geological stratigraphic data and the time-velocity relationship data; wherein the second interactive instruction is used to perform an outlier removal operation on the geological stratigraphic data and the time-velocity relationship data;

[0170] Based on the second interactive command, the geological stratigraphic data and time-velocity relationship data are edited.

[0171] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0172] The initial seismic velocity model is subjected to three-dimensional global smoothing and outlier removal operations.

[0173] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0174] Load seismic data into the three-dimensional scene;

[0175] Based on the final seismic velocity model and the seismic data, the migration imaging algorithm is invoked to generate imaging data volumes and imaging gathers.

[0176] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0177] Perform a time-depth transformation on the time-velocity relationship data to obtain time-depth relationship data;

[0178] A second interpolation smoothing operation is performed on the time-depth relationship data to generate a continuous preliminary velocity field;

[0179] The preliminary velocity field is processed to remove outliers, and local interpolation is used to fill in the removed values.

[0180] The preliminary velocity field after the outlier removal process is then gridded to generate an initial seismic velocity model.

[0181] In one embodiment, the first interaction instruction is acquired more than once, and the geological strata to be processed or the geological strata between strata in the first interaction instruction are increased sequentially.

[0182] In one embodiment, the first interpolation smoothing operation, the second interpolation smoothing operation, and the third interpolation smoothing operation are all performed based on at least one interpolation algorithm and at least one smoothing algorithm; wherein the interpolation algorithm includes at least B-spline interpolation, Kriging interpolation, and sliding Kriging interpolation, and the smoothing algorithm includes at least Gaussian smoothing and mean smoothing.

[0183] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0184] The geological stratigraphic data is interpreted to generate interpreted stratigraphic data;

[0185] Based on the interpreted stratigraphic data, the interpolation algorithm in the first interpolation smoothing operation is invoked to perform interpolation calculations on the spatial data between geological layers, generating continuous geological stratigraphic data.

[0186] Based on the continuous geological stratigraphic data, the smoothing algorithm in the first interpolation and smoothing operation is invoked to smooth the geological strata and generate geological stratigraphic sequence data.

[0187] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0188] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0189] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0190] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0191] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing this application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of this application.

Claims

1. A method for constructing a seismic velocity model, characterized in that, include: Load geological stratigraphic data and time-velocity pairs into a 3D scene; The geological stratigraphic data are subjected to a first interpolation and smoothing operation to generate geological stratigraphic sequence data; The time-velocity relationship data is subjected to a second interpolation smoothing operation and outlier removal operation, and an initial seismic velocity model is calculated and generated. Based on the geological strata in the geological stratum sequence data, the initial seismic velocity model is processed into layers; At least one user input first interaction command is obtained, and a third interpolation smoothing operation is performed on the geological segment corresponding to the initial seismic velocity model based on the first interaction command to obtain the final seismic velocity model; The first interactive instruction includes the geological segment or inter-layer geological layer to be processed, and the third interpolation smoothing operation instruction.

2. The method for constructing a seismic velocity model according to claim 1, characterized in that, After loading geological stratigraphic data and time-velocity pairs into the 3D scene, the process also includes: Obtain a second interactive instruction from the user regarding the geological stratigraphic data and the time-velocity relationship data; wherein the second interactive instruction is used to perform an outlier removal operation on the geological stratigraphic data and the time-velocity relationship data; Based on the second interactive command, the geological stratigraphic data and time-velocity relationship data are edited.

3. The method for constructing a seismic velocity model according to claim 1, characterized in that, After generating the initial seismic velocity model, the method further includes performing a three-dimensional global smoothing operation and outlier removal operation on the initial seismic velocity model.

4. The method for constructing a seismic velocity model according to claim 1, characterized in that, After obtaining the final seismic velocity model, the following is also included: Load seismic data into the three-dimensional scene; Based on the final seismic velocity model and the seismic data, the migration imaging algorithm is invoked to generate imaging data volumes and imaging gathers.

5. The method for constructing a seismic velocity model according to claim 1, characterized in that, The process of performing a second interpolation smoothing operation and outlier removal on the time-velocity relationship data, and calculating and generating an initial seismic velocity model, specifically includes: Perform a time-depth transformation on the time-velocity relationship data to obtain time-depth relationship data; A second interpolation smoothing operation is performed on the time-depth relationship data to generate a continuous preliminary velocity field; The preliminary velocity field is processed to remove outliers, and local interpolation is used to fill in the removed values. The preliminary velocity field after the outlier removal process is then gridded to generate an initial seismic velocity model.

6. A method for constructing a seismic velocity model according to any one of claims 1 to 5, characterized in that, The first interaction instruction is acquired more than once, and the geological strata or geological layers to be processed in the first interaction instruction increase sequentially.

7. A method for constructing a seismic velocity model according to any one of claims 1 to 5, characterized in that, The first interpolation smoothing operation, the second interpolation smoothing operation, and the third interpolation smoothing operation are all performed based on at least one interpolation algorithm and at least one smoothing algorithm; The interpolation algorithm includes at least B-spline interpolation, Kriging interpolation, and sliding Kriging interpolation, and the smoothing algorithm includes at least Gaussian smoothing and mean smoothing.

8. The method for constructing a seismic velocity model according to claim 7, characterized in that, The first interpolation and smoothing operation on the geological stratigraphic data to generate geological stratigraphic sequence data specifically includes: The geological stratigraphic data is interpreted to generate interpreted stratigraphic data; Based on the interpreted stratigraphic data, the interpolation algorithm in the first interpolation smoothing operation is invoked to perform interpolation calculations on the spatial data between geological layers, generating continuous geological stratigraphic data. Based on the continuous geological stratigraphic data, the smoothing algorithm in the first interpolation and smoothing operation is invoked to smooth the geological strata and generate geological stratigraphic sequence data.

9. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform a method for constructing a seismic velocity model as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a method for constructing an earthquake velocity model according to any one of claims 1 to 8.

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