A method, device and medium for analyzing seismic response characteristics of a vertically combined hole

Abstract

This invention relates to the field of seismic exploration technology and proposes a method, equipment, and medium for analyzing the seismic response characteristics of vertically combined caverns. The method includes: constructing a two-dimensional stratigraphic framework model based on the geological characteristics, P-wave velocity, and density characteristics of the target area; constructing a vertical double-cavity combined model based on the reservoir location; constructing a single-cavity model based on the size attributes of the vertical double-cavity combined model; meshing the vertical double-cavity combined model and the single-cavity model; performing finite element numerical simulations on the meshed vertical double-cavity combined model and the single-cavity model; migrating the simulation data to convert the offset domain pre-stack gather data into angle domain data; extracting the angle domain pre-stack gather data at the center of the cavern; performing feature analysis on the pre-stack gather data to obtain the seismic response characteristics of the caverns. This invention can further uncover hidden information in seismic data and provide new fundamental insights for the efficient development of carbonate fractured cavern reservoirs.

Description

Technical Field

[0001] This invention relates to the field of seismic exploration technology, and in particular to a method, equipment, and medium for analyzing the seismic response characteristics of vertical combined tunnels. Background Technology

[0002] As oil and gas exploration deepens, the exploration targets are gradually shifting from simple reservoirs to complex reservoirs such as ultra-deep and extra-deep reservoirs, increasing the difficulty of exploration. Therefore, there is an urgent need for new theories and technologies to guide the new round of oil and gas exploration. To achieve original breakthroughs in theories and key technologies, we must start from basic research and use forward modeling technology to explore and summarize the regular characteristics of wave field propagation, thereby providing basic support for subsequent seismic data processing and reservoir interpretation.

[0003] Existing cavern analysis techniques are mostly based on post-stack seismic attributes, resulting in relatively limited analytical methods. In practical applications, a correct understanding of fracture-cavity structures is crucial for accurately describing remaining oil and is a fundamental research area for significantly improving oil recovery. Analyzing cavern characteristics using only a single method fails to uncover hidden information from pre-stack seismic data, leading to low accuracy in analyzing cavern seismic response characteristics. Summary of the Invention

[0004] To address the aforementioned problems, embodiments of the present invention provide a method, equipment, and medium for analyzing the seismic response characteristics of vertically combined tunnels.

[0005] In a first aspect, embodiments of the present invention provide a method for analyzing the seismic response characteristics of vertically combined tunnels, including:

[0006] A two-dimensional stratigraphic framework model of the target area is constructed based on the pre-acquired geological features, P-wave velocity, and density characteristics of the target area.

[0007] A vertical double-cavity combined model is constructed based on the reservoir location of the two-dimensional stratigraphic framework model, and a single-cavity model is constructed based on the size attributes of the vertical double-cavity combined model.

[0008] The vertical double-hole combined model and the single-hole model are meshed respectively, and finite element numerical simulations are performed on the meshed vertical double-hole combined model and the single-hole model to obtain simulation data;

[0009] The simulation data is offset to obtain offset domain pre-stack gather data, and the offset domain pre-stack gather data is converted into angle domain data.

[0010] The angle domain pre-stack gather data at the center of the string of beads is extracted, and the feature analysis of the angle domain pre-stack gather data is performed to obtain the response characteristics of the cave seismic response.

[0011] According to an embodiment of the present invention, the step of constructing a two-dimensional stratigraphic framework model of the target area based on the pre-acquired geological characteristics, P-wave velocity, and density characteristics of the target area includes:

[0012] The strata of the target area are divided according to the geological characteristics of the described strata to obtain stratigraphic units;

[0013] Determine the thickness, P-wave velocity, and density characteristics between formation units based on well logging data;

[0014] A two-dimensional stratigraphic framework model is constructed using the stratigraphic length and the thickness between the stratigraphic units.

[0015] According to an embodiment of the present invention, the reservoir location of the two-dimensional stratigraphic framework model is constructed using a vertical dual-cavity combination model, comprising:

[0016] Construct a double-hole model based on the pre-acquired shape and size attributes;

[0017] The double-hole model is combined into a vertical double-hole combination model according to the preset hole spacing;

[0018] The vertical double-hole combination model is assigned to the reservoir location of the two-dimensional stratigraphic framework model by a preset number of double holes.

[0019] According to an embodiment of the present invention, the meshing of the vertical double-hole combined model and the single-hole model respectively includes:

[0020] Identify the stratigraphic and karst cave properties in the vertical double-cavity combined model and the single-cavity model;

[0021] The strata and karst caves are meshed using finite element methods based on their properties.

[0022] According to an embodiment of the present invention, the simulated data is offset to obtain offset-domain pre-stack gather data, including:

[0023] The Kirchhoff integral solution of the wave equation is used to realize the back propagation and imaging of the seismic wave field. That is, the travel time t is calculated based on the velocity field, and the amplitude at time t on each seismic trace is weighted and summed. The travel time is calculated based on the numerical solution of the Eikonal equation.

[0024] Depth domain imaging is performed on the simulated data based on the travel time and a predefined offset aperture.

[0025] Offset domain pre-stack gather data is determined through the depth domain imaging.

[0026] According to an embodiment of the present invention, converting the offset-domain pre-stack gather data into angle-domain data includes:

[0027] Spatial sampling is performed on the pre-stack gather of the offset domain;

[0028] The incident angle of each sampling point is calculated using a preset velocity model and the offset domain pre-stack trace after spatial sampling.

[0029] Angle gather data is generated based on the incident angle, and angle domain data is determined based on the angle gather data.

[0030] According to an embodiment of the present invention, the step of performing feature analysis on the pre-stack gather data to obtain the response characteristics of the karst cave seismic response includes:

[0031] The incident angle is calculated based on the offset and formation velocity in the pre-stack gather data, and the pre-stack angle gather data is determined based on the incident angle.

[0032] Extract the reflection amplitude at the top interface of the cavern from the pre-stack angle gather data;

[0033] An AVO curve is generated based on the reflection amplitude and the incident angle;

[0034] The gradient and intercept are determined using the AVO curve, and a gradient-intercept attribute intersection graph is generated using the gradient and intercept.

[0035] The seismic response characteristics of karst caves were analyzed based on the AVO curve and the gradient-intercept attribute cross-plot.

[0036] According to an embodiment of the present invention, the step of performing finite element mesh generation on the strata and karst caves based on their attribute characteristics includes:

[0037] Extracting the geological and karst features to determine their shapes;

[0038] Finite element meshes were created for the strata and karst caves based on their shape and physical properties.

[0039] Evaluate the mesh quality of the strata and karst caves after finite element mesh generation;

[0040] Adjust the grid according to the grid quality to obtain the optimal meshing grid corresponding to the strata and caverns.

[0041] In a second aspect, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the seismic response characteristic analysis method for vertical combined tunnels described above.

[0042] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the seismic response characteristic analysis method for vertical combined tunnels described above.

[0043] Compared with the prior art, the above-mentioned technical solution of the present invention has the following beneficial effects:

[0044] This invention moves from post-stack data analysis to pre-stack data analysis. By constructing a series of vertically combined, unequally spaced double-cavity models and performing high-precision finite element forward modeling, pre-stack seismic gather data is obtained. Based on this, AVO characteristic analysis is conducted to understand the variation of reflection amplitude with incident angle and cavity spacing, as well as the variation characteristics of gradient × intercept properties. This aims to uncover hidden information in the pre-stack seismic data and provide new fundamental insights for the efficient development of carbonate fractured-cavity reservoirs. Therefore, the seismic response characteristic analysis method, equipment, and medium proposed in this invention can provide research ideas for the subsequent analysis of pre-stack seismic data from actual carbonate fractured-cavity reservoirs. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 The flowchart shows the AVO response characteristic analysis method of vertical combined holes and single holes of equal thickness according to Embodiment 1 of the present invention.

[0047] Figure 2 A schematic diagram of a two-dimensional geological model according to Embodiment 1 of the present invention is shown;

[0048] Figure 3 A schematic diagram showing the pre-stack depth offset results of Embodiment 1 of the present invention is displayed;

[0049] Figure 4a This diagram shows a pre-stack offset range gather of the vertically combined double-hole center channel according to Embodiment 1 of the present invention.

[0050] Figure 4b A schematic diagram of the pre-stack offset domain gather of the center channel of a single-hole channel with equal thickness according to Embodiment 1 of the present invention is shown.

[0051] Figure 5a A schematic diagram of the pre-stack corner gather of the vertically combined double-hole center channel according to Embodiment 1 of the present invention is shown;

[0052] Figure 5b A schematic diagram of the pre-stack corner gather of the center channel of a single-hole channel with equal thickness according to Embodiment 1 of the present invention is shown;

[0053] Figure 6a This diagram illustrates the variation of the amplitude of the tunnel top interface with angle and tunnel spacing in the vertical combined double-tunnel model of Embodiment 1 of the present invention.

[0054] Figure 6b This diagram illustrates the variation of the amplitude of the tunnel roof interface with angle and tunnel length in the uniform thickness single-tunnel model of Embodiment 1 of the present invention.

[0055] Figure 7a The gradient-intercept intersection plot of the vertical combined double hole model of Embodiment 1 of the present invention is shown;

[0056] Figure 7b The gradient-intercept intersection plot of the uniform thickness single-hole model of Embodiment 1 of the present invention is shown;

[0057] Figure 8 The diagram shows the composition of the electronic device used to implement the seismic response characteristic analysis method for the vertical combined tunnel according to Embodiment 4 of the present invention. Detailed Implementation

[0058] The present disclosure will be further described below with reference to the embodiments shown in the accompanying drawings.

[0059] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0060] This invention proposes a seismic response characteristic analysis method for vertically combined tunnels based on forward modeling technology. Based on finite element forward modeling theory and combined with Kirchhoff's pre-stack depth migration method, it achieves the characteristic analysis of the variation of reflection amplitude at the tunnel roof interface with tunnel spacing and incident angle. Compared with traditional methods, this seismic response characteristic analysis method for vertically combined tunnels can further uncover hidden information in pre-stack seismic data, showing potential and application prospects in seismic data interpretation.

[0061] Example 1

[0062] like Figure 1 As shown, this invention proposes a method for analyzing the seismic response characteristics of vertically combined tunnels, comprising the following steps:

[0063] S1. Construct a two-dimensional stratigraphic framework model of the target area based on the pre-obtained geological features, P-wave velocity, and density characteristics of the target area.

[0064] In this embodiment of the invention, the geological characteristics of the strata refer to the geological properties and compositional characteristics of different underground strata or rock layers in the target area; the P-wave velocity refers to the speed at which seismic P-waves propagate in the underground medium; and the density characteristics refer to the density of the rock layer, i.e., the mass per unit volume. Density is an important factor in the propagation speed of seismic waves, and the density differences of different rock layers will affect the propagation characteristics of seismic waves.

[0065] In this embodiment of the invention, the step of constructing a two-dimensional stratigraphic framework model of the target area based on the pre-acquired geological characteristics, P-wave velocity, and density characteristics of the target area includes:

[0066] The strata of the target area are divided according to the geological characteristics of the described strata to obtain stratigraphic units;

[0067] Determine the thickness, P-wave velocity, and density characteristics between formation units based on well logging data;

[0068] A two-dimensional stratigraphic framework model is constructed using the stratigraphic length and the thickness between the stratigraphic units.

[0069] In detail, for ease of analysis, the strata in the study area were simplified. The model design included four main strata. The stratum thickness, velocity, and density were obtained from well logging interpretation data. The geological characteristics of the target area were obtained from geological exploration data, geological profiles, drilling records, etc. Based on the composition, structure, color, hardness, mineral composition, and other information of the rocks, different rock strata were identified. The strata in the target area were divided into multiple stratigraphic units according to the characteristics of the strata. Based on the geological data of the boreholes, the thickness between the strata was measured according to the borehole records. By comparing the boreholes, the average thickness of each stratigraphic unit was calculated.

[0070] Specifically, based on the thickness of the stratigraphic unit and the preset horizontal range, the lateral and longitudinal dimensions of each stratigraphic unit are determined. Using geological modeling software (such as Petrel, GOCAD, or Leapfrog), each stratigraphic unit is created in two-dimensional space. The stratigraphic units are arranged in order of thickness and age to form a preliminary two-dimensional stratigraphic model. The P-wave velocity and density values ​​corresponding to each stratigraphic unit are obtained from known stratigraphic characteristics and experimental data. The obtained P-wave velocity and density data are assigned to each stratigraphic unit of the two-dimensional model according to the aforementioned stratigraphic units, thereby obtaining a two-dimensional stratigraphic framework model of the target area. Considering the efficiency of the observation system and finite element simulation, the two-dimensional stratigraphic framework model is designed with a length of 20280m and a depth of 5000m.

[0071] Furthermore, moving from post-stack to pre-stack, this study focuses on two vertically combined cavities by constructing a simple model and combining it with forward modeling analysis. As the cavity spacing increases, the seismic AVO (Amplitude Variation with Offset) response characteristics change, which can further uncover hidden information in pre-stack seismic data. This provides new guidance for the subsequent processing and interpretation of this type of reservoir. Therefore, it is necessary to construct two vertically combined cavities based on a two-dimensional stratigraphic framework model.

[0072] S2. Construct a vertical double-cavity combined model based on the reservoir location of the two-dimensional stratigraphic framework model, and construct a single-cavity model based on the size attributes of the vertical double-cavity combined model.

[0073] In this embodiment of the invention, the vertical double-cavity combination model refers to designing and combining several vertical karst cave models within the same geological framework.

[0074] In this embodiment of the invention, constructing a vertical dual-cavity combined model based on the reservoir location of the two-dimensional stratigraphic framework model includes:

[0075] Construct a double-hole model based on the pre-acquired shape and size attributes;

[0076] The double-hole model is combined into a vertical double-hole combination model according to the preset hole spacing;

[0077] The vertical double-hole combination model is assigned to the reservoir location of the two-dimensional stratigraphic framework model by a preset number of double holes.

[0078] Specifically, the reservoir location refers to a depth of 3000m in the two-dimensional stratigraphic framework model. The vertical double-cavity combination model has two cavities with the following dimensions: cavity width of 30m, cavity thickness of 20m, and cavity spacing of 5m, 10m, 15m, 20m, 25m, 30m, 35m, 40m, 45m, 50m, 60m, 70m, 80m, 90m, 100m, 150m, and 20m. 0m, with a total of 17 double holes. That is, 17 sets of vertically combined double hole models were designed at the target layer of 3000m. The upper and lower holes are both square, with a hole width of 30m and a hole thickness of 20m. The hole spacing is 5m, 10m, 15m, 20m, 25m, 30m, 35m, 40m, 45m, 50m, 60m, 70m, 80m, 90m, 100m, 150m and 200m respectively.

[0079] Specifically, for comparative analysis, single tunnels with the same width and thickness as the double tunnels were designed, with heights of 45m, 50m, 55m, 60m, 65m, 70m, 75m, 80m, 85m, 90m, 100m, 110m, 120m, 130m, 140m, 190m, and 240m, respectively. Figure 2 The diagram shows a schematic of a two-dimensional geological model. Taking carbonate fracture-vuggy reservoirs as the research object, a two-dimensional geological model was first constructed based on the stratigraphic age information of the study area. Four main strata were designed, with strata velocities of 3900 m / s, 4950 m / s, 4650 m / s, and 5300 m / s from top to bottom, respectively. The surrounding rock velocity was 6000 m / s, and the velocity inside the cave was 4500 m / s. The observation system was designed with a channel spacing of 30 m and a shot spacing of 30 m. The simulated wavelet was a 25 Hz Ricker wavelet. In the geological model, a vertical double-cavity combination model and a single-cavity model were configured at a depth of 3000 m in the two-dimensional stratigraphic framework model.

[0080] Furthermore, a high-precision finite element numerical model needs to be developed for the constructed two-dimensional geological model. Before simulation, the two-dimensional geological model needs to be meshed. Compared with the regular mesh of finite difference, the finite element mesh is more suitable for complex models.

[0081] S3. Mesh the vertical double-hole combined model and the single-hole model respectively, and perform finite element numerical simulation on the meshed vertical double-hole combined model and the single-hole model to obtain simulation data.

[0082] In this embodiment of the invention, the model needs to be meshed before simulation. Compared with the regular mesh of finite difference, the finite element mesh is more suitable for complex models and can adjust the mesh size according to the velocity of each layer to achieve adaptive meshing. The mesh is automatically refined at faults, pinch-outs, undulations and velocity layer interfaces.

[0083] In this embodiment of the invention, the step of meshing the vertical double-hole combined model and the single-hole model respectively includes:

[0084] Identify the stratigraphic and karst cave properties in the vertical double-cavity combined model and the single-cavity model;

[0085] The strata and karst caves are meshed using finite element methods based on their properties.

[0086] In detail, before meshing, it is necessary to accurately identify the properties of the strata and karst caves in the model. By identifying the properties of the strata and karst caves, we can better understand the physical changes and constraints of each part of the model, ensuring the accuracy of subsequent meshing. Then, based on the identified properties of the strata and karst caves, the two-dimensional model is divided into several small units, which will serve as the basis of the finite element mesh.

[0087] Specifically, during mesh generation, the mesh density can be dynamically adjusted based on the velocity of the strata and caves. Especially in areas with drastic changes, such as faults, velocity layer interfaces, and undulations, the mesh can be automatically densified, thereby achieving adaptive mesh generation and improving computational accuracy.

[0088] Furthermore, a high-precision finite element numerical model needs to be carried out on the constructed two-dimensional geological model, that is, finite element numerical simulation is performed on the vertical double-cavity combination model and the single-cavity model after meshing to obtain simulation data. The simulation data refers to the original data containing seismic wave reflection information obtained by computer simulation of the process of seismic wave propagation in the underground medium after the finite element simulation is completed.

[0089] Furthermore, after the simulation is completed, the data needs to be offset to effectively map the reflection signals at different depths to their actual underground locations, correcting reflection time errors caused by velocity variations or geological heterogeneity, thereby improving imaging accuracy.

[0090] S4. The simulation data is offset to obtain offset domain pre-stack gather data, and the offset domain pre-stack gather data is converted into angle domain data.

[0091] In this embodiment of the invention, the offset domain pre-stack gather data refers to gather data organized by offset (ray length) in the pre-stack stage. At this stage, the data has not yet been superimposed; only seismic reflection data are collected and organized within different offsets (or distance domains). Offset domain data refers to seismic gather data at different offsets, reflecting the propagation information of seismic waves from the source to the receiver, including characteristics such as the propagation time and amplitude of the reflected waves.

[0092] In this embodiment of the invention, the offset processing of the simulated data to obtain offset-domain pre-stack gather data includes:

[0093] The back propagation and imaging of seismic wave fields are realized using the Kirchhoff integral solution of the wave equation, which includes two processes: first, the travel time t is calculated based on the velocity field; second, the amplitude at time t on each seismic trace is weighted and summed. The travel time is calculated based on the numerical solution of the Eikonal equation.

[0094] Depth domain imaging is performed on the simulated data based on the travel time and a predefined offset aperture.

[0095] Offset domain pre-stack gather data is determined through the depth domain imaging.

[0096] In detail, the Kirchhoff integral algorithm originates from the integral solution of the wave equation. It divides the computational domain into discrete segments (e.g., uniform grid partitioning), transforming the continuous integral into a discrete summation. Numerical methods (such as the trapezoidal rule and Simpson's rule) are used to calculate the Kirchhoff integral at each discrete point, thereby updating the wavefield information corresponding to the simulated data. The computational domain containing the Eikonal equation is processed using an appropriate discretization method (e.g., finite difference grid discretization), dividing the space into discrete grid nodes. Travel time is the time it takes for a wave to travel from the source to each receiver point in the simulated data (e.g., seismic wave propagation data). It is crucial for subsequent accurate imaging. Based on the travel time, images of reflections at different depths are constructed. During migration, the migration aperture is provided. This parameter is one of the main parameters in pre-stack depth migration, and its magnitude directly affects migration noise and imaging quality. If the migration aperture is too small, steep layers will not be correctly imaged, while if the migration aperture is too large, the signal-to-noise ratio will be reduced. Therefore, the optimal offset aperture must be selected through careful experimentation.

[0097] Specifically, Kirchhoff pre-stack depth migration (KPSDM) is used to obtain pre-stack gather data in the migration range domain. Based on Kirchhoff's integral theorem, KPSDM uses pre-stack gather data for migration. Its main objective is to utilize the propagation information of seismic reflections to transform the original gather data from the time domain (or distance domain) to the depth domain. Using gather data determined through simulation, velocity models and geometric optics principles, combined with the location information of reflection points, are used to calculate the actual propagation path from the source to the reflection point. After determining the reflection point and its corresponding propagation path, the propagation time of each reflection wave can be calculated using Kirchhoff's integral formula. In other words, Kirchhoff's integral formula is used to describe the propagation time from point source to point reflection. The collected wavefield propagation data, for each reflection point, calculates the total time for the reflected wave to propagate from the source point to the reflection point by constructing a path. Based on velocity models for different media, the distance and velocity along the propagation path are combined to obtain the arrival time. Then, using the velocity model, the calculated arrival time is converted into depth information. By performing smooth interpolation between reflection points, continuous reflection layers are generated, and the actual spatial location and morphology of the reflection layers are plotted. The gather data is then migrated according to the actual spatial location of the reflection layers, mapping the propagation path of the seismic wave in the subsurface medium back to the actual depth location in the subsurface, thus obtaining pre-stack depth migration data and offset-domain pre-stack gathers, such as... Figure 3 The diagram shows the pre-stack depth migration results, which are the pre-stack depth migration results of the single-hole model in the vertical double-hole combined model when the hole interval is 5m.

[0098] Furthermore, converting the offset-domain pre-stack gather data after migration processing into angle-domain data can more directly reflect the angle information of geological imaging, significantly improving imaging quality and resolution, and making the study of underground structures more comprehensive and accurate.

[0099] In this embodiment of the invention, the angle domain data is a method of describing underground structures through the reflection angle in seismic data. It is widely used in reflection layer analysis and oil and gas exploration. The angle domain is a coordinate system that represents the characteristics of underground structures through the incident angle and reflection angle of seismic wave reflection. Usually, the reflection angle is determined by the incident angle and the velocity model of the medium. By processing seismic data within different incident angle ranges, more reflection information can be obtained. Especially in complex geological environments, angle domain data can provide more refined information reflecting underground reflection layers.

[0100] In this embodiment of the invention, converting the offset-domain pre-stack gather data into angle-domain data includes:

[0101] Spatial sampling is performed on the pre-stack gather of the offset domain;

[0102] The incident angle of each sampling point is calculated using a preset velocity model and the offset domain pre-stack trace after spatial sampling.

[0103] Angle gather data is generated based on the incident angle, and angle domain data is determined based on the angle gather data.

[0104] In detail, for each reflection point in the offset domain, the corresponding reflection angle needs to be calculated based on its velocity information and incident angle. Before calculating the incident and reflection angles of the reflection points, an accurate velocity model needs to be set. The velocity model provides wave velocity information at different depths or layers. After obtaining the incident and reflection angles of the reflection points, each reflection point in the offset domain is mapped according to its calculated reflection angle. That is, for each reflection point, its corresponding incident angle is found, and the reflection angle of the reflection point is calculated using the velocity model and reflection law. These reflection information are interpolated or resampled in a new angle domain to construct a complete angle gather. After angle mapping, the reconstructed angle domain data represents the reflection characteristics under different incident angles. Analysis is performed within different reflection angle ranges (such as small angles and large angles) to obtain the angle domain data corresponding to the pre-stack gather data in the offset domain, so as to obtain clearer and more complete subsurface imaging.

[0105] S5. Extract the angle domain pre-stack gather data at the center position of the bead string, perform feature analysis on the angle domain pre-stack gather data, and obtain the response characteristics of the cave seismic response.

[0106] In this embodiment of the invention, the center position of the string of beads refers to the pre-stack seismic gather corresponding to the seismic data with the strongest energy in the string of beads.

[0107] Specifically, such as Figure 4a The diagram shows a pre-stack offset region gather for the central trace of a vertically combined double-cavity structure. The "beads" represent the seismic response of the vertical double-cavity structure. The imaging results for other models with different spacings are the same as above, with pre-stack gathers extracted from the central traces of the "beads" respectively. Figure 4b The diagram shows a pre-stack offset domain gather for the center trace of a single-cavity tunnel of uniform thickness. The "beads" represent the seismic response of the single-cavity tunnel of uniform thickness. The imaging results for models of different thicknesses are similar. Pre-stack gathers are extracted from the center traces of the "beads," and after converting the pre-stack offset domain gathers to the angle domain, pre-stack angle gathers can be obtained. Then, as shown... Figure 5a The diagram shown is a schematic of the pre-stack angle gather of a vertically combined double-tunnel central tunnel; as shown... Figure 5b The diagram shown is a schematic of the pre-stack corner set of the center tunnel of a single-tunnel of equal thickness.

[0108] Furthermore, pre-stack gather data at the center of the beaded structure were selected, and AVO analysis was performed on the data to analyze the variation of reflection amplitude with angle at the top interface of the cave and the gradient-intercept cross-plot.

[0109] In this embodiment of the invention, the response characteristics refer to the AVO curve characteristics, namely the variation law of the reflection amplitude at the top interface of the cave with the angle and the gradient-intercept attribute intersection diagram.

[0110] In this embodiment of the invention, the step of performing feature analysis on the pre-stack gather data in the angle domain to obtain the response characteristics of the karst cave seismic response includes:

[0111] The incident angle is calculated based on the offset and formation velocity in the pre-stack gather data, and the pre-stack angle gather data is determined based on the incident angle.

[0112] Extract the reflection amplitude at the top interface of the cavern from the pre-stack angle gather data;

[0113] An AVO curve is generated based on the reflection amplitude and the incident angle;

[0114] The gradient and intercept of the reflection amplitude are determined using the AVO curve, and a gradient-intercept attribute intersection plot is generated using the gradient and intercept.

[0115] The response characteristics of the karst cave seismic response were analyzed based on the AVO curve and the gradient-intercept attribute cross-plot.

[0116] In detail, by selecting pre-stack gather data at the center of the beaded structure, the pre-stack gather data contains different offsets and corresponding seismic amplitudes. AVO analysis reveals the physical characteristics of different subsurface layers by studying the variation of reflected wave amplitude with the incident angle (or offset). For the cave roof interface, the focus is on the angle dependence of the reflected wave. That is, the reflected amplitude at the cave roof interface is extracted from the pre-stack gather data, and the incident angle is calculated based on the offset and formation velocity (usually using average velocity or effective velocity). For the reflected amplitude at the cave roof interface, a graph showing the relationship between amplitude and incident angle (or offset) is plotted. Figure 6a The diagram shows the variation of the amplitude of the tunnel roof interface in a vertically combined double-tunnel model with the angle and the distance between the tunnels. The variation is more complex when combining two tunnels; the amplitude of the AVO curve of the two tunnels decreases as the offset distance increases, as shown below. Figure 6b As shown, this is a schematic diagram of the variation of the amplitude of the tunnel top interface with the angle and tunnel length in a single-tunnel model with uniform thickness. In the case of a single tunnel, the AVO variation is relatively consistent. The AVO curves of single tunnel and double tunnel have the same trend, and the amplitude decreases with the increase of the offset distance.

[0117] Specifically, the gradient-intercept intersection plot is an effective tool in AVO analysis for extracting subsurface geological features. By calculating the reflection amplitude gradient and intercept at different offset distances, the physical parameters of the subsurface medium can be obtained. The intercept is the reflection amplitude value at zero offset, and the gradient describes the rate of change of the reflection amplitude with offset distance, which can be obtained by fitting a linear relationship between the reflection amplitude and offset distance. Then, the reflection amplitude data at all offset distances are converted into intercepts and gradients to obtain the gradient-intercept intersection plot. Based on different gradient and intercept values, different geological bodies can be distinguished (e.g., the top interface of a cave may have different gradients and intercepts than the surrounding rock layers). Figure 7a As shown, this is the gradient-intercept intersection plot of the vertically combined double-hole model. In the double-hole combination, it can be seen from the AVO curve intercept and gradient relationship plot that both holes exhibit certain linear characteristics, but there are two inflection points on the double-hole plot; as shown... Figure 7b As shown, the gradient-intercept intersection plot of the uniform thickness single hole model is shown. From the AVO curve intercept and gradient relationship plot, it can be seen that both single hole and double hole exhibit certain linear characteristics, and there is an inflection point on the single hole plot.

[0118] Furthermore, moving from post-stack to pre-stack, by constructing a simple model and combining it with forward modeling analysis, we can focus on studying the vertically combined two caverns. As the distance between the caverns increases, we can observe the changes in the seismic AVO response characteristics, thereby further uncovering the hidden information in the pre-stack seismic data. This will provide new fundamental insights for the efficient development of subsequent carbonate fractured cavern reservoirs.

[0119] Example 2

[0120] To better understand the present invention, a second embodiment is provided below to further explain the situation of dynamic mesh adjustment in the finite element mesh.

[0121] In this embodiment of the invention, the finite element mesh generation refers to automatically adjusting the distribution and density of the mesh according to the physical characteristics or geological features of different regions in order to improve computational accuracy and efficiency. By densifying or widening the mesh in specific regions, computational resources are concentrated in key areas, while coarser meshes are used in areas with less variation, thereby optimizing the entire analysis process.

[0122] In this embodiment of the invention, the step of performing finite element mesh generation on the strata and karst caves based on their attribute characteristics includes:

[0123] Extracting the geological and karst features to determine their shapes;

[0124] Finite element meshes were created for the strata and karst caves based on their shape and physical properties.

[0125] Evaluate the mesh quality of the strata and karst caves after finite element mesh generation;

[0126] Adjust the grid according to the grid quality to obtain the optimal meshing grid corresponding to the strata and caverns.

[0127] In detail, to better describe the shape of the hole, it is suitable to use unstructured meshing, such as triangular meshes or tetrahedral meshes (in the case of 3D). This allows for flexible approximation of complex boundaries and reduces errors caused by the mismatch between the mesh shape and the boundary.

[0128] Specifically, due to the size limitations of the karst cave and to avoid numerical dispersion, it is necessary to perform grid densification processing on the interior of the karst cave and the low-velocity area.

[0129] This invention moves from post-stack data analysis to pre-stack data analysis. By constructing a series of vertically combined, unequally spaced double-cavity models and performing high-precision finite element forward modeling, pre-stack seismic gather data is obtained. Based on this, AVO characteristic analysis is conducted to understand the variation of reflection amplitude with incident angle and cavity spacing, as well as the variation characteristics of gradient × intercept properties. This aims to uncover hidden information in the pre-stack seismic data and provide new fundamental insights for the efficient development of carbonate fractured-cavity reservoirs. Therefore, the seismic response characteristic analysis method, equipment, and medium proposed in this invention can provide research ideas for the subsequent analysis of pre-stack seismic data from actual carbonate fractured-cavity reservoirs.

[0130] Implementation Three

[0131] Based on the above embodiments, this embodiment provides an application example.

[0132] This invention focuses on carbonate fracture-vuggy reservoirs. First, based on the stratigraphic age information of the study area, a two-dimensional geological model is constructed. Four main strata are designed, with strata velocities from top to bottom of 3900 m / s, 4950 m / s, 4650 m / s, and 5300 m / s, respectively. The surrounding rock velocity is 6000 m / s, and the velocity inside the cave is 4500 m / s. The observation system is designed with a channel spacing of 30 m and a shot spacing of 30 m. The simulated wavelet is a 25 Hz Recker wavelet. Figure 3 The results show pre-stack depth migration at a hole spacing of 5m. The left bead represents the seismic response of a vertical double hole, while the right bead represents the seismic response of a single hole of equal thickness. The imaging results for other models with different spacings are the same. Pre-stack gathers at the center trace of each bead are extracted. Figure 4a and Figure 4b As shown, it is transformed into an angle gather to obtain Figure 5a and Figure 5b Finally, draw the AVO curve of the reflected amplitude at the tunnel roof interface as a function of angle, and the intersection of gradient (G) × intercept (P), as shown below. Figure 6a , Figure 6b , Figure 7a , Figure 7b As shown in the figure, the AVO changes are relatively consistent in the case of a single hole, while it is more complex in the case of a combination of two holes. The AVO curves of single holes and double holes show the same trend, and the amplitude decreases as the offset distance increases. From the intercept and gradient relationship graph of the AVO curve, it can be seen that both single holes and double holes exhibit certain linear characteristics. However, there are two inflection points on the graph of double holes, which is different from the characteristics of single holes. The reason for this phenomenon can be further analyzed in depth later.

[0133] Example 4

[0134] like Figure 8 As shown, this embodiment also provides a computer electronic device, which may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as a seismic response characteristic analysis program for vertical combined tunnels.

[0135] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., executing a seismic response characteristic analysis program for vertical combined tunnels) and calls data stored in the memory 11 to perform various functions of the electronic device and process data.

[0136] The memory 11 includes at least one type of readable storage medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device, such as a plug-in portable hard drive, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc. Furthermore, the memory 11 can include both internal and external storage units of the electronic device. The memory 11 can be used not only to store application software and various types of data installed on the electronic device, such as the code for a seismic response characteristic analysis program for vertical combined tunnels, but also to temporarily store data that has been output or will be output.

[0137] The communication bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0138] The communication interface 13 is used for communication between the aforementioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, Bluetooth interface, etc.), typically used to establish communication connections between the electronic device and other electronic devices. The user interface may be a display, an input unit (such as a keyboard), or, optionally, a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device and to display a visual user interface.

[0139] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0140] For example, although not shown, the electronic device may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0141] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0142] The seismic response characteristic analysis program for vertically combined holes stored in the memory 11 of the electronic device is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0143] A two-dimensional stratigraphic framework model of the target area is constructed based on the pre-acquired geological features, P-wave velocity, and density characteristics of the target area.

[0144] A vertical double-cavity combined model is constructed based on the reservoir location of the two-dimensional stratigraphic framework model, and a single-cavity model is constructed based on the size attributes of the vertical double-cavity combined model.

[0145] The vertical double-hole combined model and the single-hole model are meshed respectively, and finite element numerical simulations are performed on the meshed vertical double-hole combined model and the single-hole model to obtain simulation data;

[0146] The simulation data is offset to obtain offset domain pre-stack gather data, and the offset domain pre-stack gather data is converted into angle domain data.

[0147] By extracting the angle domain pre-stack gather data at the center of the bead string, and performing feature analysis on the angle domain pre-stack gather data, the response characteristics of the cave seismic response are obtained.

[0148] Specifically, the specific implementation method of the processor 10 for the above instructions can be referred to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, and will not be repeated here.

[0149] Furthermore, if the modules / units integrated into the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0150] Example 5

[0151] This embodiment provides a storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the seismic response characteristic analysis method for vertical combined tunnels as described above.

[0152] This program code can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 Steps of a specified function in one or more processes.

[0153] Storage media include permanent and non-permanent, removable and non-removable media, and can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by computing devices.

[0154] In the several embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0155] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0156] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0157] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0158] Therefore, the embodiments should be regarded as exemplary and non-limiting in all respects. The scope of the invention is not limited to the foregoing description, and all variations within the meaning and scope of equivalents falling within the protection scope are intended to be included in the invention.

[0159] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0160] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. The terms "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for analyzing the seismic response characteristics of vertically combined tunnels, characterized in that, The method includes: A two-dimensional stratigraphic framework model of the target area is constructed based on the pre-acquired geological features, P-wave velocity, and density characteristics of the target area. A vertical double-cavity combined model is constructed based on the reservoir location of the two-dimensional stratigraphic framework model, and a single-cavity model is constructed based on the size attributes of the vertical double-cavity combined model. The vertical double-hole combined model and the single-hole model are meshed respectively, and finite element numerical simulations are performed on the meshed vertical double-hole combined model and the single-hole model to obtain simulation data; The simulation data is offset to obtain offset domain pre-stack gather data, and the offset domain pre-stack gather data is converted into angle domain data. The angle domain pre-stack gather data at the center of the string of beads is extracted, and the feature analysis of the angle domain pre-stack gather data is performed to obtain the response characteristics of the cave seismic response.

2. The seismic response characteristic analysis method for vertical combined tunnels as described in claim 1, characterized in that, The construction of a two-dimensional stratigraphic framework model of the target area based on the pre-acquired geological characteristics, P-wave velocity, and density characteristics of the target area includes: The strata of the target area are divided according to the geological characteristics of the described strata to obtain stratigraphic units; Determine the thickness, P-wave velocity, and density characteristics between formation units based on well logging data; A two-dimensional stratigraphic framework model is constructed by using the stratigraphic length and the thickness between the stratigraphic units.

3. The seismic response characteristic analysis method for vertical combined tunnels as described in claim 1, characterized in that, A vertical dual-vuggy combination model is constructed based on the reservoir location of the two-dimensional stratigraphic framework model, including: Construct a double-hole model based on the pre-acquired shape and size attributes; The double-hole model is combined into a vertical double-hole combination model according to the preset hole spacing; The vertical double-hole combination model is assigned to the reservoir location of the two-dimensional stratigraphic framework model by a preset number of double holes.

4. The seismic response characteristic analysis method for vertical combined tunnels as described in claim 3, characterized in that, The process of meshing the vertical double-hole combined model and the single-hole model respectively includes: Identify the stratigraphic and karst cave properties in the vertical double-cavity combined model and the single-cavity model; The strata and karst caves are meshed using finite element methods based on their properties.

5. The seismic response characteristic analysis method for vertical combined tunnels as described in claim 1, characterized in that, The simulated data is offset to obtain offset-domain pre-stack gather data, including: The Kirchhoff integral solution of the wave equation is used to realize the back propagation and imaging of the seismic wave field. That is, the travel time t is calculated based on the velocity field, and the amplitude at time t on each seismic trace is weighted and summed. The travel time is calculated based on the numerical solution of the Eikonal equation. Depth domain imaging is performed on the simulated data based on the travel time and a predefined offset aperture. Offset domain pre-stack gather data is determined through the depth domain imaging.

6. The seismic response characteristic analysis method for vertical combined tunnels as described in claim 1, characterized in that, Converting the offset-domain pre-stack gather data into angle-domain data includes: Spatial sampling is performed on the pre-stack gather of the offset domain; The incident angle of each sampling point is calculated using a preset velocity model and the offset domain pre-stack trace after spatial sampling. Angle gather data is generated based on the incident angle, and angle domain data is determined based on the angle gather data.

7. The seismic response characteristic analysis method for vertical combined tunnels as described in claim 1, characterized in that, The feature analysis of the pre-stack gather data to obtain the seismic response characteristics of the karst cave includes: The incident angle is calculated based on the offset and formation velocity in the pre-stack gather data, and the pre-stack angle gather data is determined based on the incident angle. Extract the reflection amplitude at the top interface of the cavern from the pre-stack angle gather data; An AVO curve is generated based on the reflection amplitude and the incident angle; The gradient and intercept are determined using the AVO curve, and a gradient-intercept attribute intersection graph is generated using the gradient and intercept. The seismic response characteristics of the karst caves were analyzed based on the AVO curves and the gradient-intercept attribute cross-plots.

8. The seismic response characteristic analysis method for vertical combined tunnels as described in claim 4, characterized in that, The step of performing finite element mesh generation on the strata and karst caves based on their attribute characteristics includes: Extracting the geological and karst features to determine their shapes; Finite element meshes were created for the strata and karst caves based on their shape and physical properties. Evaluate the mesh quality of the strata and karst caves after finite element mesh generation; Adjust the grid according to the grid quality to obtain the optimal meshing grid corresponding to the strata and caverns.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the seismic response characteristic analysis method for vertical combined tunnels according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the seismic response characteristic analysis method for vertical combined tunnels as described in any one of claims 1 to 8.

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