An automatic drawing method of elevation corridor profile of a physical simulation model

Abstract

The application discloses a kind of automatically drawing methods of elevation corridor profile of structural physical simulation model, it is related to the technical field of structural geology, comprising: the coordinates of each stage digital elevation model are unified to the coordinate system of structural physical simulation experiment;Determine the structural deformation axis based on digital elevation model, and the corresponding sampling reference path is established parallel to structural deformation axis, and the equidistant distribution sampling point is generated on reference path;Perpendicular strip is established along the normal of sampling reference path at sampling point, and sampling point is generated on perpendicular strip at fixed interval;The elevation value of all sampling points on vertical sampling strip is obtained, the maximum, minimum and average elevation value in each strip is extracted, the three types of elevation values are sequentially connected in order of sampling serial number of sampling reference path, three continuous elevation characteristic curves are formed, and elevation corridor profile is obtained.The application can batch process DEM and automatically generate elevation corridor profile without relying on GIS software.

Description

Technical Field

[0001] This invention relates to the field of structural geology, and in particular to a method for automatically drawing elevation corridor profiles of a structural physical simulation model. Background Technology

[0002] In structural geology research, reconstructing the spatiotemporal evolution of geological bodies is one of the most challenging scientific problems. Due to the extremely large spatiotemporal scales of natural geological processes, many key tectonic deformation records are destroyed, covered, or altered over long periods of evolution. Therefore, tectonic physical simulation experiments have become an important technical means to study fold-thrust zones, basin inversions, rift extensions, and orogenic processes. This method, through the principles of geometric, kinematic, and dynamic similarity, reproduces complex crustal deformation processes on an experimental scale, thereby revealing the evolutionary laws of different tectonic systems.

[0003] In simulation experiments, three-dimensional photogrammetry or laser scanning techniques are typically used to establish digital elevation models (DEMs) for each stage to characterize the surface morphology of the model. DEMs can visually reflect the topographic undulations caused by uplift, subsidence, and fault deformation, serving as a crucial data foundation for quantitatively characterizing tectonic processes. However, traditional analysis methods primarily rely on top views, DEM plan views, or single cross-sections, making it difficult to comprehensively reveal the spatial distribution and tectonic response of two-dimensional topographic changes. Especially in multi-stage comparisons or multi-model analyses, a single cross-section is often insufficient to reflect the overall structure of fold axes, fault traces, and uplift-depression zones.

[0004] The swath profile, as a statistical representation of topography, can average, maximize, and minimize elevations within a certain strip width, thereby reflecting the patterns of landform undulation and areas of concentrated tectonic activity. This method can not only be used to identify the locations of major tectonic units on the surface of experimental models, but also helps to analyze the asymmetric control of tectonic activity over topographic development.

[0005] In the field of petroleum geology, fold-thrust zones and inversion basins are important structural units for hydrocarbon accumulation. Differences in elevation on model surfaces often correspond to potential structural highs or traps, and their morphological characteristics and fault geometry are significant indicators of hydrocarbon accumulation. By jointly analyzing DEMs and corridor profiles, analogical studies of trap evolution and structural control can be conducted at the experimental scale, providing quantitative support for structural interpretation in petroleum exploration.

[0006] However, existing methods for analyzing elevation corridor profiles in digital elevation models (DEMs) are primarily designed for natural terrain or GIS environments and are not directly applicable to the specific technical scenario of structural physics simulation experiments. DEMs obtained from structural physics simulations are typically in an experimental scale coordinate system, and their spatial reference, scale relationships, and structural axes must strictly satisfy geometric similarity laws and experimental loading conditions. Existing GIS tools struggle to automatically align and batch process multi-stage DEMs in a unified structural coordinate system without human intervention. Furthermore, existing methods rely heavily on manual experience to set the sampling path, sampling interval, and strip width for corridor profiles, lacking automatic constraint mechanisms adapted to DEM resolution, terrain spatial frequency, and structural geometric features. This can easily lead to sampling aliasing or structural signal distortion in areas with high curvature or steep slopes. In addition, the surface of structural physics simulation models often exhibits local noise caused by particle accumulation, boundary effects, or photogrammetric errors. A single profile method cannot stably reflect the overall morphological characteristics of structural deformation, hindering quantitative comparison and reproduction of results from multiple models or stages. Therefore, existing technologies lack a systematic method for constructing physical simulation experiments that can automatically complete sampling path planning, sampling density control, and elevation corridor profile statistical analysis in non-GIS environments. Summary of the Invention

[0007] The purpose of this invention is to address the lack of automated analysis of digital elevation model data at various stages, independent of the GIS environment. A method for automatically drawing elevation corridor profiles from a physical simulation model is proposed, comprising the following steps:

[0008] S1. Obtain digital elevation models of each stage of geological body evolution, and transfer the coordinate system of the digital elevation models of each stage to the coordinate system of the structural physics simulation experiment.

[0009] S2. Under a unified coordinate system, the structural deformation axis is determined based on the digital elevation model, and a corresponding sampling reference path is established parallel to the structural deformation axis. Equidistant sampling points are generated on the sampling reference path.

[0010] S3. Establish a vertical strip along the normal of the sampling reference path at the sampling point, and set the width of the vertical strip according to the spatial range of the digital elevation model. Generate sampling points on the vertical strip at fixed intervals to obtain the vertical sampling strip.

[0011] S4. Obtain the elevation values ​​of all sampling points on the vertical sampling strip, extract the maximum, minimum and average elevation values ​​of each strip, and concatenate these three types of elevation values ​​in sequence according to the sampling sequence number of the sampling reference path to form three continuous elevation feature curves, thus obtaining the elevation corridor profile.

[0012] Furthermore, the mapping relationship between the coordinate system of the digital elevation model at each stage and the coordinate system of the physical simulation experiment is as follows:

[0013] ,

[0014] in, Let S represent the coordinates under the physical simulation experiment, and let S represent the geometric similarity ratio between the digital elevation model of the natural instance and the simulated digital elevation model. The matrix is ​​used to make the X-axis of the experimental coordinate system parallel to the direction of the principal strain or central bulge. This is a translation vector used to correct the origin offset of the digital elevation model at different stages. Represents the coordinates in a digital elevation model.

[0015] Furthermore, the start and end points of the sampling reference path parallel to the construction axis are:

[0016] ,

[0017] ,

[0018] in, and These represent the starting and ending coordinates of the sampling reference path, respectively. and These are the x-coordinates of the left and right boundaries of the digital elevation model, respectively. The preset vertical position is set to offset, which is the safety distance.

[0019] Furthermore, the sampling interval on the sampling reference path is calculated according to the following formula:

[0020] ,

[0021] The number of sampling points is calculated using the following formula:

[0022] ,

[0023] The coordinates of the equally spaced sampling points are as follows:

[0024] ,

[0025] in, For sampling interval, Indicates the sampling safety factor. This represents the highest spatial frequency of the terrain along the sampling reference path. This indicates the permissible elevation error threshold. This indicates the maximum curvature of the elevation curve. This indicates the permissible slope error threshold. Indicates the maximum rate of change of slope. Indicates the pixel spacing of the digital elevation model. Indicates the number of sampling points. Indicates the effective path length. Indicates rounding up. This indicates the threshold for the number of sampling points. This represents the coordinates of the i-th sampling point. The x-coordinate represents the starting point of the sampling reference path. To preset the vertical position, This represents the path direction angle.

[0026] Furthermore, the coordinates of the two endpoints of the vertical strip within its width are defined as follows:

[0027] ,

[0028] ,

[0029] ,

[0030] in, and Let represent the coordinates of the top and bottom endpoints of the i-th vertical strip, respectively. This represents the coordinates of the i-th sampling point on the sampling reference path where the vertical strip is located. This is the preset strip ratio coefficient. Indicates the sampling reference path in Normal at point Indicates the width of the vertical strip. and bound.bottom are respectively The highest and lowest values ​​in the y-direction of the digital elevation model space at the point.

[0031] Furthermore, the average elevation value on the vertical sampling strip is calculated using the following formula:

[0032] ,

[0033] in, Indicates the location of the sampling reference path parameters The average elevation value obtained at the location and along the vertical sampling strip. This represents the arc length parameter or discrete sampling position index on the sampling reference path. Indicates the width of the vertical strip. This represents the coordinates of any point on the strip. This indicates that the sampling reference path is in The center coordinate vector at that location, where u represents the offset along the normal direction of the strip. Indicates the sampling reference path in The normal at the point.

[0034] The present invention also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for automatically drawing elevation corridor profiles of a physical simulation model.

[0035] The present invention also proposes an electronic device, including a processor and a memory, wherein the processor and the memory are interconnected, wherein the memory is used to store a computer program, the computer program including computer-readable instructions, and the processor is configured to invoke the computer-readable instructions to execute the above-described method for automatically drawing elevation corridor profiles of a physical simulation model.

[0036] The present invention also proposes a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-described method for automatically drawing elevation corridor profiles of a physical simulation model.

[0037] The beneficial effects of the technical solution provided by this invention are:

[0038] This invention unifies the coordinates of the digital elevation model (DEM) at each stage to the coordinate system of the structural physics simulation experiment. Under this unified coordinate system, the structural deformation axis is determined based on the DEM, and a sampling reference path is established along this axis. Equidistant sampling points are generated along this path. Vertical strips are established along the normal direction of the sampling points on the sampling reference path, and sampling points are generated at fixed intervals along these vertical strips to obtain vertical sampling strips. The elevation values ​​of all sampling points on the vertical sampling strips are obtained, and the maximum, minimum, and average elevation values ​​of each strip are extracted. These three types of elevation values ​​are then concatenated sequentially according to the sampling sequence number of the sampling reference path to form three continuous elevation characteristic curves, resulting in an elevation corridor profile. This invention can:

[0039] (1) A method for automatically generating elevation corridor profile maps of DEMs without the need for GIS plugins, with transparent parameters and batch processing capability is provided, realizing a fully automated processing flow from reading DEM data to drawing elevation profiles;

[0040] (2) Supports automatic / manual path setting, adjustable strip width, controllable sampling interval, outlier removal and multi-model curve alignment to meet the adaptation requirements of different experimental schemes and resolutions, and ensure the flexibility and accuracy of data processing;

[0041] (3) It can efficiently generate accurate topographic corridor profiles, enabling topographic quantification and phased comparison of experimental models. The standardized results can not only assist in structural interpretation and fault identification, but also provide a visual and reproducible topographic analysis tool for the study of fold-thrust belts, basin inversion and hydrocarbon structure development. Attached Figure Description

[0042] Figure 1 This is a flowchart of the method for automatically drawing the elevation corridor profile of the physical simulation model according to an embodiment of the present invention;

[0043] Figure 2 This is a cross-sectional view of the elevation corridor of a single model according to an embodiment of the present invention;

[0044] Figure 3 This is a comparison example of the multi-model aligned elevation corridor profile diagrams according to an embodiment of the present invention;

[0045] Figure 4 This is a block diagram of an electronic device according to an exemplary embodiment of the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0047] The flowchart of the automatic drawing method for elevation corridor profile of the physical simulation model of the present invention is as follows: Figure 1 Specifically, it includes the following steps:

[0048] S1. Obtain digital elevation models of each stage of geological body evolution, and then integrate the coordinate system of the digital elevation models of each stage into the coordinate system of the structural physics simulation experiment.

[0049] Specifically, in physical modeling, the surfaces of models at different stages are reconstructed into Digital Elevation Models (DEMs) through 3D photogrammetry. Their original coordinate systems are often affected by camera angles, lighting and shadows, and the geometric similarity ratios of different model sizes. To ensure spatial comparability and structural consistency between multi-stage DEMs, the digital elevation model (DEM) file (.tif format) is first read, and the rasterized elevation matrix is ​​extracted. An elevation field is established and the geographic transformation matrix and projection definition are simultaneously analyzed to identify the spatial coverage of the model data.

[0050] Automatically detect the coordinate reference system type of the DEM. When the input data is in a geographic coordinate system (such as WGS84) or a projection system that does not match the experimental coordinates, establish a unified experimental coordinate mapping based on the geometric similarity law of the model:

[0051] ,

[0052] in, The coordinates represent the coordinates under the physical simulation experiment, and S represents the geometric similarity ratio between the digital elevation model of the natural instance and the simulated digital elevation model, used to map the real crustal scale to the model scale. The matrix is ​​used to make the X-axis of the experimental coordinate system parallel to the direction of the principal strain or central bulge. This is a translation vector used to correct the origin offset of the digital elevation model at different stages. Represents the coordinates in a digital elevation model.

[0053] In centrifuge simulations, the scale is typically [scale value missing]. ~ Even minute rotation or scaling errors can cause significant elevation shifts. Through the affine transformation described above, the system eliminates differences in scale, rotation, and reference elevation across different experimental stages, ensuring that the elevation difference truly reflects the structural deformation process of the model surface rather than coordinate errors. This step establishes a "model structural coordinate system" consistent with the structural orientation and satisfying the similarity law, guaranteeing that subsequent corridor profile extraction can track fold axis migration, depression evolution, and overall strain distribution on a unified physical benchmark.

[0054] S2. Under a unified coordinate system, the structural deformation axis is automatically determined based on the spatial range of the DEM data and the experimental loading direction, and a sampling reference path is established along this direction. This path represents the main deformation concentration zone or morphological undulation zone in the experimental model, used for subsequent profile construction and elevation sampling. The path can be automatically generated according to the experimental design, or it can be manually corrected by the user inputting the start and end points. In this invention, the sampling point spacing can be manually set according to the actual geological conditions, or it can be automatically determined based on multiple constraints such as topographic spatial frequency, curvature change rate, slope change rate, and DEM resolution, thereby minimizing the number of sampling points while ensuring the integrity of structural features.

[0055] A series of sampling points are generated along the sampling reference path. The distribution of these sampling points can be uniform or gradient-driven. When uniform sampling is used, the system controls the sampling interval through multiple constraint rules to ensure spatial rationality and geometric accuracy at the scale of the constructed physical simulation. This step specifically includes the following three sub-processes:

[0056] (1) Sampling baseline route planning

[0057] The system determines the path direction based on the DEM data boundary and the experimental loading direction, and plans a sampling baseline parallel to the structural axis within the effective data area. Users can also customize the start and end points to meet the observation requirements of specific structural directions. A safety distance offset is maintained between the path and the boundary to ensure that the sampling line is entirely within the effective elevation data range.

[0058] ,

[0059] ,

[0060] and These represent the starting and ending coordinates of the sampling reference path, respectively. and These are the x-coordinates of the left and right boundaries of the digital elevation model, respectively. The preset vertical position is set to offset, which is a safety distance (typically 1-3 pixel widths). Geologically, this path corresponds to the structural observation baseline along the deformation axis, reflecting the overall extension direction of tectonic strain.

[0061] (2) Sampling density calculation

[0062] The system automatically calculates the number and spacing of sampling points based on the DEM resolution, experimental scale, and preset accuracy requirements. To balance detailed structural identification with control over experimental data volume, the sampling spacing... The following comprehensive selection rules will be used to determine the selection:

[0063] ,

[0064] ,

[0065] in: The highest spatial frequency of the terrain along the path direction (reflecting the degree of landform undulation) is used to prevent high-frequency structural features such as fold cores and thrust fronts from being smoothed by low sampling. To achieve the maximum curvature of the elevation curve (controlling profile geometric errors) and avoid peak position shift; To maximize the rate of change of slope (controlling the elevation difference between adjacent points), and to avoid statistical bias caused by excessive elevation difference between adjacent sampling points in steep slope areas; This refers to the pixel spacing of the DEM. , These are the allowable elevation and slope error thresholds, respectively; To ensure sampling safety (0.7-0.9), redundancy is reserved for experimental noise and photographic errors, thereby improving the stability of the results; This represents the effective path length.

[0066] This comprehensive rule constrains the sampling interval in terms of both geometric features and resolution, ensuring that uniform sampling captures key deformation features while avoiding redundant sampling at the constructed simulation scale. The resulting baseline sampling point density and the geometric similarity ratio of the experimental model are thus determined. Consistency is ensured so that subsequent profile extraction results can be compared with the geological prototype at scale.

[0067] (3) Generation of equidistant points

[0068] Along the baseline route from the starting point to the ending point, the system calculates the intervals. A series of equally spaced sampling points are generated. The coordinates of the points are calculated using linear interpolation.

[0069] ,

[0070] in, This represents the coordinates of the i-th sampling point. The x-coordinate represents the starting point of the sampling reference path. To preset the vertical position, This represents the path direction angle. The system records the cumulative distance of each point relative to the starting point. This serves as the reference for subsequent profile coordinates.

[0071] In terms of geological significance in structural physics simulation, this step is equivalent to laying out standardized cross-sections along the main deformation axes, enabling subsequent strip sampling and elevation curves to objectively reflect the morphological differences and concentrated deformation distribution in different regions. Uniform sampling within this framework ensures comparability and morphological continuity between adjacent sections, serving as a spatial benchmark for subsequent strip construction and profile analysis.

[0072] By using an adaptive calculation mechanism based on sampling intervals of spatial frequency, curvature and slope change rate, this invention ensures that the elevation signals of the high undulation area and the boundary of the structural segment do not overlap or become distorted without increasing redundant sampling points, thereby improving the stability and repeatability of the elevation corridor profile in multi-model comparison.

[0073] S3. At sampling points along the normal direction of the sampling reference path, vertical strips are established. The width of the vertical strips is set according to the spatial range of the digital elevation model. Sampling points are generated on the vertical strips at fixed intervals to obtain vertical sampling strips. Compared with extracting elevations along a single profile, this invention significantly reduces the impact of random noise caused by local particle accumulation, boundary effects, or photogrammetric errors on the profile results by constructing sampling strips of finite width in the normal direction of the sampling points and statistically processing the elevations within the strips.

[0074] Along the sampling path laid out along the tectonic deformation axis, the system establishes elevation strip profiles perpendicular to the path direction at each sampling point. This method aims to comprehensively reflect the elevation variation characteristics within the normal range of the tectonic deformation zone, and compared to a single profile, it can more stably reflect the overall trend and deformation intensity distribution of landforms or tectonic morphology. The system performs dense elevation sampling on each strip to ensure that the micro-topographic information of the experimental model surface is completely captured. This step includes the following three geological and algorithmic processes:

[0075] (1) Determination of sampling strip width

[0076] The system first reads the spatial extent of the current DEM and calculates the total width of the model in the normal direction:

[0077] ,

[0078] in, Indicates the width of the vertical strip. This is the preset strip ratio coefficient. and bound.bottom are respectively The highest and lowest values ​​in the y-direction of the digital elevation model space at the point.

[0079] According to the preset strip ratio coefficient (Typically 60-90%), the system automatically determines the vertical strip width. This proportional determination method ensures that the sampling strips are within a similar relative width range at different experimental scales. In construction physics simulations, this means that regardless of changes in the overall model thickness or size, the strip sampling always covers a typical width representing a local deformation unit (such as a folded wing or fault zone), thus maintaining geometric and dynamic similarity across experiments. The system also performs boundary checks to ensure that both ends of the normal direction are within the valid DEM data range; if an out-of-bounds error occurs, the strip width will automatically reduce to the allowable range and a warning message will be recorded.

[0080] From a geological perspective, setting the width of the strip is equivalent to defining a sampling window that can represent a local structural unit. It can cover local morphologies such as folds, thrusts, and depressions, while avoiding morphological overlap caused by crossing different structural domains. The existence of the strip allows the profile to integrate the overall morphological signals within the same structural zone, reducing local anomalies caused by experimental noise such as sand grain accumulation, local collapse, or light and shadow, thereby improving the geological comparability and morphological continuity of the profile.

[0081] (2) Construction of vertical sampling lines

[0082] At each sampling point At that point, along the normal direction of the sampling reference path (defined as...) Establish a perpendicular section line segment with its two endpoints as follows:

[0083] ,

[0084] ,

[0085] in, and Let represent the coordinates of the top and bottom endpoints of the i-th vertical strip, respectively. This represents the coordinates of the i-th sampling point on the sampling reference path where the vertical strip is located. Indicates the sampling reference path in The normal at the point.

[0086] This normal section line represents the strain distribution in the vertical direction of the structural deformation zone. Unlike traditional single-line sections, the strip profile integrates the statistical characteristics of all elevation samples in the normal direction at each reference sampling location. Its strip average elevation is:

[0087] ,

[0088] in, Indicates the location of the sampling reference path parameters The average elevation value obtained at the location and along the vertical sampling strip. This represents the arc length parameter or discrete sampling location index on the sampling reference path (usually a pre-defined centerline on the DEM or a user-specified sampling trajectory). Indicates the width of the vertical strip. This represents the coordinates of any point on the strip. Indicates the sampling reference path in The center coordinate vector at the location, where u represents the offset along the normal direction of the strip.

[0089] The average elevation of the strips above is calculated using continuous integral averaging, which is suitable for providing continuous and dense sampling of strips. This average elevation can be regarded as an effective envelope curve of the local topographic undulations of the tectonic zone, which is closer to the average deformation trend in a geological sense. This process is similar to the corridor profiling method in geomorphological analysis, which can smooth local disturbances and stably reveal the spatial morphology of structures such as fold axes, thrust fronts, or depressions.

[0090] (3) Dense elevation data collection

[0091] To ensure that all terrain information within the strip area is captured completely, the system uses fixed longitudinal spacing on each vertical line segment. For uniform point distribution, the formula is as follows:

[0092] ,

[0093] ,

[0094] ,

[0095] in, This represents the coordinates of the j-th sampling point in the i-th vertical strip. This represents the offset of the j-th sampling point along the direction perpendicular to the strip normal. Indicates the sampling reference path in Normal at point This indicates the number of sampling points in the vertical strip.

[0096] The corresponding DEM elevation is read at each sampling point. , This represents the elevation value of the j-th sampling point in the i-th vertical strip, forming a longitudinal sampling sequence. Dense sampling ensures that all elevation changes within the strip profile are completely recorded, without missing any subtle undulations or abrupt changes. As long as the longitudinal spacing... Satisfying the Nyquist condition:

[0097] ,

[0098] in As the highest effective spatial frequency for normal elevation changes, the terrain signal within the strip can be accurately reconstructed in subsequent elevation curve calculations.

[0099] From a geological structural perspective, dense sampling is a crucial step in ensuring the complete capture of experimental data. It not only avoids missing local structural features due to sparse sampling but also improves morphological stability through multi-point averaging, making cross-sectional comparisons of experiments at different stages or with different parameters more repeatable and reliable in interpretation. The resulting strip-averaged cross-section can be considered a stable geomorphic projection of the tectonic deformation field, quantitatively reflecting strain distribution and morphological evolution characteristics.

[0100] S4. Obtain the elevation values ​​of all sampling points on the vertical sampling strip, extract the maximum, minimum and average elevation values ​​of each strip, and concatenate these three types of elevation values ​​in sequence according to the sampling sequence number of the sampling reference path to form three continuous elevation feature curves, thus obtaining the elevation corridor profile.

[0101] It includes the following three sub-processes:

[0102] (1) Elevation data extraction

[0103] The system sequentially reads the elevation values ​​of all sampling points in each vertical sampling strip. For each point, the system automatically matches its spatial location in the DEM data matrix and extracts the corresponding elevation data. Simultaneously, it identifies and removes invalid or out-of-bounds points to ensure the integrity and accuracy of the sampling results. From a geological perspective, this process is equivalent to systematically collecting surface micro-undulation data along the normal direction in the tectonic deformation zone. It is a crucial step in converting the model's surface morphology into a quantitative signal, laying the foundation for subsequent extraction of representative tectonic trend curves.

[0104] (2) Calculation of statistical characteristics

[0105] For the high-order sequence extracted within each vertical strip The system calculates three key statistical indicators:

[0106] ,

[0107] ,

[0108] ,

[0109] in, This represents the local highest point at the position corresponding to the i-th vertical strip, reflecting local uplift or arching; This represents the local lowest point at the position corresponding to the i-th vertical strip, indicating a relative depression or sinking. Let be the average elevation of the i-th vertical strip, which approximately represents the morphological center plane of the tectonic deformation zone. The average elevation of the vertical strips here is calculated using discrete averaging, which is suitable for analyzing the elevation distribution characteristics within the strips.

[0110] These three types of elevation values ​​are sorted by path sampling sequence number. By connecting them sequentially, three continuous elevation characteristic curves can be formed:

[0111] ,

[0112] ,

[0113] ,

[0114] Among them, the average curve of the strip It typically best reflects the overall trend of deformation zones and can be used to identify geological features such as uplift axes, morphological segments, and areas of concentrated tectonic strain. The curve representing the local minimum point of the strip. This represents the curve of the local maximum point of the strip. Compared with a single profile, the strip average curve is more stable and more repeatable, and can achieve quantitative comparisons between different experimental stages or different parameter models.

[0115] (3) Data quality monitoring and curve consistency verification

[0116] During the calculation process, the system performs data validity and statistical consistency checks to ensure the reliability and geological rationality of the results. First, the statistical relationships between the bands are verified:

[0117] ,

[0118] This is to rule out data anomalies or interpolation errors. Secondly, a continuity test is performed on the average elevation changes between adjacent strips, and the profile gradient and curvature are calculated.

[0119] ,

[0120] ,

[0121] in, Characterizing the slope gradient of the profile, and These are the average elevations of the (i+1)th and (i-1)th vertical stripes, respectively; The sampling interval for the vertical stripes; It characterizes curvature changes and is used to identify bulges, depressions, or segmental boundaries.

[0122] These processes are entirely executed by the system's backend algorithm, requiring no additional calculations from the user. In the context of physical simulation, this quality and consistency check is equivalent to assessing the topographic integrity of the experimental model's surface. The system automatically identifies and corrects outliers based on the detection results, ensuring that the elevation curves of each profile are continuous, smooth, and free of non-structural jumps, thus reflecting the true tectonic deformation trend. Through this automated control, the system effectively distinguishes between local anomalies caused by data noise and genuine topographic undulations caused by the tectonic process.

[0123] To compare the topographic differences created by experimental models with different tectonic parameters (such as the width of the weak crustal zone, friction coefficient, and orientation of the brittle upper crustal structure), the system performs unified benchmark alignment, dynamic normalization, and data consistency adjustment on the elevation profiles of each model. This method eliminates non-tectonic elevation differences while ensuring that curve differences only reflect the true morphological response caused by different tectonic control conditions. The system plots an average value curve with path distance on the horizontal axis and elevation on the vertical axis, and fills the area between the maximum and minimum values ​​with an elevation envelope to display the overall spatial pattern of uplifts and depressions under different models.

[0124] (1) Determination of benchmark elevation

[0125] The system traverses the profile data of all experimental models to identify the lowest topographic location unaffected by tectonic deformation, thereby determining a unified reference elevation. This reference surface represents the initial static equilibrium layer of the experimental system and can be understood as a topographic reference surface before tectonic loading. In tectonic physics simulations, this plane typically corresponds to the upper boundary of the lower crustal detachment layer or the background region where no strain has occurred. Aligning the profiles of different models to the same reference surface effectively eliminates system offsets caused by sand layer thickness, boundary tilt, and illumination reconstruction errors, allowing subsequent difference analysis to focus on the tectonic effects themselves.

[0126] (2) Elevation normalization processing

[0127] Elevation normalization. Based on a defined global benchmark, the system standardizes the elevation statistics for each strip. During the adjustment, the relative elevation relationships within each strip remain unchanged; only the elevation values ​​corresponding to a specific DEM file are shifted globally, ensuring all profile curves are compared on a unified reference plane. That is, for each point on the profile curve, its elevation value corresponds to the coordinates (point_x, point_y) as follows:

[0128] ,

[0129] in , These are the coordinates corresponding to the elevation values ​​of the sampling points. It is the minimum elevation value among all sampling points on a vertical sampling line.

[0130] (3) Data consistency maintenance and morphological stability regulation

[0131] During normalization and multi-model alignment, the system automatically monitors morphological deviations between profiles and maintains data consistency through internal parameter adjustments. A morphological stability coefficient is calculated. Used to evaluate the overall matching degree of different model profiles:

[0132] ,

[0133] in, The morphological consistency index of the m-th physical simulation model is represented, and L represents the total length of the sampling reference path. This represents the strip average elevation curve of the m-th simulation model. This is the average curve of multiple models.

[0134] This coefficient is not a user-input variable, but rather an internal criterion that is automatically calculated and updated in real time by the system. When Value below preset threshold At that time, the system will adaptively fine-tune the normalized weights. or reference translation This is to optimize the cross-sectional alignment results and maintain the morphological stability between models.

[0135] After completing multi-model normalization and morphological stability adjustment, batch processing and comprehensive visualization are performed on all DEM files in the specified directory, achieving fully automated output from data to structural interpretation. This module not only generates elevation profile maps and statistical result tables, but also constructs a morphological image interface for geological interpretation, providing intuitive support for tectonic process analysis.

[0136] (1) Automated batch processing and result integration

[0137] The system automatically traverses all DEM data files within a specified folder, sequentially performing a complete process of elevation extraction, statistics, normalization, and visualization for each model. During processing, the system automatically records the identification number, spatial reference information, processing status, and timestamp of each data file, creating a traceable data processing log. This mechanism ensures that all experimental stages and analyses of models with different parameters are conducted within a unified framework, thereby enabling a systematic and quantitative comparison of tectonic deformation evolution.

[0138] (2) Simultaneous visualization of multi-model profiles

[0139] Within a unified spatial coordinate system, the system simultaneously plots all processed elevation profile curves, using different color bands to distinguish between different model parameter combinations. Above and below the average elevation line of each curve, the system automatically fills in semi-transparent envelope bands, displaying the elevation range corresponding to that model. This visualization method not only reflects the overall distribution of uplifts and depressions but also intuitively reveals the influence of different tectonic parameters on landforms. For example, the curve's slope, crest spacing, and envelope width correspond to changes in strain concentration areas, tectonic segment spacing, and uplift intensity, respectively. Through multi-curve overlay, the system can clearly demonstrate the differences in morphological response between models, reflecting the dynamic laws of topographic evolution under different tectonic control conditions.

[0140] (3) Feature point annotation and construction interpretation

[0141] The system automatically identifies key feature points (including the highest point, lowest point, and curvature extreme points) of each curve in the output image, and displays each feature point with accompanying numerical and location information, which facilitates subsequent geological interpretation and data comparison.

[0142] This module not only provides an intuitive display of elevation data but also offers geologists a quantitative interface for morphological interpretation. Through parallel visualization of results from multiple models, it can quickly identify the commonalities and differences in tectonic morphology, revealing the control of weak zone geometry, frictional properties, and upper crustal structure on the segmentation and morphological development of orogenic belts. This provides important evidence for the dynamic interpretation of experimental results and comparison with natural landforms.

[0143] Example 1: Single-model elevation corridor cross-section diagram

[0144] To verify the applicability of the method of this invention to a single model in structural physics simulation experiments, terrain extraction and analysis were performed on a set of structural physics simulation models. This structural physics simulation model employs a two-layer structure: brittle feldspar sand is used to simulate the upper crust, while a plastic silica gel mixture is used to simulate the lower crust. A 2cm pre-existing weak zone is introduced into the lower crust, causing the model to shorten under controlled centrifugal force of approximately 18g, forming a compression deformation similar to that of a continental collision environment. This method enables quantitative and detailed analysis of the uplifted terrain controlled by the weak zone.

[0145] S1: Constructing a Physical Simulation DEM Data Reading and Experimental Coordinate System

[0146] The model is photographed in 3D at 0.2cm increments, and the DEM is reconstructed using photogrammetry software (resolution approximately 0.016cm / pixel). After importing the DEM file, the system automatically identifies data boundaries and pixel coordinates. To ensure comparability of multi-stage DEMs within the same spatial framework, this system employs the affine mapping proposed in this invention:

[0147] ,

[0148] Among them, geometric similarity ratio Rotation matrix Correction of shooting posture deviation Translation vector Adjust the DEM origin position. This step projects the experimental data onto a unified tectonic coordinate system, ensuring that subsequent profile trajectories and topographic differences accurately reflect the tectonic process rather than photographic errors.

[0149] S2: Determination of structural deformation axis and establishment of reference points

[0150] The model's compression direction is approximately east-west, while the weak zone extends north-south. The system automatically generates a baseline path consistent with the structural deformation trend based on the DEM boundary, geometric center, and loading direction; this can be considered a structural section line traversing the central uplift axis. The sampling interval is set as follows: The path length is approximately cm. , generate approximately 100 sampling points. This sampling density is sufficient to capture elevation changes beyond the model's non-boundary effects and abrupt slope changes at the thrust front.

[0151] S3: Vertical sampling strip construction and longitudinal elevation extraction

[0152] According to the elevation corridor width formula mentioned above: In this embodiment, the effective longitudinal range of the DEM is: That is, the width is 12cm. Take: Then the strip width is: This width is sufficient to cover key structural units such as the uplifted core, folded flanks, and thrust leading edge, enabling comprehensive statistics of the structural deformation domain.

[0153] The reference path direction angle is set to Therefore, the vertical unit vector is: That is, the direction is orthogonal to the structural strike, that is, the spatial geometry of folds, uplifts and faults is observed in a way that cuts across the structural zone.

[0154] The highest spatial frequency of elevation variation is estimated as follows: According to the Nyquist condition, In this embodiment, the following values ​​are used: This is far higher than the sampling requirements, allowing for the complete capture of small-scale undulations in the core of the fold. With a band coverage of 9.6 cm, each band contains approximately: Each sampling point constitutes a complete two-dimensional high-order sequence.

[0155] S4: Elevation Statistics and Characteristic Curve Generation

[0156] The system calculates the strip height sequence separately. Maximum, minimum and average elevation:

[0157] ,

[0158] For example, the statistical results for typical locations are as follows: Average elevation The integral average form of the corresponding strips: This represents the effective topographic center plane within the tectonic zone. The three statistical curves, when strung together, form a complete elevation corridor profile, which can stably reflect the geometric structure of the uplift axis, the changes in the fold limbs, and the concave features of the fault front.

[0159] The system outputs a single-model elevation corridor profile as follows: Figure 2 As shown in the figure, the horizontal axis represents the distance of the model from the starting edge endpoint, the vertical axis represents the model elevation value, the shaded area represents the range of elevation value variation (minimum to maximum value) along the baseline sampling route, and the dashed line represents the average model elevation. Figure 2 The geometry of the central uplift is fully displayed, indicating significant strain concentration. The peak location corresponds well with the center of the weak zone, suggesting that the geometry of the weak lower crust directly controls the location of the uplift axis. The curvature extrema on the profile clearly indicate the location of the thrust fault front; the width ratio of the anticline core-depression zone is similar to that of natural examples. This embodiment verifies that the method of the present invention can accurately capture the topographic response of tectonic deformation, providing a quantitative tool for analyzing the formation mechanism of the central uplift.

[0160] Example 2: Batch Comparison of Elevation Corridor Profiles from Multiple Models

[0161] This embodiment selects four groups of crustal weak zones with widths of 1cm (Model 1), 2cm (Model 2), 3cm (Model 3), and 4cm (Model 4) for structural physics simulation experiments. The method of this invention is used to conduct batch DEM processing, elevation corridor profile alignment, topographic morphology comparison, and structural interpretation. The experiment aims to explore its controlling role in the development of continental uplift-depression systems, the formation of tectonic segments, and topographic response patterns, and to seek its dynamic correspondence with natural orogenic belts.

[0162] Except for the width of the weak zone, the four models have the same material composition (brittle sand layer in the upper crust and silica-silica mixture in the lower crust), loading rate, similarity ratio and experimental conditions. Therefore, they can be regarded as a systematic sensitivity experiment of the single tectonic parameter of the width of the weak zone in the lower crust.

[0163] S1: Constructing a physical simulation DEM batch reading and experimental coordinate system (Part 1)

[0164] The system reads DEM files from each stage in batches, automatically identifies boundaries, and corrects coordinates. Due to slight differences in shooting angles and pixel resolutions among different models, the program uses an image boundary matching algorithm to automatically complete registration, making all data comparable under the same spatial reference.

[0165] Different experimental batches exhibit slight differences due to photogrammetric reconstruction, camera position, and lighting conditions. Without coordinate unification, spatial shifts in the peaks, fractures, and depressions between different models will occur, or false segmentation may result simply from shadow deviation, making true structural geometry comparison difficult.

[0166] Therefore, this system performs the aforementioned affine registration on four sets of DEMs in batches:

[0167] ,

[0168] Where the matrix Typical values ​​are close to the identity matrix (e.g.) ), reflecting slight scaling and rotation corrections, while translation vectors It can correct for DEM origin drift. After coordinate unification, the four sets of models are compared under the same structural reference frame, thus ensuring that the elevation differences reflect the actual structural influence, rather than reconstruction errors.

[0169] S2: Determination of structural deformation axis and establishment of reference points

[0170] The system automatically identifies the geometric center of the model and the overall orientation of the weak zone, generating a unified sampling path that runs through the center of the weak zone. This axis was chosen to identify the structural zoning section of the fold-fracture combination.

[0171] Sampling interval is This ensures that even minute-scale changes in slope and curvature in the model can be captured. The unified path provides geometric consistency across the four models, which is beneficial for identifying peak shifts, uplift width expansions, changes in the position of the fault front, and differences in morphological segmentation caused by changes in the width of the weak zone.

[0172] S3: Vertical sampling strip construction and longitudinal elevation sampling

[0173] The system is based on the formula: The strip width is automatically calculated for each model, and the results are shown in Table 1.

[0174] Table 1

[0175]

[0176] This width selection (coefficient 0.8) captures the main areas of structural deformation, avoids boundary effects affecting curve morphology, and covers the complete structural zone from the uplifted core and folded flanks to the thrust front. (Vertical unit vector) A structural profile orthogonal to the weak zone strike, i.e., transversely oriented, can be used in nature to identify uplift amplitude, fold symmetry, fracture dip angle and location, and morphological characteristics of the leading edge of a wedge or thrust zone.

[0177] The longitudinal sampling interval is uniformly set as follows: Satisfying the Nyquist condition, it can capture steep scarps at the leading edge of step-like thrust faults, sharp curvatures in the core of folds above weak zones, and gentle slope changes transitioning to depressions. The system generates approximately... Each vertical sampling point constitutes a complete two-dimensional high-order sequence matrix.

[0178] S4: Elevation Statistics and Multi-Model Characteristic Curve Calculation

[0179] The system provides high-order program sequences for each strip of each model. calculate:

[0180] ,

[0181] It reflects the location and magnitude of the uplifted core, corresponding to the strain concentration region above the weak zone. It represents subsidence or tectonic depression on the front side of a fault and is often used to identify the thrust front or basement displacement. The central plane representing the strip morphology depicts the equilibrium trend of regional tectonic strain. The patterns presented in the four sets of models are shown in Table 2.

[0182] Table 2

[0183]

[0184] The profiles of the four models were superimposed and compared under a unified reference plane. The system employs a morphological stability coefficient:

[0185] ,

[0186] The overall geometric similarity of the curves from each model was evaluated. The results show that the 1–2 cm weak band exhibits sharp curves with high and concentrated peak values. It exhibits a typical concentrated uplift zone. The 3cm weak zone corresponds to a decrease in peak value, with the uplift widening, gentle curvature, and a semi-dispersed uplift pattern. The 4cm weak zone corresponds to a gently sloping profile with a broad dome-like shape; the peak is no longer sharp. This indicates that its construction response mode is significantly different from the aforementioned model, and the strain performance is diffused.

[0187] The multi-model overlay curves output by the system show a clear geometric trend: the peak value decreases by about 35% as the weak zone widens, the uplift strength decreases, the half-width of the uplift increases by about 80%, and the stress and strain change from concentration to diffusion. The systematic weakening of the curvature peak value makes the edges of the structural segments less distinct. The widening of the minimum elevation curve corresponds to the expansion of the depression towards both wings, and the peak position maintains a corresponding relationship with the center of the weak zone. See the example diagram comparing the multi-model aligned elevation corridor profiles of this embodiment for reference. Figure 3 In the figure, the horizontal axis represents the distance of the model from the starting edge endpoint, the vertical axis represents the model elevation value, the shaded area represents the range of elevation value variation (minimum to maximum value) along the baseline sampling route, the dashed line represents the average elevation value, and the curves of different colors represent different models.

[0188] The results show that the system can automatically align and quantitatively compare elevation curves between different models under batch DEM data conditions. This method can accurately reveal the control law of changes in the width of the weak lower crust on the uplift amplitude and slope. The experimental results are consistent with the topographic segmentation characteristics along the strike of the research object, indicating that the method of this invention has high analytical capability in identifying the coupling relationship between weak width and uplift topographic features. This method provides reliable data support for reconstructing physical simulation experiments and matching relationships with orogenic belts, significantly improving the objectivity and repeatability of topographic response analysis.

[0189] In one exemplary embodiment, a computer-readable storage medium is included, which stores a computer program that, when executed by a processor, implements the above-described method for automatically drawing elevation corridor profiles of a physical simulation model.

[0190] Please see Figure 4 In one exemplary embodiment, the device further includes an electronic device including at least one processor, at least one memory, and at least one communication bus.

[0191] The memory stores a computer program, which includes computer-readable instructions. The processor calls the computer-readable instructions stored in the memory through the communication bus to execute the above-mentioned method for automatically drawing the elevation corridor profile of the physical simulation model.

[0192] In one exemplary embodiment, a computer program product is proposed, including a computer program / instruction that, when executed by a processor, implements the steps of the above-described method for automatically drawing elevation corridor profiles of a physical simulation model.

[0193] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for automatically drawing elevation corridor profiles of a physical simulation model, characterized in that, Includes the following steps: S1. Obtain digital elevation models of each stage of geological body evolution, and transfer the coordinate system of the digital elevation models of each stage to the coordinate system of the structural physics simulation experiment. S2. Under a unified coordinate system, the structural deformation axis is determined based on the digital elevation model, and a corresponding sampling reference path is established parallel to the structural deformation axis. Equidistant sampling points are generated on the sampling reference path. The sampling interval on the sampling reference path is calculated according to the following formula: ， The number of sampling points is calculated using the following formula: ， The coordinates of the equally spaced sampling points are as follows: ， in, For sampling interval, Indicates the sampling safety factor. This represents the highest spatial frequency of the terrain along the sampling reference path. This indicates the allowable elevation error threshold. This indicates the maximum curvature of the elevation curve. This indicates the permissible slope error threshold. Indicates the maximum rate of change of slope. Indicates the pixel spacing of the digital elevation model. Indicates the number of sampling points. Indicates the effective path length. Indicates rounding up. This indicates the threshold for the number of sampling points. This represents the coordinates of the i-th sampling point. The x-coordinate represents the starting point of the sampling reference path. To preset the vertical position, The path direction angle; S3. Establish a vertical strip along the normal of the sampling reference path at the sampling point, and set the width of the vertical strip according to the spatial range of the digital elevation model. Generate sampling points on the vertical strip at fixed intervals to obtain the vertical sampling strip. S4. Obtain the elevation values ​​of all sampling points on the vertical sampling strip, extract the maximum, minimum and average elevation values ​​of each strip, and concatenate these three types of elevation values ​​in sequence according to the sampling sequence number of the sampling reference path to form three continuous elevation feature curves, thus obtaining the elevation corridor profile.

2. The method for automatically drawing elevation corridor profiles of a physical simulation model according to claim 1, characterized in that, The mapping relationship between the coordinate system of the digital elevation model at each stage and the coordinate system of the physical simulation experiment is as follows: ， in, Let S represent the coordinates under the physical simulation experiment, and let S represent the geometric similarity ratio between the digital elevation model of the natural instance and the simulated digital elevation model. This is a matrix used to ensure that the X-axis of the experimental coordinate system is parallel to the direction of the principal strain or central bulge. This is a translation vector used to correct the origin offset of the digital elevation model at different stages. Represents the coordinates in a digital elevation model.

3. The method for automatically drawing elevation corridor profiles of a physical simulation model according to claim 1, characterized in that, The start and end points of the sampling reference path parallel to the construction axis are: ， ， in, and These represent the starting and ending coordinates of the sampling reference path, respectively. and These are the x-coordinates of the left and right boundaries of the digital elevation model, respectively. The preset vertical position is set to offset, which is the safety distance.

4. The method for automatically drawing elevation corridor profiles of a physical simulation model according to claim 1, characterized in that, Define the coordinates of the two endpoints of the vertical strip within its width as follows: ， ， ， in, and Let represent the coordinates of the top and bottom endpoints of the i-th vertical strip, respectively. This represents the coordinates of the i-th sampling point on the sampling reference path where the vertical strip is located. This is the preset strip ratio coefficient. Indicates the sampling reference path in Normal at point Indicates the width of the vertical strip. and bound.bottom are respectively The highest and lowest values ​​in the y-direction of the digital elevation model space at the point.

5. The method for automatically drawing elevation corridor profiles of a physical simulation model according to claim 1, characterized in that, The average elevation value on the vertical sampling strip is calculated using the following formula: ， in, Indicates the location of the sampling reference path parameters The average elevation value obtained at the location and along the vertical sampling strip. This represents the arc length parameter or discrete sampling position index on the sampling reference path. Indicates the width of the vertical strip. Represents the coordinates of any point on the strip. This indicates that the sampling reference path is in The center coordinate vector at that location, where u represents the offset along the normal direction of the strip. Indicates the sampling reference path in The normal at the point.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

7. An electronic device, characterized in that, The device includes a processor and a memory, the processor being interconnected with the memory, wherein the memory is used to store a computer program, the computer program including computer-readable instructions, and the processor is configured to invoke the computer-readable instructions to perform the method as described in any one of claims 1-5.

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-5.

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