Three-dimensional geological modeling method and system based on medium stratigraphic profile data

Abstract

The invention relates to a three-dimensional geological modeling method and system based on middle stratigraphic profile data, and the method comprises the following steps: obtaining seismic time profile map data, and carrying out the comparative analysis of a reflection waveform, arrival time and continuity, and obtaining a middle stratigraphic profile result map; obtaining a track route and positioning data in a preset field area range, and obtaining a measuring line arrangement track plane graph; preprocessing the survey line arrangement track plane graph to obtain a survey line data set; stretching on the survey line data set based on the middle stratigraphic profile result map to obtain a three-dimensional space coordinate of the middle stratigraphic profile result on the survey line; the vectorized three-dimensional space coordinates are segmented according to stratum attributes, and stratum measuring line points are obtained; processing the stratigraphic line points layer by layer by using a semi-variable function to obtain a stratigraphic point set; establishing an irregular triangulation network to obtain a continuous stratum surface; and converting the two-dimensional stratum data of the continuous stratum surface into a three-dimensional form to obtain a three-dimensional geologic model of the medium stratum profile data.

Description

Technical Field

[0001] This application relates to the field of 3D modeling, and mainly relates to a 3D geological modeling method and system based on middle stratum profile data. Background Art

[0002] In many key fields such as current geological research, resource exploration, and engineering construction, the demand for accurate understanding of underground geological structures is increasing day by day. However, traditional two-dimensional geological data is insufficient to meet these needs. Two-dimensional geological data is usually presented in the form of a plan view or a cross-sectional view, which can only provide limited planar or single-direction geological information and is difficult to intuitively and comprehensively present complex three-dimensional geological forms.

[0003] However, there are many deficiencies in existing 3D geological modeling technologies when dealing with middle stratum profile data. At the data level, the quality differences of multi-source data are large and it is difficult to fuse, affecting the accuracy of the model; in terms of model construction, the modeling accuracy is low for complex geological structures, and the computing efficiency is low when dealing with large-scale data; in addition, the model has large uncertainties, but there are no effective evaluation and control methods, and there is also a lack of a unified standard to verify the model, resulting in the difficulty of ensuring the reliability of the model.

[0004] For example, the Chinese invention patent with the publication number "CN115984501A" discloses a "Method, Device, Equipment and Storage Medium for Establishing a Geological 3D Model", which specifically discloses "obtaining sample soil layer data at a specified soil layer position in a geological area, and establishing an initial geological 3D model according to the sample soil layer data; obtaining the position of the soil layer to be measured in the geological area, and determining the predicted soil layer information of the position of the soil layer to be measured according to the sample soil layer data; establishing a final geological 3D model matching the geological area according to the initial geological 3D model and the predicted soil layer information. By obtaining the sample soil layer data at the specified soil layer position in the geological area to establish an initial geological 3D model, and then further determining the predicted soil layer information of the position of the soil layer to be measured according to the sample soil layer data, and finally establishing a final geological 3D model according to the initial geological 3D model and the predicted soil layer information", but this method only relies on the sample soil layer data at the specified soil layer position in the geological area to establish the initial geological 3D model and determine the predicted soil layer information of the position of the soil layer to be measured, which will lead to inaccurate initial models and predicted information, affecting the accuracy of the final geological 3D model; in addition, in the process of establishing the initial geological 3D model, determining the predicted soil layer information, and establishing the final geological 3D model, there is a lack of a method for dealing with abnormal geology and it is impossible to accurately reflect complex geological conditions. Summary of the Invention

[0005] In order to solve the above problems existing in the prior art, this application provides a 3D geological modeling method and system based on middle stratum profile data.

[0006] The technical solution of this application is as follows:

[0007] On the one hand, the present invention proposes a three-dimensional geological modeling method based on middle stratum profile data, and the method includes:

[0008] Obtain seismic time section diagram data, conduct comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section diagram data to obtain a middle stratum profile result diagram; obtain the track route and positioning data within the preset field area, and use surveying and mapping tools to obtain a track plan diagram of survey line layout;

[0009] Preprocess the track plan diagram of survey line layout, extract middle stratum survey line data item by item to obtain a survey line data set; stretch based on the middle stratum profile result diagram on the survey line data set to obtain the three-dimensional spatial coordinates of the middle stratum profile result on the survey line; vectorize the three-dimensional spatial coordinates, and segment the vectorized three-dimensional spatial coordinates according to stratum attributes to obtain stratum survey line points; process the stratum survey line points layer by layer using a semivariogram to obtain a stratum point set;

[0010] Establish an irregular triangular network according to the stratum point set to obtain a continuous stratum surface; convert the two-dimensional stratum data of the continuous stratum surface into a three-dimensional form to obtain a three-dimensional geological model of the middle stratum profile data.

[0011] Preferably, the comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section diagram data is specifically as follows:

[0012] Conduct data cleaning on the seismic time section data; the data cleaning includes processing missing values, outliers, and data format standardization, and extracting the characteristic values in the seismic time section diagram data, and the characteristic values include reflection waveform, arrival time, and continuity;

[0013] The comparison of the reflection waveform is specifically to check whether the reflection waveforms of the same stratum interface are similar to the reflection waveforms on adjacent seismic traces; if they are similar, it indicates that the similar waveforms belong to the same stratum interface;

[0014] The comparison of the arrival time is specifically to calculate the depth range of the stratum interface in combination with the propagation speed of seismic waves in the stratum and the arrival time of the reflected wave; compare the arrival time differences of the same reflected wave in different seismic traces, if the arrival time differences of the same reflected wave in different seismic traces are within the preset range, it indicates that the stratum interface is gentle and the inclination angle is small; if the arrival time difference exceeds the preset range, it indicates that the inclination angle of the stratum interface is large and there are faults or folds;

[0015] The comparison of the continuity is specifically as follows: if the continuity of the reflection wave event axis is complete, it indicates that the current formation interface is a stable formation interface; otherwise, it indicates that the current formation interface is an unstable formation interface, and further analyze the reasons for the discontinuity of the reflection wave, including the existence of faults and erosion.

[0016] Integrate the comparison results of the formation interface data to generate a formation interface data set with the seabed elevation within a preset range; based on the formation interface data set, use computer-aided drawing software to draw the cross-section result section diagram of the middle formation.

[0017] Preferably, preprocess the track plan of the survey line layout to obtain the three-dimensional space coordinates of the points on the middle formation section line, specifically:

[0018] According to the track plan of the survey line layout, extract the middle section formation line data item by item to obtain a line data set; use the line data set to establish an engineering section, the longitudinal section of the engineering section is the initial section, and the digital elevation model terrain data of the preset field area is the section reference; set the sampling interval and buffer range of the survey line, collect the measurement data within the sampling interval and buffer range, and generate a section template file; use the selected three-dimensional composition tool to modify the drawing scale and the maximum and minimum elevation ranges of the section template file, and measure the horizontal distance height difference of the section formation to obtain the modified drawing scale.

[0019] Stretch the cross-section result diagram of the middle formation along the survey line direction according to the modified drawing scale to obtain the terrain line and the elevations of different formations in the survey line direction; calculate the three-dimensional point coordinates (x i , y i , z i,l ) on the survey line based on the terrain line, where (x0, y0) represents the starting coordinates of the sampling point; (x n , y n ) represents the ending coordinates of the sampling point; L represents the total length of the survey line; n represents the number of sampling points; z i,k represents the elevation of the i-th sampling point on the k-th bottom layer; s i represents the distance from the i-th sampling point to the survey line; i represents the index value of the i-th sampling point; l represents the index value of the l-th formation.

[0020] Preferably, use the semi-variogram to process the formation line points layer by layer to obtain a formation point set, specifically:

[0021] Traverse all the formation line points, based on the intrinsic hypothesis in the spatial correlation hypothesis of geological bodies, where the intrinsic hypothesis includes mean stationarity and semi-variogram stationarity, and is expressed by the formula:

[0022]

[0023] In the formula, Z(w) represents the formation attribute value of the sampling point w; w represents the position of the random sampling point in space; σ represents the mean value corresponding to the random sampling point in space; h represents the relative distance between two random sampling points; γ represents the semivariogram; Var represents the variance; E[] represents the expectation;

[0024] Using the formation attribute values of the known sampling points, calculate the minimum variance of the estimated value between the preset sampling point and the known sampling points, which is expressed by the formula:

[0025]

[0026] In the formula, represents the formation attribute value of the preset sampling point w k ; Z(w i ) represents the formation attribute value of the i-th sampling point; λ i represents the weight of the i-th sampling point; Var represents the minimum variance of the estimated value; represents the minimum variance of the estimated value between the estimated formation attribute value and the true formation attribute value of the preset sampling point w k ; G represents the optimization function; j represents the index value of the j-th sampling point; μ represents the Lagrange multiplier;

[0027] Obtain the weights by solving the Kriging equations, which is expressed by the formula:

[0028]

[0029] γ ij =γ(w i -w j );

[0030] In the formula, γ ij represents the semivariogram value between the i-th sampling point and the j-th sampling point;

[0031] Optimize the parameters of the semivariogram using the cross-validation method. The parameters of the semivariogram include the range, nugget value, and sill value; the specific solution for calculating the planar formation point set is to divide the currently known formation points into m subsets; use the grid search method to generate a uniformly distributed candidate parameter combination ε=(a r ,b p ,c q ), which is expressed by the formula:

[0032] a r =a min +r·Δa, a∈[a min ,a max ,

[0033] bp = b min + p·Δb, b ∈ [b min , b max ,

[0034] c q = c min + q·Δc, q ∈ [c min , c max ,

[0035] wherein, a r represents the r-th range; a min represents the preset minimum range; a max represents the preset maximum range; Δa represents the preset range step; b p represents the p-th nugget effect value; b min represents the preset minimum nugget effect value; b max represents the preset maximum nugget effect value; Δb represents the preset nugget effect value step; c q represents the q-th sill value; c min represents the preset minimum sill value; c max represents the preset maximum sill value; Δc represents the preset sill value step; r represents the index value of the r-th range; p represents the index value of the p-th nugget effect value; q represents the index value of the q-th sill value;

[0036] Using m - 1 subsets as fitting data to fit the semivariogram, and using the remaining one subset as verification data, and evaluating based on the mean square error, which is expressed by the formula:

[0037]

[0038] wherein, MSE represents the mean square error; D represents the data volume of the verification data; represents the predicted value of the d-th verification data; Z(y d ) represents the true value of the d-th verification data; d represents the index value of the d-th verification data;

[0039] Select the candidate parameter combination with the minimum mean square error as the optimal parameter combination, substitute the optimal parameter combination into the Kriging equations, recalculate the weights and the formation property values of the preset points, and obtain the formation point set.

[0040] Preferably, an irregular triangular network is established according to the formation point set to obtain a continuous formation surface, specifically:

[0041] Calculate the distance between any two points in the formation point set, select the two formation points corresponding to the minimum distance for connection, and use the connected line as the initial baseline;

[0042] Search for formation points that satisfy the Delaunay condition on the right side of the initial baseline, connect the formation points to the endpoints of the connecting line respectively to form Delaunay triangles; select two sides of the Delaunay triangles as the new baseline according to the preset selection order to form new Delaunay triangles;

[0043] Iterate the process of forming Delaunay triangles until all formation points are selected, and all Delaunay triangles form an irregular triangular network to obtain a continuous formation surface.

[0044] Preferably, convert the two-dimensional formation data of the continuous formation surface into a three-dimensional form, specifically:

[0045] Input the upper and lower formation surface data of the preset formation, calculate the spatial range covered by the upper and lower surfaces, and perform alignment processing on the continuous formation data of the upper and lower surfaces; connect the corresponding sides of the triangles between the upper and lower formations to generate a prism;

[0046] Stretch the continuous formations of the upper and lower surfaces according to the preset formation arrangement order to obtain the stretched formations;

[0047] Merge the stretched formations to generate a three-dimensional geological body model.

[0048] Preferably, the method further includes visualizing the three-dimensional geological model of the middle formation profile data, including attribute assignment, formation stratification coloring, and model publishing, specifically:

[0049] The attribute assignment is specifically to assign specific attribute values to each element in the three-dimensional geological model of the middle formation profile data, including formation number, formation type, and formation name;

[0050] The formation stratification coloring is specifically to use different colors to distinguish different formation types;

[0051] The model publishing is specifically to share the three-dimensional geological model of the middle formation profile data as a web service.

[0052] On the other hand, the present invention also proposes a three-dimensional geological modeling system based on middle formation profile data. The system includes a data acquisition module, a data processing module, a model construction module, and a result output module, wherein:

[0053] The data acquisition module is used to acquire seismic time section data, conduct comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section data to obtain the middle stratum profile result diagram; acquire the track route and positioning data within the preset field area, and use the surveying and mapping tool to obtain the track plan of the survey line layout.

[0054] The data processing module is used to preprocess the track plan of the survey line layout, extract the middle stratum survey line data item by item to obtain the survey line data set; stretch based on the middle stratum profile result diagram on the survey line data set to obtain the three-dimensional space coordinates of the middle stratum profile result on the survey line; vectorize the three-dimensional space coordinates, and segment the vectorized three-dimensional space coordinates according to the stratum attributes to obtain the stratum survey line points; process the stratum survey line points layer by layer using the semi-variogram function to obtain the stratum point set.

[0055] The model construction module is used to establish an irregular triangular network based on the stratum point set to obtain a continuous stratum surface; convert the two-dimensional stratum data of the continuous stratum surface into a three-dimensional form to obtain the three-dimensional geological model of the middle stratum profile data.

[0056] The result output module is used to display the three-dimensional geological model of the middle stratum profile data.

[0057] On the other hand, the present invention also proposes an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements a three-dimensional geological modeling method based on middle stratum profile data as described in any embodiment of the present invention.

[0058] On the other hand, the present invention also proposes a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements a three-dimensional geological modeling method based on middle stratum profile data as described in any embodiment of the present invention.

[0059] Compared with the prior art, the beneficial effects of the present invention are:

[0060] 1) The present invention provides a three-dimensional geological modeling method and system based on middle stratum profile data. By acquiring seismic time section data and conducting comparative analysis on the reflection waveform, arrival time, and continuity therein to obtain the middle stratum profile result diagram, it improves the comprehensiveness and accuracy of stratum information acquisition, and enhances the standardization and systematicness of data.

[0061] 2) The present invention provides a three-dimensional geological modeling method and system based on middle stratum profile data. By stretching on the survey line dataset based on the middle stratum profile result map, the three-dimensional spatial coordinates of the middle stratum profile result on the survey line are obtained, improving the accuracy and reliability of the conversion from two-dimensional data to three-dimensional spatial coordinates; vectorizing the three-dimensional spatial coordinates and segmenting them according to stratum attributes to obtain stratum survey line points, improving the degree of refined processing of stratum data;

[0062] 3) The present invention provides a three-dimensional geological modeling method and system based on middle stratum profile data. Using the semi-variogram to process the stratum survey line points layer by layer to obtain a stratum point set, enhancing the analysis and integration ability of stratum point data; establishing an irregular triangular network based on the stratum point set to obtain a continuous stratum surface, converting the two-dimensional stratum data into a three-dimensional form to obtain a three-dimensional geological model, improving the ability to construct a continuous stratum surface from discrete data and generate a three-dimensional model. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 is the flowchart of the method of the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] The following describes the specific embodiments of the present invention to facilitate those skilled in the art of the present technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art of the present technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions created using the concept of the present invention are within the scope of protection.

[0065] The present invention provides the following technical solution: A three-dimensional geological modeling method and system based on middle stratum profile data.

[0066] Embodiment 1

[0067] Specifically refer to Figure 1 , this embodiment provides a three-dimensional geological modeling method based on middle stratum profile data, and the specific steps include:

[0068] S1. Obtain seismic time section data, and perform comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section data to obtain a middle stratum profile result map;

[0069] Performing comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section data specifically includes:

[0070] Perform data cleaning on the seismic time section data; the data cleaning includes processing missing values, outliers, and data format standardization, and extracting the characteristic values in the seismic time section data, where the characteristic values include reflection waveform, arrival time, and continuity;

[0071] The comparison of the reflected waveforms specifically involves checking whether the reflected waveforms of the same formation interface are similar to those on adjacent seismic traces; if they are similar, it indicates that the similar waveforms belong to the same formation interface.

[0072] The comparison of the arrival times specifically involves calculating the depth range of the formation interface by combining the propagation velocity of seismic waves in the formation and the arrival times of the reflected waves; comparing the arrival time differences of the same reflected wave in different seismic traces, if the arrival time differences of the same reflected wave in different seismic traces are within a preset range, it indicates that the formation interface is gentle and has a small inclination angle; if the arrival time differences exceed the preset range, it indicates that the formation interface has a large inclination angle and there are faults or folds.

[0073] The comparison of the continuity specifically involves that if the continuity of the reflected wave in-phase axis is complete, it indicates that the current formation interface is a stable formation interface; otherwise, it indicates that the current formation interface is an unstable formation interface, and further analyze the reasons for the discontinuity of the reflected wave, including the existence of faults and erosion.

[0074] Integrate the comparison results of the formation interface data to generate a dataset of formation interfaces with seabed elevations within a preset range; based on the dataset of formation interfaces, use computer-aided drawing software to draw the cross-section result section diagram of the middle formation.

[0075] S2. Obtain the track routes and positioning data within the preset field area, and use surveying and mapping tools to obtain the track plan of the survey line layout.

[0076] S3. Preprocess the track plan of the survey line layout, extract the middle-section formation survey line data item by item to obtain a dataset of survey lines; use the dataset of survey lines to establish an engineering section, the longitudinal section of the engineering section is the initial section, and the digital elevation model terrain data of the preset field area is the profile reference; set the sampling interval and buffer range of the survey line, collect the measurement data within the sampling interval and buffer range, and generate a section template file; use the selected 3D composition tool to modify the map scale and the maximum and minimum elevation ranges of the section template file, and measure the horizontal distance and elevation difference of the profile formation to obtain the modified map scale.

[0077] S4. Stretch based on the middle-formation profile result diagram on the dataset of survey lines to obtain the three-dimensional space coordinates of the middle-formation profile result on the survey line.

[0078] Stretch the middle-formation profile result diagram along the survey line direction according to the modified map scale to obtain the terrain line and the elevations of different formations in the survey line direction; calculate the three-dimensional point coordinates (x i , y i , z i,l ) on the survey line, where (x0, y0) represents the starting coordinates of the sampling point; (x n , y n ) represents the ending coordinates of the sampling point; L represents the total length of the survey line; n represents the number of sampling points; z i,k represents the elevation of the i-th sampling point on the bottom layer of the k-th layer; s i represents the distance from the i-th sampling point to the survey line; i represents the index value of the i-th sampling point; l represents the index value of the l-th stratum;

[0079] S5. Vectorize the three-dimensional space coordinates and segment the vectorized three-dimensional space coordinates according to the stratum attributes to obtain stratum survey line points;

[0080] S6. Process the stratum survey line points layer by layer using the semi-variogram, traverse all stratum survey line points, and based on the intrinsic hypothesis in the geobody spatial correlation hypothesis, where the intrinsic hypothesis includes mean stationarity and semi-variogram stationarity, which is expressed by the formula:

[0081]

[0082] In the formula, Z(w) represents the stratum attribute value of the sampling point w; w represents the position of a random sampling point in space; σ represents the mean value corresponding to the random sampling point in space; h represents the relative distance between two random sampling points; γ represents the semi-variogram; Var represents the variance; E[] represents the expectation;

[0083] Calculate the minimized estimated value variance between the preset sampling point and the known sampling points using the stratum attribute values of the known sampling points, which is expressed by the formula:

[0084]

[0085] In the formula, represents the stratum attribute value of the preset sampling point w k ; Z(w i ) represents the stratum attribute value of the i-th sampling point; λ i represents the weight of the i-th sampling point; Var represents the minimized estimated value variance; represents the minimized estimated value variance between the estimated stratum attribute value and the true stratum attribute value of the preset sampling point w k ; G represents the optimization function; j represents the index value of the j-th sampling point; μ represents the Lagrange multiplier;

[0086] Obtain the weights by solving the Kriging equations, which is expressed by the formula:

[0087]

[0088]

[0089] γ ij = γ(w i - w j );

[0090] Where γ ij represents the semivariogram value between the i-th sampling point and the j-th sampling point;

[0091] The parameters of the semivariogram are optimized using the cross-validation method. The parameters of the semivariogram include range, nugget, and sill. The specific calculation of the planar formation point set is to divide the currently known formation points into m subsets. The grid search method is used to generate a uniformly distributed candidate parameter combination ε = (a r , b p , c q ), which is expressed by the formula:

[0092] a r = a min + r·Δa, a ∈ [a min , a max ,

[0093] b p = b min + p·Δb, b ∈ [b min , b max ,

[0094] c q = c min + q·Δc, q ∈ [c min , c max ,

[0095] Where a r represents the r-th range; a min represents the preset minimum range; a max represents the preset maximum range; Δa represents the preset range step; b p represents the p-th nugget; b min represents the preset minimum nugget; b max represents the preset maximum nugget; Δb represents the preset nugget step; c q represents the q-th sill; c min represents the preset minimum sill; c max represents the preset maximum sill; Δc represents the preset sill step; r represents the index value of the r-th range; p represents the index value of the p-th nugget; q represents the index value of the q-th sill;

[0096] The semi-variogram is fitted using m - 1 subsets as fitting data, and the remaining one subset is used as verification data, and the evaluation is based on the mean square error, which is expressed by the formula:

[0097]

[0098] In the formula, MSE represents the mean square error; D represents the data volume of the verification data; Z~(y d ) represents the predicted value of the d-th verification data; Z(y d ) represents the true value of the d-th verification data; d represents the index value of the d-th verification data;

[0099] The candidate parameter combination with the smallest mean square error is selected as the optimal parameter combination, and the optimal parameter combination is substituted into the Kriging equations to recalculate the weights and the formation property values of the preset points, obtaining a set of formation points;

[0100] S7. An irregular triangular network is established based on the set of formation points to obtain a continuous formation surface;

[0101] The upper and lower formation surface data of the preset formation are input, the spatial range covered by the upper and lower surfaces is calculated, and the continuous formation data of the upper and lower surfaces are aligned; the corresponding sides of the triangles between the upper and lower formations are connected to generate a prism;

[0102] The continuous formations of the upper and lower surfaces are stretched according to the preset formation arrangement order to obtain the stretched formations;

[0103] The stretched formations are merged to generate a three-dimensional geological body model;

[0104] S8. The two-dimensional formation data of the continuous formation surface is converted into a three-dimensional form to obtain a three-dimensional geological model of the middle formation profile data;

[0105] S9. The method further includes visualizing the three-dimensional geological model of the middle formation profile data, including attribute assignment, formation stratification coloring, and model publishing, specifically:

[0106] The attribute assignment is specifically to assign specific attribute values to each element in the three-dimensional geological model of the middle formation profile data, including formation number, formation type, and formation name;

[0107] The formation stratification coloring is specifically to use different colors to distinguish different formation types;

[0108] The model publishing is specifically to share the three-dimensional geological model of the middle formation profile data as a web service.

[0109] Example 2

[0110] This embodiment provides a three-dimensional geological modeling system based on middle stratum profile data. The system includes a data acquisition module, a data processing module, a model construction module, and a result output module, where:

[0111] The data acquisition module is used to acquire seismic time section diagram data, perform comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section diagram data to obtain a middle stratum profile result diagram; acquire the track route and positioning data within the preset field area, and use surveying and mapping tools to obtain a track plan of survey line layout;

[0112] The data processing module is used to extract middle stratum survey line data item by item based on the track plan of survey line layout to obtain a survey line data set; stretch based on the middle stratum profile result diagram on the survey line data set to obtain the three-dimensional space coordinates of the middle stratum profile result on the survey line; vectorize the three-dimensional space coordinates, and segment the vectorized three-dimensional space coordinates according to stratum attributes to obtain stratum survey line points; use the semi-variogram to process the stratum survey line points layer by layer to obtain a stratum point set;

[0113] The model construction module is used to establish an irregular triangular network based on the stratum point set to obtain a continuous stratum surface; convert the two-dimensional stratum data of the continuous stratum surface into a three-dimensional form to obtain a three-dimensional geological model of the middle stratum profile data

[0114] The result output module is used to display the three-dimensional geological model of the middle stratum profile data.

[0115] Embodiment 3

[0116] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements a three-dimensional geological modeling method based on middle stratum profile data as described in any embodiment of the present invention.

[0117] Embodiment 4

[0118] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements a three-dimensional geological modeling method based on middle stratum profile data as described in any embodiment of the present invention.

[0119] It should be noted that the system, electronic device, and computer-readable storage medium described in the present invention are all based on the same principle as the method described in Embodiment 1, and will not be elaborated here.

[0120] The above are only embodiments of the present invention, and thus do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A three-dimensional geological modeling method based on middle formation profile data, characterized in that, The method includes: Obtain seismic time section profile data, conduct comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section profile data to obtain the middle stratum profile result diagram; obtain the track route and positioning data within the preset field area, and use surveying and mapping tools to obtain the track plan of the survey line layout; Preprocess the track plan of the survey line layout, extract the middle stratum survey line data item by item to obtain a survey line data set; stretch based on the middle stratum profile result diagram on the survey line data set to obtain the three-dimensional spatial coordinates of the middle stratum profile on the survey line; vectorize the three-dimensional spatial coordinates, and segment the vectorized three-dimensional spatial coordinates according to the stratum attributes to obtain stratum survey line points; process the stratum survey line points layer by layer using the semivariogram to obtain a stratum point set; Establish an irregular triangular network according to the stratum point set to obtain a continuous stratum surface; convert the two-dimensional stratum data of the continuous stratum surface into a three-dimensional form to obtain a three-dimensional geological model of the middle stratum profile data.

2. The three-dimensional geological modeling method based on middle stratum profile data according to claim 1, characterized in that The comparative analysis of the reflection waveform, arrival time, and continuity in the seismic time section profile data specifically includes: Conduct data cleaning on the seismic time section data; the data cleaning includes processing missing values, outliers, and data format standardization, and extracting the characteristic values in the seismic time section profile data, where the characteristic values include reflection waveform, arrival time, and continuity; The comparison of the reflection waveform specifically means checking whether the reflection waveforms of the same stratum interface are similar to the reflection waveforms on adjacent seismic traces; if they are similar, it indicates that the similar waveforms belong to the same stratum interface; The comparison of the arrival time specifically means combining the propagation speed of seismic waves in the stratum and the arrival time of the reflected wave to calculate the depth range of the stratum interface; compare the arrival time differences of the same reflected wave in different seismic traces. If the arrival time differences of the same reflected wave in different seismic traces are within the preset range, it indicates that the stratum interface is gentle and has a small inclination angle; if the arrival time difference exceeds the preset range, it indicates that the stratum interface has a large inclination angle and there are faults or folds; The comparison of the continuity specifically means that if the continuity of the reflected wave in-phase axis is complete, it indicates that the current stratum interface is a stable stratum interface; otherwise, it indicates that the current stratum interface is an unstable stratum interface, and further analyze the reasons for the discontinuity of the reflected wave, including the existence of faults and erosion; Integrate the comparison results of the stratum interface data to generate a stratum interface data set with the seabed elevation within the preset range; based on the stratum interface data set, use computer-aided drawing software to draw the cross-section diagram of the middle stratum profile result.

3. A three-dimensional geological modeling method based on middle stratum profile data according to claim 1, characterized in that The preprocessing of the track plan of the survey line layout to obtain the three-dimensional spatial coordinates of the points on the middle stratum survey line specifically includes: According to the track plan of the survey line layout, extract the middle stratum survey line data item by item to obtain a survey line data set; use the survey line data set to establish an engineering cross-section, where the longitudinal section of the engineering cross-section is the initial section, and the digital elevation model terrain data of the preset field area is the cross-section reference; Set the sampling interval and buffer range of the survey line, collect the measurement data within the sampling interval and buffer range, and generate a cross-section template file; Using the selected 3D composition tool, modify the drawing scale and the maximum and minimum elevation ranges of the cross-section template file, and measure the horizontal distance difference of the strata in the profile to obtain the modified drawing scale; Stretch the middle formation profile result diagram along the survey line direction according to the modified map scale to obtain the terrain line and the elevations of different formations in the survey line direction; calculate the three-dimensional point coordinates (x i , y i , z i,l ) on the survey line, where (x0, y0) represents the starting coordinates of the sampling point; (x n , y n ) represents the ending coordinates of the sampling point; L represents the total length of the survey line; n represents the number of sampling points; z i,k represents the elevation of the i-th sampling point on the bottom layer of the k-th layer; s i represents the distance from the i-th sampling point to the survey line; i represents the index value of the i-th sampling point; l represents the index value of the l-th formation.

4. A three-dimensional geological modeling method based on middle formation profile data according to claim 1, characterized in that Using the semi-variogram to process the strata survey line points layer by layer to obtain a set of strata points, specifically: Traverse all the strata survey line points. Based on the intrinsic hypothesis in the spatial correlation hypothesis of geological bodies, where the intrinsic hypothesis includes mean stationarity and semi-variogram stationarity, which is expressed by the formula: E[Z(w)] = E[Z(w + h)] = σ, In the formula, Z(w) represents the strata attribute value of the sampling point w; w represents the position of the random sampling point in space; σ represents the mean value corresponding to the random sampling point in space; h represents the relative distance between two random sampling points; γ represents the semi-variogram; Var represents the variance; E[] represents the expectation; Using the strata attribute values of the known sampling points, calculate the minimized estimated value variance between the preset sampling point and the known sampling points, which is expressed by the formula: In the formula, represents the formation attribute value of the preset sampling point w k ; Z(w i ) represents the formation attribute value of the i-th sampling point; λ i represents the weight of the i-th sampling point; Var represents the minimized variance of the estimated value; represents the preset sampling point w k the minimized variance between the estimated formation property value and the true formation property value of; G represents the optimization function; j represents the index value of the j-th sampling point; μ represents the Lagrange multiplier; Obtain the weights by solving the Kriging equations, which is expressed by the formula: γ ij = γ(w i - w j ); where γ ij represents the semi-variogram value between the i-th sampling point and the j-th sampling point; Optimizing the parameters of the semivariogram using the cross-validation method, where the parameters of the semivariogram include range, nugget, and sill; the specific solution for calculating the areal formation point set is to divide the currently known formation points into m subsets; generating a uniformly distributed candidate parameter combination ε = (a r , b p , c q ) of the semivariogram using the grid search method, which is expressed by the formula: a r = a min + r·Δa, a ∈ [a min , a max , b p = b min + p·Δb, b ∈ [b min , b max , c q = c min + q·Δc, q ∈ [c min , c max , where a r represents the r-th range; a min represents the preset minimum range; a max represents the preset maximum range; Δa represents a preset variogram step size; b p represents the p-th nugget effect value; b min represents a preset minimum nugget effect value; b max represents a preset maximum nugget effect value; Δb represents a preset nugget effect value step size; c q represents the q-th sill value; c min represents a preset minimum sill value; c max represents a preset maximum sill value; Δc represents a preset sill value step size; r represents the index value of the r-th range; p represents the index value of the p-th nugget effect value; q represents the index value of the q-th sill value; Use m - 1 subsets as fitting data to fit the semi-variogram, and the remaining one subset as verification data, and evaluate based on the mean square error, which is expressed by the formula: Wherein, MSE represents the mean square error; D represents the amount of verification data; represents the predicted value of the d-th verification data; Z(y d ) represents the true value of the d-th verification data; d represents the index value of the d-th verification data; Select the candidate parameter combination with the minimum mean square error as the optimal parameter combination, substitute the optimal parameter combination into the Kriging equations, recalculate the weights and the strata attribute values of the preset points to obtain a set of strata points.

5. A three-dimensional geological modeling method based on middle formation profile data according to claim 1, characterized in that Based on the set of strata points, establish an irregular triangular network to obtain a continuous strata surface, specifically: Calculate the distance between any two points in the set of strata points, select the two strata points corresponding to the minimum distance for connection, and use the connected line as the initial baseline; Find the strata points that satisfy the Delaunay condition on the right side of the initial baseline, connect the strata points to the endpoints of the connection line respectively to form Delaunay triangles; according to the preset selection order, select two sides of the Delaunay triangle as new baselines to form new Delaunay triangles; Iterate the process of forming Delaunay triangles until all the strata points are selected, and all the Delaunay triangles form an irregular triangular network to obtain a continuous strata surface.

6. A three-dimensional geological modeling method based on middle stratum profile data according to claim 1, characterized in that Convert the two-dimensional strata data of the continuous strata surface into a three-dimensional form, specifically: Input the upper and lower strata surface data of the preset strata, calculate the spatial range covered by the upper and lower surfaces, and perform alignment processing on the continuous strata data of the upper and lower surfaces; Connect the corresponding sides of the triangles between the upper and lower strata to generate a prism; Stretch the continuous strata of the upper and lower surfaces according to the preset strata arrangement order to obtain the stretched strata; Merge the stretched strata to generate a three-dimensional geological body model.

7. A three-dimensional geological modeling method based on middle formation profile data according to claim 1, characterized in that The method further includes visualizing the three-dimensional geological model of the middle strata profile data, including attribute assignment, stratigraphic layering coloring, and model publishing, specifically: The attribute assignment is specifically to assign specific attribute values to each element in the three-dimensional geological model of the middle strata profile data, including strata number, strata type, and strata name; The stratigraphic layer coloring specifically uses different colors to distinguish different stratigraphic types; The model publishing specifically shares the 3D geological model of the middle stratigraphic section data as a web service.

8. A three-dimensional geological modeling system based on middle stratum profile data, characterized in that, The system includes a data acquisition module, a data processing module, a model construction module, and a result output module, where: The data acquisition module is used to acquire seismic time section data, conduct comparative analysis on the reflection waveform, arrival time, and continuity in the seismic time section data to obtain a middle stratigraphic section result map; acquire the track route and positioning data within the preset field area, and use surveying and mapping tools to obtain a track plan of the survey line layout; The data processing module is used to preprocess the track plan of the survey line layout, extract the middle stratigraphic section survey line data item by item to obtain a survey line data set; stretch based on the middle stratigraphic section result map on the survey line data set to obtain the 3D spatial coordinates of the middle stratigraphic section result on the survey line; vectorize the 3D spatial coordinates, and segment the vectorized 3D spatial coordinates according to the stratigraphic attributes to obtain stratigraphic survey line points; use the semi-variogram to process the stratigraphic survey line points layer by layer to obtain a set of stratigraphic points; The model construction module is used to establish an irregular triangular network based on the set of stratigraphic points to obtain a continuous stratigraphic surface; convert the 2D stratigraphic data of the continuous stratigraphic surface into a 3D form to obtain a 3D geological model of the middle stratigraphic section data The result output module is used to display the 3D geological model of the middle stratigraphic section data.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements a 3D geological modeling method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements a 3D geological modeling method according to any one of claims 1 to 7.

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