Seismic profile-guided CPT data mixed field interpolation algorithm, device, medium and equipment

Abstract

The present invention relates to a seismic profile-guided CPT data hybrid field interpolation algorithm, device, medium and equipment. The method combines two-dimensional seismic data and borehole location data to model and identify geological lithology. By establishing a three-dimensional geological model to create a regional soil parameter distribution framework, the purpose of predicting the distribution of soil parameters at any point in the stratum is achieved.

Description

Technical Field

[0001] The present invention relates to the field of engineering investigation and exploration technology, and in particular to a CPT data mixed field interpolation algorithm guided by a seismic profile, a device, a medium and equipment. Background Art

[0002] Marine geological survey technology uses survey tools to acquire data on seafloor topography, stratum distribution, and rock and soil properties. By integrating multi-source geological data, combined with geological modeling and three-dimensional interpolation algorithms, key information such as seafloor structure and lithology distribution can be more accurately identified, providing a reliable basis for offshore wind farm site selection.

[0003] Predicting and interpolating geological parameters is a crucial step in geological modeling. The complex seabed geological environment requires a wide range of geophysical data. These data typically include seismic data and borehole data. Seismic data uses strong and weak reflection axes to represent different subsurface lithologies, structures, or stratigraphic boundaries. However, the use of reflection axes to identify lithologies has significant limitations. For example, the boundaries of lithologic changes can be difficult to identify, and changes in lithologic properties within the same layer can be difficult to detect visually.

[0004] CPT, on the other hand, determines the engineering mechanical properties of soil by measuring the forces acting on the probe in the stratum as it penetrates the ground at a constant speed. This allows for highly accurate, continuous, and reliable data. In practical applications, although borehole location data is often combined with seismic data for analysis, the degree of integration between the two is relatively low, typically limited to cross-reference during seismic data interpretation and geological stratification. Summary of the Invention

[0005] In response to the above problems, the purpose of the present invention is to provide a seismic profile-guided CPT data hybrid field interpolation algorithm, device, medium and equipment, which has the advantages of fusing seismic data and borehole position data, ensuring the accuracy of stratum rock and soil parameter identification, reflecting the actual situation of seabed geology as much as possible, and thus providing reliable reference opinions for engineering.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] The seismic profile-guided CPT data mixed domain interpolation algorithm of the present invention comprises the following steps:

[0008] Process 2D seismic images to obtain attribute features;

[0009] Based on the attribute characteristics, the spatial attributes and geological attributes of the points to be interpolated are calculated;

[0010] Based on spatial attributes and geological attributes, CPT attribute parameters are extracted, and the CPT attribute parameter data are combined and merged with the features;

[0011] The combined and merged data are sliced ​​horizontally, and the slices are processed along the direction of the 2D seismic data to obtain the horizontal interpolation points and interpolation parameters to form multiple slice data sets; for each slice data set, processing is performed based on the acquired 2D seismic data;

[0012] In the transverse slice data set, the interpolation model is constructed using the 2D seismic data as the interpolation parameter and the cone tip resistance obtained from the CPT hole position as the interpolation result;

[0013] Based on the interpolation model, the nearest neighbor interpolation method and the inverse distance interpolation method are used for mixed field interpolation. Combining the nearest neighbor interpolation and the inverse distance weighted interpolation, the influence of spatial attributes and geological attributes is fully considered to achieve smooth and accurate interpolation; and a three-dimensional model is established to form the final interpolation result.

[0014] The CPT data mixed domain interpolation algorithm preferably processes the two-dimensional seismic image to obtain attribute features, specifically comprising the following steps:

[0015] The two-dimensional seismic image is in the segy format file, which is a standard seismic data format used to store and exchange seismic reflection data. Seismic signal data is usually represented as a time series, and the value of each sample point is the amplitude, that is:

[0016] Amplitude(t)=x(t) (1)

[0017] Where Amplitude(t) refers to the amplitude of the seismic signal at time t; x(t) is the function of the seismic signal over time, representing the recorded seismic wave signal;

[0018] Compute phase and envelope characteristics:

[0019] The calculation of phase and envelope usually uses Hilbert transform, which is a tool in signal processing. Hilbert transform converts a real-valued signal into a complex-valued signal. The real part of the complex-valued signal is the original signal, and the imaginary part is its Hilbert transform. The formula of Hilbert transform is as follows:

[0020]

[0021] Where H(x(t)) is the signal after Hilbert transformation in time; x(τ) is the seismic signal value at time τ; t is the current time point; τ is the integral variable, representing all points on the time axis; PV is the principal value integral;

[0022] Through Hilbert transform, we can get the complex value signal, specifically:

[0023] z(t)=x(t)+jH(x(t)) (3)

[0024] Where z(t) is the complex value signal at time t; x(t) is the original seismic signal value at time t; j is the imaginary unit;

[0025] The instantaneous phase is the phase angle of a complex-valued signal and is expressed as:

[0026]

[0027] Where φ(t) is the instantaneous phase at time t; Im(z(t)) is the result of Hilbert transform, which is also the imaginary part of the complex-valued signal at time t; Re(z(t)) is the original seismic signal, which is also the real part of the complex-valued signal at time t;

[0028] The envelope is the modulus of the replicated signal and is calculated as:

[0029]

[0030] Where E(t) is the envelope amplitude at time t; |z(t)| is the modulus of the complex-valued signal at time t.

[0031] The CPT data mixed domain interpolation algorithm preferably includes the following steps:

[0032] When calculating the depth of a point within a layer, the depth needs to be normalized. The formula for calculating normalization is:

[0033]

[0034] Where d is the original depth of the point; min is the minimum thickness of the formation, that is, the depth of the top layer of the formation; max is the maximum thickness of the formation, that is, the depth of the bottom layer of the formation; d NORM The value of the normalized depth of the point.

[0035] The CPT data mixed domain interpolation algorithm preferably extracts CPT attribute parameters and combines and merges CPT attribute parameter data with features, specifically including the following steps:

[0036] The data of the area where the CPT hole is located is selected as the training data, and the data obtained from the CPT is used as the test data. The parameters of the cone tip resistance are obtained to model and analyze the geological formation. The cone tip resistance q c The calculation formula is:

[0037]

[0038] Where, F c is the cone tip penetration force; A c is the cross-sectional area of ​​the cone tip, which is calculated using a standard conical probe using the formula:

[0039]

[0040] Where D c is the diameter of the cone tip;

[0041] Obtain the 2D seismic characteristics of the CPT hole location, including amplitude, phase, and envelope, and combine them with the spatial and geological attributes of the point, and use them together with the cone tip resistance data as a training dataset;

[0042] The two-dimensional seismic characteristics of the points to be interpolated, including amplitude, phase and envelope, are merged and combined with the spatial attributes and geological attributes of the points, and the overall interpolation results are obtained after the interpolation model is trained.

[0043] The CPT data mixed domain interpolation algorithm preferably constructs an interpolation model in a transverse slice data set using two-dimensional seismic data as interpolation parameters and the cone tip resistance obtained at the CPT hole position as the interpolation result, specifically comprising the following steps:

[0044] The cone tip resistance dataset of the sample points is established as follows:

[0045]

[0046] Where, A collection of cone tip resistance data sets for sample points; f1 represents the cone tip resistance of the first sample point. K Represents the cone tip resistance at the Kth sample point;

[0047] Its spatial attributes and 2D seismic attributes are established as follows:

[0048]

[0049] Among them, x1 represents the spatial attributes of the amplitude, phase, envelope and point of a CPT hole;

[0050] Solve the diagonal equation, which is as follows:

[0051]

[0052] Where D(x) represents the metric tensor field; t(x) refers to the distance from the interpolation point to the nearest sample point x k the time required; Represents points other than sample points, that is, points to be interpolated; Represents the gradient of the function t(x), that is, the spatial rate of change of t(x) at point x;

[0053] The calculation of the metric tensor field D(x) provides the anisotropy and spatial variation coefficient of the equation. By using the metric tensor field D(x) to measure the characteristic distance, it reflects the influence of geological structure on the characteristic distance, making two points in the same geological structure very close, while two points in different structures are much farther away;

[0054] Using spatial attributes to calculate t(x), the calculation formula of t(x) is as follows:

[0055]

[0056] Where x mainly contains the spatial attributes of the interpolation points and sample points, that is, the spatial position; x k is the spatial attribute of the kth sample point; the formula for calculating t(x) for the sample point is as follows:

[0057]

[0058] The nearest neighbor interpolation method is used for the data. For each point to be interpolated, the nearest known data point is found and the value of the known data point is assigned to the point to be interpolated. For known sample points, the cone tip resistance is used as the characteristic value;

[0059] The inverse distance interpolation method is used for the data. The inverse distance interpolation method makes the closest point have a greater impact on the interpolation result, while the farthest point has a smaller impact on the interpolation result. The calculation formula of the inverse distance interpolation method is:

[0060]

[0061] Where q c (x) is the interpolation value of the point to be interpolated; N is the number of sample points that need to be provided nearby.

[0062] The CPT data mixed neighborhood interpolation algorithm, preferably, the mixed neighborhood interpolation formula is as follows:

[0063] q c (P) = w NN q c (Q nearest )+w IDW q c (IDW) (15)

[0064] Where w NN is the weight of the nearest neighbor interpolation; q c (Q nearest ) is the result of nearest neighbor interpolation; w IDW is the weight of inverse distance interpolation, qc (IDW) is the result of inverse distance interpolation; q c (P) is the final interpolation result.

[0065] The present invention also provides a seismic profile-guided CPT data mixed field interpolation method, comprising:

[0066] A first processing unit is used to process the two-dimensional seismic image to obtain attribute features;

[0067] The second processing unit is used to calculate the spatial attributes and geological attributes of the points to be interpolated based on the attribute characteristics;

[0068] The third processing unit is used to extract CPT attribute parameters based on the spatial attributes and geological attributes, and to combine and merge the CPT attribute parameter data with the features;

[0069] a fourth processing unit for performing transverse slicing on the combined and merged data, processing the slices along the direction indicated by the two-dimensional seismic data, obtaining transverse interpolation points and interpolation parameters, and forming multiple slice data sets; processing each slice data set based on the acquired two-dimensional seismic data, including analyzing and extracting seismic features in the slice data;

[0070] The fifth processing unit is used to construct an interpolation model in the transverse slice data set using the two-dimensional seismic data as the interpolation parameter and the cone tip resistance obtained at the CPT hole position as the interpolation result;

[0071] The sixth processing unit is used to perform mixed field interpolation based on the interpolation model using the nearest neighbor interpolation method and the inverse distance interpolation method, combining the nearest neighbor interpolation and the inverse distance weighted interpolation, fully considering the influence of spatial attributes and geological attributes, and achieving smooth and accurate interpolation.

[0072] The present invention also provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the seismic profile-guided CPT data mixed field interpolation algorithm.

[0073] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the seismic profile-guided CPT data hybrid field interpolation algorithm are implemented.

[0074] The present invention has the following advantages due to the adoption of the above technical solution:

[0075] The present invention combines two-dimensional seismic data and borehole location data to model and identify geological lithology. By establishing a three-dimensional geological model, a regional soil parameter distribution framework is created to achieve the purpose of predicting the distribution of soil parameters at any point in the stratum.

[0076] The present invention has the advantage of fusing seismic data and borehole position data, ensuring the accuracy of stratum rock and soil parameter identification, reflecting the true situation of seabed geology as much as possible, and thus providing reliable reference opinions for engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. Throughout the drawings, the same reference numerals are used to denote the same components. In the drawings:

[0078] Figure 1 It is the original image of the seabed 2D seismic data;

[0079] Figure 2 It is the result obtained by applying the inverse distance interpolation method to the CPT cone tip resistance based on 2D seismic data;

[0080] Figure 3 It is the profile result obtained by applying the hybrid neighborhood interpolation method to the CPT cone tip resistance based on 2D seismic data;

[0081] Figure 4 The top view and cross-sectional view of the model are obtained by applying the hybrid neighborhood interpolation method of the method of the present invention to the CPT cone tip resistance based on two-dimensional seismic data. DETAILED DESCRIPTION

[0082] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0083] The present invention provides a seismic profile-guided CPT data hybrid field interpolation algorithm, which combines two-dimensional seismic data and borehole location data to model and identify geological lithology. By establishing a three-dimensional geological model to create a regional soil parameter distribution framework, the purpose of predicting the distribution of soil parameters at any point in the stratum is achieved.

[0084] The present invention will be further described below with reference to the embodiments shown in the accompanying drawings.

[0085] The present invention provides a seismic profile-guided CPT data mixed domain interpolation algorithm, comprising the following steps:

[0086] Step 1: Process the 2D seismic image to obtain attribute features;

[0087] Step 2: Based on the attribute characteristics, calculate the spatial attributes and geological attributes of the points to be interpolated. The spatial attributes include the horizontal and vertical coordinates of the point, as well as the layer thickness and depth of the point within the layer. The regional stratigraphic data preparation stage has been divided into seven regions. The geological attributes include the region where the point is located and the stratigraphic attributes.

[0088] Step 3: Based on the spatial attributes and geological attributes, CPT attribute parameters are extracted, and the CPT attribute parameter data are combined and merged with the features;

[0089] Step 4: Slice the combined and merged data horizontally. The slices are processed along the direction indicated by the 2D seismic data to obtain transverse interpolation points and interpolation parameters to form multiple slice data sets. Each slice data set is processed based on the acquired 2D seismic data, including analyzing and extracting seismic features (including amplitude, phase, envelope, etc.) in the slice data.

[0090] Step 5: In the transverse slice data set, the interpolation model is constructed using the 2D seismic data as the interpolation parameter and the cone tip resistance obtained at the CPT hole position as the interpolation result;

[0091] Step 6: Based on the interpolation model, the nearest neighbor interpolation method and the inverse distance interpolation method are used for mixed domain interpolation. Combining the nearest neighbor interpolation and the inverse distance weighted interpolation, the effects of spatial attributes and geological attributes are fully considered to achieve smooth and accurate interpolation (such as Figure 3 ); and build a three-dimensional model to form the final interpolation result (as shown in Figure 4 shown).

[0092] In the above embodiment, preferably, the step 1 of processing the two-dimensional seismic image to obtain attribute features specifically includes the following steps:

[0093] Step 1.1, the 2D seismic image is in segy format, which is a standard seismic data format used to store and exchange seismic reflection data (such as Figure 1 As shown in Figure 2), seismic signal data is usually expressed as a time series, and the value of each sample point is the amplitude, which is:

[0094] Amplitude(t)=x(t) (1)

[0095] Where Amplitude(t) refers to the amplitude of the seismic signal at time t; x(t) is the function of the seismic signal over time, representing the recorded seismic wave signal;

[0096] Step 1.2, calculate phase and envelope characteristics:

[0097] The calculation of phase and envelope usually uses Hilbert transform, which is a tool in signal processing. Hilbert transform converts a real-valued signal into a complex-valued signal. The real part of the complex-valued signal is the original signal, and the imaginary part is its Hilbert transform. The formula of Hilbert transform is as follows:

[0098]

[0099] Where H(x(t)) is the signal after Hilbert transformation in time; x(τ) is the seismic signal value at time τ; t is the current time point; τ is the integral variable, representing all points on the time axis; PV is the principal value integral;

[0100] Through Hilbert transform, we can get the complex value signal, specifically:

[0101] z(t)=x(t)+jH(x(t)) (3)

[0102] Where z(t) is the complex value signal at time t; x(t) is the original seismic signal value at time t; j is the imaginary unit;

[0103] The instantaneous phase is the phase angle of a complex-valued signal and is expressed as:

[0104]

[0105] Where φ(t) is the instantaneous phase at time t; Im(z(t)) is the result of Hilbert transform, which is also the imaginary part of the complex-valued signal at time t; Re(z(t)) is the original seismic signal, which is also the real part of the complex-valued signal at time t;

[0106] The envelope is the modulus of the replicated signal and is calculated as:

[0107]

[0108] Where E(t) is the envelope amplitude at time t; |z(t)| is the modulus of the complex-valued signal at time t.

[0109] In the above embodiment, preferably, the step 2 of calculating the spatial attributes and geological attributes of the interpolation points includes the following steps:

[0110] Step 2.1: When calculating the depth of a point within a layer, the depth needs to be normalized. Normalizing the point depth is to normalize the depth of the seismic data to a standard range (usually 0 to 1). This makes it easier and more consistent to compare data between different strata thicknesses, and improves the accuracy of interpolation. Normalization first determines the thickness range of the strata, and then calculates the normalized value of the point. The formula for calculating normalization is:

[0111]

[0112] Where d is the original depth of the point; min is the minimum thickness of the formation, that is, the depth of the top layer of the formation; max is the maximum thickness of the formation, that is, the depth of the bottom layer of the formation; d NORM The value of the normalized depth of the point.

[0113] In the above embodiment, preferably, the extraction of CPT attribute parameters in step 3 and combining and merging the CPT attribute parameter data with the features specifically include the following steps:

[0114] Step 3.1, select the data in the area where the CPT hole is located as training data, and use the data obtained from the CPT as test data to model and analyze the geological formation by obtaining the parameters of the cone tip resistance. The cone tip resistance q c The calculation formula is:

[0115]

[0116] Where, F c The cone tip penetration force is the vertical force exerted on the cone tip during its penetration into the soil layer. This is directly measured by the sensor of the CPT device. c is the cross-sectional area of ​​the cone tip, which is calculated using a standard conical probe using the formula:

[0117]

[0118] Where D c is the diameter of the cone tip;

[0119] Step 3.2: Obtain the 2D seismic characteristics of the CPT hole location, including amplitude, phase, and envelope, and combine them with the spatial and geological attributes of the point location and use them together with the cone tip resistance data as a training dataset.

[0120] Step 3.3: Merge and combine the 2D seismic characteristics of the points to be interpolated, including amplitude, phase, and envelope, with the spatial attributes and geological attributes of the points, and wait for the interpolation model to be trained before inputting them to obtain the overall interpolation result.

[0121] In the above embodiment, preferably, in step 5, in the transverse slice data set, the two-dimensional seismic data is used as the interpolation parameter, and the cone tip resistance obtained at the CPT hole position is used as the interpolation result to construct an interpolation model, which specifically includes the following steps:

[0122] Step 5.1: Create a collection of the cone tip resistance dataset for the sample points as follows:

[0123]

[0124] Where, A collection of cone tip resistance data sets for sample points; f1 represents the cone tip resistance of the first sample point. K Represents the cone tip resistance at the Kth sample point;

[0125] Its spatial attributes and 2D seismic attributes are established as follows:

[0126]

[0127] Among them, x1 represents the spatial attributes of the amplitude, phase, envelope and point of a CPT hole;

[0128] Step 5.2, solve the diagonal equation, which is as follows:

[0129]

[0130] Where D(x) represents the metric tensor field; t(x) refers to the distance from the interpolation point to the nearest sample point x k The time required; here, time is just an abbreviation for non-Euclidean distance, that is, characteristic distance; Represents points other than sample points, that is, points to be interpolated; Represents the gradient of the function t(x), that is, the spatial rate of change of t(x) at point x;

[0131] The calculation of the metric tensor field D(x) provides the anisotropy and spatial variation coefficient of the equation. By using the metric tensor field D(x) to measure the characteristic distance, it reflects the influence of geological structure on the characteristic distance, making two points in the same geological structure very close, while two points in different structures are much farther away;

[0132] Using spatial attributes to calculate t(x), the calculation formula of t(x) is as follows:

[0133]

[0134] Where x mainly contains the spatial attributes of the interpolation points and sample points, that is, the spatial position; x k is the spatial attribute of the kth sample point; the formula for calculating t(x) for the sample point is as follows:

[0135]

[0136] Step 5.3: Use the nearest neighbor interpolation method to interpolate the data. For each point to be interpolated, find its nearest known data point and assign the value of the known data point to the point to be interpolated. For known sample points, use the cone tip resistance as the characteristic value.

[0137] Step 5.4: Use the inverse distance interpolation method on the data. The inverse distance interpolation method makes the closest point have a greater impact on the interpolation result, and the farthest point has a smaller impact on the interpolation result (e.g. Figure 2 The calculation formula of the inverse distance interpolation method is:

[0138]

[0139] Where q c (x) is the interpolation value of the point to be interpolated; N is the number of sample points that need to be provided nearby.

[0140] In the above embodiment, preferably, the formula for the mixed neighborhood interpolation in step 6 is as follows:

[0141] q c (P) = w NN q c (Q nearest )+w IDW q c (IDW) (15)

[0142] Where w NN is the weight of the nearest neighbor interpolation; q c (Q nearest ) is the result of nearest neighbor interpolation; w IDW is the weight of inverse distance interpolation, q c (IDW) is the result of inverse distance interpolation; q c (P) is the final interpolation result.

[0143] The present invention also provides a seismic profile-guided CPT data mixed domain interpolation method, which is characterized by comprising:

[0144] A first processing unit is used to process the two-dimensional seismic image to obtain attribute features;

[0145] The second processing unit is used to calculate the spatial attributes and geological attributes of the points to be interpolated based on the attribute characteristics;

[0146] The third processing unit is used to extract CPT attribute parameters based on the spatial attributes and geological attributes, and to combine and merge the CPT attribute parameter data with the features;

[0147] a fourth processing unit for performing transverse slicing on the combined and merged data, processing the slices along the direction indicated by the two-dimensional seismic data, obtaining transverse interpolation points and interpolation parameters, and forming multiple slice data sets; processing each slice data set based on the acquired two-dimensional seismic data, including analyzing and extracting seismic features in the slice data;

[0148] The fifth processing unit is used to construct an interpolation model in the transverse slice data set using the two-dimensional seismic data as the interpolation parameter and the cone tip resistance obtained at the CPT hole position as the interpolation result;

[0149] The sixth processing unit is used to perform mixed field interpolation based on the interpolation model using the nearest neighbor interpolation method and the inverse distance interpolation method, combining the nearest neighbor interpolation and the inverse distance weighted interpolation, fully considering the influence of spatial attributes and geological attributes, and achieving smooth and accurate interpolation.

[0150] The present invention also provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the seismic profile-guided CPT data mixed field interpolation algorithm.

[0151] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the seismic profile-guided CPT data hybrid field interpolation algorithm are implemented.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A seismic profile-guided CPT data mixed domain interpolation algorithm, characterized in that: The steps include: Process 2D seismic images to obtain attribute features; Based on the attribute characteristics, the spatial attributes and geological attributes of the points to be interpolated are calculated; Based on spatial attributes and geological attributes, CPT attribute parameters are extracted, and the CPT attribute parameter data are combined and merged with the features; The combined and merged data are sliced ​​horizontally, and the slices are processed along the direction of the 2D seismic data to obtain the horizontal interpolation points and interpolation parameters to form multiple slice data sets; for each slice data set, processing is performed based on the acquired 2D seismic data; In the transverse slice data set, the interpolation model is constructed using the 2D seismic data as the interpolation parameter and the cone tip resistance obtained from the CPT hole position as the interpolation result; Based on the interpolation model, the nearest neighbor interpolation method and the inverse distance interpolation method are used for mixed field interpolation. Combining the nearest neighbor interpolation and the inverse distance weighted interpolation, the influence of spatial attributes and geological attributes is fully considered to achieve smooth and accurate interpolation; and a three-dimensional model is established to form the final interpolation result.

2. The CPT data mixed domain interpolation algorithm according to claim 1, characterized in that: The processing of the two-dimensional seismic image to obtain attribute features specifically includes the following steps: The two-dimensional seismic image is in the segy format file, which is a standard seismic data format used to store and exchange seismic reflection data. Seismic signal data is usually represented as a time series, and the value of each sample point is the amplitude, that is: Amplitude(t)=x(t) (1) Where Amplitude(t) refers to the amplitude of the seismic signal at time t; x(t) is the function of the seismic signal over time, representing the recorded seismic wave signal; Compute phase and envelope characteristics: The calculation of phase and envelope usually uses Hilbert transform, which is a tool in signal processing. Hilbert transform converts a real-valued signal into a complex-valued signal. The real part of the complex-valued signal is the original signal, and the imaginary part is its Hilbert transform. The formula of Hilbert transform is as follows: Where H(x(t)) is the signal after Hilbert transformation in time; x(τ) is the seismic signal value at time τ; t is the current time point; τ is the integral variable, representing all points on the time axis; PV is the principal value integral; Through Hilbert transform, we can get the complex value signal, specifically: z(t)=x(t)+jH(x(t)) (3) Where z(t) is the complex value signal at time t; x(t) is the original seismic signal value at time t; j is the imaginary unit; The instantaneous phase is the phase angle of a complex-valued signal and is expressed as: Where φ(t) is the instantaneous phase at time t; Im(z(t)) is the result of Hilbert transform, which is also the imaginary part of the complex-valued signal at time t; Re(z(t)) is the original seismic signal, which is also the real part of the complex-valued signal at time t; The envelope is the modulus of a complex-valued signal and is calculated as: Where E(t) is the envelope amplitude at time t; |z(t)| is the modulus of the complex-valued signal at time t.

3. The CPT data mixed domain interpolation algorithm according to claim 1, characterized in that: The calculation requires the spatial attributes and geological attributes of the interpolation points, and includes the following steps: When calculating the depth of a point within a layer, the depth needs to be normalized. The formula for calculating normalization is: Where d is the original depth of the point; min is the minimum thickness of the formation, that is, the depth of the top layer of the formation; max is the maximum thickness of the formation, that is, the depth of the bottom layer of the formation; d NORM The value of the normalized depth of the point.

4. The CPT data mixed domain interpolation algorithm according to claim 1, characterized in that: The extraction of CPT attribute parameters and combining and merging CPT attribute parameter data with features specifically includes the following steps: The data of the area where the CPT hole is located is selected as the training data, and the data obtained from the CPT is used as the test data. The parameters of the cone tip resistance are obtained to model and analyze the geological formation. The cone tip resistance q c The calculation formula is: Where, F c is the cone tip penetration force; A c is the cross-sectional area of ​​the cone tip, which is calculated using a standard conical probe using the formula: Where D c is the diameter of the cone tip; Obtain the 2D seismic characteristics of the CPT hole location, including amplitude, phase, and envelope, and combine them with the spatial and geological attributes of the point, and use them together with the cone tip resistance data as a training dataset; The two-dimensional seismic characteristics of the points to be interpolated, including amplitude, phase and envelope, are merged and combined with the spatial attributes and geological attributes of the points, and the overall interpolation results are obtained after the interpolation model is trained.

5. The CPT data mixed domain interpolation algorithm according to claim 1, characterized in that: In the transverse slice data set, the interpolation model is constructed using the two-dimensional seismic data as the interpolation parameter and the cone tip resistance obtained at the CPT hole position as the interpolation result. The interpolation model specifically includes the following steps: The cone tip resistance dataset of the sample points is established as follows: Where, A collection of cone tip resistance data sets for sample points; f1 represents the cone tip resistance of the first sample point; f K Represents the cone tip resistance at the Kth sample point; Its spatial attributes and 2D seismic attributes are established as follows: Among them, x1 represents the spatial attributes of the amplitude, phase, envelope and point of a CPT hole; Solve the diagonal equation, which is as follows: Where D(x) represents the metric tensor field; t(x) refers to the distance from the interpolation point to the nearest sample point x k the time required; Represents points other than sample points, that is, points to be interpolated; Represents the gradient of the function t(x), that is, the spatial rate of change of t(x) at point x; The calculation of the metric tensor field D(x) provides the anisotropy and spatial variation coefficient of the equation. By using the metric tensor field D(x) to measure the characteristic distance, it reflects the influence of geological structure on the characteristic distance, making two points in the same geological structure very close, while two points in different structures are much farther away; Using spatial attributes to calculate t(x), the calculation formula of t(x) is as follows: Where x mainly contains the spatial attributes of the interpolation points and sample points, that is, the spatial position; x k is the spatial attribute of the kth sample point; the formula for calculating t(x) for the sample point is as follows: The nearest neighbor interpolation method is used for the data. For each point to be interpolated, the nearest known data point is found and the value of the known data point is assigned to the point to be interpolated. For known sample points, the cone tip resistance is used as the characteristic value. The inverse distance interpolation method is used for the data. The inverse distance interpolation method makes the closest point have a greater impact on the interpolation result, while the farthest point has a smaller impact on the interpolation result. The calculation formula of the inverse distance interpolation method is: Where q c (x) is the interpolation value of the point to be interpolated; N is the number of sample points that need to be provided nearby.

6. The CPT data mixed domain interpolation algorithm according to claim 1, characterized in that: The formula for the mixed field interpolation is as follows: q c (P)=w NN q c (Q nearest )+w IDW q c (IDW) (15) Where w NN is the weight of the nearest neighbor interpolation; q c (Q nearest ) is the result of nearest neighbor interpolation; w IDW is the weight of inverse distance interpolation, q c (IDW) is the result of inverse distance interpolation; q c (P) is the final interpolation result.

7. A seismic profile guided CPT data mixed field interpolation method, characterized in that: include: A first processing unit is used to process the two-dimensional seismic image to obtain attribute features; The second processing unit is used to calculate the spatial attributes and geological attributes of the points to be interpolated based on the attribute characteristics; The third processing unit is used to extract CPT attribute parameters based on the spatial attributes and geological attributes, and to combine and merge the CPT attribute parameter data with the features; a fourth processing unit for performing transverse slicing on the combined and merged data, processing the slices along the direction indicated by the two-dimensional seismic data, obtaining transverse interpolation points and interpolation parameters, and forming multiple slice data sets; processing each slice data set based on the acquired two-dimensional seismic data, including analyzing and extracting seismic features in the slice data; The fifth processing unit is used to construct an interpolation model in the transverse slice data set using the two-dimensional seismic data as the interpolation parameter and the cone tip resistance obtained at the CPT hole position as the interpolation result; The sixth processing unit is used to perform mixed field interpolation based on the interpolation model using the nearest neighbor interpolation method and the inverse distance interpolation method, combining the nearest neighbor interpolation and the inverse distance weighted interpolation, fully considering the influence of spatial attributes and geological attributes, and achieving smooth and accurate interpolation.

8. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the seismic profile-guided CPT data hybrid field interpolation algorithm steps described in any one of claims 1 to 6 are implemented.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the seismic profile-guided CPT data mixed field interpolation algorithm steps described in any one of claims 1-6 are implemented.

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