Three-dimensional refined imaging system and method based on borehole geological radar technology

Abstract

The invention relates to the technical field of geological exploration, in particular to a three-dimensional refined imaging system based on a borehole geological radar technology, which comprises a radar probe group. A signal receiving and processing module; a data fusion and three-dimensional reconstruction module; a positioning and calibration module; a visual display platform; the imaging method comprises the following steps: drilling holes and deploying a probe; collecting and preprocessing data; performing data fusion and three-dimensional reconstruction; performing three-dimensional refined imaging; and performing visual display. The invention provides a three-dimensional refined imaging system and method based on a borehole geological radar technology, and is used for solving the problem of limitation of complex geology in imaging precision and three-dimensional visualization direction.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to a three-dimensional fine imaging system and method based on borehole geological radar technology. Background Art

[0002] Geological exploration is widely used in the fields of mineral resource exploration, groundwater resource investigation, engineering construction, etc. Traditional geological exploration methods, such as drilling and seismic survey, often face problems such as low accuracy, high cost, and slow exploration speed. As a non-destructive detection method, borehole geological radar technology can obtain geological information at different depths underground in real time by deploying radar probes in boreholes. However, existing technologies have certain limitations in imaging accuracy and three-dimensional visualization, and cannot meet the needs of high-precision and high-resolution imaging under complex geological conditions.

[0003] Therefore, designing a three-dimensional refined imaging system and method based on borehole geological radar technology can improve imaging accuracy, reduce errors, and provide more intuitive and accurate underground geological structure images, which is of great significance for geological exploration and engineering applications. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a three-dimensional refined imaging system and method based on borehole geological radar technology, which is used to solve the limitations of complex geology in imaging accuracy and three-dimensional visualization.

[0005] This application discloses a three-dimensional fine-grained imaging system based on borehole geological radar technology, and the technical solution includes:

[0006] Radar probe set:

[0007] The radar probe group is composed of multiple groups of radar probes set in the borehole, and adopts a high-resolution radar signal transmitting and receiving device with adjustable frequency, which can scan at different depths and azimuths;

[0008] Signal receiving and processing module:

[0009] The signal returned by the radar probe group is received, and external interference is removed and useful geological information is extracted through processing methods such as filtering, gain adjustment, and denoising. The signal is processed by time-frequency analysis, waveform inversion and other technical methods to accurately calculate the velocity and dielectric constant of the underground reflection layer.

[0010] Data fusion and 3D reconstruction module:

[0011] The data processed by the signal receiving and processing module are integrated, and the geological data collected at different depths and orientations are converted into three-dimensional images through a three-dimensional reconstruction algorithm;

[0012] Positioning and calibration module:

[0013] The radar probe group is equipped with a precise positioning system (using drilling data, ground sensors, and GNSS positioning technology) to ensure the accurate position and depth of the radar probe in the borehole, and calibrate the imaging results to improve the precision and accuracy of imaging.

[0014] Preferably, it also includes a visualization display platform, which is used to display the three-dimensionally reconstructed geological structure image, and facilitates operators to perform intuitive analysis through multi-angle rotation and zoom-in and zoom-out interactions.

[0015] Preferably, the present application also discloses a three-dimensional fine-grained imaging method based on borehole geological radar technology, comprising the following steps:

[0016] Step S1, drilling and probe deployment:

[0017] Drill holes of a certain depth in the target area, and arrange radar probes at different depths and orientations according to design requirements to obtain underground detection data at different angles;

[0018] Step S2, data collection and preprocessing:

[0019] The radar probe is used to transmit electromagnetic waves and receive reflected signals, collect echo data from the underground reflection layer, and perform pre-processing such as noise suppression and gain adjustment on the collected data to ensure signal quality.

[0020] Step S3: Data fusion and 3D reconstruction:

[0021] Based on the radar data at different depths and orientations, the 3D reconstruction algorithm is used to reconstruct and fuse the data to obtain a preliminary 3D image of the underground structure.

[0022] Step S4: Three-dimensional fine-tuning imaging:

[0023] Based on the velocity and dielectric constant of the underground reflector, the waveform inversion technology is used to refine the three-dimensional imaging, reduce errors and improve imaging accuracy;

[0024] Step S5: Visual display:

[0025] The processed 3D imaging data is converted into visual images, and a variety of display modes are provided according to needs, including but not limited to stereograms, slice diagrams, etc.

[0026] Preferably, in step S3, deep learning or pattern recognition technology is used to optimize the spatial distribution of data and the characteristics of the reflection layer.

[0027] Technical effects and advantages of the present invention:

[0028] 1. Through multi-angle and multi-depth radar data collection and three-dimensional fine reconstruction, the imaging accuracy is significantly improved, and the complex underground geological structure can be effectively identified. With the operation of fine imaging, the accuracy and resolution of underground imaging are higher.

[0029] 2. The borehole geological radar technology is used, which does not need to destroy the ground structure and can conduct underground exploration safely and non-destructively. It is suitable for various complex geological environments and is non-destructive and highly adaptable. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of the composition of a three-dimensional fine imaging system based on borehole geological radar technology provided in an embodiment of the present application;

[0031] Figure 2 This is a flow chart of a three-dimensional refined imaging method based on borehole geological radar technology provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0033] Example 1

[0034] See also Figure 1 In this embodiment, a three-dimensional fine-grained imaging system based on borehole geological radar technology is provided, including:

[0035] Radar probe set:

[0036] The radar probe group is composed of multiple groups of radar probes set in the borehole, and adopts a high-resolution radar signal transmitting and receiving device with adjustable frequency, which can scan at different depths and azimuths;

[0037] Among them, the radar probe may include multiple small radar arrays, supporting multi-angle scanning and multi-depth detection, and optimizing data collection accuracy.

[0038] Signal receiving and processing module:

[0039] Receive the signal returned by the radar probe group, remove external interference through filtering, gain adjustment, denoising and other processing methods, and extract useful geological information;

[0040] Among them, the signal is processed by time-frequency analysis, waveform inversion and other technical methods to accurately calculate the velocity and dielectric constant of the underground reflection layer.

[0041] Data fusion and 3D reconstruction module:

[0042] The data processed by the signal receiving and processing module are integrated, and the geological data collected at different depths and orientations are converted into three-dimensional images through a three-dimensional reconstruction algorithm;

[0043] Among them, the three-dimensional reconstruction algorithm includes but is not limited to the voxel method, surface fitting algorithm, deep learning algorithm, etc., which uses the fusion of geological structure model and underground detection data to provide more accurate three-dimensional imaging results.

[0044] Positioning and calibration module:

[0045] The radar probe group is equipped with a precise positioning system (using drilling data, ground sensors, and GNSS positioning technology) to ensure the accurate position and depth of the radar probe in the borehole, and calibrate the imaging results to improve the precision and accuracy of imaging.

[0046] Visual display platform:

[0047] The visualization display platform is used to display the three-dimensionally reconstructed geological structure image, and facilitates operators to perform intuitive analysis through multi-angle rotation and zoom-in and zoom-out interactions.

[0048] Example 2

[0049] The present application discloses a three-dimensional fine-grained imaging method based on borehole geological radar technology, comprising the following steps:

[0050] Step S1, drilling and probe deployment:

[0051] Drill holes of a certain depth in the target area, and arrange radar probes at different depths and orientations according to design requirements to obtain underground detection data at different angles;

[0052] Step S2, data collection and preprocessing:

[0053] The radar probe is used to transmit electromagnetic waves and receive reflected signals, collect echo data from the underground reflection layer, and perform pre-processing such as noise suppression and gain adjustment on the collected data to ensure signal quality.

[0054] The original echo signal is obtained from the borehole radar probe. Usually, the radar probe collects multiple sets of data at different angles and depths. The above data is physically two-dimensional. In practical applications, it needs to be converted into a three-dimensional structural image. The steps for preprocessing the data include:

[0055] S2.1 De-noising: Remove noise from the original echo signal and use algorithms such as wavelet transform or mean filtering to process high-frequency noise in the signal.

[0056] S2.2 Time-frequency analysis: Use time-frequency analysis methods (such as short-time Fourier transform STFT) to perform joint analysis of the radar echo signal in the time domain and frequency domain to extract the dielectric constant information at different depths.

[0057] S2.3 Gain and correction: Based on the characteristics of signal attenuation during radar wave propagation, a gain adjustment algorithm (such as automatic gain control AGC) is applied to correct the echo signal to compensate for the signal loss during the propagation process.

[0058] Step S3: Data fusion and 3D reconstruction:

[0059] Based on the radar data at different depths and orientations, the 3D reconstruction algorithm is used to reconstruct and fuse the data to obtain a preliminary 3D image of the underground structure. The specific steps include:

[0060] S3.1 Coordinate transformation:

[0061] Since the position and orientation of the borehole radar probe in the borehole are known, it is necessary to convert the two-dimensional radar data into relative position coordinates in three-dimensional space. Because radar echo data is usually collected in a direction perpendicular to the borehole, in order to effectively synthesize these data into a three-dimensional image, it is necessary to use the borehole position and depth information for coordinate conversion.

[0062] The coordinate transformation formula is as follows:

[0063] x'=x0+△x

[0064] y'=y0+△y

[0065] z'=z0+△z

[0066] Among them, △x, △y, and △z represent the offset of the radar probe in the borehole relative to the original coordinate system.

[0067] S3.2 Data interpolation and reconstruction:

[0068] In multiple scans, radar data is presented as a discrete set of points, and interpolation algorithms are usually required to convert these discrete points into continuous three-dimensional spatial data.

[0069] In this scheme, the voxel reconstruction algorithm is used to divide the underground structure into small cubes (voxels) in three-dimensional space, and then the reflection intensity of each voxel is calculated based on radar data to fill and reconstruct the three-dimensional space. The formula is as follows:

[0070]

[0071] Where f(x, y, z) is the reconstructed reflection intensity value, R i (x, y, z) is the radar echo reflection value, w i The weight for each radar detection point.

[0072] S3.3 Inversion of reflected wave velocity and dielectric constant:

[0073] The propagation characteristics of the echo signal and the electromagnetic characteristics of the underground medium are used to invert the underground dielectric constant and wave velocity information using tomography or reflection wave method.

[0074] Among them, the tomography method is based on the time difference analysis of radar signals, and uses the tomography algorithm to invert the dielectric constant and wave velocity of different underground layers. The reflection wave method estimates the dielectric constant of the underground medium by calculating the propagation speed of different reflection layers and combining the echo time and reflection depth.

[0075] S3.4 3D data fusion and deep learning optimization:

[0076] Data fusion technology is used to comprehensively process the data obtained from multiple scans, thereby processing radar data at different depths and locations.

[0077] The radar data at different depths are weighted averaged to ensure the relative relationship between depth information and spatial position. The formula is as follows:

[0078]

[0079] Among them, D i (x, y, z) is the data of the i-th scan, w i is a weighting factor, which is usually set according to the scanning depth, data quality and signal-to-noise ratio.

[0080] In addition, deep learning optimization algorithms can be used to perform data fusion optimization using convolutional neural networks (CNN) or generative adversarial networks (GAN), and the characteristics of underground structures can be automatically identified through training models to reduce human interference and errors.

[0081] Among them, the CNN structure needs to input the two-dimensional data of the radar signal, extract the underground features through multi-layer convolution and pooling operations, and then map it to the three-dimensional space through the fully connected layer.

[0082] The GAN model optimizes radar data through a generative adversarial network, trains the generator to generate high-quality three-dimensional underground images, and uses the discriminator to evaluate the generated images to help optimize the data fusion and reconstruction process.

[0083] Step S4: 3D fine-tuning imaging:

[0084] Based on the velocity and dielectric constant of the underground reflector, waveform inversion technology is used to refine three-dimensional imaging, reduce errors and improve imaging accuracy.

[0085] Since borehole radar scanning involves a lot of data processing and spatial interpolation, certain errors may occur.

[0086] To this end, the following methods are used to further optimize the accuracy:

[0087] S4.1 Geological model correction: According to the existing geological model, the imaging results are corrected to eliminate the errors caused by the propagation characteristics of the radar signal and the irregularities of the reflection layer.

[0088] S4.2 Multi-source data fusion: Combine borehole sampling data, ground exploration data, seismic data, etc. to perform data fusion, and improve the accuracy of imaging through cross-validation of multi-source information.

[0089] Step S5: Visual display:

[0090] After the above data processing, reconstruction and optimization, a 3D underground structure image will be generated and presented to the user. The processed 3D imaging data is converted into a visual image, and a variety of display modes are provided according to needs, including but not limited to stereograms, slices, etc.

[0091] The radar scan data and 3D imaging results are displayed through a real-time graphical interface, supporting users to conduct rapid post-analysis. The slice display allows users to view underground structures through slices at different depths.

[0092] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A three-dimensional fine-grained imaging system based on borehole geological radar technology, characterized in that: include: Radar probe group: The radar probe group is composed of multiple groups of radar probes set in the borehole, and adopts a high-resolution radar signal transmitting and receiving device with adjustable frequency to scan at different depths and azimuths; Signal receiving and processing module: used to receive the signal returned by the radar probe group and remove external interference through filtering, gain adjustment and denoising. Data fusion and 3D reconstruction module: fuses the data processed by the signal receiving and processing module, and converts the geological data collected at different depths and directions into 3D images through the 3D reconstruction algorithm; Positioning and calibration module: The radar probe group is equipped with a precise positioning system to ensure the accurate position and depth of the radar probe in the borehole and calibrate the imaging results.

2. The three-dimensional fine-grained imaging system based on borehole geological radar technology according to claim 1 is characterized in that: The radar probe group includes multiple small radar arrays, supports multi-angle scanning and multi-depth detection, and optimizes data collection accuracy.

3. The three-dimensional fine-grained imaging system based on borehole geological radar technology according to claim 2 is characterized in that: The signal receiving and processing module is used to perform time-frequency analysis, waveform inversion and other technical processing on the signal, and accurately calculate the velocity and dielectric constant of the underground reflection layer.

4. The three-dimensional fine-grained imaging system based on borehole geological radar technology according to claim 3 is characterized in that: The three-dimensional reconstruction algorithm includes processing by means of voxel method, surface fitting algorithm, and deep learning algorithm, and fusing the geological structure model with underground detection data.

5. The three-dimensional fine-grained imaging system based on borehole geological radar technology according to claim 4 is characterized in that: The system also includes a visualization display platform, which is used to display the three-dimensionally reconstructed geological structure image and provide an interactive mode of multi-angle rotation and zooming in and out.

6. An imaging method of a three-dimensional fine imaging system based on borehole geological radar technology according to any one of claims 1 to 5, characterized in that: The following steps are involved: Step S1, drilling and probe deployment: drilling a borehole of a certain depth in the target area, and arranging the radar probes at different depths and orientations according to the design requirements to obtain underground detection data at different angles; Step S2, data collection and preprocessing: using a radar probe to transmit electromagnetic waves and receive reflected signals, collecting echo data of the underground reflection layer, and preprocessing the collected data; Step S3, data fusion and 3D reconstruction: Reconstruct and fuse the radar data at different depths and orientations using a 3D reconstruction algorithm to obtain a preliminary 3D image of the underground structure; Step S4, three-dimensional fine imaging: based on the velocity and dielectric constant of the underground reflection layer, the three-dimensional imaging is refined by waveform inversion technology to reduce errors and improve imaging accuracy; Step S5: Visual display: convert the processed three-dimensional imaging data into a visual image and provide a variety of display modes according to needs.

7. The three-dimensional fine-grained imaging method based on borehole geological radar technology according to claim 6 is characterized in that: The step of preprocessing the data in step S2 specifically includes: S2.1 De-noising: remove noise from the original echo signal and use algorithms such as wavelet transform or mean filtering to process high-frequency noise in the signal; S2.2 Time-frequency analysis: Use the time-frequency analysis method to perform joint analysis of the radar echo signal in the time domain and frequency domain to extract the dielectric constant information at different depths; S2.3 Gain and correction: Based on the characteristics of signal attenuation during radar wave propagation, the gain adjustment algorithm is applied to correct the echo signal to compensate for the signal loss during the propagation process.

8. The three-dimensional fine-grained imaging method based on borehole geological radar technology according to claim 6 is characterized in that: The specific steps in step S3 include: S3.1 Coordinate conversion: Convert the two-dimensional radar data into relative position coordinates in three-dimensional space, and use the location and depth information of the drill hole for coordinate conversion. S3.2 Data interpolation and reconstruction: In multiple scans, radar data is presented as a discrete set of points. The voxel reconstruction algorithm is used to convert these discrete points into continuous three-dimensional spatial data. The reflection intensity of each voxel is calculated based on the radar data to fill and reconstruct the three-dimensional space. S3.3 Inversion of reflected wave velocity and dielectric constant: Utilizing the propagation characteristics of the echo signal and the electromagnetic characteristics of the underground medium, tomography or reflection wave method is used to invert the underground dielectric constant and wave velocity information. S3.4 Three-dimensional data fusion and deep learning optimization: Data fusion technology is used to comprehensively process the data obtained from multiple scans, thereby processing radar data at different depths and different locations.

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