A multi-source dynamic survey method and system for urban underground space

Abstract

The present invention relates to a method and system for dynamic survey of multiple sources in urban underground space. The method comprises constructing a convolution model of urban underground space, performing numerical simulation based on collected basic data, generating a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space, and judging whether the conditions for conducting multi-source time-lapse survey are met; calibrating monitoring positions when the conditions for conducting multi-source time-lapse survey are met, repeatedly collecting urban underground space data at preset intervals, and generating survey line information; performing consistency processing on the survey line information to obtain difference information and perform mutual equalization processing; determining the deformation of the rock and soil body and fluid information of the urban underground space, and performing dynamic prediction of the urban underground space. The present invention first performs a feasibility analysis, then calibrates the monitoring positions and repeatedly samples, performs consistency processing to obtain difference information, so as to determine the deformation of the rock and soil body and fluid information of the urban underground space, thereby realizing dynamic survey and management of complex urban underground space bodies.

Description

Technical Field

[0001] The present invention relates to the technical field of urban underground space surveying, and in particular to a multi-source dynamic surveying method and system for urban underground space. Background Art

[0002] At present, the main methods for urban underground space survey are either passive sources (natural fields) or active sources (artificially stimulated fields), and they are all static survey methods (one-time survey). The survey results reflect the state of the underground rock and soil at that time, and cannot describe the changing characteristics of the underground space, such as the changes in the geometric shape and properties of the geological body after disturbance by engineering activities. It is impossible to dynamically monitor the changes in the underground rock and soil with high precision. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and system for dynamic survey of urban underground space using multiple sources in response to the above-mentioned deficiencies in the prior art.

[0004] The present invention solves the above-mentioned technical problem with the following technical solution: A method for dynamic survey of urban underground space using multiple sources, comprising the following steps:

[0005] S1: Construct a convolution model of the urban underground space, perform numerical simulation based on the collected basic data, generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space, and determine whether the conditions for conducting multi-source time-lapse survey are met;

[0006] S2: When conditions are met for conducting multi-source time-lapse surveys, the monitoring locations are calibrated, urban underground space data are repeatedly collected at preset intervals, and survey line information is generated;

[0007] S3: performing consistency processing on the survey line information according to a multi-source time-lapse survey formula to obtain difference information, and performing mutual averaging processing on the difference information;

[0008] S4: Determine the rock and soil deformation and fluid information of the urban underground space based on the difference information, and perform dynamic prediction of the urban underground space.

[0009] The beneficial effects of the present invention are: the multi-source dynamic survey method of urban underground space of the present invention constructs a convolution model of urban underground space and performs numerical simulation based on basic data to construct a basic data table for feasibility analysis of multi-source time-lapse survey to perform feasibility analysis of multi-source time-lapse survey, and when the feasibility meets the requirements, the monitoring position is calibrated and repeated sampling is performed to perform consistency processing to obtain difference information, and the difference data is comprehensively analyzed to determine the deformation of the rock and soil body and fluid information of the urban underground space, thereby realizing dynamic survey and management of complex urban underground space bodies, avoiding the multi-solution nature of a single single-source method, and improving the accuracy of the survey results.

[0010] On the basis of the above technical solution, the present invention can also be improved as follows:

[0011] Further: In S1, constructing the urban underground space convolution model and performing numerical simulation based on the collected basic data to generate a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space specifically includes the following steps:

[0012] S11: Constructing a convolution model of urban underground space:

[0013] J(t)=g(t)*d(t)*w(t)

[0014] Where g(t) represents the urban underground engineering system, d(t) represents the geological internal force system, w(t) represents the geological external force system, and J(t) represents the total output of the interaction between the urban underground engineering system g(t), the geological internal force system d(t), and the geological external force system w(t).

[0015] S12: Input the collected basic data into the urban underground space convolution model, perform calculations, obtain urban underground space data, and construct a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space.

[0016] The beneficial effect of the above further scheme is: by constructing the urban underground space convolution model, numerical simulation can be performed based on the collected basic data, thereby obtaining a basic data table for feasibility analysis of multi-source time-lapse survey of underground space, so as to facilitate subsequent accurate analysis of whether the conditions for carrying out multi-source time-lapse survey are met based on the basic data table for feasibility analysis of multi-source time-lapse survey of underground space.

[0017] Further: In S1, the step of determining whether the conditions for conducting multi-source time-lapse survey are met specifically includes the following steps:

[0018] S13: Reading an imaging quality index and a repeatability index according to the basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space, and if both the imaging quality index and the repeatability index meet corresponding preset standards, proceeding to S14; otherwise, determining that the conditions for conducting multi-source time-lapse survey are not met;

[0019] S14: determining an influencing factor of each feasibility indicator according to a plurality of feasibility indicators in the engineering system, the geological internal force system, and the geological external force system and corresponding preset standards;

[0020] S15: A feasibility index is calculated based on the influencing factors of the feasibility indicators, and when the feasibility index is greater than or equal to a preset feasibility index threshold, it is determined that the conditions for conducting multi-source time-lapse survey are met; otherwise, it is determined that the conditions for conducting multi-source time-lapse survey are not met.

[0021] The beneficial effect of the above further scheme is: by reading the imaging quality index and repeatability index, and judging whether the read imaging quality index and repeatability index meet the corresponding preset standards, it is possible to ensure that the imaging quality index and repeatability index meet the preset standards, thereby conducting multiple feasibility index analyses in the engineering system, geological internal force system and geological external force system, thereby ensuring the accuracy of the analysis results.

[0022] Further: in S3, performing consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and performing mutual averaging processing on the difference information includes the following steps:

[0023] S31: Read the survey line information received in the area where the urban underground engineering system is located, and perform root mean square amplitude correction processing on the survey line information. The correction operator is:

[0024] Amp=A1 / A2

[0025] Among them, A1 and A2 are the maximum RMS amplitudes of the basic survey line signal and the survey line signal in the time window respectively;

[0026] S32: Perform cross-correlation delay correction on the survey line signals collected above the area where the urban underground engineering system is located. The calculation formula is as follows:

[0027] J1(t)=S(t)+N1(t)

[0028] J2(t)=α*S(t-Td)+N2(t)

[0029] Where S(t) is the expected signal above the area where the urban underground engineering system is located, N1(t) and N2(t) are Gaussian white noise, Td is the delay time, α is the attenuation coefficient, J1(t) and J2(t) are the basic survey line signal and the survey line signal above the area where the urban underground engineering system is located, respectively. The cross-correlation function of J1(t) and J2(t) is:

[0030] R J1 J2 (τ) = E{J1(t)J2(t+τ)}

[0031] S33: Using the base survey line signal as a reference, performing phase rotation on the survey line signal above the area where the urban underground engineering system is located, selecting a phase angle corresponding to a maximum similarity coefficient between the base survey line signal and the survey line signal, and performing phase rotation on the survey record signal using the phase angle;

[0032] S34: Calculate the convolution filter factor for the survey line signal and perform matched filtering. The calculation formula is:

[0033] r=F*J1-J2

[0034] Where F is the convolution filter factor, J1 and J2 represent the traces above the target layer in the time window, and r is the preset variable that is minimized in the least squares sense.

[0035] The beneficial effect of the above further scheme is: by combining the basic survey line information with the survey line information and sequentially performing root mean square correction processing, cross-correlation delay correction processing, phase correction and matched filtering processing, the amplitude, time, phase and frequency of the basic survey line information can be corrected to be consistent with the basic survey line, and then the obtained correction operator is applied to the survey line information, thereby achieving consistency processing of the survey line information and accurately obtaining difference information.

[0036] The present invention also provides a multi-source dynamic survey system for urban underground space, comprising a feasibility analysis module, a positioning acquisition module, a difference information module and a prediction module;

[0037] The feasibility analysis module is used to construct a convolution model of the urban underground space, perform numerical simulation based on the collected basic data, generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space, and determine whether the conditions for conducting multi-source time-lapse survey are met;

[0038] The positioning and acquisition module is used to calibrate the monitoring position when the conditions for carrying out multi-source time-lapse survey are met, repeatedly collect urban underground space data at preset intervals, and generate survey line information;

[0039] The difference information module is used to perform consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and perform mutual averaging processing on the difference information;

[0040] The prediction module is used to determine the rock and soil deformation and fluid information of the urban underground space based on the difference information, and to perform dynamic prediction of the urban underground space.

[0041] The multi-source dynamic survey system for urban underground space of the present invention constructs a convolution model of urban underground space and performs numerical simulation based on basic data to construct a basic data table for feasibility analysis of multi-source time-lapse survey to perform feasibility analysis of multi-source time-lapse survey. When the feasibility meets the requirements, the monitoring position is calibrated and repeated sampling is performed to perform consistency processing to obtain difference information, and the difference data is comprehensively analyzed to determine the deformation of the rock and soil body and fluid information of the urban underground space, thereby realizing dynamic survey and management of complex urban underground space bodies, avoiding the multi-solution nature of a single single-source method, and improving the accuracy of the survey results.

[0042] On the basis of the above technical solution, the present invention can also be improved as follows:

[0043] Further: The feasibility analysis module constructs a convolution model of the urban underground space and performs numerical simulation based on the collected basic data to generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space. The specific implementation is:

[0044] Constructing a convolution model of urban underground space:

[0045] J(t)=g(t)*d(t)*w(t)

[0046] Where g(t) represents the urban underground engineering system, d(t) represents the geological internal force system, w(t) represents the geological external force system, and J(t) represents the total output of the interaction between the urban underground engineering system g(t), the geological internal force system d(t), and the geological external force system w(t).

[0047] The collected basic data is input into the urban underground space convolution model and calculated to obtain urban underground space data, and a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space is constructed.

[0048] The beneficial effect of the above further scheme is: by constructing the urban underground space convolution model, numerical simulation can be performed based on the collected basic data, thereby obtaining a basic data table for feasibility analysis of multi-source time-lapse survey of underground space, so as to facilitate subsequent accurate analysis of whether the conditions for carrying out multi-source time-lapse survey are met based on the basic data table for feasibility analysis of multi-source time-lapse survey of underground space.

[0049] Further: The feasibility analysis module determines whether the conditions for carrying out multi-source time-lapse survey are met in the following specific implementations:

[0050] Reading the imaging quality index and the repeatability index according to the basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space, and determining that the conditions for conducting multi-source time-lapse survey are not met when the imaging quality index and / or the repeatability index do not meet the corresponding preset standards;

[0051] otherwise;

[0052] Determining the influencing factors of the feasibility indicators in the engineering system, the geological internal force system and the geological external force system respectively according to the plurality of feasibility indicators and the corresponding preset standards;

[0053] A feasibility index is calculated based on the influencing factors of each of the feasibility indicators, and when the feasibility index is greater than or equal to a preset feasibility index threshold, it is determined that the conditions for conducting multi-source time-lapse survey are met; otherwise, it is determined that the conditions for conducting multi-source time-lapse survey are not met.

[0054] The beneficial effect of the above further scheme is: by reading the imaging quality index and repeatability index, and judging whether the read imaging quality index and repeatability index meet the corresponding preset standards, it is possible to ensure that the imaging quality index and repeatability index meet the preset standards, thereby conducting multiple feasibility index analyses in the engineering system, geological internal force system and geological external force system, thereby ensuring the accuracy of the analysis results.

[0055] Further: the difference information module performs consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and the specific implementation of performing mutual averaging processing on the difference information is:

[0056] The survey line information received in the area where the urban underground engineering system is located is read, and the root mean square amplitude correction processing is performed on the survey line information. The correction operator is:

[0057] Amp=A1 / A2

[0058] Among them, A1 and A2 are the maximum RMS amplitudes of the basic survey line signal and the survey line signal in the time window respectively;

[0059] The cross-correlation delay correction is performed on the survey line signals collected above the area where the urban underground engineering system is located. The calculation formula is as follows:

[0060] J1(t)=S(t)+N1(t)

[0061] J2(t)=α*S(t-Td)+N2(t)

[0062] Where S(t) is the expected signal above the area where the urban underground engineering system is located, N1(t) and N2(t) are Gaussian white noise, Td is the delay time, α is the attenuation coefficient, J1(t) and J2(t) are the basic survey line signal and the survey line signal above the area where the urban underground engineering system is located, respectively. The cross-correlation function of J1(t) and J2(t) is:

[0063] R J1 J2 (τ) = E{J1(t)J2(t+τ)}

[0064] Taking the basic survey line signal as a reference, performing phase rotation on the survey line signal above the area where the urban underground engineering system is located, selecting the phase angle corresponding to the maximum similarity coefficient between the basic survey line signal and the survey line signal, and performing phase rotation on the survey record signal at the phase angle;

[0065] The convolution filter factor is solved for the survey line signal and matched filtering is performed. The calculation formula is:

[0066] r=F*J1-J2

[0067] Where F is the convolution filter factor, J1 and J2 represent the traces above the target layer in the time window, and r is the preset variable that is minimized in the least squares sense.

[0068] The beneficial effect of the above further scheme is: by combining the basic survey line information with the survey line information and sequentially performing root mean square correction processing, cross-correlation delay correction processing, phase correction and matched filtering processing, the amplitude, time, phase and frequency of the basic survey line information can be corrected to be consistent with the basic survey line, and then the obtained correction operator is applied to the survey line information, thereby achieving consistency processing of the survey line information and accurately obtaining difference information.

[0069] The present invention also provides a computer-readable storage medium, which stores computer instructions. The computer instructions are used to enable a processor to implement the multi-field source dynamic survey method for urban underground space when executed.

[0070] The present invention also provides a multi-source dynamic survey device for urban underground space, characterized in that the multi-source dynamic survey device for urban underground space comprises:

[0071] at least one processor and a storage medium, wherein the storage medium is communicatively connected to the processor;

[0072] In which, the storage medium stores a computer program that can be executed by at least one of the processors, and the computer program is executed by the at least one processor so that the at least one processor can execute the multi-field source dynamic survey method for urban underground space. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 Schematic diagram of the process of a multi-source dynamic survey method for urban underground space according to an embodiment of the present invention;

[0074] Figure 2 A schematic diagram of qualitative surface stratum attribute change trends and development rules determined through time-lapse survey according to an embodiment of the present invention;

[0075] Figure 3 This is a schematic diagram of quantitatively characterizing fluid saturation and ground stress changes using time-lapse survey data combined with drilling data according to an embodiment of the present invention;

[0076] Figure 4 Schematic diagram of the structure of a multi-source dynamic survey system for urban underground space according to an embodiment of the present invention. DETAILED DESCRIPTION

[0077] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0078] like Figure 1 As shown, a multi-source dynamic survey method for urban underground space includes the following steps:

[0079] S1: Construct a convolution model of the urban underground space, perform numerical simulation based on the collected basic data, generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space, and determine whether the conditions for conducting multi-source time-lapse survey are met;

[0080] S2: When conditions are met for conducting multi-source time-lapse surveys, the monitoring locations are calibrated, urban underground space data are repeatedly collected at preset intervals, and survey line information is generated;

[0081] S3: performing consistency processing on the survey line information according to a multi-source time-lapse survey formula to obtain difference information, and performing mutual averaging processing on the difference information;

[0082] S4: Determine the rock and soil deformation and fluid information of the urban underground space based on the difference information, and perform dynamic prediction of the urban underground space.

[0083] The multi-source dynamic survey method for urban underground space of the present invention constructs a convolution model of urban underground space and performs numerical simulation based on basic data to construct a basic data table for feasibility analysis of multi-source time-lapse survey to perform feasibility analysis of multi-source time-lapse survey. When the feasibility meets the requirements, the monitoring position is calibrated and repeated sampling is performed to perform consistency processing to obtain difference information, and the difference data is comprehensively analyzed to determine the deformation of the rock and soil body and fluid information of the urban underground space, thereby realizing dynamic survey and management of complex urban underground space bodies, avoiding the multi-solution nature of a single single-source method, and improving the accuracy of the survey results.

[0084] In one or more embodiments of the present invention, constructing a convolution model of an urban underground space and performing numerical simulation based on collected basic data to generate a basic data table for feasibility analysis of multi-source time-lapse survey of an urban underground space specifically includes the following steps:

[0085] S11: Constructing a convolution model of urban underground space:

[0086] J(t)=g(t)*d(t)*w(t)

[0087] Where g(t) represents the urban underground engineering system, d(t) represents the geological internal force system, w(t) represents the geological external force system, and J(t) represents the total output of the interaction between the urban underground engineering system g(t), the geological internal force system d(t), and the geological external force system w(t).

[0088] It should be pointed out that the urban underground engineering system g(t), the geological internal force system d(t) and the geological external force system w(t) influence and interact with each other. For the convenience of calculation, they are simplified into a linear cumulative response system. The urban underground engineering system g(t) is related to factors such as the scale, spatial distribution (point-like, strip-like), and burial depth of the project (bridge, tunnel, foundation pit, underground cavern). The geological internal force system d(t) is related to factors such as tectonic movement, earthquake events, rock and soil properties, underground fluids (water, oil, gas), ground stress, latitude, and altitude. The geological external force system w(t) is related to factors such as wind, atmospheric precipitation (ice and snow), rivers, lakes, and seas, climate, human activities (blasting vibration), external (celestial body) impacts, and landslides.

[0089] S12: Input the collected basic data into the urban underground space convolution model, perform calculations, obtain urban underground space data, and construct a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space.

[0090] Here, a new convolution model is used to carry out numerical simulations of rock and air replacement, surrounding rock and structure integration, and fracture combination, analyze the changes in the physical field under different urban underground space conditions, and calculate various feasibility assessment factors to evaluate the feasibility of multi-source time-lapse survey technology.

[0091] The basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space is shown in Table 1 below:

[0092] Table 1

[0093]

[0094]

[0095] By constructing the urban underground space convolution model, numerical simulation can be performed based on the collected basic data, thereby obtaining a basic data table for feasibility analysis of multi-source time-lapse survey of underground space, so as to facilitate subsequent accurate analysis of whether the conditions for carrying out multi-source time-lapse survey are met based on the basic data table for feasibility analysis of multi-source time-lapse survey of underground space.

[0096] In one or more embodiments of the present invention, in S1, determining whether the conditions for performing multi-source time-lapse survey are met specifically includes the following steps:

[0097] S13: Reading an imaging quality index and a repeatability index according to the basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space, and if both the imaging quality index and the repeatability index meet corresponding preset standards, proceeding to S14; otherwise, determining that the conditions for conducting multi-source time-lapse survey are not met;

[0098] S14: determining an influencing factor of each feasibility indicator according to a plurality of feasibility indicators in the engineering system, the geological internal force system, and the geological external force system and corresponding preset standards;

[0099] S15: A feasibility index is calculated based on the influencing factors of the feasibility indicators, and when the feasibility index is greater than or equal to a preset feasibility index threshold, it is determined that the conditions for conducting multi-source time-lapse survey are met; otherwise, it is determined that the conditions for conducting multi-source time-lapse survey are not met.

[0100] By reading the imaging quality index and repeatability index, and judging whether the read imaging quality index and repeatability index meet the corresponding preset standards, it is possible to conduct multiple feasibility index analyses in the engineering system, geological internal force system and geological external force system on the premise that the imaging quality index and repeatability index meet the preset standards, thereby ensuring the accuracy of the analysis results.

[0101] Here, the feasibility index is calculated based on the preset influencing factors (the weight of each item in this embodiment is preferably 0.1), and when the feasibility index is greater than the preset feasibility index threshold of 1.2, it is determined that the conditions for carrying out multi-source time-lapse survey are met; otherwise, it is determined that the conditions for carrying out multi-source time-lapse survey are not met.

[0102] In this embodiment of the present invention, in step S2, to improve the repeatability of data acquisition, a fixed survey network is used, fixed monitoring locations are calibrated, and identical acquisition parameters, multi-source sensors, and recording equipment are used. Urban underground space data is collected at regular intervals and output in SEGD format. Furthermore, during this repetitive acquisition, a novel urban underground space convolution model is utilized for numerical simulation and acquisition parameter verification.

[0103] In one or more embodiments of the present invention, in S3, performing consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and performing mutual averaging processing on the difference information includes the following steps:

[0104] S31: Read the survey line information received in the area where the urban underground engineering system is located, and perform root mean square amplitude correction processing on the survey line information. The correction operator is:

[0105] Amp=A1 / A2

[0106] Among them, A1 and A2 are the maximum RMS amplitudes of the basic survey line signal and the survey line signal in the time window respectively;

[0107] The purpose of the RMS amplitude correction processing is to make the energy of the two received signals consistent. The correction operator can be time-varying or a unified correction operator can be used. In this embodiment, a unified correction operator Amp is used.

[0108] S32: Perform cross-correlation delay correction on the survey line signals collected above the area where the urban underground engineering system is located. The calculation formula is as follows:

[0109] J1(t)=S(t)+N1(t)

[0110] J2(t)=α*S(t-Td)+N2(t)

[0111] Where S(t) is the expected signal above the area where the urban underground engineering system is located, N1(t) and N2(t) are Gaussian white noise, Td is the delay time, α is the attenuation coefficient, J1(t) and J2(t) are the basic survey line signal and the survey line signal above the area where the urban underground engineering system is located, respectively. The cross-correlation function of J1(t) and J2(t) is:

[0112] R J1 J2 (τ) = E{J1(t)J2(t+τ)}

[0113] Since Rss(τ)≤Rss(0), Rss(τ) reaches its maximum value when τ-td=0, that is, when τ=td. By using this relationship, the td value can be obtained, and then the monitoring survey line can be time-shifted by td according to the track or the entire line.

[0114] S33: Using the base survey line signal as a reference, performing phase rotation on the survey line signal above the area where the urban underground engineering system is located, selecting a phase angle corresponding to a maximum similarity coefficient between the base survey line signal and the survey line signal, and performing phase rotation on the survey record signal using the phase angle;

[0115] Here, the phase scanning method is adopted to perform phase rotation on the monitoring line based on the basic survey line.

[0116] S34: Calculate the convolution filter factor for the survey line signal and perform matched filtering. The calculation formula is:

[0117] r=F*J1-J2

[0118] Where F is the convolution filter factor, J1 and J2 represent the traces above the target layer in the time window, and r is the preset variable that is minimized in the least squares sense.

[0119] Here, the two recording channels are matched locally, while the two measurement lines are matched globally. The convolution filter factor F is calculated and convolved with the monitoring line to complete the matching process.

[0120] By combining the basic survey line information with the survey line information and sequentially performing root mean square correction processing, cross-correlation delay correction processing, phase correction processing, and matched filtering processing, the amplitude, time, phase, and frequency of the basic survey line information can be corrected to be consistent with the basic survey line. The obtained correction operator is then applied to the survey line information, thereby achieving consistency processing of the survey line information and accurately obtaining difference information.

[0121] Here, multi-source time-lapse survey data are used to better evaluate the stability, safety and other characteristics of urban underground space, and a new "source-transport-engineering" urban underground space survey, measurement and interpretation model is constructed. That is, by studying the "geological" object (which we call "target geological body") on which the project will be implemented, analyzing the "material source and sedimentary environment" of the target geological body, and developing the "cap-reservoir-base" stratigraphic rock and soil combination elements of the "source" of the target geological body, that is, the temporal and spatial mutual configuration relationship of the geological reservoir layer, cover layer and bedrock layer where the engineering structure is located, analyzing the position change (deformation, destruction, flow) of the rock and soil (fluid) of the target geological body under the drive of a certain dynamic force (gravity, stress, external force) through a certain transportation mode, and finally adopting certain engineering measures to solve the style as a complete "source-transport-engineering" system. Taking the sudden mud and water gushing in tunnels as an example, a comprehensive analysis is conducted on the interactions and results of the "engineering system, internal forces, and external forces" that control the system. Based on multi-source time-lapse survey data, the source of the "mud and water" material (material source) is analyzed, and the source of the material near the "mud and water" (near the material source) is clarified. Is it caused by heavy atmospheric rainfall (external forces) directly transported to the tunnel through surface fractures or by the rupture of the pressurized water layer during the tunnel excavation process (that is, the source of mud and water supply, the direction of runoff movement, and the discharge conditions must be identified). The next step of engineering measures (drainage interception, reinforcement, etc.) is formulated to solve the problem of sudden mud and water gushing, thereby establishing a more accurate quantitative interpretation model of the "source-transport-engineering" system, and then guiding the prediction of corresponding urban underground space events.

[0122] like Figure 2 and Figure 3 The figures are respectively a schematic diagram of determining the changing trend and development law of qualitative surface formation properties through time-lapse exploration according to an embodiment of the present invention and a schematic diagram of quantitatively characterizing the changes in fluid saturation and ground stress by combining time-lapse exploration data with drilling data according to an embodiment of the present invention.

[0123] like Figure 4 As shown, the present invention also provides a multi-source dynamic survey system for urban underground space, including a feasibility analysis module, a positioning acquisition module, a difference information module and a prediction module;

[0124] The feasibility analysis module is used to construct a convolution model of the urban underground space, perform numerical simulation based on the collected basic data, generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space, and determine whether the conditions for conducting multi-source time-lapse survey are met;

[0125] The positioning and acquisition module is used to calibrate the monitoring position when the conditions for carrying out multi-source time-lapse survey are met, repeatedly collect urban underground space data at preset intervals, and generate survey line information;

[0126] The difference information module is used to perform consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and perform mutual averaging processing on the difference information;

[0127] The prediction module is used to determine the rock and soil deformation and fluid information of the urban underground space based on the difference information, and to perform dynamic prediction of the urban underground space.

[0128] The multi-source dynamic survey system for urban underground space of the present invention constructs a convolution model of urban underground space and performs numerical simulation based on basic data to construct a basic data table for feasibility analysis of multi-source time-lapse survey to perform feasibility analysis of multi-source time-lapse survey. When the feasibility meets the requirements, the monitoring position is calibrated and repeated sampling is performed to perform consistency processing to obtain difference information, and the difference data is comprehensively analyzed to determine the deformation of the rock and soil body and fluid information of the urban underground space, thereby realizing dynamic survey and management of complex urban underground space bodies, avoiding the multi-solution nature of a single single-source method, and improving the accuracy of the survey results.

[0129] In one or more embodiments of the present invention, the feasibility analysis module constructs a convolution model of the urban underground space and performs numerical simulation based on the collected basic data to generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space. The specific implementation is:

[0130] Constructing a convolution model of urban underground space:

[0131] J(t)=g(t)*d(t)*w(t)

[0132] Where g(t) represents the urban underground engineering system, d(t) represents the geological internal force system, w(t) represents the geological external force system, and J(t) represents the total output of the interaction between the urban underground engineering system g(t), the geological internal force system d(t), and the geological external force system w(t).

[0133] The collected basic data is input into the urban underground space convolution model and calculated to obtain urban underground space data, and a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space is constructed.

[0134] By constructing the urban underground space convolution model, numerical simulation can be performed based on the collected basic data, thereby obtaining a basic data table for feasibility analysis of multi-source time-lapse survey of underground space, so as to facilitate subsequent accurate analysis of whether the conditions for carrying out multi-source time-lapse survey are met based on the basic data table for feasibility analysis of multi-source time-lapse survey of underground space.

[0135] In one or more embodiments of the present invention, the feasibility analysis module determines whether the conditions for carrying out multi-source time-lapse survey are met by:

[0136] Reading the imaging quality index and the repeatability index according to the basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space, and determining that the conditions for conducting multi-source time-lapse survey are not met when the imaging quality index and / or the repeatability index do not meet the corresponding preset standards;

[0137] otherwise;

[0138] Determining the influencing factors of the feasibility indicators in the engineering system, the geological internal force system and the geological external force system respectively according to the plurality of feasibility indicators and the corresponding preset standards;

[0139] A feasibility index is calculated based on the influencing factors of each of the feasibility indicators, and when the feasibility index is greater than or equal to a preset feasibility index threshold, it is determined that the conditions for conducting multi-source time-lapse survey are met; otherwise, it is determined that the conditions for conducting multi-source time-lapse survey are not met.

[0140] By reading the imaging quality index and repeatability index, and judging whether the read imaging quality index and repeatability index meet the corresponding preset standards, it is possible to conduct multiple feasibility index analyses in the engineering system, geological internal force system and geological external force system on the premise that the imaging quality index and repeatability index meet the preset standards, thereby ensuring the accuracy of the analysis results.

[0141] In one or more embodiments of the present invention, the difference information module performs consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and the mutual averaging processing on the difference information is specifically implemented as follows:

[0142] The survey line information received in the area where the urban underground engineering system is located is read, and the root mean square amplitude correction processing is performed on the survey line information. The correction operator is:

[0143] Amp=A1 / A2

[0144] Among them, A1 and A2 are the maximum RMS amplitudes of the basic survey line signal and the survey line signal in the time window respectively;

[0145] The cross-correlation delay correction is performed on the survey line signals collected above the area where the urban underground engineering system is located. The calculation formula is as follows:

[0146] J1(t)=S(t)+N1(t)

[0147] J2(t)=α*S(t-Td)+N2(t)

[0148] Where S(t) is the expected signal above the area where the urban underground engineering system is located, N1(t) and N2(t) are Gaussian white noise, Td is the delay time, α is the attenuation coefficient, J1(t) and J2(t) are the basic survey line signal and the survey line signal above the area where the urban underground engineering system is located, respectively. The cross-correlation function of J1(t) and J2(t) is:

[0149] R J1 J2 (τ) = E{J1(t)J2(t+τ)}

[0150] Since Rss(τ)≤Rss(0), Rss(τ) reaches its maximum value when τ-td=0, that is, when τ=td. By using this relationship, the td value can be obtained, and then the monitoring survey line can be time-shifted by td according to the track or the entire line.

[0151] Taking the basic survey line signal as a reference, performing phase rotation on the survey line signal above the area where the urban underground engineering system is located, selecting the phase angle corresponding to the maximum similarity coefficient between the basic survey line signal and the survey line signal, and performing phase rotation on the survey record signal at the phase angle;

[0152] The convolution filter factor is solved for the survey line signal and matched filtering is performed. The calculation formula is:

[0153] r=F*J1-J2

[0154] Where F is the convolution filter factor, J1 and J2 represent the traces above the target layer in the time window, and r is the preset variable that is minimized in the least squares sense.

[0155] By combining the basic survey line information with the survey line information and sequentially performing root mean square correction processing, cross-correlation delay correction processing, phase correction processing, and matched filtering processing, the amplitude, time, phase, and frequency of the basic survey line information can be corrected to be consistent with the basic survey line. The obtained correction operator is then applied to the survey line information, thereby achieving consistency processing of the survey line information and accurately obtaining difference information.

[0156] The multi-source dynamic survey method and system for urban underground space of the present invention can know the situation and location of the target area of ​​urban underground space through multi-source time-lapse survey data. The time-lapse survey monitors the target area of ​​urban underground space by recording survey data at different time intervals at the same location, and analyzes these data to analyze the changes in physical responses caused by fluid movement, pressure changes, rock deformation and other stratum rock and soil characteristics caused by the activities of the target area, and inverts the changes in these responses into the changes in rock and soil characteristics over time.

[0157] The present invention also provides a computer-readable storage medium, which stores computer instructions. The computer instructions are used to enable a processor to implement the multi-field source dynamic survey method for urban underground space when executed.

[0158] The present invention also provides a multi-source dynamic survey device for urban underground space, characterized in that the multi-source dynamic survey device for urban underground space comprises:

[0159] at least one processor and a storage medium, wherein the storage medium is communicatively connected to the processor;

[0160] In which, the storage medium stores a computer program that can be executed by at least one of the processors, and the computer program is executed by the at least one processor so that the at least one processor can execute the multi-field source dynamic survey method for urban underground space.

[0161] This scheme is a new technology and new method for realizing dynamic survey of urban underground space. First, it adopts multi-field source electrical method, seismic method, electromagnetic wave and other joint detection technologies to improve the accuracy of survey results and effectively reduce the multi-solution of survey results; secondly, by constructing a convolution model of urban underground space, because convolution has the commutative law and associative law operation characteristics, the mutual transformation of the effects between "engineering system, internal factors and external factors" does not affect the effect of the urban underground space system, thereby better characterizing the interaction between engineering system, internal forces and external forces, and conducting feasibility studies on multi-source time-lapse survey of urban underground space is more scientific and reasonable; thirdly, the scheme proposes to conduct high-repeatability monitoring at the same location at a certain time interval to obtain data bodies of different periods, which greatly improves the repeatability of time-lapse survey; fourthly, the use of this technical method can quickly eliminate system errors and obtain meaningful difference information.

[0162] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-source dynamic survey method for urban underground space, characterized in that: The steps include: S1: Construct a convolution model of the urban underground space, perform numerical simulation based on the collected basic data, generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space, and determine whether the conditions for conducting multi-source time-lapse survey are met; S2: When conditions are met for conducting multi-source time-lapse surveys, the monitoring locations are calibrated, urban underground space data are repeatedly collected at preset intervals, and survey line information is generated; S3: performing consistency processing on the survey line information according to a multi-source time-lapse survey formula to obtain difference information, and performing mutual averaging processing on the difference information; S4: Determine the deformation of the rock and soil mass and fluid information of the urban underground space based on the difference information, and perform dynamic prediction of the urban underground space; In S1, the steps of constructing a convolution model of the urban underground space and performing numerical simulation based on the collected basic data to generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space specifically include the following steps: S11: Constructing a convolution model of urban underground space: J(t)=g(t)*d(t)*w(t) Where g(t) represents the urban underground engineering system, d(t) represents the geological internal force system, w(t) represents the geological external force system, and J(t) represents the total output of the interaction between the urban underground engineering system g(t), the geological internal force system d(t), and the geological external force system w(t). S12: Inputting the collected basic data into the urban underground space convolution model and performing calculations to obtain urban underground space data, and constructing a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space; In S1, the determination of whether the conditions for carrying out multi-source time-lapse survey are met specifically includes the following steps: S13: Reading an imaging quality index and a repeatability index according to the basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space, and if both the imaging quality index and the repeatability index meet corresponding preset standards, proceeding to S14; otherwise, determining that the conditions for conducting multi-source time-lapse survey are not met; S14: determining an influencing factor of each feasibility indicator according to a plurality of feasibility indicators in the engineering system, the geological internal force system, and the geological external force system and corresponding preset standards; S15: Calculating a feasibility index based on the influencing factors of the feasibility indicators, and determining that the conditions for conducting the multi-source time-lapse survey are met when the feasibility index is greater than or equal to a preset feasibility index threshold; otherwise, determining that the conditions for conducting the multi-source time-lapse survey are not met; In S3, performing consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and performing mutual averaging processing on the difference information includes the following steps: S31: Read the survey line information received in the area where the urban underground engineering system is located, and perform root mean square amplitude correction processing on the survey line information. The correction operator is: Amp=A1 / A2 Among them, A1 and A2 are the maximum RMS amplitudes of the basic survey line signal and the survey line signal in the time window respectively; S32: Perform cross-correlation delay correction on the survey line signals collected above the area where the urban underground engineering system is located. The calculation formula is as follows: J1(t)=S(t)+N1(t) J2(t)=α*S(t-Td)+N2(t) Where S(t) is the expected signal above the area where the urban underground engineering system is located, N1(t) and N2(t) are Gaussian white noise, Td is the delay time, α is the attenuation coefficient, J1(t) and J2(t) are the basic survey line signal and the survey line signal above the area where the urban underground engineering system is located, respectively. The cross-correlation function of J1(t) and J2(t) is: R J1 J2 (τ)=E{J1(t)J2(t+τ)} S33: Using the base survey line signal as a reference, performing phase rotation on the survey line signal above the area where the urban underground engineering system is located, selecting a phase angle corresponding to a maximum similarity coefficient between the base survey line signal and the survey line signal, and performing phase rotation on the survey record signal using the phase angle; S34: Calculate the convolution filter factor for the survey line signal and perform matched filtering. The calculation formula is: r=F*J1-J2 Where F is the convolution filter factor, J1 and J2 represent the traces above the target layer in the time window, and r is the preset variable that is minimized in the least squares sense.

2. A multi-source dynamic survey system for urban underground space, characterized in that: It includes feasibility analysis module, positioning acquisition module, difference information module and prediction module; The feasibility analysis module is used to construct a convolution model of the urban underground space, perform numerical simulation based on the collected basic data, generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space, and determine whether the conditions for conducting multi-source time-lapse survey are met; The positioning and acquisition module is used to calibrate the monitoring position when the conditions for carrying out multi-source time-lapse survey are met, repeatedly collect urban underground space data at preset intervals, and generate survey line information; The difference information module is used to perform consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information, and perform mutual averaging processing on the difference information; The prediction module is used to determine the deformation of the rock and soil mass and the fluid information of the urban underground space based on the difference information, and to perform dynamic prediction of the urban underground space; The feasibility analysis module constructs a convolution model of the urban underground space and performs numerical simulation based on the collected basic data to generate a basic data table for feasibility analysis of multi-source time-lapse survey of the urban underground space. The specific implementation is as follows: Constructing a convolution model of urban underground space: J(t)=g(t)*d(t)*w(t) in, g (t) represents the urban underground engineering system, d(t) represents the geological internal force system, w(t) represents the geological external force system, and J(t) represents the total output result of the interaction between the urban underground engineering system g(t), the geological internal force system d(t) and the geological external force system w(t); Input the collected basic data into the urban underground space convolution model and perform calculations to obtain urban underground space data, and construct a basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space; The feasibility analysis module determines whether the conditions for carrying out multi-source time-lapse survey are met in the following specific implementations: Reading the imaging quality index and the repeatability index according to the basic data table for feasibility analysis of multi-source time-lapse survey of urban underground space, and determining that the conditions for conducting multi-source time-lapse survey are not met when the imaging quality index and / or the repeatability index do not meet the corresponding preset standards; otherwise; Determining the influencing factors of the feasibility indicators in the engineering system, the geological internal force system and the geological external force system respectively according to the plurality of feasibility indicators and the corresponding preset standards; A feasibility index is calculated based on the influencing factors of the feasibility indicators, and when the feasibility index is greater than or equal to a preset feasibility index threshold, it is determined that the conditions for carrying out the multi-source time-lapse survey are met; otherwise, it is determined that the conditions for carrying out the multi-source time-lapse survey are not met; The difference information module performs consistency processing on the survey line information according to the multi-source time-lapse survey formula to obtain difference information. The specific implementation of performing mutual averaging processing on the difference information is as follows: The survey line information received in the area where the urban underground engineering system is located is read, and the root mean square amplitude correction processing is performed on the survey line information. The correction operator is: Amp=A1 / A2 Among them, A1 and A2 are the maximum RMS amplitudes of the basic survey line signal and the survey line signal in the time window respectively; The cross-correlation delay correction is performed on the survey line signals collected above the area where the urban underground engineering system is located. The calculation formula is as follows: J1(t)=S(t)+N1(t) J2(t)=α*S(t-Td)+N2(t) Where S(t) is the expected signal above the area where the urban underground engineering system is located, N1(t) and N2(t) are Gaussian white noise, Td is the delay time, α is the attenuation coefficient, J1(t) and J2(t) are the basic survey line signal and the survey line signal above the area where the urban underground engineering system is located, respectively. The cross-correlation function of J1(t) and J2(t) is: R J1 J2 (τ)=E{J1(t)J2(t+τ)} Taking the basic survey line signal as a reference, performing phase rotation on the survey line signal above the area where the urban underground engineering system is located, selecting the phase angle corresponding to the maximum similarity coefficient between the basic survey line signal and the survey line signal, and performing phase rotation on the survey record signal at the phase angle; The convolution filter factor is solved for the survey line signal and matched filtering is performed. The calculation formula is: r=F*J1-J2 Where F is the convolution filter factor, J1 and J2 represent the traces above the target layer in the time window, and r is the preset variable that is minimized in the least squares sense.

3. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the urban underground space multi-source dynamic survey method according to claim 1 when executed.

4. A multi-source dynamic survey device for urban underground space, characterized in that: The urban underground space multi-source dynamic survey equipment includes: at least one processor and a storage medium, the storage medium being communicatively connected to the processor; Wherein, the storage medium stores a computer program that can be executed by at least one of the processors, and the computer program is executed by the at least one processor so that the at least one processor can execute the multi-field source dynamic survey method for urban underground space as described in claim 1.

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