Method, device, equipment, medium and program product for monitoring a subsurface medium

Abstract

The embodiment of the application provides a kind of underground medium dynamic monitoring method, device, equipment, medium and program product, underground seismic data is collected by distributed acoustic wave sensing system, ground seismic data is collected by seismic array, the data collected by distributed acoustic wave sensing system and the data collected by seismic array are combined, underground seismic data and ground seismic data are preprocessed, according to the phase difference of current cross-correlation function and reference cross-correlation function, time shift change is obtained, and according to the wave velocity variation information of underground medium, the dynamic change of underground medium is monitored, the effect of monitoring underground medium dynamic information is improved.

Description

Technical Field

[0001] This application relates to the field of geological monitoring technology, and in particular to a method, device, equipment, medium and program product for dynamic monitoring of underground media. Background Technology

[0002] Subsurface media are complex geological bodies composed of different substances that exist below the Earth's surface. They are a general term for solids, fluids, and multiphase mixtures in the Earth's shallow layer. The composition, structure, and dynamic characteristics of subsurface media directly affect underground engineering, resource development, and the monitoring and assessment of geological hazards.

[0003] In existing technologies, dynamic information about underground media is obtained through fiber optic sensor networks or detectors.

[0004] However, in existing technologies, fiber optic sensor networks are easily interfered with by environmental noise, making it impossible to collect weak signals. Furthermore, detectors are difficult to achieve wide-area coverage when deployed underground. Existing technologies suffer from poor performance in monitoring the dynamic information of underground media. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, medium, and program product for dynamic monitoring of underground media, in order to solve the problem of poor monitoring effect of underground media dynamic information in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for dynamic monitoring of underground media, applied to an underground media dynamic monitoring system, comprising:

[0007] Acquire downhole seismic data collected by a distributed acoustic wave sensing system and surface seismic data collected by a seismic array;

[0008] The downhole seismic data is preprocessed to obtain preprocessed downhole seismic data;

[0009] The ground seismic data is preprocessed to obtain preprocessed ground seismic data;

[0010] Based on the preprocessed downhole seismic data and the preprocessed surface seismic data, the cross-correlation is calculated to generate the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system;

[0011] The time shift of the underground medium dynamic monitoring system is obtained based on the phase difference between the current cross-correlation function and the reference cross-correlation function;

[0012] Based on the time-shift changes of the underground medium dynamic monitoring system, wave velocity change information of the underground medium is calculated and generated;

[0013] The dynamic changes of the underground medium are monitored based on the wave velocity change information.

[0014] In one possible implementation, the step of calculating and generating wave velocity change information of the underground medium based on the time-shift change of the underground medium dynamic monitoring system includes: dividing the empirical Green's function of the underground medium dynamic monitoring system into signal windows to obtain multiple time windows; performing cross-spectral analysis on the multiple time windows to obtain the phase spectrum of the multiple time windows; determining the time shift of the empirical Green's function of the underground medium dynamic monitoring system based on the phase spectrum of the multiple time windows; and calculating and generating wave velocity change information of the underground medium based on the time shift of the empirical Green's function of the underground medium dynamic monitoring system.

[0015] In one possible implementation, the step of calculating and generating wave velocity change information of the underground medium based on the time-shift change of the underground medium dynamic monitoring system includes: determining a reference function based on a preset reference time period; stretching the empirical Green's function of the underground medium dynamic monitoring system to obtain the time shift of multiple stretched empirical Green's functions; determining an optimal stretching factor based on the time shift of the multiple stretched empirical Green's functions and the reference function; and calculating and generating wave velocity change information of the underground medium based on the optimal stretching factor.

[0016] In one possible implementation, the formula for calculating the wave velocity variation information of the subsurface medium is:

[0017] Δv / v=-Δτ / τ

[0018] In the formula, v represents the wave speed under the reference state; τ represents the propagation time of the reference signal; and Δv / v represents the change in wave speed.

[0019] In one possible implementation, the step of calculating the cross-correlation based on the preprocessed downhole seismic data and the preprocessed surface seismic data to generate the current cross-correlation function and reference cross-correlation function of the subsurface medium dynamic monitoring system includes: calculating the channel correlation of the distributed acoustic sensing system based on the preprocessed downhole seismic data to generate the cross-correlation function of the system channels; calculating the correlation of each seismic station in the seismic array based on the preprocessed surface seismic data to generate the cross-correlation function of the seismic array; calculating the correlation between the distributed acoustic sensing system and the seismic array based on the preprocessed downhole seismic data and the preprocessed surface seismic data to generate the cross-correlation function between the seismic array and the sensing system; and generating the current cross-correlation function and reference cross-correlation function of the subsurface medium dynamic monitoring system based on the cross-correlation function of the system channels, the cross-correlation function of the seismic array, and the cross-correlation function between the seismic array and the sensing system.

[0020] In one possible implementation, the formula for generating the cross-correlation function of the underground medium dynamic monitoring system is:

[0021] C(f) = X * (f)×Y(f)

[0022] In the formula, C(f) represents the cross-correlation function; X * (f) denotes the conjugate of the Fourier transform of the time series x(t); Y(f) denotes the Fourier transform of the time series y(t).

[0023] Secondly, embodiments of this application provide a dynamic monitoring device for underground media, applied to a dynamic monitoring system for underground media, comprising:

[0024] The first acquisition module is used to acquire downhole seismic data collected by the distributed acoustic wave sensing system and surface seismic data collected by the seismic array.

[0025] The first preprocessing module is used to preprocess the downhole seismic data to obtain preprocessed downhole seismic data.

[0026] The second preprocessing module is used to preprocess the ground seismic data to obtain preprocessed ground seismic data.

[0027] The first calculation module is used to calculate the cross-correlation based on the preprocessed downhole seismic data and the preprocessed surface seismic data, and generate the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system.

[0028] The second acquisition module is used to obtain the time shift change of the underground medium dynamic monitoring system based on the phase difference between the current cross-correlation function and the reference cross-correlation function;

[0029] The second calculation module is used to calculate and generate wave velocity change information of the underground medium based on the time-shift changes of the underground medium dynamic monitoring system.

[0030] The monitoring module is used to monitor the dynamic changes of the underground medium based on the wave velocity change information.

[0031] Thirdly, embodiments of this application provide an electronic device, including:

[0032] At least one processor and memory;

[0033] The memory stores computer-executed instructions;

[0034] The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0035] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0036] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0037] This application provides a method, apparatus, equipment, medium, and program product for dynamic monitoring of underground media. It collects downhole seismic data through a distributed acoustic wave sensing system and surface seismic data through a seismic array. The data from the distributed acoustic wave sensing system and the seismic array are combined to preprocess the downhole and surface seismic data. Based on the preprocessed downhole and surface seismic data, a current cross-correlation function and a reference cross-correlation function are calculated. The time shift change is obtained based on the phase difference between the current and reference cross-correlation functions, and the wave velocity change information of the underground media is calculated based on the time shift change. The dynamic changes of the underground media are monitored based on the wave velocity change information, thus improving the effectiveness of monitoring the dynamic information of the underground media. Attached Figure Description

[0038] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0039] Figure 1 This is a schematic diagram illustrating an application scenario of the underground medium dynamic monitoring method provided in the embodiments of this application;

[0040] Figure 2 A flowchart illustrating the dynamic monitoring method for underground media provided in this application embodiment;

[0041] Figure 3 A graph showing the relationship between the cross-correlation function and time provided in the embodiments of this application;

[0042] Figure 4 A comparison diagram of the cross-correlation function and a reference cross-correlation function provided for embodiments of this application;

[0043] Figure 5 A schematic diagram illustrating the average relative wave velocity variations of some seismic stations and channels provided in this application embodiment;

[0044] Figure 6 This is a schematic diagram of the structure of the underground medium dynamic monitoring device provided in the embodiments of this application;

[0045] Figure 7A schematic diagram of the structure of the electronic device provided in this application.

[0046] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0047] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0048] First, let me explain the terms used in this application:

[0049] Phase-sensitive optical time-domain reflectometry (PTZ): This is a fiber optic sensing technology that monitors external disturbances by measuring the phase changes of signals in an optical fiber.

[0050] Subsurface media are complex geological bodies composed of different substances existing below the Earth's surface; they are a general term for solids, fluids, and multiphase mixtures in the Earth's shallow layer. The composition, structure, and dynamic characteristics of subsurface media directly affect underground engineering, resource development, and the monitoring and assessment of geological hazards. Current technologies acquire dynamic information about subsurface media through fiber optic sensor networks or geophones. However, existing technologies suffer from limitations: fiber optic sensor networks are easily interfered with by environmental noise, making it impossible to collect weak signals; and geophones are difficult to deploy over large areas underground. Therefore, existing methods suffer from poor performance in monitoring the dynamic information of subsurface media.

[0051] To address the aforementioned technical problems, this application proposes the following technical concept: The inventors considered combining data from a distributed acoustic sensing system with data acquired by a seismic array. The downhole seismic data acquired by the distributed acoustic sensing system underwent data preprocessing, as did the surface seismic data acquired by the seismic array, resulting in preprocessed downhole and surface seismic data. Considering the correlation between the downhole and surface seismic data, a current cross-correlation function and a reference cross-correlation function for the subsurface medium dynamic monitoring system were generated. By calculating the phase difference between the current and reference cross-correlation functions, the time-shift change of the subsurface medium dynamic monitoring system was obtained. The wave velocity change information of the subsurface medium was calculated based on the time-shift change of the subsurface medium dynamic monitoring system. Monitoring the dynamic changes of the subsurface medium based on the wave velocity change information improved the effectiveness of monitoring subsurface medium dynamic information. Detailed embodiments are described below.

[0052] Figure 1 This is a schematic diagram illustrating an application scenario of the dynamic monitoring method for underground media provided in this application. For example... Figure 1 As shown, the application scenario includes: a dynamic monitoring system for underground media, which includes a distributed acoustic wave sensing system 101 and a seismic array 102.

[0053] Specifically, the subsurface medium dynamic monitoring system preprocesses the downhole seismic data collected by the distributed acoustic wave sensing system 101 and the surface seismic data collected by the seismic array 102 to obtain preprocessed downhole seismic data and surface seismic data. Based on the preprocessed downhole seismic data and surface seismic data, the system calculates the correlation to generate the current cross-correlation function and the reference cross-correlation function of the subsurface medium dynamic monitoring system. Based on the phase difference between the current cross-correlation function and the reference cross-correlation function, the system obtains the time shift change of the subsurface medium dynamic monitoring system. Based on the time shift change of the subsurface medium dynamic monitoring system, the system calculates and generates the wave velocity change information of the subsurface medium and monitors the dynamic changes of the subsurface medium based on the wave velocity change information.

[0054] Figure 2 This is a flowchart illustrating the underground medium dynamic monitoring method provided in this embodiment. The implementing entity in this embodiment can be an underground medium dynamic monitoring system; however, no particular limitation is made here. Figure 2 As shown, the method includes:

[0055] S201: Acquire downhole seismic data collected by the distributed acoustic wave sensing system and surface seismic data collected by the seismic array.

[0056] For example, the area to be tested is a hydraulic fracturing test site with a depth of 4km. The seismic array consists of 30 broadband mobile seismic stations with a station spacing of 2-3km. A 10km field optical cable is arranged at the center of the array of stations. The armored optical cable is shallowly buried at a depth of 0.5-1m. The sensor system channel spacing is set to 5m and the scale is set to 50m.

[0057] In this embodiment, the distributed acoustic wave sensing system deploys armored optical fibers along the underground drilling well and collects vibration signals in real time using phase-sensitive optical time-domain reflectometry. The spatial resolution of the distributed acoustic wave sensing system is at the meter level.

[0058] In this embodiment, the fiber optic deployment methods of the distributed acoustic wave sensing system include, but are not limited to, ring deployment, linear deployment, and grid deployment.

[0059] In this embodiment, the downhole seismic data recorded in the distributed acoustic sensing system includes, but is not limited to, pulse width, sampling rate, channel spacing, and recording duration.

[0060] In this embodiment, the seismic array is equipped with broadband three-component detectors to form a high-density observation network.

[0061] In this embodiment, the seismic array is deployed according to the geological structure and the target depth of the area to be monitored. The unit of station spacing is on the order of hundreds of meters or kilometers. The seismometer is a broadband high-sensitivity seismometer. The measurement range of the seismometer is selected according to the background noise signal of the area to be measured.

[0062] In this embodiment, the data acquisition time unit of the seismic array is in months, the sampling rate is set to 50Hz to 200Hz, the seismic array is synchronized with the satellite time, and the time error unit is set to milliseconds.

[0063] In this embodiment, the downhole seismic data collected by the distributed acoustic wave sensing system and the surface seismic data collected by the seismic array are stored in time slices, with spatial coordinates and timestamps marked in the time slices.

[0064] In this embodiment, the time slices collected by the distributed acoustic sensing system and the seismic array are backed up.

[0065] In this embodiment, the distributed acoustic sensing system and the seismic array need to be calibrated periodically.

[0066] S202: Perform data preprocessing on the downhole seismic data to obtain preprocessed downhole seismic data.

[0067] Specifically, the downhole seismic data is denoised to remove traffic and industrial noise interference. The denoised data is then unwrapped in phase to convert strain information into absolute displacement information, resulting in preprocessed downhole seismic data.

[0068] In this embodiment, the denoising method uses median filtering with a window length of 10 channels.

[0069] S203: Perform data preprocessing on the ground seismic data to obtain preprocessed ground seismic data.

[0070] In this embodiment, the data preprocessing steps for seismic station data include, but are not limited to, removing instrument response, removing mean and linear trend, bandpass filtering, time normalization, and spectral whitening.

[0071] In this process, the data recorded by the seismic array is converted into ground motion signals by removing the instrument response.

[0072] Specifically, by removing the mean and removing the linear trend, DC bias and long-term trend in the records are eliminated.

[0073] Among them, the background noise signal within the target frequency range is extracted by selecting a frequency band through bandpass filtering.

[0074] Among them, the amplitude information in the downhole seismic data is normalized to positive and negative 1 by normalization method, which reduces the impact of seismic events and strong signals on the cross-correlation results of background noise.

[0075] Among these methods, spectral whitening suppresses strong single-frequency signals, balances the energy distribution across different frequency bands, and improves the stability of the cross-correlation function.

[0076] S204: Calculate the cross-correlation based on the preprocessed downhole seismic data and the preprocessed surface seismic data to generate the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system.

[0077] Specifically, the cross-correlation functions between seismic arrays, between system channels, and between seismic arrays and the sensing system are calculated. Based on these three types of cross-correlation functions, the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system are determined.

[0078] In this embodiment, the reference cross-correlation function is a selected function that calculates the phase difference with the current cross-correlation function.

[0079] In this embodiment, the current cross-correlation function is obtained by superimposing the cross-correlation calculated daily between the seismic station and the DAS channel.

[0080] In this embodiment, the formula for generating the cross-correlation function of the underground medium dynamic monitoring system is:

[0081] C(f) = X * (f)×Y(f)

[0082] In the formula, C(f) represents the cross-correlation function; X * (f) denotes the conjugate of the Fourier transform of the time series x(t); Y(f) denotes the Fourier transform of the time series y(t).

[0083] Figure 3 A graph showing the relationship between the cross-correlation function and time provided in the embodiments of this application.

[0084] S205: Based on the phase difference between the current cross-correlation function and the reference cross-correlation function, the time shift change of the underground medium dynamic monitoring system is obtained.

[0085] In this embodiment, the empirical Green's function of the underground medium dynamic monitoring system is obtained based on the phase difference between the current cross-correlation function and the reference cross-correlation function, and the time shift change is calculated based on the empirical Green's function.

[0086] S206: Calculate and generate wave velocity change information of underground media based on the time-shift changes of the underground media dynamic monitoring system.

[0087] Specifically, the empirical Green's function is divided into signal windows using the moving window cross-spectrum method. Cross-spectrum analysis is performed on multiple time windows after windowing to obtain multiple phase spectra. The time shift of the empirical Green's function of the underground medium dynamic monitoring system is determined based on the phase spectra, and the information on the change in underground medium wave velocity is calculated and generated.

[0088] Specifically, the empirical Green's function of the underground medium dynamic monitoring system is stretched using the stretching method. The correlation between the stretched empirical Green's function and the reference function is calculated to determine the optimal stretching factor. Based on the optimal stretching factor, the wave velocity change information of the underground medium is calculated and generated.

[0089] S207: Monitor the dynamic changes of underground media based on wave velocity variation information.

[0090] In this embodiment, the wave speed change information includes, but is not limited to, the amplitude of the wave speed change, the range of the wave speed change, and the duration of the wave speed change.

[0091] As can be seen from the above embodiments, by collecting downhole seismic data through a distributed acoustic wave sensing system and collecting surface seismic data through a seismic array, the data collected by the distributed acoustic wave sensing system and the data collected by the seismic array are combined to preprocess the downhole and surface seismic data. Based on the preprocessed downhole and surface seismic data, a current cross-correlation function and a reference cross-correlation function are calculated and generated. The time shift change is obtained based on the phase difference between the current and reference cross-correlation functions, and the wave velocity change information of the subsurface medium is calculated and generated based on the time shift change. The dynamic changes of the subsurface medium are monitored based on the wave velocity change information, which improves the effect of monitoring the dynamic information of the subsurface medium.

[0092] In one embodiment of this application, step S206 includes:

[0093] S2061: The empirical Green's function of the underground medium dynamic monitoring system is divided into signal windows to obtain multiple time windows.

[0094] Specifically, the empirical Green's function is divided into multiple time windows according to a preset window length.

[0095] In this embodiment, the time window function is selected as either a Hanning window or a Hamming window.

[0096] S2062: Perform cross-spectral analysis on multiple time windows to obtain the phase spectra of multiple time windows.

[0097] Specifically, Fourier transforms are performed on multiple time windows to obtain the spectrum of each time window, and the cross spectrum between the time window and the reference window is calculated to obtain the phase spectrum of the multiple time windows.

[0098] Figure 4 This is a schematic diagram of the moving window cross spectrum and interferogram provided in the embodiments of this application.

[0099] S2063: Determine the time shift of the empirical Green's function for the dynamic monitoring system of underground media based on the phase spectrum of multiple time windows.

[0100] Specifically, the winding phase is unwound along the frequency axis to obtain a continuous phase, and the time shift at each frequency point is calculated based on the linear relationship between time shift and phase.

[0101] In this embodiment, data points with a correlation lower than 0.75 are removed during the time shift calculation.

[0102] S2064: Based on the time-shift calculation of the empirical Green's function of the underground medium dynamic monitoring system, the wave velocity change information of the underground medium is generated.

[0103] Figure 5 This is a schematic diagram illustrating the average relative wave velocity variation of three seismic stations provided in an embodiment of this application.

[0104] In this embodiment, the formula for calculating the wave velocity variation information of the underground medium is:

[0105] Δv / v=-Δτ / τ

[0106] In the formula, v represents the wave speed under the reference state; τ represents the propagation time of the reference signal; and Δv / v represents the change in wave speed.

[0107] In this embodiment, the relative wave speed change is inversely proportional to the time shift.

[0108] As can be seen from the above embodiments, by dividing the empirical Green's function signal into multiple time windows using the moving window cross-spectrum method, performing cross-spectrum analysis on the multiple time windows to obtain the phase spectrum, determining the time shift based on the phase spectrum, and then calculating the wave velocity change information, the efficiency of the calculation is improved by using the moving window cross-spectrum method to calculate the wave velocity change information.

[0109] In one embodiment of this application, step S206 includes:

[0110] S301: Determine the reference function based on the preset reference time period.

[0111] In this embodiment, the reference time period is the initial state period or the stable state period of the underground medium dynamic monitoring system.

[0112] S302: The empirical Green's function of the underground medium dynamic monitoring system is stretched to obtain the time shift of multiple stretched empirical Green's functions.

[0113] Specifically, the reference function and the empirical Green's function to be calculated are aligned on the time axis, and multiple stretched empirical Green's functions are calculated according to different stretching factors.

[0114] S303: Determine the optimal stretching factor based on the time shift of multiple stretched empirical Green's functions and the reference function.

[0115] Specifically, the correlation between multiple stretched empirical Green's functions and the reference function is calculated. Based on the magnitude of the correlation, the stretching factor corresponding to the empirical Green's function with the highest correlation is selected and determined as the optimal stretching factor.

[0116] In this embodiment, data points with a correlation value lower than 0.75 are removed.

[0117] S304: Calculates and generates wave velocity variation information of the underground medium based on the optimal stretching factor.

[0118] In this embodiment, the optimal stretching factor is inversely proportional to the change in relative wave velocity.

[0119] The formula for calculating the wave velocity of the subsurface medium based on the optimal stretching factor is as follows:

[0120]

[0121] In the formula, v represents the wave velocity under the reference state; s represents the stretching factor; and Δv / v represents the wave velocity change.

[0122] As can be seen from the above embodiments, by stretching the empirical Green's function using the stretching method to minimize the difference between it and the reference function, the optimal stretching factor is determined, and then the wave velocity change information of the underground medium is calculated and generated. Calculating the wave velocity change information using the stretching method improves the anti-interference ability of noise on the calculation results.

[0123] In one embodiment of this application, step S204 includes:

[0124] S2041: Calculate the channel correlation of the distributed acoustic wave sensing system based on the preprocessed downhole seismic data, and generate the cross-correlation function of the system channels.

[0125] Specifically, a cross-correlation time window is selected, and cross-correlation calculations are performed on the strain data recorded in the distributed acoustic wave sensing system to generate the cross-correlation function of the system channel.

[0126] In this embodiment, the spacing between the cross-correlation channels in the distributed acoustic wave sensing system is adjusted according to the address structure and resolution of the area to be measured, and the spacing is several meters or tens of meters.

[0127] S2042: Calculate the correlation between the seismic stations in the seismic array based on the preprocessed ground seismic data, and generate the cross-correlation function of the seismic array.

[0128] Specifically, a cross-correlation time window is selected, and cross-correlation calculations are performed on the background noise data recorded by the seismic array to generate the cross-correlation function of the seismic array.

[0129] In this embodiment, the length of the cross-correlation time window is in seconds or minutes, and is adjusted according to the background noise of the area to be measured and the detection depth. The method for calculating the cross-correlation function is the sliding time window method.

[0130] S2043: Calculate the correlation between the distributed acoustic sensing system and the seismic array based on the preprocessed downhole seismic data and the preprocessed surface seismic data, and generate the cross-correlation function between the seismic array and the sensing system.

[0131] Specifically, the background noise data recorded by the seismic array and the strain data recorded by the distributed acoustic wave sensing system are cross-correlated to generate a cross-correlation function between the seismic array and the sensing system.

[0132] In this embodiment, background noise data and strain data need to be synchronized in time.

[0133] S2044: Generate the current cross-correlation function and reference cross-correlation function of the underground medium dynamic monitoring system based on the cross-correlation function of the system channels, the cross-correlation function of the seismic array, and the cross-correlation function between the seismic array and the sensing system.

[0134] In this embodiment, the formula for generating the cross-correlation function of the underground medium dynamic monitoring system is:

[0135] C(f) = X * (f)×Y(f)

[0136] In the formula, C(f) represents the cross-correlation function; X * (f) denotes the conjugate of the Fourier transform of the time series x(t); Y(f) denotes the Fourier transform of the time series y(t).

[0137] As can be seen from the above embodiments, by using the window sliding method, the cross-correlation function of the system channel is calculated based on the downhole seismic data, the cross-correlation function of the seismic array is calculated based on the surface seismic data, and the cross-correlation function between the seismic array and the sensing system is calculated based on the downhole seismic data and the surface seismic data. These three types of cross-correlation functions are determined as the cross-correlation functions of the underground medium dynamic monitoring system. The cross-correlation function is calculated by combining the data of the distributed acoustic wave sensing system with the data of the seismic array, which improves the monitoring accuracy and spatial resolution.

[0138] Figure 6 This is a schematic diagram of the structure of the underground medium dynamic monitoring device provided in the embodiments of this application, as shown below. Figure 6 As shown, the underground medium dynamic monitoring device 60 provided in this embodiment includes: a first acquisition module 601, a first preprocessing module 602, a second preprocessing module 603, a first calculation module 604, a second acquisition module 605, a second calculation module 606, and a monitoring module 607.

[0139] The first acquisition module 601 is used to acquire downhole seismic data collected by the distributed acoustic wave sensing system and surface seismic data collected by the seismic array.

[0140] The first preprocessing module 602 is used to preprocess the downhole seismic data to obtain preprocessed downhole seismic data.

[0141] The second preprocessing module 603 is used to preprocess the ground seismic data to obtain preprocessed ground seismic data.

[0142] The first calculation module 604 is used to calculate the cross-correlation based on the preprocessed downhole seismic data and the preprocessed surface seismic data, and to generate the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system.

[0143] The second acquisition module 605 is used to obtain the time shift change of the underground medium dynamic monitoring system based on the phase difference between the current cross-correlation function and the reference cross-correlation function.

[0144] The second calculation module 606 is used to calculate and generate wave velocity change information of the underground medium based on the time-shift changes of the underground medium dynamic monitoring system.

[0145] Monitoring module 607 is used to monitor the dynamic changes of underground media based on wave velocity change information.

[0146] In one embodiment of this application, the second computing module 606 includes:

[0147] The windowing unit is used to divide the empirical Green's function of the underground medium dynamic monitoring system into multiple time windows.

[0148] The analysis unit is used to perform cross-spectral analysis on multiple time windows to obtain the phase spectrum of multiple time windows.

[0149] The first determining unit is used to determine the time shift of the empirical Green's function of the underground medium dynamic monitoring system based on the phase spectrum of multiple time windows.

[0150] The first calculation unit is used to generate wave velocity change information of the underground medium based on the time shift calculation of the empirical Green's function of the underground medium dynamic monitoring system.

[0151] In one embodiment of this application, the second computing module 606 includes:

[0152] The second determining unit is used to determine the reference function based on a preset reference time period.

[0153] The stretching element is used to stretch the empirical Green's function of the underground medium dynamic monitoring system to obtain multiple stretched empirical Green's functions with time shifts.

[0154] The third determining unit is used to determine the optimal stretching factor based on the time shift of multiple stretched empirical Green's functions and the reference function.

[0155] The second calculation unit is used to calculate and generate wave velocity variation information of the underground medium based on the optimal stretching factor.

[0156] In one embodiment of this application, the formula for calculating the wave velocity variation information of the subsurface medium in the first calculation unit is as follows:

[0157] Δv / v=-Δτ / τ

[0158] In the formula, v represents the wave speed under the reference state; τ represents the propagation time of the reference signal; and Δv / v represents the change in wave speed.

[0159] In one embodiment of this application, the first computing module 604 includes:

[0160] The third calculation unit is used to calculate the channel correlation of the distributed acoustic wave sensing system based on the preprocessed downhole seismic data and generate the cross-correlation function of the system channels.

[0161] The fourth calculation unit is used to calculate the correlation between the seismic stations in the seismic array based on the preprocessed ground seismic data and generate the cross-correlation function of the seismic array.

[0162] The fifth calculation unit is used to calculate the correlation between the distributed acoustic sensing system and the seismic array based on the preprocessed downhole seismic data and the preprocessed surface seismic data, and to generate the cross-correlation function between the seismic array and the sensing system.

[0163] The conversion unit is used to generate the current cross-correlation function and reference cross-correlation function of the underground medium dynamic monitoring system based on the cross-correlation function of the system channels, the cross-correlation function of the seismic array, and the cross-correlation function between the seismic array and the sensing system.

[0164] In one embodiment of this application, the formula for generating the cross-correlation function of the underground medium dynamic monitoring system in the first calculation module 604 is as follows:

[0165] C(f) = X * (f)×Y(f)

[0166] In the formula, C(f) represents the cross-correlation function; X * (f) denotes the conjugate of the Fourier transform of the time series x(t); Y(f) denotes the Fourier transform of the time series y(t).

[0167] The underground medium dynamic monitoring device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0168] Figure 7 A schematic diagram of the structure of the electronic device provided in this application. Figure 7 As shown, the electronic device 70 provided in this embodiment includes at least one processor 701 and a memory 702. Optionally, the electronic device 70 further includes a communication component 703. The processor 701, memory 702, and communication component 703 are connected via a bus 704.

[0169] In the specific implementation process, at least one processor 701 executes computer execution instructions stored in memory 702, causing at least one processor 701 to execute the above-mentioned underground medium dynamic monitoring method.

[0170] The specific implementation process of processor 701 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0171] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0172] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0173] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0174] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for dynamic monitoring of underground media.

[0175] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method for dynamic monitoring of underground media.

[0176] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0177] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0178] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0179] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0180] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0181] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0182] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0183] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for dynamic monitoring of underground media, characterized in that, Applications in underground media dynamic monitoring systems include: Acquire downhole seismic data collected by a distributed acoustic wave sensing system and surface seismic data collected by a seismic array; The downhole seismic data is preprocessed to obtain preprocessed downhole seismic data; The ground seismic data is preprocessed to obtain preprocessed ground seismic data; Based on the preprocessed downhole seismic data and the preprocessed surface seismic data, the cross-correlation is calculated to generate the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system; The time shift of the underground medium dynamic monitoring system is obtained based on the phase difference between the current cross-correlation function and the reference cross-correlation function; Based on the time-shift changes of the underground medium dynamic monitoring system, wave velocity change information of the underground medium is calculated and generated; The dynamic changes of the underground medium are monitored based on the wave velocity change information.

2. The method according to claim 1, characterized in that, The step of calculating and generating wave velocity change information of the underground medium based on the time-shift changes of the underground medium dynamic monitoring system includes: The empirical Green's function of the underground medium dynamic monitoring system is windowed to obtain multiple time windows; Cross-spectral analysis is performed on the multiple time windows to obtain the phase spectra of the multiple time windows; The time shift of the empirical Green's function of the underground medium dynamic monitoring system is determined based on the phase spectrum of the multiple time windows; The wave velocity change information of the underground medium is generated based on the time shift calculation of the empirical Green's function of the underground medium dynamic monitoring system.

3. The method according to claim 1, characterized in that, The step of calculating and generating wave velocity change information of the underground medium based on the time-shift changes of the underground medium dynamic monitoring system includes: The reference function is determined based on the preset reference time period; The empirical Green's function of the underground medium dynamic monitoring system is stretched to obtain multiple time shifts of the stretched empirical Green's function; The optimal stretching factor is determined based on the time shift of the multiple stretched empirical Green's functions and the reference function; Based on the optimal stretching factor, the wave velocity variation information of the underground medium is calculated and generated.

4. The method according to claim 2, characterized in that, The formula for calculating the wave velocity variation information of the underground medium is as follows: Δv / v=-Δτ / τ In the formula, v represents the wave speed under the reference state; τ represents the propagation time of the reference signal; and Δv / v represents the change in wave speed.

5. The method according to claim 1, characterized in that, The step of calculating the cross-correlation based on the preprocessed downhole seismic data and the preprocessed surface seismic data to generate the current cross-correlation function and reference cross-correlation function of the subsurface medium dynamic monitoring system includes: The channel correlation of the distributed acoustic sensing system is calculated based on the preprocessed downhole seismic data, and the cross-correlation function of the system channels is generated. The correlation between the seismic stations in the seismic array is calculated based on the preprocessed ground seismic data, and the cross-correlation function of the seismic array is generated. The correlation between the distributed acoustic sensing system and the seismic array is calculated based on the preprocessed downhole seismic data and the preprocessed surface seismic data, and a cross-correlation function between the seismic array and the sensing system is generated. Based on the cross-correlation function of the system channel, the cross-correlation function of the seismic array, and the cross-correlation function between the seismic array and the sensing system, the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system are generated.

6. The method according to claim 1, characterized in that, The formula for generating the cross-correlation function of the underground medium dynamic monitoring system is: C(f) = X*(f) × Y(f) In the formula, C(f) represents the cross-correlation function; X*(f) represents the conjugate of the Fourier transform of the time series x(t); and Y(f) represents the Fourier transform of the time series y(t).

7. A dynamic monitoring device for underground media, characterized in that, Applications in underground media dynamic monitoring systems include: The first acquisition module is used to acquire downhole seismic data collected by the distributed acoustic wave sensing system and surface seismic data collected by the seismic array. The first preprocessing module is used to preprocess the downhole seismic data to obtain preprocessed downhole seismic data. The second preprocessing module is used to preprocess the ground seismic data to obtain preprocessed ground seismic data. The first calculation module is used to calculate the cross-correlation based on the preprocessed downhole seismic data and the preprocessed surface seismic data, and generate the current cross-correlation function and the reference cross-correlation function of the underground medium dynamic monitoring system. The second acquisition module is used to obtain the time shift change of the underground medium dynamic monitoring system based on the phase difference between the current cross-correlation function and the reference cross-correlation function; The second calculation module is used to calculate and generate wave velocity change information of the underground medium based on the time-shift changes of the underground medium dynamic monitoring system. The monitoring module is used to monitor the dynamic changes of the underground medium based on the wave velocity change information.

8. An electronic device, characterized in that, include: At least one processor and memory; The memory stores computer-executed instructions; The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the underground medium dynamic monitoring method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the underground medium dynamic monitoring method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the dynamic monitoring method for underground media as described in any one of claims 1 to 6.

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