Aquifer relative water-rich layer section fine detection system and method based on sound wave sensing

Abstract

The invention provides a fine detection system and method for a relative aquifer section of an aquifer based on passive distributed sound wave sensing, and a distributed sound wave data collection subsystem is used for collecting hydrodynamic sound wave signals of water from the ground to a straight-through drainage drill hole. The armored optical cable laying device is used for ensuring that the armored logging optical cable is accurately laid to the preset depth of the drill hole and recording the lowering depth of the armored logging optical cable. The test sleeve subsystem is used for obtaining hydrodynamic information through dynamic sound waves generated by water flow. The flow control and measurement device is used for controlling and monitoring the total flow of the straight-through drainage drill hole. According to the hydrogeological parameter testing system and method, hydrodynamic sound waves generated by outflow of water in the straight-through drainage drill hole are analyzed, the frequency and energy distribution characteristics of sound wave signals are utilized, a correlation model with the stratum flow is established, and the hydrogeological parameter testing system and method which can provide high resolution, high efficiency and high precision are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of hydrogeological exploration, relates to the detection of aquifers, and particularly relates to a fine detection system and method for relatively water-rich sections of aquifers based on passive distributed acoustic sensing. Background Art

[0002] In hydrogeological exploration, especially for extremely thick aquifers, accurately identifying and evaluating water-rich sections is crucial for the rational development, management of water resources, and prevention and control of water hazards in mining areas. The hydrogeological parameters (such as permeability coefficient, recharge volume, water storage capacity, water level, and water quality, etc.) of extremely thick aquifers provide a scientific basis for effective water resource management and disaster prevention and mitigation measures.

[0003] In the prior art, the commonly used pumping tests and geophysical exploration methods have certain limitations. Especially in the fine detection of extremely thick aquifers, it is difficult to obtain accurate stratification data due to equipment and environmental conditions, and it may cause interference to the environment. At the same time, when the traditional distributed acoustic sensing technology is used to detect the water-rich sections of extremely thick aquifers, there are still problems such as insufficient signal resolution, low data acquisition efficiency, and inaccurate stratification.

[0004] Therefore, there is an urgent need for a system and method that can accurately and efficiently detect the water-rich sections of extremely thick aquifers by using passive distributed acoustic sensing technology in the natural environment to support hydrogeological exploration, mine safety management, and sustainable utilization of water resources. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a fine detection system and method for relatively water-rich sections of aquifers based on passive distributed acoustic sensing, and solve the technical problem that the overall performance of the existing detection methods needs to be further improved.

[0006] To solve the above technical problems, the present invention is implemented by adopting the following technical solutions:

[0007] A fine detection system for relatively water-rich sections of aquifers based on passive distributed acoustic sensing, the system includes a distributed acoustic data acquisition subsystem, an armored optical cable laying device, a test casing subsystem, and a flow control and measurement device.

[0008] The system further includes a direct-through drainage borehole vertically opened on the ground, and the bottom end of the direct-through drainage borehole is connected to the underground roadway.

[0009] The distributed acoustic data acquisition subsystem is used to collect hydrodynamic acoustic signals of water from the ground to the water in the direct-through drainage borehole.

[0010] The described armored optical cable laying device is used to ensure that the armored logging optical cable is accurately laid to the predetermined depth of the borehole and record the lowering depth of the armored logging optical cable.

[0011] The described test casing subsystem is used to obtain hydrodynamic information through the dynamic acoustic waves generated by water flow.

[0012] The described flow control and measurement device is used to control and monitor the total flow rate of the direct drainage borehole.

[0013] The present invention also has the following technical features:

[0014] The described distributed acoustic wave data acquisition subsystem includes a computer terminal, a signal processor, a distributed acoustic wave sensing device, and an armored logging optical cable that are connected in sequence.

[0015] The described armored optical cable laying device includes an electric logging winch installed on the ground. The armored logging optical cable is wound on the upper disk of the electric logging winch, and a depth recorder for monitoring the lowering depth of the armored logging optical cable is also installed on the electric logging winch; a wellhead fixed pulley is installed on the ground near the orifice edge of the direct drainage borehole. The armored logging optical cable bypasses the wellhead fixed pulley and extends into the direct drainage borehole, and a counterweight is installed on the armored logging optical cable in the direct drainage borehole.

[0016] The described test casing subsystem includes a first-opening solid pipe casing installed in the direct drainage borehole. A second-opening solid pipe casing is sleeved inside the first-opening solid pipe casing. The ground at the orifice edge of the direct drainage borehole, the top end of the first-opening solid pipe casing, and the top end of the second-opening solid pipe casing are flush; the depth of the second-opening solid pipe casing is greater than that of the first-opening solid pipe casing; the part of the second-opening solid pipe casing located in the thick aquifer test section is set as a second-opening small-diameter filter water pipe casing; the bottom end of the second-opening solid pipe casing is flush with the roof interface of the underground roadway.

[0017] The described flow control and measurement device includes a mine intrinsically safe flowmeter and a stop valve. The mine intrinsically safe flowmeter is installed on the casing for protecting the wall near the bottom end of the second-opening solid pipe casing; the stop valve is also installed on the casing for protecting the wall near the bottom end of the second-opening solid pipe casing.

[0018] The present invention also protects a fine detection method for relatively water-rich layers of an aquifer based on passive distributed acoustic sensing. This method uses the fine detection system for relatively water-rich layers of an aquifer based on passive distributed acoustic sensing as described above.

[0019] Specifically, this method includes the following steps:

[0020] Step 1, borehole construction:

[0021] Construct a direct drainage borehole for testing at a selected location on the ground to the designated underground roadway for testing. In the thick aquifer test section of the direct drainage borehole, a two-opening small-diameter filter water pipe casing is used to convert the dynamic force of underground water into measurable acoustic signals. In other sections of the direct drainage borehole, a two-opening solid pipe casing is used for shaft protection, and a mine intrinsically safe flowmeter and a stop valve are installed on the two-opening solid pipe casing near the bottom end of the underground roadway.

[0022] Step Two, Optical Cable Deployment:

[0023] Use the armored optical cable deployment device to lower the armored logging optical cable to the predetermined depth of the direct drainage borehole to ensure accurate positioning of the optical cable.

[0024] Step Three, System Initialization:

[0025] Start the distributed acoustic sensing device, and set the sampling frequency, spatial sampling interval, and data storage duration of the distributed acoustic sensing device; at the same time, turn on the mine intrinsically safe flowmeter and set the sampling frequency of the mine intrinsically safe flowmeter to.

[0026] Step Four, Depth Calibration:

[0027] Precisely calibrate the entry hole depth of the armored logging optical cable through the depth recorder.

[0028] Step Five, Data Acquisition:

[0029] Collect the acoustic signals of stable water flow and the flow data at the bottom of the borehole for at least 20 minutes or more.

[0030] Step Six, Data Preprocessing:

[0031] Perform adaptive Wiener filtering denoising on the acoustic signals collected in Step Five to eliminate background noise.

[0032] Step Seven, Spectrum Feature Extraction:

[0033] Step 701, Frequency Domain Conversion:

[0034] First, use the fast Fourier transform method to perform frequency domain conversion on the time domain signal x(t) of the acoustic wave after preprocessing in Step Six to obtain the frequency domain signal X(f).

[0035] Step 702, Extraction of Spectrum Features:

[0036] Extract key spectrum features from the frequency domain signal X(f) obtained in Step 701.

[0037] The key spectrum features include the total acoustic power P band , spectrum mean μ, spectrum variance σ 2 , peak frequency f peak and spectrum centroid f c。

[0038] Step 703, Feature processing:

[0039] Fuse the key spectral features extracted in Step 702 for each frequency band to construct a comprehensive feature vector for describing the overall hydrodynamic characteristics of each aquifer section.

[0040] Step Eight, Fine stratigraphic division:

[0041] Step 801, Feature vector construction:

[0042] For the i-th sampling point, fuse the key spectral features extracted in Step 702 into the feature vector v of the i-th sampling point i ,

[0043] Step 802, Preliminary clustering:

[0044] Use K-means clustering for the preliminary division of the thick aquifer, and divide the layers with similar hydrodynamic characteristics into one category to obtain the preliminary clustering result of the division.

[0045] Step 803, Hierarchical refinement clustering:

[0046] Further refine the preliminary clustering result obtained in Step 802 using hierarchical clustering to obtain the hierarchical refinement stratification result.

[0047] Step Nine, Flow distribution inversion:

[0048] According to the hierarchical refinement stratification result obtained in Step 803, obtain the top and bottom interfaces of each aquifer, combine the acoustic wave energy characteristics in the relevant frequency band, and calculate the acoustic power distribution of each aquifer; use the mathematical model of acoustic wave energy and the water flow velocity of the water outlet, and invert the flow velocity of each aquifer through the acoustic power distribution of each aquifer; according to the relationship between the flow velocity and the flow rate, calculate the proportion of the water output of each aquifer.

[0049] Step Ten, Actual flow calculation:

[0050] Combine the flow data obtained in Step Five with the proportion of the water output of each aquifer in Step Nine to calculate the actual water flow and the specific capacity of each aquifer.

[0051] Preferably, in Step Three, the sampling frequency of the distributed acoustic wave sensing device is 1-4 kHz, the spatial sampling interval is 0.2-0.8 m, and the data storage duration is 10-30 s; the sampling frequency of the intrinsically safe mine flowmeter is 0.1-1 Hz.

[0052] Compared with the prior art, the present invention has the following technical effects:

[0053] (Ⅰ) By analyzing the hydrodynamic acoustic waves generated by the outflow of water in the direct-discharge borehole, and using the frequency and energy distribution characteristics of the acoustic wave signals, the present invention establishes a correlation model with the formation flow rate, and realizes a hydrogeological parameter testing system and method that can provide higher resolution, higher efficiency and higher precision.

[0054] (Ⅱ) By collecting the hydrodynamic acoustic wave signals generated by the outflow of water in the direct-discharge borehole from the ground to the underground, and analyzing their spectral distribution characteristics, and combining with the formation flow rate model, the present invention realizes the detection of hydrogeological parameters with high resolution and high precision, making up for the deficiencies of the prior art.

[0055] (Ⅲ) The present invention can achieve a more refined formation division: compared with the traditional method of only dividing the formation by the acoustic wave energy characteristics, the present invention adopts a more refined formation division technology. The traditional method usually relies on the overall energy distribution or the energy of the relevant frequency band of the acoustic wave signal to roughly judge the water-richness of the aquifer, and this method is often difficult to provide sufficient accuracy. Especially under the complex geological conditions of thick aquifers, misjudgment or over-simplification is likely to occur. This solution realizes a higher-precision water layer stratification and water-richness analysis by introducing spectral feature extraction and comprehensive analysis, not only relying on the energy of the acoustic wave signal, but also considering details such as frequency distribution, spectral mean, variance, peak frequency, etc. This method can accurately distinguish the hydrodynamic characteristics of different aquifer sections, overcomes the limitations of the traditional method in complex formations, provides a more refined and reliable formation division effect, and provides more scientific data support for hydrogeological exploration and water resource management.

[0056] (Ⅳ) The present invention can achieve high-precision stratified flow rate detection. Through the spectral feature analysis and flow calibration of the acoustic wave signals, the accurate division and flow rate measurement of the aquifer sections are realized, ensuring that the water flow characteristics of different sections are accurately captured.

[0057] (Ⅴ) The present invention can achieve dynamic acoustic wave monitoring and stratified inversion. Through passive acoustic wave collection and data processing, the hydrodynamic characteristics of each section can be monitored in real time, and the water output and water-richness of each section can be accurately calculated, providing reliable data support for the dynamic hydrogeological research of the aquifer.

[0058] (Ⅵ) The present invention can achieve automation and environmental friendliness. The design of the system of the present invention is suitable for automated operation, avoiding the pumping interference in the traditional method, maintaining the natural state of the formation, reducing the environmental impact, and facilitating long-term unattended monitoring work.

[0059] (Ⅶ) The present invention has good environmental adaptability. The system of the present invention can operate stably in complex geological environments. By arranging small-diameter filter water pipe casings and effective optical cable arrangements in the key aquifers of the test section, it can meet the monitoring requirements of long time and low interference, and is applicable to the prevention and control of mine water hazards and long-term hydrogeological monitoring, providing continuous support for water resource management and mine safety. Description of the Drawings

[0060] Figure 1 It is a schematic diagram of the overall structure of a fine detection system for relatively water-rich sections of aquifers based on passive distributed acoustic sensing.

[0061] Figure 2 It is the water output flow of the water-bearing layer of the extremely thick sandstone aquifer after fine division in the application example.

[0062] The meanings of the various reference numerals in the figure are as follows: 1 - Distributed acoustic data acquisition subsystem, 2 - Armored optical cable laying device, 3 - Test casing subsystem, 4 - Flow control and measurement device, 5 - Ground surface, 6 - Direct drainage borehole, 7 - Underground roadway, 8 - Test section of extremely thick aquifer.

[0063] 101 - Computer terminal, 102 - Signal processor, 103 - Distributed acoustic sensing device, 104 - Armored logging optical cable.

[0064] 201 - Electric logging winch, 202 - Depth recorder, 203 - Wellhead fixed pulley, 204 - Counterweight.

[0065] 301 - First-opening solid pipe casing, 302 - Second-opening solid pipe casing, 303 - Second-opening small-diameter filter water pipe casing

[0066] 401 - Mine intrinsically safe flowmeter, 402 - Stop valve.

[0067] The following further explains the specific content of the present invention in detail in conjunction with embodiments. Specific Embodiments

[0068] It should be noted that all the devices, algorithms, mathematical models and methods in the present invention, unless otherwise specified, all adopt the devices, algorithms, mathematical models and methods known in the prior art.

[0069] In the present invention, the thickness range of the extremely thick aquifer is 200m to 500m and above.

[0070] In the present invention, the relatively water-rich layer is divided according to the magnitude of the specific yield q: q > 10 L / (s·m) represents extremely strong water-richness; 1 < q < 10 L / (s·m) represents strong water-richness; 0.1 < q < 1 L / (s·m) represents medium water-richness; 0.01 < q < 0.1 L / (s·m) represents weak water-richness; and q < 0.01 L / (s·m) represents extremely weak water-richness.

[0071] The following are specific embodiments of the present invention. It should be noted that the present invention is not limited to the following specific embodiments, and all equivalent transformations made on the basis of the technical solution of this application fall within the protection scope of the present invention.

[0072] Embodiment 1:

[0073] This embodiment provides a fine detection system for the relatively water-rich layer section of an aquifer based on passive distributed acoustic sensing, as Figure 1 shown. The system includes a distributed acoustic data acquisition subsystem 1, an armored optical cable laying device 2, a test casing subsystem 3, and a flow control and measurement device 4.

[0074] As Figure 1 shown, the system further includes a direct-through drainage borehole 6 vertically opened on the ground 5, and the bottom end of the direct-through drainage borehole 6 is communicated with the underground roadway 7.

[0075] Specifically, the distributed acoustic data acquisition subsystem 1 is used to collect the hydrodynamic acoustic signals of the water in the direct-through drainage borehole 6 from the ground 5.

[0076] As Figure 1 shown, the distributed acoustic data acquisition subsystem 1 includes a computer terminal 101, a signal processor 102, a distributed acoustic sensing device 103, and an armored logging optical cable 104 that are connected in sequence.

[0077] In this embodiment, the computer terminal 101, the signal processor 102, and the distributed acoustic sensing device 103 all adopt the computer terminal 101, the signal processor, and the distributed acoustic sensing device known in the art. Preferably, the distributed acoustic sensing device 103 adopts a known distributed acoustic sensing system, abbreviated as DAS.

[0078] In this embodiment, the armored logging optical cable 104 is used to capture the hydrodynamic acoustic signals and convert them into backward scattering optical signals in the optical fiber core of the optical cable. The distributed acoustic sensing device 103 is used to convert the backward scattering optical signals in the optical fiber core into analog acoustic electrical signals. The signal processor 102 is used to digitize the analog acoustic electrical signals output by the distributed acoustic sensing device 103 and perform digital acoustic signal analysis. The computer terminal 101 is responsible for monitoring, operation setting, and display and storage of the acoustic characteristic signals after analysis.

[0079] Specifically, the armored optical cable laying device 2 is used to ensure that the armored logging optical cable 104 is accurately laid to the predetermined depth of the borehole and record the lowering depth of the armored logging optical cable 104.

[0080] As Figure 1 shown, the armored optical cable laying device 2 includes an electric logging winch 201 installed on the ground 5. The armored logging optical cable 104 is wound on the electric logging winch 201. A depth recorder 202 for monitoring the lowering depth of the armored logging optical cable 104 is also installed on the electric logging winch 201. A wellhead fixed pulley 203 is installed on the ground 5 near the orifice edge of the direct drainage borehole 6. The armored logging optical cable 104 bypasses the wellhead fixed pulley 203 and extends into the direct drainage borehole 6. A counterweight 204 is installed on the armored logging optical cable 104 in the direct drainage borehole 6.

[0081] In this embodiment, the electric logging winch 201 is used to control the lowering and recovery of the armored logging optical cable 104. The depth recorder 202 is used to record the lowering depth of the armored logging optical cable 104 to ensure accurate positioning. The wellhead fixed pulley 203 is used to ensure the smooth lowering of the armored logging optical cable 104 and avoid abrasion. The counterweight 204 is used to ensure the smooth lowering of the armored logging optical cable 104; keep the armored logging optical cable 104 in a vertical state and improve the measurement accuracy.

[0082] Specifically, the test casing subsystem 3 is used to obtain hydrodynamic information through the dynamic sound waves generated by water flow.

[0083] As Figure 1 shown, the test casing subsystem 3 includes a first-opening solid pipe casing 301 installed in the direct drainage borehole 6. A second-opening solid pipe casing 302 is sleeved inside the first-opening solid pipe casing 301. The ground 5 at the orifice edge of the direct drainage borehole 6, the top end of the first-opening solid pipe casing 301 and the top end of the second-opening solid pipe casing 302 are flush. The depth of the second-opening solid pipe casing 302 is greater than that of the first-opening solid pipe casing 301. The part of the second-opening solid pipe casing 302 located in the thick aquifer test section 8 is set as a second-opening small-diameter filter water pipe casing 303. The bottom end of the second-opening solid pipe casing 302 is flush with the roof interface of the underground roadway 7.

[0084] In this embodiment, a first-opening solid pipe casing 301 is used for the preliminary drilling from the ground surface 5 to the downhole test section position, providing the basic support and protection structure for drilling, preventing borehole collapse, and ensuring the safe lowering of the optical cable and monitoring equipment. The second-opening solid pipe casing 302 is used for secondary drilling and adding solid pipe casings after reaching a specific water-resisting rock layer depth, further consolidating the borehole, separating different aquifers and water-resisting layers, and ensuring the accuracy of measurement of the thick aquifer. The second-opening small-diameter filter water pipe casing 303 is used to be arranged in the thick aquifer test section 8, and the water flow power of the aquifer is converted into acoustic signals by the small-diameter filter water pipe. This design allows the borehole to be in full contact with the aquifer, and the diameter of its filter water pipe is small enough, generally 3 - 7 mm, so that the dynamic acoustic waves generated by the water flow passing through the filter water pipe are more easily captured accurately by the distributed acoustic sensing device 103.

[0085] Specifically, the flow control and measurement device 4 is used to control and monitor the total flow of the direct drainage borehole 6, ensuring accurate data collection.

[0086] As Figure 1 shown, the flow control and measurement device 4 includes a mine intrinsically safe flowmeter 401 and a stop valve 402. The mine intrinsically safe flowmeter 401 is installed at a position near the bottom end of the second-opening solid pipe casing 302; the stop valve 402 is also installed at a position near the bottom end of the second-opening solid pipe casing 302.

[0087] In this embodiment, the mine intrinsically safe flowmeter 401 is used to accurately measure the total flow of the water flowing out from the direct drainage borehole 6. The stop valve 402 is used to control the flow of water in the direct drainage borehole 6, realizing the opening, closing or adjustment of the water flow.

[0088] In this embodiment, the direct drainage borehole 6 is a drainage channel that directly guides groundwater to the roadway, used to lower the water level of the aquifer, reduce the water pressure, and enable the acquisition system to monitor the actual flow and specific capacity of the water outlet section.

[0089] Embodiment 2:

[0090] This embodiment provides a fine detection method for relatively water-rich sections of an aquifer based on passive distributed acoustic sensing. This method uses the fine detection system for relatively water-rich sections of an aquifer based on passive distributed acoustic sensing given in the above Embodiment 1.

[0091] This method includes the following steps:

[0092] Step 1, borehole construction:

[0093] At a selected position on the ground 5, a direct drainage borehole 6 for construction tests is drilled to the specified underground roadway 7. In the test section 8 of the thick aquifer in the direct drainage borehole 6, a two-opening small-diameter filter water pipe casing 303 is used to convert the dynamic force of the underground water flow into a measurable acoustic signal. In other sections of the direct drainage borehole 6, a two-opening solid pipe casing 302 is used for shaft protection, and a mine intrinsically safe flowmeter 401 and a stop valve 402 are installed on the two-opening solid pipe casing 302 near the bottom end of the underground roadway 7.

[0094] Step two, optical cable laying:

[0095] Using the armored optical cable laying device 2, slowly lower the armored logging optical cable 104 to the predetermined depth of the direct drainage borehole 6 to ensure the accurate positioning of the optical cable.

[0096] Step three, system initialization:

[0097] Start the distributed acoustic sensing device 103 (i.e., DAS, distributed acoustic sensing system), set the sampling frequency of the distributed acoustic sensing device 103 to 1 - 4 kHz, the spatial sampling interval to 0.2 - 0.8 m, and the data storage duration to 10 - 30 s; at the same time, turn on the mine intrinsically safe flowmeter 401 and set the sampling frequency of the mine intrinsically safe flowmeter 401 to 0.1 - 1 Hz.

[0098] Step four, depth calibration:

[0099] Precisely calibrate the entry hole depth of the armored logging optical cable 104 through the depth recorder 202 to ensure that the collected data corresponds to accurate depth information.

[0100] Step five, data acquisition:

[0101] Acquire the acoustic signals of the stable water flow and the flow rate data at the bottom of the borehole for at least 20 minutes or more.

[0102] Step six, data preprocessing:

[0103] Perform adaptive Wiener filtering denoising on the acoustic signals collected in step five to eliminate background noise and ensure the purity of the data.

[0104] Step seven, spectral feature extraction:

[0105] Step seven aims to analyze the performance of the acoustic signals under different geological conditions, so as to obtain important spectral information that can characterize the water-richness of the aquifer.

[0106] Step 701, frequency domain conversion:

[0107] First, use the fast Fourier transform (FFT) method to perform frequency domain conversion on the time domain signal x(t) of the acoustic wave after preprocessing in step six to obtain the frequency domain signal X(f).

[0108] In step 701, the expression of the time-domain signal x(t) represented as the frequency-domain signal X(f) is:

[0109]

[0110] Where:

[0111] j represents the imaginary unit;

[0112] f represents the frequency;

[0113] t represents the time.

[0114] In step 701, this conversion transforms the acoustic wave signal from the time domain to the frequency domain, enabling the separation of acoustic wave components of different frequencies and revealing the characteristics of the interaction between the hydrodynamic force in the aquifer and the rock formation. FFT is an efficient algorithm for achieving this frequency-domain conversion and can quickly calculate the spectrum of a discrete signal.

[0115] Step 702, extraction of spectral features:

[0116] Extract key spectral features from the frequency-domain signal X(f) obtained in step 701.

[0117] The key spectral features include the total acoustic power P band , the spectral mean μ, the spectral variance σ 2 , the peak frequency f peak and the spectral centroid f c .

[0118] In step 702, the acoustic power P(f) within the relevant frequency band is obtained by calculating the squared modulus of the frequency-domain signal X(f), i.e.: P(f) = |X(f)| 2 . For a specific frequency band from f1 to f2, calculate the total acoustic power within this frequency band This feature is used to evaluate the strength of the water flow, and the acoustic power of different frequency bands can reflect the interaction between the water flow and different geological materials.

[0119] In step 702, the spectral mean μ represents the average energy level of the spectrum, and the calculation formula is: Where N is the total number of discrete frequency points in the spectrum. The spectral mean μ is used to evaluate the overall hydrodynamic activity degree of the aquifer.

[0120] In step 702, the spectral variance σ 2 is used to measure the degree of dispersion of the spectral energy, and the calculation formula is: A larger spectral variance σ 2 usually means that the water flow distribution in the aquifer is uneven, and there may be local water-rich areas.

[0121] In step 702, the peak frequency fpeak Defined as the frequency at which the maximum power in the spectrum lies: Peak frequency f peak It reflects the main vibration characteristics when water flows through the rock formation and is a key indicator for judging the intensity of hydrodynamic activities.

[0122] In step 702, the spectral centroid f c Represents the average position of the frequency distribution, and the calculation formula is: The change in the spectral centroid can be used to judge the change in water flow velocity.

[0123] Furthermore, in step 702, data statistics and anomaly rejection need to be performed on the extracted key spectral features. The extracted key spectral features are statistically analyzed to ensure the stability of the data. Statistical indicators such as the mean and standard deviation are calculated, and the outliers caused by noise are removed. The extracted key spectral features are mean-normalized and standardized so that different features have the same scale, which is convenient for subsequent clustering and analysis.

[0124] Step 703, Feature processing:

[0125] Feature fusion is performed on the key spectral features extracted in step 702 for each frequency band to construct a comprehensive feature vector for describing the overall hydrodynamic characteristics of each aquifer section.

[0126] Step eight, Fine stratification of the formation:

[0127] Step eight is a process of stratifying the thick aquifer based on spectral features, using a combination of K-means clustering and hierarchical clustering methods to improve the accuracy and rationality of stratification.

[0128] Step 801, Feature vector construction:

[0129] For the i-th sampling point, the key spectral features extracted in step 702 are fused into the feature vector v of the i-th sampling point i ,

[0130] In step 801, the construction of the feature vector is based on the key spectral features extracted in step 702. These spectral features can accurately reflect the hydrodynamic activity characteristics of the aquifer and provide a detailed description of the intensity, distribution of the water flow, and water richness of the formation. The feature vector v i Can provide a comprehensive and accurate description for subsequent formation division and hydrogeological analysis.

[0131] Step 802, Preliminary clustering:

[0132] K-means clustering is used for the preliminary division of the thick aquifer, and the segments with similar hydrodynamic characteristics are divided into one category to obtain the preliminary clustering result.

[0133] In step 802, the goal of K-means clustering is to minimize the sum of the squared distances from each data point to its cluster center:

[0134]

[0135] In the formula:

[0136] J represents the minimized objective function;

[0137] K represents the number of clusters;

[0138] v i represents the feature vector of the i-th sampling point;

[0139] C k represents the k-th cluster;

[0140] μ k is the center of the k-th cluster.

[0141] Step 803, hierarchical refinement clustering:

[0142] The preliminary clustering result obtained in step 802 is further refined using hierarchical clustering to obtain a hierarchically refined stratification result.

[0143] In step 803, hierarchical clustering describes the clustering relationship of data by constructing a dendrogram, which can effectively refine the result of preliminary clustering and make the division of each aquifer section more accurate. By calculating the similarity (such as Euclidean distance) between clusters, data points are gradually merged or divided. The result of hierarchical clustering is presented in the form of a dendrogram, which can help engineers understand the similarities and differences between different aquifers.

[0144] Step 804, verification of the stratification result:

[0145] The stratification result obtained in step 803 is verified by a borehole histogram and matched and calibrated with the known lithology information of the formation.

[0146] Verification by borehole histogram: Compare the clustering division result with the borehole histogram to check the rationality and accuracy of the clustering division.

[0147] Matching and calibration: Match the clustering result with the known lithology information of the formation to calibrate the actual position and characteristics of each aquifer and ensure that the clustering division conforms to the actual geological conditions.

[0148] Step 805, visualization of the stratification result:

[0149] According to the clustering result, draw cross-sectional views of different sections, and use different colors to represent different water-rich sections to visually display the internal structure of the aquifer.

[0150] Step Nine, flow distribution inversion:

[0151] Based on the hierarchical refinement results of the 803 level obtained in the previous steps, the top and bottom interfaces of each aquifer are obtained. Combining the acoustic energy characteristics within the relevant frequency bands, the acoustic power distribution of each aquifer is calculated. Using the mathematical model of acoustic energy and the water outlet flow velocity, the flow velocity of each aquifer is inversed through the acoustic power distribution of each aquifer. According to the relationship between the flow velocity and the flow rate, the proportion of the water output of each aquifer is calculated.

[0152] In Step Nine, the mathematical model of acoustic energy and the water outlet flow velocity adopts the commonly known mathematical model of acoustic energy and the water outlet flow velocity in this field.

[0153] Step Ten, actual flow rate calculation:

[0154] Combining the flow rate data obtained in Step Five with the proportion of the water output of each aquifer in Step Nine, the actual water flow rate and the specific capacity of each aquifer are calculated, effectively guiding the prevention and control of mine water disasters.

[0155] Application example:

[0156] This application example presents a fine detection method for relatively water-rich layers of aquifers based on passive distributed acoustic sensing according to the above-mentioned Embodiment 2. Taking the fine detection of the relatively water-rich layer section of the ZX-1 borehole of the main vertical shaft and auxiliary vertical shaft inspection holes in Wenjiapo Mine in the eastern part of the Binchang Mining Area of the Huanglong Coalfield in China as an example, a distributed acoustic sensing (DAS) system based on TGD-OFDR is used to collect differential acoustic wave data for the ZX-1 borehole. The data acquisition device is the HiFi-DAS system of Pouniu (Shanghai) Technology Co., Ltd. Its principle is to use optical fiber as the sensing medium. Based on the optical reflectometer technology, by detecting the phase change of the Rayleigh scattered light signal, the amplitude and phase information of the acoustic wave (vibration) waveform at any position in the optical fiber can be obtained. This system is based on the principle of coherent Rayleigh scattering, using a single-mode optical cable as the front-end sensor. A laser pulse signal is continuously injected at one end of the optical cable. Utilizing the sensitivity of the optical fiber to acoustic waves (vibrations), when the hydrodynamic acoustic wave in the borehole inspection hole acts on the sensing optical fiber, the tiny deformation of the optical fiber changes the spacing and refractive index of the internal scatterers in the optical fiber, thereby causing changes in the phase and intensity of the backscattered signal. By analyzing the phase and intensity of the backscattered signal, the deformation of the optical cable caused by the hydrodynamic acoustic wave in the borehole inspection hole can be detected, and all the acoustic wave (vibration) signals of the optical cable along the borehole direction can be obtained at one time. The system has the characteristics of low noise and high fidelity throughout the length of the sensing optical fiber. Through data processing and interpretation, the relatively water-rich layer section of the extremely thick aquifer can be finely detected, providing a scientific basis for mine water prevention and control measures.

[0157] The borehole structure of this application example is shown in Table 1. Under ambient conditions, a distributed acoustic sensing device was used to monitor groundwater discharge for 4 hours. The depth of the borehole test section was 276 - 540 m, the test horizon was the Lower Cretaceous Luohe Formation (K1l), the test optical cable was lowered to a depth of 600 m, the sampling frequency of the test data was 4000 Hz, the spatial sampling interval was 0.5 m, and 1 set of data was stored every 30 s. 423 sets of effective acoustic data were obtained during the 4-hour monitoring period of borehole ZX-1, and the data size was over 238 G.

[0158] Table 1 Borehole structure of this application example

[0159]

[0160] In this application example, the water-richness distribution of the water-bearing layer after fine division of the extremely thick sandstone aquifer is as shown in the appendix. Figure 2 As can be seen from Figure 2 the test results effectively achieved the fine stratification of the extremely thick aquifer, and the stratification results had a high degree of coincidence with the borehole columnar diagram. In addition, the test results also provided the specific yield data characterizing the water-richness of each layer. According to the analysis of the water-richness distribution map, the 383 - 393 m and 442 - 508 m intervals in this embodiment belong to moderately water-rich layers, and the remaining intervals are weakly water-rich layers.

Claims

1. A fine detection system for relatively water-rich sections of aquifers based on passive distributed acoustic sensing, characterized in that, The system includes a distributed acoustic wave data acquisition subsystem (1), an armored optical cable laying device (2), a test casing subsystem (3), and a flow control and measurement device (4); The system further includes a direct drainage borehole (6) vertically drilled on the ground (5), and the bottom end of the direct drainage borehole (6) is communicated with the underground roadway (7); The described distributed acoustic wave data acquisition subsystem (1) is used to collect the hydrodynamic acoustic wave signals of the water from the ground (5) to the direct drainage borehole (6); The described armored optical cable laying device (2) is used to ensure that the armored logging optical cable (104) is accurately laid to the predetermined depth of the borehole and record the lowering depth of the armored logging optical cable (104); The described test casing subsystem (3) is used to obtain hydrodynamic information through the dynamic acoustic waves generated by the water flow; The described flow control and measurement device (4) is used to control and monitor the total flow of the direct drainage borehole (6).

2. The fine detection system for relatively water-rich aquifer sections based on passive distributed acoustic sensing according to claim 1, wherein The described distributed acoustic wave data acquisition subsystem (1) includes a computer terminal (101), a signal processor (102), a distributed acoustic wave sensing device (103), and an armored logging optical cable (104) connected in sequence.

3. The fine detection system for relatively water-rich aquifer sections based on passive distributed acoustic sensing according to claim 2, characterized in that, The described armored optical cable laying device (2) includes an electric logging winch (201) installed on the ground (5), the armored logging optical cable (104) is coiled on the electric logging winch (201), and a depth recorder (202) for monitoring the lowering depth of the armored logging optical cable (104) is also installed on the electric logging winch (201); A wellhead fixed pulley (203) is installed on the ground (5) near the orifice edge of the direct drainage borehole (6), the armored logging optical cable (104) bypasses the wellhead fixed pulley (203) and extends into the direct drainage borehole (6), and a counterweight (204) is installed on the armored logging optical cable (104) in the direct drainage borehole (6).

4. The fine detection system for relatively water-rich aquifer segments based on passive distributed acoustic sensing according to claim 3, wherein The described test casing subsystem (3) includes a first-opening solid pipe casing (301) installed in the direct drainage borehole (6), a second-opening solid pipe casing (302) is sleeved inside the first-opening solid pipe casing (301), the ground (5) at the orifice edge of the direct drainage borehole (6), the top end of the first-opening solid pipe casing (301), and the top end of the second-opening solid pipe casing (302) are flush; The depth of the second-opening solid pipe casing (302) is greater than that of the first-opening solid pipe casing (301); The part of the second-opening solid pipe casing (302) located in the extremely thick aquifer test section (8) is set as a second-opening small-diameter filter water pipe casing (303); The bottom end of the second-opening solid pipe casing (302) is flush with the roof interface of the underground roadway (7).

5. The fine detection system for relatively water-rich aquifer segments based on passive distributed acoustic sensing according to claim 4, characterized in that The described flow control and measurement device (4) includes a mine intrinsically safe flowmeter (401) and a stop valve (402), the mine intrinsically safe flowmeter (401) is installed on the protecting wall casing near the bottom end of the second-opening solid pipe casing (302); The stop valve (402) is also installed on the protecting wall casing near the bottom end of the second-opening solid pipe casing (302).

6. A fine detection method for relatively water-rich sections of aquifers based on passive distributed acoustic sensing, characterized in that, This method adopts the fine detection system for relatively water-rich layers of aquifers based on passive distributed acoustic wave sensing as described in claim 5.

7. The fine detection method for relatively water-rich aquifer segments based on passive distributed acoustic sensing according to claim 6, characterized in that, This method includes the following steps: Step 1, borehole construction: Construct a direct drainage borehole (6) for testing at a selected location on the ground (5) to the specified underground roadway (7) for testing. In the direct drainage borehole (6), in the thick aquifer test section (8), a two-opening small-diameter filter water pipe casing (303) is used to convert the dynamic force of underground water flow into measurable acoustic signals. In other sections of the direct drainage borehole (6), a two-opening solid pipe casing (302) is used for shaft protection, and a mine intrinsically safe flowmeter (401) and a stop valve (402) are installed on the two-opening solid pipe casing (302) near the bottom end of the underground roadway (7); Step two, optical cable laying: Using the armored optical cable laying device (2), lower the armored logging optical cable (104) to the predetermined depth of the direct drainage borehole (6) to ensure the accurate positioning of the optical cable; Step three, system initialization: Start the distributed acoustic sensing device (103), and set the sampling frequency, spatial sampling interval, and data storage duration of the distributed acoustic sensing device (103); at the same time, turn on the mine intrinsically safe flowmeter (401) and set the sampling frequency of the mine intrinsically safe flowmeter (401) to; Step four, depth calibration: Precisely calibrate the entry hole depth of the armored logging optical cable (104) through the depth recorder (202); Step five, data acquisition: Collect the acoustic signals of stable water flow and the flow data at the bottom of the borehole for at least 20 minutes or more; Step six, data preprocessing: Perform adaptive Wiener filtering denoising on the acoustic signals collected in step five to eliminate background noise; Step seven, spectral feature extraction: Step 701, frequency domain conversion: First, use the fast Fourier transform method to perform frequency domain conversion on the time domain signal x(t) of the acoustic wave after being preprocessed in step six to obtain the frequency domain signal X(f); Step 702, extraction of spectral features: Extract the key spectral features from the frequency domain signal X(f) obtained in step 701; The key spectral features described include the total sound power P band , the spectral mean μ, the spectral variance σ 2 , the peak frequency f peak and the spectral centroid f c ; Step 703, feature processing: Perform feature fusion on the key spectral features extracted in step 702 for each frequency band to construct a comprehensive feature vector for describing the overall hydrodynamic characteristics of each aquifer section; Step eight, fine stratification of the formation: Step 801, construction of the feature vector: For the i-th sampling point, fuse the key spectral features extracted in step 702 into the feature vector v of the i-th sampling point i , Step 802, preliminary clustering: Use K-means clustering to preliminarily divide the thick aquifer, and divide the sections with similar hydrodynamic characteristics into one category to obtain the preliminary clustering result of the division; Step 803, hierarchical refinement clustering: Use hierarchical clustering to further refine the preliminary clustering result obtained in step 802 to obtain the hierarchically refined stratification result; Step nine, inversion of flow distribution: According to the hierarchically refined stratification result obtained in step 803, obtain the top and bottom interfaces of each aquifer, and combine the acoustic wave energy characteristics in the relevant frequency band to calculate the acoustic power distribution of each aquifer; use the mathematical model of acoustic wave energy and the water flow velocity of the water outlet to invert the flow velocity of each aquifer through the acoustic power distribution of each aquifer; according to the relationship between the flow velocity and the flow rate, calculate the proportion of the water output of each aquifer; Step ten, calculation of actual flow rate: Combine the flow data obtained in step five with the proportion of the water output of each aquifer in step nine to calculate the actual water flow rate and the specific capacity of each aquifer.

8. The fine detection method for relatively water-rich aquifer segments based on passive distributed acoustic sensing according to claim 7, characterized in that In step 3, the sampling frequency of the distributed acoustic sensing device (103) is 1 - 4 kHz, the spatial sampling interval is 0.2 - 0.8 m, and the data storage duration is 10 - 30 s; the sampling frequency of the intrinsically safe mine flowmeter (401) is 0.1 - 1 Hz.

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