Pseudo-flow field method automatic data acquisition system and method and seepage flow estimation method

Abstract

The invention discloses a pseudo flow field method automatic data acquisition system and method and a seepage flow estimation method, and relates to the technical field of seepage detection.The system comprises a track, the track is erected in the directions of the two banks of a reservoir, the track is provided with a first driving device and a sliding block, and the first driving device is used for driving the sliding block to slide on the track; the second driving device is used for driving the track to move in the length direction of the shoreside of the water surface; the measuring probe is used for measuring electric potential; the measuring probe is hung below the sliding block through a connecting piece, and the length of the connecting piece is variable; and the control machine is used for receiving a signal of the measuring probe. By adopting the scheme, the measurement precision and efficiency can be improved, the cost can be reduced, and the stability and reliability of the system can be enhanced through automatic data acquisition.

Description

Technical Field

[0001] The present invention relates to the technical field of leakage detection, and in particular to a pseudo-flow field method automatic data acquisition system and method and a seepage amount estimation method. Background Art

[0002] In the field of reservoir leakage detection, the pseudo-flow field method is currently a technical means that has been verified to be feasible and effective. Its basic principle is to use a dual-frequency induced polarization instrument to arrange electrodes at the far end of the reservoir and the suspected leakage location to supply high voltage to the reservoir water, thereby forming a stable current field distribution in the water body. On this basis, by presetting the measuring lines and measuring points in the reservoir waters, technicians take a small boat with a special probe to the corresponding point, and there the probe is lifted from the bottom of the water to the top in layers. Each height interval is left to stand for about 5 seconds, and the receiver is used to measure and record the potential difference between the two ends of the probe. When there is no obvious flow in the water body, the potential difference is close to zero; in waters with seepage, the flow of water will cause the potential difference near the probe to increase significantly. Through comprehensive analysis of the measuring point data, potential leakage locations can be identified.

[0003] However, in practical applications, there are still the following problems:

[0004] 1. Inaccurate positioning and difficult measurement point control

[0005] Small boats are easily affected by wind and waves on the water, causing displacement and swaying, making the predetermined measurement point position inaccurate. The shaking of the hull and the probe not only introduces additional disturbances, which may cause secondary flow of local water bodies and affect the authenticity of potential data, but also increases the safety risks of operators in unstable water environments.

[0006] 2. Limited depth control accuracy

[0007] Currently, the interval and depth of the probe lifting are determined by marking scales on the rope. This manual method has limited accuracy, and human errors during the lifting process may cause the actual measurement position of the probe to be inconsistent with the preset depth, thereby reducing the reliability and spatial resolution of the data.

[0008] 3. Low labor costs and operational efficiency

[0009] The traditional mode usually requires at least three operators: one person is responsible for controlling the probe lifting and measuring data recording, one person is responsible for rowing to maintain the measuring point position, and another person is responsible for assisting the operation. This not only increases the manpower and cost investment, but also because each moving and static measurement takes a lot of time, making large-scale or high-density measurement point collection time-consuming and labor-intensive, and the overall efficiency is relatively low.

[0010] 4. Limited distribution and flexibility of measurement points

[0011] In the existing mode, the depth intervals of the measuring lines and measuring points are designed and collected according to a fixed mode, which requires comprehensive efficiency and coverage area. This may cause the measuring point location to be far away from the actual leakage location, making it impossible to collect abnormal data.

[0012] 5. Excessive line usage

[0013] In the current mode, the probe needs to transmit the electrical signal to the receiver through the connecting copper wire. This not only increases the consumption of a large amount of copper wire, resulting in a significant increase in costs, but also because the copper wire is easy to wear, wear and tear may cause signal transmission distortion or generate false signals, thus affecting the accuracy and reliability of the measurement data. In addition, the management and maintenance of copper wires also increase the complexity of operations and the risk of potential failures.

[0014] In summary, the current traditional operation mode still has many shortcomings, which affect the stability, accuracy and efficiency of the measurement results. Therefore, there is an urgent need for a measurement method that can improve the stability, accuracy and efficiency of the measurement results. Summary of the invention

[0015] The present invention aims to solve the deficiencies in the prior art and to provide a pseudo-flow field method automated data acquisition system and method and a seepage estimation method. By adopting this scheme, the measurement accuracy and efficiency can be improved, the cost can be reduced, and the stability and reliability of the system can be enhanced through automated data acquisition.

[0016] The present invention is achieved through the following technical solutions:

[0017] A pseudo-flow field method automatic data acquisition system, comprising:

[0018] A track, the track is set up along the two banks of the reservoir, and a first driving device and a slider are provided on the track, wherein the first driving device is used to drive the slider to slide on the track;

[0019] A second driving device, the second driving device is used to drive the track to move along the length direction of the shore of the water surface;

[0020] A measuring probe, the measuring probe is used to measure electric potential; the measuring probe is hung below the slider through a connecting piece, and the length of the connecting piece is variable;

[0021] A control machine is used to receive the signal from the measuring probe.

[0022] In view of the problems in the prior art that the traditional manual measurement method has many shortcomings such as inaccurate measurement point positioning, low measurement accuracy, and high labor costs, the present invention provides a pseudo-flow field method automatic data acquisition system, which can improve measurement accuracy and efficiency, reduce costs, and enhance the stability and reliability of the system through automatic data acquisition. In the specific scheme, it includes a track across the water surface, which can be erected along both sides of the reservoir and connected to both sides. If the strength meets the conditions, it can also be connected to one bank and extend toward the other bank to form a cantilever; the track can preferably be placed horizontally; a fixed node is set up every 10 cm on the track, and it is laid in sections; in addition, the track can be made of corrosion-resistant and wear-resistant stainless steel materials to ensure stability in a long-term water contact environment. There is a slider on the track, and the slider is driven by a first drive device to slide on the track. The stepper motor in the first drive device cooperates with a high-precision driver, and each movement of 10 cm or its multiple is accurately controlled by a control machine. As the control center, the control machine is responsible for sending forward or backward instructions, or automatically moving according to the set process, and monitoring the operating status of the stepper motor to ensure the accurate positioning of the stepper motor on the track, and recording the position information in real time as the lateral position. In addition, the second drive device can also drive the track to move as a whole to measure the potential of the entire reservoir. The measuring probe is connected to the slider through a connector, where the connector can be an electrically controlled telescopic device or a rope; driven by the connector, the measuring probe can be driven up and down to measure the potential of several points in the longitudinal direction; therefore, through the longitudinal movement of the measuring probe, the lateral movement of the slider and the overall movement of the track, the measurement accuracy and efficiency can be improved through automated data collection, the cost can be reduced, and the stability and reliability of the system can be enhanced.

[0023] A further solution, as a specific structure of the measurement probe, the measurement probe includes a sealed housing, and two external copper sheets are distributed up and down on the side wall of the sealed housing. Both of the two external copper sheets extend out of the sealed housing and are connected to a voltmeter inside the sealed housing through wires. The voltmeter is used to measure the potential difference between the two external copper sheets; the control machine is used to receive the data of the voltmeter. In this solution, the measurement probe is designed as a cylindrical sealed housing with a length of 40 cm. The sealed housing is made of waterproof, corrosion-resistant, and non-conductive materials to ensure long-term stability in the underwater environment and not interfere with the measurement results. The upper and lower ends of the measurement probe are used for potential difference measurement through external copper sheets. The copper sheets are connected to the internal voltmeter through high-conductivity wires and are covered with insulating materials for strict waterproof design. The vehicle probe is connected to the winch through a slider by a high-strength waterproof rope. The rope is stored in the winch, and the winch contains a rope pay-out measuring device to record the length of the rope retrieved. The recorded retrieved length information is transmitted into the control machine for recording. At the same time, a wireless transmission device is used in the control machine to transmit signals to the probe, so that the probe controls the built-in control switch to collect data according to the transmitted signals. The measurement probe also contains a power supply, a control switch, and a wireless transmission module inside. The voltmeter records the potential difference of the conductive copper sheets and sends it to the control machine. The data of each point can be recorded on the measuring line and converted into two-dimensional profile data. It can also be converted into three-dimensional overall data of the reservoir area according to multiple measuring lines. Wireless data transmission can also avoid the signal interference and high cost problems brought by traditional copper wire transmission.

[0024] A further solution, to meet the depth of the reservoir, the connecting member uses a rope. A winch is fixed on the slider. One end of the rope is wound around the winch, and the other end of the rope is connected to the measurement probe. Among them, a strip-shaped hole can be adopted in the chute of the track. The strip-shaped hole is a through hole, which is convenient for the rope to extend downward from the strip-shaped hole.

[0025] A further solution, the present invention also provides a collection method for an automated data collection system using the virtual flow field method, including the following steps:

[0026] S1: Set the lateral displacement parameter of the slider and the longitudinal displacement parameter of the measurement probe through the control machine;

[0027] S2: At the initial position, lower the measurement probe to the specified depth;

[0028] S3: According to the longitudinal displacement parameter, sequentially lift the measurement probe at intervals and measure the potential differences at several points in the longitudinal direction;

[0029] S4: After completing the data collection in one longitudinal direction, move the slider to the next lateral position according to the lateral displacement parameter and perform the data collection in the next longitudinal direction;

[0030] S5: repeating steps S2 to S4 until data collection of a complete cross-sectional area is completed;

[0031] S6: Then drive the track as a whole to move to the next cross-sectional area position for data collection;

[0032] S7: Repeat steps S2 to S6 until data collection of the entire reservoir area is completed.

[0033] In a further embodiment, step S3 further comprises the following specific steps:

[0034] Driving the measuring probe to be lifted at a uniform speed;

[0035] When the measuring probe moves a longitudinal displacement parameter, controlling the measuring probe to stop moving and to remain still for a certain threshold time;

[0036] A plurality of potential difference data collected by the measuring probe within the threshold time is recorded, and an average value of the plurality of potential difference data is calculated to obtain the potential difference data at the coordinate position.

[0037] In a further embodiment, the present invention also provides a method for estimating seepage volume, comprising the following steps:

[0038] Step 1: pre-process all data collected by the collection method and form a data set; the data set includes the lateral position X, longitudinal position Y and potential difference value V of each measuring point;

[0039] Step 2: converting a number of measurement points on each measurement line in the data set into a two-dimensional profile;

[0040] Step 3: After converting the two-dimensional profile of each survey line, splice the profile data of several survey lines into a three-dimensional data model;

[0041] Step 4: In the three-dimensional data model, the potential difference threshold V thresh The measuring points are set as potential leakage points, and a number of the potential leakage points are divided into a number of leakage areas by a clustering algorithm;

[0042] Step 5: In the leakage area, the flow rate of the area is estimated according to the size of the potential difference and the regional characteristics to obtain the seepage amount.

[0043] In a further embodiment, the pre-processing comprises:

[0044] Remove the measuring points whose coordinates are not in water;

[0045] Among the remaining measuring points, the longitudinal data of each measuring point is smoothed by sliding average:

[0046]

[0047] Wherein, V(i) is the potential difference data corresponding to the current position i, V filtered (i) is the processed potential difference, n is the window size, and k is the offset within the window, which controls the movement of the window.

[0048] For a further solution, the specific steps of the second step include:

[0049] For each measurement point, the horizontal position X i and the vertical depth Z i are matched with the potential difference V i to construct a data pair: (X i , Z i , V i );

[0050] Subsequently, assume that the coordinates and potential differences of n j points on a measurement line are:

[0051] Use quadratic spline interpolation to interpolate the two-dimensional profile formed by this measurement line to generate a smooth profile: Wherein, φ i (x) and ψ j (y) are spline basis functions, α ij is the interpolation coefficient, and x and y are the horizontal position and vertical depth of the measurement point;

[0052] Based on the profile function f(x, y), obtain the spatial distribution of the potential difference.

[0053] For a further solution, the specific steps of the third step include:

[0054] For two measurement lines j and j + 1, the values of their horizontal position x are respectively [X start , X end , the depth z value is [Z min , Z max , and the corresponding two-dimensional potential difference data are respectively: and

[0055] Stitch the two-dimensional data of different measurement lines in the X-axis direction to obtain a complete three-dimensional data volume, denoted as: {(X i , Y j , Z k , V ijk )}; wherein, X i is the horizontal position, Y j is the vertical position (step of the measurement line), Z k is the vertical depth, Vijk is the potential difference;

[0056] In the three-dimensional data volume, a three-dimensional spline difference is used to generate a smooth potential difference field; the three-dimensional spline difference formula is: Among them, φ i (x), ψ j (y),ξ k (z) is the spline basis function, α ijk is the interpolation coefficient, x, y, z are the horizontal position, vertical position and depth respectively;

[0057] The potential difference distribution in the reservoir area is obtained based on the three-dimensional function f(x, y, z).

[0058] In a further solution, the formula for estimating the seepage volume Q in step 5 is:

[0059]

[0060] Where k is the fluid permeability coefficient, which depends on the permeability of the soil or rock in the reservoir area; A leak is the area of ​​the leakage area; V avg is the average potential difference in the leakage region; V max is the maximum potential difference in the leakage area.

[0061] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0062] 1. The present invention provides a pseudo-flow field method automatic data acquisition system and method and a seepage estimation method. By adopting this scheme, the longitudinal movement of the measuring probe, the lateral movement of the slider and the overall movement of the track are measured, so as to improve the measurement accuracy and efficiency, reduce the cost, and enhance the stability and reliability of the system through automatic data acquisition.

[0063] 2. The present invention provides an automated data acquisition system and method using a pseudo-flow field method and a seepage estimation method. By adopting this solution, real-time data acquisition, processing and three-dimensional imaging can be achieved through wireless data transmission and remote control, thereby constructing a reservoir leakage model, and completing an automated detection solution for reservoir leakage and flow estimation through automatic delineation of the leakage area and a flow estimation calculation method. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. In the drawings:

[0065] Figure 1 A schematic diagram of the structure of the acquisition system provided by the present invention;

[0066] Figure 2 A top view of the collection system provided by the present invention;

[0067] Figure 3 A partial schematic diagram of the track provided by the present invention;

[0068] Figure 4 A schematic diagram of the structure of the measuring probe provided by the present invention;

[0069] Figure 5 A schematic diagram of the process of the collection method provided by the present invention;

[0070] Figure 6 The present invention is a flow chart of the seepage estimation method provided by the present invention.

[0071] Marks and corresponding parts names in the attached drawings:

[0072] 1-track, 101-strip hole, 2-slider, 3-measuring probe, 301-sealed housing, 302-external copper sheet, 303-voltmeter, 304-power supply, 305-wireless transmission module, 306-control switch, 4-connector, 5-control machine, 6-winder, 7-first drive device. DETAILED DESCRIPTION

[0073] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0074] Embodiment 1: This embodiment 1 provides a pseudo-flow field method automatic data acquisition system, such as Figure 1-Figure 4 As shown, including:

[0075] A track 1 is set up along the two banks of the reservoir, and a first driving device 7 and a slider 2 are provided on the track 1. The first driving device 7 is used to drive the slider 2 to slide on the track 1;

[0076] A second driving device, the second driving device is used to drive the track 1 to move along the length direction of the shore of the water surface;

[0077] A measuring probe 3, the measuring probe 3 is used to measure electric potential; the measuring probe 3 is suspended below the slider 2 through a connecting member 4, and the length of the connecting member 4 is variable;

[0078] The control machine 5 is used to receive the signal from the measuring probe 3 .

[0079] In view of the problems in the prior art that the traditional manual measurement method has many shortcomings such as inaccurate measurement point positioning, low measurement accuracy, and high labor costs, the present invention provides a pseudo-flow field method automatic data acquisition system, which can improve measurement accuracy and efficiency, reduce costs, and enhance the stability and reliability of the system through automatic data acquisition. In the specific scheme, it includes a track 1 across the water surface, and the track 1 can be set up along both sides of the reservoir and connected to both sides. If the strength meets the conditions, it can also be connected to one bank and extend toward the other bank to form a cantilever; the track 1 can preferably be placed horizontally; a fixed node is set up every 10 cm on the track 1, and it is laid in sections; in addition, the track 1 can be made of corrosion-resistant and wear-resistant stainless steel materials to ensure stability in a long-term water contact environment. There is a slider 2 on the track 1, and the slider 2 is driven by the first drive device 7 to slide on the track 1. The stepping motor in the first drive device 7 cooperates with the high-precision driver, and the control machine 5 accurately controls each movement of 10 cm or its multiples. The control machine 5, as the control center, is responsible for sending forward or backward instructions, or automatically moving according to the set process, and monitoring the operating status of the stepper motor to ensure the accurate positioning of the stepper motor on the track 1, and recording the position information in real time as the lateral position. In addition, the second drive device can also drive the track 1 to move as a whole to measure the potential of the entire reservoir. The measuring probe 3 is connected to the slider 2 through the connector 4, wherein the connector 4 can be an electrically controlled telescopic device or a rope; driven by the connector 4, the measuring probe 3 can be driven to move up and down, so as to measure the potential of several points in the longitudinal direction; therefore, through the longitudinal movement of the measuring probe 3, the lateral movement of the slider 2 and the overall movement of the track 1, the measurement accuracy and efficiency can be improved, the cost can be reduced, and the stability and reliability of the system can be enhanced through automated data collection.

[0080] In this embodiment, as a specific structure of a measuring probe 3, the measuring probe 3 includes a sealed housing 301, and the side wall of the sealed housing 301 has two external copper sheets 302 distributed up and down, and the two external copper sheets 302 extend out of the sealed housing 301 and are connected to the voltmeter 303 inside the sealed housing 301 through a wire, and the voltmeter 303 is used to measure the potential difference between the two external copper sheets 302; the control machine 5 is used to receive the data of the voltmeter 303. In this solution, the measuring probe 3 is designed as a 40 cm long cylindrical sealed housing, and the sealed housing is made of waterproof, anti-corrosion, non-conductive materials to ensure long-term stability in an underwater environment and not interfere with the measurement results. The upper and lower ends of the measuring probe 3 are used for potential difference measurement through external copper sheets 302, and the copper sheets are connected to the internal voltmeter 303 through a high-conductivity wire, and covered with insulating materials for a strict waterproof design. The vehicle probe is connected to the reel 6 through a high-strength waterproof rope through the slider 2. The rope is stored in the reel 6, and the reel 6 contains a rope pay-off metering device to record the length of the rope collected. The recorded collected length information is transmitted to the control machine 5 for recording. At the same time, a wireless transmitter is used in the control machine 5 to transmit a signal to the probe, so that the probe controls the built-in control switch 306 to collect data according to the transmission signal. The measuring probe 3 also contains a power supply 304, a control switch 306 and a wireless transmission module 305. The voltmeter 303 records the potential difference of the conductive copper sheet and sends it to the control machine 5. The data of each point on the measuring line can be recorded and converted into two-dimensional profile data, and it can also be converted into three-dimensional reservoir area overall data according to multiple measuring lines. Wireless data transmission can also avoid signal interference and high cost problems caused by traditional copper wire transmission.

[0081] In this embodiment, in order to meet the depth of the reservoir, the connecting member 4 is a rope, a reel 6 is fixed on the slider 2, one end of the rope is wound around the reel 6, and the other end of the rope is connected to the measuring probe 3. Among them, a strip hole 101 can be used in the slide groove of the track 1, and the strip hole 101 is a through hole, which can facilitate the rope to extend downward from the strip hole 101.

[0082] Embodiment 2: This embodiment 2 is further optimized on the basis of embodiment 1, such as Figure 5 As shown, a collection method of a pseudo-flow field method automatic data collection system is also provided, comprising the following specific steps:

[0083] 1. First, set the acquisition parameters in the control machine 5, including the horizontal stepping distance and the vertical acquisition depth interval. The horizontal stepping distance determines the moving range of the probe 3 on the track 1 each time, which is usually 50m; the vertical depth interval determines the vertical distance between the underwater acquisition points of the probe, for example, every 0.05 measurement, the interval can be reduced during detailed inspection.

[0084] 2. Before data collection, fix the measuring probe 3 to the slider 2 system through a high-strength waterproof rope and place it in the initial position on the slide rail, set to 0 meters. After the slide rail controller 5 is started, slowly lower the measuring probe 3 to the bottom of the reservoir, and the bottom sensor will provide real-time feedback to ensure that the measuring probe 3 safely reaches the specified depth. After touching the bottom, let it stand for 5 seconds to eliminate the shaking of the measuring probe 3 and the interference of water flow, so as to ensure the accuracy of the collected data. After touching the bottom, the wireless transmission device transmits a signal to the controller 5, recording the depth at this time as 0 meters.

[0085] 3. The measuring probe 3 is lifted uniformly from the bottom of the reservoir according to the preset longitudinal depth interval. During the lifting process, the control machine 5 transmits a signal to the measuring probe 3 according to the set distance, and the signal transmission device receives it. Then the control switch 306 is closed to collect data for 1S, and all the collected data in 0.5S are recorded and averaged. Due to the slow lifting speed of the probe, 0.5S can be defaulted to the true data value at this position, and the potential difference data at the current position is recorded and transmitted to the control machine 5 by the wireless transmission device to match the corresponding lateral position and depth coordinates.

[0086] 4. When the measuring probe 3 is lifted to the slider 2 and cannot be lifted further, a longitudinal collection process is completed at this time, and the integrity of the data collection is checked. After confirmation, the control machine 5 will move the slider 2 to the next set horizontal position, and at the same time lower the probe to the bottom of the warehouse again, and repeat the above longitudinal collection process.

[0087] 5. Move the measuring probe 3 step by step along the transverse track 1 to complete the data collection of each measuring line in turn to ensure full coverage of the cross-sectional area. After completing the collection of one measuring line, the track 1 is moved as a whole to the position of the next parallel measuring line through the slide rail controller 5, and the measurement is continued until the data collection of all measuring lines in the entire reservoir area is completed.

[0088] 6. During the acquisition process, the system detects the status of the probe and equipment in real time. If there are abnormal situations such as rope jamming and signal loss, the control system will automatically stop running and issue an alarm. At the same time, the built-in breakpoint resume function ensures that the acquired data will not be lost, which is convenient for users to continue the acquisition work after troubleshooting.

[0089] The control machine 5 in the above steps is equipped with a graphical user interface (GUI) to achieve remote control and real-time monitoring. The lateral position, longitudinal depth position and collected potential difference data are matched in the control machine 5. The data of all measured points are displayed in real time and the image is rendered according to the value. The user can check in real time to pay attention to whether there is leakage and adjust the distance of the horizontal or longitudinal collection points to narrow the scope for detailed inspection. When the survey line is completed, the measurement of the next survey line can be carried out directly. When all data collection is completed, the potential difference of the entire reservoir area can be obtained, so as to perform three-dimensional imaging to simulate the leakage state of the entire reservoir area.

[0090] Embodiment 3: This embodiment 3 is further optimized on the basis of embodiment 2, such as Figure 6 As shown, a method for estimating seepage volume is provided, comprising the following specific steps:

[0091] 1. Data preprocessing: If the data collected is not in water, the measured value is a flying value. The first step is to delete all flying values. Then smooth the longitudinal data of each measuring point by sliding average:

[0092]

[0093] Where V(i) is the potential difference data corresponding to the current position i, V filtered (i) is the potential difference after processing, n is the window size, and k is the offset within the window, which controls the movement of the window.

[0094] 2. The preprocessed data set includes the potential difference value V and the corresponding lateral position X and longitudinal depth Z. The position of each measuring point has been determined. Now it needs to be converted into a two-dimensional profile for further analysis, including:

[0095] 2.1 Horizontal and vertical data matching: For each measuring point, the horizontal position X i and longitudinal depth Z i With potential difference V i Match and build data pairs:

[0096] (X i ,Z i ,V i );

[0097] 2.2 Two-dimensional interpolation profile generation: On the same survey line j, a smooth potential difference distribution can be generated by interpolation. Assume that n on a survey line j The coordinates and potential difference of each point are:

[0098]

[0099] Use quadratic spline interpolation to interpolate the two-dimensional profile formed by the survey line to generate a smooth profile:

[0100]

[0101] where φ i (x) and ψ j (y) is the spline basis function, α ij is the interpolation coefficient, x and y are the lateral position and longitudinal depth of the measuring point. The obtained profile function f(x,y) is the spatial distribution of the potential difference.

[0102] 3. 3D data volume splicing and fusion: After completing the 2D profile data of each survey line, the next step is to splice the profile data of different survey lines into a 3D data set, so that the potential difference distribution of the entire reservoir area can be displayed. Specifically including:

[0103] 3.1 Splicing survey line data: For two survey lines j and j+1, the values ​​of their lateral positions x are [X start ,X end ], the depth z is [Z min ,Z max ], since the reservoir bottom is not smooth but undulating, and the distance between the two banks is not the same, then [X start ,X end ] and [Z min ,Z max ] are all different. Their corresponding two-dimensional potential difference data are:

[0104] and The two-dimensional data of different survey lines are spliced ​​in the X-axis direction to obtain a complete three-dimensional data volume, which is recorded as:

[0105] {(X i ,Y j ,Z k ,V ijk )};

[0106] Among them, X i is the horizontal position, Y j is the longitudinal position (stepping of the line), Z k is the vertical depth, V ijk is the potential difference.

[0107] 3.2 Three-dimensional interpolation to generate potential difference field: For the spliced ​​data body, three-dimensional spline interpolation can be used to generate a smooth potential difference field. The three-dimensional spline interpolation formula is:

[0108]

[0109] where φ i (x), ψj (y),ξ k (z) is the spline basis function, α ijk is the interpolation coefficient, x, y, z are the horizontal position, vertical position and depth respectively. The obtained three-dimensional function f(x, y, z) is the potential difference distribution in the reservoir area.

[0110] 4. Leak point identification and flow estimation.

[0111] 4.1 Abnormal potential difference detection: By setting a potential difference threshold V thresh , we first identify the points with abnormal potential difference. If the potential difference of a certain measuring point exceeds the threshold V thresh , then the point is considered to be a potential leakage point.

[0112] V thresh =μ+k·σ;

[0113] Where μ is the mean of the potential difference, σ is the standard deviation, and k is an empirical coefficient

[0114] 4.2 Leakage area identification: After identifying a single leakage point, it is divided into "multiple leakage areas" or "single point noise". For this purpose, the clustering algorithm DBSCAN is used to identify the leakage area. DBSCAN (density clustering algorithm) can automatically identify adjacent abnormal points and classify them as a leakage area. The core idea of ​​the DBSCAN algorithm is to cluster according to the density of points, and the parameters are defined as: ε: distance threshold, used to determine whether two points are within each other's neighborhood. MinPts: the minimum number of neighbors required to determine whether a point is a core point.

[0115] Using Euclidean distance:

[0116]

[0117] In the formula, (x i ,y i ,z i ) is the coordinate of point p in three-dimensional space; (x j ,y j ,z j ) is the coordinate of point q in three-dimensional space; d(p,q) is the Euclidean distance between p and q.

[0118] Neighborhood: For any point p, its ε-neighborhood is defined as:

[0119] N ε (p) = {q∈V abnormal |d(p,q)≤ε};

[0120] Where N ε(p): The ε-neighborhood of point p, which represents the set of all “outlier points” whose distance to p in three-dimensional space does not exceed ε. V abnormal : The data set where the outlier point is located; d(p,q): Euclidean distance function; ε: Neighborhood radius, that is, the set distance threshold. Point q is considered to be a neighbor of point p only when the distance does not exceed ε.

[0121] Point type judgment:

[0122] Core Point: If the size of the neighborhood of p is not less than MinPts, that is, |N ε (p)|≥MinPts, then p is the core point;

[0123] Border Point: If p does not meet the core point condition, but p falls within the neighborhood of a core point, then p is a border point;

[0124] Noise Point: If p is neither a core point nor in the neighborhood of any core point, it is considered a noise point.

[0125] Finally, a leakage area is formed with the core point as the center and surrounded by boundary points.

[0126] 4.3 Flow estimation in leakage area: Identify the leakage area and estimate the flow in the area based on the size of the potential difference and regional characteristics. Flow estimation requires the relationship between potential difference and fluid flow.

[0127] The basic idea of ​​estimating flow is that the greater the potential difference in the seepage area, the stronger the water penetration capacity in the area, and the greater the flow rate. The flow rate can be inferred by combining the potential difference with the geometric characteristics of the flow area (such as the permeable area).

[0128] (1) Calculation of the area of ​​the leakage area: First calculate the area A of the leakage area leak , is calculated by the spatial distribution of the leakage area after clustering. Assume that the point set in the area m is the total number of points in the region, and the outer enclosing area of ​​the region is calculated by fitting.

[0129] (2) Relationship between potential difference and flow rate: Assuming the potential difference V avg is the average value of the potential difference in the leakage area, and the flow rate Q can be estimated using the following formula:

[0130]

[0131] Where: k is the fluid permeability coefficient, which depends on the soil or rock permeability of the reservoir area; A leak is the area of ​​the leakage region; V avg is the average potential difference in the leakage region; Vmax is the maximum potential difference in the leakage area.

[0132] The flow rate calculated as above can represent the amount of permeation or the strength of the permeation capacity to determine the leakage status.

[0133] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. The automatic data acquisition system of pseudo-flow field method is characterized by: include: A track (1), the track (1) being erected along the two banks of the reservoir, the track (1) being provided with a first driving device (7) and a slider (2), the first driving device (7) being used to drive the slider (2) to slide on the track (1); A second driving device, the second driving device is used to drive the track (1) to move along the length direction of the shore of the water surface; A measuring probe (3), the measuring probe (3) being used to measure electric potential; the measuring probe (3) is suspended below the slider (2) via a connecting piece (4), and the length of the connecting piece (4) is variable; A control machine (5), the control machine (5) is used to receive the signal of the measuring probe (3).

2. The automatic data acquisition system of the pseudo-flow field method according to claim 1 is characterized in that: The measuring probe (3) comprises a sealed housing (301), the side wall of the sealed housing (301) being provided with two external copper sheets (302) distributed up and down, the two external copper sheets (302) both extending out of the sealed housing (301) and connected to a voltmeter (303) inside the sealed housing (301) via a wire, the voltmeter (303) being used to measure the potential difference between the two external copper sheets (302); The control machine (5) is used to receive data from the voltage meter (303).

3. The automatic data acquisition system of the pseudo-flow field method according to claim 1 is characterized in that: The connecting member (4) is a rope, a wire reel (6) is fixed on the slider (2), one end of the rope is wound around the wire reel (6), and the other end of the rope is connected to the measuring probe (3).

4. The acquisition method of the pseudo-flow field method automatic data acquisition system according to any one of claims 1 to 3, characterized in that: The following steps are involved: S1: setting the lateral displacement parameters of the slider (2) and the longitudinal displacement parameters of the measuring probe (3) through a control machine; S2: At the initial position, lowering the measuring probe (3) to a specified depth; S3: lifting the measuring probe (3) in sequence at intervals according to the longitudinal displacement parameter, and measuring the potential difference at a plurality of points in the longitudinal direction; S4: after completing data collection in one longitudinal direction, the slider (2) is moved to the next transverse position according to the transverse displacement parameter, and data collection in the next longitudinal direction is performed; S5: repeating steps S2 to S4 until data collection of a complete cross-sectional area is completed; S6: then driving the track (1) as a whole to move to the next cross-sectional area position for data collection; S7: Repeat steps S2 to S6 until data collection of the entire reservoir area is completed.

5. The acquisition method of the pseudo-flow field method automatic data acquisition system according to claim 4, characterized in that: The step S3 also includes the following specific steps: driving the measuring probe (3) to be lifted at a uniform speed; When the measuring probe (3) moves a longitudinal displacement parameter, controlling the measuring probe (3) to stop moving and to remain stationary for a certain threshold time; A plurality of potential difference data collected by the measuring probe (3) within the threshold time is recorded, and an average value of the plurality of potential difference data is calculated to obtain the potential difference data at the coordinate position.

6. A method for estimating seepage volume, characterized in that: The following steps are involved: Step 1: pre-process all data collected by the collection method described in claim 4 or 5 to form a data set; the data set includes the lateral position X, longitudinal position Y and potential difference value V of each measuring point; Step 2: converting a number of measurement points on each measurement line in the data set into a two-dimensional profile; Step 3: After converting the two-dimensional profile of each survey line, splice the profile data of several survey lines into a three-dimensional data model; Step 4: In the three-dimensional data model, the potential difference threshold V thresh The measuring points are set as potential leakage points, and a number of the potential leakage points are divided into a number of leakage areas by a clustering algorithm; Step 5: In the leakage area, the flow rate of the area is estimated according to the size of the potential difference and the regional characteristics to obtain the seepage amount.

7. The method for estimating seepage volume according to claim 6, characterized in that: The pre-processing comprises: Remove the measuring points whose coordinates are not in water; Among the remaining measuring points, the longitudinal data of each measuring point is smoothed by sliding average: Where V(i) is the potential difference data corresponding to the current position i, V filtered (i) is the potential difference after processing, n is the window size, and k is the offset within the window, which controls the movement of the window.

8. The method for estimating seepage volume according to claim 6, characterized in that: The specific steps of step 2 include: For each measuring point, the lateral position X i and longitudinal depth Z i With potential difference V i Match and build data pairs: (X i ,Z i ,V i ); Then assume that n j The coordinates and potential difference of each point are: Use quadratic spline interpolation to interpolate the two-dimensional profile formed by the survey line to generate a smooth profile: In the formula, φ i (x) and ψ j (y) is the spline basis function, α ij is the interpolation coefficient, x and y are the lateral position and longitudinal depth of the measuring point; Based on the profile function f(x, y), the spatial distribution of the potential difference is obtained.

9. The method for estimating seepage volume according to claim 6, characterized in that: The specific steps of step three include: For two measuring lines j and j+1, the values ​​of their lateral positions x are [X start ,X end ], the depth z is [Z min ,Z max ], and the corresponding two-dimensional potential difference data are: and The two-dimensional data of different survey lines are spliced ​​in the X-axis direction to obtain a complete three-dimensional data volume, which is recorded as: i ,Y j ,Z k ,V ijk )}; where X i is the horizontal position, Y j is the longitudinal position (stepping of the line), Z k is the vertical depth, V ijk is the potential difference; In the three-dimensional data volume, a three-dimensional spline difference is used to generate a smooth potential difference field; the three-dimensional spline difference formula is: Among them, φ i (x), ψ j (y),ξ k (z) is the spline basis function, α ijk is the interpolation coefficient, x, y, z are the horizontal position, vertical position and depth respectively; The potential difference distribution in the reservoir area is obtained based on the three-dimensional function f(x, y, z).

10. The method for estimating seepage volume according to claim 6, characterized in that: The formula for estimating the seepage volume Q in step 5 is: Where k is the fluid permeability coefficient, which depends on the permeability of the soil or rock in the reservoir area; A leak is the area of ​​the leakage area; V avg is the average potential difference in the leakage region; V max is the maximum potential difference in the leakage area.

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