CN113092702A - Water body pollution detection method based on ground penetrating radar-seismic wave amplitude attribute - Google Patents
Water body pollution detection method based on ground penetrating radar-seismic wave amplitude attribute Download PDFInfo
- Publication number
- CN113092702A CN113092702A CN202110369711.6A CN202110369711A CN113092702A CN 113092702 A CN113092702 A CN 113092702A CN 202110369711 A CN202110369711 A CN 202110369711A CN 113092702 A CN113092702 A CN 113092702A
- Authority
- CN
- China
- Prior art keywords
- data
- ground penetrating
- penetrating radar
- model
- reflection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000000149 penetrating effect Effects 0.000 title claims abstract description 50
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 49
- 238000001514 detection method Methods 0.000 title claims abstract description 16
- 239000007788 liquid Substances 0.000 claims abstract description 70
- 239000008346 aqueous phase Substances 0.000 claims abstract description 42
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000012360 testing method Methods 0.000 claims abstract description 16
- 238000004458 analytical method Methods 0.000 claims abstract description 14
- 239000004576 sand Substances 0.000 claims description 41
- 239000000463 material Substances 0.000 claims description 20
- 238000012545 processing Methods 0.000 claims description 14
- 238000004088 simulation Methods 0.000 claims description 14
- 239000002689 soil Substances 0.000 claims description 14
- 230000008859 change Effects 0.000 claims description 8
- 238000012880 independent component analysis Methods 0.000 claims description 8
- 230000004044 response Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 7
- 238000011160 research Methods 0.000 claims description 6
- 239000003673 groundwater Substances 0.000 claims description 4
- 230000005284 excitation Effects 0.000 claims description 3
- 238000013178 mathematical model Methods 0.000 claims description 3
- 239000002184 metal Substances 0.000 claims description 3
- 239000011435 rock Substances 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 238000011426 transformation method Methods 0.000 claims description 2
- 239000000126 substance Substances 0.000 abstract description 5
- 238000003911 water pollution Methods 0.000 abstract description 3
- 238000002474 experimental method Methods 0.000 description 5
- 230000007423 decrease Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 239000012071 phase Substances 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000009545 invasion Effects 0.000 description 2
- 238000009533 lab test Methods 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 230000010287 polarization Effects 0.000 description 2
- KJCVRFUGPWSIIH-UHFFFAOYSA-N 1-naphthol Chemical compound C1=CC=C2C(O)=CC=CC2=C1 KJCVRFUGPWSIIH-UHFFFAOYSA-N 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000002547 anomalous effect Effects 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006065 biodegradation reaction Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000000356 contaminant Substances 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 239000011707 mineral Substances 0.000 description 1
- 150000007524 organic acids Chemical class 0.000 description 1
- 235000005985 organic acids Nutrition 0.000 description 1
- 239000011368 organic material Substances 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 230000007903 penetration ability Effects 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000002310 reflectometry Methods 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000004083 survival effect Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- 238000009736 wetting Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Radar, Positioning & Navigation (AREA)
- Chemical & Material Sciences (AREA)
- Health & Medical Sciences (AREA)
- Electromagnetism (AREA)
- Theoretical Computer Science (AREA)
- Geophysics (AREA)
- Computer Hardware Design (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- General Engineering & Computer Science (AREA)
- Geometry (AREA)
- Computer Networks & Wireless Communication (AREA)
- Evolutionary Computation (AREA)
- Environmental & Geological Engineering (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
本发明涉及检测方法，具体是一种基于探地雷达‑地震波振幅属性的水体污染检测方法,从理论上证明了低导电性非水相液体对水的侵入是如何改变反射图样的；将此模型应用于探地雷达‑地震波振幅属性数据进行实际测试；研究表明了非水相液体的性质与相对介电常数或孔隙率之间的相关性，并根据所得结果提出了概念模型；使用了与探地雷达‑地震波振幅属性分析相关的不同技术；生成了一个概念模型，并提供了清晰的证据来证明所获取的数据的反射模式是如何随着非水相液体的入侵而突然改变的；反射模式与概念模型相比，随着不同物质的侵入，反射模式有相似的变化；确定了相对介电常数与深度和速度之间的趋势关系，验证所得结果。
The invention relates to a detection method, in particular to a water pollution detection method based on a ground penetrating radar-seismic wave amplitude attribute, which theoretically proves how the intrusion of a low-conductivity non-aqueous phase liquid to water changes a reflection pattern; Applied to ground penetrating radar-seismic wave amplitude property data for practical testing; studies have shown the correlation between properties of non-aqueous liquids and relative permittivity or porosity, and conceptual models have been developed based on the results obtained; Different techniques related to ground-radar-seismic amplitude property analysis; a conceptual model was generated and clear evidence was provided of how the reflection pattern of the acquired data changed abruptly with the intrusion of non-aqueous liquids; the reflection pattern Compared with the conceptual model, the reflection pattern changes similarly with the intrusion of different substances; the trend relationship between relative permittivity and depth and velocity is determined, validating the obtained results.
Description
Technical Field
The invention relates to a detection method, in particular to a water body pollution detection method based on a ground penetrating radar-seismic wave amplitude attribute.
Background
Water is vital to human survival. Non-aqueous phase liquids (NAPLs) are one of the major factors responsible for water pollution. Geophysical methods play an important role in determining areas and aquifers that contain contaminated water.
Theoretical modeling is a tool to determine the feasibility of geophysical exploration. According to the amplitude attribute of the ground penetrating radar-seismic wave, theoretical modeling is carried out on the non-aqueous phase liquid polluted site containing wet sand. In the simulation, the reflectivity varied significantly with the water and non-aqueous liquid content. The introduction of wet and dry sand into the model creates two main phenomena: first, the change of the wave pattern; the second is a change in amplitude. Research results show that the moisture content in the non-aqueous phase liquid can be effectively detected by the ground penetrating radar-seismic wave amplitude attribute analysis.
There are two types of non-aqueous liquids: light weight, less density than water, floating on the water surface; heavy, with a density greater than water, penetrates down the fractures in the formation to the water barrier. The non-polar fluid is low dielectric constant. A high conductivity plume of light non-aqueous liquid may occur when biodegradation of the non-aqueous liquid produces organic acids that then dissolve mineral particles in the formation, resulting in an increase in dissolved solids content. The free phase non-aqueous phase liquid maintains low conductivity and low dielectric constant. The georadar wavefield is polarized, if acquired in end-to-end mode (similar to SV waves in seismology), can be polarized on a plane; if obtained in broadside mode (similar to SH waves), polarization can be perpendicular to the plane. Depending on the design and polarization of the antenna, there is significant angle-dependent radiation, which may be one of the more challenging aspects of the georadar-seismic wave amplitude properties, since it also depends on the electrical properties of the near field. The radar amplitude may also be affected by other factors.
Disclosure of Invention
The invention aims to provide a water body pollution detection method based on a ground penetrating radar-seismic wave amplitude attribute, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a water body pollution detection method based on ground penetrating radar-seismic wave amplitude attributes comprises the following steps:
theoretical modeling, namely respectively placing a seismic source and an output point in a model through excitation and output, summarizing the geometric structure of the model, and simulating heterogeneous soil with a rough surface, a ground penetrating radar antenna model, a simulated metal target and rock in the model;
establishing a physical model, confirming an approximate result in theoretical research, and providing a theory about a data reflection mode of the ground penetrating radar;
driving factors influencing groundwater detection, including water content, modeling a given material, calculating the relative dielectric constant of the light non-aqueous phase liquid, drawing the relation between the values and the sum of depths, and analyzing the variation trend of the dielectric constant along with the depths;
combining the reflection mode with the non-aqueous phase liquid abnormity, and processing the ground penetrating radar signal by adopting independent component analysis; applying ICA to ground penetrating radar simulation data by performing three-component analysis on a reflection mode of ground penetrating radar-seismic wave amplitude attribute data;
step five, each material is reflected independently, and the difference of the reflection modes is identified by using the frequency;
and sixthly, reflecting the seismic wave amplitude attribute response, using a 500MHZ frequency plate transmitting antenna, and recording data of three stages.
As a further scheme of the invention: the theoretical model building is to define model parameters by using a file, and the simulation needs a total model to image the whole space; three materials, water, sand and light non-aqueous liquid, were inserted in the same model and the relative reflection intensity of each dataset was calculated.
As a still further scheme of the invention: the calculation of the relative reflection intensity of the data set comprises the steps of firstly calculating all record tracks of the center of the model corresponding to the position of the simulation model, and then calculating the envelope function of the calculated tracks; selecting the maximum amplitude of the envelope function within a gating time window centered on a reflection point of the simulated reflection event; finally, the percent increase in reflection intensity for the three models was determined by comparing the synthetic control of the non-simulated light non-aqueous phase liquid and the simulated light non-aqueous phase liquid.
As a still further scheme of the invention: the step two comprises the following parts:
s1, data acquisition, wherein the test is carried out in a geophysical simulation laboratory, sandy soil with the same water content is filled in a test box, and then a vector network analyzer is connected with 500MHZ and 1000MHZ antennas for exploration; collecting data of the ground penetrating radar by adopting a fixed antenna spacing; for the ground penetrating radar-seismic wave amplitude attribute analysis, a common center point mode is adopted; in the mode of common center point, the antenna moves according to proportion for each offset, and all target areas are marked in the middle of the test box;
s2, data processing, before actual processing, encoding each row to generate a radar map of the original data to verify whether the proposed theory is valid for the original data; introducing the data into a time domain by adopting a fast Fourier inverse transformation method; establishing a double-layer mathematical model of the change of the dielectric constant of the upper sand from low to high;
s3, using two kinds of software to process the data set, converting the data into the format required by the software; using 32-bit floating points and a step size of zero, a time increment of 1ns, an acquisition duration of 500ns, which is the actual time required to acquire the data.
As a still further scheme of the invention: in the sixth step, firstly, collecting data of dry sand to obtain three-line data covering the whole experiment pool, then invading the experiment pool by using light non-aqueous phase liquid, combining all measuring lines in the process of software processing, processing the data, marking a target area and obtaining a complete reflection mode.
Compared with the prior art, the invention has the beneficial effects that: this method shows, through strong evidence, that the reflection patterns of different materials (such as sand and water) are different when detecting non-aqueous liquids of low conductivity; the method is characterized in that the method firstly demonstrates the point theoretically and then is practically verified through laboratory experiments; if the frequency is reduced below 500MHz, more accurate results can be obtained; the relative permittivity is the decisive evidence that the light non-aqueous phase liquid is present underground, while the reflection mode confirms the presence of the light non-aqueous phase liquid; therefore, if the light non-aqueous phase liquid is easily detected by a ground penetrating radar-seismic wave amplitude attribute analysis method, serious consequences caused by pollution of the light non-aqueous phase liquid can be avoided.
Drawings
FIG. 1 is a theoretical model diagram of sand-containing, water-containing sandy soil and light non-aqueous phase liquid established using a ground penetrating radar Max-2D.
FIG. 2 is a graph of the use of a ground penetrating radar Max-2D on (a) sandy soil, (b) sandy soil aqueous, and (c) sandy soil aqueous and light non-aqueous liquid.
FIG. 3 is a graph showing treatment data using 500MHZ and 1000MHZ frequencies, comprising (a) and (d) dry sand, (b) and (e) hydrous sand, and (c) and (f) hydrous sand, and light non-aqueous liquid intrusion, respectively, for a target area in an experimental pond.
Fig. 4 is a graph of the relative permeability as a function of depth.
FIG. 5 is a diagram of a total subsurface reflection pattern for a target anomaly region using ground penetrating radar-seismic amplitude attribute data.
FIG. 6 is a plot of 3 independent reflection patterns of a target anomaly region using ground penetrating radar-seismic amplitude attribute data at a frequency of 500 MH.
FIG. 7 is a graphical representation of dry sand, light non-aqueous phase liquid, water reflection.
FIG. 8 is a study of dry sand, light non-aqueous liquid, water reflectance.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In addition, an element of the present invention may be said to be "fixed" or "disposed" to another element, either directly on the other element or with intervening elements present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not denote a unique embodiment.
Referring to fig. 1 to 8, in an embodiment of the present invention, a method for detecting water pollution based on a ground penetrating radar-seismic wave amplitude attribute includes the following steps:
theoretical modeling, namely respectively placing a seismic source and an output point in a model through excitation and output, summarizing the geometric structure of the model, and simulating heterogeneous soil with a rough surface, a ground penetrating radar antenna model, a simulated metal target and rock in the model;
wherein, the theoretical model building uses an ASCII (text information interchange) file to define the model parameters, and can be simulated in ground penetrating radar Max2D and 3D programs, and the simulation needs a total model (a scanning) to image the whole space;
table 1 gives the key parameters of the simulation, as follows:
modeling parameter of ground penetrating radar Max-2D for calculating model
In addition, three materials are inserted into the same model; the model comprises a 2m wide pool of sand, water, and a light non-aqueous liquid at an average depth of about 150 mm; the electrical properties of the system are preset as follows: the model is similar to the design diagram shown in figure 1, wherein epsilon r is 6, and sigma is 0.01 s/m;
calculating the relative reflection intensity of each data set, specifically, firstly, calculating all record tracks of the model center corresponding to the position of the simulation model, and then calculating the envelope function of the calculated track; selecting a maximum amplitude of the envelope function within a gating time window centered on a reflection point of the simulated reflection event; finally, determining the percentage increase of the reflection intensity of the three models by comparing the synthetic control of the non-simulated light non-aqueous phase liquid and the simulated light non-aqueous phase liquid;
through seismic wave amplitude attribute analysis, the change of the amplitude along with the offset is researched; the first part of FIG. 2 shows the B-scan results of the (E _ z) field component; the initial part of the signal (0.9-1.2ns) represents the direct wave from the transmitter to the receiver, and then the reflected wave from the sand layer (1.4-1.6ns) forms the reflecting layer;
the first part in fig. 2 shows a slight reaction with two changes, two events can be observed, one being the same (0.9-1.2ns) sand layer (1.5-1.7ns) which is the same, due to shifting of the green sand layer and invasion of the light non-aqueous liquid;
the third part of fig. 2 shows the parabolic pattern and weak reflections in the model using water, sand and light non-aqueous liquid, and events due to intrusion of the non-aqueous liquid layer into the model can be seen (1.9-2.7 ns);
establishing a physical model, confirming an approximate result in theoretical research, and providing a theory about a data reflection mode of the ground penetrating radar; the method comprises the following steps:
s1, collecting data, and performing a test in a geophysical simulation laboratory, wherein the test box is filled with sandy soil with the same water content, and the total length of the water tank is about 10 meters, wherein the test is performed only by 3-4 meters; the width of the water tank is about 1m, and the full width of the water tank is utilized; also, the total depth of the tank is close to 1.2m, the depth used is about 1 m; the first layer consists of 7cm of fine sand, the second layer is 16cm thick, and the water content of the second layer is about 30% when only water exists; in the same layer, a pit of about 20cm by 20cm is dug, and the aquifer is polluted by naphthol which is commercially available and exists in different chemical substances; the bottom is 14 cm of dry sand; then, a vector network analyzer is connected with 500MHZ and 1000MHZ antennas for exploration, and the exploration results are shown in the following table;
ground penetrating radar data acquisition parameter
Collecting data of the ground penetrating radar by adopting a fixed antenna spacing; for the ground penetrating radar-seismic wave amplitude attribute analysis, a common center point mode is adopted; in the mode of common center point, the antenna moves according to proportion for each offset, and all target areas are marked in the middle of the test box;
this region was further used to focus the reflection pattern of all materials used in the experiment: dry sand, water and a light non-aqueous liquid; the antenna with single frequency is not used, but different antennas are connected in the detection process; in the common center point mode detection, the signal generator is a 1000MHZ antenna, and the signal receiving uses a lower 500MHZ antenna, so that the image quality is good and the resolution is high;
s2, data processing, before the actual processing of the data, using MATLAB program to encode each line, generating a radar map of the original data, so as to verify whether the proposed theory is effective to the original data; the frequencies used in the experiment can be clearly distinguished between 500MHZ and 1000 MHZ; the data recording of the vector analyzer is carried out in a frequency domain, so that the vector analyzer can only work on a larger frequency domain, and in order to extract data, a fast Fourier inversion method is adopted to introduce the data into a time domain;
the visualization of seismic wave amplitude attribute response is realized by utilizing an MATLAB program; according to the measured data, a double-layer mathematical model of the change of the dielectric constant of the upper sand from low to high is established; when more water and light non-aqueous phase liquid are cut, the seismic wave amplitude attribute response is more obvious;
with particular reference to fig. 3, when the first portion of fig. 3 is reached, the curve will reach a very steep slope; in the comprehensive modeling, the seismic wave amplitude attribute response of water and light non-aqueous phase liquid is more obvious;
although the obtained result is not conclusive and further processing is needed to be carried out on the ground penetrating radar data, the preprocessing result shows that the ground penetrating radar-seismic wave amplitude attribute data analysis is a powerful and practical tool in the fields of environment and applied geophysics; furthermore, differences in results can be attributed to differences in frequency of use; the optimal frequency of the field test can be further provided;
s3, processing the data set using two types of software, including reflexw2D and 3D software and ground penetrating radar slices; converting the data into a format required by the software; using 32-bit floating points and the step length is zero, the time increment is 1ns, the acquisition duration is 500ns, and the time is the actual time required for acquiring data;
driving factors influencing groundwater detection, including water content, modeling a given material, calculating the relative dielectric constant of the light non-aqueous phase liquid, drawing the relation between the values and the sum of depths, and analyzing the variation trend of the dielectric constant along with the depths;
wherein, the following formula is adopted for calculating the relative dielectric constant of the light nonaqueous phase liquid:
wherein
Is porosity, SNAPLIs the saturation degree of the light non-aqueous liquid, and epsilon is the relative dielectric constant of the non-aqueous liquidmIs the relative dielectric constant, epsilon, of the sand matrixwIs the relative dielectric constant of water or air; different materials have different dielectric constants, sand is no exception; the intrusion of any other material, such as sand under investigation, affects the relative permittivity of the material; the dielectric constant of the dry sand is between 3 and 7; part (1) in fig. 4 refers to a portion where dry sand exists; the relative dielectric constant of the wet sand or the saturated sand is between 20 and 30; part (2) of fig. 4 shows a region having such a material, the relative dielectric constant of which varies between 21 and 26 when any chemical substance other than the organic material invades the material, and part (3) of fig. 4 is marked as a region where a chemical substance called a non-aqueous liquid exists;
step four, combining the reflection mode with the non-aqueous phase liquid abnormity, and processing the ground penetrating radar signal by adopting Independent Component Analysis (ICA); by performing three-component analysis on the reflection mode of the ground penetrating radar-seismic wave amplitude attribute data, all uncertainty related to an actual target can be compensated; with this method, independent component analysis can easily extract the signal of each component; applying ICA to ground penetrating radar simulation data;
FIG. 5 shows a three-component reflection pattern obtained by modeling and experimental observation using a time domain finite difference method; processing a two-layer structure with a rough interface below the horizontal ground; after interpreting clutter and its relationship to reflection patterns, comparing the three component results with the theoretical results previously presented in the theoretical section of fig. 5, it was concluded that reflection patterns that vary with the intrusion of light non-aqueous liquids are common in both theoretical and practical studies;
step five, each material is reflected independently, and the difference of the reflection modes is identified by using the frequency; firstly, collecting data of dry sand, and then collecting data of sand with water invasion and light non-aqueous phase liquid; significant differences in the reflection patterns for each data set were observed; the details of the reflection mode are shown in fig. 6 and are divided into three sections (a, b, c): a is the reflection pattern of dry sand, b is the reflection pattern of sand with water, c is the reflection pattern of sand invaded by light non-aqueous phase liquid; it is evident from the figure that there is a significant difference in reflection pattern for the intrusion of light non-aqueous liquids, and that, considering the theoretical part, the figure also shows the individual reflection patterns for different materials intruding into the sandy soil; thus, these individual reflection modes are a clear proof of the theoretical part;
seismic wave amplitude attribute acquisition and processing enables us to determine significant changes in seismic and ground penetrating radar data reflection patterns. The technology proves that the amplitude attribute of the ground penetrating radar-seismic wave is a direct indication of the existence of the light non-aqueous phase liquid on the near-surface and changes along with the change of the reflection mode;
sixthly, reflecting and seismic wave amplitude attribute response, using a 500MHZ frequency board to transmit an antenna, and recording data of three stages; firstly, collecting data of dry sand to obtain three-line data covering the whole experimental pool; FIG. 7(a) is a graphical representation of dry sand reflectance; the seismic wave amplitude attribute response is very weak; the same method is adopted, and light non-aqueous phase liquid is used for invading the test cell; in the software processing process, all the measuring lines are combined, data are processed, a target area is marked, and compared with the sand and water areas in the figure 7(c), a complete reflection mode is given;
FIG. 8(a) combines without offset, but still has some effect in different reflection modes, while FIG. 8(b) has a clear evidence of dramatic changes in the reflection mode of the target area; observing that under the same constraint condition, the relative water content and the non-aqueous phase liquid can be initialized by the seismic wave amplitude attribute response of the radar detection section;
since it has been determined that as the frequency changes, the depth will be affected; comparing these results with the theoretical part of the study, it is clear that the target area (light non-aqueous liquid) where contamination is present is completely different from the other two parts; furthermore, in theoretical studies, the variation of the reflection mode (observed by physical experiments) at a frequency of 500MHZ was observed, which is consistent with the theoretical studies;
to conclude, it is necessary to use a variable frequency, so the transmit antenna is changed to a frequency of 1000 MHZ. In the last review we have demonstrated that with the intrusion of light non-aqueous liquids, the reflection pattern changes with frequency. The procedure is the same as for the 500MHZ frequency. Considering that as the frequency increases, the penetration ability of the electromagnetic wave decreases, the reflection amplitude also decreases. At low frequencies, strong reflections can be observed and vice versa. Although a weak reflection pattern is obtained with the increase of the frequency, there is obvious evidence that the reflection pattern is changed, which is a main problem of the theoretical and physical research of the research;
seismic wave amplitude attribute analysis is a technique for directly indicating hydrocarbons in aquifers and groundwater. Therefore, the amplitude property of the ground penetrating radar-seismic wave is theoretically proposed and proved to be a direct index of a water polluted site, particularly a light non-aqueous phase liquid polluted area for the first time. Furthermore, in the theoretical part, it is of major interest to determine the change in reflection pattern with different substances penetrating into water, however, it has some limitations when used on moist soil and at greater depths. The relative dielectric constant decreases with increasing depth due to less penetration of the light non-aqueous phase liquid; at depths exceeding 10m, a larger antenna pitch is required. In these three cases, the presence of contaminants in the water affects the deep reflection coefficient, and if the water level is underground, an anomalous zone will appear. Studies have shown that collapse of the capillary edge portion due to wetting of soil particles by light non-aqueous phase liquids increases the difference in reflection coefficient between unaffected and affected sites. Thus, collapse of the capillary channel edges will improve the ability to detect light non-aqueous phase liquids.
Finally, physical and theoretical models indicate that when light non-aqueous phase liquid collects on the soil capillaries, abnormal zones and phase changes occur. However, the detection of the residue of the non-aqueous phase liquid in the saturation region using the seismic wave amplitude property analysis method depends on the saturation value of the light non-aqueous phase liquid and the dielectric properties of the low interface. In this study we have evidence that the reflection patterns of different materials (e.g. sand and water) are different when probing non-aqueous liquids of low conductivity. This was first demonstrated theoretically and then verified practically by laboratory experiments. Experimental analysis showed that the results were correct for different frequencies. If the frequency drops below 500MHZ, we can get more accurate results. Since i have better results at a frequency of 500MHZ than at a frequency of 1000 MHZ. The anomaly in the relative permittivity is the definitive evidence of the presence of the light non-aqueous phase liquid in the subsurface, while the reflection mode confirms the presence of the light non-aqueous phase liquid. Therefore, if the light non-aqueous phase liquid is easily detected by the ground penetrating radar-seismic wave amplitude attribute analysis method, serious consequences caused by the pollution of the light non-aqueous phase liquid can be avoided. In our studies, reflection patterns are of major concern, and changes in reflection patterns have been demonstrated to be a direct indication of contaminated sites.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art will be able to make the description as a whole, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (6)
1. A water body pollution detection method based on a ground penetrating radar-seismic wave amplitude attribute is characterized by comprising the following steps:
theoretical modeling, namely respectively placing a seismic source and an output point in a model through excitation and output, summarizing the geometric structure of the model, and simulating heterogeneous soil with a rough surface, a ground penetrating radar antenna model, a simulated metal target and rock in the model;
establishing a physical model, confirming an approximate result in theoretical research, and providing a theory about a ground penetrating radar data reflection mode;
driving factors influencing groundwater detection, including water content, modeling a given material, calculating the relative dielectric constant of the light non-aqueous phase liquid, drawing the relation between the values and the sum of depths, and analyzing the variation trend of the dielectric constant along with the depths;
combining the reflection mode with the non-aqueous phase liquid abnormity, and processing the ground penetrating radar signal by adopting independent component analysis; applying ICA to ground penetrating radar simulation data by performing three-component analysis on a reflection mode of ground penetrating radar-seismic wave amplitude attribute data;
step five, each material is reflected independently, and the difference of the reflection modes is identified by using the frequency;
and sixthly, reflecting the seismic wave amplitude attribute response, using a 500MHZ frequency plate transmitting antenna, and recording data of three stages.
2. The method for detecting water body pollution based on the amplitude attribute of the ground penetrating radar and the seismic wave as claimed in claim 1, wherein the theoretical model establishment is to define model parameters by using a file, and a total model is needed for simulation to image the whole space; three materials, water, sand and light non-aqueous liquid, were inserted in the same model and the relative reflection intensity of each dataset was calculated.
3. The method as claimed in claim 2, wherein the calculation of the relative reflection intensity of the data set comprises calculating all traces of the model center corresponding to the position of the simulation model, and calculating the envelope function of the calculated traces; selecting a maximum amplitude of the envelope function within a gating time window centered on the reflection of the simulated reflection event; finally, the percent increase in reflection intensity for the three models was determined by comparing the synthetic control of the non-simulated light non-aqueous phase liquid and the simulated light non-aqueous phase liquid.
4. The method for detecting water body pollution based on the amplitude attribute of the ground penetrating radar-seismic wave as claimed in claim 1, wherein the two steps comprise the following parts:
s1, collecting data, performing a test in a geophysical simulation laboratory, filling sandy soil with the same water content in a test box, and then connecting 500MHZ and 1000MHZ antennas by using a vector network analyzer for exploration; collecting data of the ground penetrating radar by adopting a fixed antenna spacing; for the ground penetrating radar-seismic wave amplitude attribute analysis, a common center point mode is adopted; under a common center point mode, for each offset, the antenna moves proportionally, and all target areas are marked in the middle of the test box;
s2, data processing, before actual processing, encoding each row to generate a radar map of the original data to verify whether the proposed theory is valid for the original data; introducing the data into a time domain by adopting a fast Fourier inverse transformation method; establishing a double-layer mathematical model of the change of the dielectric constant of the upper sand from low to high;
s3, using two kinds of software to process the data set, converting the data into the format required by the software; using 32-bit floating points and a step size of zero, a time increment of 1ns, an acquisition duration of 500ns, which is the actual time required to acquire data.
5. The method as claimed in claim 1, wherein in the fifth step, the individual reflection of each material comprises collecting dry sand data, and then water intrusion and light non-aqueous liquid intrusion, and the individual reflection mode of different materials intruding into sand is researched.
6. The method as claimed in claim 1, wherein in the sixth step, the data of dry sand is collected to obtain three-line data covering the whole test chamber, then the light non-aqueous liquid is used to invade the test chamber, and in the software processing process, all the test lines are combined to process the data, and the target area is marked to obtain a complete reflection mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110369711.6A CN113092702A (en) | 2021-04-06 | 2021-04-06 | Water body pollution detection method based on ground penetrating radar-seismic wave amplitude attribute |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110369711.6A CN113092702A (en) | 2021-04-06 | 2021-04-06 | Water body pollution detection method based on ground penetrating radar-seismic wave amplitude attribute |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113092702A true CN113092702A (en) | 2021-07-09 |
Family
ID=76674141
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110369711.6A Pending CN113092702A (en) | 2021-04-06 | 2021-04-06 | Water body pollution detection method based on ground penetrating radar-seismic wave amplitude attribute |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113092702A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140203806A1 (en) * | 2013-01-22 | 2014-07-24 | Vista Clara Inc. | Combination nmr and dielectric measurement |
| CN109581516A (en) * | 2018-11-29 | 2019-04-05 | 桂林理工大学 | Bent wave zone statistic adaptive threshold Coherent Noise in GPR Record denoising method and system |
| CN110082832A (en) * | 2019-05-17 | 2019-08-02 | 吉林大学 | A kind of ground magnetic resonance and Coherent Noise in GPR Record joint imaging method |
| CN111239726A (en) * | 2020-02-26 | 2020-06-05 | 山东超越数控电子股份有限公司 | Method, device and readable storage medium for identifying underground pollutant area |
-
2021
- 2021-04-06 CN CN202110369711.6A patent/CN113092702A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140203806A1 (en) * | 2013-01-22 | 2014-07-24 | Vista Clara Inc. | Combination nmr and dielectric measurement |
| CN109581516A (en) * | 2018-11-29 | 2019-04-05 | 桂林理工大学 | Bent wave zone statistic adaptive threshold Coherent Noise in GPR Record denoising method and system |
| CN110082832A (en) * | 2019-05-17 | 2019-08-02 | 吉林大学 | A kind of ground magnetic resonance and Coherent Noise in GPR Record joint imaging method |
| CN111239726A (en) * | 2020-02-26 | 2020-06-05 | 山东超越数控电子股份有限公司 | Method, device and readable storage medium for identifying underground pollutant area |
Non-Patent Citations (1)
| Title |
|---|
| IQBAL I等: "Symmetry between theoretical and physical investigation of water contamination using amplitude variation with offset analysis of ground-penetrating radar data", 《SYMMETRY》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Romero‐Ruiz et al. | A review of geophysical methods for soil structure characterization | |
| Leucci | Nondestructive Testing for Archaeology and Cultural Heritage | |
| Mahmoudzadeh et al. | Using ground penetrating radar to investigate the water table depth in weathered granites—Sardon case study, Spain | |
| Gaber et al. | Integration of 2D/3D ground penetrating radar and electrical resistivity tomography surveys as enhanced imaging of archaeological ruins: A case study in San El‐Hager (Tanis) site, northeastern Nile Delta, Egypt | |
| Tao et al. | Evaluating the joint use of GPR and ERT on mapping shallow subsurface features of karst critical zone in southwest China | |
| Alsharahi et al. | Analysis and modeling of GPR signals to detect cavities: case studies in Morocco | |
| De Benedetto et al. | Spatial relationship between clay content and geophysical data | |
| Simms et al. | In situ root volume estimation using ground penetrating radar | |
| Adepelumi et al. | Geophysical mapping of subsurface stratigraphy beneath a river bed using ground penetrating radar: Lagos Nigeria case study | |
| Durdağ et al. | Combined application of electrical resistivity tomography and multi-channel analysis of surface waves methods in the tunnel detection: A case study from Kocaeli University Campus Site, Turkey | |
| Seren et al. | Imaging fractures in a massive limestone with ground penetrating radar, Haymana, Turkey | |
| Mukherjee et al. | Geoelectrical constraints on radar probing of shallow water-saturated zones within karstified carbonates in semi-arid environments | |
| Iqbal et al. | Analysis of 2D and 3D GPR data interpretation using continuous wavelet transforms: Case study from an archaeological test site | |
| Van den Bril et al. | Ground‐penetrating radar as a tool to detect rock heterogeneities (channels, cemented layers and fractures) in the Luxembourg Sandstone Formation (Grand‐Duchy of Luxembourg) | |
| Win et al. | Geophysical investigation using resistivity and GPR: A case study of an oil spill site at Seberang Prai, Penang | |
| Leucci et al. | Nondestructive testing technologies for cultural heritage: Overview | |
| CN113092702A (en) | Water body pollution detection method based on ground penetrating radar-seismic wave amplitude attribute | |
| Chen et al. | Ground penetrating radar signal processing improves mapping accuracy of underground voids and seawater table: an application in deteriorating coastal structure, Nanfangao Port, Taiwan | |
| Kana et al. | Fracture aperture and fill characterization in a limestone quarry using GPR thin‐layer AVA analysis | |
| Liu et al. | A system for inspecting karst voids during construction of cast-in-place pile foundations | |
| dos Reis Júnior et al. | ERT and GPR survey of collapsed paleocave systems at the western border of the Potiguar Basin in northeast Brazil | |
| Rasol et al. | Background clutter amplitude and frequency of GPR signals to analyse water content in sedimentary deposits: Urban infrastructure environment | |
| Giroux et al. | Quantitative analysis of water-content estimation errors using ground-penetrating radar data and a low-loss approximation | |
| Arisona et al. | Forward Modeling of Ground Penetrating Radar for the Reconstruction of Models Response Profiles using Synthetic Data | |
| Gołębiowski et al. | The application of non-standard GPR techniques for the examination of river dikes |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210709 |
|
| RJ01 | Rejection of invention patent application after publication |