CN118011501A - Deep spontaneous combustion region detection method based on full waveform data multi-parameter joint inversion of transient electromagnetic method - Google Patents
Deep spontaneous combustion region detection method based on full waveform data multi-parameter joint inversion of transient electromagnetic method Download PDFInfo
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Abstract
The invention discloses a deep spontaneous combustion region detection method based on full-wave data multi-parameter joint inversion of a transient electromagnetic method, which comprises the steps of firstly carrying out geological investigation, combining beam tube monitoring and optical fiber temperature measurement monitoring results, and delineating a suspected spontaneous combustion region after comprehensive analysis to provide a target region for transient electromagnetic method detection; a square transmitting loop is paved above the delineated target area, and square wave current is supplied; during power supply, a transient electromagnetic instrument is adopted to collect full waveform data; decomposing transient electromagnetic full-waveform data into primary field data before turn-off and secondary field data after turn-off, and carrying out susceptibility inversion on the primary field data to obtain susceptibility distribution of an underground medium; taking susceptibility distribution as priori information, carrying out resistivity inversion on secondary field data to obtain resistivity distribution; and comprehensively analyzing the distribution conditions of the magnetic susceptibility and the resistivity, and further judging the plane and the depth range of the spontaneous combustion area of the deep coal seam.
Description
Technical Field
The invention belongs to the field of mine fireproof safety methods, and particularly relates to a deep spontaneous combustion region detection method based on full waveform data multi-parameter joint inversion by a transient electromagnetic method.
Background
The easy spontaneous combustion or spontaneous combustion coal seam is widely distributed in China, and the mining ratio of the well and mining of the easy spontaneous combustion or spontaneous combustion coal seam is 58.2% by 2020. The spontaneous combustion fire has high potential hazard, is easy to cause secondary disasters such as dust, gas explosion and the like, and becomes one of main disasters of the coal mine. The rules of 'rules for preventing and extinguishing fire in coal mine' prescribe that the coal mine fire prevention and extinguishing work must adhere to the principles of 'prevention in advance, early warning, proper local conditions and comprehensive treatment', and the transition from passive treatment to active prevention of coal mine fire prevention and control is realized. Therefore, the accurate detection of the spontaneous combustion area of the coal bed is of great practical significance to fire prevention and extinguishing engineering.
The interval between the upper coal bed and the lower coal bed of the close-range coal bed group is smaller, the influence on the overlying stratum is larger when the lower coal bed is mined, a caving zone and a fracture zone are easily generated in the top rock bed, a large number of fractures are generated and even penetrate through the ground surface, the fractures in the caving zone and the fracture zone become main channels for air seepage, oxygen is fully supplied to the goaf of multiple coal beds, and spontaneous combustion of the multiple coal beds is easily caused. In the prior art, when detecting the spontaneous combustion zone of multiple coal beds, the situation of the underground spontaneous combustion zone cannot be accurately known, and potential safety hazards are caused. Therefore, the range and depth detection of spontaneous combustion areas of multiple coal beds around deep close distances is of great significance in further research.
Disclosure of Invention
The invention aims to provide a deep spontaneous combustion region detection method based on full-wave data multi-parameter joint inversion of a transient electromagnetic method, which aims to solve the problem that the depth of an underground spontaneous combustion region cannot be accurately detected and potential safety hazards are caused in the prior art.
In order to solve the problems of the method, the invention is realized by adopting the following method scheme:
a deep spontaneous combustion region detection method based on full waveform data multi-parameter joint inversion by a transient electromagnetic method is characterized by comprising the following steps:
And step 1, collecting the composition data of the spontaneous combustion ignition marking gas of the coal bed in the area to be detected and the temperature data corresponding to each gas.
And 2, judging the position of the high-temperature spontaneous combustion area according to the spontaneous combustion mark gas of the coal seam and the fire disaster early warning model of the multi-level information fusion corresponding to each gas, and determining the position as a target area.
Step 3, paving an emission source in the surface area above the target area, applying square wave current to the emission source to form a square emission loop, and further forming a corresponding magnetic field underground; the transient electromagnetic instrument is used to collect magnetic field full waveform data inside the square transmit loop.
And step 4, data separation is carried out on the acquired magnetic field full waveform data, and primary field data and secondary field data are obtained.
Step 5, carrying out susceptibility inversion on the primary field data to obtain susceptibility distribution information of the underground medium; and taking the magnetic susceptibility distribution information as a constraint condition, and carrying out resistivity constraint inversion on the secondary field data to obtain the resistivity distribution condition of the underground medium.
And 6, determining the plane and depth range of the spontaneous combustion area of the deep coal seam by utilizing the distribution conditions of the magnetic susceptibility and the resistivity of the underground medium.
The invention also has the following characteristics:
further, the specific operation of step 1 is: and acquiring a coal-rock sample of the area to be detected, and acquiring spontaneous combustion ignition marking gas component data of each stage of spontaneous combustion of the coal bed and the corresponding temperature of each gas by adopting a gas chromatography.
Further, the specific operation of step 2 is: and carrying the gas component data monitored by the beam tube and the temperature data monitored by the optical fiber into a fire disaster early warning information model with multi-stage information fusion, obtaining the spontaneous combustion condition of the coal bed of the working face, and delineating a detection target area of the spontaneous combustion area of the coal bed after comprehensive analysis.
Further, in the step3, according to the detection depth required by the geological task, a transmitting source is paved in the surface area above the target area;
Square wave current with duration not less than 10ms and current not less than 15A is applied to the emitting source, and the side length of the formed square emitting loop is 2 times of the detection depth.
Further, in the step3, the transient electromagnetic instrument collects magnetic field full waveform data within the area range of 1/9 of the middle part in the square transmitting loop;
the acquisition density of the transient electromagnetic instrument is (5-20) m× (5-20) m.
Further, the step4 includes the following sub-steps:
Step 41, dividing the collected magnetic field full waveform data into a plurality of periods according to the emission frequency of the emission source and the sampling rate of the transient electromagnetic instrument in the period of stabilizing the square wave current.
And 42, searching the maximum amplitude value in all periods, and determining the data before the position of the maximum amplitude value as stable magnetic field data, wherein the position is added with 1/4 period as attenuation voltage data corresponding to the falling edge.
And 43, superposing the data of all periods to form single-measuring-point attenuation voltage data, and obtaining a sampling channel number attenuation curve by utilizing an integral channel extraction, so as to separate the full-waveform data into primary field data and secondary field data.
Further, the step 5 includes the following sub-steps:
step 51, forward modeling is performed on the primary field data using the following formula;
d＝Gk
Wherein d represents a primary field data vector;
g represents a sensitivity matrix containing the physical relationship between each cell and each data in the model;
k represents the magnetic susceptibility of the model, k= (k 1,k2,…,kM)T; M represents the number of models;
Step 52, inversion is carried out on the primary field data by using a Tikhonov regularization method by taking the magnetic susceptibility as a constraint condition, so as to obtain magnetic susceptibility distribution information:
bl≤k≤bu
Wherein, Representing an objective function;
representing a data fitting function;
representing a model objective function;
beta represents a regularization parameter;
b l and b u represent upper and lower limits, respectively, of the model values;
Step 53, adding susceptibility distribution information as prior information into secondary field data resistivity inversion; synthesizing the data fitting equation and the magnetic susceptibility constraint equation to form a weighted constraint inversion equation, and obtaining the resistivity distribution condition of the underground medium, wherein the expression is as follows:
wherein p data represents a fitting term balance factor;
p rμ represents the balance factor corresponding to the constraint term;
G represents a Jacobian matrix;
R μ represents a stratum permeability transverse constraint matrix;
Δm represents a model correction amount;
Δd obs denotes the fit residual;
Δr μ is the susceptibility fitting residual;
e obs denotes the allowable error of the fitting term;
e rμ denotes the allowable error of the lateral constraint.
Further, in the step 53, the loop source is split into a plurality of electric dipoles, the frequency domain response generated by excitation of each electric dipole is calculated and vector superposition is performed, so as to obtain the frequency domain response of any position of the layered medium of the large loop source, and the time domain response is obtained by using the following formula:
Wherein,
ki 2＝-iωμiσi；
M represents the number of electric dipoles;
σ i represents the i-th layer conductivity;
mu i represents the i-th layer permeability;
h i represents the i-th layer thickness;
the included angle between the jth electric dipole and the measuring point is shown;
r j represents the distance between the measuring point and the jth electric dipole;
the magnetic moment of the j-th electric dipole is shown.
Further, in the step 6, the distribution characteristics of magnetism and electricity in the aspect of distinguishing geological units of the spontaneous combustion area are evaluated.
And grouping the magnetic susceptibility and resistivity data based on a k-mean clustering algorithm to generate a geological result map of the spontaneous combustion area of the coal bed, so as to obtain the plane and depth of the spontaneous combustion area.
Compared with the prior art, the invention has the following technical effects:
According to the deep spontaneous combustion region detection method based on the multi-parameter joint inversion of full waveform data of the transient electromagnetic method, firstly, geological investigation is carried out, beam tube monitoring and optical fiber temperature measurement monitoring results are combined, and a suspected spontaneous combustion region is defined after comprehensive analysis, so that a target region is provided for transient electromagnetic method detection; a square transmitting loop is paved above the delineated target area, and square wave current is supplied; during power supply, a transient electromagnetic instrument is adopted to collect full waveform data; decomposing transient electromagnetic full-waveform data into primary field data before turn-off and secondary field data after turn-off, and carrying out susceptibility inversion on the primary field data to obtain susceptibility distribution of an underground medium; taking susceptibility distribution as priori information, carrying out resistivity inversion on secondary field data to obtain resistivity distribution; and comprehensively analyzing the distribution conditions of the magnetic susceptibility and the resistivity, and further judging the plane and the depth range of the spontaneous combustion area of the deep coal seam.
Square wave current is supplied to the underground through a ground ungrounded square transmitting loop, transient electromagnetic field full-waveform response data are collected by utilizing a transient electromagnetic instrument in a certain area inside a loop source, and the full-waveform data are separated into primary field data and secondary field data, so that the transient electromagnetic field full-waveform data are effectively utilized, and deep detection can be effectively realized. The transient electromagnetic method is utilized to realize multi-parameter joint interpretation, comprehensively analyze the resistivity and magnetic susceptibility distribution condition of the underground medium, solve the problem of multi-resolution of single parameter interpretation, further improve the precision of the plane and depth range of the spontaneous combustion zone at the deep part, and be suitable for industrial large-scale use and popularization.
Drawings
FIG. 1 is a flow chart of a deep spontaneous combustion region detection method based on full-wave data multi-parameter joint inversion by a transient electromagnetic method;
figure 2 is a schematic diagram of the network layout of the present invention.
Detailed Description
All the components in the present invention are known in the art unless otherwise specified.
The following specific examples of the present application are given, and it should be noted that the present application is not limited to the following specific examples, and all equivalent changes made on the basis of the method scheme of the present application fall within the protection scope of the present application.
A deep spontaneous combustion region detection method based on full waveform data multi-parameter joint inversion by a transient electromagnetic method comprises the following steps:
a deep spontaneous combustion region detection method based on full waveform data multi-parameter joint inversion by a transient electromagnetic method is characterized by comprising the following steps:
And step 1, collecting the composition data of the spontaneous combustion ignition marking gas of the coal bed in the area to be detected and the temperature data corresponding to each gas.
And 2, judging the position of the high-temperature spontaneous combustion area according to the spontaneous combustion mark gas of the coal seam and the fire disaster early warning model of the multi-level information fusion corresponding to each gas, and determining the position as a target area.
Step 3, paving an emission source in the surface area above the target area, applying square wave current to the emission source to form a square emission loop, and further forming a corresponding magnetic field underground; the transient electromagnetic instrument is used to collect magnetic field full waveform data inside the square transmit loop.
And step 4, data separation is carried out on the acquired magnetic field full waveform data, and primary field data and secondary field data are obtained.
Step 5, carrying out susceptibility inversion on the primary field data to obtain susceptibility distribution information of the underground medium; and taking the magnetic susceptibility distribution information as a constraint condition, and carrying out resistivity constraint inversion on the secondary field data to obtain the resistivity distribution condition of the underground medium.
And 6, determining the plane and depth range of the spontaneous combustion area of the deep coal seam by utilizing the distribution conditions of the magnetic susceptibility and the resistivity of the underground medium.
Specifically, the specific operation of step 1 is: and acquiring a coal-rock sample of the area to be detected, and acquiring spontaneous combustion ignition marking gas component data of each stage of spontaneous combustion of the coal bed and the corresponding temperature of each gas by adopting a gas chromatography.
Specifically, the specific operation of step 2 is: and carrying the gas component data monitored by the beam tube and the temperature data monitored by the optical fiber into a fire disaster early warning information model with multi-stage information fusion, obtaining the spontaneous combustion condition of the coal bed of the working face, and delineating a detection target area of the spontaneous combustion area of the coal bed after comprehensive analysis.
Specifically, in the step 3, according to the detection depth required by the geological task, paving a transmitting source in the surface area above the target area;
Square wave current with duration not less than 10ms and current not less than 15A is applied to the emitting source, and the side length of the formed square emitting loop is 2 times of the detection depth.
As a preferable scheme, the transient electromagnetic instrument collects magnetic field full waveform data within the area range of 1/9 of the middle part in the square transmitting loop; the acquisition density is (5-20) m× (5-20) m (i.e. the line distance is 5-20 m and the point distance is 5-20 m). The transient electromagnetic instrument collection efficiency can be effectively improved through the arrangement.
Specifically, step 4 includes the following sub-steps:
Step 41, dividing the full-time data collected by the instrument into a plurality of periods according to the emission frequency and the sampling rate of the transient electromagnetic instrument in the period of stabilizing the square wave current.
And 42, searching the maximum amplitude value in all periods, and determining the data before the position of the maximum amplitude value as stable magnetic field data, wherein the position is added with 1/4 period as attenuation voltage data corresponding to the falling edge.
And 43, superposing a plurality of period data to form single-measuring-point attenuation voltage data, and obtaining a sampling channel number attenuation curve by utilizing an integral channel extraction, so as to separate the full-waveform data into primary field data and secondary field data.
Specifically, step 5 includes the following sub-steps:
step 51, forward modeling is performed on the primary field data using the following formula;
d＝Gk
Wherein d represents a primary field data vector;
g represents a sensitivity matrix containing the physical relationship between each cell and each data in the model;
k represents the magnetic susceptibility of the model, k= (k 1,k2,…,kM)T; M represents the number of models;
Step 52, inversion is carried out on the primary field data by using a Tikhonov regularization method by taking the magnetic susceptibility as a constraint condition, so as to obtain magnetic susceptibility distribution information:
Wherein, Representing an objective function;
representing a data fitting function;
representing a model objective function;
beta represents a regularization parameter;
b l and b u represent upper and lower limits, respectively, of the model values;
For a pair of And carrying out inversion operation to obtain the resistivity.
Step 53, adding susceptibility distribution information as prior information into secondary field data resistivity inversion; synthesizing the data fitting equation and the magnetic susceptibility constraint equation to form a weighted constraint inversion equation, and obtaining the resistivity distribution condition of the underground medium, wherein the expression is as follows:
wherein p data represents a fitting term balance factor;
p rμ represents the balance factor corresponding to the constraint term;
G represents a Jacobian matrix;
R μ represents a stratum permeability transverse constraint matrix;
Δm represents a model correction amount;
Δd obs denotes the fit residual;
Δr μ is the susceptibility fitting residual;
e obs denotes the allowable error of the fitting term;
e rμ denotes the allowable error of the lateral constraint.
Specifically, in step 53, the loop source is split into a plurality of electric dipoles, the frequency domain response generated by excitation of each electric dipole is calculated, and vector superposition is performed, so as to obtain the frequency domain response of any position of the layered medium of the large loop source, and the time domain response is obtained by using the following formula:
Wherein,
ki 2＝-iωμiσi；
M represents the number of electric dipoles;
σ i represents the i-th layer conductivity;
mu i represents the i-th layer permeability;
h i represents the i-th layer thickness;
the included angle between the jth electric dipole and the measuring point is shown;
r j represents the distance between the measuring point and the jth electric dipole;
the magnetic moment of the j-th electric dipole is shown.
Specifically, in step 6, the distribution characteristics of magnetism and electricity in distinguishing geological units in the spontaneous combustion area are evaluated; and grouping the magnetic susceptibility and resistivity data based on a k-mean clustering algorithm to generate a geological result map of the spontaneous combustion area of the coal bed, so as to obtain the plane and depth of the spontaneous combustion area.
Claims (9)
1. A deep spontaneous combustion region detection method based on full waveform data multi-parameter joint inversion by a transient electromagnetic method is characterized by comprising the following steps:
Step 1, collecting coal seam spontaneous combustion ignition marking gas composition data and temperature data corresponding to each gas in a region to be detected;
Step 2, judging the position of the high-temperature spontaneous combustion area according to the spontaneous combustion mark gas of the coal seam, the critical value corresponding to each gas and the fire disaster early warning model with multi-level information fusion, and determining the position as a target area;
Step 3, paving an emission source in the surface area above the target area, applying square wave current to the emission source to form a square emission loop, and further forming a corresponding magnetic field underground; acquiring magnetic field full waveform data inside a square transmitting loop by using a transient electromagnetic instrument;
step 4, data separation is carried out on the acquired magnetic field full waveform data to obtain primary field data and secondary field data;
step 5, carrying out susceptibility inversion on the primary field data to obtain susceptibility distribution information of the underground medium; taking the magnetic susceptibility distribution information as constraint conditions, carrying out resistivity constraint inversion on secondary field data, and obtaining the resistivity distribution condition of the underground medium;
And 6, determining the plane and depth range of the spontaneous combustion area of the deep coal seam by utilizing the distribution conditions of the magnetic susceptibility and the resistivity of the underground medium.
2. The deep spontaneous combustion region detection method based on transient electromagnetic method full waveform data multi-parameter joint inversion according to claim 1, wherein the specific operation of step 1 is as follows: and acquiring a coal-rock sample of the area to be detected, and acquiring spontaneous combustion ignition marking gas component data of each stage of spontaneous combustion of the coal bed and the corresponding temperature of each gas by adopting a gas chromatography.
3. The deep spontaneous combustion region detection method based on transient electromagnetic method full waveform data multi-parameter joint inversion according to claim 1, wherein the specific operation of step 2 is as follows: and carrying the gas component data monitored by the beam tube and the temperature data monitored by the optical fiber into a fire disaster early warning information model with multi-stage information fusion, obtaining the spontaneous combustion condition of the coal bed of the working face, and delineating a detection target area of the spontaneous combustion area of the coal bed after comprehensive analysis.
4. The deep spontaneous combustion region detection method based on full-wave data multi-parameter joint inversion of the transient electromagnetic method according to claim 1, wherein in the step 3, a transmitting source is paved in a surface region above a target region according to a detection depth required by geological tasks;
Square wave current with duration not less than 10ms and current not less than 15A is applied to the emitting source, and the side length of the formed square emitting loop is 2 times of the detection depth.
5. The deep spontaneous combustion region detection method based on full-wave data multi-parameter joint inversion of the transient electromagnetic method as claimed in claim 3, wherein in the step 3, the transient electromagnetic instrument collects full-wave data of a magnetic field within a range of 1/9 area of the middle part in a square emission loop;
the acquisition density of the transient electromagnetic instrument is (5-20) m× (5-20) m.
6. The deep spontaneous combustion region detection method based on transient electromagnetic method full waveform data multi-parameter joint inversion according to claim 1, wherein said step 4 comprises the following sub-steps:
Step 41, dividing the collected magnetic field full waveform data into a plurality of periods according to the emission frequency of the emission source and the sampling rate of the transient electromagnetic instrument in the period of stable square wave current;
Step 42, searching the maximum amplitude value in all periods, determining the data before the position of the maximum amplitude value as stable magnetic field data, wherein the position is added with 1/4 period as attenuation voltage data corresponding to the falling edge;
and 43, superposing the data of all periods to form single-measuring-point attenuation voltage data, and obtaining a sampling channel number attenuation curve by utilizing an integral channel extraction, so as to separate the full-waveform data into primary field data and secondary field data.
7. The deep auto-ignition region detection method based on transient electromagnetic method full waveform data multi-parameter joint inversion of claim 1, wherein said step 5 comprises the following sub-steps:
step 51, forward modeling is performed on the primary field data using the following formula;
d＝Gk
Wherein d represents a primary field data vector;
g represents a sensitivity matrix containing the physical relationship between each cell and each data in the model;
k represents the magnetic susceptibility of the model, k= (k 1,k2,…,kM)T; M represents the number of models;
Step 52, inversion is carried out on the primary field data by using a Tikhonov regularization method by taking the magnetic susceptibility as a constraint condition, so as to obtain magnetic susceptibility distribution information:
bl≤k≤bu
Wherein, Representing an objective function;
representing a data fitting function;
representing a model objective function;
beta represents a regularization parameter;
b l and b u represent upper and lower limits, respectively, of the model values;
Step 53, adding susceptibility distribution information as prior information into secondary field data resistivity inversion; synthesizing the data fitting equation and the magnetic susceptibility constraint equation to form a weighted constraint inversion equation, and obtaining the resistivity distribution condition of the underground medium, wherein the expression is as follows:
wherein p data represents a fitting term balance factor;
p rμ represents the balance factor corresponding to the constraint term;
G represents a Jacobian matrix;
R μ represents a stratum permeability transverse constraint matrix;
Δm represents a model correction amount;
Δd obs denotes the fit residual;
Δr μ is the susceptibility fitting residual;
e obs denotes the allowable error of the fitting term;
e rμ denotes the allowable error of the lateral constraint.
8. The method for deep spontaneous combustion region detection based on transient electromagnetic method full waveform data multi-parameter joint inversion according to claim 7, wherein in step 53, the loop source is split into a plurality of electric dipoles, the frequency domain response generated by excitation of each electric dipole is calculated and vector superposition is performed, the frequency domain response of any position of the layered medium of the large loop source is obtained, and the time domain response is obtained by using the following formula:
Wherein,
ki 2＝-iωμiσi；
M represents the number of electric dipoles;
σ i represents the i-th layer conductivity;
mu i represents the i-th layer permeability;
h i represents the i-th layer thickness;
the included angle between the jth electric dipole and the measuring point is shown;
r j represents the distance between the measuring point and the jth electric dipole;
the magnetic moment of the j-th electric dipole is shown.
9. The method for deep spontaneous combustion zone detection based on multi-parameter joint inversion of full-wave data by transient electromagnetic method as claimed in claim 1, wherein in said step 6, the distribution characteristics of the geological units in the spontaneous combustion zone are distinguished by evaluating the magnetism and the electricity.
And grouping the magnetic susceptibility and resistivity data based on a k-mean clustering algorithm to generate a geological result map of the spontaneous combustion area of the coal bed, so as to obtain the plane and depth of the spontaneous combustion area.
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