CA3122828A1 - Squid-based electromagnetic detection method for induction-polarization symbiotic effect of two-phase coducting medium - Google Patents

Abstract

The invention provides a SQUID-based electromagnetic detection method for an induction-polarization symbiotic effect of a two-phase conductive medium. The method includes: 1) establishing a dual-time-scale fractional conductivity model of an induction- polarization symbiotic effect, and substituting the dual-time-scale fractional conductivity model into a Maxwell equations to obtain a dual-time fractional electromagnetic field diffusion equation; 2) directly solving the fractional term in the dual-time- scale fractional conductivity model by a fractional time-domain finite difference method according to the dual-time fractional electromagnetic field diffusion equation established in 1), performing discrete recursion on a component form containing the fractional differential term to realize dual-time-scale three-dimensional electromagnetic response numerical simulation of the induction-polarization symbiotic effect, and calculating the magnetic field response of the induction-polarization symbiotic effect; 3) for the dual-time-scale fractional conductivity model in 1), performing three-dimensional numerical simulation of current excitation with different falling edges by using 2).

Description

SQUID-BASED ELECTROMAGNETIC DETECTION METHOD FOR
INDUCTION-POLARIZATION SYMBIOTIC EFFECT OF TWO-PHASE
CODUCTING MEDIUM
TECHNICAL FIELD
[0001] The disclosure relates to a detection method in the geophysical exploration field, and more particularly to a superconducting quantum interference device (SQUID)-based electromagnetic detection method for an induction-polarization symbiotic effect of a two-phase conductive medium, which is suitable for an actual geological two-phase conductive medium.
BACKGROUND

[0002] In the geophysical exploration field, a single induction or polarization effect is usually obtained by measuring electric and magnetic fields. Since the earth is a rough and highly-dissipative medium, underground lithologic and physical properties are highly rough and non-linear. Actually, polymetallic ore and other media belong to composite multiphase conductive media, so it is particularly important to measure complex physical properties or parameters at multiple scales. Under the excitation of an alternating field, the induction and polarization effects in multiphase conducing media exist simultaneously and are accompanied by each other. The induction response can better distinguish formation lithology, and the polarization response can effectively identify favorable oil and gas reservoirs and metal ore anomalies. To realize high-resolution and deep detection of complex underground geological structures, it is necessary to simultaneously measure the information of multiple physical fields such as electrical, magnetic and polarization fields of the complex geological structures and simultaneously acquire multiple parameters comprising conductivity and polarizability of the rock.

[0003] At present, in the electromagnetic detection field of the induction and polarization effect, by only considering the single effect of electromagnetic induction or polarization during measurement and by only interpreting the resistivity or polarizability, there may be multiple solutions, resulting in low detection resolution and the inability to Date Recue/Date Received 2021-06-21 realize deep and fine detection. In the wide field electromagnetic method proposed by He Jishan (2019), apparent resistivity was acquired by measuring the components of the electric field or magnetic field in frequency domain. However, this method only focused on the inversion of the resistivity, and could not fully reflect the multi-scale dispersion characteristics of underground complex multi-phase mediums. Yang Zhenwei (2016) obtained the complex resistivity by measuring the imaginary and real components of the electric field, but it was required to measure two field quantities which are the changes rates of the electric field and the magnetic field. He Zhanxiang (2019) obtained the resistivity and polarizability by a time-frequency electromagnetic method;
however, in the method both time domain and frequency domain were required.

[0004] Chinse Patent Application No. CN201510882791.X discloses a multi-frequency detection device for detecting complex resistivity. This device can generate multiple types of frequency signals. It can analyze and process the waveforms of voltage signals and current signals, and accurately measure the complex resistivity spectrum of the formation. However, only the spectral information is acquired by this method, and it is difficult to analyze geometrical characteristics and physicochemical characteristics of an underground medium.

[0005] Chinse Patent Application No. CN202010339342.1 discloses a method and system for analyzing a time-domain induced polarization spectrum of a porous medium.
The relaxation time distribution of the porous medium is jointly inversed and estimated by using the apparent polarizability data calculated at several different charging times, and the distribution of apertures can be reflected. In the existing electromagnetic detection methods, polymetallic ore such as copper ore can be detected by observing the induction-polarization symbiotic effect, but it is still required to switch between the time domain and frequency domain to measure electric and magnetic fields.
Therefore, it is necessary to design a time-domain electromagnetic detection method which can finely measure the induction-polarization symbiotic effect in the multi-phase conductive medium.
SUMMARY

Date Recue/Date Received 2021-06-21

[0006] In view of the difficulty of realizing detection of a two-phase medium by the existing detection methods, an objective of the disclosure is to establish a generalized equivalent induced polarization model according to the complex characteristics of the actual underground medium and the composition characteristics of polymetallic mineral rock, and provide an electromagnetic detection method for an induction-polarization symbiotic effect of a two-phase conductive medium.

[0007] The disclosure provides a two-phase conductive medium induction-polarization symbiosis electromagnetic detection method based on SQUID, the method comprising:

[0008] 1) establishing a dual-time-scale fractional conductivity model of an induction-polarization symbiotic effect, and substituting the dual-time-scale fractional conductivity model into Maxwell equations to obtain dual-time fractional electromagnetic field diffusion equations;

[0009] 2) directly solving the fractional term in the dual-time-scale fractional conductivity model by a fractional finite-difference time-domain method according to the dual-time fractional electromagnetic field diffusion equations established in 1), performing discrete recursion on a component form containing the fractional differential term to realize dual-time-scale three-dimensional electromagnetic response numerical simulation of the induction-polarization symbiotic effect, and calculating the magnetic field response of the induction-polarization symbiotic effect;

[0010] 3) for the dual-time-scale fractional conductivity model in 1), performing three-dimensional numerical simulation of current excitation with different falling edges by using 2), determining, according to characteristics of the induction-polarization symbiotic effect, emission parameters in the case of maximum induction and polarization responses, and constructing a dual-controllable-edge trapezoidal wave transmission targeted excitation relationship to realize targeted excitation of transmission of trapezoidal waves with two falling edges;

[0011] 4) transmitting, by a transmission for trapezoidal waves with two controllable edges according to the dual-controllable-edge trapezoidal wave transmission targeted excitation relationship in 3), receiving based on a superconducting quantum interference Date Recue/Date Received 2021-06-21 device (SQUID), reading data by using a non-modulated flux phase-locked readout circuit, removing geomagnetic interference from read data through an external AC and internal DC magnetic field compensation method, and removing human noise and electromagnetic noise through a multilateralism mixed noise shielding technology, and then measuring magnetic fields of the induction-polarization symbiotic effect;

[0012] 5) preprocessing the measured data of the induction-polarization symbiotic effect measured in 4), performing polarization identification by a data mining method, and intelligently extracting and imaging multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction by quantum particle swarm optimization (QPSO) and image the results;

[0013] 6) calculating a singularity index of the results extracted in 5) by a local singularity index algorithm of a rectangular window, and identifying and predetermining valuable economic mineral resources and unvalued mineralized zones.

[0014] Further, 2) is implemented as follows:

[0015] 2.1) according to the dual-time fractional electromagnetic field diffusion equations in 1), performing piecewise-linear approximation on the complex frequency variable fractional power of the dual-time fractional electromagnetic field diffusion equation to obtain diffusion equations of an integer power;

[0016] 2.2) transforming the diffusion equations to the time domain, performing difference approximation by a finite difference method, directly solving the fractional item in the conductivity model of the two-phase conductive medium, and deriving the iterative relationship among components of the electric field and magnetic field;

[0017] 2.3) dividing a calculation region by a non-uniform Yee grid, calculating conductivity, polarizability, dispersion coefficient, polarization volume fraction and polarization particle radius, loading an initial field under the excitation of trapezoidal waves and boundary conditions, and iteratively calculating each component of the electromagnetic fields to realize dual-time-scale three-dimensional electromagnetic numerical simulation of the induction-polarization symbiotic effect; and Date Recue/Date Received 2021-06-21

[0018] 2.4) calculating the magnetic field response of the induction-polarization symbiotic effect according to 2.3), analyzing the influence of the transmitting parameters on polarization, and optimizing the transmitting parameters.

[0019] Further, in 3), the specific control idea of the transmission of trapezoidal waves with two falling edges is described below. During the turn-off period of a first set of trapezoidal waves in one transmission cycle, it is required to switch a discharge circuit to a quick break circuit. At this time, a high-voltage transient suppression diode is broken down by voltage overshoot. The voltages at two ends of a transmission coil are clamped to a high voltage. The turn-off speed can be quickened by increasing the clamping voltage threshold. The time on the falling edge is:
/ =L
t = COIL
" IITõ (1).

[0020] In the formula (1), / is the current value of the transmitting ceiling section, LCOIL is the induction value of the wire which is obtained by calculation or measurement, and HTVS is the clamping voltage of the high-voltage transient suppression diode.
Broadband excitation mainly measures the electromagnetic information after the transmitting current is turned off

[0021] During the turn-off period of a second set of trapezoidal waves, it is required to switch the discharge circuit to a slow break circuit, a low-voltage transient suppression diode is turned on, and the voltages at two ends of the transmitting loop are clamped to a low voltage, so that the falling edge discharges slowly. By selecting appropriate circuit parameters, the time on the slow break falling edge can be regulated. The time on the falling edge is:
/ = ',COIL
t¨off = ULTVS ¨UDecho ¨UMOS (2)

[0022] where Umvs is the clamping voltage of the low-voltage transient suppression diode, Dedi 0 is the voltage drop of the freewheeling diode (FWD) for the switch device, Date Recue/Date Received 2021-06-21 and Uffos is the forward voltage drop when the switch device is turned on.
Soft turn-off can prolong the polarization discharge time, to realize stronger induced polarization response. The main control circuit controls the operation time sequence of the power transmitting circuit and the absorption circuit under the synchronization of high-precision timing signals, so that quick and soft turn-off time current waveforms can be realized in one transmitting cycle.

[0023] Further, in 4), the non-modulated flux phase-locked loop readout circuit is of a structure of two relaxation oscillating circuits and two single flux phase-locked loop circuits, wherein the two relaxation oscillating circuits are connected by two matching resistors and Josephson Junctions connected to the two matching resistors; the Josephson Junctions, the matching resistors and a low-noise biased constant-current source form a SQUID loop; the matching resistors are used to limit the damping state during operation;
each Josephson Junction and the matching resistor connected to the Josephson Junction form a single flux phase-locked loop circuit in the form of grounding; an external magnetic field signal enters the sensor by magnetic coupling with the SQUID
coil, so that the two relaxation oscillating comparators generate a signal voltage pulse and a reference voltage pulse; the voltage pulses are converted into single flux quantum pulses via the single flux-quantum flux phase-locked loop circuits; and finally, flux quanta are counted by a high-speed single flux quantum logic counting circuit.

[0024] Further, 5) is implemented as follows:

[0025] 5.1) baseline correcting, superimposing and filtering the data of the induction-polarization symbiotic effect measured in 4);

[0026] 5.2) extracting polarization response characteristic attribute parameters of the data processed in 5.1) by the partial mutual information method, and screening characteristics to effectively extract main polarization characteristic parameters;

[0027] 5.3) based on a support vector machine, establishing a polarization effect detection model by using the polarization characteristic parameters extracted in 5.2), screening out the optimal input variable, and using WHETHER THERE IS A
POLARIZATION EFFECT' as an output;

Date Recue/Date Received 2021-06-21

[0028] 5.4) directly calculating the surrounding rock conductivity go for the early data in the measured data of the output 'THERE IS A POLARIZATION EFFECT' in 5.3), setting a constraint range by using this result, and intelligently extracting multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction by the QPSO algorithm;

[0029] 5.5) for the dual-time-scale fractional conductivity model, re-deriving a generalized skin depth formula, and substituting the multiple polarization parameters extracted in 5.4) into the generalized skin depth formula for calculation;

[0030] deriving, according to the GEMTIP model of the two-phase conductive medium, the expression of the number of complex waves is:
to to k 2 co 2w icopo_ef po_eni 1 (icori)C1+ 111Cre2 1+ (ior2)C2 (3)

[0031] if k2 = (a +=13)2, then:
a _VVA/2 N2 A/ (Vm2 N2 Al) 2N (4) r f, tor \c1 aff (cor )C2 m (02 gki cop el k 11 e2 21

[0032] where l+(1)2d1 1+(coz-2)2c 2 h= //
ael ae2 N = ¨comfe+
1_-F(C,)Z- 1 (C)r ) 1)2C1 2C2 2 ; according to the definition of the skin depth, the skin depth d is equal to the distance by which el is passed when the amplitude of the field quantity is attenuated to its surface value, so that e-ad e',= and the generalized skin depth formula of the porous polarization medium is obtained, d= = n _________________ a V2 _____ IM2 N2 ¨ M M2 + N2 + M)

[0033] 5.6) imaging the conductivity and polarizability-depth according to the results in 5.4) and 5.5).

Date Recue/Date Received 2021-06-21

[0034] Further, the QPSO algorithm in 5.4) is implemented as follows:
1 N Ft(X)¨Bt ¨
P = IV i=1 __ Ft (X)

[0035] a. establishing a target function: , where Xis a parameter to be extracted, Ft(X) is the magnetic field response of the induction-polarization symbiotic effect in 2), N is the number of effective sampling points of the magnetic field data of the induction-polarization symbiotic effect in 4), and Bt is the magnetic field data of the induction-polarization symbiotic effect in 4);

[0036] b. initializing the number A/ of individuals in the population, and randomly x. (t) = (1),xi2 (1), = = = xiD (0) generating, within the constraint range, the position of particles conforming to uniform distribution, where i = 1,2, = = ='M, and 1) is the spatial dimensionality;

[0037] c. calculating the fitnessfr(i) of each particle, and initializing the individual optimal solution PiD(t) and the global optimal solution g iD(t) ;
4)= cOiD(t) p (t) + [1¨ coiD(t)]g- (t) , where

[0038] d. solving the local attract factor C 7D(t) is the random number of (0,1);
1 m c(t) = (t)

[0039] e. calculating the average best position 1 , and updating the position of particles according to the following formula:

xiD(t +1) = AiD(t) alc(t) ¨ x 0(01 ln( up(t)

[0040] where "o(t) is the random number of (0,1); and, it is "2 if u7D(t) 0.5 , or otherwise, it is "+";

[0041] f. comparing the fitness value of each particle, and updating the individual optimal solution P iD(t) and the global optimal solution g7D(t); and Date Recue/Date Received 2021-06-21

[0042] g. repeating operations c-f until the optimal value is found or the maximum number of iterations is reached, and outputting the global optimal solution

[0043] Further, 6) is implemented as follows:

[0044] 6.1) for any given spatial position, defining a series of spatial overlay boxes (squares), where the window size of the spatial overlay boxes increases successively, i.e.,

[0045] 6.2) calculating the average P(6') of multiple physical quantities such as the measurement magnetic field, conductivity and polarizability in each window, and performing numerical translation during calculation to ensure that it is not zero;
log p (E )) i =

[0046] 6.3) in the log-log coordinates, drawing , / (where 1 2 . . .n by o. I g (6 ) log p (6) log p(s) .
using as the horizontal axis and as the vertical axis, where is linear along with log (s), and the slope of the linear relationship is the estimation of the codimension (a-2); and

[0047] 6.4) sliding the series of windows to other sampling positions, and repeating the processing methods in the first three steps to obtain a spatial distribution map of local singularity indexes a of magnetic field data, conductivity, polarizability and other anomalies.

[0048] The following advantages are associated with the method of the disclosure.
Compared with the prior art, by the SQUID-based electromagnetic detection method for an induction-polarization symbiotic effect of a two-phase conductive medium provided by the disclosure, in the disclosure, high-precision detection of the induction-polarization symbiotic effect of the two-phase conductive medium can be realized by a single magnetic field, multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction of the two-phase conductive medium are intelligently extracted, and valuable economic mineral resources and unvalued mineralized zones are identified and predetermined. This method provides new technical support for deep Date Recue/Date Received 2021-06-21 electromagnetic exploration of mineral resources such as complex ore, polymetallic ore, which is beneficial to the practical application of electromagnetic exploration methods.
BRIEF DESCRIPTION OF THE DRAWINGS

[0049] FIG. 1 is a flowchart of an electromagnetic detection method for an induction-polarization symbiotic effect;

[0050] FIG. 2 is a schematic view of a transmitting control module for trapezoidal waves with two falling edges;

[0051] FIG. 3 shows a low-noise front adaptive gain amplification and acquisition circuit;

[0052] FIG. 4 shows a non-modulated flux phase-locked loop readout circuit;

[0053] FIG. 5 is a schematic view of an automatically controlled constant-temperature system;

[0054] FIG. 6 is a flowchart of a QPSO algorithm; and

[0055] FIG. 7 is an effect diagram of resistivity imaging according to an embodiment of the disclosure.
DETAILED DESCRIPTION

[0056] To further illustrate, embodiments detailing a superconducting quantum interference device (SQUID)-based electromagnetic detection method for an induction-polarization symbiotic effect of a two-phase conductive medium are described below. It should be noted that the following embodiments are intended to describe and not to limit the disclosure.

[0057] A two-phase conductive medium is taken as an example.
Date Recue/Date Received 2021-06-21

[0058] As shown in FIG. 1, an electromagnetic detection method for an induction-polarization symbiotic effect of an electric source two-phase conductive medium is implemented as follows:

[0059] 1) Based on the conductivity model of the two-phase conductive medium, a fractional laplace operator is introduced, the multi-capacitance polarization effect of the medium is represented by multiple time fractional orders, a dual-time-scale fractional conductivity model of the induction-polarization symbiotic effect is established, and dual-time fractional electromagnetic field diffusion equations are further established.

[0060] The conductivity expression of the two-phase conductive effective medium model is:

= co 1+ fi 1 Mi 1 __ f2M2 1 C2 1+(icoroc 1+(icor2) (1) ( a, ¨an - 0-n /11/1 m 2 _______ 200 +02 2a10- , and where 2o-0 + al ( a2 2 1 2a o- a 2 \ 2 0 )

[0061] There are total 11 parameters, comprising the surrounding rock conductivity o-0, five strong polarization medium parameters and five weak polarization medium parameters. The strong polarization medium parameters comprise the strong polarization medium conductivity o-i, the strong polarization dispersion coefficient Ci, the strong polarization volume fractionfi, the strong polarization particle radius ai and the strong surface polarization coefficient al. The weak polarization medium parameters comprise the weak polarization medium conductivity a2, the weak polarization dispersion coefficient C2, the weak polarization volume fractionf2, the weak polarization particle radius a2 and the weak surface polarization coefficient a2. a) is the angular frequency.

[0062] According to the fractional conductivity model of the induction-polarization symbiotic effect (the formula (1) is substituted into the Maxwell equations to obtain Date Recue/Date Received 2021-06-21 formulae (2) and (3)), dual-time fractional electromagnetic field diffusion equations (2) and (3) are established.

[0063] The formula (1) is substituted into the Maxwell equations to obtain:
v2E k2E 0 (2) v2f/ k2fi 0 (3) i co to k 2 co 2 w cop 0_ po_effi

[0064] where 1+ (icori)C1 IUCT e 2 1+ (iWT2)c 2 is the electromagnetic intensity, I/ is the magnetic field intensity, k is the wave number, e is the dielectric constant, ,u is the magnetic conductivity, Cr: =C70 Cr0f1M1 Cr0f2M2 Cren1 (70 fl M1 , and Cren2 (70 f2 M2

[0065] 2) The fractional term in the dual-time-scale fractional conductivity model is directly solved by a fractional finite-difference time-domain method according to the dual-time fractional electromagnetic diffusion equation established in 1), discrete recursion is performed on a component form containing the fractional differential term to realize dual-time-scale three-dimensional electromagnetic response numerical simulation of the induction-polarization symbiotic effect, and the magnetic field response of the induction-polarization symbiotic effect is calculated.

[0066] 2) is implemented as follows:

[0067] 2.1) According to the dual-time fractional electromagnetic field diffusion equations in 1), piecewise-linear approximation is performed on the complex frequency variable fractional power of the dual-time fractional electromagnetic field diffusion equations to obtain a diffusion equation of an integer power, where the fractional power in the formulae (2) and (3) is subjected to Laplace transformation, and the piecewise-linear approximation is performed on the exponential function 8' in the Laplace domain.

[0068] 2.2) The diffusion equations are transformed to the time domain, difference approximation is performed by a finite difference method, the fractional item in the Date Recue/Date Received 2021-06-21 conductivity model of the two-phase conductive medium is directly solved, and the iterative relationship among components of the electric field and magnetic field is derived.

[0069] The control equations are dispersed by a finite difference method to obtain the iterative relationship among components of the electric field and magnetic field:
Ex(x,y,z,tõ,i) = A2Eõ (x, y, z, in ) + +
(crein + 0;2" )Ex(x,Y,z,0)+ mz(x y "zt n __ UY aZ
) (4) A - 4_ -2AtnAti, 1E 4K1 E + AtK2E - At,,,K2E -2K3AtnAt1E
[4Ki +K2E] [4Ki +K2E]

[0070] where ,and ¨ At1[K2E -A3 _______________ [4K1 +K2E]
=
H.z(x, y,z+1,tõ)= H.z(x, y, z,tõ) ¨
H. (x +1, y, z ,t n) ¨ H + Az .(x, y,z,tn) H.Y (x, y +1, z, t) ¨ I
my (.)C y, z, ) Az ___________________________________ Ax Ay (5) H.(x,y,z,t)=EY(X,y,z+1,t,,)- Ey(X5 y, z,tõ) Ez(x,y+1, z,t,,)- Ez(x,y, z,tõ)

[0071] where PAz pAy , and E=Atõ + Atõ+1.
The iteration equation of Ez can be obtained from the formula (4) by recursion. The HmY iteration can be obtained from the formula (5) by recursion.

[0072] Ex, Ey and Ez are three components of the electric field x,y,z; tn is the nth moment;
At. 1 = tõ 1- tõ ; At. = tõ - tõ 1; H.= OH Ot ;
- 1 __________ 1 ,ff, -C
-C C2) n -C2 (1 C2 11 1 2 2 2 el '1 e2 2 2 . K2 r e ell" (1 1 1 1 e2T 2 2 ) .
and 2 e el 1

[0073] 2.3) A calculation region is divided by a non-uniform Yee grid; the calculated conductivity, polarizability, dispersion coefficient, polarization volume fraction and Date Recue/Date Received 2021-06-21 polarization particle radius are set; an initial field under the excitation of trapezoidal waves is loaded; boundary conditions are loaded; and components of the electromagnetic field are iteratively calculated to realize dual-time-scale three-dimensional electromagnetic numerical simulation of the induction-polarization symbiotic effect.

[0074] 2.4) The magnetic field response of the induction-polarization symbiotic effect is calculated according to the dual-time-scale three-dimensional electromagnetic numerical simulation of the induction-polarization symbiotic effect in 2.3), the influence of the transmitting parameters on polarization is analyzed, and the transmitting parameters are optimized.

[0075] 3) For the dual-time-scale fractional conductivity model (formula 1) in 1), three-dimensional numerical simulation of current excitation with different falling edges is performed by using 2). Transmitting parameters in the case of maximum induction and polarization responses are obtained according to the characteristics of the induction-polarization symbiotic effect, to obtain a dual-controllable-edge trapezoidal wave emission targeted excitation relationship. The induction and polarization electromagnetic responses of different transmitting parameters are analyzed according to the numerical simulation results of different falling edge excitations. The emission parameter in the case of maximum induction and polarization responses is regarded as the targeted excitation of transmission, so that the targeted excitation of transmission of trapezoidal waves with two falling edges is realized.

[0076] As shown in FIG. 2, a transmission for trapezoidal waves with two controllable edges comprises a synchronization module, a main control circuit, a power transmitting bridge and an absorption circuit. An ARM is used as the controller. The control circuit generates a time sequence with a variable duty ratio, and controls an H bridge comprising IGBTs via a driving circuit to generate alternatively positive and negative currents. A
current recording unit ensures the capture and recording of transient waveforms of the current within a large dynamic range by connecting sampling resistors in series to the transmitting cable and using an induction and shunt two-way measurement technology, so that the whole process of transmitting the current and the transient characteristics of the current can be recorded accurately. The ground resistance is measured in real time by a Date Recue/Date Received 2021-06-21 built-in precision bridge. The real-time measured data such as the ground resistance and transmitting induction are returned to the main control unit. The main control unit automatically switches to a reconfigurable impedance matching network built in the transmitting system by efficient closed-loop control, performs adaptive impedance matching, adjusts the operation state of the transmitting circuit in real time or performs abnormity protection, and realizes multi-parameter self-measurement and monitoring by the transmitting system. The transmission for trapezoidal waves with two controllable edges measures the ground resistance in real time by a built-in precision bridge. When the electric source is excited, it is greatly affected by the ground resistance, which restricts the magnitude and waveform quality of the transmitting current. When the ground resistance is low, current limiting measures are taken to avoid the burning of the inverter bridge. When the ground resistance is high, the output voltage and the output power can be automatically adjusted to increase the current and improve the excitation energy of the field source. The real-time measured data such as the ground resistance and inductance are returned to the main control unit. The transmitting system is integrated with the ground resistance real-time measurement and feedback unit. The main control unit automatically switches to the reconfigurable impedance matching network built in the system by efficient closed-loop control, performs adaptive impedance matching, adjusts the operation state of the transmitting circuit in real time or performs abnormity protection, and realizes the long-term stable operation of the transmitting system.

[0077] The specific control method for transmission of trapezoidal waves with two falling edges is described below. During the turn-off period of a first set of trapezoidal waves in one transmitting cycle, it is required to switch a discharge circuit to a quick break circuit. At this time, a high-voltage transient suppression diode is broken down by voltage overshoot. The voltages at two ends of a transmitting coil are clamped to a high voltage. The turn-off speed can be quickened by increasing the clamping voltage threshold. The time on the falling edge is:
/.L
t _ COIL
f U HTVS (6) Date Recue/Date Received 2021-06-21

[0078] where I is the current value of the transmitting ceiling sectionõ
11ff7Vs is the induction value of the transmitting wire and is calculated or measured, and Lcol" is the clamping voltage of the high-voltage transient suppression diode. Broadband excitation mainly measures the electromagnetic information after the transmitting current is turned off.

[0079] During the turn-off period of a second set of trapezoidal waves, it is required to switch the discharge circuit to a slow break circuit. A low-voltage transient suppression diode is turned on, and the voltages at two ends of the transmitting loop are clamped to a low voltage, so that the falling edge discharges slowly. By selecting appropriate circuit parameters, the time on the slow break falling edge can be regulated. The time on the falling edge is:
I=LCQJL
ts¨off =
ULTVS ¨ UDecho ¨UMOS (7)

[0080] where U.L TVS is the clamping voltage of the low-voltage transient suppression diode, Dedio is the voltage drop of the FWD for the switch device, and U105 is the forward voltage drop when the switch device is turned on. Soft turn-off can prolong the polarization discharge time, to realize stronger induced polarization response. The main control circuit controls the operation time sequence of the power transmitting circuit and the absorption circuit under the synchronization of high-precision timing signals, so that quick and soft turn-off time current waveforms can be realized in one transmitting cycle.

[0081] 4) By the targeted excitation of transmission of trapezoidal waves with two falling edges in 3), based on a superconducting quantum interference device (SQUID), use a non-modulated flux phase-locked readout technology, an external AC and internal DC magnetic field compensation method and a multilateralism mixed noise shielding technology, then a high-precision system for sensing a single magnetic field of the high-slew rate and low-noise superconducting quantum interference device is realized, and magnetic fields of the induction-polarization symbiotic effect are measured.

Date Recue/Date Received 2021-06-21

[0082] In the high-precision system for sensing a single magnetic field of the high-slew rate and low-noise superconducting quantum interference device, the high-sensitivity matching of the acquisition system with the output of the SQUID is realized by a low-noise front adaptive gain amplification and acquisition technology; it is mounted in an ideal-crosstalk asymmetric manner, and the compensation coil and the transmitting coil are synchronously controlled by GPS; flux counting and magnetic field measurement at a high slew rate and in a large dynamic range are performed by a non-modulated flux phase-locked loop readout circuit; the SQUID can operate continuously and stable for a long time by using a constant-temperature control system with an automatic temperature control function; by using Cu/Ni or Ag/A1 material, the SQUID is shielded by selecting an appropriate thickness of the shielding layer.

[0083] As shown in FIG. 3, low-noise front adaptive gain amplification and acquisition circuit suppresses the common-mode interference of signals by differential-mode amplification, the dynamic range of the system is improved by adaptive gain control.
Design the attenuator to avoid signal saturation, filter the out-of-band noise by the program-controlled anti-aliasing filtering technology, suppress noise for different signal frequencies, and improve the signal-to-noise ratio of the system.

[0084] As shown in FIG. 4, the non-modulated flux phase-locked loop readout circuit is of a structure of two relaxation oscillating circuits 6 and two single flux phase-locked loop circuits 7. The two relaxation oscillating circuits 6 are connected by two matching resistors 4 and Josephson Junctions 5 connected to the two matching resistors 4. The Josephson Junctions 5, the matching resistors 4 and a low-noise biased constant-current source 3 form a SQUID loop 2. The matching resistors 4 are used to limit the damping state during operation. Each Josephson Junction 5 and the matching resistor 4 connected to the Josephson Junction 5 form a single flux phase-locked loop circuit 7 in the form of grounding. An external magnetic field signal enters the sensor by magnetic coupling with a pickup SQUID coil 1, so that the two relaxation oscillating circuits generate a signal voltage pulse and a reference voltage pulse; the voltage pulses are converted into single flux quantum pulses via the single flux-quantum flux phase-locked loop circuits; and Date Recue/Date Received 2021-06-21 finally, flux quanta are counted by a high-speed single flux quantum logic counting circuit 8.

[0085] As shown in FIG. 5, the constant-temperature system with an automatic control function comprises a low-pass filter, a temperature indicator adjustment meter, a thyristor voltage stabilizer, a transformer and a rectifier. The temperature acquired by the temperature sensor is transmitted to the low-pass filter, adjusted by the temperature indicator adjustment meter, stabilized by the thyristor voltage stabilizer, passed through the transformer and the rectifier, and driven by a vacuum pump driven by a DC
motor.
When the Pt/Co temperature sensor senses that the temperature of liquid nitrogen in Dewar changes, the temperature signal is transmitted to the temperature indicator by the low-pass filter, and the temperature is automatically regulated by a fuzzy adaptive MD
feedback control algorithm. The temperature of the liquid nitrogen is kept constant by changing the pressure in Dewar by the voltage stabilizer, the transformer, the rectifier and the vacuum pump driven by the DC motor. The low-pass filter and the current rectifier can effectively reduce the noise contribution of the Pt/Co temperature sensor to the SQUID.

[0086] 5) The measured data of the induction-polarization symbiotic effect measured in 4) is preprocessed, polarization identification is performed by a data mining method, and multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction are intelligently extracted and imaged by QPSO algorithm.

[0087] 5) is implemented as follows:

[0088] 5.1) The measured data of the induction-polarization symbiotic effect measured in 4) is baseline corrected, superimposed and filtered.

[0089] 5.2) Polarization response characteristic attribute parameters of the data processed in 5.1) are extracted by the partial mutual information method, and characteristics are screened to effectively extract main polarization characteristic parameters.

[0090] 5.3) Based on a support vector machine, a polarization effect detection model is established by using the polarization characteristic parameters extracted in 5.2), the Date Recue/Date Received 2021-06-21 optimal input variable is screened out, and 'WHETHER THERE IS A POLARIZATION
EFFECT' is used as an output.

[0091] 5.4) The surrounding rock conductivity go is directly calculated for the early data in the measured data of the output 'THERE IS A POLARIZATION EFFECT' in 5.3), a constraint range is set by using this result, and multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction intelligently extracted by the QPSO algorithm.

[0092] The QPSO algorithm is implemented as follows:
kp I IN. Ft(X)¨Bt ¨
mm N 1=1 Ft (X)

[0093] a. A target function is established: , where Xis a parameter to be extracted, Ft(X) is the magnetic field response of the induction-polarization symbiotic effect in 2), Nis the number of effective sampling points of the magnetic field data of the induction-polarization symbiotic effect in 4), and Bt is the magnetic field data of the induction-polarization symbiotic effect in 4).

[0094] b. The number M of individuals in the population is initialized, and the position xi (t) = (xil (1),xi2(1), = = = , x0 (1)) of particles conforming to uniform distribution is randomly generated within the constraint range, where i ¨1,2'= = .'M, and D is the spatial dimensionality.

[0095] c. The fitnessfr(i) of each particle is calculated, and the individual optimal solution p(t) and the global optimal solution giD(t) are initialized.

[0096] d. The local attract factor AiD iD (1) P (1) El D (1)]g (1) is solved, where C6'iD (1) is the random number of (0,1).
1 m c(t) = o(t)

[0097] e. The average best position M 1 is calculated, and the position of particles is updated according to the following formula:

Date Recue/Date Received 2021-06-21 X iD(t +1) AD(t) alc(t)¨ xiD(t)11n( 1 tio(t)

[0098] where uo(t) is the random number of (0,1); and, it is "2 if uo(t) 0.5 , or otherwise, it is "+".

[0099] f. The fitness value of each particle is compared, and the individual optimal solution Pip and the global optimal solution g iD(t) are updated.

[0100] g. The operations c-f are repeated until the optimal value is found or the maximum number of iterations is reached, and the global optimal solution g iD(t) is output.

[0101] 5.5) For the dual-time-scale fractional conductivity model, a generalized skin depth formula is re-derived, and the multiple polarization parameters extracted in 5.4) are substituted into the generalized skin depth formula for calculation.

[0102] The expression of the number of complex waves is derived according to the GEMTIP model of the two-phase conductive medium:
/co 10)PP k 2 co 2 gilt i + eff 1+(icori)C +
1111Cre21+(icor2) 2 (8)

[0103] If k2 = (a + /3)2 , then a _ANA/2 + N2 A/ (411/2 + N2 + Al) 2N (9) an icor \ aff (cor )C2 M=a) 2 ep co,"" elk + 2) 2C

[0104] where / 1+ (a r1) 2C1 1+ (cor2)2 a el N = ¨comfe+ cop (coz-1)2C1 C e2 1+ (CO r2 )2C2 . According to the definition of the skin depth, the skin depth d is equal to the distance by which e 1 is passed when the -ad amplitude of the field quantity is attenuated to its surface value, so that e = e', and Date Recue/Date Received 2021-06-21 the generalized skin depth formula of the porous polarization medium is obtained:

d= = n _________________ cc V2 NI M2 + N2 ¨M (4M2 N2 M)

[0105] 5.6) The conductivity and polarizability-depth are imaged according to the results in 5.4) and 5.5).

[0106] 6) The singularity index of the results extracted in 5) is calculated by a local singularity index algorithm of a rectangular window, and valuable economic mineral resources and unvalued mineralized zones are identified and predetermined.

[0107] Specifically, 6) is implemented as follows:

[0108] 6.1) For any given spatial position, a series of spatial overlay boxes (squares) is defined, where the window size of the spatial overlay boxes increases successively, i.e., = <62 < < =

[0109] 6.2) The average Pk) of multiple physical quantities such as the measurement magnetic field, conductivity and polarizability in each window is calculated, and numerical translation is performed during calculation to ensure that it is not zero.
6. i ='

[0110] 6.3) In the log-log coordinates, p ()) (where 12...n) is drawn by o. I g(s) log p (s) log p (s) using .
as the horizontal axis and as the vertical axis, where is linear along with log (8), and the slope of the linear relationship is the estimation of the codimension (a-2).

[0111] 6.4) The series of windows is slid to other sampling positions, and the processing methods in the first three steps are repeated to obtain a spatial distribution map of local singularity indexes a of magnetic field data, conductivity, polarizability and other anomalies.

[0112] FIG. 6 shows the resistivity-depth results of the field experiment in Luanchuan in Henan province according to an embodiment of the disclosure. The results are Date Recue/Date Received 2021-06-21 consistent with the geological data result, so that the effectiveness of this method is fully verified.

[0113] It will be obvious to those skilled in the art that changes and modifications may be made, and therefore, the aim in the appended claims is to cover all such changes and modifications.

Date Recue/Date Received 2021-06-21

Claims (7)

1. A
superconducting quantum interference device (SQUID)-based electromagnetic detection method for an induction-polarization symbiotic effect of a two-phase conductive medium, the method comprising:
1) establishing a dual-time-scale fractional conductivity model of an induction-polarization symbiotic effect, and substituting the dual-time-scale fractional conductivity model into Maxwell equations to obtain dual-time fractional electromagnetic field diffusion equations;
2) directly solving a fractional term in the dual-time-scale fractional conductivity model by a fractional finite-difference time-domain method according to the dual-time fractional electromagnetic field diffusion equation established in 1), performing discrete recursion on a component form containing a fractional differential term to realize dual-time-scale three-dimensional electromagnetic response numerical simulation of the induction-polarization symbiotic effect, and calculating a magnetic field response of the induction-polarization symbiotic effect;
3) for the dual-time-scale fractional conductivity model in 1), performing three-dimensional numerical simulation of current excitation with different falling edges by using 2), determining, according to characteristics of the induction-polarization symbiotic effect, transmitting parameters in the case of maximum induction and polarization responses, and constructing a dual-controllable-edge trapezoidal wave transmission targeted excitation relationship to realize targeted excitation of transmission of trapezoidal waves with two falling edges;
4) transmitting, by a transmission for trapezoidal waves with two controllable edges according to the dual-controllable-edge trapezoidal wave transmission targeted excitation relationship in 3), receiving based on a superconducting quantum interference device (SQUID), reading data by using a non-modulated flux phase-locked readout circuit, removing geomagnetic Date Recue/Date Received 2021-06-21 interference from read data through an external AC and internal DC magnetic field compensation method, and removing human noise and electromagnetic noise through a multilateralism mixed noise shielding technology, and then measuring magnetic fields of the induction-polarization symbiotic effect;
5) preprocessing the measured data of the induction-polarization symbiotic effect measured in 4), performing polarization identification by a data mining method, and intelligently extracting multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction by quantum particle swarm optimization (QPSO) and imaging results; and 6) calculating a singularity index of results extracted in 5) by a local singularity index algorithm of a rectangular window, and identifying and predetermining valuable economic mineral resources and unvalued mineralized zones.

2. The method of claim 1, wherein 2) is implemented as follows:
2.1) according to the dual-time fractional electromagnetic field diffusion equations in 1), performing piecewise-linear approximation on a complex frequency variable fractional power of the dual-time fractional electromagnetic field diffusion equation to obtain diffusion equations of an integer power;
2.2) transforming the diffusion equation to a time domain, performing difference approximation by a finite difference method, directly solving a fractional item in the conductivity model of the two-phase conductive medium, and deriving an iterative relationship among components of an electric field and a magnetic field;
2.3) dividing a calculation region by a non-uniform Yee grid, setting conductivity, polarizability, dispersion coefficient, polarization volume fraction and polarization particle radius, loading an initial field under the excitation of trapezoidal waves and boundary conditions, and iteratively calculating each component of the electromagnetic fields to realize dual-time-scale three-Date Recue/Date Received 2021-06-21 dimensional electromagnetic numerical simulation of the induction-polarization symbiotic effect; and 2.4) calculating the magnetic field response of the induction-polarization symbiotic effect according to 2.3), analyzing the influence of the transmitting parameters on polarization, and optimizing the transmitting parameters.

3. The method of claim 1, wherein in 4), transmitting, by a transmission for trapezoidal waves with two controllable edges according to the dual-controllable-edge trapezoidal wave transmission targeted excitation relationship in 3), is implemented as follows:
during a turn-off period of a first set of trapezoidal waves in one transmitting cycle, a discharge circuit is switched to a quick break circuit;
at this time, a high-voltage transient suppression diode is broken down by voltage overshoot; voltages at two ends of a transmitting coil are clamped to a high voltage; the turn-off speed is quickened by increasing a lamping voltage threshold; a time on the falling edge is:
t = / .kOIL
f-off U HTVS (1);
in the formula (1), I is a current value of a transmitting ceiling section, LCOIL is an induction value of a transmitting wire which is obtained by calculation or measurement, and HTVS is a clamping voltage of a high-voltage transient suppression diode; broadband excitation is configured to measure electromagnetic information after the current is turned off;
during the turn-off period of a second set of trapezoidal waves, the discharge circuit is switched to a slow break circuit, a low-voltage transient suppression diode is turned on, and the voltages at two ends of a transmitting loop are clamped to a low voltage, so that the falling edge discharges slowly; by Date Recue/Date Received 2021-06-21 selecting appropriate circuit parameters, the time on a slow break falling edge is regulable; the time on the falling edge is:
/. LCOI L
ts¨off = _________________________________ U LTVS ¨ U Decho ¨U ALOS .. (2);
where I/
LTVS is a clamping voltage of the low-voltage transient suppression diode, Dedio is a voltage drop of the freewheeling diode (FWD) for the switch device, and 105 is a forward voltage drop when the switch device is turned on; soft turn-off prolongs the polarization discharge time, to realize stronger induced polarization response; a main control circuit controls an operation time sequence of a power transmitting circuit and an absorption circuit under the synchronization of high-precision timing signals, so that quick and soft turn-off time current waveforms is realized in one transmitting cycle.

4. The method of claim 1, wherein in 4), the non-modulated flux phase-locked loop readout circuit is of a structure of two relaxation oscillating circuits and two single flux phase-locked loop circuits; the two relaxation oscillating circuits are connected by two matching resistors and Josephson Junctions connected to the two matching resistors; the Josephson Junctions, the matching resistors and a low-noise biased constant-current source form a SQUID loop; the matching resistors are used to limit the damping state during operation; each Josephson Junction and the matching resistor connected to the Josephson Junction form a single flux phase-locked loop circuit in the form of grounding; an external magnetic field signal enters a sensor by magnetic coupling with the SQUID coil, so that the two relaxation oscillating comparators generate a signal voltage pulse and a reference voltage pulse; the voltage pulses are converted into single flux quantum pulses via the single flux-quantum flux phase-locked loop circuits; and finally, flux quanta are counted by a high-speed single flux quantum logic counting circuit.

Date Recue/Date Received 2021-06-21

5. The method of claim 1, wherein 5) is implemented as follows:
5.1) baseline correcting, superimposing and filtering the data of the induction-polarization symbiotic effect measured in 4);
5.2) extracting polarization response characteristic attribute parameters of the data processed in 5.1) by the partial mutual information method, and screen characteristics to effectively extract main polarization characteristic parameters;
5.3) based on a support vector machine, establishing a polarization effect detection model by using the polarization characteristic parameters extracted in 5.2), screening out the optimal input variable, and using 'WHETHER THERE IS
A POLARIZATION EFFECT' as an output;
5.4) directly calculating the surrounding rock conductivity a() for the early data in the measured data of the output 'THERE IS A POLARIZATION EFFECT' in 5.3), setting a constraint range by using this result, and intelligently extracting multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction by a QPSO algorithm;
5.5) for the dual-time-scale fractional conductivity model, re-deriving a generalized skin depth formula, and substituting the multiple polarization parameters extracted in 5.4) into the generalized skin depth formula for calculation.

6. The method of claim 5, wherein in 5.5), re-deriving a generalized skin depth formula comprises:
deriving, according to the GEMTIP model of the two-phase conductive medium; the expression of the number of complex waves is:
to to k 2 co 2 = Eiu icopure pun1 1 + (icor1)C1+ PC e2 1+ (t= Or2)C2 (3) if k2 = (a + 13)2 , then:

Date Recue/Date Received 2021-06-21 a _VVA12 __________________ +N2 __ Al (VA12 __ +N2 + Al) 2N (4) r a"i(or )C1 + a:2 (a) r2 )C2 A/ co 2gp + cop e I
+ (COri )2C1 1 + (co z-2 )2C
where 2 a" a"
el N = ¨cc op'e + cop 2c + e2 2C
\1+ (co z-1) 1 1+ (6) r2)2 ; according to the definition of the skin depth, the skin depth d is equal to the distance by which e 1 is passed when the amplitude of the field quantity is attenuated to its surface value, so that -ad -1 e =e , and the generalized skin depth formula of the porous polarization medium is obtained:

d = = F-CC Af 2 VM2 + N2 ¨ M (\I + N2 + M) 2N (5).

7. The method of claim 5, wherein intelligently extracting multiple parameters comprising conductivity, polarizability, dispersion coefficient and volume fraction by a QPSO algorithm is implemented as follows:
1 x-1N Ft(X)¨Bt ¨

klf min N Ft (X) a. establishing a target function: , where X is a parameter to be extracted, Ft(X) is the magnetic field response of the induction-polarization symbiotic effect in 2), N is the number of effective sampling points of magnetic field data of the induction-polarization symbiotic effect in 4), and Bt is magnetic field data of the induction-polarization symbiotic effect in 4);
b. initializing the number A/ of individuals in the population, and randomly generating, within the constraint range, the position x,(t) = (x,1(t), xi2 (0, = = = xiD (t)) =
of particles conforming to uniform distribution, where i ¨1,2'= = =,M, and D is a spatial dimensionality;

Date Recue/Date Received 2021-06-21 c. calculating a fitnessfr(i) of each particle, and initializing an individual optimal solution P (1) and a global optimal solution AiD ¨ cOiD(t) p (t) + [1 ¨ c OiD(t)]g- (t) d. solving a local attract factor , where (6 (1) is a random number of (0,1);
1 m c(t) = PiD (t) e. calculating an average best position 1 , and updating the position of particles according to the following formula:

ic x o(t +1) = Ao(t) a I(t) ¨ xiD(t)1 ln( uo(t) u. uo(t) > 0.5 , or where iD (I) is a random number of (0,1); and, it is "2 if otherwise, it is "+";
f. comparing the fitness value of each particle, and updating the individual optimal solution iD(1) and the global optimal solution g iD(1) ; and g. repeating operations c-f until the optimal value is found or the maximum number of iterations is reached, and outputting the global optimal solution g 0(1) .

Date Recue/Date Received 2021-06-21