CN111175336A - Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor - Google Patents

Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor Download PDF

Info

Publication number
CN111175336A
CN111175336A CN202010052741.XA CN202010052741A CN111175336A CN 111175336 A CN111175336 A CN 111175336A CN 202010052741 A CN202010052741 A CN 202010052741A CN 111175336 A CN111175336 A CN 111175336A
Authority
CN
China
Prior art keywords
coil
magnetic field
magnet
length
parameters
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.)
Granted
Application number
CN202010052741.XA
Other languages
Chinese (zh)
Other versions
CN111175336B (en
Inventor
李利品
童美帅
袁景峰
韩瑞强
王韵
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xian Shiyou University
Original Assignee
Xian Shiyou University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Xian Shiyou University filed Critical Xian Shiyou University
Priority to CN202010052741.XA priority Critical patent/CN111175336B/en
Publication of CN111175336A publication Critical patent/CN111175336A/en
Application granted granted Critical
Publication of CN111175336B publication Critical patent/CN111175336B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N24/00—Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects
    • G01N24/08—Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects by using nuclear magnetic resonance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/30—Assessment of water resources

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Pathology (AREA)
  • Biochemistry (AREA)
  • Analytical Chemistry (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Immunology (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Chemical & Material Sciences (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)

Abstract

A method for measuring and calculating a nuclear magnetic resonance two-phase flow sensor comprises the steps of firstly, aiming at magnet design, determining the length of a pre-magnetized magnet A by analyzing the relationship between magnetization vectors and magnetization lengths of different flow rates and different water contents; study of Halbach Structure and target magnetic field intensity B0And uniformity P1Determining the parameters of the main measuring magnetic field B; target field homogeneity P by compensation magnet C2Determining the size of the bucking magnet C; secondly, aiming at coil design, firstly establishing a theoretical model for quantifying an FID signal and a coil, and analyzing the functional relation between the FID and the coil length under the influence of the flow velocity and the phase content rate of two-phase flow; the solenoid was then investigated for the number of turns, coil spacing,and determining structural parameters of the sectional type coil and completing the design of matching resonance parameters of the coil by using the structural parameter influence factors such as the depth-height ratio and the like. Finally, determining the integral design of the structural parameters of the coil of the magnetic resonance two-phase flow sensor; the invention realizes more accurate measurement of the nuclear magnetic resonance sensor.

Description

Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor
Technical Field
The invention relates to the technical field of oil-water two-phase flow parameter measurement, in particular to a method for measuring and calculating a nuclear magnetic resonance two-phase flow sensor.
Background
In the process of oil exploitation, the produced fluid is mostly a mixture of oil and water two-phase flows, and the measurement difficulty of the produced fluid is far higher than that of a single-phase flow due to the variability and complexity of flow characteristics such as flow patterns, flow rates of various phases and the like, so that the two-phase flow measurement is still a great technical problem in the oil industry. Therefore, the research on the parameter measurement and calculation method of the oil-water two-phase flow has very important significance for the optimized exploitation of oil-gas wells, the effective protection of reservoir stratums, the improvement of the recovery ratio and the improvement of the economic benefits of the petroleum industry.
Most of the traditional two-phase flow measuring methods are contact type measuring methods, but because a measuring medium directly contacts the surface of a sensor, the problems of sensitivity reduction, accuracy deterioration and the like of the sensor are caused. The two-phase flow measuring technology based on the nuclear magnetic resonance principle has the advantages that the measuring result is not influenced by macroscopic physical characteristics, the limitation of the traditional measuring method can be effectively overcome, and the two-phase flow measuring technology is a new direction in the field of two-phase flow research at present. In oil-water two-phase flow, the nuclear magnetic resonance phenomenon is the result of the interaction of electromagnetic waves and hydrogen element substances, an oil pipe is placed in a static magnetic field environment with specific strength, radio frequency pulses with corresponding frequency are applied to enable sample atomic nuclei in the pipeline to resonate, and the acquired echo signals are utilized to complete parameter information such as the structure, density distribution and the like of the two-phase flow substances. The magnetic resonance sensor has strict requirements on high uniformity of a magnetic field, high sensitivity of a radio frequency coil signal and high signal-to-noise ratio. For a magnet device, the magnet device has the function of generating a high-strength, uniform and stable main magnetic field, and is the primary condition for generating nuclear magnetic resonance, and the performance of the main magnet directly influences the sensitivity and the precision of nuclear magnetic resonance measurement; for a coil system, when two separated coils work, the problems of mutual coupling, reduction of signal-to-noise ratio, energy transfer error and the like can occur, and the receiving and transmitting coils are combined into a whole, so that the high uniformity of a radio frequency magnetic field and the high sensitivity and the high signal-to-noise ratio of a received signal are difficult to simultaneously meet. Therefore, the optimization research of the magnetic resonance two-phase flow sensor is one of the hot spots and difficulties of NMR.
Disclosure of Invention
In order to solve the problems and difficulties in the prior art, the invention aims to provide a method for measuring and calculating a nuclear magnetic resonance two-phase flow sensor, which constructs an accurate nuclear magnetic resonance sensor structure model by introducing two-phase flow system parameters and optimizes and calculates various parameters aiming at a magnet and a coil device, fully analyzes and researches the effect and the precision influence of the sensor structure parameters on measurement signals, and improves the overall performance of the sensor.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for measuring and calculating a nuclear magnetic resonance two-phase flow sensor comprises the following steps:
the first step is as follows: the method comprises the following steps of determining the structural parameters of a magnet of the nuclear magnetic resonance two-phase flow sensor, wherein the magnet is formed by sequentially connecting a pre-magnetized magnet A, a measuring magnet B and a compensating magnet C on a coaxial line, and the method comprises the following specific steps:
1. determining the length of a pre-magnetized magnet A
(1) Determining the functional relationship among the flow velocity, the water content, the magnetization vector and the magnetization length according to the flow characteristics of the oil-water two-phase flow, wherein the expression is as follows:
Figure BDA0002371767670000021
where M is the actual magnetization vector, M0Is the vector of complete magnetization, x is the magnetization length, v is the average flow velocity of oil-water two-phase flow, T1The longitudinal relaxation time of the oil-water two-phase flow is related to the phase content a% of the oil-water two-phase flow, T2The transverse relaxation time of the oil-water two-phase flow;
(2) obtaining a normalized magnetization vector according to equation (1)
Figure BDA0002371767670000022
Figure BDA0002371767670000023
Analyzing the magnetization vector M/M under different water content a% and different flow velocity v0Characteristic relationship with magnetization length;
(3) according to M/M0Finding the magnetization vector M/M according to the curve diagram of the magnetization length0The corresponding magnetization length when approaching the maximum value of 1, thereby determining the length of the pre-magnetized magnet a;
2. measuring parameters of magnet B
(1) Establishing a magnetic field two-dimensional plane uniformity expression by adopting a Halbach magnet array
Figure BDA0002371767670000031
Wherein
Figure BDA0002371767670000037
Average static magnetic field strength, B, generated for a working space magnetmaxFor a large field strength quantization value of the working range, BminA quantized value of the magnetic field strength in a lower working interval is obtained;
(2) determining a discrete Halbach mathematical model, and respectively researching the magnetic field intensity B according to four parameters of an internal-external diameter ratio value R/R, the number N of assembly blocks, the shape of the blocks and a magnetic material0The following calculation model is obtained:
Figure BDA0002371767670000032
wherein: b is0Strength of static magnetic field generated for magnet, BrThe residual magnetic flux density is shown, R is the outer radius of the magnet, R is the inner radius, and n is the number of magnet blocks;
(3) establishing a particle swarm optimization model according to a formula (2), wherein the shape of the blocks influences the error between the integral performance and the ideal structure of the discrete Halbach, and the magnetic material influences the residual magnetic flux density BrInfluence of the number of building blocks N
Figure BDA0002371767670000033
Numerical relationship of (1), inside and outsideInfluence of diameter ratio
Figure BDA0002371767670000034
Using finite element simulation to comprehensively analyze the magnetic field intensity B0Two-dimensional plane uniformity P of magnetic field1The rule of the change of the parameters of the four magnets;
(4) according to the simulation analysis result, determining the restriction relation and the influence rule among the parameters, and finding out the magnetic field intensity B meeting the requirement0And the magnetic field two-dimensional plane uniformity P1The parameter with the highest uniformity, thereby determining each structural parameter of the measuring magnet B;
3. determining parameters of the bucking magnet C
(1) Study of three-dimensional axial magnetic field uniformity
Figure BDA0002371767670000035
Relationship to magnet length: wherein the content of the first and second substances,
Figure BDA0002371767670000036
for the average field strength in the axial z-direction, it can be concluded that the field homogeneity P increases infinitely with the magnet length2The axial magnetic field uniformity P is improved by adding the compensation magnets C at two ends of the measurement magnet B2；
(2) According to Maxwell equation of three-position static magnetic field and calculation formula of magnetic induction intensity of permanent magnet, obtaining uniformity P of compensation magnets C with different sizes to axial magnetic field by finite element static magnetic field simulation2Influence relationship of (1):
Figure BDA0002371767670000041
Figure BDA0002371767670000042
Figure BDA0002371767670000043
wherein B (x, y, z) is magnetic induction, H (x, y, z) is magnetic field intensity, J (x, y, z) is current density, the three vectors are all functional relations of vectors in all directions, and mu0Is the absolute permeability in vacuum, murFor relative permeability, MPThe polarization intensity of the permanent magnetic material;
(3) according to simulation analysis, comparing the axial magnetic field uniformity P of the magnets C with different structural sizes2Finding the magnet parameters with the highest optimization on the magnetic field uniformity and the smallest volume, thereby determining the size of the compensation magnet C;
finally determining the integral design of the magnet structure parameters of the magnetic resonance two-phase flow sensor according to the steps and the analysis result;
the second step is that: the method for determining the structural parameters of the coil of the nuclear magnetic resonance two-phase flow sensor comprises four steps as follows:
the first part of the steps are as follows:
1. establishing a theoretical model of a quantitative FID signal and a coil, determining a functional relation between a nuclear magnetic resonance receiving signal FID and the length of the coil, and solving the nuclear magnetic resonance receiving signal FID under different average flow velocities v and different water contents a%, wherein the expression is as follows:
Figure BDA0002371767670000044
wherein: sFIDFor quantizing the FID signal received by the coil, where Mi0＝SiHI，i，SiIs the saturation of the ith component, H, in a two-phase flowI，iIs the hydrogen index, L, of the ith component in a two-phase flowDIs the length of the coil, LMFor the length of magnetization, T is the sampling time, c is the correction factor, T1，iIs the spin lattice relaxation time, T, of the ith component2，iIs the spin-spin relaxation time of the ith component;
2. analyzing FID signals S received by coils under models with different average flow velocities v and different water contents a% according to a formula (4)FIDThe rule of variation with the length of the coil;
3. by analysing the FID signal S received by the coilFIDThe corresponding coil length tends to be stable, so that the basic length parameter range of the detection coil is determined;
the second part of the steps are as follows:
1. theoretical models of coil performance and solenoid parameters were established, and the impact factor of coil sensitivity Bxy was determined:
Figure BDA0002371767670000051
wherein, B1I is the radio frequency magnetic field intensity B generated by a unit current i in the coil1N is the number of turns of the coil, H/D is the ratio of depth to height of the tube diameter, H is the height of the solenoid coil, D is the diameter of the coil, u0Is a vacuum magnetic conductivity;
2. establishing an equivalent model of coil resistance R under the skin effect and the proximity effect, and obtaining the following expression:
Figure BDA0002371767670000052
wherein R iscoilIs the resistance value of an equivalent straight wire at radio frequency, epsilon is the enhancement factor of two adjacent turns of coils, RsThe method is an equivalent resistance model, wherein l is the length of a lead used by a coil, d is the wire diameter of the coil, f is the resonance frequency of the coil, mu is the magnetic conductivity, and rho is the resistivity of a copper lead;
3. establishing relative signal-to-noise ratio SNR and sensitivity B under fixed pulse frequencyxyAnd a resistance RsThe response relationship of (a) is shown in formula 7; and analyzing the influence rule of each parameter of the coil on the SNR by applying a particle swarm optimization algorithm and combining finite element simulation:
Figure BDA0002371767670000061
Figure BDA0002371767670000062
wherein: b isxyIs the sensitivity of the coil; k is a reaction radio frequency magnetic field B1Constant of homogeneity, vsFor detecting the volume of the sample, N is the number of nuclear spins per unit volume, γ is the magnetic spin ratio of the atoms, h is Planckian, I is the spin quantum number of the nuclei, w0Is the precession frequency of the nucleus, KBIs Boltzmann constant, RsIs the coil resistance, T is the temperature of the test sample; Δ f is the measured bandwidth;
4. according to the above influence factors and result analysis, the high sensitivity B is obtainedxyAnd coil parameters of high signal-to-noise ratio (SNR);
the third part of the steps are as follows:
1. establishing a solenoid coil to generate a radio frequency magnetic field B1The theoretical model of (2) calculates the intensity of the radio frequency magnetic field generated by the coil, and the calculation formula is as follows:
Figure BDA0002371767670000063
wherein: mu.s0The magnetic field strength is vacuum magnetic conductivity, N is the number of turns of a coil, I is the current intensity of the coil, H is the height of a solenoid coil, R is the radius of the solenoid coil, and Z is the distance from any point of an axial space of the solenoid to a central point;
2. analysis of the radio frequency magnetic field B by finite element magnetic field simulation according to equation (8)1And calculating the uniformity of the RF magnetic field in the target space
Figure BDA0002371767670000064
Is the average intensity of the radio frequency magnetic field;
3. by analyzing the change rule of the magnetic field intensity in the solenoid space, the result that the magnetic field intensity in the middle of the pipeline is high and gradually decreases towards the two ends is obtained. Therefore, a segmented coil structure with sparse middle and compact two ends is provided, and the purposes of weakening the magnetic field intensity of the middle section and enhancing the magnetic field intensity of the two ends are achieved by adjusting the space proportion of three segments of coils, so that the uniformity of the whole radio frequency magnetic field is improved;
the fourth step is as follows:
1. the resonance characteristic of a radio frequency system is researched, and various parameter values of a coil under a fixed frequency, including a resistor R, an inductance L and a capacitance C, are measured by using an impedance analyzer;
2. establishing an RLC matching response relation, and calculating to obtain various matching parameters of the coil quality factor according to the following expression, wherein Z is total impedance, W is frequency, and C ismCapacitors, C, connected in series with the desired matching circuittConnecting capacitors in parallel to the obtained matching circuit, wherein R is the actually measured coil resistance value, L is the coil inductance value, and j is a physical vector;
Figure BDA0002371767670000071
Figure BDA0002371767670000072
Figure BDA0002371767670000073
and finally determining the integral design of the coil structure parameters of the magnetic resonance two-phase flow sensor according to the steps and the analysis result.
The invention relates to a parameter measuring and calculating method of a nuclear magnetic resonance two-phase flow sensor, which mainly comprises two steps, wherein in the first step, aiming at magnet design, the length of a pre-magnetized magnet A is determined by analyzing the relationship between magnetization vectors and magnetization lengths with different flow rates and different water contents; then by researching Halbach structure and target magnetic field intensity B0And uniformity P1Determining the size parameter of the main measuring field B by adopting a particle swarm optimization algorithm and combining finite element simulation; by using the principle of magnetic field superposition, the target magnetic field uniformity P is obtained by the compensation magnet C2Determining the optimal size of the compensation magnet C within the error tolerance; through the steps, the overall design of the magnetic structure parameters of the magnetic resonance two-phase flow sensor is finally determined. The second step is to design the coil, firstly, a theoretical model of quantitative FID signal and the coil is established, and the flow velocity of two-phase flow, including phase, is fully analyzedThe FID as a function of coil length under the influence of rate; then researching structural parameter influence factors of the solenoid including wire diameter, turns, coil spacing, depth-height ratio and the like, and establishing relative signal-to-noise ratio Sn and sensitivity BxyThe response relation with the resistance R; finally aiming at the uniformity P of the radio frequency magnetic field3And (4) determining the structural parameters of the segmented coil and completing the design of the matching resonance parameters of the coil. Through the steps, the overall design of the coil structure parameters of the magnetic resonance two-phase flow sensor is finally determined. The parameter calculation method of the nuclear magnetic resonance two-phase flow sensor realizes more accurate measurement of the nuclear magnetic resonance sensor.
Drawings
FIG. 1 is a flow chart of a method for measuring and calculating a NMR two-phase flow sensor according to an embodiment of the invention, wherein FIG. 1a is a flow chart of the determination of NMR magnet structural parameters; FIG. 1b is a flow chart of the determination of structural parameters of the MRI coil in step two.
FIG. 2 is the variation rule of magnetization vector with magnetization length under different flow rates and different water contents in the present invention; wherein: FIG. 2(a) shows a flow velocity of 0.1m/s, and FIG. 2(b) shows a flow velocity of 0.3 m/s.
Fig. 3 is a schematic diagram of a Halbach structure adopted by the magnet of the present invention.
In fig. 4, a is a change rule of the magnetic field strength in the Halbach structure according to the ratio of the inner diameter to the outer diameter; b is the change rule of the magnetic field intensity in the Halbach structure along with the discrete block array N.
Fig. 5 is a two-dimensional plane distribution diagram and a curve trend diagram of the magnetic field of the magnet B determined by the invention.
FIG. 6 is a graph showing the effect of compensating magnet configuration parameters on magnetic field strength and uniformity in accordance with the present invention; wherein: FIG. 6(a) is a comparative schematic of an optimized sensor magnet configuration; fig. 6(b) shows the influence of the magnets C with different structural parameters on the uniformity of the magnetic field.
FIG. 7 is the change rule of the quantized value of the FID signal with the detection coil length under different average flow velocity and water content of the oil-water two-phase flow in the invention; FIG. 7(a) shows a flow velocity of 0.1m/s, and FIG. 7(b) shows a flow velocity of 0.3 m/s.
FIG. 8 is a diagram of solenoid coil physical model and structural parameters, wherein: fig. 8(a) is a physical model of a solenoid coil, and fig. 8(b) is a parameter diagram of the coil structure.
FIG. 9 is a diagram showing performance analysis of coil sensitivity, signal-to-noise ratio, etc. under different coil parameters; wherein: FIG. 9(a) is a graph of wire diameter, number of turns, and signal-to-noise ratio; FIG. 9(b) is a graph showing the relationship between the wire diameter, the pitch, and the quality factor.
FIG. 10 is a graph showing the effect on magnetic field uniformity using a segmented coil structure in comparison to a conventional structure, in which: FIG. 10(a) shows the variation of the magnetic field generated by the solenoid coil of the conventional structure along the axial direction (z-axis direction) of the pipe; fig. 10(b) shows the variation of the magnetic field generated by the optimized segmented solenoid coil along the axial direction (z-axis direction) of the pipeline.
Fig. 11 is a schematic diagram of a circuit employing a parallel resonant circuit.
Detailed Description
The following is for diameter
Figure BDA0002371767670000091
The invention is described in detail by taking an oil pipe as an example and combining the attached drawings:
the invention relates to a parameter measuring and calculating method of a nuclear magnetic resonance two-phase flow sensor, which mainly comprises two steps, wherein in the first step, aiming at magnet design, the length of a pre-magnetized magnet A is determined by analyzing the relationship between magnetization vectors and magnetization lengths with different flow rates and different water contents; then by researching Halbach structure and target magnetic field intensity B0And uniformity P1Determining the size parameter of the main measuring field B by adopting a particle swarm optimization algorithm and combining finite element simulation; by using the principle of magnetic field superposition, the target magnetic field uniformity P is obtained by the compensation magnet C2Determining the optimal size of the compensation magnet C within the error tolerance; through the steps, the overall design of the magnetic structure parameters of the magnetic resonance two-phase flow sensor is finally determined. Secondly, aiming at coil design, firstly establishing a theoretical model for quantifying an FID signal and a coil, and fully analyzing the functional relation between the FID and the coil length under the influence of the phase content rate and the flow velocity of two-phase flow; then the solenoid including wire diameter, turns, coil spacing, depth-height ratio and other junctions is studiedConstructing parameter influence factors, establishing relative signal-to-noise ratio Sn and sensitivity BxyThe response relation with the resistance R; finally aiming at the uniformity P of the radio frequency magnetic field3And (4) determining the structural parameters of the segmented coil and completing the design of the matching resonance parameters of the coil. Through the steps, the overall design of the coil structure parameters of the magnetic resonance two-phase flow sensor is finally determined. The parameter calculation method of the nuclear magnetic resonance two-phase flow sensor realizes more accurate measurement of the nuclear magnetic resonance sensor.
With reference to fig. 1, the present invention comprises the following steps in detail:
the first step is as follows: the method comprises the following steps of determining the structural parameters of a magnet of the nuclear magnetic resonance two-phase flow sensor, wherein the magnet is formed by sequentially connecting a pre-magnetized magnet A, a measuring magnet B and a compensating magnet C on a coaxial line to form a three-section Halbach cylinder array structure, and the method specifically comprises the following steps:
1. determining the length of a pre-magnetized magnet A
(1) Determining the functional relationship among the flow velocity, the water content, the magnetization vector and the magnetization length according to the flow characteristics of the oil-water two-phase flow, wherein the expression is as follows:
Figure BDA0002371767670000101
where M is the actual magnetization vector, M0Is the vector of complete magnetization, x is the magnetization length, v is the average flow velocity of oil-water two-phase flow, T1The longitudinal relaxation time of the oil-water two-phase flow is related to the phase content a% of the oil-water two-phase flow, T2The transverse relaxation time of the oil-water two-phase flow;
(2) obtaining a normalized magnetization vector according to the calculation formula 1
Figure BDA0002371767670000102
Figure BDA0002371767670000103
Analyzing the magnetization vector M/M under different water content a% and different flow velocity v0Characteristic relationship with magnetization length;
(3) according to M/M0Finding the magnetization vector M/M according to the curve diagram of the magnetization length0The corresponding magnetization length when approaching the maximum value of 1, thereby determining the length of the pre-magnetized magnet a;
and (3) analyzing the change rule of the magnetization vector of the oil-water two-phase flow along with the magnetization length under different average flow velocities v and different water contents a% by combining the graph 2. FIG. 2 shows the magnetization vector as a function of the magnetization length for different average flow rates (0.1m/s, 0.3m/s) and different water contents (10%, 30%, 50%, 70%) of the oil-water mixture. Under a constant flow rate, the magnetization length to achieve complete magnetization becomes longer as the water content increases. Under the condition of a certain water content, the magnetization vector tends to be downward along with the increase of the flow speed. Further, at the same water content and flow rate, the magnetization vector gradually increases and stabilizes as the magnetization length increases. It can be seen that when the water content is less than 50% at a flow rate of 0.1m/s, the magnetization vector tends to be stable already when the magnetization length is in the range of 0.1-0.2 m; when the water content is less than 50% at a flow rate of 0.3m/s, the magnetization vector reaches a steady state when the magnetization length is in the range of 0.3 to 0.5 m. Therefore, the length of the pre-polarized magnet A is determined to be 0.3m by combining the effective utilization rate of the magnet aiming at the low flow rate and low water content state of the small pipe diameter.
2. Measuring parameters of magnet B
(1) Establishing a magnetic field two-dimensional plane uniformity expression by adopting a Halbach magnet array
Figure BDA0002371767670000111
Wherein
Figure BDA0002371767670000112
For the mean magnetic field strength of the working space, BmaxFor a large field strength quantization value of the working range, BminA quantized value of the magnetic field strength in a lower working interval is obtained;
(2) determining a discrete Halbach mathematical model, and respectively researching the magnetic field intensity B according to four parameters of an internal-external diameter ratio value R/R, the number N of assembly blocks, the shape of the blocks and a magnetic material0The following calculation model is obtained:
Figure BDA0002371767670000113
wherein: b is0Strength of static magnetic field generated for magnet, BrThe residual magnetic flux density is shown, R is the outer radius of the magnet, R is the inner radius, and n is the number of magnet blocks;
(3) establishing a particle swarm optimization model according to a formula (2), wherein the shape of the blocks influences the error between the integral performance and the ideal structure of the discrete Halbach, and the magnetic material influences the residual magnetic flux density BrInfluence of the number of building blocks N
Figure BDA0002371767670000114
The numerical relationship of (1), the influence of the inner and outer diameter ratio values
Figure BDA0002371767670000115
Using finite element simulation to comprehensively analyze the magnetic field intensity B0Two-dimensional plane uniformity P of magnetic field1The rule of the change of the parameters of the four magnets;
as shown in fig. 3, which is a schematic diagram of an ideal Halbach array, the discrete Halbach structure can be assembled in a square, circular or fan shape as a single magnet. The sector is closest to the ideal state by finite element simulation method analysis. According to various performance parameters, namely, residual magnetism Br, coercive force Hc, intrinsic coercive force Hcj, maximum magnetic energy product W and Curie temperature Tc, given in the table 1, the neodymium iron boron with moderate cost performance is finally selected by combining with the analysis of actual requirements.
TABLE 1 comparison of the properties of various materials of different permanent magnets
Figure BDA0002371767670000121
TABLE 1
Fig. 4(a) shows the simulation results of 8 sub-block Halbach arrays of 2 different sizes, respectively. The circular radiuses of the inner cavities are 15mm, and the outer radiuses are 20mm and 25mm respectively. I.e. the ratio of the inner diameter to the outer diameter is 3/4 and 3/5 respectively, and the obtained magnetic field strength is 0.165T and 0.301T respectively. Therefore, when the working area is constant, the strength of the magnetic induction increases as the thickness of the magnet increases, i.e., the inner-outer diameter ratio decreases. Fig. 4(b) shows the magnetic induction distribution plots of 4,8 and 16 Halbach arrays of the same material and the same size, respectively, and from the simulation results, it is shown that as the number N of permanent magnet blocks increases (4,8,16), the magnetic induction and uniformity generated in the hollow region also increases (0.25T,0.36T, 0.5T).
Combining the simulation results to obtain the magnetic field intensity B through comprehensive analysis0、P1The law of the change of the parameters of the four magnets. The magnetic induction strength and uniformity of the Halbach array are mainly related to the shape and the number of blocks of the assembled magnet, the ratio of the inner diameter to the outer diameter, the performance of the permanent magnet material and the like. In determining the target intensity B0、P1The optimal solution meeting the result is obtained by integrating the changes of a plurality of influence parameters, which is a typical electromagnetic field inversion problem applying a particle swarm optimization algorithm.
(4) According to the simulation analysis result, determining the restriction relation and the influence rule among the parameters, and finding out the magnetic field intensity B meeting the requirement0And P is1Determining the optimal parameters with high uniformity, thereby determining various structural parameters of the measuring magnet B;
in connection with fig. 5, for diameter
Figure BDA0002371767670000131
An oil pipe, considering that 16 magnets in actual processing are difficult to assemble and easy to generate errors, the sensor adopts an 8-subblock Halbach array made of neodymium iron boron (with residual magnetism of about 1.1T) materials, and according to the steps, the results of calculation analysis and simulation are obtained and the magnetic field intensity B is used0Target 0.27T, and compromise P1The effective range and uniformity effect design optimizes the structure size of the magnet B. Finally, the length of the magnet B is determined to be 200mm, the outer radius is 40mm, and the inner radius is 30 mm. The two-dimensional distribution and curve trend chart of the magnetic field plane is shown in fig. 5, and the magnetic field intensity is satisfied while the magnetic field uniformity is good.
3. Compensating magnet C parameter
(1) Study of three-dimensional axial magnetic field uniformity
Figure BDA0002371767670000132
The relationship to the length of the magnet. Wherein
Figure BDA0002371767670000133
For the axial (z-direction) average field strength, it can be concluded that the field homogeneity P increases infinitely with the magnet length2The improvement is achieved, but in practice the magnet length dimension is limited, so that the method of adding the compensation magnet C at the two ends of the measurement magnet B (with the length of 200mm) is provided for improving the axial magnetic field uniformity P2；
(2) Adding a compensation magnet C to axial magnetic field uniformity P through finite element static magnetic field simulation analysis according to Maxwell equation of three-dimensional static magnetic field and magnetic induction calculation formula of permanent magnet2Influence relationship of (1):
Figure BDA0002371767670000134
Figure BDA0002371767670000135
Figure BDA0002371767670000141
b (x, y, z) is magnetic induction, H (x, y, z) is magnetic field intensity, J (x, y, z) is current density, and the three vectors are all in function of vectors in all directions. Wherein, mu0Is the absolute permeability in vacuum, murFor relative permeability, MPThe polarization intensity of the permanent magnetic material;
as described in detail with reference to fig. 6, the influence of the change in the compensation magnet C on the magnetic field strength was investigated on the basis of the holding magnet B. FIG. 6a is a schematic diagram of the original structure and the improved structure of the magnet, and FIG. 6b is a schematic diagram of the dimensional parameters of different magnets C versus the magnetic field uniformity P2The influence law of (2). Wherein, the axial length of the compensation magnet is 10mm and the radial thickness is 15mm in figure (2), the axial length of the compensation magnet is 15mm and the radial thickness is 15mm in figure (3), the axial length of the compensation magnet is 15mm and the radial thickness is 18mm in figure (4), and the axial length and the radial thickness can be seenThe axial uniformity P of the magnetic field is obtained by continuously changing the radial thickness and the axial length of the compensation magnet C2Improved and enhanced to various degrees.
(3) According to simulation analysis, comparing the axial magnetic field uniformity P of the magnets C with different structural sizes2Finding the magnet parameters with the highest optimization on the magnetic field uniformity and the smallest volume, thereby determining the size of the compensation magnet C;
through the analysis of the steps, the compensation magnet C and the axial uniformity P are determined2In increasing P2The volume of the magnet should be kept as small as possible in terms of diameter on the premise of uniformity
Figure BDA0002371767670000142
And an oil pipe, wherein the axial length of the finally determined compensating magnet C is 15mm, and the radial thickness of the finally determined compensating magnet C is 15 mm.
And finally determining the overall design of the magnetic structure parameters of the magnetic resonance two-phase flow sensor according to the steps and the analysis result.
The second step is that: the method for determining the structural parameters of the coil of the nuclear magnetic resonance two-phase flow sensor comprises four steps as follows:
the first part of the steps are as follows:
1. and establishing a theoretical model of the quantitative FID signal and the coil, and determining the functional relation between the nuclear magnetic resonance receiving signal FID and the coil length. Obtaining nuclear magnetic resonance receiving signals FID under different average flow velocities v and different water contents, wherein the expression is as follows:
Figure BDA0002371767670000151
wherein: sFIDFor quantizing the FID signal received by the coil, where Mi0＝SiHI，i，SiIs the saturation of the ith component, H, in a two-phase flowI，iIs the hydrogen index, L, of the ith component in a two-phase flowDIs the length of the coil, LMFor the length of magnetization, T is the sampling time, c is the correction factor, T1，iIs the spin lattice relaxation of the ith componentTime of relaxation, T2，iIs the spin-spin relaxation time of the ith component;
2. analyzing the quantitative FID signal S received by the coil under the model with different average flow velocity v and different water content a% according to the formula (4)FIDThe rule of variation with the length of the coil;
3. quantitative FID signal S received by analysis coilFIDThe corresponding coil length tends to be stable, so that the basic length parameter range of the detection coil is determined;
referring to FIG. 7, the water contents are 10%, 30%, 50%, and 70%, respectively, and the average flow rates are 0.1m/s and 0.3m/s, respectively. At the same water cut and flow rate, the FID signal gradually increases and stabilizes as the detector coil length increases. At the same flow rate, the FID signal increases with increasing water cut. At the same water content, the FID signal decreased with increasing flow rate. For lower average flow velocity and lower water content, when the length of the coil of the detector is in the range of 0.4-0.6m, the FID signal tends to be stable;
the second part of the steps are as follows:
1. establishing a theoretical model of coil performance and solenoid parameters, and determining coil sensitivity BxyThe influence factor of (c): the distance g, the number of turns N, the wire diameter D and the pipe diameter ratio H/D;
Figure BDA0002371767670000152
wherein, B1I is the radio frequency magnetic field intensity B generated by a unit current i in the coil1N is the number of turns of the coil, H/D is the ratio of depth to height of the tube diameter, H is the height of the solenoid coil, D is the diameter of the coil, u0Is a vacuum magnetic permeability. FIG. 8 is a schematic diagram of a solenoid model and the physical parameters involved;
2. establishing an equivalent model of coil resistance R under the skin effect and the proximity effect, and obtaining the following expression:
Figure BDA0002371767670000161
wherein R iscoilIs the resistance value of an equivalent straight wire at radio frequency, epsilon is the enhancement factor of two adjacent turns of coils, RsFor the equivalent resistance model, l is the length of the wire used by the coil, d is the wire diameter of the coil, f is the resonance frequency of the coil, mu is the magnetic permeability, and rho is the resistivity of the copper wire. The coil is an enameled copper wire, and the skin effect of the metal conductor under the high-frequency condition is considered
Figure BDA0002371767670000162
The wire diameter should be greater than or equal to twice the skin depth;
3. establishing relative signal-to-noise ratio SNR and sensitivity B under fixed pulse frequencyxyAnd a resistance RsThe response relationship of (a) is shown in formula 7; analyzing the influence rule of each parameter of the coil on the SNR by applying a particle swarm optimization algorithm and combining finite element simulation;
Figure BDA0002371767670000163
Figure BDA0002371767670000164
wherein: b isxyIs the sensitivity of the coil; k is a reaction radio frequency magnetic field B1Constant of homogeneity, vsFor detecting the volume of the sample, N is the number of nuclear spins per unit volume, γ is the magnetic spin ratio of the atoms, h is Planckian, I is the spin quantum number of the nuclei, w0Is the precession frequency of the nucleus, KBIs Boltzmann constant, RsIs the coil resistance, T is the temperature of the test sample; Δ f is the measured bandwidth;
in designing the solenoid radio frequency coil, the above parameters are mutually influenced, which is a typical particle swarm optimization problem. The higher the magnetic field per unit current, the lower the radio frequency resistance of the coil, and the higher the SNR, given the magnetic field B0 and the particular sample conditions. In short, the main optimization direction is to obtain the best relative signal-to-noise ratio by maximizing the coil sensitivity and minimizing the effective resistance. To obtain high-quality images, the transmitting coil is required to have high energy conversion speed and high efficiency, and the radio frequency field is required to be highly uniform so as to ensure that the excited biological samples obtain uniform excitation intensity; for the receiving coil, it is essential that the sensitivity of the detection is high to ensure a sufficient signal-to-noise ratio.
With reference to FIG. 9(a), the diameter of the coil is controlled between 0.6mm and 1.5mm in the process of manufacturing the coil of the small-diameter nuclear magnetic resonance multiphase flow sensor in a static magnetic field B0In a static magnetic field environment of 100mt, the proton resonance frequency is 4 MHz. Considering the coil driving transmitting power and the current carrying capacity, an enameled copper wire is selected according to 2.5-3A per square millimeter, the influence rule of the number of turns of the coil on the signal to noise ratio under different wire diameters is researched, as shown in fig. 9(a), when the wire diameter is 0.5mm, the quantized signal to noise ratio reaches the maximum value when the number of turns is between 25 and 30 turns; when the wire diameter is 1mm, the quantized signal-to-noise ratio reaches the maximum between 10 and 15 turns. When the wire diameter is 1.5mm, the quantized signal-to-noise ratio reaches the maximum between 5 and 10 turns.
With reference to fig. 9(b), at a certain line diameter d, as the coil pitch p increases, the resistance and the inductance of the coil gradually decrease, and the Q value of the quality factor tends to increase and decrease due to the influence of the skin effect and the proximity effect. As can be seen from the figure, the value of the coil quality factor is maximized for different wire diameters d when the pitch p is equal to 1 times the wire diameter, i.e., g — d.
4. According to the above influence factors and result analysis, the high sensitivity B is obtainedxyAnd high signal-to-noise ratio SNR. Through the above steps, calculation and analysis are carried out for the diameter
Figure BDA0002371767670000171
An oil pipe, wherein the wire diameter is determined to be 1mm, and the number of turns is 15;
the third part of the steps are as follows:
1. establishing a solenoid coil to generate a radio frequency magnetic field B1The theoretical model of (2) calculates the intensity of the radio frequency magnetic field generated by the coil, and the calculation formula is as follows:
Figure BDA0002371767670000181
wherein: mu.s0The magnetic field strength is vacuum magnetic conductivity, N is the number of turns of a coil, I is the current intensity of the coil, H is the height of a solenoid coil, R is the radius of the solenoid coil, and Z is the distance from any point of an axial space of the solenoid to a central point;
referring to fig. 8, the solenoid coil can be seen as being composed of a plurality of coaxial circular coils with the same radius, and when the length of the solenoid and the number of turns of the coil are known, the current flowing into the solenoid coil is constant, and the current density of the coil per unit length can be calculated. And (3) completing the integration of Z' on the solenoid coil with the height H to obtain the magnetic induction intensity of any point p on the axis.
2. Analysis of the radio frequency magnetic field B by finite element magnetic field simulation according to equation (8)1And calculating the uniformity of the RF magnetic field in the target space
Figure BDA0002371767670000182
Is the average intensity of the radio frequency magnetic field;
3. by analyzing the change rule of the magnetic field intensity in the solenoid space, the result that the magnetic field intensity in the middle of the pipeline is high and gradually decreases towards the two ends is obtained. Therefore, a sectional type (sparse in the middle and compact at two ends) coil structure is provided, and the purposes of weakening the magnetic field intensity in the middle section and enhancing the magnetic field intensity at two ends are achieved by adjusting the space proportion of three sections of coils, so that the uniformity of the whole radio frequency magnetic field is improved;
with reference to fig. 10, in a certain detection range, as the number of turns of the coil is continuously increased and the coverage area is larger, the uniform range of the obtained radio frequency magnetic field is higher and higher, but if the uniform range of the magnetic field is desired to be improved, the length and the number of turns of the coil cannot be increased at a time, infinite increase of resistance of the coil is caused, and signal to noise ratio is greatly reduced. As can be seen from the graph of figure 10,the radio frequency magnetic field generated by the optimized coil structure tends to be stable relative to the magnetic field generated by the original structure, the variation amplitude is reduced, the integral uniformity P3 is improved, and the error allowable range of the magnetic resonance device is met. Thus aiming at the diameter
Figure BDA0002371767670000194
And the oil pipe adopts a winding mode of density combination to improve the uniformity of a magnetic field on the basis of ensuring the optimal signal-to-noise ratio under the condition that the number of turns and the length of the front part of coils are not changed. The parameters finally determined are: the diameter of the wire is 1mm, the number of turns is 16, the middle part is 8, the turn interval is 1mm, the two ends are respectively 4, and the turn interval is 0.5 mm.
The fourth step is as follows:
1. the resonance characteristics of the radio frequency system were studied. Firstly, measuring various parameter values of a coil under a fixed frequency by using an impedance analyzer, wherein the parameter values comprise a resistor R, an inductance L and a capacitance C;
2. and establishing an RLC matching response relation, and calculating to obtain various matching parameters of the coil quality factor according to the following expression. Wherein Z is the total impedance, W is the frequency, CmCapacitors, C, connected in series with the desired matching circuittConnecting capacitors in parallel to the obtained matching circuit, wherein R is the actually measured coil resistance value, L is the coil inductance value, and j is a physical vector;
Figure BDA0002371767670000191
Figure BDA0002371767670000192
Figure BDA0002371767670000193
referring to fig. 11, which is a schematic diagram of a resonant matching circuit adopted by a coil, the characteristic impedance of the nmr power amplification system and the coaxial cable in this study is 50 Ω, and the resonant frequency is consistent with the larmor resonant frequency. From the above-mentioned calculation formula 9 and circuit analysis, let Z equal 50 Ω, it is possible to determine the designThe theoretical parameters of inductance, capacitance and supplementary resistance needed by the antenna. During the matching tuning process of the radio frequency coil, an eddy current effect is generated due to the action of the magnet, so that the alternating current resistance and the alternating current inductance of the coil are changed. Therefore, the radio frequency coil needs to be in an actual working position in the processes of measuring coil parameters, matching and tuning, the total impedance is kept to be 50 omega, and C is adjustedmAnd CtIs such that the resonance frequency of the matching circuit reaches the larmor resonance frequency point of the magnetic resonance system.
And finally determining the integral design of the coil structure parameters of the magnetic resonance two-phase flow sensor according to the steps and the analysis result.

Claims (1)

1. A method for measuring and calculating a nuclear magnetic resonance two-phase flow sensor is characterized by comprising the following steps:
the first step is as follows: the method comprises the following steps of determining the structural parameters of a magnet of the nuclear magnetic resonance two-phase flow sensor, wherein the magnet is formed by sequentially connecting a pre-magnetized magnet A, a measuring magnet B and a compensating magnet C on a coaxial line, and the method comprises the following specific steps:
1. determining the length of a pre-magnetized magnet A
(1) Determining the functional relationship among the flow velocity, the water content, the magnetization vector and the magnetization length according to the flow characteristics of the oil-water two-phase flow, wherein the expression is as follows:
Figure FDA0002371767660000011
where M is the actual magnetization vector, M0Is the vector of complete magnetization, x is the magnetization length, v is the average flow velocity of oil-water two-phase flow, T1The longitudinal relaxation time of the oil-water two-phase flow is related to the phase content a% of the oil-water two-phase flow, T2The transverse relaxation time of the oil-water two-phase flow;
(2) obtaining a normalized magnetization vector according to equation (1)
Figure FDA0002371767660000012
Figure FDA0002371767660000013
Analyzing the magnetization vector M/M under different water content a% and different flow velocity v0Characteristic relationship with magnetization length;
(3) according to M/M0Finding the magnetization vector M/M according to the curve diagram of the magnetization length0The corresponding magnetization length when approaching the maximum value of 1, thereby determining the length of the pre-magnetized magnet a;
2. measuring parameters of magnet B
(1) Establishing a magnetic field two-dimensional plane uniformity expression by adopting a Halbach magnet array
Figure FDA0002371767660000014
Wherein
Figure FDA0002371767660000015
Average static magnetic field strength, B, generated for a working space magnetmaxFor a large field strength quantization value of the working range, BminA quantized value of the magnetic field strength in a lower working interval is obtained;
(2) determining a discrete Halbach mathematical model, and respectively researching the magnetic field intensity B according to four parameters of an internal-external diameter ratio value R/R, the number N of assembly blocks, the shape of the blocks and a magnetic material0The following calculation model is obtained:
Figure FDA0002371767660000021
wherein: b is0Strength of static magnetic field generated for magnet, BrThe residual magnetic flux density is shown, R is the outer radius of the magnet, R is the inner radius, and n is the number of magnet blocks;
(3) establishing a particle swarm optimization model according to a formula (2), wherein the shape of the blocks influences the error between the integral performance and the ideal structure of the discrete Halbach, and the magnetic material influences the residual magnetic flux density BrInfluence of the number of building blocks N
Figure FDA0002371767660000022
Numerical relationship ofInfluence of inner and outer diameter ratio
Figure FDA0002371767660000023
Using finite element simulation to comprehensively analyze the magnetic field intensity B0Two-dimensional plane uniformity P of magnetic field1The rule of the change of the parameters of the four magnets;
(4) according to the simulation analysis result, determining the restriction relation and the influence rule among the parameters, and finding out the magnetic field intensity B meeting the requirement0And the magnetic field two-dimensional plane uniformity P1The parameter with the highest uniformity, thereby determining each structural parameter of the measuring magnet B;
3. determining parameters of the bucking magnet C
(1) Study of three-dimensional axial magnetic field uniformity
Figure FDA0002371767660000024
Relationship to magnet length: wherein the content of the first and second substances,
Figure FDA0002371767660000025
for the average field strength in the axial z-direction, it can be concluded that the field homogeneity P increases infinitely with the magnet length2The axial magnetic field uniformity P is improved by adding the compensation magnets C at two ends of the measurement magnet B2；
(2) According to Maxwell equation of three-position static magnetic field and calculation formula of magnetic induction intensity of permanent magnet, obtaining uniformity P of compensation magnets C with different sizes to axial magnetic field by finite element static magnetic field simulation2Influence relationship of (1):
B(x，y，z)＝μ0·μr·H+μ0·MP
Figure FDA0002371767660000031
Figure FDA0002371767660000032
wherein B (x, y, z) is magnetic induction, H (x, y, z) is magnetic field intensity, J (x, y, z) is current density, the three vectors are all functional relations of vectors in all directions, and mu0Is the absolute permeability in vacuum, murFor relative permeability, MPThe polarization intensity of the permanent magnetic material;
(3) according to simulation analysis, comparing the axial magnetic field uniformity P of the magnets C with different structural sizes2Finding the magnet parameters with the highest optimization on the magnetic field uniformity and the smallest volume, thereby determining the size of the compensation magnet C;
finally determining the integral design of the magnet structure parameters of the magnetic resonance two-phase flow sensor according to the steps and the analysis result;
the second step is that: the method for determining the structural parameters of the coil of the nuclear magnetic resonance two-phase flow sensor comprises four steps as follows:
the first part of the steps are as follows:
1. establishing a theoretical model of a quantitative FID signal and a coil, determining a functional relation between a nuclear magnetic resonance receiving signal FID and the length of the coil, and solving the nuclear magnetic resonance receiving signal FID under different average flow velocities v and different water contents a%, wherein the expression is as follows:
Figure FDA0002371767660000033
wherein: sFIDFor quantizing the FID signal received by the coil, where Mi0＝SiHI，i，SiIs the saturation of the ith component, H, in a two-phase flowI，iIs the hydrogen index, L, of the ith component in a two-phase flowDIs the length of the coil, LMFor the length of magnetization, T is the sampling time, c is the correction factor, T1，iIs the spin lattice relaxation time, T, of the ith component2，iIs the spin-spin relaxation time of the ith component;
2. analyzing FID signals S received by coils under models with different average flow velocities v and different water contents a% according to a formula (4)FIDThe rule of variation with the length of the coil;
3. by analysing the FID signal S received by the coilFIDThe corresponding coil length tends to be stable, so that the basic length parameter range of the detection coil is determined;
the second part of the steps are as follows:
1. theoretical models of coil performance and solenoid parameters were established, and the impact factor of coil sensitivity Bxy was determined:
Figure FDA0002371767660000041
wherein, B1I is the radio frequency magnetic field intensity B generated by a unit current i in the coil1N is the number of turns of the coil, H/D is the ratio of depth to height of the tube diameter, H is the height of the solenoid coil, D is the diameter of the coil, u0Is a vacuum magnetic conductivity;
2. establishing an equivalent model of coil resistance R under the skin effect and the proximity effect, and obtaining the following expression:
Figure FDA0002371767660000042
wherein R iscoilIs the resistance value of an equivalent straight wire at radio frequency, epsilon is the enhancement factor of two adjacent turns of coils, RsThe method is an equivalent resistance model, wherein l is the length of a lead used by a coil, d is the wire diameter of the coil, f is the resonance frequency of the coil, mu is the magnetic conductivity, and rho is the resistivity of a copper lead;
3. establishing relative signal-to-noise ratio SNR and sensitivity B under fixed pulse frequencyxyAnd a resistance RsThe response relationship of (a) is shown in formula 7; and analyzing the influence rule of each parameter of the coil on the SNR by applying a particle swarm optimization algorithm and combining finite element simulation:
Figure FDA0002371767660000043
Figure FDA0002371767660000044
wherein: b isxyIs the sensitivity of the coil; k is a reaction radio frequency magnetic field B1Constant of homogeneity, vSFor detecting the volume of the sample, N is the number of nuclear spins per unit volume, γ is the magnetic spin ratio of the atoms, h is Planckian, I is the spin quantum number of the nuclei, w0Is the precession frequency of the nucleus, KBIs Boltzmann constant, RsIs the coil resistance, T is the temperature of the test sample; Δ f is the measured bandwidth;
4. according to the above influence factors and result analysis, the high sensitivity B is obtainedxyAnd coil parameters of high signal-to-noise ratio (SNR);
the third part of the steps are as follows:
1. establishing a solenoid coil to generate a radio frequency magnetic field B1The theoretical model of (2) calculates the intensity of the radio frequency magnetic field generated by the coil, and the calculation formula is as follows:
Figure FDA0002371767660000051
wherein: mu.s0The magnetic field strength is vacuum magnetic conductivity, N is the number of turns of a coil, I is the current intensity of the coil, H is the height of a solenoid coil, R is the radius of the solenoid coil, and Z is the distance from any point of an axial space of the solenoid to a central point;
2. analysis of the radio frequency magnetic field B by finite element magnetic field simulation according to equation (8)1And calculating the uniformity of the RF magnetic field in the target space
Figure FDA0002371767660000052
Figure FDA0002371767660000053
Is the average intensity of the radio frequency magnetic field;
3. by analyzing the change rule of the magnetic field intensity in the solenoid space, the result that the magnetic field intensity in the middle of the pipeline is high and gradually decreases when going to the two ends is obtained, so that a coil structure with sparse middle and compact and sectional type at the two ends is provided, and the purposes of weakening the magnetic field intensity in the middle section and enhancing the magnetic field intensity at the two ends are achieved by adjusting the space proportion of three sections of coils, so that the uniformity of the whole radio frequency magnetic field is improved;
the fourth step is as follows:
1. the resonance characteristic of a radio frequency system is researched, and various parameter values of a coil under a fixed frequency, including a resistor R, an inductance L and a capacitance C, are measured by using an impedance analyzer;
2. establishing an RLC matching response relation, and calculating to obtain various matching parameters of the coil quality factor according to the following expression, wherein Z is total impedance, W is frequency, and C ismCapacitors, C, connected in series with the desired matching circuittConnecting capacitors in parallel to the obtained matching circuit, wherein R is the actually measured coil resistance value, L is the coil inductance value, and j is a physical vector;
Figure FDA0002371767660000061
Figure FDA0002371767660000062
Figure FDA0002371767660000063
and finally determining the integral design of the coil structure parameters of the magnetic resonance two-phase flow sensor according to the steps and the analysis result.
CN202010052741.XA 2020-01-17 2020-01-17 Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor Active CN111175336B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010052741.XA CN111175336B (en) 2020-01-17 2020-01-17 Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010052741.XA CN111175336B (en) 2020-01-17 2020-01-17 Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor

Publications (2)

Publication Number Publication Date
CN111175336A true CN111175336A (en) 2020-05-19
CN111175336B CN111175336B (en) 2023-04-07

Family

ID=70657982

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010052741.XA Active CN111175336B (en) 2020-01-17 2020-01-17 Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor

Country Status (1)

Country Link
CN (1) CN111175336B (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112711876A (en) * 2020-12-17 2021-04-27 中国人民解放军国防科技大学 Dipole uniform magnetic field coil design method capable of reducing magnetic shielding coupling effect
CN113109882A (en) * 2021-04-13 2021-07-13 西安华舜测量设备有限责任公司 Matching device and method
CN114236440A (en) * 2021-11-16 2022-03-25 中国科学院深圳先进技术研究院 Shimming method and device, electronic equipment and storage medium
CN114446397A (en) * 2020-10-19 2022-05-06 中国石油化工股份有限公司 Memory, refining process flow segmentation simulation and optimization method, device and equipment
CN115062507A (en) * 2022-05-31 2022-09-16 广东博亿精科传感有限公司 Design method of coreless coil, sensor, device and storage medium

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1566990A (en) * 2003-07-03 2005-01-19 石油大学(北京) Method and apparatus for measuring characteristic for fluid in downhole well casing based on nuclear magnetic resonance
US20110001474A1 (en) * 2009-07-06 2011-01-06 Cema Technologies, Llc Nmr instrumentation and flow meter/controller methods and apparatus
US20160077026A1 (en) * 2014-09-16 2016-03-17 Spinlock Srl Method and an apparatus to measure flow properties, including flow rates, regime and relative concentrations of phases in multiphasic fluids using nuclear magnetic resonance relaxation in the rotating frame
CN108828057A (en) * 2018-06-26 2018-11-16 西安石油大学 A kind of oil-water two-phase flow Multi-parameter detection device and method based on electromagnetism acoustical coupling

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1566990A (en) * 2003-07-03 2005-01-19 石油大学(北京) Method and apparatus for measuring characteristic for fluid in downhole well casing based on nuclear magnetic resonance
US20110001474A1 (en) * 2009-07-06 2011-01-06 Cema Technologies, Llc Nmr instrumentation and flow meter/controller methods and apparatus
US20160077026A1 (en) * 2014-09-16 2016-03-17 Spinlock Srl Method and an apparatus to measure flow properties, including flow rates, regime and relative concentrations of phases in multiphasic fluids using nuclear magnetic resonance relaxation in the rotating frame
CN108828057A (en) * 2018-06-26 2018-11-16 西安石油大学 A kind of oil-water two-phase flow Multi-parameter detection device and method based on electromagnetism acoustical coupling

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
KEELAN T. O\'NEILL.ETC: "Two-phase oil/water flow measurement using an Earth’s field nuclear magnetic resonance flow meter" *
尹升华;薛振林;吴爱祥;刘超;李红;: "基于核磁共振成像技术的堆浸细观渗流速度场特性" *
李晓南;刘国强;胡丽丽;: "核磁共振高信噪比弱信号检测的理论与实验研究" *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114446397A (en) * 2020-10-19 2022-05-06 中国石油化工股份有限公司 Memory, refining process flow segmentation simulation and optimization method, device and equipment
CN112711876A (en) * 2020-12-17 2021-04-27 中国人民解放军国防科技大学 Dipole uniform magnetic field coil design method capable of reducing magnetic shielding coupling effect
CN113109882A (en) * 2021-04-13 2021-07-13 西安华舜测量设备有限责任公司 Matching device and method
CN113109882B (en) * 2021-04-13 2024-04-26 西安华舜测量设备有限责任公司 Matching device and method
CN114236440A (en) * 2021-11-16 2022-03-25 中国科学院深圳先进技术研究院 Shimming method and device, electronic equipment and storage medium
CN115062507A (en) * 2022-05-31 2022-09-16 广东博亿精科传感有限公司 Design method of coreless coil, sensor, device and storage medium

Also Published As

Publication number Publication date
CN111175336B (en) 2023-04-07

Similar Documents

Publication Publication Date Title
CN111175336B (en) Method for measuring and calculating nuclear magnetic resonance two-phase flow sensor
Kleinberg et al. Novel NMR apparatus for investigating an external sample
Blümich et al. Mobile single-sided NMR
Massin et al. Planar microcoil-based microfluidic NMR probes
US7683613B2 (en) High pressure/high temperature magnetic resonance tool
US4717876A (en) NMR magnet system for well logging
WO2013037093A1 (en) Nuclear magnetic resonance rock sample analysis method and instrument with constant gradient field
Anferova et al. Construction of a NMR‐MOUSE with short dead time
Perlo et al. Optimized slim-line logging NMR tool to measure soil moisture in situ
CN107703174B (en) Nuclear magnetic resonance fluid analyzer and preparation method thereof
RU2367982C1 (en) Method of logging with application of nuclear-magnetic resonance and device for its realisation
Anferova et al. A mobile NMR device for measurements of porosity and pore size distributions of drilled core samples
US20140091800A1 (en) Nmr sample containment
Shi et al. A proposed NMR solution for multi-phase flow fluid detection
Luo et al. Design of an innovative downhole NMR scanning probe
Xu et al. Optimization of inside-out nuclear magnetic resonance sensor with logging-while-drilling tool specification and experimental validation
Yang et al. A low-cost, miniature Halbach magnet designed for portable time domain NMR
Wu et al. Sensor design and implementation for a downhole NMR fluid analysis laboratory
Blümich et al. Magnets for small-scale and portable NMR
Suits et al. Optimizing surface coils and the self-shielded gradiometer
Demas et al. Electronic characterization of lithographically patterned microcoils for high sensitivity NMR detection
Zhu et al. High depth resolution design of small diameter nuclear magnetic resonance logging probe based on compensating magnets for soil moisture measurement in situ
RU2181901C1 (en) Logging method and device using nuclear-magnetic resonance
US7486078B1 (en) Compact orthogonal NMR field sensor
Ali et al. Design of planar microcoil-based NMR probe ensuring high SNR

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
GR01 Patent grant
GR01 Patent grant