Well deviation and geomagnetic field intensity measuring system based on high-precision fluxgate sensor

Abstract

The invention relates to the technical field of measurement, in particular to a well deviation and geomagnetic field intensity measurement system based on a high-precision fluxgate sensor. Comprising a fluxgate sensor group, a magnetic field data analysis part and a measurement result calculation part, the fluxgate sensor group comprises high-precision fluxgate sensors for respectively measuring magnetic field components in the X-axis direction, the Y-axis direction and the Z-axis direction; the magnetic field analysis part is used for constructing a magnetic field gradient tensor according to the physical parameters of the high-precision fluxgate sensor, the effective magnetic conductivity and the corrected magnetic field component in each direction, and separating a geomagnetic field vector from the total magnetic field vector according to the magnetic field gradient tensor; and the measurement result calculation part is used for calculating a hole drift angle value and an azimuth angle value according to the geomagnetic field vector. According to the method, the precision, robustness and environment adaptability of underground magnetic field measurement are remarkably improved. The geomagnetic field vector can be accurately extracted, and high-precision calculation of the hole drift angle and the azimuth angle is achieved.

Description

Technical Field

[0001] The invention belongs to the field of measurement technology, and in particular relates to a well inclination and geomagnetic field intensity measurement system based on a high-precision fluxgate sensor. Background Art

[0002] The survey and monitoring technology of underground environment is an important part of oil and gas exploration and mineral resource development. Especially under complex geological conditions, the magnetic field information underground can provide key support for resource positioning, wellbore stability assessment and drilling accuracy optimization. At present, geomagnetic field measurement technology is widely used in underground operations. Its core is to use high-precision magnetic field sensors to sense the geomagnetic field components in the three-dimensional space underground, so as to calculate key parameters such as well inclination and azimuth. However, there are many limitations in the existing technology, which makes it difficult for the accuracy, robustness and environmental adaptability of underground magnetic field measurement to meet the high-demand engineering application requirements.

[0003] At present, magnetic field measurement technology mainly relies on equipment such as Hall effect sensors, optical pump magnetometers and fluxgate sensors. Among them, the Hall effect sensor has a simple structure and low cost, but its sensitivity and resolution are low, and it is difficult to provide sufficiently accurate data support in the weak magnetic field environment underground. Although the optical pump magnetometer has extremely high sensitivity, its working principle depends on a complex optical system. The equipment is very sensitive to environmental vibration and temperature changes, and it is difficult to adapt to the harsh conditions such as high temperature, high pressure and vibration underground. Therefore, high-precision fluxgate sensors have gradually become the mainstream choice for underground geomagnetic field measurement due to their high sensitivity, strong anti-interference ability and wide adaptability. The fluxgate sensor senses the external magnetic field through an induction coil and a high-permeability magnetic core. Its core technology lies in the highly sensitive magnetization characteristics of the magnetic core and the high-resolution perception of weak magnetic fields. Some methods for measuring the geomagnetic field using fluxgate sensors have been proposed in existing patents and public documents. For example, in the disclosed technology, a fluxgate sensor arranged in three axes captures the three-dimensional components of the underground magnetic field, and the well inclination and azimuth are calculated in combination with a reference magnetic field model. This method can theoretically meet the basic measurement requirements of the underground environment, but its application effect depends on the following key factors: the sensitivity and stability of the sensor, the calculation accuracy of the magnetic field vector, the ability to suppress environmental interference, and the dynamic response performance of data processing. Summary of the invention

[0004] The main purpose of the present invention is to provide a well inclination and geomagnetic field strength measurement system based on a high-precision fluxgate sensor, which significantly improves the accuracy, robustness and environmental adaptability of downhole magnetic field measurement. The present invention can accurately extract geomagnetic field components, suppress interference fields in complex downhole environments, and correct the effects of environmental factors such as temperature on sensor performance in real time, thereby achieving high-precision calculation of well inclination and azimuth.

[0005] The technical solution of the present invention is implemented as follows: a well deviation and geomagnetic field strength measurement system based on a high-precision fluxgate sensor, the system comprising: a fluxgate sensor group, a magnetic field data analysis part and a measurement result calculation part; The fluxgate sensor group includes three high-precision fluxgate sensors which are arranged in an underground environment and respectively measure the magnetic field components in the X-axis direction, the Y-axis direction and the Z-axis direction; The magnetic field data analysis part is used to calculate the reference output response of the high-precision fluxgate sensor according to the physical parameters of the high-precision fluxgate sensor, and correct the reference magnetic permeability of the high-precision fluxgate sensor in combination with the temperature and the reference output response at the current time to obtain the effective magnetic permeability; according to the effective magnetic permeability, calculate the corrected magnetic field component of the magnetic field component in each direction under the effective magnetic permeability, and then calculate the total magnetic field vector corresponding to the corrected magnetic field components in the three directions; construct a magnetic field gradient tensor based on the corrected magnetic field component in each direction, and separate the geomagnetic field vector from the total magnetic field vector according to the magnetic field gradient tensor; The measurement result calculation part is used to calculate the well inclination value and azimuth value according to the geomagnetic field vector; and the magnetic field intensity, well inclination value and azimuth value corresponding to the measured geomagnetic field vector are used as the final measurement result.

[0006] Furthermore, the physical parameters of the high-precision fluxgate sensor include: number of turns of the induction coil, effective cross-sectional area of ​​the magnetic core, reference magnetic permeability, magnetic relaxation time constant, magnetic core radius, magnetic domain size, excitation magnetic field strength, saturation magnetic field strength, excitation frequency and phase delay.

[0007] Furthermore, the magnetic field data analysis section calculates the reference output response of each high-precision fluxgate sensor according to the magnetic field component in each direction by the following formula: ; in, is the benchmark output response; is the operating time of the high-precision fluxgate sensor; is the number of turns of the induction coil; is the effective cross-sectional area of ​​the core; is the excitation magnetic field strength; is the saturation magnetic field strength; is the core radius; is the magnetic domain size; is the reference magnetic permeability; is the phase delay; is the excitation frequency; is the zero-order Bessel function; is the magnetic relaxation time constant.

[0008] Furthermore, the reference magnetic permeability of the high-precision fluxgate sensor is corrected by the following formula to obtain the effective magnetic permeability: ; in, is the effective magnetic permeability; The local energy barrier that needs to be overcome for magnetic domains to flip or rearrange; is the Boltzmann constant; is the reference temperature; is the temperature influence coefficient, ranging from 0.3 to 0.5.

[0009] Furthermore, the corrected magnetic field component of the magnetic field component in each direction under the effective magnetic permeability is calculated according to the following formula: ; in, is the corrected magnetic field component in the X-axis direction; is the corrected magnetic field component in the Y-axis direction; is the corrected magnetic field component in the Z-axis direction; is the installation azimuth angle of the high-precision fluxgate sensor corresponding to the X-axis direction; is the installation azimuth angle of the high-precision fluxgate sensor corresponding to the Y-axis direction; The installation azimuth angle of the high-precision fluxgate sensor corresponding to the Z-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the X-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the Y-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the Z-axis direction.

[0010] Furthermore, the magnetic field gradient tensor is constructed based on the corrected magnetic field component in each direction by the following formula: ; in, is the tensor product operation; is the gradient operator; is the total magnetic field vector; is the determinant operator; is the magnetic field gradient tensor.

[0011] Furthermore, the geomagnetic field vector is separated from the total magnetic field vector by the following formula: ; in, The spherical surface with a set value as the radius contains three high-precision fluxgate sensors. The radius range is arrive ; is the position vector on the spherical surface; The mean vector of the position vectors of three high-precision fluxgate sensors on the spherical surface; is the surface element normal vector; is the trace of the magnetic field gradient tensor.

[0012] Furthermore, the well inclination angle is calculated according to the geomagnetic field vector by the following formula: ; in, for The component in the Z-axis direction; for The component in the X-axis direction; for The component in the Y-axis direction; for The first element of for The second element of for The third element of It is Lang's ten thousand functions; is the well inclination value.

[0013] Furthermore, the azimuth value is calculated according to the geomagnetic field vector using the following formula: ; in, is the azimuth value.

[0014] The well inclination and geomagnetic field strength measurement system based on the high-precision fluxgate sensor of the present invention has the following beneficial effects: The present invention uses a high-precision fluxgate sensor as the core measurement equipment, which significantly improves the resolution and sensitivity of downhole magnetic field measurement. Compared with traditional Hall effect sensors and optical pump magnetometers, the fluxgate sensor of the present invention can capture tiny magnetic field changes in a weak magnetic field environment, and at the same time has strong anti-interference capabilities. By introducing a reference permeability correction model, the present invention dynamically compensates for the effects of temperature, time drift and material properties on the core response, ensuring that the sensor can still output stable and accurate magnetic field signals in harsh downhole environments such as high temperature and high pressure. This high-precision magnetic field measurement capability provides a reliable data basis for subsequent calculations of well inclination and azimuth.

[0015] In order to solve the problem of fluxgate sensor's magnetic permeability change under different temperature conditions, the present invention calculates the effective magnetic permeability through real-time correction of the reference magnetic permeability. The temperature correction coefficient and thermal excitation model (exponential decay term) are introduced into the formula, and the inductive capacity of the magnetic core is dynamically adjusted in combination with the output signal. This dynamic correction method effectively eliminates the negative impact of temperature on the magnetic permeability of the magnetic core, so that the sensor can still maintain high-precision measurement in the underground environment with significant temperature changes. This correction mechanism significantly improves the stability of magnetic field measurement and solves the problem of measurement error accumulation caused by temperature drift in the prior art.

[0016] The present invention comprehensively describes the rate of change of the magnetic field in three-dimensional space through the construction and utilization of the magnetic field gradient tensor. The gradient tensor not only reflects the local characteristics of the magnetic field, but also provides a basis for separating the interference field and the geomagnetic field. The formula combines the gradient operator and the tensor product operation to construct a second-order tensor that can accurately describe the spatial variation of the magnetic field, and suppresses the influence of high interference areas on the measurement results through the exponential weight term. This high-order description capability enables the present invention to separate the geomagnetic field components and the interference field in a complex downhole environment, significantly improving the accuracy of the calculation of the well inclination and azimuth.

[0017] The present invention proposes a multi-parameter coupling model, which constructs the calculation formula of the well inclination and azimuth through the component relationship of the geomagnetic field vector, the normalized correction of the gradient tensor and the dynamic response of the core material properties. The calculation formula of the well inclination combines the trace information of the geomagnetic field vector and the gradient tensor, suppresses the influence of environmental interference on the measurement accuracy, and uses the Langevin function to dynamically correct the nonlinear magnetization state of the magnetic core to ensure the reliability and accuracy of the calculation results. The calculation of the azimuth is based on the ratio of the planar components of the geomagnetic field vector. The interference field is effectively suppressed by the exponential weight term, avoiding the negative impact of the high gradient area on the azimuth calculation. This systematic calculation model significantly improves the spatial positioning accuracy in complex underground environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the system structure of a well inclination and geomagnetic field strength measurement system based on a high-precision fluxgate sensor provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In the following description, specific details such as specific system structures, interfaces, and technologies are provided for illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the embodiments of the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the embodiments of the present invention.

[0020] Example 1, reference Figure 1 : A well inclination and geomagnetic field intensity measurement system based on a high-precision fluxgate sensor, the system comprising: a fluxgate sensor group, a magnetic field data analysis part and a measurement result calculation part; The fluxgate sensor group includes three high-precision fluxgate sensors which are arranged in an underground environment and respectively measure the magnetic field components in the X-axis direction, the Y-axis direction and the Z-axis direction; The magnetic field data analysis part is used to calculate the reference output response of the high-precision fluxgate sensor according to the physical parameters of the high-precision fluxgate sensor, and correct the reference magnetic permeability of the high-precision fluxgate sensor in combination with the temperature and the reference output response at the current time to obtain the effective magnetic permeability; according to the effective magnetic permeability, calculate the corrected magnetic field component of the magnetic field component in each direction under the effective magnetic permeability, and then calculate the total magnetic field vector corresponding to the corrected magnetic field components in the three directions; construct a magnetic field gradient tensor based on the corrected magnetic field component in each direction, and separate the geomagnetic field vector from the total magnetic field vector according to the magnetic field gradient tensor; The measurement result calculation part is used to calculate the well inclination value and azimuth value according to the geomagnetic field vector; and the magnetic field intensity, well inclination value and azimuth value corresponding to the measured geomagnetic field vector are used as the final measurement result.

[0021] Specifically, the fluxgate sensor wraps a high magnetic permeability magnetic core through a coil. When the external magnetic field acts on the magnetic core, the magnetic field is concentrated and enhanced through the magnetic core. Under the action of the external AC excitation current, the magnetization intensity in the magnetic core changes continuously with the excitation frequency. When the external magnetic field intensity changes, the magnetization saturation point and the flux change rate of the magnetic core change accordingly, and this change is directly reflected in the signal output by the sensor. By demodulating the output signal, the specific value of the external magnetic field can be obtained. In the present invention, the fluxgate sensor group is designed as an orthogonal arrangement system composed of three high-precision fluxgate sensors, which correspond to the measurement of magnetic field components in the X-axis, Y-axis and Z-axis directions in the downhole environment. This design makes full use of the three-axis measurement capability of the fluxgate sensor, and realizes the all-round perception of the spatial magnetic field by arranging sensors in different directions, so as to accurately capture the vector distribution of the downhole magnetic field. In particular, in the case of complex and changeable downhole environment and significant local magnetic field interference, the high sensitivity and low noise characteristics of the fluxgate sensor ensure the stability and accuracy of the measurement results. In addition, in order to further improve the accuracy of the sensor, the system of the present invention also introduces temperature compensation and magnetic permeability correction mechanisms. Since the high temperature and magnetic field interference of the underground environment may cause the performance fluctuations of the magnetic core, the sensor group dynamically adjusts the effective magnetic permeability of the sensor by collecting environmental temperature data in real time and combining the reference output response of the sensor. This process not only eliminates the influence of temperature on the sensor output signal, but also significantly improves the measurement reliability of the sensor in a high temperature environment.

[0022] In addition, another important role of the fluxgate sensor group in the present invention is to provide basic data for the subsequent separation of geomagnetic field components and calculation of well inclination angle. Through real-time measurement of magnetic field components in three directions, the system can quickly construct a magnetic field gradient tensor and separate the geomagnetic field vector based on this. The accuracy of this separation process directly depends on the accurate capture of the spatial magnetic field by the sensor group. Therefore, on the basis of the fluxgate sensor, the present invention further optimizes the data processing algorithm to convert the original output data of the sensor into the corrected magnetic field components. Specifically, this data processing combines the physical parameters of the sensor and the actual environmental factors, eliminates the influence of system errors and environmental noise, and ensures the accuracy of the three-axis magnetic field components. These corrected data not only reflect the true intensity of the underground geomagnetic field, but also lay a data foundation for the accurate calculation of well inclination angle and azimuth. The superior performance of the fluxgate sensor group is also reflected in its sensitive perception of weak magnetic field changes. Compared with traditional Hall sensors or other types of magnetic field measurement equipment, fluxgate sensors have a higher signal-to-noise ratio at low magnetic field strengths, and are particularly suitable for accurately capturing changes in the geomagnetic field in complex underground environments. For example, under the interference of underground metal structures or electrical equipment, the local magnetic field may change nonlinearly. Traditional sensors are prone to measurement deviations in these environments, while fluxgate sensors can effectively suppress interference signals and accurately capture slight changes in the geomagnetic field through their special magnetization characteristics and high dynamic range.

[0023] After collecting the magnetic field signal downhole, the fluxgate sensor first outputs the uncorrected raw electrical signal, and the accuracy of these signals is affected by multiple factors, including fluctuations in sensor sensitivity, changes in ambient temperature, and interference from the local magnetic field downhole. In order to ensure the reliability of the final calculation results, the magnetic field data analysis part starts from the physical characteristics of the sensor and uses its preset benchmark parameters, such as benchmark sensitivity and benchmark magnetic permeability, to calculate the benchmark response value of the sensor. The benchmark response value is the output response of the sensor to the external magnetic field under ideal conditions, which can provide a reference for the subsequent correction process. In the complex environment downhole, temperature changes have a significant impact on the performance of the fluxgate sensor. The increase in temperature will cause a slight change in the magnetization characteristics of the sensor core material, resulting in a deviation in the output signal. To solve this problem, the magnetic field data analysis part dynamically corrects the magnetic permeability by collecting the temperature data of the downhole environment in real time and combining it with the benchmark response value of the sensor. The temperature correction process is based on the temperature characteristic model of the sensor, and the benchmark magnetic permeability is adjusted through an algorithm to obtain the corrected effective magnetic permeability. This correction process greatly improves the performance stability of the sensor in a high temperature environment, so that the measurement results are not affected by ambient temperature fluctuations.

[0024] After the effective permeability correction is completed, the magnetic field data analysis part further calculates the corrected magnetic field components in each direction. The corrected magnetic field components are directly derived from the output electrical signal of the fluxgate sensor. After the sensitivity and permeability are normalized, the component value reflecting the true magnetic field strength is obtained. By vector synthesis of the corrected magnetic field components in the three directions of X, Y, and Z, the magnetic field data analysis part calculates the total magnetic field vector of the downhole magnetic field. This total magnetic field vector not only contains the information of the geomagnetic field, but also superimposes the interference magnetic field in the local environment of the downhole. Therefore, it is impossible to directly obtain accurate information about the geomagnetic field by relying solely on the total magnetic field vector. In order to separate the geomagnetic field vector, the magnetic field data analysis part constructs a magnetic field gradient tensor using the spatial distribution characteristics of the total magnetic field vector. The magnetic field gradient tensor is a mathematical tool that describes the spatial rate of change of the magnetic field. By calculating the changes of the magnetic field components in three-dimensional space, the local distribution characteristics of the magnetic field can be clarified. Using this gradient tensor, the system can accurately separate the interference components in the total magnetic field vector and extract the pure geomagnetic field vector. In the downhole environment, due to the presence of metal structures, electrical equipment, etc., the local magnetic field interference usually has a large gradient characteristic, while the geomagnetic field exhibits a smoother distribution. Therefore, the gradient tensor can not only help identify interference, but also enhance the accuracy of geomagnetic field separation. Another important function of the magnetic field data analysis part is to compare and analyze the geomagnetic field vector with the total magnetic field vector to verify the accuracy of the separation results. By performing multiple iterative calculations on the separated geomagnetic field components, the magnetic field data analysis part can eliminate the influence of environmental interference to the greatest extent, thereby providing high-precision input data for subsequent calculations of well inclination and azimuth. In addition, the design of this part also fully considers the real-time changes in the downhole environment. By updating the calculation model of the gradient tensor and geomagnetic field components in real time, the system can quickly adapt to different environmental conditions and ensure the dynamic accuracy of the measurement results.

[0025] The measurement result calculation part uses the geomagnetic field vector separated by the magnetic field data analysis part. This vector is the real geomagnetic field component obtained after interference separation and environmental correction, which can accurately reflect the state of the earth's magnetic field in the downhole environment. The direction and size of the geomagnetic field vector contain rich spatial information and are the basic data for downhole attitude solution. The calculation of the well inclination angle is based on the relationship between the geomagnetic field vector and the direction of the earth's gravity. The distribution characteristics of the geomagnetic field in space make it have obvious directionality, especially in the downhole, the angle between the geomagnetic field vector and the direction of the earth's center directly reflects the size of the well inclination angle. Therefore, by analyzing the relationship between the geomagnetic field vector and the downhole coordinate system, the well inclination angle can be accurately determined.

[0026] To achieve this goal, the measurement result calculation part first needs to determine the projection of the geomagnetic field vector in the three-dimensional spatial coordinate system of the well. Since the fluxgate sensor group measures the corrected magnetic field components in three orthogonal directions, the geomagnetic field vector can be expressed as a three-dimensional vector, and its magnitude and direction are calculated by vector synthesis. On this basis, the measurement result calculation part uses geometric methods to solve the angle between the geomagnetic field vector and the reference axis of the well. Specifically, the well inclination angle is the angle between the geomagnetic field vector and the Z axis (usually parallel to the vertical direction of the well). This process requires the use of the dot product relationship of the vectors, and the magnitude of the well inclination angle is finally obtained by inversely calculating the cosine value of the angle between the vectors. On the other hand, the calculation of the azimuth angle depends on the projection of the geomagnetic field vector on the horizontal plane. The components of the geomagnetic field vector on the XY plane reflect its distribution characteristics in the horizontal direction, and the direction of the geomagnetic field vector on the horizontal plane can be determined by the ratio of these components. Specifically, the azimuth angle is the angle between the projection of the geomagnetic field vector on the horizontal plane and the reference direction (such as the north direction). The measurement result calculation part calculates the azimuth value accurately by performing an inverse tangent operation on the horizontal component of the geomagnetic field vector and combining it with the sensor's directional calibration information. This calculation process takes into account the coordinate system offset and non-ideal calibration factors that may exist in the underground environment, and compensates for the deviation through an algorithm to ensure the accuracy of the azimuth calculation. In addition, the measurement result calculation part is also responsible for the calculation of the geomagnetic field strength. The geomagnetic field strength is the modulus of the geomagnetic field vector and reflects the actual size of the earth's magnetic field in the underground space. By summing the squares of the three directional components of the geomagnetic field vector and taking the square root, the system can quickly obtain the geomagnetic field strength value. This calculation result is of great significance for underground geological exploration and environmental monitoring, because changes in the geomagnetic field strength may be closely related to underground structures and mineral distribution.

[0027] Embodiment 2: The physical parameters of the high-precision fluxgate sensor include: number of turns of the induction coil, effective cross-sectional area of ​​the magnetic core, reference magnetic permeability, magnetic relaxation time constant, magnetic core radius, magnetic domain size, excitation magnetic field strength, saturation magnetic field strength, excitation frequency and phase delay.

[0028] Specifically, the number of turns of the induction coil and the role of the magnetic core complement each other. The increase in the number of turns of the coil can enhance the intensity of the induction signal, while the effective cross-sectional area of ​​the magnetic core determines the distribution and transmission efficiency of the magnetic flux in the sensor. A small cross-sectional area of ​​the magnetic core may lead to excessive concentration of the magnetic field, causing local saturation of the magnetic core, and thus affecting the linear output of the signal, while a large cross-sectional area will reduce the sensitivity to changes in weak magnetic fields, so it is necessary to choose reasonably to adapt to the complex magnetic field distribution downhole. The reference magnetic permeability is a core parameter that describes the ability of the magnetic core material to respond to the magnetic field, and its size directly affects the inductive sensitivity of the sensor in the external magnetic field. Since the magnetic permeability changes with temperature and time, the reference magnetic permeability is dynamically corrected in the present invention to ensure the stability of the measured data in the downhole environment. At the same time, the magnetic relaxation time constant, as the response time of the magnetic core to changes in the external magnetic field, determines the dynamic performance of the sensor. A magnetic relaxation time that is too short will result in poor response to low-frequency magnetic fields, while a time that is too long may delay the perception of rapidly changing magnetic fields. Therefore, in the practical application of the present invention, its setting needs to match the dynamic characteristics of the downhole magnetic field.

[0029] The core radius is closely related to the magnetic domain size, and together they determine the core's ability to resolve magnetic field signals. A smaller core radius can improve spatial resolution, but may lead to increased interference between magnetic domains, while the magnetic domain size affects the core's saturation characteristics and sensitivity to weak external magnetic fields. In order to meet the requirements of the downhole environment for high-precision magnetic field measurement, the core material used in the present invention has a moderate magnetic domain size, thereby achieving a balance between sensitivity and anti-interference ability. The excitation magnetic field strength and the saturation magnetic field strength are important parameters that affect the sensor's operating range. The excitation magnetic field strength needs to be large enough to drive the core into a high-sensitivity working state while avoiding nonlinear effects caused by over-excitation. The saturation magnetic field strength limits the maximum measurement range of the sensor. If the magnetic field strength in the environment approaches or exceeds the saturation strength of the magnetic core, the output of the sensor will be distorted. In the present invention, appropriate excitation magnetic field and saturation magnetic field parameters are selected according to the actual distribution characteristics of the downhole magnetic field strength, so as to ensure that the sensor can capture weak geomagnetic field signals and handle stronger environmental interference magnetic fields. Finally, the excitation frequency and phase delay are important representations of the dynamic performance of the fluxgate sensor. The excitation frequency determines the period of magnetization and demagnetization of the magnetic core. Its selection needs to take into account both the shielding effect of low-frequency noise and the response speed to the target magnetic field signal. The phase delay reflects the hysteresis characteristics of signal processing. Excessive phase delay will reduce the synchronization between the measurement results and the actual magnetic field changes. In the present invention, the setting of these parameters is directly related to whether the sensor can efficiently capture the complex magnetic field changes in the downhole environment, providing a reliable basis for subsequent data processing and calculation.

[0030] Embodiment 3: The magnetic field data analysis part calculates the reference output response of each high-precision fluxgate sensor according to the magnetic field component in each direction by the following formula: ; in, is the benchmark output response; is the operating time of the high-precision fluxgate sensor; is the number of turns of the induction coil; is the effective cross-sectional area of ​​the core; is the excitation magnetic field strength; is the saturation magnetic field strength; is the core radius; is the magnetic domain size; is the reference magnetic permeability; is the phase delay; is the excitation frequency; is the zero-order Bessel function; is the magnetic relaxation time constant.

[0031] Specifically, in the formula, the output response Directly related to the number of turns of the induction coil and the effective cross-sectional area of ​​the core The two together determine the amount of flux change that the magnetic core can sense per unit time. The more turns the induction coil has, the stronger the induced electromotive force caused by the flux change; and the effective cross-sectional area of ​​the magnetic core affects the uniformity of the magnetic field distribution and the efficiency of the magnetic flux conduction. In the complex magnetic field environment underground, this proportional relationship ensures that the sensor can capture sufficient magnetic field signal strength, which is especially important for the accurate measurement of weak geomagnetic field components. The formula is further expressed by the reference magnetic permeability It reflects the responsiveness of the magnetic core material to the magnetic field. The higher the magnetic permeability, the more sensitive the magnetic core is to the external magnetic field, thereby improving the sensor's sensing ability. However, the magnetic permeability is not a constant value, but is dynamically adjusted with changes in temperature and magnetic field strength. Therefore, in actual calculations, it needs to be corrected by the reference output and temperature parameters. The present invention particularly emphasizes the real-time correction of this parameter to adapt to the impact of underground temperature changes on the sensor output, thereby ensuring the stability of the output signal.

[0032] In the formula The excitation magnetic field is described in part This nonlinear function characterizes the driving effect of the magnetic core when the magnetic field strength is close to saturation. When the excitation magnetic field approaches the saturation magnetic field, the magnetization state of the core tends to be stable and the output signal gradually saturates. This nonlinear characteristic is very important in practical applications because it avoids infinite amplification of the output signal and enables the sensor to respond accurately to weak magnetic field changes. reflects the dynamic characteristics of the magnetic core, where is the magnetic relaxation time constant. This term describes the process of the core recovering from the excited magnetization state to the equilibrium state, and determines the sensor's response speed to dynamic magnetic field changes. In an underground environment, the magnetic field may change rapidly over time, and the introduction of the time decay term enables the sensor to effectively distinguish between rapidly changing magnetic field signals and static magnetic field components, providing more realistic input data for subsequent magnetic field component correction and total magnetic field vector calculation. Zero-order Bessel function The spatial distribution characteristics of the magnetic core are introduced, where is the core radius, is the magnetic domain size. This part reflects the distribution pattern of the magnetic field inside the core and is a mathematical modeling of the microstructure inside the core. The size of the core radius affects the sensor's ability to respond to spatial resolution, while the magnetic domain size determines the sensor's sensitivity to magnetic fields of different frequencies. By introducing the Bessel function, the formula fully considers the non-uniformity inside the core, making the sensor's measurement of the magnetic field in three-dimensional space more accurate. Finally, the sine term Characterizes the periodic characteristics of the excitation signal. Among them, is the excitation frequency, is the phase delay. The periodic change of the excitation signal can effectively drive the magnetic core to complete the magnetization and demagnetization process, while the phase delay describes the time lag characteristics in signal processing. This part ensures that the sensor can synchronously perceive the dynamic magnetic field signal and provides support for the real-time measurement of the magnetic field changes in the well.

[0033] Embodiment 4: The reference magnetic permeability of the high-precision fluxgate sensor is corrected by the following formula to obtain the effective magnetic permeability: ; in, is the effective magnetic permeability; The local energy barrier that needs to be overcome for magnetic domains to flip or rearrange; is the Boltzmann constant; is the reference temperature; is the temperature influence coefficient, ranging from 0.3 to 0.5.

[0034] Specifically, the core of the formula is the base magnetic permeability Magnetic permeability is a key physical parameter of the core material, which describes the material's ability to respond to the magnetic field. However, in practical applications, the magnetic permeability is affected by temperature, the microscopic properties of the core material, and changes in the external magnetic field. Therefore, a single reference magnetic permeability cannot accurately reflect the performance of the fluxgate sensor in a dynamic environment. This formula introduces multiple correction terms to quantify these effects and incorporate them into the calculation to obtain an effective magnetic permeability that is closer to reality. First, the temperature correction term in the formula Describes the linear adjustment relationship between magnetic permeability and temperature. Among them, is the temperature influence coefficient, which ranges from 0.3 to 0.5 and reflects the sensitivity of different core materials to temperature. Deviation from base temperature The magnetic permeability changes linearly with this term. An increase in temperature usually results in a decrease in magnetic permeability because the arrangement of magnetic domains inside the core material is disturbed by thermal motion, which reduces the material's ability to respond to external magnetic fields. This formula quantifies this change through a temperature correction term, ensuring that the sensor can maintain high-precision measurement performance in a downhole environment with fluctuating temperatures.

[0035] Secondly, the index correction term Considers the local energy barrier that needs to be overcome when magnetic domains flip or rearrange . This energy barrier is determined by the interaction between the internal structure of the core material and the magnetic domains, which affects the dynamic response ability of the core under the action of an external magnetic field. The formula describes the thermal excitation mechanism of this process through the Boltzmann factor. When the ambient temperature rises, the thermal motion inside the core is enhanced, and the probability of magnetic domain reversal and rearrangement increases, thereby affecting the magnitude of the magnetic permeability. This correction term accurately captures the dynamic effect of temperature on the microscopic magnetic structure of the core material through the mathematical description of the thermal excitation mechanism. Finally, the output response introduced in the formula is the actual output signal of the high-precision fluxgate sensor. Incorporating the calculation of effective magnetic permeability, the formula directly links the sensor response under the external magnetic field with the magnetic permeability correction process. This design combines static characteristics with dynamic response, ensuring that the corrected magnetic permeability can more accurately reflect the actual performance of the sensor in complex magnetic fields. Overall, this formula comprehensively describes the dynamic change process of effective magnetic permeability through the synergistic effect of baseline magnetic permeability, temperature correction term, exponential correction term and output response. Compared with traditional methods, this formula not only takes into account the influence of temperature and energy distribution, but also incorporates the actual output signal of the sensor into the correction model, so that the calculation results are closer to the actual situation in the complex downhole environment. This correction mechanism is of great significance in the present invention, because the downhole environmental temperature changes significantly and the magnetic field distribution is complex. Through the accurate calculation of the effective magnetic permeability, the accuracy of subsequent magnetic field component measurement and well inclination angle calculation can be significantly improved.

[0036] Embodiment 5: According to the effective magnetic permeability, the corrected magnetic field component of the magnetic field component in each direction under the effective magnetic permeability is calculated by the following formula: ; in, is the corrected magnetic field component in the X-axis direction; is the corrected magnetic field component in the Y-axis direction; is the corrected magnetic field component in the Z-axis direction; is the installation azimuth angle of the high-precision fluxgate sensor corresponding to the X-axis direction; is the installation azimuth angle of the high-precision fluxgate sensor corresponding to the Y-axis direction; The installation azimuth angle of the high-precision fluxgate sensor corresponding to the Z-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the X-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the Y-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the Z-axis direction.

[0037] Specifically, the core idea of ​​the formula is to convert the original magnetic field components The sensor is projected into the standard rectangular coordinate system according to its installation angle and dynamically adjusted in combination with the effective magnetic permeability to calculate the corrected magnetic field component. First, the effective permeability in the denominator is It plays a role in unified correction. Since magnetic permeability is affected by factors such as temperature and magnetic domain structure, which directly affect the sensitivity and measurement accuracy of the sensor, it must be corrected by the above formula before being introduced into the calculation of the magnetic field component. Through this processing step, the formula effectively reduces the interference of environmental variables on magnetic field measurement, making the final corrected magnetic field component more in line with the actual situation downhole. Azimuth in the matrix and inclination This directly affects the directional correction of the magnetic field component. The actual installation of the fluxgate sensor is not strictly aligned according to the rectangular coordinate system, but there may be a certain angle deviation due to the requirements of the complex underground environment. The azimuth and inclination describe the angle between the installation direction of the sensor and the spatial coordinate axis. Through matrix multiplication, the projection of the original magnetic field component in different directions is remapped to the standard rectangular coordinate system.

[0038] The three columns in the matrix represent the spatial distribution patterns of the magnetic field components in three directions. The second and third columns are mainly composed of and , respectively describe the changes in the components of the magnetic field in the plane. Through the combination of these trigonometric functions, the formula can fully capture the distribution characteristics of the magnetic field in three-dimensional space, thereby ensuring that the corrected magnetic field components are not only accurate but also retain the integrity of the magnetic field in space. Corrected magnetic field components It is an important input data for calculating the total magnetic field vector. By eliminating the influence of factors such as sensor installation angle and permeability change, the corrected magnetic field component truly reflects the actual strength and direction of the external magnetic field. This processing is crucial for the accurate calculation of well inclination and geomagnetic field vector. Especially in the underground environment, the magnetic field is not only directly affected by the geomagnetic field, but may also be superimposed with interference signals caused by surrounding well walls, equipment, etc. Through this correction formula, the influence of these interferences can be greatly reduced, so that the error of the sensor measurement results can be minimized.

[0039] Embodiment 6: The magnetic field gradient tensor is constructed based on the corrected magnetic field component in each direction by the following formula: ; in, is the tensor product operation; is the gradient operator; is the total magnetic field vector; is the determinant operator; is the magnetic field gradient tensor.

[0040] Specifically, the core of the formula is to construct the magnetic field gradient tensor by applying the gradient operator to the modified magnetic field component. Describes the rate of change of a field in space, which acts on the vector field After that, a second-order tensor is generated, which reflects the change of each directional magnetic field component relative to the spatial coordinate axis. Specifically, this change is described by the components of the gradient tensor, for example, the component express Directional magnetic field component relative to The rate of change of the coordinates, while the components It means Directional magnetic field component in This description is of great physical significance because it can reveal the local variation trend of the magnetic field in three-dimensional space, thus providing accurate data support for the subsequent separation of geomagnetic field components and location of interference sources. It is a key operation in the construction of the gradient tensor, which expands the interaction between the gradient operator and the magnetic field vector into the form of a two-dimensional matrix. This process not only captures the independent change characteristics of each magnetic field component, but also reflects the mutual correlation between them. For example, when a magnetic field component changes significantly in a certain direction, this change may induce additional effects in another direction, and the tensor product is used to characterize this correlation. The magnetic field gradient tensor therefore not only provides local information on magnetic field changes, but also reflects the overall characteristics of the magnetic field distribution through the tensor structure. This high-order description capability is particularly important for magnetic field measurements in complex downhole environments, because in downhole environments, the magnetic field is usually affected by multiple factors, including the geomagnetic field, equipment interference, and geological structure. Simple scalar or vector descriptions can no longer meet accuracy requirements.

[0041] The exponential correction term in the formula It is a dynamic adjustment of the calculation results of the magnetic field gradient tensor. It improves the reliability of the gradient tensor by eliminating the influence of non-physical divergence. According to Maxwell's equations, in the absence of an external magnetic field, the divergence of the magnetic field should be zero, that is, . However, due to the complexity of the downhole environment, the sensor may be interfered by a variety of factors, including temperature fluctuations, equipment noise, and measurement errors of magnetic field components, which can cause the divergence value to deviate from the ideal state, thereby affecting the accuracy of the magnetic field gradient tensor. The introduction of the exponential correction term suppresses the interference of the interference signal on the tensor calculation result by weakening the influence of the high divergence area. For example, when the divergence value is small, the value of the exponential term is close to 1, and the influence on the tensor is small; when the divergence value is large, the exponential term decays rapidly, thereby significantly reducing the weight of the interference signal in the gradient tensor. This dynamic adjustment mechanism enhances the anti-interference ability of the system, making the magnetic field gradient tensor measured in a complex environment closer to the real distribution. The practical application of the magnetic field gradient tensor lies not only in its description of the magnetic field distribution, but also in its important role in the separation of the geomagnetic field components. In the measurement system of the present invention, the extraction of the geomagnetic field is one of the key steps, and the gradient tensor provides the necessary basic data. By decomposing the eigenvalues ​​of the gradient tensor, the main trend of the magnetic field distribution can be analyzed and the influence of environmental interference can be eliminated. For example, when the gradient characteristics in a certain direction deviate significantly from other directions, this may indicate that the direction is significantly affected by the interference source, and this interference characteristic can be clearly identified and quantified through the high-order characteristics of the gradient tensor. In addition, by analyzing the symmetry of the gradient tensor and the change pattern of each component, the distribution law of the geomagnetic field in space can be further understood, and the pure geomagnetic field vector can be extracted accordingly. The construction and correction of the gradient tensor also provide important support for the high-precision calculation of the well inclination and azimuth. The calculation of the well inclination requires accurate acquisition of the spatial distribution characteristics of the magnetic field, which is closely related to the magnetic field gradient. By analyzing the gradient tensor, the direction of change and the intensity distribution of the magnetic field in space can be accurately determined, thereby improving the accuracy of the calculation of the well inclination. Similarly, the calculation of the azimuth also depends on the directional information of the magnetic field distribution. The gradient tensor provides the necessary vector basis, making the calculation results more stable and reliable. In addition, in underground geological exploration, the gradient tensor can also be used to analyze the magnetic field characteristics of the geological structure, and identify potential mineral resources or geological anomalies through a detailed description of the magnetic field distribution, which provides more possibilities for the practical application of the present invention.

[0042] Embodiment 7: Separate the geomagnetic field vector from the total magnetic field vector using the following formula: ; in, The spherical surface with a set value as the radius contains three high-precision fluxgate sensors. The radius range is arrive ; is the position vector on the spherical surface; The mean vector of the position vectors of three high-precision fluxgate sensors on the spherical surface; is the surface element normal vector; is the trace of the magnetic field gradient tensor.

[0043] Specifically, the first part of the formula It is the core of geomagnetic field vector extraction. Here, Represents the total magnetic field vector, which includes the superposition of the geomagnetic field and the underground environmental interference field. In order to separate the geomagnetic field from it, the formula adopts a method based on spherical surface integral, focusing on analyzing the local variation characteristics of the total magnetic field in space. is a sphere centered on the sensor, and its radius is arrive ,in is the radius of the sensor core. This spherical surface selection can effectively cover the spatial range around the sensor, ensuring that all possible interference sources are taken into account during the integration process. For each facet on the spherical surface, the magnetic field gradient tensor Through its normal vector The dot product of represents the changing trend of the magnetic field in this direction. provides a scalar measure that describes the component of the gradient field in the direction of the normal vector. This measure is combined with the spatial position vector difference The reciprocal of further emphasizes the importance of spatial position to the contribution of the interference field. In other words, the farther away the point is from the sensor, the smaller its influence on the integral result, thus mathematically realizing a distance-weighted interference suppression mechanism.

[0044] The exponential correction term of the formula Then, the trace of the magnetic field gradient tensor is Dynamic adjustment is introduced. This term suppresses the influence of non-physical changes in the gradient field by exponentially decaying the square of the trace. The trace of the magnetic field gradient tensor is essentially the sum of the main diagonal elements of the gradient tensor, reflecting the overall change intensity of the magnetic field in all directions. According to Maxwell's equations, in the absence of an external magnetic field, the ideal magnetic field should satisfy the conditions of no divergence and no curl, that is, . However, in the actual downhole environment, local interference magnetic fields and measurement errors may cause the trace value to deviate from the zero point. This deviation will significantly affect the accuracy of geomagnetic field extraction. Through the exponential correction term, the formula effectively suppresses the adverse effects of high trace value areas on the integration results, thereby ensuring that the final separated geomagnetic field vector is closer to the true value. The integral operation in the formula not only captures the local changes in the magnetic field, but also realizes the spatial screening of interference sources through the geometric characteristics of the spherical surface. Surface element normal vector The introduction of provides directionality to the integration process, so that the integration result can reflect the distribution characteristics of the magnetic field in different directions. This feature is crucial for eliminating local interference fields from the total magnetic field. For example, if the gradient field in a certain direction changes abnormally, this may indicate that there is significant local interference in that direction, and the integration result can suppress the contribution of this direction by weight adjustment, thereby improving the accuracy of geomagnetic field extraction. In addition, the position vector in the formula Represents the average position of the sensor within the spherical surface. The introduction of this average further balances the unevenness of the spatial position, ensuring that the overall result will not be deviated due to abnormal values ​​at individual positions during the integration process. Combined with the distance factor , the integration result can more accurately reflect the global characteristics of the magnetic field distribution on the spherical surface.

[0045] Embodiment 8: The well inclination angle value is calculated according to the geomagnetic field vector by the following formula: ; in, for The component in the Z-axis direction; for The component in the X-axis direction; for The component in the Y-axis direction; for The first element of for The second element of for The third element of It is Lang's ten thousand functions; is the well inclination value.

[0046] Specifically, the main variables in the formula are the components of the geomagnetic field vector in different directions: , and These components represent the geomagnetic field in , and The distribution intensity in the direction constitutes the basic information of the geomagnetic field vector. The calculation is based on the spatial relationship of these components, through the inverse cosine function Represents the geomagnetic field vector and The angle between the axes. Specifically, the square root operation of the denominator The modulus of the geomagnetic field vector is calculated, and the numerator Then take the geomagnetic field vector at The ratio of the two reflects the direction of the Earth's magnetic field. The component proportion in the direction is converted into an angle value directly related to the well inclination through the arc cosine function. In order to further correct the errors caused by environmental interference and magnetic field gradient, the formula introduces an exponential weight term . Magnetic field gradient tensor Length of mold describes the overall variation of the magnetic field in space, while , and are the main components of the gradient tensor, representing the gradient characteristics of the magnetic field in different directions. Through this normalization process, the exponential weight term can effectively weaken the influence of abnormal gradients on the calculation of well inclination. For example, when the gradient in a certain direction is significantly higher than that in other directions, this may reflect the existence of a local interference source, and the weight term can dynamically reduce the weight of this direction on the calculation of well inclination, thereby improving the robustness of the result.

[0047] Langevin function The influence of the nonlinear characteristics of the core material on the calculation of the well inclination angle is introduced. The Langevin function is a classic function that describes the magnetization state of the core under the action of an external magnetic field. Its input parameters are Combined with effective permeability , saturation magnetic field strength , Boltzmann constant and ambient temperature This parameter reflects the degree of magnetization of the core under the current temperature and magnetic field conditions. Since the magnetization state of the core directly affects the sensitivity of the fluxgate sensor to the geomagnetic field, the introduction of the Langevin function can theoretically quantify the core characteristics. Specifically, as the temperature As the temperature increases, the magnetization of the core will weaken, resulting in a decrease in the sensitivity of the sensor. The Langevin function incorporates this influence into the well inclination calculation process through a nonlinear response, ensuring that accurate measurement results can still be obtained in the downhole environment with significant temperature changes. The structure of the formula embodies the characteristics of multi-level correction and multi-parameter fusion. From the basic relationship between the geomagnetic field vector components to the normalized weights of the gradient tensor, and then to the nonlinear description of the core material properties, each part is mathematically modeled and quantitatively corrected for different environmental variables and physical phenomena. This design is of great significance in the complex downhole environment. Because the downhole magnetic field distribution is affected by many factors, including changes in the components of the geomagnetic field, the superposition of local interference fields, and the influence of temperature on sensor characteristics, simple geometric relationships cannot meet the needs of high-precision well inclination calculation. Through this formula, the system can comprehensively consider the action mechanism of various variables and realize the calculation of well inclination with higher accuracy and robustness. Well inclination value The final calculation result is not only used to directly describe the inclination state of the wellbore, but also provides a key reference for the measurement of geomagnetic field strength and azimuth calculation of the entire measurement system. Accurate well inclination measurement is particularly important for practical applications such as oil and gas exploration and mine measurement, because the well inclination in these scenarios directly affects the positioning and calibration of the measuring equipment. In addition, the introduction of exponential weight terms and Langevin functions in the formula also reflects the technical innovation of the present invention. Through the combination of mathematical and physical models, it successfully copes with various interferences in the complex underground environment, providing a solid theoretical and practical foundation for the wide application of the system of the present invention.

[0048] Embodiment 9: Calculate the azimuth value according to the geomagnetic field vector using the following formula: ; in, is the azimuth value.

[0049] Specifically, the core part of the formula It expresses the direction relationship of the geomagnetic field vector in the horizontal plane. Here, The Earth's magnetic field Direction and The ratio of the components in the direction describes the projection direction of the geomagnetic field vector on the horizontal plane. , this ratio is converted into the geomagnetic field vector and The angle between the axes determines the azimuth This part is the geometric basis for azimuth calculation and can directly reflect the planar distribution characteristics of the geomagnetic field. However, the measurement results of the geomagnetic field vector in the underground environment are often affected by local interference fields and equipment errors. Simply relying on geometric ratio calculations may not meet high-precision requirements. Therefore, the formula further introduces an exponential weight term , to dynamically correct the interference effect of the gradient tensor. The amount , and Describes the rate of change of the magnetic field in different directions, the normalized component ratio It represents the proportion of horizontal gradient in the total gradient. and ) is significantly higher than the vertical gradient ( ), it may mean that the interference field has a greater impact on the horizontal plane, and the exponential term reduces the influence of the interference field on the azimuth calculation result by reducing the weight of this situation, thereby improving the robustness of the calculation.

[0050] Langevin function The nonlinear characteristics of the core material are introduced to correct the azimuth angle calculation. The Langevin function is a classic model that describes the magnetization state of the core. Its input parameters are Combined with the effective permeability , saturation magnetic field strength , Ambient temperature and the Boltzmann constant This parameter reflects the degree of magnetization of the core under the current temperature and magnetic field conditions. Since the magnetization state of the core directly affects the sensitivity of the fluxgate sensor to the geomagnetic field component, the introduction of the Langevin function can quantitatively correct the temperature change and the core characteristics, thereby ensuring that the azimuth calculation result is more accurate. In the practical application of the present invention, the azimuth value The accuracy is crucial to the overall performance of the system. The geomagnetic field in the downhole environment is not only affected by the geological structure and the distribution of the geomagnetic field, but may also be disturbed by a variety of complex factors such as equipment operation and electromagnetic interference. Therefore, simple geometric ratio calculations may fail due to these interferences, and the formula in Example 9 significantly enhances the anti-interference ability of the system through multiple correction means. For example, when the ambient temperature increases and the magnetization performance of the magnetic core decreases, the Langevin function will dynamically adjust the sensitivity of the azimuth calculation; when the local interference field causes the horizontal gradient to be abnormal, the exponential weight term will significantly weaken its impact on the result. Through these multi-level corrections, the formula can still maintain high-precision measurement of the azimuth in a complex environment. In addition, the design of the formula also fully considers the synergy between azimuth calculation and well inclination measurement. In actual measurements, the azimuth and well inclination jointly determine the precise positioning of the wellbore in space. The gradient tensor and core characteristic correction term introduced in the formula not only improve the calculation accuracy of the azimuth, but also share some physical models and parameters with the well inclination formula in Example 8, such as the normalization of the effective magnetic permeability and magnetic field gradient tensor. This synergy is of great significance in the overall implementation of the system, and can effectively reduce the error transmission between different measurement modules and improve the overall accuracy of the measurement system. Example 10: In this example, the system uses a high-precision fluxgate sensor group with three axes arranged orthogonally, and its main parameters are as follows: Number of turns of the induction coil : 1200 turns; effective cross-sectional area of ​​core :0.015m²; Base magnetic permeability : 2500H / m; magnetic relaxation time constant : 0.002s; core radius :0.005m; Magnetic domain size :0.0002m; Excitation magnetic field strength : 50A / m; saturation magnetic field intensity : 500A / m; Excitation frequency : 1000Hz (angular frequency is about rad / s); Phase delay : 10° (about 0.1745 radians); the downhole ambient temperature is monitored in real time, and the reference temperature is set to K, temperature influence coefficient Take 0.4, the activation energy of magnetic domain rearrangement Take 0.1eV, the Boltzmann constant eV / K.

[0051] In addition, in order to facilitate accurate correction of the downhole magnetic field, this embodiment introduces specific installation angle parameters when installing the sensor, as follows: The azimuth angle of the X-axis sensor when installed : 30° (0.5236 radians), inclination : 5° (0.0873 radians); azimuth angle when the Y-axis sensor is installed : 120° (2.0944 radians), inclination : 8° (0.1396 radians); azimuth angle when the Z-axis sensor is installed : 0° (0 radians), inclination : 0° (perfect vertical installation); the overall system architecture is as follows Figure 1 As shown, each module is interconnected through a high-speed data acquisition system, and the original output signal of the sensor is transmitted to the magnetic field data analysis part for real-time data processing.

[0052] Specific calculation of the fluxgate sensor reference output response: Based on the above parameters, the magnetic field data analysis part first calculates the fluxgate sensor reference output response in each direction according to the following formula : ;in: , , H / m; Excitation magnetic field strength A / m and saturation magnetic field strength A / m, so ; Magnetic relaxation time constant s, sensor operation time In the initial stage, t=0.001s is generally used for preliminary calibration; the core radius , domain size m, then the Bessel function part From the numerical calculation, it can be obtained that its value tends to be a smaller oscillation value, which is corrected by the pre-established lookup table in the actual data processing; the excitation frequency rad / s, and phase delay In actual calculations, the system performs digital signal processing on the time derivative and periodic sinusoidal term of the above function, and uses a real-time filtering algorithm to smooth the output, ensuring that each sensor can provide stable benchmark response data in a dynamic environment.

[0053] Dynamic correction of the reference magnetic permeability: Considering the influence of underground high temperature and environmental disturbance on the characteristics of magnetic core materials, the magnetic field data analysis part uses the following formula to correct the reference magnetic permeability: Correction is made to obtain the effective permeability : ; Among them, temperature To collect data in real time. Assuming that the underground temperature is 310K during a certain measurement, the temperature correction term is: (Note: The calculated value of the temperature compensation factor here is relatively large. In actual applications, it can be corrected according to the core characteristics. This is only an example). The exponential correction term is ; Combined with sensor output A stable output value is obtained through numerical integration or filtering, for example, V (the actual value depends on the calibration result). Therefore, after this correction, we get: This correction result enables the system to adjust the sensitivity of the magnetic core in real time under high temperature environment, thereby ensuring the accuracy of the measurement data.

[0054] Correction calculation of the three-axis magnetic field component: After obtaining the original magnetic field component data of the sensor group After that, it is projected into the standard rectangular coordinate system by the following formula and combined with the effective magnetic permeability Correction is performed and the corrected magnetic field component is calculated : ; Taking the actual sensor data as an example, assume that the original magnetic field components obtained in one acquisition are: mV, mV, mV, after amplification, filtering and normalization, they are converted into corresponding digital quantities. Using the above installation angle parameters: ; ; ; ; ; ; ; ; ; ; For the Z-axis sensor, the inclination angle is 0°, so , After the matrix calculation, the corrected magnetic field component in each direction can be determined. H / m, which can be numerically calculated to ensure that the magnetic field value in each direction accurately reflects the actual downhole magnetic field conditions.

[0055] Construction and correction of magnetic field gradient tensor: Using the corrected three-axis magnetic field components, this embodiment uses a gradient operator to construct a magnetic field gradient tensor : ;in: It means partial differential operation on spatial coordinates. To facilitate implementation, this system has a built-in high-precision spatial sampling unit, and its sampling interval is set to 0.1m; The value is consistent with the excitation magnetic field strength, that is, 50A / m; the exponential correction term is used to weaken the influence of non-zero divergence caused by local interference. For example, after numerically calculating the components of the gradient tensor, it is assumed that there are the following values ​​in a certain sampling area (the units are all in standard international units): T / m, T / m, T / m; T / m, T / m, T / m; T / m, T / m, T / m; after the gradient tensor is subjected to determinant or divergence operation, it is processed by exponential correction term to ensure that the gradient tensor data can be used for subsequent geomagnetic field separation. The specific numerical calculation process has been automated in the digital signal processing module.

[0056] Separation algorithm of geomagnetic field vector: In order to remove the local interference magnetic field from the total magnetic field vector, Separate the geomagnetic field vector Surface is a sphere centered on the sensor group, and its radius is to The radius here is m; is the position vector of each point on the sphere, is the mean vector of sensor positions; is the surface element normal vector; is the trace of the gradient tensor, obtained by summing the main diagonal elements of the tensor. By integrating all the elements in the sphere, the system can effectively filter out the local interference magnetic field. For example, in one measurement, the interference component is determined to be about 0.0003T after integral calculation. After exponential correction, the final separated geomagnetic field vector is The value is closer to the real geomagnetic field value. This process is completed by numerical integration algorithm inside the system and runs in real time in the digital signal processor.

[0057] Well inclination calculation: using the separated geomagnetic field vector The measurement result calculation part calculates the well inclination angle according to the following formula : ;in: , , are the components of the geomagnetic field vector in the X, Y, and Z directions respectively; , , are the values ​​of the main components in the gradient tensor respectively; is the Langevin function. Taking the data in this example, take H / m, A / m, eV / K, K, then: The corresponding Langevin function A stable value can be obtained through numerical calculation (the specific value is determined by the pre-calibration function). Assume that the separated geomagnetic field vector value is: T, T, T, after calculation, its modulus is approximately T, the well inclination angle is calculated as: ; Assuming that the exponential term after normalization of the gradient tensor is 0.95, and the result of the Langevin function is about 0.98, the final calculated well inclination angle is approximately: ; This angle value can more accurately reflect the actual inclination state of the wellbore.

[0058] Azimuth calculation: Similarly, based on the separated geomagnetic field vector, this embodiment uses the following formula to calculate the wellbore azimuth : ; Assume that the horizontal component of the geomagnetic field vector is T, T, then the preliminary calculation is: ; Combining the above exponential correction term (assuming the normalized result is 0.97) and the Langevin function (0.98), the final calculated azimuth is: This angle value reflects the true direction of the wellbore in the horizontal plane.

[0059] To ensure accurate calculation of the parameters of the above modules, the system has a built-in high-precision data acquisition card with a sampling frequency set to 10kHz to ensure that the periodic changes of the excitation signal can be accurately captured when the excitation frequency is 1000Hz. All signals enter the analog-to-digital conversion module after passing through the analog front-end amplifier circuit and the low-pass filter (the cut-off frequency is set to 1.2kHz). The digital signal processor (DSP) is responsible for processing the collected raw data in the following steps: Time domain filtering: Kalman filtering and moving average filtering algorithms are used to smooth the raw data to eliminate high-frequency noise and environmental interference. Temperature compensation: Real-time acquisition of downhole temperature data (the error is controlled within ±0.5K), and the magnetic permeability is corrected by the aforementioned temperature correction formula. Multi-channel data fusion: The three-directional sensor data are fused into the standard rectangular coordinate system using matrix transformation, and the space vector reconstruction is realized in combination with calibration parameters. Gradient tensor calculation and integration: The magnetic field gradient tensor of each sampling point in space is calculated using the differential algorithm, and numerical integration is implemented in the spherical area to separate the local interference field. Angle solution: Based on the separated geomagnetic field vector, the inclination angle and azimuth angle are obtained by arccosine and arctangent operations, and further corrected by exponential correction and Langevin function. Data acquisition and processing are all realized through real-time software modules, and the calculation results of each step can be monitored by the host computer software. The user interface provided by the system can display the magnetic field components, gradient tensor parameters, geomagnetic field vectors and the final calculated inclination angle and azimuth angle before and after correction in real time, so that engineers can adjust the correction parameters according to actual conditions.

[0060] In order to verify the specific parameters and data processing flow in Example 10, this embodiment is tested in an actual underground environment. The test well is about 1000m deep, and there are metal pipes and electrical equipment interference in the wellbore. After preliminary calibration, the system optimizes and adjusts the various parameters of the sensor, and the specific results are as follows: after temperature compensation and permeability correction, the stability of the sensor output signal is improved by about 35%, and the noise level is reduced to 60% of the original; after data fusion and gradient tensor separation, the separated geomagnetic field vector and the national geomagnetic field database data match with an error of less than 5%; the measured values ​​of the well inclination angle and azimuth angle are 36.2° and 33.8° respectively. Compared with the traditional gyroscope measurement data, the deviation is controlled within ±2°. The test results show that the specific parameters and data processing methods used in this embodiment can effectively deal with the magnetic field interference in the complex underground environment, ensuring that the measurement results have high accuracy and stability.

[0061] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. The well inclination and geomagnetic field strength measurement system based on high-precision fluxgate sensor is characterized by: The system comprises: a fluxgate sensor group, a magnetic field data analysis part and a measurement result calculation part; The fluxgate sensor group includes three high-precision fluxgate sensors which are arranged in an underground environment and respectively measure the magnetic field components in the X-axis direction, the Y-axis direction and the Z-axis direction; The magnetic field data analysis part is used to calculate the reference output response of the high-precision fluxgate sensor according to the physical parameters of the high-precision fluxgate sensor, and correct the reference magnetic permeability of the high-precision fluxgate sensor in combination with the temperature and the reference output response at the current time to obtain the effective magnetic permeability; according to the effective magnetic permeability, calculate the corrected magnetic field component of the magnetic field component in each direction under the effective magnetic permeability, and then calculate the total magnetic field vector corresponding to the corrected magnetic field components in the three directions; construct a magnetic field gradient tensor based on the corrected magnetic field component in each direction, and separate the geomagnetic field vector from the total magnetic field vector according to the magnetic field gradient tensor; The measurement result calculation part is used to calculate the well inclination value and azimuth value according to the geomagnetic field vector; and the magnetic field intensity, well inclination value and azimuth value corresponding to the measured geomagnetic field vector are used as the final measurement result.

2. The well inclination and geomagnetic field strength measurement system based on high-precision fluxgate sensor according to claim 1, characterized in that: The physical parameters of the high-precision fluxgate sensor include: number of turns of the induction coil, effective cross-sectional area of ​​the magnetic core, reference magnetic permeability, magnetic relaxation time constant, magnetic core radius, magnetic domain size, excitation magnetic field strength, saturation magnetic field strength, excitation frequency and phase delay.

3. The well inclination and geomagnetic field intensity measurement system based on high-precision fluxgate sensor according to claim 2, characterized in that: The magnetic field data analysis part calculates the reference output response of each high-precision fluxgate sensor according to the magnetic field component in each direction through the following formula: ； in, is the benchmark output response; is the operating time of the high-precision fluxgate sensor; is the number of turns of the induction coil; is the effective cross-sectional area of ​​the core; is the excitation magnetic field strength; is the saturation magnetic field strength; is the core radius; is the magnetic domain size; is the reference magnetic permeability; is the phase delay; is the excitation frequency; is the zero-order Bessel function; is the magnetic relaxation time constant.

4. The well inclination and geomagnetic field intensity measurement system based on high-precision fluxgate sensor according to claim 3, characterized in that: The reference magnetic permeability of the high-precision fluxgate sensor is corrected by the following formula to obtain the effective magnetic permeability: ； in, is the effective magnetic permeability; The local energy barrier that needs to be overcome for magnetic domains to flip or rearrange; is the Boltzmann constant; is the reference temperature; is the temperature influence coefficient, ranging from 0.3 to 0.

5.

5. The well inclination and geomagnetic field intensity measurement system based on high-precision fluxgate sensor according to claim 4, characterized in that: The corrected magnetic field component of the magnetic field component in each direction under the effective magnetic permeability is calculated by the following formula according to the effective magnetic permeability: ； in, is the corrected magnetic field component in the X-axis direction; is the corrected magnetic field component in the Y-axis direction; is the corrected magnetic field component in the Z-axis direction; is the installation azimuth angle of the high-precision fluxgate sensor corresponding to the X-axis direction; is the installation azimuth angle of the high-precision fluxgate sensor corresponding to the Y-axis direction; The installation azimuth angle of the high-precision fluxgate sensor corresponding to the Z-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the X-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the Y-axis direction; is the inclination angle of the high-precision fluxgate sensor corresponding to the Z-axis direction.

6. The well inclination and geomagnetic field intensity measurement system based on high-precision fluxgate sensor according to claim 5, characterized in that: The magnetic field gradient tensor is constructed based on the corrected magnetic field component in each direction using the following formula: ； in, is the tensor product operation; is the gradient operator; is the total magnetic field vector; is the determinant operator; is the magnetic field gradient tensor.

7. The well inclination and geomagnetic field intensity measurement system based on high-precision fluxgate sensor according to claim 6, characterized in that: The geomagnetic field vector is separated from the total magnetic field vector by the following formula: ； in, The spherical surface with a set value as the radius contains three high-precision fluxgate sensors. The radius range is arrive ; is the position vector on the spherical surface; The mean vector of the position vectors of three high-precision fluxgate sensors on the spherical surface; is the surface element normal vector; is the trace of the magnetic field gradient tensor.

8. The well inclination and geomagnetic field intensity measurement system based on high-precision fluxgate sensor according to claim 7, characterized in that: The well inclination angle is calculated according to the geomagnetic field vector using the following formula: ； in, for The component in the Z-axis direction; for The component in the X-axis direction; for The component in the Y-axis direction; for The first element of for The second element of for The third element of It is Lang's ten thousand functions; is the well inclination value.

9. The well inclination and geomagnetic field intensity measurement system based on high-precision fluxgate sensor according to claim 8, characterized in that: The azimuth value is calculated according to the geomagnetic field vector using the following formula: ； in, is the azimuth value.

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