Novel well trajectory continuous measurement real-time correction method and system

Abstract

The invention provides a novel well track continuous measurement real-time correction method and system, continuous measurement data is cleaned, fitted and corrected in real time by combining fixed measurement data, then track calculation is performed, the track calculation precision can be remarkably improved, and the vertical depth error is reduced. Static measurement data and first dynamic measurement data are acquired and cleaned; performing data fitting processing, correcting the cleaned first dynamic measurement data to enable a curve to approach the static measurement data, and obtaining corrected second dynamic measurement data; and real-time well trajectory calculation: re-calculating the well trajectory by using the second dynamic measurement data to obtain a real-time well trajectory.

Description

Technical Field

[0001] The present invention relates to the technical field of drilling engineering, and in particular to a novel well trajectory continuous measurement and real-time correction method and system. Background Art

[0002] In the traditional drilling process, the inclination angle, azimuth and other data are generally measured by a while drilling inclinometer. In order to minimize the downhole vibration interference, the single while drilling inclinometer is installed far away from the drill bit, and drilling is stopped during measurement. On the one hand, the measurement position is far away from the drill bit, the information has errors and real-time data cannot be obtained. This traditional method cannot provide accurate wellbore trajectory information; on the other hand, it will reduce drilling efficiency and bring greater well control risks.

[0003] The near-drill-bit measurement system commonly used at present can realize real-time measurement without additional drilling stops and without increasing the cost of the drilling rig. However, under the existing conditions, it cannot guarantee that the accuracy of continuous measurement data can reach the accuracy of static measurement.

[0004] Among them, the patent application number is CN202211532836.7, which is a method for detecting and correcting data anomalies in the calculation of drilling pressure parameters. The gradient descent fitting algorithm of machine learning is used to calculate parameters such as pressure during drilling, detect the input data of each calculation module and the data anomalies in the calculation results, and give the optimal calculation results of various pressures and parameters. However, the essence is to find out the abnormal data with large discreteness and delete it, so as to reduce the impact of the basic data error on the calculation results and improve the timeliness and accuracy of data processing.

[0005] In addition to deleting abnormal original data, the present invention also obtains continuous measurement data with the help of a near-bit continuous measurement system, and corrects the continuous measurement data in real time in combination with fixed measurement data. The calculated well trajectory results not only ensure data integrity, but also greatly reduce the vertical depth error of trajectory calculation. Summary of the invention

[0006] The purpose of the present invention is to provide a novel real-time correction method and system for continuous measurement of well trajectories. By cleaning and fitting the continuous measurement data in real time in combination with fixed measurement data, and then performing trajectory calculation, the trajectory calculation accuracy can be significantly improved and the vertical depth error can be reduced.

[0007] The embodiment of the present invention is achieved as follows:

[0008] A novel real-time correction method for continuous measurement of well trajectory, the correction method comprising the following steps:

[0009] Data preprocessing, acquiring and cleaning static measurement data and first dynamic measurement data;

[0010] Data fitting processing, after correcting the first dynamic measurement data after cleaning, the curve approximates the static measurement data to obtain the corrected second dynamic measurement data;

[0011] Real-time well trajectory calculation, using the second dynamic measurement data to recalculate the well trajectory to obtain the real-time well trajectory.

[0012] In a preferred embodiment of the present invention, the data fitting processing method includes:

[0013] When there are two static measurement points, the midpoint line of the two static measurement points is used as the first baseline, so that the first dynamic measurement data is approached to the first baseline; when the first dynamic measurement data after approximation is still inconsistent with the data of the static measurement points, the starting point of the first dynamic measurement data is first aligned, and the measurement data of the remaining points are translated to the same extent; then, when the first dynamic measurement data is aligned to the end point of the continuous measurement, the interpolation coefficients of the remaining points are calculated according to the well depth ratio, and the continuous measurement points are translated according to the interpolation coefficients to obtain the first fitting data;

[0014] When the number of static measurement points is greater than 2, the static measurement points are interpolated to obtain a second reference curve, so that the first dynamic measurement data approaches the second reference line; when the first dynamic measurement data after approximation is still not consistent with the static measurement points, the starting point and the end point of the first dynamic measurement data are first replaced with the two points of the latest static measurement, and then the interpolation method is used to interpolate the replaced continuous measurement data and the continuous measurement data of the previous well section, and the interpolated data is the second fitting data.

[0015] In a preferred embodiment of the present invention, the algorithm for approximating the first dynamic measurement data to the first reference line adopts the least square method.

[0016] In a preferred embodiment of the present invention, the above interpolation method is a piecewise cubic spline interpolation method.

[0017] In a preferred embodiment of the present invention, the method for making the first dynamic measurement data approach the second reference line is to take the second reference curve between the two latest static measurement points and approximate the continuous measurement data corresponding to the well section to the second reference curve.

[0018] In a preferred embodiment of the present invention, the above-mentioned data fitting processing method also includes: after obtaining the first fitting data or the second fitting data, starting from the second point of static measurement, the well inclination and azimuth correction are updated once each time the static measurement is performed to obtain the second dynamic measurement data.

[0019] In a preferred embodiment of the present invention, after the real-time well trajectory is obtained, the real-time well trajectory is compared with the planned well trajectory. If there is a large deviation or abnormal geological conditions are encountered, the drilling plan is adjusted in time and the measurement data is continued to be recorded.

[0020] In a preferred embodiment of the present invention, the cleaning method is to remove abnormal values ​​and outliers in the measurement data and retain the basic trend of the measurement data.

[0021] In a preferred embodiment of the present invention, the static measurement data include drilling data measured by an inclinometer; and the dynamic measurement data include drilling data measured by a near-drill-bit measurement system.

[0022] A novel well trajectory continuous measurement and real-time correction system includes:

[0023] A data preprocessing module, used for acquiring and cleaning static measurement data and first dynamic measurement data;

[0024] A data fitting processing module is used to correct the first dynamic measurement data after cleaning, so that the curve approximates the static measurement data, and obtains the corrected second dynamic measurement data;

[0025] The real-time well trajectory calculation module is used to recalculate the well trajectory using the second dynamic measurement data to obtain the real-time well trajectory.

[0026] The beneficial effects of the embodiments of the present invention are as follows: the real-time correction method for continuous measurement of well trajectories in the present invention, during the drilling process, the dynamic measurement data is segmented and combined with the fixed measurement data for fitting, the correction method is used to correct the continuous measurement data near the drill bit, and the drilled trajectory is drawn in real time, thereby improving the overall trajectory calculation accuracy and improving the layer encounter rate during the drilling process. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 This is a flow chart of a novel well trajectory continuous measurement and real-time correction method in an embodiment of the present invention;

[0029] Figure 2 It is an operation flow chart of the data fitting processing step in the real-time correction method for continuous measurement of well trajectory in an embodiment of the present invention;

[0030] Figure 3 is a curve showing the variation of the well inclination angle data with the well depth before preprocessing in an embodiment of the present invention;

[0031] Figure 4 is a curve showing the variation of well inclination angle data after preprocessing with well depth in an embodiment of the present invention;

[0032] Figure 5 The curves of the continuous measurement and fixed measurement well inclination angles versus well depth drawn together in the embodiment of the present invention before and after correction;

[0033] Figure 6 It is a partial enlarged diagram of the curves of the continuous measurement and fixed measurement of the well inclination angle changing with the well depth before and after correction in the embodiment of the present invention;

[0034] Figure 7 It is a curve showing the variation of the vertical depth difference between the continuous measurement and the fixed measurement with the apparent well depth before and after correction in the embodiment of the present invention;

[0035] Figure 8 This is a schematic block diagram of the connection of a novel well trajectory continuous measurement and real-time correction system in an embodiment of the present invention.

[0036] Icon: M1-data preprocessing module; M2-data fitting processing module; M3-real-time well trajectory calculation module. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0038] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0040] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0041] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0042] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0043] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0044] First embodiment

[0045] See also Figure 1 and Figure 2 , This embodiment provides a novel well trajectory continuous measurement and real-time correction method, which is mainly used for the control and measurement of rotary steering tools in oil drilling projects.

[0046] During the drilling process, a fixed measurement interval is performed, and continuous measurement near the drill bit can be performed multiple times. Real-time correction is to correct the continuous measurement data between two fixed measurement points. Therefore, during the entire drilling process, the total number of corrections to the continuous measurement data is consistent with the number of fixed measurement points. The core of this correction method is to consider the fixed measurement data as accurate data, and to approximate the continuous measurement data to the fixed point through a nonlinear interpolation method. The correction method includes the following steps:

[0047] S1: data preprocessing, acquiring and cleaning static measurement data and first dynamic measurement data;

[0048] S2: data fitting processing, after correcting the first dynamic measurement data after cleaning, the curve approximates the static measurement data to obtain the corrected second dynamic measurement data;

[0049] S3: Real-time well trajectory calculation: recalculate the well trajectory using the second dynamic measurement data to obtain the real-time well trajectory.

[0050] In the data preprocessing step of S1, two types of data are included, static measurement data and dynamic measurement data. The static measurement data include data measured by GNSS combined with total station, RTK measurement, GNSS combined with rope measurement, inclinometer and other equipment. Dynamic measurement data include drilling data measured by near-bit measurement system or other real-time measurement instruments. Input parameters include well depth MD, well inclination Inc and azimuth Azi of each continuous measurement point and static measurement point.

[0051] In this embodiment, the abnormal data of the dynamic measurement data is mainly cleaned, and the purpose of cleaning is mainly to remove the abnormal values ​​and outliers in the measurement data and retain the basic trend of the measurement data. In order to overcome the system error caused by sensor offset, noise generated by the high-vibration drilling environment or the operation of the accelerometer in the near-drill bit measurement system, continuous measurement data usually have abnormal values ​​or outliers, and abnormal points may seriously affect the fitting results. It will get better results to eliminate these points first and then make corrections, for example, by denoising the data, adding appropriate sensor offsets and other methods to improve the quality, consistency and applicability of dynamic measurement data.

[0052] Since in the prior art, the near-drill-bit measurement system can perform real-time continuous drilling and measurement, and rarely has other abnormal situations such as missing or repeated measurement data, the preprocessing step in this embodiment does not use missing value interpolation, duplicate value deletion and other preprocessing methods as the main abnormal data cleaning, but only deletes abnormal values ​​or outliers; when missing values ​​or duplicate values ​​appear, those skilled in the art should know and be able to use the corresponding processing method for data preprocessing. Of course, in the process of abnormal data cleaning, it is also possible to find abnormal points and delete them similar to the clustering method in CN202211532836.7.

[0053] The data fitting process in S2 is the core part of this case. This data fitting process is based on fixed measurement data and divides the measurement data into two parts. Figure 2 , and its fitting processing methods include:

[0054] In the first part, the number of static measurement points is equal to 2. At this time, the number of fixed measurement points is small, and the boundary trend at the interpolation endpoint cannot be determined. The midpoint line of the two fixed measurement points is used as the first baseline, and the least squares method is used to make the first dynamic measurement data approach the first baseline until the sum of square errors of each point is minimized; when the first dynamic measurement data is consistent with the data of the static measurement point, the adjusted first dynamic measurement data is used as the first fitting data.

[0055] When the first dynamic measurement data after approximation is still inconsistent with the data of the static measurement point, the starting point of the first dynamic measurement data is first aligned, and the measurement data of the remaining points are translated to the same extent; then, when the first dynamic measurement data is aligned to the end point of the continuous measurement, the interpolation coefficients of the remaining points are calculated according to the well depth ratio, and the continuous measurement points are translated according to the interpolation coefficients to obtain the first fitting data.

[0056] In the second part, the number of static measurement points is greater than 2. First, the existing static measurement points are interpolated, and the interpolation adopts the piecewise cubic spline interpolation method to obtain the second reference curve, so that the continuous measurement data corresponding to the well section is approximated to the second reference line. The approximation method is to take the second reference curve between the latest two static measurement points, and approximate the continuous measurement data corresponding to the well section to the second reference curve; when the first dynamic measurement data after approximation is consistent with the static measurement point, the adjusted first dynamic measurement data is used as the second fitting data.

[0057] When the first dynamic measurement data after approximation is still not consistent with the static measurement points, the starting point and end point of the first dynamic measurement data are first replaced with the two points of the latest static measurement, and then the interpolation method is used to interpolate the replaced continuous measurement data and the continuous measurement data of the previous well section. The interpolated data is the second fitting data.

[0058] After obtaining the first fitting data or the second fitting data, starting from the second point of the static measurement, the dynamic measurement data correction is updated once each time the static measurement is performed, such as the correction of the well inclination and azimuth, to obtain the corrected well inclination and azimuth data.

[0059] In step S3, after the real-time well trajectory is obtained, a new real-time well trajectory is obtained at each fixed measurement point. The real-time well trajectory is compared with the planned well trajectory. If the deviation is large or abnormal geological conditions are encountered, the drilling plan is adjusted in time and the measurement data continues to be recorded.

[0060] In the process of directional well drilling, how to depict the actual well trajectory as accurately as possible is of great significance to improving drilling efficiency and accurately reaching the target layer. This embodiment provides a method for improving the accuracy of well trajectory, which can significantly improve the trajectory calculation accuracy and reduce the vertical depth error by cleaning and correcting the continuous measurement data in real time combined with fixed measurement data and then performing trajectory calculation.

[0061] Second embodiment

[0062] This embodiment is based on the real-time correction method for continuous measurement of well trajectory given in the first embodiment, taking well inclination data as an example.

[0063] First, preprocess the well inclination data. Figure 3 and Figure 4The variation curve of well inclination angle data with well depth before and after preprocessing shows that after removing the outliers and outliers of well inclination angle data, the variation curve retains the basic trend.

[0064] The curves of the change of well inclination angle with well depth before and after preprocessing are plotted on the same graph. It can be seen that the overall trend of the well inclination angle change of continuous measurement and fixed measurement is consistent, but due to the small measurement interval, the well inclination change trend of continuous measurement is more detailed, which will lead to differences in the calculation of the well trajectory between the two. At the same time, there is a deviation between fixed measurement and continuous measurement at the fixed point, so it is necessary to perform fitting correction processing on the well inclination angle data through S2. The curves of the change of well inclination angle with well depth of continuous measurement and fixed measurement before and after correction are shown in the figure. Figure 5 and Figure 6 .

[0065] Similarly, the same operation can be performed on the azimuth data to obtain the corrected well depth, well inclination and azimuth. Figure 7 The curve of vertical depth difference between continuous measurement and fixed measurement before and after correction versus apparent well depth.

[0066] It can be seen that the vertical depth difference between the well trajectory calculated by continuous measurement and fixed measurement before correction is 1.56m at the end of the deflection section, which proves that the continuous measurement data has a certain reliability after quality inspection. After the continuous measurement data is corrected by the correction method, the final error of the deflection section is about 0.63m, which is less than about 1.4m before correction.

[0067] Through practical verification, it can be concluded that the new real-time correction method for continuous measurement of well trajectories, during the drilling process, the dynamic measurement data is segmented and combined with the fixed measurement data for fitting, and the correction method is used to correct the continuous measurement data near the drill bit, and the drilled trajectory is drawn in real time, which can improve the overall trajectory calculation accuracy and increase the layer encounter rate during the drilling process.

[0068] Third embodiment

[0069] This embodiment provides a new well trajectory continuous measurement real-time correction system based on the trajectory correction method of the first embodiment. Figure 8 , which includes a data preprocessing module, a data fitting processing module and a real-time well trajectory calculation module which are sequentially connected in communication:

[0070] A data preprocessing module M1, used for acquiring and cleaning static measurement data and first dynamic measurement data;

[0071] The data fitting processing module M2 is used to correct the first dynamic measurement data after cleaning, so that the curve approximates the static measurement data, and obtains the corrected second dynamic measurement data;

[0072] The real-time well trajectory calculation module M3 is used to recalculate the well trajectory using the second dynamic measurement data to obtain the real-time well trajectory.

[0073] The data fitting processing module is further configured as follows:

[0074] When the number of static measurement points is equal to 2, the midpoint line of the two fixed measurement points is used as the first reference line, and the least square method is used to make the first dynamic measurement data approach the first reference line until the sum of square errors of each point is minimized.

[0075] When the first dynamic measurement data after approximation is still inconsistent with the data of the static measurement point, the starting point of the first dynamic measurement data is first aligned, and the measurement data of the remaining points are translated to the same extent; then, when the first dynamic measurement data is aligned to the end point of the continuous measurement, the interpolation coefficients of the remaining points are calculated according to the well depth ratio, and the continuous measurement points are translated according to the interpolation coefficients to obtain the first fitting data.

[0076] When the number of static measurement points is greater than 2, the existing static measurement points are first used for interpolation, and the interpolation adopts the piecewise cubic spline interpolation method to obtain the second reference curve, so that the continuous measurement data corresponding to the well section is approximated to the second reference line. The approximation method is to take the second reference curve between the latest two static measurement points, and approximate the continuous measurement data corresponding to the well section to the second reference curve.

[0077] When the first dynamic measurement data after approximation is still not consistent with the static measurement points, the starting point and end point of the first dynamic measurement data are first replaced with the two points of the latest static measurement, and then the interpolation method is used to interpolate the replaced continuous measurement data and the continuous measurement data of the previous well section. The interpolated data is the second fitting data.

[0078] After obtaining the first fitting data or the second fitting data, starting from the second point of the static measurement, the dynamic measurement data correction is updated once each time the static measurement is performed, such as the correction of the well inclination and azimuth, to obtain the corrected well inclination and azimuth data.

[0079] The well trajectory continuous measurement real-time correction system can be applied to downhole real-time measurement and real-time data fitting correction. By using the corrected measurement data for trajectory calculation, the trajectory calculation accuracy can be significantly improved and the vertical depth error can be reduced.

[0080] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0081] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, or it can be an electrical, mechanical or other form of connection.

[0082] The modules described as separate components may or may not be physically separated. As modules, ordinary technicians in the field can realize that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0083] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing module, each module may exist physically separately, or two or more modules may be integrated into one module. The above integrated module may be implemented in the form of hardware or in the form of software functional modules.

[0084] If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a grid device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0085] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A novel real-time correction method for continuous measurement of well trajectory, characterized in that: The correction method comprises the following steps: Data preprocessing, acquiring and cleaning static measurement data and first dynamic measurement data; Data fitting processing, after correcting the first dynamic measurement data after cleaning, the curve approximates the static measurement data to obtain the corrected second dynamic measurement data; Real-time well trajectory calculation: recalculate the well trajectory using the second dynamic measurement data to obtain the real-time well trajectory.

2. The novel well trajectory continuous measurement real-time correction method according to claim 1 is characterized in that: The data fitting processing method comprises: When there are two static measurement points, the midpoint line of the two static measurement points is used as the first reference line, so that the first dynamic measurement data is approached to the first reference line; when the approximated first dynamic measurement data is not consistent with the data of the static measurement points, the starting point of the first dynamic measurement data is first aligned, and the measurement data of the remaining points are translated to the same extent; then, when the first dynamic measurement data is aligned to the end point of the continuous measurement, the interpolation coefficients of the remaining points are calculated according to the well depth ratio, and the continuous measurement points are translated according to the interpolation coefficients to obtain the first fitting data; When the number of static measurement points is greater than 2, the static measurement points are interpolated to obtain a second reference curve, so that the first dynamic measurement data approaches the second reference line; when the first dynamic measurement data after approximation is still not consistent with the static measurement points, the starting point and the end point of the first dynamic measurement data are first replaced with the two points of the latest static measurement, and then the interpolation method is used to interpolate the replaced continuous measurement data and the continuous measurement data of the previous well section, and the interpolated data is the second fitting data.

3. The novel well trajectory continuous measurement real-time correction method according to claim 2 is characterized in that: The algorithm for approximating the first dynamic measurement data to the first reference line adopts the least square method.

4. The novel well trajectory continuous measurement real-time correction method according to claim 2 is characterized in that: The interpolation method is a piecewise cubic spline interpolation method.

5. The novel well trajectory continuous measurement real-time correction method according to claim 4 is characterized in that: The method for making the first dynamic measurement data approach the second reference line is to take the second reference curve between the two latest static measurement points and approximate the continuous measurement data corresponding to the well section to the second reference curve.

6. The novel well trajectory continuous measurement real-time correction method according to claim 2 is characterized in that: The data fitting processing method also includes: after obtaining the first fitting data or the second fitting data, starting from the second point of static measurement, updating the well inclination angle and azimuth correction once each time the static measurement is performed to obtain the second dynamic measurement data.

7. The novel well trajectory continuous measurement real-time correction method according to claim 1 is characterized in that: After the real-time well trajectory is obtained, the real-time well trajectory is compared with the planned well trajectory. If there is a large deviation or abnormal geological conditions are encountered, the drilling plan is adjusted in time and the measurement data is continued to be recorded.

8. The novel well trajectory continuous measurement real-time correction method according to claim 1 is characterized in that: The cleaning method is to remove abnormal values ​​and outliers in the measurement data and retain the basic trend of the measurement data.

9. The novel well trajectory continuous measurement real-time correction method according to claim 1 is characterized in that: The static measurement data includes drilling data measured by an inclinometer; the dynamic measurement data includes drilling data measured by a near-bit measurement system.

10. A new type of well trajectory continuous measurement real-time correction system, characterized in that: Including sequential communication connections: A data preprocessing module, used for acquiring and cleaning static measurement data and first dynamic measurement data; A data fitting processing module, used for correcting the first dynamic measurement data after cleaning so that a curve approximates the static measurement data to obtain a corrected second dynamic measurement data; The real-time well trajectory calculation module is used to recalculate the well trajectory using the second dynamic measurement data to obtain the real-time well trajectory.

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