Method for transmitting data of inclinometer while drilling based on MWD (Measurement While Drilling)

Abstract

The invention relates to the technical field of data transmission, in particular to an MWD (Measurement While Drilling)-based inclinometer data transmission method. The method comprises the following steps: correcting original measurement data, generating and detecting corrected data, and determining a data abrupt change value; on the basis of the positioning data, terrain data are obtained and analyzed, and the terrain characteristics of the position where the inclinometer is located are determined; determining a dynamic sudden change threshold according to the terrain characteristics and the positioning data; when it is detected that the correction data sudden change value exceeds the dynamic sudden change threshold value, a Bluetooth retransmission instruction is sent to the inclined drilling instrument; acquiring the transmitted verification data; and comparing the correction data with the verification data, judging an interference type according to a comparison result, and further switching a data transmission mode. Redundant verification points are provided, data integrity and reliability are ensured, and the decision is prevented from being influenced by errors of a single data source. And the real-time performance and reliability of data transmission are optimized, the anti-interference capability is enhanced in a self-adaptive manner for different interferences, and the stability and high efficiency of data streams are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of data transmission, and in particular to a method for transmitting while-drilling inclinometer data based on MWD. Background Art

[0002] In fields such as oil drilling and geological exploration, measurement-while-drilling (MWD) systems are key technologies for ensuring precise control of wellbore trajectories. The inclinometer, a core component of the MWD system, measures the wellbore's spatial attitude parameters in real time and transmits these results to the operator terminal via a data transmission link to guide drilling operations.

[0003] In harsh environments with frequent interference, existing technologies usually rely solely on filtering algorithms to smooth the raw measurement data. However, the filtering lag effect can cause data mutation points to be incorrectly smoothed, making it impossible to identify anomalies in a timely manner and increasing the risk of wellbore trajectory deviation. Summary of the Invention

[0004] The present application provides a method for transmitting inclinometer data while drilling based on MWD to solve the above problems.

[0005] In a first aspect, the present application provides a method for transmitting inclinometer data while drilling based on MWD, the method comprising: Obtaining original measurement data and positioning data of the while drilling inclinometer; Correcting the original measurement data to generate corrected data; detecting the corrected data to determine a data mutation value; Based on the positioning data, acquiring and analyzing terrain data to determine the terrain characteristics of the location of the while drilling inclinometer; determining a dynamic mutation threshold value based on the terrain characteristics and the positioning data; When it is detected that the correction data mutation value exceeds the dynamic mutation threshold, a Bluetooth retransmission instruction is sent to the deflection drill; and verification data retransmitted by the deflection drill is obtained; The correction data is compared with the verification data, and the interference type is determined according to the comparison result; and the data transmission mode is switched according to the interference type.

[0006] This solution corrects the original measurement data to generate corrected data, improving data accuracy and reducing the impact of noise. Corrected data is detected and the data mutation value is determined, enabling real-time detection of data anomalies. This provides a basis for triggering the retransmission mechanism and preventing potential interference events from being missed. Based on positioning data, terrain data is acquired and analyzed to determine the topographic characteristics of the location of the inclinometer, enhancing awareness of different risks at the drilling location. Based on the terrain characteristics and positioning data, a dynamic mutation threshold is determined to optimize the sensitivity and accuracy of interference detection. The threshold is adaptively adjusted according to environmental changes to reduce false positives and missed negatives. When the corrected data mutation value exceeds the dynamic mutation threshold, a Bluetooth retransmission command is sent to the inclinometer. Verification data from the retransmitted inclinometer is obtained, providing redundant verification points to ensure data integrity and reliability, preventing errors from a single data source from influencing decision-making. Corrected data is compared with verification data, and based on the comparison results, the interference type is determined, enabling classification and identification of interference sources, providing a basis for decision-making when switching modes. Data transmission mode is switched based on the interference type, optimizing the real-time and reliability of data transmission. Interference mitigation is adaptively enhanced to address different interference scenarios, ensuring a stable and efficient data flow.

[0007] Optionally, the analysis of terrain data to determine the terrain characteristics of the location where the while drilling inclinometer is located includes: parsing the positioning data to determine the longitude and latitude coordinates and the altitude; extracting the terrain undulation, rock hardness distribution and historical geological disaster records within a preset radius from a preset geological database based on the longitude and latitude coordinates and the altitude; analyzing the terrain undulation, the rock hardness distribution and the historical geological disaster records to determine the terrain stability level; and determining the terrain stability level as the terrain characteristic of the location where the while drilling inclinometer is located.

[0008] This solution parses positioning data to determine latitude and longitude coordinates and altitude, ensuring accurate location information. This avoids deviations in terrain feature extraction due to coordinate errors and enables standardized conversion of positioning data from its original format to usable geographic coordinates. Based on the latitude and longitude coordinates and altitude, the terrain relief, rock hardness distribution, and historical geological disaster records within a preset radius are extracted from a preset geological database to avoid misjudgment of terrain features due to missing or inaccurate environmental information. The terrain relief, rock hardness distribution, and historical geological disaster records are analyzed to determine the terrain stability level, enabling a quantitative assessment of terrain features and ensuring that the assessment results are consistent and operational. The terrain stability level is determined as a terrain characteristic of the location of the while-drilling inclinometer, simplifying the representation of terrain features and converting complex geological analysis results into a single, easy-to-use variable to avoid redundant processing.

[0009] Optionally, determining the dynamic mutation threshold based on the terrain characteristics and the positioning data includes: obtaining the current drilling depth and the current drill bit speed; outputting the dynamic mutation threshold through a threshold calculation model based on the current drilling depth, the current drill bit speed and the terrain stability level.

[0010] This solution captures the current drilling depth and drill bit speed, ensuring that threshold calculations adapt to changes in drilling depth, improving the targeted nature of interference processing and avoiding the risk of data distortion due to increasing depth. Furthermore, it ensures that threshold calculations respond in real time to changes in the drilling tool's operating status, enhancing the real-time and reliability of data transmission. Based on the current drilling depth, drill bit speed, and terrain stability level, the threshold calculation model outputs dynamic mutation thresholds, improving data transmission coordination, reducing errors, and ensuring real-time performance.

[0011] Optionally, the correction processing of the original measurement data to generate corrected data includes: obtaining the original measurement values of the three-axis accelerometer, the original measurement values of the three-axis magnetometer and the real-time drill pipe orientation of the downhole inclinometer; extracting the geomagnetic declination reference value from the geomagnetic database according to the latitude and longitude coordinates; determining the magnetic interference intensity coefficient according to the vector deviation between the original measurement values of the three-axis magnetometer and the geomagnetic declination reference value; performing orthogonal decomposition compensation on the original measurement values according to the magnetic interference intensity coefficient and the drill pipe orientation to generate first corrected azimuth data; performing inclination compensation on the original measurement values of the three-axis accelerometer according to the gravity acceleration model to generate first corrected inclination data; obtaining drilling operation parameters, parsing the drilling operation parameters, and determining the current drilling fluid density; performing pressure drift calibration on the first corrected inclination data and the first corrected azimuth data according to the current drilling fluid density to generate corrected data.

[0012] This solution captures the raw measurements of the triaxial accelerometer and magnetometer, along with real-time drill pipe orientation, from the inclinometer while drilling (WWD). This ensures that corrections are made directly using unprocessed sensor information, avoiding correction interruptions due to missing data. A reference value for geomagnetic declination is extracted from the geomagnetic database based on longitude and latitude coordinates. The deviation of the magnetometer measurements from ideal geomagnetic conditions is quantified, providing a basis for magnetic interference detection. The magnetic interference intensity coefficient is determined based on the vector deviation between the raw triaxial magnetometer measurements and the reference value for geomagnetic declination. This quantifies the current level of magnetic interference and provides adjustment weights for orthogonal decomposition compensation, ensuring that interference intensity is incorporated into the compensation process. Orthogonal decomposition compensation is performed on the raw measurements based on the magnetic interference intensity coefficient and drill pipe orientation to generate first-corrected azimuth data, reducing errors caused by magnetic interference and improving azimuth accuracy. The raw triaxial accelerometer measurements are then inclination-compensated based on a gravity acceleration model to generate first-corrected inclination data, correcting for errors caused by deviations in the gravity acceleration model and improving wellbore inclination accuracy. Acquire and analyze drilling operating parameters to determine the current drilling fluid density, ensuring the calibration process is tailored to the specific drilling environment. Perform pressure drift correction on the first corrected inclination and first corrected azimuth data based on the current drilling fluid density to generate corrected data, eliminating drilling fluid density-related drift and improving overall measurement data reliability.

[0013] Optionally, the magnetic interference intensity coefficient is determined based on the vector deviation between the original measurement value of the three-axis magnetometer and the geomagnetic declination reference value, including: obtaining the casing material parameters of the drill bit; calculating the eddy current electromagnetic interference intensity based on the current drill bit speed and the casing material parameters; querying the preset rock formation magnetization distribution table according to the current drilling depth to determine the formation magnetic anomaly weight factor; based on the formation magnetic anomaly weight factor and the current drill bit speed, weightedly fusing the eddy current electromagnetic interference intensity and the vector deviation to generate a magnetic interference intensity coefficient.

[0014] This solution obtains the drill bit's casing material parameters to specifically address the constant or slowly varying magnetic field interference caused by the eddy current effect of the drill pipe casing material. This ensures that the interference processing mechanism distinguishes material-related interference sources and lays a data foundation for calculating the eddy current electromagnetic interference intensity. Based on the current drill bit speed and casing material parameters, the eddy current electromagnetic interference intensity is calculated, quantifying the magnitude of the eddy current effect interference caused by drill tool rotation and characterizing the intensity of the drill tool magnetization interference. This effectively distinguishes drill tool-related interference from other interference sources and provides an independent interference index for weighted fusion, avoiding error accumulation caused by interference coupling. Based on the current drilling depth, a preset rock formation magnetization distribution table is queried to determine the formation magnetic anomaly weight factor. This dynamically assesses the influence of rock formation magnetization on geomagnetic anomalies at the current depth. This adapts to the dynamic characteristics of sudden changes in underground rock formation magnetization, ensures that the interference processing mechanism can adjust the weight according to changes in the geological environment, and enhances the ability to identify geomagnetic anomaly interference. Based on the formation magnetic anomaly weight factor and the current drill bit speed, the eddy current electromagnetic interference intensity is weighted and fused with the vector deviation to generate a magnetic interference intensity coefficient. This achieves dynamic fusion and adaptive compensation of interference sources, ensuring a coordinated and efficient interference processing mechanism.

[0015] Optionally, the comparing the corrected data with the verification data and judging the interference type based on the comparison result includes: calculating the Euclidean distance between the corrected data and the verification data on the gravitational acceleration component; calculating the cosine similarity between the corrected data and the verification data on the geomagnetic component; determining the mechanical vibration interference level based on the ratio of the Euclidean distance to a preset gravity mutation threshold; determining the electromagnetic pulse interference level based on the deviation between the cosine similarity and a preset geomagnetic interference threshold; and judging the interference type based on the mechanical vibration interference level and the electromagnetic pulse interference level.

[0016] This solution calculates the Euclidean distance between the correction data and the verification data on the gravity acceleration component, eliminating the problem of incorrectly smoothing data mutation points caused by filtering lag, ensuring timely detection of interference signs on the gravity component. The cosine similarity between the correction data and the verification data on the geomagnetic component is calculated, eliminating the problem of inability to timely identify anomalies and enhancing sensitivity to geomagnetic interference. The mechanical vibration interference level is determined based on the ratio of the Euclidean distance to a preset gravity mutation threshold. This difference in gravity acceleration is converted into an actionable interference intensity index, identifying the vibration effects caused by electromagnetic pulse interference, eliminating the lack of dynamic identification of interference types, and providing a quantitative basis for mechanical vibration interference in decision-making. The electromagnetic pulse interference level is determined based on the deviation of the cosine similarity from a preset geomagnetic interference threshold. This directional deviation of the geomagnetic component is converted into an actionable interference intensity index, identifying signal interruptions or packet loss caused by electromagnetic pulse interference in data transmission links, eliminating the problem of being unable to adaptively adjust transmission strategies for different interference sources, and providing a quantitative basis for electromagnetic pulse interference in decision-making. According to the mechanical vibration interference level and electromagnetic pulse interference level, the interference type is judged, the lack of coordination between data transmission and interference processing mechanism is eliminated, and the decision output in the closed-loop mechanism is formed to ensure the reliability and real-time performance of data transmission.

[0017] Optionally, determining the mechanical vibration interference level based on the ratio of the Euclidean distance to a preset gravity mutation threshold includes: normalizing the Euclidean distance to a unit speed vibration intensity coefficient based on the current drill bit speed; obtaining a drill collar vibration spectrum, analyzing the drill collar vibration spectrum, and determining spectrum characteristics; analyzing the vibration spectrum characteristics to determine the energy proportion of a preset frequency band; and determining the mechanical vibration interference level based on the product of the unit speed vibration intensity coefficient and the energy proportion.

[0018] This solution normalizes the Euclidean distance to the unit speed vibration intensity coefficient based on the current drill bit speed, eliminating the interference of drill bit speed changes on the vibration intensity assessment. The drill collar vibration spectrum is acquired and analyzed to determine the spectrum characteristics, revealing the frequency distribution characteristics of the vibration energy. The raw spectrum data is converted into a quantifiable feature set to support targeted frequency band analysis. The vibration spectrum characteristics are analyzed to determine the energy proportion of the preset frequency band, filter high-frequency noise and low-frequency drift, focus on the core interference frequency band, and improve the targetedness of the vibration interference assessment. The mechanical vibration interference level is determined based on the product of the unit speed vibration intensity coefficient and the energy proportion, avoiding the limitations of a single indicator and providing a decision-making basis for switching transmission strategies.

[0019] Optionally, the data transmission mode is switched according to the interference type, including: when the interference type is mechanical vibration interference, switching to the anti-vibration transmission mode: reducing the data transmission rate and increasing Hamming code error correction; when the interference type is electromagnetic pulse interference, switching to the frequency hopping transmission mode: adaptively selecting the transmission frequency according to the pulse period; when two types of interference exist at the same time, activating multi-modal mixed transmission: performing frequency hopping data packet burst transmission during the vibration interval.

[0020] Through this solution, when the interference type is mechanical vibration interference, it switches to the vibration-resistant transmission mode: the data transmission rate is reduced and Hamming code error correction is added, reducing the probability of signal distortion caused by mechanical vibration during data transmission, enhancing the identifiability of the signal in noise, and reducing the bit error rate; ensuring the integrity of the measurement data, avoiding the need for data packet retransmission due to vibration interference, and maintaining the reliability of data transmission. When the interference type is electromagnetic pulse interference, it switches to the frequency hopping transmission mode: the transmission frequency is adaptively selected according to the pulse period to ensure that the data transmission link maintains connection stability under pulse interference and reduce the bit error rate. When two types of interference exist at the same time, multi-mode hybrid transmission is activated: frequency hopping data packet burst transmission is performed during the vibration interval to avoid signal distortion caused by transmission during strong vibration periods; at the same time, electromagnetic pulse interference is avoided during the interval, maximizing data transmission efficiency and ensuring the complete delivery of data packets in a dual interference environment.

[0021] Optionally, the pressure drift calibration of the first corrected inclination data and the first corrected azimuth data is performed according to the current drilling fluid density to generate the corrected data, including: obtaining wellbore temperature data; analyzing the wellbore temperature data to determine the temperature gradient change; constructing a pressure-inclination mapping table according to the temperature gradient change and the current drilling fluid density; and performing pressure drift calibration on the first corrected inclination data and the first corrected azimuth data according to the pressure-inclination mapping table to generate the corrected data.

[0022] This solution captures wellbore temperature data, ensuring its availability and integrity. The wellbore temperature data is analyzed to determine temperature gradients and quantify the impact of temperature on pressure, ensuring accurate pressure estimates. A pressure-inclination mapping table is constructed based on temperature gradients and current drilling fluid density, enabling efficient retrieval and application of drift during the calibration process, reducing computational latency. Based on the pressure-inclination mapping table, pressure drift correction is performed on the first-corrected inclination and first-corrected azimuth data to generate corrected data. This ensures that the measured data is not affected by pressure drift and improves the real-time output reliability of the while-drilling inclinometer.

[0023] Optionally, the dynamic mutation threshold includes a gravity threshold and a geomagnetic threshold; detecting the corrected data and determining the data mutation value includes: determining the dynamic sampling window length according to the current drill bit speed; extracting the gravity acceleration component sequence and the geomagnetic component sequence in the corrected data within the dynamic sampling window length; calculating the absolute difference value of adjacent sampling points of the gravity acceleration component sequence and the vector angle change rate of adjacent sampling points of the geomagnetic component sequence; when the absolute difference value exceeds the gravity threshold, or the vector angle change rate exceeds the geomagnetic threshold, marking the current sampling point as a data mutation value.

[0024] This solution determines the dynamic sampling window length based on the current drill bit speed, ensuring that the mutation detection process can respond to changes in the drilling environment in real time and avoiding detection delays or omissions caused by fixed window lengths. Within the dynamic sampling window length, the gravity acceleration component sequence and geomagnetic component sequence in the corrected data are extracted to ensure that the analysis is based only on real-time measurement data within the current window, thereby eliminating interference from old data and improving the timeliness and pertinence of detection. The absolute difference value of adjacent sampling points in the gravity acceleration component sequence and the rate of change of the vector angle of adjacent sampling points in the geomagnetic component sequence are calculated, converting the raw data into comparable indicators, transforming mutation detection from qualitative to quantitative. When the absolute difference value exceeds the gravity threshold, or the rate of change of the vector angle exceeds the geomagnetic threshold, the current sampling point is marked as a data mutation value, reducing the impact of interference on data accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0026] Figure 1 A schematic diagram of an application scenario provided in one embodiment of the present application; Figure 2 A flowchart of a method for transmitting inclinometer data based on MWD is provided in one embodiment of the present application. DETAILED DESCRIPTION

[0027] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0028] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0029] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0030] In harsh environments with frequent interference, existing technologies usually rely solely on filtering algorithms to smooth the raw measurement data. However, the filtering lag effect can cause data mutation points to be incorrectly smoothed, making it impossible to identify anomalies in a timely manner and increasing the risk of wellbore trajectory deviation.

[0031] Based on this, this application provides a method for transmitting data from a while-drilling (WWD) inclinometer. The method acquires raw measurement data and positioning data from the WWD inclinometer, ensuring data availability and synchronization. The raw measurement data is corrected to generate corrected data, improving data accuracy and reducing noise. The corrected data is detected to determine the data mutation value, enabling real-time detection of data anomalies, providing a basis for triggering a retransmission mechanism and avoiding missing potential interference events. Based on positioning data, terrain data is acquired and analyzed to determine the topographic characteristics of the WWD location, enhancing the ability to detect different risks at the drilling location. Based on the terrain characteristics and positioning data, a dynamic mutation threshold is determined to optimize the sensitivity and accuracy of interference detection. The threshold is adaptively adjusted based on environmental changes to reduce false positives and missed negatives. When the correction data mutation value exceeds the dynamic mutation threshold, a Bluetooth retransmission command is sent to the inclinometer. Verification data from the retransmitted data is obtained, providing redundant verification points to ensure data integrity and reliability, preventing errors from a single data source from influencing decision-making. The correction data is compared with the verification data, and based on the comparison results, the interference type is determined, enabling classification and identification of the interference source, providing a basis for decision-making when switching modes. According to the interference type, the data transmission mode is switched to optimize the real-time performance and reliability of data transmission, and the anti-interference capability is adaptively enhanced for different interferences to ensure stable and efficient data flow.

[0032] Figure 1 This is a schematic diagram of an application scenario provided by this application. The method provided by this application is applied when transmitting data from a while-drilling inclinometer.

[0033] Specifically, the method provided in the present application is applied to any server, and the server interacts with the downhole inclinometer and the drilling system, and obtains the original measurement data in real time through the downhole inclinometer; at the same time, the positioning data is obtained through the drilling system. The original measurement data is corrected and processed to generate corrected data. The corrected data is detected and the data mutation value is determined. Based on the positioning data, the terrain data is obtained and analyzed to determine the terrain characteristics of the location of the downhole inclinometer. According to the terrain characteristics and positioning data, the dynamic mutation threshold is determined. When it is detected that the mutation value of the corrected data exceeds the dynamic mutation threshold, a Bluetooth retransmission instruction is sent to the inclinometer; and the verification data retransmitted by the inclinometer is obtained. The corrected data and the verification data are compared, and the interference type is judged according to the comparison results, and the interference source is classified and identified, providing a decision basis for mode switching. According to the interference type, the data transmission mode is switched to optimize the real-time and reliability of data transmission, and the anti-interference capability is adaptively enhanced for different interferences to ensure stable and efficient data flow. For specific implementation methods, please refer to the following embodiments.

[0034] Figure 2 This is a flow chart of a method for transmitting data of a while-drilling inclinometer based on MWD provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201, obtaining original measurement data and positioning data of a while-drilling inclinometer; The inclinometer while drilling can be the core component of the measurement while drilling (MWD) system, which is an instrument specifically used to measure the spatial posture of the wellbore (well inclination, azimuth, tool face angle).

[0035] The raw measurement data may be raw values output by a three-axis accelerometer and a three-axis magnetometer of a while-drilling inclinometer, including unprocessed measurement data of well inclination, azimuth, and tool face angle.

[0036] Positioning data can be the real-time location information of the well, including longitude, latitude and depth.

[0037] Specifically, the three-axis accelerometer and three-axis magnetometer of the while-drilling inclinometer are used to obtain raw measurement data in real time; at the same time, the real-time position coordinates (such as longitude, latitude and depth) are obtained through the drilling system as positioning data.

[0038] S202, correcting the original measurement data to generate corrected data; testing the corrected data to determine the data mutation value; The corrected data may be data generated after correcting the original measurement data.

[0039] The data mutation value can be the instantaneous change amplitude of the correction data at consecutive time points.

[0040] Specifically, data smoothing is performed on the original measurement data, dividing it into continuous time series groups according to fixed time windows. The average value of each data group is calculated (to remove high-frequency noise) to generate corrected data. The corrected data is then tested, and the absolute difference between the current corrected data and the corrected data at the previous time point (such as the difference in well inclination) is calculated as the data mutation value.

[0041] S203, based on the positioning data, acquiring and analyzing terrain data to determine the terrain characteristics of the location of the while drilling inclinometer; determining a dynamic mutation threshold based on the terrain characteristics and the positioning data; Topographic data can be information about the surface and underground characteristics of the drilling location, including rock type, hardness distribution, and historical geological disaster records.

[0042] Terrain characteristics can be specific location attributes derived from terrain data analysis, including areas of high magnetic interference, high vibration, etc.

[0043] The dynamic mutation threshold can be a critical value dynamically set based on terrain characteristics and positioning data to determine whether the data mutation value is significant.

[0044] Specifically, by accessing the preset geological database constructed based on geological surveys (storing historical geological information, such as rock type, magnetization distribution and interference history), positioning data is used to obtain and analyze terrain data, thereby determining the terrain characteristics of the location of the downhole inclinometer (such as magnetic field intensity distribution, rock hardness, historical geological disaster events, etc.). For example, in areas with uneven rock hardness, the terrain characteristics are determined to be high magnetic anomaly risks; in areas with stable sedimentary layers, the terrain characteristics are determined to be low interference areas.

[0045] Determine the dynamic mutation threshold based on terrain characteristics and positioning data. For example, set a lower mutation threshold in the magnetization anomaly area and increase the mutation threshold as the drilling depth increases.

[0046] S204, when it is detected that the mutation value of the correction data exceeds the dynamic mutation threshold, sending a Bluetooth retransmission instruction to the deflection drill; and obtaining verification data retransmitted by the deflection drill; The Bluetooth retransmission instruction may be an instruction sent via the Bluetooth protocol to request the while drilling inclinometer to retransmit the original measurement data at a specified time point. The verification data may be the original measurement data retransmitted by the while drilling inclinometer in response to the Bluetooth retransmission instruction.

[0047] Specifically, the correction data mutation value is compared with the dynamic mutation threshold in real time. If the correction data mutation value exceeds the dynamic mutation threshold, a Bluetooth retransmission instruction is sent to the LWD inclinometer via the Bluetooth protocol (only a single request is sent to avoid delay accumulation).

[0048] Then, the Bluetooth channel is monitored to obtain the verification data retransmitted by the while drilling inclinometer (the while drilling inclinometer immediately re-collects and sends data after receiving the command).

[0049] S205 , comparing the correction data with the verification data, and determining the interference type based on the comparison result; and switching the data transmission mode based on the interference type.

[0050] The comparison result can be the difference between the corrected data and the verified data. The interference type can be a classification of data transmission interference sources based on the comparison result and terrain characteristics, including random noise, geomagnetic anomaly interference, and electromagnetic pulse interference. The data transmission mode can be a configuration of the Bluetooth transmission strategy, including standard mode, data correction priority mode, and high-frequency retransmission mode.

[0051] Specifically, the consistency of the corrected data and the verification data is compared (the degree of agreement between the corrected data and the verification data at the same time), and the absolute difference between the two is calculated (such as the absolute difference in well inclination). The type of interference is determined based on the size of the absolute difference and the terrain characteristics. For example, if the absolute difference is small, the interference type is random noise; if the absolute difference is large and the terrain characteristics are high magnetic interference, the interference type is determined to be geomagnetic anomaly interference; if the absolute difference is large and the terrain characteristics are high vibration, the interference type is determined to be electromagnetic pulse interference.

[0052] Adjust the data transmission mode according to the interference type. For example, if the interference type is random noise, switch to standard mode (maintain the default grouping and retransmission interval); if the interference type is geomagnetic anomaly interference, switch to data correction priority mode (increase the smoothing filter intensity); if the interference type is electromagnetic pulse interference, switch to high-frequency retransmission mode (shorten the retransmission interval).

[0053] This solution corrects the original measurement data to generate corrected data, improving data accuracy and reducing the impact of noise. Corrected data is detected and the data mutation value is determined, enabling real-time detection of data anomalies. This provides a basis for triggering the retransmission mechanism and preventing potential interference events from being missed. Based on positioning data, terrain data is acquired and analyzed to determine the topographic characteristics of the location of the inclinometer, enhancing awareness of different risks at the drilling location. Based on the terrain characteristics and positioning data, a dynamic mutation threshold is determined to optimize the sensitivity and accuracy of interference detection. The threshold is adaptively adjusted according to environmental changes to reduce false positives and missed negatives. When the corrected data mutation value exceeds the dynamic mutation threshold, a Bluetooth retransmission command is sent to the inclinometer. Verification data from the retransmitted inclinometer is obtained, providing redundant verification points to ensure data integrity and reliability, preventing errors from a single data source from influencing decision-making. Corrected data is compared with verification data, and based on the comparison results, the interference type is determined, enabling classification and identification of interference sources, providing a basis for decision-making when switching modes. Data transmission mode is switched based on the interference type, optimizing the real-time and reliability of data transmission. Interference mitigation is adaptively enhanced to address different interference scenarios, ensuring a stable and efficient data flow.

[0054] In some embodiments, the positioning data is analyzed to determine the longitude and latitude coordinates and the altitude; based on the longitude and latitude coordinates and the altitude, the terrain undulation, rock hardness distribution and historical geological disaster records within a preset radius are extracted from a preset geological database; the terrain undulation, rock hardness distribution and historical geological disaster records are analyzed to determine the terrain stability level; the terrain stability level is determined as the terrain characteristics of the location where the downhole inclinometer is located.

[0055] Latitude and longitude coordinates can be geographic location identifiers obtained by parsing positioning data, including longitude and latitude values. Altitude can be a vertical position value obtained by parsing positioning data. The preset geological database can be a database that pre-stores geological environmental parameters such as terrain relief, rock hardness distribution, and historical geological disaster records, pre-stored on a server and retrieved when needed. The preset radius range can be a pre-defined fixed distance value used to limit the spatial range of the preset geological database query, pre-stored on a server and retrieved when needed. Terrain relief can be a quantitative parameter extracted from the preset geological database that represents the degree of change in surface slope within a preset radius. Rock hardness distribution can be a rock physical property parameter extracted from the preset geological database that represents a set of hardness values of rock layers within a preset radius. Historical geological disaster records can be disaster event logs extracted from the preset geological database, including the type, time, and impact range of geological disasters that occurred within a preset radius. The terrain stability level can be a qualitative rating result that quantifies the geological risk level of the current location.

[0056] Specifically, the positioning data is parsed, the latitude field is extracted, and converted into decimal format as the latitude value of the longitude and latitude coordinates; the longitude field is extracted and converted into decimal format as the longitude value of the longitude and latitude coordinates; and the altitude field is extracted as the altitude (the depth or height of the while drilling inclinometer relative to the sea level).

[0057] Based on the longitude and latitude coordinates and altitude, a spatial query statement is used to extract the terrain relief, rock hardness distribution and historical geological disaster records within a preset radius range set with the longitude and latitude coordinates as the center point (used to limit the spatial range of the preset geological database query) from the preset geological database.

[0058] Assess the terrain undulation and calculate the average slope value (the average inclination of all slope values within a preset radius, quantifying the terrain undulation); evaluate the rock hardness distribution and calculate the hardness variation coefficient (the variation of the rock hardness values within a preset radius, quantifying the uniformity of the rock hardness distribution); evaluate historical geological disaster records and check whether any events have occurred in the records; determine the terrain stability level based on the average slope value, hardness variation coefficient and event occurrence. For example, if the terrain undulation is high, the rock hardness distribution is low, and the frequency of historical geological disasters is high, the terrain stability level is set to low stability; if the terrain undulation is low, the rock hardness distribution is high, and the frequency of historical geological disasters is low, the terrain stability level is set to high stability.

[0059] The terrain stability level is directly assigned to the terrain characteristics of the location where the LWD inclinometer is located. For example, if the terrain stability level is unstable, the terrain characteristics are unstable.

[0060] This solution parses positioning data to determine latitude and longitude coordinates and altitude, ensuring accurate location information. This avoids deviations in terrain feature extraction due to coordinate errors and enables standardized conversion of positioning data from its original format to usable geographic coordinates. Based on the latitude and longitude coordinates and altitude, the terrain relief, rock hardness distribution, and historical geological disaster records within a preset radius are extracted from a preset geological database to avoid misjudgment of terrain features due to missing or inaccurate environmental information. The terrain relief, rock hardness distribution, and historical geological disaster records are analyzed to determine the terrain stability level, enabling a quantitative assessment of terrain features and ensuring that the assessment results are consistent and operational. The terrain stability level is determined as a terrain characteristic of the location of the while-drilling inclinometer, simplifying the representation of terrain features and converting complex geological analysis results into a single, easy-to-use variable to avoid redundant processing.

[0061] In some embodiments, the current drilling depth and the current drill bit speed are obtained; and according to the current drilling depth, the current drill bit speed and the terrain stability level, a dynamic mutation threshold is output through a threshold calculation model.

[0062] The current drilling depth may be a drilling depth value measured in real time during the drilling process, indicating the vertical depth of the drill bit or drilling tool from the ground surface. The current drill bit speed may be the drill bit rotation speed measured in real time during the drilling process. The threshold calculation model may be a predefined calculation module for calculating and outputting a dynamic mutation threshold.

[0063] Specifically, the current drilling depth and drill bit speed are obtained from the drilling system. These values, along with the terrain stability level, are input into the threshold calculation model. The threshold baseline (the initial value of the dynamic mutation threshold, used to determine the dynamic mutation threshold; for example, the greater the current drilling depth, the stricter the threshold). The threshold sensitivity (a parameter that measures the speed of response to data changes, used to determine the dynamic mutation threshold; for example, the higher the current drill bit speed, the lower the threshold to accommodate highly dynamic environments) is adjusted based on the current drill bit speed. The threshold weight (a weighting factor for the degree of threshold stability, used to determine the dynamic mutation threshold; for example, when the terrain stability level is low, the threshold setting is more conservative to address high risks) is adjusted based on the stability level. The dynamic mutation threshold is then determined based on the calculation results of the threshold calculation model.

[0064] This solution captures the current drilling depth and drill bit speed, ensuring that threshold calculations adapt to changes in drilling depth, improving the targeted nature of interference processing and avoiding the risk of data distortion due to increasing depth. Furthermore, it ensures that threshold calculations respond in real time to changes in the drilling tool's operating status, enhancing the real-time and reliability of data transmission. Based on the current drilling depth, drill bit speed, and terrain stability level, the threshold calculation model outputs dynamic mutation thresholds, improving data transmission coordination, reducing errors, and ensuring real-time performance.

[0065] In some embodiments, the three-axis accelerometer raw measurement values, the three-axis magnetometer raw measurement values and the real-time drill pipe orientation of the while drilling inclinometer are obtained; the geomagnetic declination reference value is extracted from the geomagnetic database according to the latitude and longitude coordinates; the magnetic interference intensity coefficient is determined according to the vector deviation between the three-axis magnetometer raw measurement value and the geomagnetic declination reference value; the raw measurement value is orthogonally decomposed and compensated according to the magnetic interference intensity coefficient and the drill pipe orientation to generate first corrected azimuth data; the three-axis accelerometer raw measurement value is inclination compensated according to the gravity acceleration model to generate first corrected inclination data; the drilling operation parameters are obtained, the drilling operation parameters are analyzed, and the current drilling fluid density is determined; the first corrected inclination data and the first corrected azimuth data are pressure drift calibrated according to the current drilling fluid density to generate corrected data.

[0066] The three-axis accelerometer raw measurement value may be unprocessed raw data obtained from a three-axis accelerometer sensor of a while-drilling inclinometer, including acceleration components of the x-axis, y-axis, and z-axis.

[0067] The three-axis magnetometer raw measurement value may be unprocessed raw data acquired from a three-axis magnetometer sensor of a while-drilling inclinometer, including magnetic field intensity components of the x-axis, the y-axis, and the z-axis.

[0068] The geomagnetic database may be a pre-stored database containing geomagnetic reference data for the entire region.

[0069] The geomagnetic declination reference value may be a standard reference value of geomagnetic declination representing different longitude and latitude positions extracted from a geomagnetic database.

[0070] The vector deviation can be the difference vector between the raw measurement value of the triaxial magnetometer and the reference value of the geomagnetic declination. The magnetic interference intensity coefficient can be a scalar value representing the current magnetic interference intensity level, determined based on the vector deviation. The drill rod orientation can be the spatial orientation data of the drill rod acquired in real time. The raw measurement value can be a combination of the raw measurement value of the triaxial accelerometer and the raw measurement value of the triaxial magnetometer.

[0071] The first corrected azimuth data may be corrected data generated by performing orthogonal decomposition compensation on original measurement values of the three-axis magnetometer.

[0072] The gravity acceleration model may be a predefined standard model used to calibrate raw measurement values of a triaxial accelerometer to eliminate tilt errors.

[0073] The first corrected inclination data may be corrected data generated by applying a gravity acceleration model to original measurement values of the triaxial accelerometer to perform inclination compensation.

[0074] The drilling operation parameters may be drilling operation data such as pump pressure, flow rate and temperature.

[0075] The current drilling fluid density may be a real-time value of the drilling fluid density obtained by analyzing drilling operation parameters.

[0076] Specifically, the three-axis accelerometer raw measurement values (i.e., acceleration data of the x-axis, y-axis, and z-axis) are obtained in real time from the three-axis accelerometer sensor of the while-drilling inclinometer. At the same time, the three-axis magnetometer raw measurement values (i.e., magnetic field intensity data of the x-axis, y-axis, and z-axis) are obtained from the three-axis magnetometer sensor of the while-drilling inclinometer. The real-time drill pipe orientation is obtained through the direction sensor on the drill bit.

[0077] Using longitude and latitude coordinates, the geomagnetic database constructed from geomagnetic measurement data at different longitude and latitude coordinates is retrieved (storing the mapping relationship between longitude and latitude coordinates and corresponding geomagnetic declination reference values). The corresponding geomagnetic declination reference value is extracted (the geomagnetic declination reference value is a scalar representing the standard geomagnetic field declination). Vector subtraction is performed on the raw measurement values of the three-axis magnetometer and the geomagnetic declination reference value to calculate the vector deviation between the two (indicating the strength and direction of the magnetic interference). The magnetic interference intensity coefficient is then determined based on the vector deviation.

[0078] Based on the magnetic interference intensity coefficient and the real-time drill pipe orientation, the original measurement values of the three-axis magnetometer are orthogonally decomposed (for example, the component parallel to the drill pipe orientation and the component perpendicular to the drill pipe orientation). Then, the compensation weight is adjusted according to the magnetic interference intensity coefficient (for example, the larger the magnetic interference intensity coefficient, the higher the compensation amplitude for the vertical component) to generate corrected magnetic field data. Based on the corrected magnetic field data, the azimuth (the azimuth angle of the wellbore) is calculated using the standard azimuth calculation formula to determine the first corrected azimuth data.

[0079] The original measurement values of the three-axis accelerometer are compared with the gravity acceleration model constructed based on the standard gravity acceleration reference value to determine the deviation vector (representing the deviation value of the original measurement values of the three-axis accelerometer and the gravity acceleration model on each axis component); and the inclination compensation formula is applied to compensate to obtain the corrected accelerometer data; then, based on the corrected accelerometer data, the standard inclination calculation formula is used to generate the first corrected inclination data.

[0080] Drilling operating parameters are obtained from the drilling control system. These parameters are parsed to extract the drilling fluid density field. This extracted drilling fluid density field is then used as the current drilling fluid density. Based on the current drilling fluid density, a preset drift correction factor, developed based on experimental data, is applied (for example, a higher current drilling fluid density results in a larger preset drift correction factor, indicating more significant drift compensation). Pressure drift correction (e.g., linear scaling or offset) is performed on the first corrected inclination data and the first corrected azimuth data, respectively, to compensate for measurement errors caused by drilling fluid pressure and generate corrected data.

[0081] This solution captures the raw measurements of the triaxial accelerometer and magnetometer, along with real-time drill pipe orientation, from the inclinometer while drilling (WWD). This ensures that corrections are made directly using unprocessed sensor information, avoiding correction interruptions due to missing data. A reference value for geomagnetic declination is extracted from the geomagnetic database based on longitude and latitude coordinates. The deviation of the magnetometer measurements from ideal geomagnetic conditions is quantified, providing a basis for magnetic interference detection. The magnetic interference intensity coefficient is determined based on the vector deviation between the raw triaxial magnetometer measurements and the reference value for geomagnetic declination. This quantifies the current level of magnetic interference and provides adjustment weights for orthogonal decomposition compensation, ensuring that interference intensity is incorporated into the compensation process. Orthogonal decomposition compensation is performed on the raw measurements based on the magnetic interference intensity coefficient and drill pipe orientation to generate first-corrected azimuth data, reducing errors caused by magnetic interference and improving azimuth accuracy. The raw triaxial accelerometer measurements are then inclination-compensated based on a gravity acceleration model to generate first-corrected inclination data, correcting for errors caused by deviations in the gravity acceleration model and improving wellbore inclination accuracy. Acquire and analyze drilling operating parameters to determine the current drilling fluid density, ensuring the calibration process is tailored to the specific drilling environment. Perform pressure drift correction on the first corrected inclination and first corrected azimuth data based on the current drilling fluid density to generate corrected data, eliminating drilling fluid density-related drift and improving overall measurement data reliability.

[0082] In some embodiments, the casing material parameters of the drill bit are obtained; the eddy current electromagnetic interference intensity is calculated based on the current drill bit speed and the casing material parameters; based on the current drilling depth, a preset rock formation magnetization distribution table is queried to determine the formation magnetic anomaly weight factor; based on the formation magnetic anomaly weight factor and the current drill bit speed, the eddy current electromagnetic interference intensity and the vector deviation are weightedly fused to generate a magnetic interference intensity coefficient.

[0083] A drill bit may be a tool used in drilling operations for drilling a wellbore. A casing material parameter may be a physical property of the drill tool casing material. Eddy current electromagnetic interference intensity may be a scalar value representing the level of electromagnetic interference caused by the drill tool magnetization interference. A preset formation magnetization distribution table may be a pre-stored structured database for real-time querying of formation magnetic anomaly weight factors, pre-stored on a server and accessed when needed. A formation magnetic anomaly weight factor may be a scalar coefficient representing the relative weight of formation magnetic anomaly interference at the current drilling depth.

[0084] Specifically, the drill bit's casing material parameters are read from a drill tool configuration database (which stores casing material parameters such as material type, magnetic permeability, and electrical conductivity) constructed based on the drill tool manufacturer's technical manual. The current drill bit speed is multiplied by the casing material parameters to determine the eddy current electromagnetic interference intensity (the level of electromagnetic interference caused by magnetization interference in the drill tool).

[0085] Based on the current drilling depth, the system searches for matching entries in a preset rock formation magnetization distribution table (a mapping between drilling depth and formation magnetic anomaly weight factors, used for real-time querying of formation magnetic anomaly weight factors) established based on geological exploration data. The formation magnetic anomaly weight factor is extracted. The vector deviation is weighted using the formation magnetic anomaly weight factor. Simultaneously, the eddy current electromagnetic interference intensity is weighted using the current drill bit speed. The weighted vector deviation and the weighted eddy current electromagnetic interference intensity are then integrated to generate the final magnetic interference intensity coefficient.

[0086] This solution obtains the drill bit's casing material parameters to specifically address the constant or slowly varying magnetic field interference caused by the eddy current effect of the drill pipe casing material. This ensures that the interference processing mechanism distinguishes material-related interference sources and lays a data foundation for calculating the eddy current electromagnetic interference intensity. Based on the current drill bit speed and casing material parameters, the eddy current electromagnetic interference intensity is calculated, quantifying the magnitude of the eddy current effect interference caused by drill tool rotation and characterizing the intensity of the drill tool magnetization interference. This effectively distinguishes drill tool-related interference from other interference sources and provides an independent interference index for weighted fusion, avoiding error accumulation caused by interference coupling. Based on the current drilling depth, a preset rock formation magnetization distribution table is queried to determine the formation magnetic anomaly weight factor. This dynamically assesses the influence of rock formation magnetization on geomagnetic anomalies at the current depth. This adapts to the dynamic characteristics of sudden changes in underground rock formation magnetization, ensures that the interference processing mechanism can adjust the weight according to changes in the geological environment, and enhances the ability to identify geomagnetic anomaly interference. Based on the formation magnetic anomaly weight factor and the current drill bit speed, the eddy current electromagnetic interference intensity is weighted and fused with the vector deviation to generate a magnetic interference intensity coefficient. This achieves dynamic fusion and adaptive compensation of interference sources, ensuring a coordinated and efficient interference processing mechanism.

[0087] In some embodiments, the Euclidean distance between the correction data and the verification data on the gravitational acceleration component is calculated; the cosine similarity between the correction data and the verification data on the geomagnetic component is calculated; the mechanical vibration interference level is determined based on the ratio of the Euclidean distance to a preset gravity mutation threshold; the electromagnetic pulse interference level is determined based on the deviation between the cosine similarity and a preset geomagnetic interference threshold; and the interference type is determined based on the mechanical vibration interference level and the electromagnetic pulse interference level.

[0088] The gravity acceleration component can be a gravity acceleration vector measured by a three-axis accelerometer in a while-drilling inclinometer, including component values for the X-axis, Y-axis, and Z-axis. The geomagnetic component can be a geomagnetic field intensity vector measured by a three-axis magnetometer in a while-drilling inclinometer, including component values for the X-axis, Y-axis, and Z-axis. Cosine similarity can be a measure of directional consistency between the geomagnetic components of the correction data and the geomagnetic components of the verification data. The preset gravity mutation threshold can be a preset parameter value representing the maximum allowable change in the gravity acceleration component, pre-stored in the server and retrieved when used. The mechanical vibration interference level can be a discrete indicator of interference severity determined based on a ratio, including three levels: low, medium, and high. The preset geomagnetic interference threshold can be a preset parameter value representing the minimum allowable directional similarity of the geomagnetic components, pre-stored in the server and retrieved when used. The deviation can be the absolute difference between the cosine similarity and the preset geomagnetic interference threshold when determining the electromagnetic pulse interference level. The electromagnetic pulse interference level can be a discrete indicator of interference severity determined based on the deviation degree, including low, medium and high levels.

[0089] Specifically, the gravity acceleration component vector (three-axis acceleration values, including the X-axis, Y-axis, and Z-axis component values, indicating the direction of gravity) is extracted from the correction data. At the same time, the gravity acceleration component vector (three-axis acceleration values, including the X-axis, Y-axis, and Z-axis component values, indicating the direction of gravity) is extracted from the verification data. For the gravity acceleration components, the difference between the correction data and the verification data is calculated axis by axis (i.e., the X-axis difference, the Y-axis difference, and the Z-axis difference). The squares of the differences are then summed and the square root is taken to obtain the Euclidean distance (indicating the magnitude of the vector difference between the two data in the direction of gravity).

[0090] Extract the geomagnetic component vector (three-axis magnetic values, including the X-axis, Y-axis, and Z-axis component values, indicating the direction of the geomagnetic field) from the correction data. Simultaneously, extract the geomagnetic component vector (three-axis magnetic values, including the X-axis, Y-axis, and Z-axis component values, indicating the direction of the geomagnetic field) from the verification data. For the geomagnetic components, calculate the dot product of the correction data and the verification data (that is, the sum of the X-axis product, the Y-axis product, and the Z-axis product). Then calculate the modulus of the correction data (the square root of the sum of the squares of the values on each axis) and the modulus of the verification data vector (the square root of the sum of the squares of the values on each axis). Finally, divide the dot product by the product of the two moduli to obtain the cosine similarity (indicating the vector direction similarity of the two data in the geomagnetic direction).

[0091] A preset gravity mutation threshold is set based on experimental calibration (indicating the maximum allowable variation of the gravity acceleration component, used to quantify the level of mechanical vibration interference); the ratio of the Euclidean distance to the preset gravity mutation threshold is calculated; and the mechanical vibration interference level is determined based on the size of the ratio.

[0092] A preset geomagnetic interference threshold is set based on the stability of the geomagnetic field (indicating the minimum allowable value of the similarity of the directions of the geomagnetic components, used to quantify the level of mechanical vibration interference); the ratio of the Euclidean distance to the preset geomagnetic interference threshold is calculated; and the mechanical vibration interference level is determined based on the size of the ratio.

[0093] The interference type is determined based on the mechanical vibration interference level and the electromagnetic pulse interference level. For example, when the mechanical vibration interference level is high and the electromagnetic pulse interference level is low, the interference type is determined to be mechanical vibration interference; when the mechanical vibration interference level is low and the electromagnetic pulse interference level is high, the interference type is determined to be electromagnetic pulse interference; when the mechanical vibration interference level is high and the electromagnetic pulse interference level is high, the interference type is determined to be composite interference (superposition of mechanical vibration and electromagnetic pulse); when the mechanical vibration interference level and the electromagnetic pulse interference level are both low or medium, the interference type is determined to be no significant interference.

[0094] This solution calculates the Euclidean distance between the correction data and the verification data on the gravity acceleration component, eliminating the problem of incorrectly smoothing data mutation points caused by filtering lag, ensuring timely detection of interference signs on the gravity component. The cosine similarity between the correction data and the verification data on the geomagnetic component is calculated, eliminating the problem of inability to timely identify anomalies and enhancing sensitivity to geomagnetic interference. The mechanical vibration interference level is determined based on the ratio of the Euclidean distance to a preset gravity mutation threshold. This difference in gravity acceleration is converted into an actionable interference intensity index, identifying the vibration effects caused by electromagnetic pulse interference, eliminating the lack of dynamic identification of interference types, and providing a quantitative basis for mechanical vibration interference in decision-making. The electromagnetic pulse interference level is determined based on the deviation of the cosine similarity from a preset geomagnetic interference threshold. This directional deviation of the geomagnetic component is converted into an actionable interference intensity index, identifying signal interruptions or packet loss caused by electromagnetic pulse interference in data transmission links, eliminating the problem of being unable to adaptively adjust transmission strategies for different interference sources, and providing a quantitative basis for electromagnetic pulse interference in decision-making. According to the mechanical vibration interference level and electromagnetic pulse interference level, the interference type is judged, the lack of coordination between data transmission and interference processing mechanism is eliminated, and the decision output in the closed-loop mechanism is formed to ensure the reliability and real-time performance of data transmission.

[0095] In some embodiments, the Euclidean distance is normalized to a unit speed vibration intensity coefficient based on the current drill bit speed; the drill collar vibration spectrum is obtained, the drill collar vibration spectrum is analyzed, and the spectrum characteristics are determined; the vibration spectrum characteristics are analyzed to determine the energy proportion of a preset frequency band; and the mechanical vibration interference level is determined based on the product of the unit speed vibration intensity coefficient and the energy proportion.

[0096] The unit speed vibration intensity coefficient can be a normalized vibration intensity index. The drill collar vibration spectrum can be a frequency domain representation of the drill collar vibration signal. The vibration spectrum characteristics can be characteristic parameters such as peak frequency, average energy, and bandwidth extracted from the drill collar vibration spectrum. The preset frequency band can be a pre-set frequency range of 1-200 Hz, pre-stored on a server and recalled when used. The energy proportion can be the ratio of the signal energy of the preset frequency band to the total signal energy.

[0097] Specifically, the Euclidean distance is normalized (eliminating the influence of rotational speed). The quotient of the normalized Euclidean distance and the current drill bit rotational speed is calculated to determine the vibration intensity coefficient per unit rotational speed. A vibration sensor installed on the drill collar collects the drill collar vibration signal. A fast Fourier transform is performed on the collected drill collar vibration signal to calculate the distribution of vibration energy in the frequency domain and generate a drill collar vibration spectrum. The peak frequency, average energy, and bandwidth are extracted from the drill collar vibration spectrum as spectral features.

[0098] According to the typical frequency band characteristics of mechanical vibration interference (the frequency range in which the mechanical vibration energy of the drill tool is concentrated), a preset frequency band is set (the main energy of the drill tool vibration is concentrated in the range of 1-200Hz); the spectrum characteristics within the preset frequency band are summed to obtain the signal energy; the total signal energy of the entire spectrum characteristics (full frequency range) is calculated; and the energy proportion of the preset frequency band is determined based on the quotient of the signal energy and the total signal energy.

[0099] The unit speed vibration intensity coefficient is multiplied by the energy proportion to obtain a comprehensive interference index; the comprehensive interference index is mapped to the mechanical vibration interference level according to a preset mapping rule pre-defined by the experimental data (a preset decision mechanism for mapping the comprehensive interference index to the mechanical vibration interference level).

[0100] This solution normalizes the Euclidean distance to the unit speed vibration intensity coefficient based on the current drill bit speed, eliminating the interference of drill bit speed changes on the vibration intensity assessment. The drill collar vibration spectrum is acquired and analyzed to determine the spectrum characteristics, revealing the frequency distribution characteristics of the vibration energy. The raw spectrum data is converted into a quantifiable feature set to support targeted frequency band analysis. The vibration spectrum characteristics are analyzed to determine the energy proportion of the preset frequency band, filter high-frequency noise and low-frequency drift, focus on the core interference frequency band, and improve the targetedness of the vibration interference assessment. The mechanical vibration interference level is determined based on the product of the unit speed vibration intensity coefficient and the energy proportion, avoiding the limitations of a single indicator and providing a decision-making basis for switching transmission strategies.

[0101] In some embodiments, when the interference type is mechanical vibration interference, switch to the anti-vibration transmission mode: reduce the data transmission rate and increase Hamming code error correction; when the interference type is electromagnetic pulse interference, switch to the frequency hopping transmission mode: adaptively select the transmission frequency according to the pulse period; when both interferences exist at the same time, activate multi-modal hybrid transmission: perform frequency hopping data packet burst transmission during the vibration interval.

[0102] Mechanical vibration interference can be physical vibrations generated by high-speed rotation of the drill tool or formation impact during drilling. Anti-vibration transmission mode can be a dedicated transmission mode activated to address mechanical vibration interference. Data transmission rate can be the amount of data sent over the Bluetooth link per unit time. Hamming code error correction can be the addition of redundant check bits to data packets, enabling the receiver to automatically detect and correct single-bit errors during transmission. Electromagnetic pulse interference can be transient electromagnetic noise generated by equipment such as the drilling rig motor. Frequency hopping transmission mode can be a transmission mode activated to address electromagnetic pulse interference. The pulse period can be the repetition time interval of the electromagnetic pulse interference signal. The transmission frequency can be a specific frequency channel available in Bluetooth communication. Multimodal hybrid transmission can be a composite transmission mode that addresses both mechanical vibration and electromagnetic pulse interference. The vibration pause period can be a brief window of time during which the mechanical vibration intensity is below a preset threshold.

[0103] Specifically, when the interference type is mechanical vibration, the data transmission mode is switched to vibration-resistant transmission mode: the configuration parameters of the data transmission link (Bluetooth) are adjusted to reduce the data transmission rate; Hamming code calculations are performed during the data encoding phase to generate new data packets containing error correction bits; at the receiving end, a Hamming code decoder automatically detects and corrects single-bit errors during transmission (such as signal distortion caused by vibration). When the interference type is electromagnetic pulse interference, the data transmission mode is switched to frequency hopping transmission mode: the electromagnetic pulse period is monitored (such as the time interval of the pulse signal captured by the electromagnetic sensor) to obtain the pulse period (the time interval between two adjacent peaks of the electromagnetic pulse interference signal); based on the pulse period, a frequency with minimal interference is selected from the available frequency points of the data transmission link (a set of multiple optional communication channels in the 2.4GHz frequency band for the data transmission link (Bluetooth), each channel corresponding to an independent frequency point), avoiding the period of high pulse frequency occurrence; and the transmission frequency configuration is updated through the frequency switching module.

[0104] When two types of interference exist at the same time, the activated data transmission mode is multimodal mixed transmission: when the comprehensive interference index is lower than the preset threshold set according to the average vibration intensity during the stable drilling period (the trigger condition for activating multimodal mixed transmission), it is determined to be a vibration pause period (i.e., a period of low vibration intensity); during the vibration pause period, the adaptive frequency selection mechanism (the algorithm module for the optimal transmission frequency) is used to perform frequency hopping data packet burst transmission.

[0105] Through this solution, when the interference type is mechanical vibration interference, it switches to the vibration-resistant transmission mode: the data transmission rate is reduced and Hamming code error correction is added, reducing the probability of signal distortion caused by mechanical vibration during data transmission, enhancing the identifiability of the signal in noise, and reducing the bit error rate; ensuring the integrity of the measurement data, avoiding the need for data packet retransmission due to vibration interference, and maintaining the reliability of data transmission. When the interference type is electromagnetic pulse interference, it switches to the frequency hopping transmission mode: the transmission frequency is adaptively selected according to the pulse period to ensure that the data transmission link maintains connection stability under pulse interference and reduce the bit error rate. When two types of interference exist at the same time, multi-mode hybrid transmission is activated: frequency hopping data packet burst transmission is performed during the vibration interval to avoid signal distortion caused by transmission during strong vibration periods; at the same time, electromagnetic pulse interference is avoided during the interval, maximizing data transmission efficiency and ensuring the complete delivery of data packets in a dual interference environment.

[0106] In some embodiments, wellbore temperature data is obtained; the wellbore temperature data is analyzed to determine the temperature gradient change; a pressure-inclination mapping table is constructed based on the temperature gradient change and the current drilling fluid density; and based on the pressure-inclination mapping table, the first corrected inclination data and the first corrected azimuth data are pressure drift calibrated to generate corrected data.

[0107] Wellbore temperature data can be a collection of raw temperature measurements collected in real time by a temperature sensor within the wellbore environment. Temperature gradient change can be the calculated rate of temperature change per unit depth along the wellbore depth. The pressure-inclination mapping table can be a two-dimensional lookup table that correlates pressure conditions with wellbore inclination measurement drift.

[0108] Specifically, temperature sensors installed on the drill string collect real-time wellbore temperature data at different depths. The wellbore temperature data is sorted by well depth (obtained by drill pipe length). A differential algorithm is used to calculate the temperature change rate (temperature change per unit depth) of adjacent data points. Based on the temperature change rate, the temperature gradient is determined. The temperature gradient change is converted into an equivalent pressure change (the higher the temperature gradient, the greater the equivalent pressure change). The pressure value is then calculated based on the current drilling fluid density (quantifying the combined pressure of the drilling fluid weight and temperature). A pressure-inclination mapping table is constructed, using the pressure value as the row index and the well inclination offset (the drift of the well inclination at different pressures) as the column index.

[0109] Based on the pressure value, the closest pressure value entry in the pressure-inclination mapping table is queried, and the corresponding inclination drift calibration value (the expected drift of the well inclination angle, with a positive value indicating positive drift and a negative value indicating negative drift) is extracted. The inclination drift calibration value is subtracted or added to the first corrected inclination data (the addition and subtraction operation is determined based on the drift direction) to generate the calibrated well inclination data.

[0110] Based on the pressure value, the closest pressure value entry in the pressure-inclination mapping table is searched and the corresponding azimuth drift calibration value (the expected azimuth drift, with a positive value indicating positive drift and a negative value indicating negative drift) is extracted. The azimuth drift calibration value is subtracted or added to the first corrected azimuth data (the addition and subtraction operation is determined by the drift direction) to generate the calibrated azimuth data. The calibrated inclination data is combined with the azimuth data to generate the corrected data.

[0111] This solution captures wellbore temperature data, ensuring its availability and integrity. The wellbore temperature data is analyzed to determine temperature gradients and quantify the impact of temperature on pressure, ensuring accurate pressure estimates. A pressure-inclination mapping table is constructed based on temperature gradients and current drilling fluid density, enabling efficient retrieval and application of drift during the calibration process, reducing computational latency. Based on the pressure-inclination mapping table, pressure drift correction is performed on the first-corrected inclination and first-corrected azimuth data to generate corrected data. This ensures that the measured data is not affected by pressure drift and improves the real-time output reliability of the while-drilling inclinometer.

[0112] In some embodiments, the length of the dynamic sampling window is determined based on the current drill bit speed; within the dynamic sampling window length, the gravity acceleration component sequence and the geomagnetic component sequence in the corrected data are extracted; the absolute difference value of adjacent sampling points of the gravity acceleration component sequence and the vector angle change rate of adjacent sampling points of the geomagnetic component sequence are calculated; when the absolute difference value exceeds the gravity threshold, or the vector angle change rate exceeds the geomagnetic threshold, the current sampling point is marked as a data mutation value.

[0113] The dynamic sampling window length can be a range of sampling points dynamically determined based on the current drill bit speed. The gravity acceleration component sequence can be a sequence of gravity acceleration component values within the dynamic sampling window length. The geomagnetic component sequence can be a sequence of geomagnetic component values within the dynamic sampling window length. Adjacent sampling points can be two temporally consecutive sampling points in the gravity acceleration component sequence or the geomagnetic component sequence. The absolute value of the difference can be the absolute value of the difference between the values of each component between adjacent sampling points in the gravity acceleration component sequence. The vector angle change rate can be the rate of angular change of the geomagnetic vector direction between adjacent sampling points in the geomagnetic component sequence. The gravity threshold can be a preset scalar threshold used to determine whether the absolute value of the gravity difference is abnormal. The geomagnetic threshold can be a preset scalar threshold used to determine whether the rate of change of the geomagnetic vector angle is abnormal. The current sampling point can be the next adjacent point when calculating the absolute value of the difference or the rate of change of the vector angle.

[0114] Specifically, according to the current drill bit speed, the dynamic sampling window length is set (the sampling window length is inversely proportional to the drill bit speed) through a predefined mapping rule calibrated by experiments (a table storing the correspondence between the drill bit speed and the dynamic sampling window length). For example, when the drill bit speed is high, the sampling window length is shortened to adapt to rapid changes; when the drill bit speed is low, the sampling window length is extended to cover a longer time period.

[0115] Based on the dynamic sampling window length, extract the gravity acceleration component sequence within the corresponding time range from the corrected data. Simultaneously, within the same dynamic sampling window length, extract the geomagnetic component sequence from the corrected data. Traverse each sampling point in the gravity acceleration component sequence (starting with the second sampling point). For each sampling point, calculate the difference between it and the adjacent sampling point. Then, take the absolute value of this difference as the absolute value of the difference. Traverse each sampling point in the geomagnetic component sequence (starting with the second sampling point). For each sampling point, calculate the rate of change of the vector angle between it and the adjacent sampling point. Traverse the sequence of absolute difference values and the sequence of vector angle change rates; compare the absolute difference values with the gravity threshold set based on the normal fluctuation range of gravity acceleration (the reasonable change range of the absolute difference values between adjacent sampling points) (used to determine whether the absolute difference value of gravity is abnormal); at the same time, compare the vector angle change rate with the geomagnetic threshold set based on the normal change rate range of the geomagnetic component sequence (the reasonable change range of the vector angle change rate between adjacent sampling points) (used to determine whether the geomagnetic vector angle change rate is abnormal); if the absolute difference value exceeds the gravity threshold, or the vector angle change rate exceeds the geomagnetic threshold, mark the current sampling point as a data mutation value.

[0116] This solution determines the dynamic sampling window length based on the current drill bit speed, ensuring that the mutation detection process can respond to changes in the drilling environment in real time and avoiding detection delays or omissions caused by fixed window lengths. Within the dynamic sampling window length, the gravity acceleration component sequence and geomagnetic component sequence in the corrected data are extracted to ensure that the analysis is based only on real-time measurement data within the current window, thereby eliminating interference from old data and improving the timeliness and pertinence of detection. The absolute difference value of adjacent sampling points in the gravity acceleration component sequence and the rate of change of the vector angle of adjacent sampling points in the geomagnetic component sequence are calculated, converting the raw data into comparable indicators, transforming mutation detection from qualitative to quantitative. When the absolute difference value exceeds the gravity threshold, or the rate of change of the vector angle exceeds the geomagnetic threshold, the current sampling point is marked as a data mutation value, reducing the impact of interference on data accuracy.

Claims

1. A method for transmitting data of a while drilling inclinometer based on MWD, characterized in that: include: Obtaining original measurement data and positioning data of the while drilling inclinometer; performing correction processing on the original measurement data to generate corrected data; Detecting the corrected data to determine a data mutation value; Based on the positioning data, acquiring and analyzing terrain data to determine the terrain characteristics of the location of the while drilling inclinometer; determining a dynamic mutation threshold value based on the terrain characteristics and the positioning data; When it is detected that the correction data mutation value exceeds the dynamic mutation threshold, a Bluetooth retransmission instruction is sent to the deflection drill; and verification data retransmitted by the deflection drill is obtained; The correction data is compared with the verification data, and the interference type is determined according to the comparison result; and the data transmission mode is switched according to the interference type.

2. The method according to claim 1, characterized in that The analyzing the terrain data to determine the terrain characteristics of the location of the while drilling inclinometer includes: Analyzing the positioning data to determine the latitude and longitude coordinates and altitude; Extracting terrain relief, rock hardness distribution, and historical geological disaster records within a preset radius from a preset geological database based on the latitude and longitude coordinates and the altitude; Analyze the terrain relief, the rock hardness distribution, and the historical geological disaster records to determine the terrain stability level; The terrain stability level is determined as a characteristic of the terrain at the location of the inclinometer.

3. The method according to claim 2, characterized in that Determining the dynamic mutation threshold according to the terrain characteristics and the positioning data includes: Get the current drilling depth and current drill bit speed; According to the current drilling depth, the current drill bit speed and the terrain stability level, a dynamic mutation threshold is outputted through a threshold calculation model.

4. The method according to claim 3, characterized in that The correcting the original measurement data to generate corrected data includes: Obtain the original measurement values of the three-axis accelerometer and three-axis magnetometer of the while-drilling inclinometer and the real-time drill pipe orientation; Extracting a geomagnetic declination reference value from a geomagnetic database according to the latitude and longitude coordinates; Determining a magnetic interference intensity coefficient based on a vector deviation between an original measurement value of the three-axis magnetometer and a reference value of the geomagnetic declination; Performing orthogonal decomposition compensation on the original measurement value according to the magnetic interference intensity coefficient and the drill pipe orientation to generate first corrected azimuth data; Performing tilt compensation on the original measurement value of the triaxial accelerometer according to the gravity acceleration model to generate first corrected tilt data; Acquiring drilling operation parameters, analyzing the drilling operation parameters, and determining current drilling fluid density; The first corrected inclination data and the first corrected azimuth data are calibrated for pressure drift according to the current drilling fluid density to generate corrected data.

5. The method according to claim 4, characterized in that Determining the magnetic interference intensity coefficient according to the vector deviation between the original measurement value of the three-axis magnetometer and the reference value of the geomagnetic declination includes: Get the casing material parameters of the drill bit; Calculating eddy current electromagnetic interference intensity according to the current drill bit speed and the casing material parameters; According to the current drilling depth, querying a preset rock formation magnetization distribution table to determine a formation magnetic anomaly weight factor; Based on the formation magnetic anomaly weight factor and the current drill bit speed, the eddy current electromagnetic interference intensity and the vector deviation are weighted and fused to generate a magnetic interference intensity coefficient.

6. The method according to claim 3, characterized in that The comparing the correction data with the verification data and determining the interference type according to the comparison result includes: Calculating the Euclidean distance between the correction data and the verification data on the gravitational acceleration component; Calculating the cosine similarity between the correction data and the verification data in the geomagnetic component; determining a mechanical vibration interference level according to a ratio of the Euclidean distance to a preset gravity mutation threshold; Determining an electromagnetic pulse interference level based on a deviation between the cosine similarity and a preset geomagnetic interference threshold; The interference type is determined according to the mechanical vibration interference level and the electromagnetic pulse interference level.

7. The method according to claim 6, characterized in that Determining the mechanical vibration interference level according to the ratio of the Euclidean distance to a preset gravity mutation threshold includes: Normalizing the Euclidean distance to a unit speed vibration intensity coefficient according to the current drill bit speed; Acquiring a drill collar vibration spectrum, analyzing the drill collar vibration spectrum, and determining spectrum characteristics; Analyze the vibration spectrum characteristics and determine the energy proportion of the preset frequency band; The mechanical vibration interference level is determined according to the product of the unit speed vibration intensity coefficient and the energy proportion.

8. The method according to claim 6, characterized in that The switching of the data transmission mode according to the interference type includes: When the interference type is mechanical vibration interference, switch to anti-vibration transmission mode: reduce the data transmission rate and increase Hamming code error correction; When the interference type is electromagnetic pulse interference, switch to frequency hopping transmission mode: adaptively select the transmission frequency according to the pulse period; When two interferences exist simultaneously, multi-mode hybrid transmission is activated: frequency hopping data packet burst transmission is performed during the vibration pause period.

9. The method according to claim 4, characterized in that The step of performing pressure drift calibration on the first corrected inclination data and the first corrected azimuth data according to the current drilling fluid density to generate corrected data includes: Acquiring wellbore temperature data; analyzing the wellbore temperature data to determine temperature gradient changes; constructing a pressure-inclination mapping table according to the temperature gradient change and the current drilling fluid density; According to the pressure-tilt mapping table, pressure drift calibration is performed on the first corrected tilt data and the first corrected azimuth data to generate corrected data.

10. The method according to claim 4, characterized in that The dynamic mutation threshold includes a gravity threshold and a geomagnetic threshold; and detecting the correction data to determine the data mutation value includes: Determining a dynamic sampling window length according to the current drill bit speed; Extracting the gravitational acceleration component sequence and the geomagnetic component sequence in the correction data within the dynamic sampling window length; Calculating the absolute difference values of adjacent sampling points of the gravity acceleration component sequence and the rate of change of the vector angle of adjacent sampling points of the geomagnetic component sequence; When the absolute value of the difference exceeds the gravity threshold, or the rate of change of the vector angle exceeds the geomagnetic threshold, the current sampling point is marked as a data mutation value.

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