Oilfield underground multi-parameter wireless monitoring and signal compensation method, system and equipment and storage medium

Abstract

The invention discloses an oil field underground multi-parameter wireless monitoring and signal compensation method, system and device and a storage medium, and relates to the technical field of oil field exploitation, and the method comprises the steps: collecting working condition parameters through an underground multi-parameter sensor, and carrying out the signal conditioning and analog-to-digital conversion; performing noise suppression and normalization processing on the working condition parameters based on frequency domain analysis and adaptive filtering, constructing a data frame with a timestamp, and inserting a pilot frequency sequence to perform coded modulation transmission; and completing phase and frequency offset estimation at a ground receiving end by using a pilot frequency sequence, executing I / Q imbalance compensation and signal correction, recovering multi-parameter monitoring data, and performing threshold judgment and alarm. According to the method, noise is suppressed through frequency domain analysis and adaptive filtering, a pilot frequency coding frame is constructed for wireless transmission, phase and frequency offset estimation and I / Q imbalance compensation are completed at a ground receiving end, real monitoring data are recovered, threshold alarm is triggered, and the precision, stability and safety of oil well monitoring are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oilfield exploitation, in particular to an oilfield downhole multi-parameter wireless monitoring and signal compensation method, system, device and storage medium. BACKGROUND

[0002] In the process of oilfield exploitation, downhole pressure, temperature, flow and other parameters are crucial to the production efficiency and safety of oil wells. Real-time and accurate monitoring of these parameters can help operators judge well conditions, control production and prevent safety accidents in a timely manner.

[0003] Traditional downhole monitoring equipment in oilfields relies on wired transmission, but wired systems are complex to install, require laying a large number of cables, and need to be shut down for maintenance, resulting in high costs. In addition, wired monitoring systems are prone to physical damage in harsh environments such as high temperature and high pressure, affecting the stability of signal transmission and even causing monitoring to be interrupted.

[0004] Wireless monitoring technology has been gradually applied in oilfield development in recent years, but existing wireless systems still have limitations in multi-parameter acquisition and real-time performance, especially in high-temperature and high-pressure oilfield environments. The stability and data accuracy of the system need to be further improved. SUMMARY

[0005] In view of the above problems, the present application is proposed.

[0006] Therefore, the technical problem solved by the present application is that the existing downhole monitoring method for oilfields relies on wired transmission of monitoring equipment, the wired system is complex to install, requires laying a large number of cables, and needs to be shut down for maintenance, resulting in high costs, and the wired monitoring system has poor stability.

[0007] To solve the above technical problems, the present application provides the following technical scheme: An oilfield downhole multi-parameter wireless monitoring and signal compensation method, comprising relying on a downhole multi-parameter sensor, collecting working condition parameters, and performing signal conditioning and analog-to-digital conversion; based on frequency domain analysis and adaptive filtering, noise suppression and normalization processing are performed on the working condition parameters, a data frame with a time stamp is constructed, and a pilot sequence is inserted for encoding modulation transmission; at the ground receiving end, the pilot sequence is used to complete phase and frequency offset estimation, I / Q imbalance compensation and signal correction are performed, multi-parameter monitoring data are recovered and threshold judgment and alarm are performed; noise suppression includes low-frequency drift detection based on a sliding window and dynamic noise reduction using an adaptive filter; phase and frequency offset estimation includes obtaining phase drift and frequency offset based on correlation operation of pilot symbols; I / Q imbalance compensation includes constructing a phase deviation matrix and performing inverse matrix correction on the received in-phase and quadrature signals.

[0008] As a preferred scheme of the oilfield downhole multi-parameter wireless monitoring and signal compensation method, the noise suppression comprises frequency domain interference identification by using fast Fourier transform, and dynamic elimination of low frequency drift and power frequency interference based on a minimum mean square error adaptive filtering algorithm.

[0009] As a preferred scheme of the oilfield downhole multi-parameter wireless monitoring and signal compensation method, the data frame comprises a frame header, a pilot sequence, a service load and a cyclic redundancy check code; wherein the frame header contains time stamp, well number, depth section and device number identification information.

[0010] As a preferred scheme of the oilfield downhole multi-parameter wireless monitoring and signal compensation method, the encoding modulation comprises one of frequency shift keying, phase shift keying or spread spectrum modulation, and channel encoding in combination with BCH code or low density parity check code.

[0011] As a preferred scheme of the oilfield downhole multi-parameter wireless monitoring and signal compensation method, the phase and frequency offset estimation comprises outputting average phase drift and frequency offset based on the pilot sequence, and correcting at the receiving end by using a local phase-locked loop.

[0012] As a preferred scheme of the oilfield downhole multi-parameter wireless monitoring and signal compensation method, the I / Q imbalance compensation comprises establishing a phase deviation matrix, and performing inverse matrix transformation on the in-phase component and the quadrature component to obtain the corrected signal.

[0013] As a preferred scheme of the oilfield downhole multi-parameter wireless monitoring and signal compensation method, the threshold determination comprises a fixed threshold mode and an adaptive threshold mode; the adaptive threshold mode calculates the mean and standard deviation of the measured value by using a sliding window, and dynamically updates the threshold based on the quantile method.

[0014] Another object of the present application is to provide an oilfield downhole multi-parameter wireless monitoring and signal compensation system, which can complete phase and frequency offset estimation, perform I / Q imbalance compensation and signal correction, restore multi-parameter monitoring data and perform threshold determination and alarm by using a pilot sequence at a ground receiving end; and solve the problem of poor transmission stability in the current oilfield downhole monitoring method.

[0015] As a preferred scheme of the oilfield downhole multi-parameter wireless monitoring and signal compensation system, wherein: comprising a downhole multi-parameter acquisition and signal conditioning module, a noise suppression and wireless coding transmission module, and a receiving end compensation and alarm determination module; the downhole multi-parameter acquisition and signal conditioning module is used for collecting working condition parameters relying on downhole sensors, generating original digital signals after signal conditioning and analog-to-digital conversion; the noise suppression and wireless coding transmission module is used for frequency domain analysis and adaptive filtering of collected data, noise suppression and normalization, construction of a data frame with a time stamp, insertion of a pilot sequence and execution of coding modulation, and transmission to the ground through a wireless link; and the receiving end compensation and alarm determination module is used for phase and frequency offset estimation by the ground receiving end using the pilot sequence, I / Q imbalance compensation and signal correction, recovery of multi-parameter data, threshold determination and alarm processing

[0016] A computer device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the steps of the oilfield downhole multi-parameter wireless monitoring and signal compensation method.

[0017] A computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the oilfield downhole multi-parameter wireless monitoring and signal compensation method.

[0018] The oilfield downhole multi-parameter wireless monitoring and signal compensation method provided by the present application realizes real-time acquisition and high-precision digital processing of key working condition parameters such as temperature, pressure, flow rate and water cut by relying on downhole multi-parameter sensors and combining signal conditioning and analog-to-digital conversion, to ensure that reliable original monitoring data can still be obtained under high temperature and high pressure and strong interference environment downhole; through frequency domain analysis and adaptive filtering based noise suppression and normalization of working condition parameters, and construction of a data frame with a time stamp inserted with a pilot sequence for coding modulation transmission, dynamic suppression of time-varying noise and power frequency interference and robust transmission of wellbore long-distance attenuation channels are realized, to ensure the real-time and stability of data transmission between downhole and ground; through phase and frequency offset estimation by the ground receiving end using the pilot sequence, I / Q imbalance compensation and signal correction, effective correction of frequency offset, phase drift and hardware non-ideal error introduced by the transmission link is realized, to recover multi-parameter monitoring data consistent with the actual downhole, and trigger local and remote alarms based on threshold determination, to realize rapid early warning under abnormal working conditions. The present application significantly improves the accuracy, real-time and safety of oil well multi-parameter wireless monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0020] Figure 1 A whole flow chart of an oilfield downhole multi-parameter wireless monitoring and signal compensation method provided for Embodiment 1 of the present application. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned objects, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings in the specification. Obviously, the described embodiments are only some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort should belong to the protection scope of the present application.

[0022] Embodiment 1, refer to Figure 1 For an embodiment of the present application, an oilfield downhole multi-parameter wireless monitoring and signal compensation method is provided, comprising:

[0023] S1: Collecting working condition parameters by relying on a downhole multi-parameter sensor, and performing signal conditioning and analog-digital conversion.

[0024] Furthermore, a multi-parameter sensor group is arranged in the oil well downhole tool string for real-time collection of various working condition parameters such as oil temperature, oil pressure, flow rate and water cut. The temperature sensor adopts a platinum resistance or a thermosensitive element suitable for high-temperature environment, with a measurement range of -20℃ to 175℃; the pressure sensor selects a silicon piezoresistance or a quartz resonant pressure sensor, with a measurement range of 0 to 140MPa, and has an isolation diaphragm and a corrosion-resistant package; the flow sensor can be selected according to the well type, with a differential pressure type, ultrasonic type or pulse counting type structure; the water cut sensor adopts a capacitance method or a conductivity method probe, which reflects the water cut ratio by measuring the dielectric constant or conductivity. The sensor probe and the electronic cabin are connected through high-temperature sealing lead wires, with corrosion-resistant metal and high-reliability sealing structure, to ensure long-term stable operation in high-temperature high-pressure and corrosive downhole environment.

[0025] It should be noted that the analog output of each sensor is first amplified, filtered, temperature compensated and zero drift corrected by the front-end signal conditioning circuit. Among them, the temperature signal is processed by constant current source excitation and high precision instrument amplifier; the pressure signal adopts bridge measurement combined with programmable gain amplifier, and an anti-aliasing filter is set before entering the analog-to-digital converter; the flow signal is processed according to the sensor type, the acoustic arrival time difference is calculated or the pulse is shaped; the moisture content signal adopts AC excitation and capacitance-voltage conversion in the capacitance method, and AC excitation is combined with homophase rectification to avoid polarization effect in the conductance method.

[0026] It should also be noted that the conditioned signal is sent to a multi-channel analog-to-digital conversion module with a resolution of not less than 16 bits, the sampling rate is set in the range of 100Hz to 500Hz, and the sampling of each channel adopts a hardware synchronous trigger mode to ensure the time alignment of multiple parameters. The sampling data is bound with a high-precision time stamp at the same time to ensure the time consistency of the data.

[0027] Before the device is shipped, all sensors are factory calibrated. The temperature sensor measures multiple temperature points to establish a polynomial or lookup table relationship between the original resistance value and the actual temperature; the pressure sensor collects data under multiple temperature and pressure conditions to fit the pressure calculation formula containing the temperature cross compensation term; the flow sensor is calibrated by a standard flow source to obtain the discharge coefficient and installation correction coefficient; the moisture content sensor measures the capacitance or conductance value under the condition of known water-oil ratio to establish a fitting model. The coefficients obtained by calibration are written into the read-only memory of the device for real-time calculation during operation.

[0028] After the device is run downhole, secondary calibration can be performed according to the field conditions to correct the zero point and gain deviation caused by sensor aging or environmental changes. The secondary calibration is performed under shutdown or stable conditions, and the zero point and gain parameters are adjusted by comparing with the standard instrument at the wellhead or the test data to ensure the measurement accuracy.

[0029] During data acquisition, the system also compensates for the temperature drift of the sampling clock according to the real-time temperature of the downhole electronic cabin to ensure the accuracy of the time stamp. At the same time, the system performs self-checking on the sensor state to monitor abnormalities such as broken wire, short circuit, excessive range, drift overrun, etc., and adds a quality flag bit to the data to provide a basis for subsequent data processing and abnormal rejection.

[0030] S2: Based on frequency domain analysis and adaptive filtering, the working condition parameters are subjected to noise suppression and normalization processing, a data frame with time stamp is constructed, and a pilot sequence is inserted for encoding modulation transmission.

[0031] Furthermore, the collected raw data such as temperature, pressure, flow rate, and moisture content are input into the digital signal processing module in chronological order. The processing module has a built-in frequency domain interference identification mechanism. It analyzes the signal's spectral distribution within the range of 0Hz to half the sampling frequency using Fast Fourier Transform (FFT) to detect the presence of distinctive interference peaks. For example, 50Hz or 60Hz power frequency interference, low-frequency components of 1–5Hz caused by fluid pulsation, and broadband spectral lines corresponding to high-frequency spikes are all identified as interference frequency bands. The frequency domain identification results are used as the mask input for subsequent filtering.

[0032] It should be noted that the system employs an adaptive filtering algorithm for dynamic noise reduction in the time domain. The adaptive filter can be selected from the Least Mean Square Error (LMS), Recursive Least Squares (RLS), or Kalman filter depending on the operating conditions. When downhole noise characteristics change rapidly, the RLS algorithm with faster convergence speed is selected; when noise characteristics are stable and computational resource requirements are low, the LMS algorithm is selected; and when it is necessary to simultaneously model state variables and noise characteristics, the Kalman filter is selected. Filtering parameters such as step size μ and filter order N are automatically set according to the operating conditions, with μ typically ranging from 10. -4 Up to 10 -3 The filter order N is between 128 and 256 to ensure a balance between the filter convergence speed and the signal fidelity.

[0033] It should also be noted that during the filtering process, the system dynamically optimizes the filter weight adjustment strategy based on the frequency domain identification results. For example, it uses a high-order high-pass filter strategy for low-frequency drift, a notch filter for narrowband power frequency interference, and a sliding window mid-range filter for impulse noise in the time domain. During this process, the filtering module also monitors changes in the signal-to-noise ratio (SNR) of the output signal. When it detects that the filtering has caused signal attenuation exceeding a set threshold, it automatically adjusts the filtering strength to avoid excessive suppression of the effective signal.

[0034] After noise suppression is completed, the system normalizes the denoised multi-parameter signal to unify the amplitudes of different physical quantities into a standardized range (such as 01 or -11) for subsequent coding, modulation, and error correction. Meanwhile, to ensure data temporal consistency, each sampling point is bound to a high-precision timestamp derived from the synchronization triggering system in step S1 and compensated for temperature drift.

[0035] The system encapsulates the noise-reduced and normalized multi-parameter data with the corresponding timestamps into data frames. Each data frame contains a frame header identifier, timestamp, multi-parameter measurement values, data quality flags, and a CRC checksum. The encapsulated data frame is then passed to the next step, S3, for pilot insertion and wireless modulation / coding.

[0036] S3: At the ground receiving end, the pilot sequence is used to complete phase and frequency offset estimation, perform I / Q imbalance compensation and signal correction, recover multi-parameter monitoring data, and perform threshold determination and alarm.

[0037] Furthermore, standardized multi-parameter data is framed. The frame structure adopts a "frame header—pilot—payload—checksum" organization. The frame header includes fields such as protocol version, device identifier, hash number, depth segment identifier, frame sequence number, timestamp, and data quality flags, used to distinguish data sources and ensure playback consistency; the frame sequence number and timestamp are used to detect packet loss and out-of-order delivery. The payload carries temperature, pressure, flow rate, moisture content, and their status flags in a compact field-length-value format, and short-window statistics (such as mean, variance, and extreme values) can be attached when necessary for rapid edge diagnostics. A cyclic redundancy check (CRC) code is set at the end of the frame for error detection at the receiving end.

[0038] It should be noted that pilot sequences for synchronization and compensation are inserted at the physical layer. To ensure acquisition capability and estimation accuracy under low signal-to-noise ratio, the pilot sequence uses a fixed-length training segment with good autocorrelation characteristics. In one embodiment, the length is set to 64 symbols, placed after the frame header and adjacent to the preamble pulse, so that the receiver can quickly complete frame detection, timing synchronization, and coarse frequency offset estimation. For longer service payloads or frequency bands with faster environmental frequency offset drift, the system can insert short pilots (i.e., "intermediate pilots") at fixed intervals within the payload to track the remaining frequency offset and phase drift; the duty cycle and insertion interval of the pilots can be adaptively adjusted according to link quality and energy consumption targets.

[0039] It should also be noted that channel coding and interleaving are performed on the service payload. The coding scheme balances reliability and computational complexity, preferentially using error-correcting codes with mature engineering implementations, such as BCH or convolutional codes. Low-density parity-check codes can be used in more demanding scenarios. The interleaver disperses burst interference using block interleaving or pseudo-random interleaving, reducing the impact of consecutive errors on decoding performance. When the service payload is short, the system can use repetitive coding or symbol-level time diversity to enhance robustness. To reduce spectral concentration caused by long zero sequences, the system scrambles the encoded bitstream, and the scrambling polynomial and initial state are written into the frame header for the receiver to reconstruct.

[0040] Furthermore, the bitstream is mapped to symbols according to a preset modulation scheme and then transmitted via radio frequency. The modulation scheme is selected based on the downhole propagation method and link budget: in near-field magnetic induction or low-frequency electromagnetic coupling links, frequency shift keying is preferred to obtain better frequency offset tolerance; when channel conditions permit, phase keying is used to improve spectral efficiency; in scenarios requiring long distance, low data rate, and strong anti-interference capability, a spread-spectrum low-data-rate long-symbol scheme can be used. For symbol shaping, the system configures reasonable shaping filters and guard intervals for the baseband or intermediate frequency signals to control out-of-band radiation and inter-symbol interference; specific filtering and guard interval parameters are matched with the sampling rate, symbol rate, and power amplifier linearity to ensure that the transmit mask requirements are met.

[0041] It should be noted that an adaptive modulation and coding strategy is introduced. The transmitter selects an appropriate transmission mode from multiple "modulation-coding-repetition" combinations based on the previous cycle's reception acknowledgments and link quality statistics (such as estimated signal-to-noise ratio and packet error rate): when link quality deteriorates, the modulation order is reduced, coding redundancy is increased, or repeated transmission is enabled; when link quality improves, the system reverts to a higher-efficiency combination. This adaptive strategy works in conjunction with the power management unit to minimize average transmit power consumption while meeting real-time requirements. Furthermore, the system supports graded transmit power control and duty cycle constraints, further reducing energy consumption by shortening the preamble length, reducing the number of intermediate pilot frequencies, or merging multiple small frames into a single large frame.

[0042] It should also be noted that, in terms of security, the system can perform lightweight encryption and integrity protection on the service payload before channel coding as needed. Symmetric encryption and message authentication code mechanisms are recommended to prevent production risks caused by false alarms and forged messages. Encryption and authentication parameters and key identifiers are marked in a controlled manner in the frame header to facilitate correct decryption and verification at the receiving end.

[0043] At the end of the transmission link, the system buffers and schedules frames. Under normal operating conditions, monitoring frames are sent at fixed intervals. When a threshold triggers an alarm, the system immediately inserts a high-priority alarm frame and may temporarily increase the repetition count or transmission power to improve the alarm arrival rate. In the event of continuous packet loss or prolonged lack of acknowledgment at the receiver, the system enters a conservative transmission mode, extending the pilot signal, reducing the symbol rate, and increasing the interleaving depth until the link is restored.

[0044] Through the coordinated design of the above-mentioned framing, pilot insertion, coding interleaving, scrambling and modulation transmission, the system can still achieve stable synchronization and compensation parameter estimation in the downhole environment with high attenuation, high noise and frequency drift, providing a reliable basis for phase correction and I / Q imbalance compensation, and taking into account energy consumption and real-time requirements while ensuring transmission reliability.

[0045] Furthermore, the ground receiver receives wireless signals from underground via an antenna and sequentially performs RF front-end amplification, downconversion, synchronization, and pre-demodulation compensation to recover high-precision multi-parameter measurement data and correct phase drift, frequency offset, and I / Q imbalance distortion caused by channel transmission and transmit / receive links.

[0046] First, the receiver's RF front-end includes an antenna, a low-noise amplifier (LNA), and a mixer-downconverter module. The downhole signal received by the antenna is amplified by the LNA and then enters the downconverter unit, where it is mixed with the local oscillator signal to generate an intermediate frequency (IF) or direct baseband signal, and output as two components: in-phase (I) and quadrature (Q). The I / Q signal is sampled by an analog-to-digital converter (ADC) and then enters the digital signal processing module.

[0047] In the digital domain, the system first uses the pilot sequence inserted in step S3 for coarse synchronization and timing alignment, and then performs phase drift and frequency offset estimation. The phase drift estimate is expressed as:

[0048]

[0049] in, This represents the estimated average phase shift (in radians), used to reflect the overall phase rotation of the received signal; n represents the sampling point index; The set of indices of the pilot symbols in the received sequence; r[n] represents the complex signal (in I+jQ form) sampled at the receiver; p[n] represents the known pilot symbol sequence (fixed configuration at the transmitter); p * [n] denotes the complex conjugate of the pilot symbol.

[0050] The frequency offset estimate is expressed as:

[0051]

[0052] in, This represents the estimated frequency offset; T represents the sampling period, which is equal to the reciprocal of the sampling frequency; r * [n-1] represents the complex conjugate of the received signal r[n-1].

[0053] It should be noted that after completing the phase and frequency offset estimation, the system enters the estimation and compensation stage for the I / Q imbalance parameters. I / Q imbalance is caused by differences in the analog front-end devices at the receiving end or temperature variations, resulting in amplitude inconsistencies and phase errors between the in-phase and positive-phase channels. This imbalance can be described by the following matrix model:

[0054]

[0055] Where I and Q represent the uncompensated in-phase and quadrature components (unit: amplitude, normalized form); I ′ Q ′ The values ​​represent the in-phase and quadrature components after compensation processing; ∈: I / Q represents the amplitude imbalance coefficient (dimensionless), whose value reflects the degree of inconsistency between the gains of the I and Q channels. When ∈ = 0, it indicates that the amplitudes are completely balanced; θ: I / Q represents the phase imbalance angle (unit: radians), whose value reflects the deviation of the phase difference between the I and Q channels from the ideal 90°. When θ = 0, it indicates that the phases are completely quadrature.

[0056] The compensation process includes three sub-steps, using pilot sequences to estimate... and Calculate the inverse of the I / Q imbalance matrix; apply the inverse matrix to the received (I,Q) component to obtain the compensated (I) component. ′ Q ′ ).

[0057] By combining the compensation for frequency offset and phase drift into the result of I / Q compensation, a comprehensive compensation formula is formed:

[0058]

[0059] in This represents the received signal (in complex form) after I / Q imbalance compensation and phase and frequency offset correction.

[0060] It should also be noted that after the above compensation processing, the constellation diagram distortion of the received signal is corrected, and the error vector amplitude (EVM) is significantly reduced, thereby improving the demodulation success rate and the accuracy of restoring multi-parameter measurements. The compensated signal is then sent to the demodulation and channel decoding module to recover the multi-parameter data such as temperature, pressure, flow rate, and water cut collected downhole, and these data are used for threshold determination and alarm processing.

[0061] Furthermore, after completing signal compensation and data recovery, the system performs real-time threshold determination and alarm processing on the demodulated multi-parameter monitoring data, so as to quickly issue early warnings to the ground management system when abnormal working conditions occur downhole.

[0062] First, the system extracts physical quantities such as temperature, pressure, flow rate, and moisture content from the output multi-parameter data stream, and compares and judges them according to pre-set threshold rules or adaptively updated threshold models.

[0063] The threshold can be determined in the following two ways:

[0064] 1. Fixed threshold mode: An absolute threshold input by the wellhead manager during system initialization or maintenance, for example:

[0065] Upper temperature limit T max and lower limit T min ;

[0066] Pressure limit P max and lower limit P min ;

[0067] Traffic upper and lower limits Q max Q min ;

[0068] Upper limit of moisture content WC max .

[0069] 2. Adaptive Threshold Mode: The system automatically adjusts the threshold based on the statistical characteristics of historical data. For example, calculation based on the sliding window quantile method:

[0070] Th (u) =μ win +k·σ win ,Th (l) =μ win -k·σ win

[0071] Among them, Th (u) ,Th (l) Indicates the upper and lower thresholds obtained through dynamic calculation; μ win σ represents the mean of the measurements within the current sliding window. win The standard deviation of the measured values ​​within the current sliding window is represented by ; k represents the threshold coefficient (dimensionless), which is usually taken as 2 to 3; the sliding window length N is determined according to the sampling period and response time requirements.

[0072] When the real-time measurement value X of the detected object t When the corresponding upper or lower threshold range is exceeded, the system determines that an abnormal operating condition has occurred and enters the alarm triggering process. In order to reduce frequent alarms caused by threshold fluctuations, the system introduces a hysteresis strategy, that is, it requires M consecutive samplings (e.g., M=3~5) to exceed the limit before triggering an alarm, and during recovery, it also requires several consecutive samplings to recover to the safe range before the alarm is cleared.

[0073] Upon alarm triggering, the system performs the following actions: Local notification: The abnormal parameter is highlighted in red on the ground receiving terminal display screen, accompanied by an audible and visual alarm signal. The duration and interval of the audible and visual alarm are configurable to allow operators to quickly locate the abnormal well section. Remote reporting: The system encapsulates the alarm information into a high-priority alarm frame and sends it directly to the host computer monitoring system or oilfield production management platform. The alarm frame contains the following fields: well number, depth segment, equipment number; abnormal parameter name and measured value; upper and lower threshold values; alarm start timestamp; alarm type code (e.g., over-temperature, over-pressure, low flow, high water content, etc.). Link priority adjustment: Alarm frames are sent with priority over ordinary monitoring frames in transmission scheduling, and the transmission power can be temporarily increased, the number of repetitions increased, or additional pilot frequencies inserted to improve the reliability of alarm information arrival. Local evidence storage: Alarm events are recorded in the ground data storage unit to form an alarm log, facilitating subsequent accident analysis and maintenance traceability.

[0074] In adaptive threshold mode, after the alarm is cleared, the system automatically recalculates the sliding window statistics based on the data during the alarm period and updates the threshold range for the next period, thus making the threshold closer to the actual production situation. For fixed threshold mode, maintenance personnel manually adjust the threshold according to the on-site conditions.

[0075] Furthermore, the system supports multi-parameter linkage alarms in its judgment logic. This means that a composite alarm is triggered when the changes in multiple parameters conform to a preset abnormal pattern. For example, the "pressure drop + water cut increase" pattern can be used as a well casing leak warning. This pattern is defined through logical expressions, such as: Alarm = (P t <P min ∧WC t WC max ).

[0076] Through the aforementioned threshold determination and alarm mechanism, the system can promptly issue multi-channel warnings to operators when abnormal downhole conditions occur, and ensure that alarm information still has a high arrival rate and reliability in the downhole communication environment with high interference and long delay, thus providing a guarantee for safe production of oil wells.

[0077] It should be noted that the system stores the data frames generated from each sampling in the ground data storage unit according to a unified time-series data structure. Each record includes: timestamp (accurate to milliseconds); identification information such as well number, well depth, and equipment number; measured values ​​such as temperature, pressure, flow rate, and water content; data quality flags (including states such as disconnection, drift, over-range, and high noise); alarm status flags and corresponding alarm types.

[0078] The data storage format supports both efficient binary encoding and structured database storage modes to balance access efficiency and system compatibility. Under high sampling rate conditions, the system prioritizes binary batch storage to reduce storage overhead; when real-time interaction with the production management system is required, a structured database interface (such as SQL or a time-series database) is used to achieve conditional retrieval and fast querying.

[0079] To support the visualization and analysis of historical data, the system has a built-in historical playback function. Users can select any time period, and the system will replay the multi-parameter curves for that period in chronological order, while marking alarm events and threshold exceedance points. To improve analysis efficiency, the system supports playback at multiple time scales (such as aggregation at the minute, hour, and day levels) and can overlay and display the changing trends of multiple parameters for analyzing the correlation between parameters.

[0080] In terms of data analysis, the system can calculate long-term trends, periodic fluctuations, and correlation coefficients between parameters based on historical data. For oil well conditions with obvious seasonality or periodicity, the sliding window mean and standard deviation can be used to extract patterns of change, providing a reference for production optimization. When historical analysis reveals abnormal trends in parameter changes (e.g., a gradual increase in temperature accompanied by increased pressure fluctuations), the system can issue early warnings to prompt maintenance personnel to take preventative measures.

[0081] Furthermore, in adaptive threshold mode, historical data analysis results can also serve as the basis for threshold updates. The system periodically calculates the statistical distribution (such as mean, standard deviation, quantiles, etc.) over a period of time and automatically adjusts the upper and lower limits for the next period according to the set threshold update strategy, ensuring that the threshold dynamically matches the actual production situation.

[0082] It should also be noted that the downhole monitoring unit uses a high-temperature lithium battery as its main power source, and the battery must be able to maintain stable output for extended periods at a high temperature of 175℃. In well sections where conditions permit, a thermoelectric generator module or a vibration energy harvesting device can be configured as an auxiliary power source, connected in parallel with the main battery through an energy management circuit to extend the overall power supply cycle.

[0083] The core of the system's power consumption control is a multi-level sleep strategy and an event wake-up mechanism. The multi-level sleep modes include: Deep sleep mode: only the real-time clock and a very small number of monitoring circuits are retained, resulting in the lowest power consumption, used when there are no sampling tasks or communication tasks for a long time; Standby mode: the sensors and data processing modules are kept in the off state, and only the communication receiver or wake-up trigger circuit is kept in low-power listening mode; Active mode: all functional units operate at full power for data acquisition, signal processing, and communication processes.

[0084] The event wake-up mechanism supports three triggering methods: timed wake-up: the system is woken up by a real-time clock according to a set sampling period; threshold-triggered wake-up: the system is woken up in advance to sample and transmit when the sensor detects a sudden change in parameters or an out-of-limit trend; external signal wake-up: the system is woken up by special control commands received through the downhole-to-surface communication link.

[0085] The system's duty cycle scheduling algorithm calculates average power consumption based on the sampling period, processing time, and communication duration. For example, under typical operating conditions, with a sampling period set to 30 seconds, data processing and transmission taking approximately 1 second, the power consumption in active mode is approximately 200mW, and in deep sleep mode it is less than 1mW. Under these conditions, the system's average duty cycle is less than 2%, achieving a battery life of over 24 months.

[0086] To further reduce communication power consumption, the system automatically reduces transmission power and the number of repeated transmissions when the link quality is good, and merges data into batches for transmission within multiple sampling periods; when the link quality deteriorates, the pilot length and transmission redundancy are appropriately increased to ensure reliability.

[0087] The energy consumption control module also monitors battery voltage, temperature and remaining capacity, predicts the remaining usable time based on the battery discharge curve, and issues maintenance warnings through the ground terminal when the battery is low, so as to arrange replacement or maintenance in advance.

[0088] Example 2, one embodiment of the present invention, provides an oilfield downhole multi-parameter wireless monitoring and signal compensation system, including a downhole multi-parameter acquisition and signal conditioning module, a noise suppression and wireless coding transmission module, and a receiver compensation and alarm determination module.

[0089] The downhole multi-parameter acquisition and signal conditioning module is used to acquire working condition parameters based on downhole sensors. After signal conditioning and analog-to-digital conversion, it generates the original digital signal. The noise suppression and wireless coding transmission module is used to perform frequency domain analysis and adaptive filtering on the acquired data, suppress noise and normalize it, construct data frames with timestamps, insert pilot sequences and perform coding modulation, and transmit it to the ground through a wireless link. The receiver compensation and alarm judgment module is used by the ground receiver to estimate the phase and frequency offset using the pilot sequence, perform I / Q imbalance compensation and signal correction, recover multi-parameter data, and perform threshold judgment and alarm processing.

Claims

1. A method for multi-parameter wireless monitoring and signal compensation in oilfield downhole wells, characterized in that, include: Relying on downhole multi-parameter sensors, operating parameters are collected, and signal conditioning and analog-to-digital conversion are performed; Based on frequency domain analysis and adaptive filtering, noise suppression and normalization processing of operating parameters are performed to construct data frames with timestamps, and pilot sequences are inserted for coded modulation and transmission. At the ground receiving end, pilot sequences are used to estimate phase and frequency offset, perform I / Q imbalance compensation and signal correction, recover multi-parameter monitoring data, and determine thresholds and alarms. Noise suppression includes low-frequency drift detection based on a sliding window and dynamic noise reduction using an adaptive filter; Phase and frequency offset estimation includes obtaining phase drift and frequency offset based on correlation operations of pilot symbols; I / Q imbalance compensation includes constructing a phase deviation matrix and performing inverse matrix correction on the received in-phase and quadrature signals.

2. The method for multi-parameter wireless monitoring and signal compensation in oilfield downhole as described in claim 1, characterized in that: The noise suppression includes, Fast Fourier Transform is used for frequency domain interference identification, and a minimum mean square error adaptive filtering algorithm is used to dynamically eliminate low-frequency drift and power frequency interference.

3. The method for multi-parameter wireless monitoring and signal compensation in oilfield downhole as described in claim 1, characterized in that: The data frame includes, Frame header, pilot sequence, traffic payload, and cyclic redundancy check code; The frame header contains a timestamp, hash number, depth segment, and device identification information.

4. The method for multi-parameter wireless monitoring and signal compensation in oilfield downhole as described in claim 1, characterized in that: The coding modulation includes, Channel coding is performed using one of frequency shift keying, phase shift keying, or spread spectrum modulation, combined with BCH codes or low-density parity-check codes.

5. The method for multi-parameter wireless monitoring and signal compensation in oilfield downhole as described in claim 1, characterized in that: The phase and frequency offset estimation includes, The average phase drift and frequency offset are output based on the pilot sequence, and corrected at the receiving end by a local phase-locked loop.

6. The method for multi-parameter wireless monitoring and signal compensation in oilfield downholes as described in any one of claims 1, 4, or 5, characterized in that: The I / Q imbalance compensation includes, By establishing a phase deviation matrix and performing an inverse matrix transformation on the in-phase and quadrature components, the corrected signal is obtained.

7. The method for multi-parameter wireless monitoring and signal compensation in oilfield downholes as described in claim 1 or 6, characterized in that: The threshold determination includes, Fixed threshold mode and adaptive threshold mode; The adaptive threshold mode calculates the mean and standard deviation of the measured values ​​through a sliding window and dynamically updates the threshold based on the quantile method.

8. A multi-parameter wireless monitoring and signal compensation system for oilfield downholes, employing the multi-parameter wireless monitoring and signal compensation method for oilfield downholes as described in any one of claims 1 to 7, characterized in that: It includes a downhole multi-parameter acquisition and signal conditioning module, a noise suppression and wireless coding transmission module, and a receiver compensation and alarm determination module; The downhole multi-parameter acquisition and signal conditioning module is used to acquire operating parameters based on downhole sensors, and generate raw digital signals after signal conditioning and analog-to-digital conversion. The noise suppression and wireless coding transmission module is used to perform frequency domain analysis and adaptive filtering on the collected data, suppress noise and normalize it, construct data frames with timestamps, insert pilot sequences and perform coding modulation, and transmit them to the ground through a wireless link; The receiving end compensation and alarm determination module is used by the ground receiving end to estimate the phase and frequency offset using pilot sequences, perform I / Q imbalance compensation and signal correction, recover multi-parameter data, and perform threshold determination and alarm processing.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the oilfield downhole multi-parameter wireless monitoring and signal compensation method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the oilfield downhole multi-parameter wireless monitoring and signal compensation method as described in any one of claims 1 to 7.

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