A system for monitoring gas content in associated gas of an oil pipeline

Abstract

The application relates to the technical field of gas content monitoring, in particular to a gas content monitoring system for associated gas in an oil extraction pipeline. The system comprises a data acquisition module for acquiring the spectral absorption rate signal of the gas to be measured and corresponding temperature and current signals; a gas signal weight acquisition module for determining the first and second noise residual degrees by analyzing the shape deviation of the spectral signal and environmental fluctuations, calculating the signal weight and acquiring the spectral absorption rate signal after noise suppression according to the signal weight; and a gas content monitoring module for acquiring the gas content monitoring result according to the signal after noise suppression. The application solves the problem that the traditional average noise reduction technology ignores the signal noise difference, effectively suppresses the background noise through adaptive weighting, and significantly improves the monitoring accuracy of the gas content.

Description

Technical Field

[0001] This application relates to the field of gas content monitoring technology, specifically to a gas content monitoring system for associated gas in oil production pipelines. Background Technology

[0002] Associated gas in oil pipelines, an important mixed gas produced alongside crude oil during oil extraction, mainly consists of light hydrocarbon components such as methane and ethane, as well as non-hydrocarbon gases such as carbon dioxide and oxygen. Accurate monitoring of the content of each component is crucial for ensuring the safe operation of pipelines. Laser gas sensors based on Tunable Semiconductor Laser Absorption Spectroscopy (TDLAS) technology have become a core tool in gas content monitoring due to their significant advantages, including high sensitivity, real-time speed, non-contact measurement, and simultaneous detection of multiple components.

[0003] In practical applications of laser gas sensors, noise suppression processing is often performed on the raw spectral absorbance signal to improve detection accuracy. Among these methods, multiple signal averaging is widely used in TDLAS sensors due to its low computational cost and low resource consumption. However, the actual oilfield operating environment is complex, affected by multiple factors such as pressure fluctuations, temperature changes, impurity interference, and laser current and temperature fluctuations within the pipeline. Consequently, the raw signals from continuous sampling often contain varying degrees of noise. Traditional multiple signal averaging techniques assign equal weight to all signals, resulting in the inability to effectively remove high-noise signals and excessive residual noise, thereby reducing the accuracy of gas content monitoring in associated gas from oil pipelines. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a gas content monitoring system for associated gas in oil production pipelines, the specific technical solution of which is as follows: This application discloses a gas content monitoring system for associated gas in oil production pipelines, the system comprising: The data acquisition module is used to continuously measure a preset number of spectral absorbance signals of the gas to be tested in the associated gas of the oil pipeline, as well as the corresponding temperature signal and input current signal in the laser gas sensor, using a laser gas sensor. The gas signal weight acquisition module is used to determine the first noise residual of the spectral absorbance signal of the gas under test by analyzing the amplitude distribution of the non-absorption peak region in the spectral absorbance signal and the changing trend of the line connecting the two ends of the characteristic absorption peak in the spectral absorbance signal of the gas under test. The fluctuations of the temperature signal and input current signal corresponding to the spectral absorbance signal are analyzed respectively, as well as the influence of the temperature signal and input current signal on the spectral absorbance signal, to determine the second noise residual of the spectral absorbance signal of the gas to be measured. Based on the first noise residual and the second noise residual, the weights of the spectral absorbance signal are determined to obtain the noise-suppressed spectral absorbance signal. The gas content monitoring module is used to obtain the monitoring results of the gas content to be measured based on the spectral absorbance signal after noise suppression.

[0005] Preferably, the method for determining the first noise residual of the spectral absorbance signal of the gas to be measured is as follows: The out-of-peak absorption rate of the spectral absorbance signal is determined by analyzing the amplitude distribution in the non-absorption peak region of the spectral absorbance signal. Based on the changing trend of the line connecting the two nearest troughs at both ends of the characteristic absorption peak in the spectral absorbance signal of the gas to be measured, the peak-bottom deviation of the spectral absorbance signal is determined. The first noise residual of the spectral absorbance signal of the gas to be measured is positively correlated with the out-of-peak absorbance and the peak bottom deviation, respectively.

[0006] Preferably, the out-of-peak absorption rate of the spectral absorbance signal is the mean of all normalized amplitude values ​​in the non-absorption peak region of the spectral absorbance signal.

[0007] Preferably, the peak-bottom deviation of the spectral absorbance signal is the absolute value of the slope of the line connecting the two nearest adjacent troughs at both ends of the characteristic absorption peak of the gas to be measured in the spectral absorbance signal.

[0008] Preferably, the method for determining the second noise residual of the spectral absorbance signal of the gas to be measured is as follows: The fluctuations of the temperature signal and the input current signal corresponding to the spectral absorbance signal are analyzed respectively to determine the laser environment fluctuation coefficient. The deviation of the spectral absorbance signal is determined based on the degree of influence of the temperature signal and the input current signal on the spectral absorbance signal. The second noise residual of the spectral absorbance signal of the gas under test is positively correlated with the laser environment fluctuation coefficient and the deviation.

[0009] Preferably, the laser environmental fluctuation coefficient is positively correlated with the dispersion of all amplitudes in the temperature signal corresponding to the spectral absorbance signal and the dispersion of all amplitudes in the input current signal.

[0010] Preferably, the method for determining the deviation of the spectral absorbance signal is as follows: Based on the molecular mass of the gas to be tested, as well as the preset pressure and temperature values, the corresponding Voigt linear function is obtained. The normalized values ​​of all amplitudes on the characteristic absorption peaks of the gas component to be measured in the spectral absorbance signal are fitted using the Voigt linear function, and the fitting error is denoted as the deviation of the spectral absorbance signal.

[0011] Preferably, the method for determining the weights of the spectral absorbance signal is as follows: The combined noise residual of the spectral absorbance signal is determined based on the normalized values ​​of the first and second noise residuals. The reciprocal of the comprehensive noise residual is normalized and used as the weight of the spectral absorbance signal.

[0012] Preferably, the overall noise residual of the spectral absorbance signal is the average of the normalized values ​​of the first noise residual and the second noise residual of the spectral absorbance signal.

[0013] Preferably, the noise-suppressed spectral absorbance signal is the result of a weighted average of all spectral absorbance signals according to the weights.

[0014] This application has the following beneficial effects: This application constructs first and second noise residuals by comprehensively analyzing the morphological distortion characteristics and environmental fluctuations of the spectral absorbance signal, and determines the signal weight accordingly. This achieves accurate quantification and differentiated processing of residual background noise in the preprocessed signal. This method breaks through the limitation of equal weights in traditional averaging techniques, and can adaptively reduce the contribution of high-noise signals in the fusion process, effectively suppressing the interference of background noise on the detection results. This helps to improve the signal-to-noise ratio of the spectral absorbance signal and the monitoring accuracy of associated gas content in oil pipelines. Furthermore, by inputting the noise-suppressed spectral absorbance signal into the signal processing unit, this application achieves accurate inversion and real-time display of the gas content to be measured, improving the monitoring accuracy of gas content in associated gas in oil pipelines. Attached Figure Description

[0015] Figure 1 This is a block diagram of a gas content monitoring system in associated gas of an oil production pipeline provided in one embodiment of this application; Figure 2 This is a schematic diagram of the comprehensive noise residual extraction process provided in one embodiment of this application. Detailed Implementation

[0016] The following description, in conjunction with the accompanying drawings, details a specific scheme for a gas content monitoring system in associated gas of an oil production pipeline provided in this application.

[0017] Please see Figure 1 The diagram illustrates a block diagram of a gas content monitoring system in associated gas of an oil pipeline according to an embodiment of this application. The system includes: a data acquisition module 101, a gas signal weight acquisition module 102, and a gas content monitoring module 103.

[0018] The data acquisition module 101 is used to continuously measure a preset number of spectral absorbance signals of the gas to be tested in the associated gas of the oil pipeline, as well as the corresponding temperature signal and input current signal in the laser gas sensor, using a laser gas sensor.

[0019] Obtain the commonly used absorption spectrum wavelengths of the gas to be tested in the associated gas (e.g., the absorption spectrum wavelength corresponding to the characteristic absorption peak of oxygen is 760.8 nm) as the benchmark parameters for laser wavelength scanning and subsequent screening of characteristic absorption peaks.

[0020] Furthermore, the associated gas in the oil pipeline is sampled using a sample gas sampling system, and the sample of associated gas is subjected to dust removal, oil removal, dehumidification, and constant pressure and temperature control (set to 1MPa and 25℃ in this embodiment). This process eliminates pressure fluctuations, temperature changes, and impurity interference in the pipeline while keeping the chemical properties and component content of the sample gas unchanged, thus producing a standard state of the associated gas to be tested input laser gas sensor.

[0021] Furthermore, within a preset time window, the spectral absorbance signal of the gas to be tested in the associated gas, as well as the corresponding laser temperature signal and input current signal, are synchronously acquired using a laser gas sensor. A preset number of spectral absorbance signals and their corresponding laser temperature signals and input current signals are continuously acquired.

[0022] It should be noted that the preset time window value is set manually. In this embodiment, the preset time window value is 1 second and the preset number value is 50. In actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0023] Furthermore, the different types of data collected are processed as follows: By utilizing the upper and lower limits of the sensor's range, the temperature signal and the input current signal are normalized using the maximum and minimum value normalization method to eliminate the influence of data dimensions.

[0024] Before baseline correction of the spectral absorbance signal, the amplitude distribution of the non-absorption peak region in the original spectral absorbance signal is first extracted, and the out-of-peak absorbance is calculated. The spectral absorbance signal is processed using a baseline correction method. In this embodiment, the baseline correction is performed based on the least squares method with adaptive iterative reweighting penalty, which initially suppresses noise caused by particulate matter, droplets, and background interference. The baseline-corrected spectral absorbance signal is then normalized using the maximum-minimum normalization method. In practical applications, as other implementation methods, implementers may also use other baseline correction methods or normalization methods depending on the specific circumstances. This embodiment does not impose any specific limitations.

[0025] Among them, the process of using the least squares method based on adaptive iterative reweighting penalty to perform baseline correction on the signal, and the process of using the maximum-minimum normalization method to normalize the data are well-known techniques, and will not be described in detail here.

[0026] The gas signal weight acquisition module 102 is used to determine the first noise residual of the spectral absorbance signal of the gas under test by analyzing the amplitude distribution of the non-absorption peak region in the spectral absorbance signal and the changing trend of the line connecting the two ends of the characteristic absorption peak in the spectral absorbance signal of the gas under test; to determine the second noise residual of the spectral absorbance signal of the gas under test by analyzing the fluctuation degree of the temperature signal and the input current signal corresponding to the spectral absorbance signal, and the influence degree of the temperature signal and the input current signal on the spectral absorbance signal; and to determine the weight of the spectral absorbance signal based on the first noise residual and the second noise residual to obtain the noise-suppressed spectral absorbance signal.

[0027] Since baseline correction cannot completely eliminate background noise, an ideal spectral absorbance signal should have a horizontal baseline with a zero value. Therefore, the residual degree of background noise in the spectral absorbance signal can be characterized by the morphological deviation of the signal itself: the greater the baseline tilt at the bottom of the characteristic absorption peak, or the higher the signal amplitude in the non-absorption peak region, the more severe the residual background noise. Therefore, based on the above analysis, this embodiment constructs the first noise residual degree of the spectral absorbance signal by analyzing the amplitude distribution in the non-absorption peak region of the spectral absorbance signal and the changing trend of the line connecting the two ends of the characteristic absorption peak of the analyte gas in the spectral absorbance signal. This is used to preliminarily quantify the residual degree of background noise in the spectral absorbance signal. The specific process is as follows: First, all absorption peaks and characteristic absorption peaks in the spectral absorbance signal are obtained. The process of obtaining the absorption peaks and characteristic absorption peaks is a well-known technique and will not be described in detail here.

[0028] Furthermore, this embodiment determines the out-of-peak absorptivity of the spectral absorbance signal by analyzing the amplitude distribution of the non-absorption peak region in the spectral absorbance signal. Specifically, in this embodiment, the mean of the normalized values ​​of all amplitudes in the non-absorption peak region of the original spectral absorbance signal is used as the out-of-peak absorptivity of the spectral absorbance signal of the gas to be tested. This is used to characterize the background noise level of the non-absorption peak region (i.e., the baseline region) in the spectral absorbance signal, reflecting the residual degree of solid particles, droplet interference, and sensor circuit noise in the associated gas on the signal baseline. The larger the value, the more severe the baseline fluctuation or the greater the offset in the non-absorption region of the signal, the higher the residual degree of background noise, and the worse the signal-to-noise ratio of the signal. Conversely, the smaller the value, the more stable the signal baseline and the closer it is to the ideal zero baseline, the better the suppression effect of background noise, and the higher the signal quality.

[0029] Furthermore, based on the changing trend of the line connecting the two ends of the characteristic absorption peak in the spectral absorbance signal of the gas to be tested, the peak-bottom deviation of the spectral absorbance signal is determined. Specifically, in this embodiment, the absolute value of the slope of the line connecting the two ends of the characteristic absorption peak of the gas to be tested to the nearest adjacent troughs is used as the peak-bottom deviation of the spectral absorbance signal of the gas to be tested. This value is used to characterize the inclination of the baseline at the bottom of the characteristic absorption peak, reflecting the residual status of low-frequency background noise (such as slow light intensity drift or baseline fitting error) in the spectral absorbance signal. The larger the value, the greater the deviation of the baseline at the bottom of the characteristic absorption peak from the horizontal direction, and the more serious the residual low-frequency background noise, which will lead to an increase in the error of the integral area calculation when inverting the gas concentration. Conversely, the smaller the value, the more horizontal the baseline at the bottom of the absorption peak is, the closer the signal shape is to the ideal absorption spectrum, the less background noise interference, and the more conducive it is to improving the accuracy of gas content calculation.

[0030] Based on the out-of-peak absorbance and the peak-bottom deviation, the first noise residual of the spectral absorbance signal of the gas to be tested is determined. Specifically, in this embodiment, the first noise residual of the spectral absorbance signal of the gas to be tested is positively correlated with the out-of-peak absorbance and the peak-bottom deviation, respectively.

[0031] It should be understood that a positive correlation means that the dependent variable increases as the independent variable increases, and the dependent variable decreases as the independent variable decreases. The specific relationship can be additive or multiplicative, etc., and is determined by the actual application. This application does not impose any special restrictions.

[0032] Preferably, as one implementation method, in this embodiment, the mean of the normalized values ​​of the out-of-peak absorbance and peak bottom deviation of the spectral absorbance signal of the gas to be measured is used as the first noise residual of the spectral absorbance signal of the gas to be measured. In practical applications, as other implementation methods, implementers may also use other positive correlation calculation methods such as sum or product according to specific circumstances. This embodiment does not impose any special restrictions.

[0033] It should be noted that this embodiment uses the maximum and minimum value normalization method to normalize the peak bottom deviation. The maximum and minimum values ​​are the maximum and minimum values ​​of the peak bottom deviation of all spectral absorbance signals, respectively. In practical applications, as other implementation methods, implementers may also use other normalization methods according to specific circumstances. This embodiment does not impose any special restrictions.

[0034] The first noise residual can be understood as the level of combined background noise caused by ambient stray light, particulate scattering, and circuit fluctuations that remains in the signal morphology of the spectral absorbance signal after preprocessing such as baseline correction. This index is used to characterize the relative cleanliness and reliability of the signal itself. The calculation of the first noise residual is affected by two factors: off-peak absorbance and peak-bottom deviation. The larger these two factors are, the larger the first noise residual is, reflecting the more serious the residual background noise in the signal and the lower the reliability of the signal in subsequent averaging processing. Conversely, the smaller these two factors are, the smaller the first noise residual is, reflecting the less interference the signal is with background noise, the closer the signal morphology is to the ideal state, and the higher its reference value in subsequent processing.

[0035] Secondly, although this embodiment utilizes a sample gas pretreatment system and a laser driver to control the pressure and temperature of the gas under test and the temperature and current of the laser, the inherent steady-state error in the control circuit cannot be completely eliminated. Furthermore, since the gas under test is no longer directly controlled by the pretreatment system after entering the gas transmission channel, its pressure and temperature may fluctuate, causing the actual gas conditions to deviate from the calibration state. The greater the deviation of the gas under test from the calibration gas conditions, or the more drastic the fluctuations in the laser's temperature and input current, the more background noise is typically introduced into the original spectral absorbance signal. Since all signals use the same pretreatment method, the more drastic the fluctuations in gas conditions and laser state during signal measurement, the greater the residual background noise in the preprocessed spectral absorbance signal.

[0036] Therefore, based on the above analysis, this embodiment constructs a second noise residual of the spectral absorbance signal by analyzing the fluctuation of the temperature signal and the input current signal corresponding to the spectral absorbance signal, as well as the degree to which the actual conditions of the associated gas deviate from the calibration conditions. This is used to quantify the residual degree of background noise in the spectral absorbance signal from the perspective of environmental factors. The specific process is as follows: In this embodiment, firstly, the fluctuation degree of the temperature signal and the input current signal corresponding to the spectral absorbance signal are analyzed respectively to determine the laser environment fluctuation coefficient. Specifically, in this embodiment, the laser environment fluctuation coefficient is positively correlated with the dispersion degree of all amplitudes in the temperature signal corresponding to the spectral absorbance signal and the dispersion degree of all amplitudes in the input current signal.

[0037] Preferably, as one implementation, in this embodiment, the average of the dispersion of all normalized amplitude values ​​in the temperature signal corresponding to the spectral absorbance signal and the dispersion of all normalized amplitude values ​​in the input current signal is used as the laser environment fluctuation coefficient corresponding to the spectral absorbance signal of the gas under test. This coefficient characterizes the dynamic stability of the core hardware parameters (laser temperature and input current) of the laser gas sensor during spectral signal measurement, reflecting the robustness of the sensor's own operating state. The larger the value, the more severe the temperature and current fluctuations of the laser, causing the center wavelength and intensity of the emitted laser to fluctuate, thus mixing more random background noise caused by hardware instability into the spectral absorbance signal. Conversely, the smaller the value, the more stable the laser's operating state, the more constant the emitted laser parameters, the less the spectral signal is affected by the sensor's own fluctuations, and the higher the data quality.

[0038] It should be noted that there are many methods to measure the dispersion of data. In this embodiment, the standard deviation of all normalized amplitude values ​​in the temperature signal corresponding to the spectral absorbance signal is used as the dispersion of all normalized amplitude values ​​in the temperature signal corresponding to the spectral absorbance signal. For the input current signal, since TDLAS technology achieves wavelength scanning by periodically changing the injected current, the normal scanning signal itself exhibits a ramp or sawtooth wave shape. Directly calculating the standard deviation would misjudge the effective scanning trend as noise. Therefore, an ideal sawtooth wave synchronized with the input current signal is first constructed, and the residual signal between the input current signal and the ideal sawtooth wave is calculated. The standard deviation of all amplitude values ​​in this residual signal is used as the dispersion of the input current signal to characterize the ripple noise and random fluctuations in the current driving process. In practical applications, as other implementation methods, implementers can also use other methods such as variance or coefficient of variation to measure the dispersion of data, depending on the specific circumstances. This embodiment does not impose any special restrictions. Furthermore, based on the degree of influence of the temperature signal and the input current signal on the spectral absorbance signal, the deviation of the spectral absorbance signal is determined, specifically: In this embodiment, the corresponding Voigt line shape function is obtained based on the molecular mass of the gas to be tested, as well as the preset pressure and temperature values. Specifically, the Gaussian half-width, which characterizes Doppler broadening, is calculated based on the molecular mass and temperature preset values ​​of the gas to be tested. The Lorentz half-width, which characterizes collision broadening, is calculated based on the preset pressure and the collision broadening coefficient of the gas to be tested. Then, the Gaussian half-width and the Lorentz half-width are convolved and integrated to construct the Voigt line shape function that characterizes the ideal absorption spectral shape of the gas to be tested under the calibration gas conditions.

[0039] Furthermore, the normalized values ​​of all amplitudes on the characteristic absorption peaks of the analyte gas components in the spectral absorbance signal are fitted using the Voigt line shape function. The fitting error is denoted as the deviation of the spectral absorbance signal of the analyte gas, which characterizes the degree to which the actual physical state (pressure and temperature) of the analyte gas in the associated gas deviates from the calibration gas conditions (preset pressure and temperature values). This reflects the magnitude of the difference between the actual measurement environment and the ideal calibration environment. The larger the value, the further the actual gas pressure and temperature deviate from the preset standards, resulting in distortion of the broadening characteristics of the spectral absorption peaks. This increases the fitting error between the actual spectral lines and the theoretical Voigt line shape, and the stronger the environmental noise introduced into the signal. Conversely, the smaller the value, the closer the actual gas conditions are to the calibration state, the higher the degree of agreement between the absorption peak shape and the theoretical model, the less interference the signal is caused by environmental factors, and the more accurate the gas concentration inversion result.

[0040] The collision widening coefficient, the method for obtaining the Voigt line shape function, and the process of using the Voigt line shape function to fit the data and obtain the fitting error are all well-known techniques and will not be elaborated further.

[0041] Furthermore, based on the laser environment fluctuation coefficient and the deviation, a second noise residual is determined. Specifically, in this embodiment, the second noise residual of the spectral absorbance signal of the gas to be measured is positively correlated with the laser environment fluctuation coefficient and the deviation.

[0042] Preferably, as one implementation method, in this embodiment, the average value of the laser environment fluctuation coefficient and deviation corresponding to the spectral absorbance signal of the gas to be tested is used as the second noise residual of the spectral absorbance signal of the gas to be tested. In practical applications, as other implementation methods, implementers may also use other positive correlation calculation methods such as sum or product in combination with specific circumstances. This embodiment does not impose any special restrictions.

[0043] The second noise residual can be understood as the degree of implicit interference to the spectral signal caused by fluctuations in external environmental factors and deviations in gas state during signal measurement. This index is used to characterize the residual background noise introduced by laser instability and changes in gas conditions. The calculation of the second noise residual is affected by two factors: the laser environment fluctuation coefficient and the deviation. The larger these two factors are, the larger the second noise residual is, reflecting that the more severe the temperature and current fluctuations of the laser or the further the actual state of the gas under test deviates from the calibration state, the more additional noise is introduced into the signal, and the greater the risk of signal data distortion. Conversely, the smaller these two factors are, the smaller the second noise residual is, reflecting that the measurement environment is more stable and the gas state is closer to the calibration conditions, and the higher the authenticity and usability of the signal data.

[0044] Furthermore, in this embodiment, the weights of the spectral absorbance signal are determined based on the first noise residual and the second noise residual to obtain the noise-suppressed spectral absorbance signal. Specifically: In this embodiment, the comprehensive noise residual of the spectral absorbance signal is determined based on the normalized value of the first noise residual and the normalized value of the second noise residual. Specifically, the mean of the normalized value of the first noise residual and the normalized value of the second noise residual of the spectral absorbance signal is used as the comprehensive noise residual of the spectral absorbance signal of the gas to be tested. Here, the normalization method adopts the maximum-minimum normalization method, which maps the first noise residual and the second noise residual to the range of (0,1) respectively. Furthermore, the reciprocal of the comprehensive noise residual is normalized and used as the weight of the spectral absorbance signal. The normalization method for the reciprocal of the comprehensive noise residual is as follows: calculate the sum of the reciprocals of the comprehensive noise residual of all spectral absorbance signals of the gas to be measured, and divide the reciprocal of the comprehensive noise residual corresponding to each spectral absorbance signal by the sum of the reciprocals of the comprehensive noise residual. This is used as the normalized result of the reciprocal of the comprehensive noise residual corresponding to each spectral absorbance signal. This is done to ensure that the sum of the weights of all spectral absorbance signals of the gas to be measured is 1.

[0045] Preferably, the schematic diagram of the comprehensive noise residual extraction process provided in this embodiment is as follows: Figure 2 As shown.

[0046] It should be noted that the overall noise residual is used to characterize the overall residual level of background noise in the spectral absorbance signal caused by the combined effects of signal morphological distortion and environmental fluctuations. It reflects the degree of comprehensive interference still contained in a single spectral absorbance signal after preprocessing and the quality of its data. The larger the value, the more severe the background noise interference on the corresponding spectral absorbance signal, the lower the signal-to-noise ratio of the spectral absorbance signal, and the worse the reliability and usability of the data. Conversely, the smaller the value, the purer the corresponding spectral absorbance signal, the closer it is to the ideal noise-free absorption spectrum, the higher the reliability of the data, and the more important it should be in subsequent noise suppression processing.

[0047] The weights of the spectral absorbance signals can be understood as representing the proportion of each spectral absorbance signal's contribution to the final average noise reduction process. This indicator characterizes the importance of the spectral absorbance signal relative to the overall dataset, reflecting the quality of the corresponding spectral absorbance signal data. The calculation of the weights is affected by the overall noise residual. The larger the overall noise residual, the smaller the weight, reflecting severe residual background noise and low data reliability in the corresponding spectral absorbance signal, requiring a reduction in its contribution to the averaging calculation to avoid contaminating the final result. Conversely, the smaller the overall noise residual, the larger the weight, reflecting excellent spectral absorbance signal quality and high signal-to-noise ratio, which should play a greater role as the dominant signal in the averaging process, thereby effectively improving the accuracy and monitoring precision of the final signal.

[0048] Furthermore, the result of weighting and averaging all spectral absorbance signals of the gas to be tested according to the weights is used as the noise-suppressed spectral absorbance signal. The weighted average means that all amplitudes at the same wavelength are averaged according to their corresponding weights, and the weighted average signal is obtained by traversing all wavelengths.

[0049] Thus, this embodiment constructs first and second noise residuals by comprehensively analyzing the morphological distortion characteristics of the spectral absorbance signal and the degree of fluctuation of environmental factors, and determines the signal weight accordingly. This achieves accurate quantification and differentiated processing of residual background noise in the preprocessed signal. This method breaks the limitation of equal weights in traditional averaging techniques, and can adaptively reduce the contribution of high-noise signals in the fusion process, effectively suppressing the interference of background noise on the detection results. It helps to improve the signal-to-noise ratio of the spectral absorbance signal and the monitoring accuracy of associated gas content in oil pipelines.

[0050] The gas content monitoring module 103 is used to obtain the monitoring results of the gas content to be measured based on the spectral absorbance signal after noise suppression.

[0051] The spectral absorbance signal of the gas under test after noise suppression is used as the input of the signal processing unit of the laser gas sensor. The output is the gas content monitoring result of the gas under test in the associated gas, and the gas content monitoring result is displayed on the display. When the gas content monitoring result of the gas under test is greater than the preset alarm value, an alarm is issued on the display. In this embodiment, the preset alarm value of the gas under test (e.g., oxygen) is set to 3%. The preset alarm value of 3% is based on the safety threshold consideration of oxygen content in the associated gas of the oil pipeline. Because the oil pipeline mainly contains flammable and explosive light hydrocarbon components such as methane and ethane, when the oxygen content exceeds 3%, the mixed gas is very likely to reach the explosion limit range, forming a great safety hazard, which may cause combustion or explosion accidents and threaten production safety. Therefore, setting 3% as the preset alarm value of oxygen content can promptly warn and prompt operators to take safety measures such as replacement and venting, thereby ensuring the safe operation of the oil pipeline. In actual application, as other implementation methods, implementers can also set their own values ​​according to specific circumstances. This embodiment does not impose any special restrictions.

[0052] Thus, this embodiment achieves accurate inversion and real-time display of the gas content to be measured by inputting the noise-suppressed spectral absorbance signal into the signal processing unit, thereby improving the monitoring accuracy of gas content in associated gas in oil pipelines.

Claims

1. A gas content monitoring system for associated gas in oil production pipelines, characterized in that, The system includes: The data acquisition module is used to continuously measure a preset number of spectral absorbance signals of the gas to be tested in the associated gas of the oil pipeline, as well as the corresponding temperature signal and input current signal in the laser gas sensor, using a laser gas sensor. The gas signal weight acquisition module is used to determine the first noise residual of the spectral absorbance signal of the gas under test by analyzing the amplitude distribution of the non-absorption peak region in the spectral absorbance signal and the changing trend of the line connecting the two nearest adjacent troughs of the characteristic absorption peaks of the gas under test in the spectral absorbance signal. The fluctuations of the temperature signal and input current signal corresponding to the spectral absorbance signal are analyzed separately, as well as the influence of the temperature signal and input current signal on the spectral absorbance signal, to determine the second noise residual of the spectral absorbance signal of the gas to be measured. Based on the first noise residual and the second noise residual, the weights of the spectral absorbance signal are determined to obtain the noise-suppressed spectral absorbance signal. The gas content monitoring module is used to obtain the monitoring results of the gas content to be measured based on the spectral absorbance signal after noise suppression.

2. The gas content monitoring system in associated gas of an oil production pipeline according to claim 1, characterized in that, The method for determining the first noise residual of the spectral absorbance signal of the gas to be measured is as follows: The out-of-peak absorption rate of the spectral absorbance signal is determined by analyzing the amplitude distribution in the non-absorption peak region of the spectral absorbance signal. Based on the changing trend of the line connecting the two ends of the characteristic absorption peak in the spectral absorbance signal of the gas to be tested, the peak bottom deviation of the spectral absorbance signal is determined. The first noise residual of the spectral absorbance signal of the gas to be measured is positively correlated with the out-of-peak absorbance and the peak bottom deviation, respectively.

3. A gas content monitoring system for associated gas in oil production pipelines according to claim 2, characterized in that, The out-of-peak absorption rate of the spectral absorbance signal is the mean of all normalized amplitude values ​​in the non-absorption peak region of the spectral absorbance signal.

4. A gas content monitoring system for associated gas in oil production pipelines according to claim 2, characterized in that, The peak-bottom deviation of the spectral absorbance signal is the absolute value of the slope of the line connecting the two nearest adjacent troughs at both ends of the characteristic absorption peak of the gas under test in the spectral absorbance signal.

5. A gas content monitoring system for associated gas in oil production pipelines according to claim 1, characterized in that, The method for determining the second noise residual of the spectral absorbance signal of the gas to be measured is as follows: The fluctuations of the temperature signal and the input current signal corresponding to the spectral absorbance signal are analyzed respectively to determine the laser environment fluctuation coefficient. The deviation of the spectral absorbance signal is determined based on the degree of influence of the temperature signal and the input current signal on the spectral absorbance signal. The second noise residual of the spectral absorbance signal of the gas under test is positively correlated with the laser environment fluctuation coefficient and the deviation.

6. A gas content monitoring system for associated gas in an oil production pipeline according to claim 5, characterized in that, The laser's environmental fluctuation coefficient is positively correlated with the dispersion of all amplitudes in the temperature signal corresponding to the spectral absorbance signal and the dispersion of all amplitudes in the input current signal.

7. A gas content monitoring system for associated gas in an oil production pipeline according to claim 5, characterized in that, The method for determining the deviation of the spectral absorbance signal is as follows: Based on the molecular mass of the gas to be measured, as well as the preset pressure and temperature values, the corresponding Voigt linear function is obtained. The normalized values ​​of all amplitudes on the characteristic absorption peaks of the gas component to be measured in the spectral absorbance signal are fitted using the Voigt linear function, and the fitting error is denoted as the deviation of the spectral absorbance signal.

8. A gas content monitoring system for associated gas in oil production pipelines according to claim 1, characterized in that, The method for determining the weights of the spectral absorbance signal is as follows: The combined noise residual of the spectral absorbance signal is determined based on the normalized values ​​of the first and second noise residuals. The reciprocal of the comprehensive noise residual is normalized and used as the weight of the spectral absorbance signal.

9. A gas content monitoring system for associated gas in an oil production pipeline according to claim 1, characterized in that, The overall noise residual of the spectral absorbance signal is the average of the normalized values ​​of the first noise residual and the second noise residual of the spectral absorbance signal.

10. A gas content monitoring system for associated gas in an oil production pipeline according to claim 1, characterized in that, The noise-suppressed spectral absorbance signal is the result of a weighted average of all spectral absorbance signals according to the weights.

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