Aquifer identification system and method based on infrared spectrum gas logging

Abstract

The invention belongs to the field of oil-gas exploration, and discloses an aquifer identification system and method based on infrared spectrum gas logging. In the conventional oil-gas exploration water layer identification, the infrared spectroscopy is adopted to replace a gas chromatographic method to analyze the wellhead gas removed from the drilling fluid, and the method has the advantages of being rapid, safe, sensitive, easy to maintain and the like. In addition, the infrared spectrum of the well head gas further comprises water vapor absorption peaks, and the aquifer recognition method established according to the characteristics of the water vapor absorption peaks can effectively avoid the problem of weak aquifer recognition signals under the complex conditions of heterogeneous, low-porosity-permeability, low-resistance oil and gas reservoirs and the like, and greatly improves the coincidence rate of aquifer recognition. By establishing the weighted composite factor and combining the direction, the threshold value and the volatility of the water vapor absorption peak of the infrared spectrum of the wellhead gas, the accuracy and the redundancy of identification are improved.

Description

Technical Field

[0001] The invention belongs to the field of oil and gas exploration, and in particular relates to an aquifer identification system and method based on infrared spectrum gas logging. Background Art

[0002] During the oil and gas exploration process, drilling fluid is injected from the middle of the drill pipe, reaches the drill bit at the bottom of the well, and then returns to the ground from between the drill pipe and the casing. The drill bit drills water, oil, gas, etc. in the formation, which penetrate into the drilling fluid due to the pressure of the formation and then pass to the ground. Gas logging technology identifies reservoir properties by analyzing the concentration of each component of the wellhead gas in the drilling fluid, which is the key to discovering and evaluating oil and gas resources. With the development and utilization of emerging oil and gas resources such as offshore oil fields and shale oil and gas, the difficulty and complexity of oil and gas exploration are increasing. Factors such as uneven distribution of oil and gas and complex fluid properties make it difficult to identify aquifers. The low compliance rate of aquifer identification will affect the oil and gas evaluation of some well sections. If a certain formation has a high water content, even if there is oil, a large amount of water will be produced during the exploitation process, which will seriously affect oil production. Therefore, the identification of aquifers is of great significance for evaluating reservoir properties, determining subsequent drilling methods, and ensuring oil and gas quality.

[0003] At present, the identification of aquifers in the process of oil and gas exploration at home and abroad is mainly based on geochemical methods such as quantitative fluorescence and nuclear magnetic resonance and logging data methods such as resistivity curve change characteristics. However, under conditions such as light oil reservoirs, the fluorescence characteristics are not obvious, nuclear magnetic resonance can only identify cracks and holes, and the resistivity curve changes are not obvious under conditions of heterogeneity and low porosity and permeability, low resistivity oil and gas reservoirs. These have greatly limited its application in aquifer identification, resulting in a low aquifer identification compliance rate. At present, a universal, effective and accurate aquifer identification method has not yet been formed.

[0004] Patent CN201510672417.7 discloses a comprehensive logging system and method for oil and gas exploration wells. The instrument analyzes the wellhead gas components of oil and gas exploration well gas logging based on infrared spectroscopy. Usually, in the process of infrared spectroscopy logging, air is used as the background gas and wellhead gas is used as the gas to be analyzed. In recent years, infrared spectroscopy analysis technology has been widely used in gas logging for oil and gas exploration due to its advantages of fast, accurate and safe. In the wellhead gas infrared spectrum obtained by the instrument, the water vapor absorption peaks of aquifers and non-aquifers show significant differences.

[0005] The main components in wellhead gas such as hydrocarbon gas have similar molecular structures, and their infrared spectra overlap seriously, which affects the analysis of water vapor. Therefore, accurate analysis of each component in wellhead gas is crucial. Patent CN201110355413.8 discloses a multi-component gas Fourier transform infrared spectroscopy online analysis filtering method, which combines the change in the value of the target component spectral line, the sensitivity, selectivity and noise level of the target component spectral line to other components, and sets the concentration change range, thereby constraining the value range of the analysis result, reducing the noise level while retaining the rapidly changing concentration information in the continuous analysis results of each component gas. The study "Optimization of Savitzky-Golay Filter Parameters and Its Application in Fourier Transform Infrared Gas Spectrum Data Smoothing Preprocessing" published by Tang Xiaojun et al. in 2016 achieved smoothing and denoising of infrared spectral data, further improving the accuracy of spectral gas quantitative analysis. Patent CN201010268039.3 discloses a Fourier transform infrared spectrum distortion identification and processing method, which divides the spectrum into sensitive and non-sensitive segments and uses spectrum rotation and translation methods to correct the baseline drift in the spectrum. The airPLS method proposed by Liang Yizeng, Zhang Zhimin and others in 2010 is widely used in baseline correction of spectral signals (Baseline correction using adaptive iteratively reweightedpenalized least squares). Patent CN201210076501.9 discloses an improved TR multi-component gas Fourier transform infrared spectrum characteristic variable extraction method, which improves the accuracy of multi-component gas analysis results. Patent CN201010270822.3 discloses a multi-component gas spectrum quantitative analysis calibration method based on forward and inverse models, which greatly improves the efficiency of analysis by extracting characteristic variables, and uses BP / RBF neural network to establish a quantitative analysis model for multi-component gas. Patent CN201210076502.3 discloses a multi-analysis model information fusion method for Fourier transform spectral analysis of multi-component gases, which combines partial least squares regression and weighted average methods to establish a quantitative analysis model for multi-component gases, thus achieving accurate quantitative analysis of multi-component gases. These methods and techniques provide an important basis for the acquisition and analysis of water vapor absorption characteristics of the present invention.

[0006] The results of the "Method for Identifying Water Content in Archean Buried Hill Reservoirs of Bozhong 26-6 Structure" published by Guo Mingyu et al. in 2023 show that the directions of water vapor absorption peaks in infrared spectra of oil layers and water layers are opposite. In fact, the water in the strata of offshore oil fields usually has a high salt content. After infiltrating into the drilling fluid, the water evaporation rate of the drilling fluid is low, which makes the water vapor content in the wellhead gas separated from the drilling fluid lower than the water content in the air, resulting in the upward water vapor absorption peak of the wellhead gas infrared absorption spectrum (transmittance) of the water layer gas logging. After drilling into the fresh water layer during the exploration process, due to the infiltration of fresh water into the drilling fluid, after this section of drilling fluid is transferred to the wellhead, the water content of the wellhead gas separated from the drilling fluid is higher than the water content of the air, making the water vapor absorption peak of the wellhead gas infrared absorption spectrum (transmittance) downward. There is a high correlation between the water vapor absorption peak of the wellhead gas and whether the reservoir contains water. The water content of the reservoir can be effectively identified based on the characteristics and change laws of the water vapor absorption peak of the wellhead gas infrared spectrum. This new aquifer identification method based on wellhead gas infrared spectrum can effectively avoid the problem of low aquifer identification compliance rate caused by complex conditions such as heterogeneity, low porosity and permeability, and low resistivity oil and gas reservoirs. It only relies on infrared spectrum gas logging spectra, without adding additional test systems and data, and provides a new method for aquifer identification. This method is of great significance for improving the aquifer identification compliance rate, ensuring oil and gas quality, and optimizing exploration decisions. Summary of the invention

[0007] The purpose of the present invention is to overcome the problems of low identification conformity rate and low versatility of existing aquifer identification methods, and to provide an aquifer identification system and method based on infrared spectroscopy gas logging.

[0008] In order to achieve the above object, the present invention adopts the following technical solution: First, an aquifer identification system based on infrared spectroscopy gas logging includes a mud pump, a degasser, a vacuum pump, an infrared spectroscopy gas logging unit, a hydrogen sensor, a hydrogen sulfide sensor and a host computer; Mud pumps, degassers and vacuum pumps are used to extract and separate wellhead gas from drilling fluid / mud and send it to infrared spectrum gas logging unit, hydrogen sensor and hydrogen sulfide sensor; The infrared spectrum gas logging unit is used to obtain the infrared spectrum of polar molecular components in the wellhead gas; The hydrogen sensor and hydrogen sulfide sensor are metal oxide semiconductor sensors used to detect the concentration of hydrogen and hydrogen sulfide in wellhead gas; The host computer is equipped with spectrum analysis software, which is used to analyze the infrared spectrum of wellhead gas, obtain the concentration of each component, and identify the water content of the reservoir based on the water vapor absorption peak of the infrared spectrum of wellhead gas.

[0009] A further improvement of the present invention is that the infrared spectrum gas logging unit includes a Fourier transform infrared spectrometer, a measuring gas chamber, a humidity sensor, a temperature sensor, a pressure sensor, a core controller, a data transmission device, and an uninterruptible power supply (UPS); Fourier transform infrared spectrometer is used to scan the infrared spectrum of wellhead gas sample; The measuring gas chamber is used to collect gas samples at the wellhead; Humidity, temperature and pressure sensors to measure the humidity, temperature and pressure of the background gas; The core controller is used to collect humidity, temperature, and pressure data; The data transmission device is used to transmit humidity, temperature and pressure data to the host computer; UPS is used to ensure that the power supply to various parts of the system will not be suddenly interrupted.

[0010] A further improvement of the present invention is that the measuring air chamber comprises an air chamber, a first infrared window and a second infrared window are arranged on the air chamber, light emitted by the Fourier transform infrared spectrometer passes through the infrared windows, an air inlet, an air outlet and an air pressure controller are opened on the air chamber, a three-way solenoid valve is arranged on the air inlet of the air chamber, a heater is wound around the outside of the air chamber, a temperature sensor and a pressure sensor are arranged in the air chamber, and a humidity sensor is arranged on the three-way solenoid valve; The first air inlet of the three-way solenoid valve is connected to the air end, the second air inlet is connected to the degasser end, the air outlet is connected to the air chamber, the humidity sensor is arranged at the first air inlet, and the solenoid valve coil of the three-way solenoid valve is connected to the host computer; The heater is connected to a thermostatic controller, and the thermostatic controller is used to control the temperature of the heater.

[0011] In a second aspect, the present invention provides a method for identifying an aquifer based on infrared spectroscopy gas logging, comprising the following steps: The wellhead gas separated after degassing is sent into the measuring gas chamber, and the background gas and wellhead gas are sent into the gas chamber in turn through the three-way solenoid valve, and the infrared spectrum of the wellhead gas is scanned and transmitted to the host computer together with the temperature, pressure and humidity data; The host computer analyzes the infrared spectrum of the wellhead gas based on the received data to obtain the concentration of each component and the characteristics of water vapor; The water content of the reservoir is identified based on the water vapor absorption peak threshold, fluctuation, and direction characteristics.

[0012] A further improvement of the present invention is that the host computer analyzes the infrared spectrum of the wellhead gas according to the received data, and the specific method for obtaining the concentration of each component is as follows: The received data is smoothed, de-noised, baseline corrected, feature screened and quantitatively analyzed to obtain the concentration of each component; Continuous convergence constraint analysis or Savitzky-Golay filter is used for smoothing and denoising to eliminate high-frequency noise in the in-situ spectrum. Segment ratio correction or adaptive iterative reweighted penalized least squares (airPLS) is used for baseline correction to eliminate baseline drift. Tikhonov regularization or forward and inverse model methods are used for feature screening to improve modeling accuracy and efficiency and eliminate cross-influence between different components. Partial least squares regression (PLSR) or neural network (BP neural network, RBF neural network) is used for quantitative analysis to model and obtain the concentration of each component.

[0013] A further improvement of the present invention is that the water vapor absorption peak characteristic is located at 3715cm -1 Up to 3440cm -1 and 2021cm -1 Up to 1600cm -1 range to avoid interference from alkanes, carbon monoxide, carbon dioxide and other gases as much as possible; according to the superposition of spectra, in the characteristic band of water vapor absorption, the original wellhead gas infrared spectrum is used to obtain the i Transmittance t Ri Subtract the first j The gas wave number i The transmittance at t Dji The original water vapor absorption characteristic transmittance with the interference of other components eliminated is obtained t i , in order to further eliminate the interference of 7 components of alkanes, carbon monoxide, carbon dioxide and nitrous oxide on water vapor analysis, the calculation formula is:

[0014] Background spectral transmittance corresponding to the humidity sensor measurement result in the system t Bi The relative humidity is divided into intervals of 10%RH by standard humidity infrared spectrum calculation, and the lower limit of the interval to which the humidity measurement result belongs x 0 and upper limit x 1 corresponds to the standard humidity infrared spectrum transmittance t x0i and t x1i Interpolation calculation, coefficients f 1 and f 2 is obtained by fitting the standard humidity infrared spectrum, and the calculation formula is:

[0015] Water vapor absorption peak transmittance t Si Spectral transmittance through background tBi The characteristic transmittance of the original water vapor absorption t i Calculation, the calculation formula is:

[0016] A further improvement of the present invention is that the water vapor absorption peak threshold characteristic is expressed by a threshold characteristic factor F 1 means that according to the water vapor absorption peak in the well section i The transmittance at the characteristic wave number t Si The average absolute value of the difference from 1.0 M Calculation, expressed as:

[0017] A further improvement of the present invention is that the fluctuation characteristics of the water vapor absorption peak are expressed by the fluctuation characteristic factor F 2 indicates that the transmittance at the characteristic wave number of the water vapor absorption peak in the well section t Si The standard deviation of the absolute value of the difference from 1.0 S Calculation, expressed as:

[0018] A further improvement of the present invention is that the directional characteristics of the water vapor absorption peak are determined by the directional characteristic factor F 3 indicates that the transmittance at the characteristic wave number of the water vapor absorption peak in the well section t Si The frequency greater than 1.0 n 1 and frequencies less than 1.0 n 2 calculation, expressed as:

[0019] A further improvement of the present invention is that the water content is determined by constructing a composite characteristic factor F S Identification, expressed as:

[0020] If the composite characteristic factor F S If the composite characteristic factor is less than the threshold value of 0.8, the well section is judged as a non-aquifer. F S If the directional characteristic factor is greater than the threshold value of 0.8, the well section is judged to be an aquifer. Furthermore, for an aquifer, if the directional characteristic factor F 3 is greater than 0.5, then the aquifer is a saline layer. If the directional characteristic factor F 3 is less than -0.5, then the aquifer is freshwater. F3 is between -0.5 and 0.5, then rescan the spectrum and identify it.

[0021] Compared with the prior art, the present invention has the following beneficial effects: In the conventional identification of water layers in oil and gas exploration, the present invention adopts infrared spectroscopy instead of gas chromatography to analyze the wellhead gas released from the drilling fluid, which has the advantages of being fast, safe, sensitive and easy to maintain. In addition, the infrared spectrum of the wellhead gas also contains water vapor absorption peaks. The aquifer identification method established based on the characteristics of these water vapor absorption peaks can effectively avoid the problem of weak aquifer identification signals under complex conditions such as heterogeneous, low porosity and permeability, and low-resistance oil and gas reservoirs, and greatly improve the compliance rate of aquifer identification. By establishing a weighted composite factor and combining the direction, threshold and volatility of the water vapor absorption peak of the wellhead gas infrared spectrum, the accuracy and redundancy of the identification are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 Infrared spectrum gas logging system structure diagram; Figure 2 Structural diagram of the measuring chamber; Figure 3 Flow chart of a new aquifer identification method based on infrared spectroscopy gas logging; Figure 4 Standard water vapor infrared transmission spectrum; Figure 5 Infrared transmission spectra of different types of wellhead gas; Among them, 1. the first infrared window; 2. the second infrared window; 3. the air inlet of the air chamber; 4. the air outlet of the air chamber; 5. the three-way solenoid valve; 6. the first air inlet; 7. the second air inlet; 8. the air outlet; 9. the solenoid valve coil; 10. the constant temperature controller; 11. the heater; 12. the air pressure controller; 13. the air chamber. DETAILED DESCRIPTION

[0023] In order to further understand the content of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0024] See also Figure 1 The aquifer identification system based on infrared spectroscopy gas logging includes a Fourier transform infrared spectrometer, a measuring gas chamber, a humidity sensor, a temperature sensor, a pressure sensor, a core controller, a data transmission device, and an uninterruptible power supply (UPS).

[0025] Mud pumps, degassers and vacuum pumps are used to extract and separate wellhead gas from drilling fluid / mud and send it to infrared spectrum gas logging unit, hydrogen sensor and hydrogen sulfide sensor; The infrared spectrum gas logging unit is used to obtain the infrared spectrum of polar molecular components in the wellhead gas; The hydrogen sensor and hydrogen sulfide sensor are metal oxide semiconductor sensors used to detect the concentration of hydrogen and hydrogen sulfide in wellhead gas; The host computer is equipped with spectrum analysis software, which is used to analyze the infrared spectrum of wellhead gas, obtain the concentration of each component, and identify the water content of the reservoir based on the water vapor absorption peak of the infrared spectrum of wellhead gas.

[0026] The infrared spectrum gas logging unit includes a Fourier transform infrared spectrometer, a measuring gas chamber, a humidity sensor, a temperature sensor, a pressure sensor, a core controller, a data transmission device and an uninterruptible power supply; Fourier transform infrared spectrometer is used to scan the infrared spectrum of wellhead gas sample; The measuring gas chamber is used to collect gas samples at the wellhead; Humidity, temperature and pressure sensors to measure the humidity, temperature and pressure of the background gas; The core controller is used to collect humidity, temperature, and pressure data; The data transmission device is used to transmit humidity, temperature and pressure data to the host computer; UPS is used to ensure that the power supply to various parts of the system will not be suddenly interrupted.

[0027] See also Figure 2 The measuring air chamber includes an air chamber 13, an infrared window is arranged on the air chamber 13, the Fourier transform infrared spectrometer points to the infrared window, an air chamber air inlet 3, an air chamber air outlet 4 and an air pressure controller 12 are opened on the air chamber 13, a three-way solenoid valve 5 is arranged on the air chamber air inlet 3, a heater 11 is wrapped around the air chamber 13, a temperature sensor and a pressure sensor are arranged inside the air chamber 13, and a humidity sensor is arranged on the three-way solenoid valve 5; two infrared windows are arranged on the air chamber 13, namely, a first infrared window 1 and a second infrared window 2, and the first infrared window 1 and the second infrared window 2 are arranged opposite to each other. The first air inlet 6 of the three-way solenoid valve 5 is connected to the air end, the second air inlet 7 is connected to the degasser end, and the air outlet 8 is connected to the air chamber 13. The humidity sensor is arranged at the first air inlet 6, and the solenoid valve coil 9 of the three-way solenoid valve 5 is connected to the host computer. The heater 11 is connected to the constant temperature controller 10, and the constant temperature controller 10 is used to control the temperature of the heater 11.

[0028] The host computer sets the scanning parameters of the spectrometer, controls the three-way solenoid valve 5 of the measuring gas chamber to switch between air (background gas) and wellhead gas samples in turn, and controls the spectrometer to scan the background spectrum and the wellhead gas sample spectrum in turn. The detection results of the humidity, temperature, and pressure sensors are transmitted to the host computer via the core controller and the data transmission device. The UPS ensures that the power supply of each part of the system will not be suddenly interrupted. The analysis software in the host computer processes the in-situ spectrum of the wellhead gas to obtain the concentration of each component of the wellhead gas and the characteristics of the water vapor absorption peak. The threshold, fluctuation, composite, and directional characteristic factors are calculated based on the characteristics of the water vapor absorption peak, and the water layer identification results are obtained.

[0029] The process of the new aquifer identification method based on infrared spectroscopy gas logging is as follows: Figure 3 As shown. After the Fourier transform infrared spectrometer scans and obtains the in-situ infrared spectrum of the wellhead gas, the spectral analysis software in the host computer preprocesses the in-situ infrared spectrum of the wellhead gas. The preprocessing includes two steps: smoothing denoising and baseline correction. Smoothing denoising uses continuous convergence constraint analysis or Savitzky-Golay filter to eliminate high-frequency noise in the in-situ spectrum; the baseline correction uses segmented ratio correction or adaptive iterative reweighted penalty least squares to eliminate baseline drift; the feature screening uses Tikhonov regularization or forward and inverse model methods to improve modeling accuracy and efficiency and eliminate cross-influences between different components; the quantitative analysis uses partial least squares regression or neural network for modeling to obtain the concentration of each component. After preprocessing, the high-frequency noise of the wellhead gas infrared spectrum is effectively suppressed and the baseline drift is eliminated. The baseline of the absorption spectrum is basically 0, and the baseline of the transmission spectrum is basically 1.

[0030] Extract the 3715cm in the infrared spectrum of the wellhead gas after pretreatment -1 Up to 3440cm -1 and 2021cm -1 Up to 1600cm -1 The spectral lines in the two ranges are used as water vapor characteristic spectra. i Transmittance t Ri Subtract the first j The gas wave number i The transmittance at t Dji The original water vapor absorption characteristic transmittance with the interference of other components eliminated is obtained t i :

[0031] The background spectral transmittance corresponding to the humidity measurement results t Bi Wellhead gas infrared spectral transmittance ti Calculate the water vapor absorption peak transmittance t Si :

[0032] According to the measurement results of the humidity sensor x ,pass x Lower limit of the interval x 0 and upper limit x 1 corresponds to the standard humidity infrared spectrum transmittance t x0i and t x1i The background spectral transmittance is obtained by interpolation calculation t Bi :

[0033] According to the background spectral transmittance t Bi Wellhead gas infrared spectral transmittance t i Calculate the water vapor absorption peak transmittance t Si :

[0034] According to the water vapor absorption peak transmittance t Si The average absolute value of the difference from 1.0 M Calculate threshold characteristic factor F 1:

[0035] According to the water vapor absorption peak transmittance t Si The standard deviation of the absolute value of the difference from 1.0 S Calculate the volatility factor F 2:

[0036] according to F 1 and F 2. Constructing composite feature factors by weighted summation F S :

[0037] Determine whether it is an aquifer. If the composite characteristic factor F S If the composite characteristic factor is greater than the threshold value of 0.8, the well section is judged to be an aquifer. F SIf it is less than the threshold value of 0.8, the well section is judged as a non-aquifer.

[0038] If it is judged to be a water-containing layer, determine the direction of the water vapor absorption peak and calculate the water vapor absorption peak transmittance. t Si The frequency greater than 1.0 n The frequency of 1 and less than 1.0 n 2 Calculate the directional characteristic factor F 3:

[0039] For an aquifer, if the directional characteristic factor F 3 is less than -0.5, then the aquifer is freshwater. F 3 is greater than 0.5, then the aquifer is a saline layer. If the directional characteristic factor F 3 is between -0.5 and 0.5, then rescan the infrared spectrum of the wellhead gas and identify it again.

[0040] The standard concentration of water vapor is at 3997cm -1 Up to 3440cm -1 and 2021cm -1 Up to 1215cm -1 The infrared transmission spectra in the two ranges are as follows Figure 4 As shown. The concentrations of water vapor are 0.05% and 0.1% respectively. The pressure is 1atm, the temperature is 300K, the optical path is 80cm, and the fitting line type is the Voigt line type. The absorption peak of water vapor presents multiple sharp absorption peaks within the two characteristic bands, and P branches and R branches appear. The height of the absorption peak is related to the water vapor concentration. The higher the water vapor concentration, the stronger the absorption and the lower the transmittance.

[0041] The infrared transmission spectra of the wellhead gas in the water vapor characteristic band of the aquifer and non-aquifer at the actual logging site are as follows: Figure 5 As shown. The aquifer is a saltwater layer from an offshore oil field. Within the two characteristic ranges, the water vapor absorption peak of the transmission spectrum of the aquifer is upward, showing a peak, and the transmittance is greater than 1; the water vapor absorption peak of the transmission spectrum of the non-aquifer is downward, showing a peak valley, and the transmittance is less than 1. The water vapor absorption peaks between different aquifers are very different, while the water vapor absorption peaks between different non-aquifers are relatively stable and close to overlapping. At the same time, the water vapor absorption peak height of the aquifer is higher than that of the non-aquifer. In the infrared spectrum of the wellhead gas at the actual logging site, the water vapor absorption peaks of the aquifer and the non-aquifer show significant differences.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. Aquifer identification system based on infrared spectrum gas logging, characterized in that: It includes mud pump, degasser, vacuum pump, infrared spectrum gas logging unit, hydrogen sensor, hydrogen sulfide sensor and host computer; Mud pumps, degassers and vacuum pumps are used to extract and separate wellhead gas from drilling fluid / mud and send it to the infrared spectrum gas logging unit and hydrogen sensor; The infrared spectrum gas logging unit is used to obtain the infrared spectrum of polar molecular components in the wellhead gas; The hydrogen sensor and hydrogen sulfide sensor are metal oxide semiconductor sensors used to detect the concentration of hydrogen and hydrogen sulfide in wellhead gas; The host computer is equipped with spectrum analysis software, which is used to analyze the infrared spectrum of wellhead gas, obtain the concentration of each component, and identify the water content of the reservoir based on the water vapor absorption peak of the infrared spectrum of wellhead gas.

2. The aquifer identification system based on infrared spectrum gas logging according to claim 1 is characterized in that: The infrared spectrum gas logging unit includes a Fourier transform infrared spectrometer, a measuring gas chamber, a humidity sensor, a temperature sensor, a pressure sensor, a core controller, a data transmission device and an uninterruptible power supply; Fourier transform infrared spectrometer is used to scan the infrared spectrum of wellhead gas sample; The measuring gas chamber is used to collect wellhead gas samples; Humidity, temperature and pressure sensors to measure the humidity, temperature and pressure of the background gas; The core controller is used to collect humidity, temperature, and pressure data; The data transmission device is used to transmit humidity, temperature and pressure data to the host computer; UPS is used to ensure that the power supply to various parts of the system will not be suddenly interrupted.

3. The aquifer identification system based on infrared spectrum gas logging according to claim 1 is characterized in that: The measuring gas chamber is used to store the wellhead gas separated after degassing; The measuring air chamber comprises an air chamber (13), a first infrared window (1) and a second infrared window (2) are provided on the air chamber (13), light emitted by a Fourier transform infrared spectrometer passes through the infrared windows, an air inlet (3), an air outlet (4) and an air pressure controller (12) are provided on the air chamber (13), a three-way solenoid valve (5) is provided on the air chamber air inlet (3), a heater (11) is wound around the outside of the air chamber (13), a temperature sensor and a pressure sensor are provided in the air chamber (13), and a humidity sensor is provided on the three-way solenoid valve (5); The first air inlet (6) of the three-way solenoid valve (5) is connected to the air end, the second air inlet (7) is connected to the degasser end, the air outlet (8) is connected to the air chamber (13), the humidity sensor is arranged at the first air inlet (6), and the solenoid valve coil (9) of the three-way solenoid valve (5) is connected to the host computer; The heater (11) is connected to a constant temperature controller (10), and the constant temperature controller (10) is used to control the temperature of the heater (11).

4. A method for identifying aquifers based on infrared spectroscopy gas logging, characterized in that: The aquifer identification system based on infrared spectroscopy gas logging according to any one of claims 1 to 3 comprises the following steps: The wellhead gas separated after degassing is sent into the measuring gas chamber, and the background gas and the wellhead gas are sent into the gas chamber (13) in sequence through the three-way solenoid valve (5), and the infrared spectrum of the wellhead gas is scanned and transmitted to the upper computer together with the temperature, pressure and humidity data; The host computer analyzes the infrared spectrum of the wellhead gas based on the received data to obtain the concentration of each component and the characteristics of water vapor; The water content of the reservoir is identified based on the water vapor absorption peak threshold, fluctuation, and direction characteristics.

5. The method for identifying aquifers based on infrared spectrum gas logging according to claim 4 is characterized in that: The host computer analyzes the infrared spectrum of the wellhead gas based on the received data, and the specific method for obtaining the concentration of each component is as follows: The received data is smoothed, de-noised, baseline corrected, feature screened and quantitatively analyzed to obtain the concentration of each component; The smoothing denoising adopts continuous convergence constraint analysis or Savitzky-Golay filter to eliminate high-frequency noise in the in-situ spectrum; the baseline correction adopts segmented ratio correction or adaptive iterative reweighted penalty least squares to eliminate baseline drift; The feature screening adopts Tikhonov regularization or forward and inverse model methods to improve the modeling accuracy and efficiency and eliminate the cross-influence between different components; the quantitative analysis adopts partial least squares regression or neural network for modeling to obtain the concentration of each component.

6. The method for identifying aquifers based on infrared spectrum gas logging according to claim 4, characterized in that: The water vapor absorption peak characteristic is located at 3715 cm -1 Up to 3440cm -1 and 2021cm -1 Up to 1600cm -1 within the scope; According to the superposition of spectra, in the characteristic band of water vapor absorption, the original wellhead gas infrared spectrum is used to calculate the wave number i Transmittance t Ri Subtract the first j Gas at wave number i The transmittance at t Dji The original water vapor absorption characteristic transmittance with the interference of other components eliminated is obtained t i , to eliminate the interference of 7 components of alkanes, carbon monoxide, carbon dioxide and nitrous oxide on water vapor analysis, the calculation formula is: Background spectral transmittance corresponding to humidity sensor measurement results t Bi The relative humidity is divided into intervals of 10%RH by standard humidity infrared spectrum calculation, and the lower limit of the interval to which the humidity measurement result belongs x 0 and upper limit x 1 corresponds to the standard humidity infrared spectrum transmittance t x0i and t x1i Interpolation calculation, coefficients f 1 and f 2 is obtained by fitting the standard humidity infrared spectrum, and the calculation formula is: Water vapor absorption peak transmittance t Si Spectral transmittance through background t Bi The characteristic transmittance of the original water vapor absorption t i Calculation, the calculation formula is: 。 7. The method for identifying aquifers based on infrared spectrum gas logging according to claim 4, characterized in that: The water vapor absorption peak threshold characteristic is characterized by a threshold characteristic factor F 1 means that according to the water vapor absorption peak in the well section i The transmittance at the characteristic wave number t Si The average absolute value of the difference from 1.0 M Calculation, expressed as: 。 8. The method for identifying aquifers based on infrared spectrum gas logging according to claim 4, characterized in that: The water vapor absorption peak fluctuation characteristics are characterized by the fluctuation characteristic factor F 2 indicates that the transmittance at the characteristic wave number of the water vapor absorption peak in the well section t Si The standard deviation of the absolute value of the difference from 1.0 S Calculation, expressed as: 。 9. The method for identifying aquifers based on infrared spectrum gas logging according to claim 4, characterized in that: The directional characteristics of the water vapor absorption peak are determined by the directional characteristic factor F 3 indicates that the transmittance at the characteristic wave number of the water vapor absorption peak in the well section t Si The frequency greater than 1.0 n 1 and frequencies less than 1.0 n 2 calculation, expressed as: 。 10. The method for identifying aquifers based on infrared spectrum gas logging according to claim 4, characterized in that: The water content is obtained by constructing a composite characteristic factor F S Identification, expressed as: If the composite characteristic factor F S If the composite characteristic factor is less than the threshold value of 0.8, the well section is judged as a non-aquifer. F S If the directional characteristic factor is greater than the threshold value of 0.8, the well section is judged to be an aquifer. Furthermore, for an aquifer, if the directional characteristic factor F 3 is greater than 0.5, then the aquifer is a saline layer. If the directional characteristic factor F 3 is less than -0.5, then the aquifer is freshwater. F 3 is between -0.5 and 0.5, then rescan the spectrum and identify it.

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