High-temperature hydrothermal fluid in-situ pH measurement method based on ionization equilibrium Raman spectrum characteristics of hydrogen sulfide and hydrosulfide ions

Abstract

The invention provides a high-temperature hydrothermal fluid in-situ pH measurement method based on ionization equilibrium Raman spectrum characteristics of hydrogen sulfide and hydrosulfide ions. The method comprises the steps of establishing a Raman spectrum calibration model, calculating pK1 and pH, performing in-situ pH actual measurement and the like. Raman spectrum measurement is carried out on H2S and HS-mixed solutions at different temperatures and pressures, the pH value is calculated in combination with specific calculation formulas and equations, and data acquisition and processing are carried out by loading a probe on a remote control submersible. The invention relates to the technical field of hydrothermal fluid pH measurement. According to the method, the in-situ pH of the high-temperature hydrothermal fluid can be accurately measured in real time, data are accurate and real, and sample transfer errors are avoided; the electrode adapts to high-temperature and high-pressure environments and overcomes the limitation of a traditional electrode; the real-time dynamic monitoring capability is realized, and the method is suitable for researching a rapidly changing geochemical process; multiple parameters can be measured synchronously, and more comprehensive chemical information of the hydrothermal system is provided.

Description

Technical Field

[0001] The invention relates to the technical field of hydrothermal fluid pH measurement, and in particular to an in-situ pH measurement method for high-temperature hydrothermal fluid based on Raman spectral characteristics of ionization equilibrium of hydrogen sulfide and hydrogen sulfide ions. Background Art

[0002] The pH value of hydrothermal fluids is a key parameter that controls the chemical reaction rate, mineral solubility, and element migration behavior in hydrothermal systems. It has an important impact on the formation of ore deposits, the evolution of hydrothermal systems, and microbial ecosystems. Accurately measuring the pH value in hydrothermal fluids is of great significance for understanding the chemical processes in the Earth's interior. However, there are many difficulties in the in-situ pH measurement of high-temperature hydrothermal fluids, such as high temperature and high pressure environment, chemical complexity, in-situ measurement challenges, and dynamically changing fluid properties.

[0003] The existing methods for measuring hydrothermal pH include conventional laboratory pH electrode measurement and in-situ measurement using zirconia electrodes. However, these methods have disadvantages such as the original pH value deviation caused by the transition of the hydrothermal fluid from a high temperature and high pressure environment to a normal temperature and pressure environment, the measurement equipment being easily damaged in extreme environments, and the slow response speed inability to capture pH changes in real time. Summary of the invention

[0004] The present invention aims to provide a method for accurately and in real time measuring the in-situ pH of a high-temperature hydrothermal fluid, thereby overcoming the deficiencies of the existing measurement methods. In view of the deficiencies of the prior art, the present invention adopts a technical solution to solve the technical problems thereof: a method for measuring the in-situ pH of a high-temperature hydrothermal fluid based on the Raman spectral characteristics of the ionization equilibrium of hydrogen sulfide and hydrogen sulfide ions, comprising the following steps:

[0005] Step 1: First, at different temperatures and pressures, the concentrations of H2S and HS - The mixed solution is subjected to Raman spectroscopy measurement, and the measurement data includes the following aspects:

[0006] Raman scattered light intensity measures the intensity of Raman scattered light generated by the sample under laser irradiation. Different substances have different Raman scattering cross sections.

[0007] Raman shift refers to the frequency difference between Raman scattered light and incident light. Different substances have specific Raman shifts, and the type of substance can be determined by measuring the Raman shift.

[0008] Spectral resolution refers to the smallest wavelength difference that a Raman spectrometer can distinguish;

[0009] Signal-to-noise ratio, which represents the ratio of Raman signal to noise;

[0010] Secondly, by analyzing the measurement data, the H2S and HS - Raman spectroscopy calibration model;

[0011] Step 2: Calculate pK1, calculate H2S and HS - The ionization equilibrium constant pK1 decreases with increasing temperature, indicating that as the temperature increases, H2S ionizes into HS - The specific ionization process is as follows:

[0012] From the perspective of chemical thermodynamics, the ionization process of H2S is an endothermic reaction. The hydrolysis of ions and the destruction of chemical bonds in the solute are both endothermic. According to Le Chatelier's principle, when the temperature rises, the reaction will move in the endothermic direction, that is, it will promote the ionization of H2S, thereby increasing the ionization equilibrium constant, indicating that under high temperature environment, H2S molecules will be ionized into HS - The speed of HS - The concentration of increases relatively, and the concentration of H2S decreases relatively, that is, the value of pK1 decreases;

[0013] Step 3: Calculate pH: Based on the Henderson-Hasselbalch equation, the pH of H2S and HS - The pH value of the hydrothermal fluid is calculated based on the concentration ratio of and the calculated pK1 value;

[0014] Step 4: In-situ measurement of the pH value of high-temperature hydrothermal fluids. A high-temperature tolerant Raman probe is loaded onto a remotely operated submersible and inserted into the hydrothermal vent for data collection. The collected data is then processed and analyzed to finally obtain the pH value of the hydrothermal fluid.

[0015] Preferably, the H2S and HS - The establishment of the Raman spectroscopy calibration model includes the following steps:

[0016] Step 1: Sample preparation: prepare a sample of H2S and HS with known concentrations - Mixed solution, as a reference feature, prepared different concentrations of H2S and HS using a high temperature and high pressure reactor - The mixed solution, the temperature of the reactor was set at 100°C, 150°C, 200°C and 250°C, and the pressure was controlled at 5MPa-50MPa;

[0017] Step 2: Raman spectrum acquisition, using a high temperature resistant Raman spectrum probe to collect H2S and HS at known concentrations at each temperature - The mixed solution was subjected to Raman spectroscopy measurement, and each temperature point was measured at least three times;

[0018] Step 3: Spectral processing and data analysis, collect Raman spectra, obtain acquisition signals, which include Raman scattered light signals, background noise signals and fluorescence signals. Set the exposure time and accumulation times according to the quality of the acquisition signals. The setting method is as follows:

[0019] First, collect an initial Raman spectrum and observe the signal intensity and signal-to-noise ratio. The signal-to-noise ratio is the ratio of the Raman signal intensity to the background noise intensity. The larger the ratio, the better the signal quality. When the signal intensity decreases, the signal-to-noise ratio is low. The signal quality can be improved by increasing the exposure time and the number of accumulations. According to the characteristics of the sample, different samples respond differently to the laser. For samples that are prone to photobleaching or thermal damage, shorten the exposure time. If the sample has fluorescence interference, adjust the laser wavelength or use fluorescence suppression technology. At the same time, adjust the exposure time and the number of accumulations according to the fluorescence intensity. Gradually adjust the parameters, first increase the exposure time, observe the changes in signal intensity and signal-to-noise ratio. If the signal intensity increases, but the noise also increases, increase the number of accumulations, average out the random noise, and improve the signal-to-noise ratio, but it will also increase the measurement time. Therefore, it is necessary to balance the signal quality and measurement time. After each parameter adjustment, re-collect the spectrum and evaluate the signal quality until a high signal-to-noise ratio is reached, that is, the signal-to-noise ratio is greater than 10, and the signal-to-noise ratio remains stable in multiple measurements, and the test can be repeated.

[0020] The collected Raman spectra are baseline corrected to obtain the corrected spectra, which are used to eliminate the influence of noise and background signals on the peak area. In the corrected spectra, H2S and HS - The Raman peak positions of H2S and HS were calculated by integrating these peaks using GRAM / AI software. - The Raman peak area and And at the same time calculate the water level is 2800-3900cm -1 The area of ​​the OH stretching vibration peak

[0021] Step 4: Model establishment, H2S and HS - The ratio of the Raman peak area of ​​​​to the Raman peak area of ​​​​water and With known concentrations of H2S and HS - Linear fitting was performed to obtain H2S and HS - The calibration model:

[0022]

[0023] in, and Represents H2S and HS respectively - The concentration of H2S and HS is in mmol / kg. The experimental results show that the change of temperature has a great influence on the - The quantitative analysis of H2S is less affected, so the calibration model is also applicable under high temperature conditions and can accurately reflect the quantitative analysis of H2S and HS at different temperatures. -in situ concentration.

[0024] Preferably, the calculation method of pK1 is as follows:

[0025] pK1 is the difference between H2S and HS - The constant of the ionization equilibrium between H2S and HS in high temperature aqueous solution varies with temperature. - The ionization equilibrium of the experiment was tested to obtain the temperature-dependent pK1 experimental calculation formula. The specific calculation formula is as follows:

[0026]

[0027] Where T is the fluid temperature in Kelvin K. Through this formula, the H2S and HS at different temperatures can be accurately calculated. - The equilibrium constant pK1 between them is then used to calculate the in situ pH value.

[0028] The pH is calculated as follows:

[0029] Based on the Henderson-Hasselbalch equation, H2S and HS - The pH value of the hydrothermal fluid is calculated by the concentration ratio of

[0030]

[0031] in, and HS - The Raman peak area of ​​​​H2S is obtained through Raman spectroscopy measurement. Combined with the calculation result of pK1, the real-time pH value of the fluid can be obtained

[0032] Preferably, the step of measuring the in-situ pH of the high-temperature hydrothermal fluid comprises the following steps:

[0033] Step 1: Collection of hydrothermal in-situ data. Before conducting measurements in the seafloor hydrothermal vent area, first use the remotely operated submersible ROV to load the high-temperature tolerant Raman probe RiP-Hv. The probe is installed on the robotic arm of the ROV. The robotic arm can control the movement and insertion depth of the probe, so that the probe can be stably inserted into the hydrothermal vent during measurement. After the ROV arrives at the target hydrothermal vent, the ROV controls the robotic arm to insert the Raman probe into the center area of ​​the hydrothermal vent. Insert it as deep as possible to reduce the possibility of seawater mixing, and ensure that the probe is in a high-temperature and high-pressure environment of the fluid. After the probe is in place, start the Raman spectrometer for data collection. The same vent can be measured repeatedly for multiple times. After the data collection is completed, the probe is removed from the vent by the ROV and moved to the next measurement point to repeat the above steps until the measurement is completed. The ROV is recovered and the data is extracted;

[0034] Step 2: Hydrothermal in-situ data processing and analysis. After the ROV is recovered and the data is extracted, the collected Raman spectra are preliminarily processed using HoloGRAMS software, and further baseline correction is performed using GRAM / AI software to eliminate the interference of noise and background signals and ensure the accuracy of the peak area. According to the calibration model, H2S and HS - The Raman peak position of H2S is about 2590cm -1 , HS - The Raman peak is located at about 2573cm -1 , these peaks are integrated by software to calculate H2S and HS - The peak area and and the OH stretching vibration peak area of ​​water Compare and obtain the H2S and HS in the fluid - concentration;

[0035] Step 3: Obtaining the in-situ pH value of hydrothermal fluids, using Raman spectroscopy to obtain H2S and HS - The peak area ratio Combined with the calculated pK1 value, the pH value of the hydrothermal fluid was calculated using the Henderson-Hasselbalch equation.

[0036] Preferably, an intelligent fusion baseline algorithm is used to perform baseline correction on the collected Raman spectrum, using morphological filtering to quickly extract baseline trends, adaptive weighting to highlight data points that deviate from the baseline, and the flexibility of polynomial fitting, to achieve more accurate Raman spectrum baseline correction through intelligent iterative optimization. The specific correction method is as follows:

[0037] Step 1: Data preprocessing: preliminary observation and analysis of the original Raman spectrum S(x) to determine possible outliers or noise points. If there are outliers, use robust statistical methods to eliminate them.

[0038] Step 2: Morphological rough extraction, select the structural element E(x), perform a combination of morphological opening and closing operations on the original Raman spectrum S(x), and obtain a rough estimated baseline B1(x), where:

[0039] The opening operation is defined as

[0040] The closing operation is defined as S·E(x)=max{S(xt)-E(t)};

[0041] In the above formula, t represents a variable parameter, which is used to perform translation operation in the morphological operation process;

[0042] After the combination operation, we get Where m represents the number of opening operations, and n represents the number of closing operations;

[0043] Step 3: Adaptive weight calculation: calculate the difference between the original Raman spectrum S(x) and the rough estimated baseline B1(x) D1(x) = S(x) - B1(x), and design the adaptive weight function w(x) = 1 + γ × exp(δ × |D1(x)| ò ), where γ, δ, and ò are tuning parameters;

[0044] Step 4: Polynomial fine fitting, using weighted polynomial fitting method, assuming the polynomial function is Minimize the weighted function By solving the system of equations Determination coefficient a i ;

[0045] Step 5: Iterative optimization and convergence judgment. The obtained polynomial fitting function is used as the new baseline estimate B2(x)=P(x), and the new difference D2(x)=S(x)-B2(x) is calculated. The weight ω(x) is updated and steps 4 and 5 are repeated until the convergence condition is met, that is, the baseline change obtained from two consecutive iterations is less than the threshold τ, ||B k+1 (x)-B k (x)||<τ, where k is the number of iterations;

[0046] Step 6: Post-processing and result output. When the iteration converges, the final baseline function B(x) is obtained. The spectrum S after baseline correction is corrected (x) = S(x) - B(x) is further smoothed to output the corrected Raman spectrum.

[0047] The beneficial effects of the present invention are as follows:

[0048] Data accuracy and authenticity: The present invention can measure pH in situ, avoiding chemical changes in the fluid during sample transfer. The measured data is more accurate and can truly reflect the pH value of the hydrothermal fluid in the natural environment.

[0049] Adaptability to high temperature and high pressure environments: The combination of Raman spectroscopy and high temperature tolerance probes enables the present invention to work in extreme environments and is suitable for harsh conditions such as deep-sea hydrothermal vents, overcoming the limitations of traditional electrodes.

[0050] Real-time and dynamic monitoring capabilities: The present invention can capture pH changes of hydrothermal fluids in real time and provide dynamic monitoring data, which is suitable for studying rapidly changing geochemical processes in hydrothermal systems.

[0051] Multi-parameter simultaneous measurement: In addition to pH measurement, the present invention can also obtain other important chemical parameters such as H2S and HS through Raman spectroscopy -concentrations, providing more comprehensive information on the chemistry of the hydrothermal system. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 (a) and (b) are the Raman spectra quantitative curves of hydrogen sulfide and hydrogen sulfide ions of the present invention respectively.

[0053] Figure 2 (a), (b), (c) and (d) are the Raman spectra of the Jade hydrothermal fluid of the present invention, the Raman spectra of the Biwako hydrothermal fluid, the Raman spectra of the Onsen hydrothermal fluid and the Raman spectra of the Faxian hydrothermal fluid, respectively;

[0054] Figure 3 is the in-situ pH value of the fluids in different hydrothermal areas of the present invention; DETAILED DESCRIPTION

[0055] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0056] Example:

[0057] The present invention provides a technical solution: a method for measuring the in-situ pH of a high-temperature hydrothermal fluid based on the Raman spectrum characteristics of the ionization equilibrium of hydrogen sulfide and hydrogen sulfide ions, comprising the following steps:

[0058] Step 1: First, at different temperatures and pressures, the concentrations of H2S and HS - The mixed solution is subjected to Raman spectroscopy measurement, and the measurement data includes the following aspects:

[0059] Raman scattered light intensity measures the intensity of Raman scattered light generated by the sample under laser irradiation. Different substances have different Raman scattering cross sections.

[0060] Raman shift refers to the frequency difference between Raman scattered light and incident light. Different substances have specific Raman shifts, and the type of substance can be determined by measuring the Raman shift.

[0061] Spectral resolution refers to the smallest wavelength difference that a Raman spectrometer can distinguish;

[0062] Signal-to-noise ratio, which represents the ratio of Raman signal to noise;

[0063] Secondly, by analyzing the measurement data, the H2S and HS- Raman spectroscopy calibration model;

[0064] Step 2: Calculate pK1, calculate H2S and HS - The ionization equilibrium constant pK1 decreases with increasing temperature, indicating that as the temperature increases, H2S ionizes into HS - The specific ionization process is as follows:

[0065] From the perspective of chemical thermodynamics, the ionization process of H2S is an endothermic reaction. The hydrolysis of ions and the destruction of chemical bonds in the solute are both endothermic. According to Le Chatelier's principle, when the temperature rises, the reaction will move in the endothermic direction, that is, it will promote the ionization of H2S, thereby increasing the ionization equilibrium constant, indicating that under high temperature environment, H2S molecules will be ionized into HS - The speed of HS - The concentration of increases relatively, and the concentration of H2S decreases relatively, that is, the value of pK1 decreases;

[0066] Step 3: Calculate pH: Based on the Henderson-Hasselbalch equation, the pH of H2S and HS - The pH value of the hydrothermal fluid is calculated based on the concentration ratio of and the calculated pK1 value;

[0067] Step 4: In-situ measurement of the pH value of high-temperature hydrothermal fluids. A high-temperature tolerant Raman probe is loaded onto a remotely operated submersible and inserted into the hydrothermal vent for data collection. The collected data is then processed and analyzed to finally obtain the pH value of the hydrothermal fluid.

[0068] The H2S and HS - The establishment of the Raman spectroscopy calibration model includes the following steps:

[0069] Step 1: Sample preparation: prepare a sample of H2S and HS with known concentrations - Mixed solution, as a reference feature, prepared different concentrations of H2S and HS using a high temperature and high pressure reactor - The mixed solution, the temperature of the reactor was set at 100°C, 150°C, 200°C and 250°C, and the pressure was controlled at 5MPa-50MPa;

[0070] Step 2: Raman spectrum acquisition, using a high temperature resistant Raman spectrum probe to collect H2S and HS at known concentrations at each temperature - The mixed solution was subjected to Raman spectroscopy measurement, and each temperature point was measured at least three times;

[0071] Step 3: Spectral processing and data analysis, collect Raman spectra, obtain acquisition signals, which include Raman scattered light signals, background noise signals and fluorescence signals. Set the exposure time and accumulation times according to the quality of the acquisition signals. The setting method is as follows:

[0072] First, collect an initial Raman spectrum and observe the signal intensity and signal-to-noise ratio. The signal-to-noise ratio is the ratio of the Raman signal intensity to the background noise intensity. The larger the ratio, the better the signal quality. When the signal intensity decreases, the signal-to-noise ratio is low. The signal quality can be improved by increasing the exposure time and the number of accumulations. According to the characteristics of the sample, different samples respond differently to the laser. For samples that are prone to photobleaching or thermal damage, shorten the exposure time. If the sample has fluorescence interference, adjust the laser wavelength or use fluorescence suppression technology. At the same time, adjust the exposure time and the number of accumulations according to the fluorescence intensity. Gradually adjust the parameters, first increase the exposure time, observe the changes in signal intensity and signal-to-noise ratio. If the signal intensity increases, but the noise also increases, increase the number of accumulations, average out the random noise, and improve the signal-to-noise ratio, but it will also increase the measurement time. Therefore, it is necessary to balance the signal quality and measurement time. After each parameter adjustment, re-collect the spectrum and evaluate the signal quality until a high signal-to-noise ratio is reached, that is, the signal-to-noise ratio is greater than 10, and the signal-to-noise ratio remains stable in multiple measurements, and the test can be repeated.

[0073] The collected Raman spectra are baseline corrected to obtain the corrected spectra, which are used to eliminate the influence of noise and background signals on the peak area. In the corrected spectra, H2S and HS - The Raman peak positions of H2S and HS were calculated by integrating these peaks using GRAM / AI software. - The Raman peak area and And at the same time calculate the water level is 2800-3900cm -1 The area of ​​the OH stretching vibration peak

[0074] Step 4: Model establishment, H2S and HS - The ratio of the Raman peak area of ​​​​to the Raman peak area of ​​​​water and With known concentrations of H2S and HS - Linear fitting was performed to obtain H2S and HS - The calibration model:

[0075]

[0076] in, and Represents H2S and HS respectively -The concentration of H2S and HS is in mmol / kg. The experimental results show that the change of temperature has a great influence on the - The quantitative analysis of H2S is less affected, so the calibration model is also applicable under high temperature conditions and can accurately reflect the quantitative analysis of H2S and HS at different temperatures. - in situ concentration.

[0077] The calculation method of pK1 is as follows:

[0078] pK1 is the difference between H2S and HS - The constant of the ionization equilibrium between H2S and HS in high temperature aqueous solution varies with temperature. - The ionization equilibrium of the experiment was tested to obtain the temperature-dependent pK1 experimental calculation formula. The specific calculation formula is as follows:

[0079]

[0080] Where T is the fluid temperature in Kelvin K. Through this formula, the H2S and HS at different temperatures can be accurately calculated. - The equilibrium constant pK1 between them is then used to calculate the in situ pH value.

[0081] The pH is calculated as follows:

[0082] Based on the Henderson-Hasselbalch equation, H2S and HS - The pH value of the hydrothermal fluid is calculated by the concentration ratio of

[0083]

[0084] in, and HS - The Raman peak area of ​​​​H2S is obtained through Raman spectroscopy measurement. Combined with the calculation result of pK1, the real-time pH value of the fluid can be obtained

[0085] The in-situ pH measurement procedure of high-temperature hydrothermal fluids includes the following steps:

[0086] Step 1: Collection of hydrothermal in-situ data. Before conducting measurements in the seafloor hydrothermal vent area, first use the remotely operated submersible ROV to load the high-temperature tolerant Raman probe RiP-Hv. The probe is installed on the robotic arm of the ROV. The robotic arm can control the movement and insertion depth of the probe, so that the probe can be stably inserted into the hydrothermal vent during measurement. After the ROV arrives at the target hydrothermal vent, the ROV controls the robotic arm to insert the Raman probe into the center area of ​​the hydrothermal vent. Insert it as deep as possible to reduce the possibility of seawater mixing, and ensure that the probe is in a high-temperature and high-pressure environment of the fluid. After the probe is in place, start the Raman spectrometer for data collection. The same vent can be measured repeatedly for multiple times. After the data collection is completed, the probe is removed from the vent by the ROV and moved to the next measurement point to repeat the above steps until the measurement is completed. The ROV is recovered and the data is extracted;

[0087] Step 2: Hydrothermal in-situ data processing and analysis. After the ROV is recovered and the data is extracted, the collected Raman spectra are preliminarily processed using HoloGRAMS software, and further baseline correction is performed using GRAM / AI software to eliminate the interference of noise and background signals and ensure the accuracy of the peak area. According to the calibration model, H2S and HS - The Raman peak position of H2S is about 2590cm -1 , HS - The Raman peak is located at about 2573cm -1 , these peaks are integrated by software to calculate H2S and HS - The peak area and and the OH stretching vibration peak area of ​​water Compare and obtain the H2S and HS in the fluid - concentration;

[0088] Step 3: Obtaining the in-situ pH value of hydrothermal fluids, using Raman spectroscopy to obtain H2S and HS - The peak area ratio Combined with the calculated pK1 value, the pH value of the hydrothermal fluid was calculated using the Henderson-Hasselbalch equation.

[0089] The baseline correction of the collected Raman spectrum is performed using an intelligent fusion baseline algorithm. Morphological filtering is used to quickly extract baseline trends, adaptive weighting is used to highlight data points that deviate from the baseline, and the flexibility of polynomial fitting is used to achieve more accurate Raman spectrum baseline correction through intelligent iterative optimization. The specific correction method is as follows:

[0090] Step 1: Data preprocessing: preliminary observation and analysis of the original Raman spectrum S(x) to determine possible outliers or noise points. If there are outliers, use robust statistical methods to eliminate them.

[0091] Step 2: Morphological rough extraction, select the structural element E(x), perform a combination of morphological opening and closing operations on the original Raman spectrum S(x), and obtain a rough estimated baseline B1(x), where:

[0092] The opening operation is defined as

[0093] The closing operation is defined as S·E(x)=max{S(xt)-E(t)};

[0094] In the above formula, t represents a variable parameter, which is used to perform translation operation in the morphological operation process;

[0095] After the combination operation, we get Where m represents the number of opening operations, and n represents the number of closing operations;

[0096] Step 3: Adaptive weight calculation: calculate the difference between the original Raman spectrum S(x) and the rough estimated baseline B1(x) D1(x) = S(x) - B1(x), and design the adaptive weight function w(x) = 1 + γ × exp(δ × |D1(x)| ò ), where γ, δ, and ò are tuning parameters;

[0097] Step 4: Polynomial fine fitting, using weighted polynomial fitting method, assuming the polynomial function is Minimize the weighted function By solving the system of equations Determination coefficient a i ;

[0098] Step 5: Iterative optimization and convergence judgment. The obtained polynomial fitting function is used as the new baseline estimate B2(x)=P(x), and the new difference D2(x)=S(x)-B2(x) is calculated. The weight ω(x) is updated and steps 4 and 5 are repeated until the convergence condition is met, that is, the baseline change obtained from two consecutive iterations is less than the threshold τ, ||B k+1 (x)-B k (x)||<τ, where k is the number of iterations;

[0099] Step 6: Post-processing and result output. When the iteration converges, the final baseline function B(x) is obtained. The spectrum S after baseline correction is corrected (x) = S(x) - B(x) is further smoothed to output the corrected Raman spectrum.

[0100] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A method for measuring the in-situ pH of high-temperature hydrothermal fluids based on the Raman spectral characteristics of the ionization equilibrium of hydrogen sulfide and hydrogen sulfide ions, characterized in that: The following steps are involved: Step 1: First, at different temperatures and pressures, the concentrations of H2S and HS - The mixed solution is subjected to Raman spectroscopy measurement, and the measurement data includes the following aspects: Raman scattered light intensity, measuring the intensity of Raman scattered light generated by the sample under laser irradiation; Raman shift, which represents the frequency difference between the Raman scattered light and the incident light; Spectral resolution refers to the smallest wavelength difference that a Raman spectrometer can distinguish; Signal-to-noise ratio, which represents the ratio of Raman signal to noise; Secondly, the Raman spectroscopy calibration model of H2S and HS- is established by analyzing the measurement data; Step 2: Calculate pK1, calculate the ionization equilibrium constant pK1 between H2S and HS-. This constant decreases with increasing temperature, indicating that as the temperature increases, the degree of H2S ionization into HS- increases. The specific ionization process is as follows: When the temperature rises, the reaction will move in the endothermic direction, that is, the ionization of H2S is promoted, thereby increasing the ionization equilibrium constant, which means that under high temperature environment, the speed of H2S molecules ionizing into HS- is accelerated, resulting in a relative increase in the concentration of HS- and a relative decrease in the concentration of H2S, that is, the value of pK1 will decrease; Step 3: Calculate pH: Based on the Henderson-Hasselbalch equation, the pH value of the hydrothermal fluid is calculated by the concentration ratio of H2S and HS- and the calculated pK1 value; Step 4: In-situ measurement of the pH value of high-temperature hydrothermal fluids. A high-temperature tolerant Raman probe is loaded onto a remotely operated submersible and inserted into the hydrothermal vent for data collection. The collected data is then processed and analyzed to finally obtain the pH value of the hydrothermal fluid.

2. The in-situ pH measurement method for high-temperature hydrothermal fluid based on the Raman spectrum characteristics of hydrogen sulfide and hydrogen sulfide ion ionization equilibrium according to claim 1 is characterized in that: The H2S and HS - The establishment of the Raman spectroscopy calibration model includes the following steps: Step 1: Sample preparation: prepare a sample of H2S and HS with known concentrations - Mixed solution, as a reference feature, prepared different concentrations of H2S and HS using a high temperature and high pressure reactor - The mixed solution, the temperature of the reactor was set at 100°C, 150°C, 200°C and 250°C, and the pressure was controlled at 5MPa-50MPa; Step 2: Raman spectrum acquisition, using a high temperature resistant Raman spectrum probe to collect H2S and HS at known concentrations at each temperature - The mixed solution was subjected to Raman spectroscopy measurement, and each temperature point was measured at least three times; Step 3: Spectral processing and data analysis, collect Raman spectra, obtain collected signals, which include Raman scattered light signals, background noise signals and fluorescence signals, and set exposure time and accumulation times according to the quality of collected signals; Step 4: Model establishment, the ratio of the Raman peak area of ​​H2S and HS- to the Raman peak area of ​​water and With known concentrations of H2S and HS - Linear fitting was performed to obtain H2S and HS - The calibration model: in, and Represents H2S and HS respectively - The concentration is in mmol / kg.

3. The in-situ pH measurement method for high-temperature hydrothermal fluid based on the Raman spectrum characteristics of hydrogen sulfide and hydrogen sulfide ion ionization equilibrium according to claim 1 is characterized in that: The calculation method of pK1 is as follows: By conducting experiments on the ionization equilibrium of H2S and HS- in high-temperature aqueous solutions, the temperature-dependent pK1 experimental calculation formula is obtained. The specific calculation formula is as follows: Where T is the fluid temperature in Kelvin K; The pH is calculated as follows: Based on the Henderson-Hasselbalch equation, H2S and HS - The pH value of the hydrothermal fluid is calculated by the concentration ratio of in, and HS - The Raman peak areas of NH4+ and H2S were measured by Raman spectroscopy.

4. The in-situ pH measurement method for high-temperature hydrothermal fluid based on the Raman spectrum characteristics of hydrogen sulfide and hydrogen sulfide ion ionization equilibrium according to claim 1 is characterized in that: The in-situ pH measurement procedure of high-temperature hydrothermal fluids includes the following steps: Step 1: Collection of hydrothermal in-situ data. Before conducting measurements in the seafloor hydrothermal vent area, first use the remotely operated submersible ROV to load the high-temperature tolerant Raman probe RiP-Hv. The probe is installed on the ROV's mechanical arm, which can control the movement and insertion depth of the probe. After the ROV arrives at the target hydrothermal vent, the ROV controls the mechanical arm to insert the Raman probe into the center of the hydrothermal vent. After the probe is in place, the Raman spectrometer is started for data collection. The same vent can be measured repeatedly. After the data collection is completed, the probe is removed from the vent by the ROV and moved to the next measurement point to repeat the above steps until the measurement is completed. The ROV is recovered and the data is extracted. Step 2: Hydrothermal in-situ data processing and analysis. After the ROV is recovered and the data is extracted, the collected Raman spectra are preliminarily processed and further baseline correction is performed. According to the calibration model, H2S and HS - The Raman peak position of H2S is at about 2590cm -1 , HS - The Raman peak is located at about 2573cm -1 , calculate H2S and HS - The peak area and and the OH stretching vibration peak area of ​​water Compare and obtain the concentration of H2S and HS- in the fluid; Step 3: Obtaining the in-situ pH value of the hydrothermal fluid and the peak area ratio of H2S and HS- obtained by Raman spectroscopy Combined with the calculated pK1 value, the pH value of the hydrothermal fluid was calculated using the Henderson-Hasselbalch equation.

5. The in-situ pH measurement method for high-temperature hydrothermal fluid based on the Raman spectrum characteristics of hydrogen sulfide and hydrogen sulfide ion ionization equilibrium according to claim 2 is characterized in that: The baseline correction of the collected Raman spectrum is performed using an intelligent fusion baseline algorithm. Morphological filtering is used to quickly extract baseline trends, adaptive weighting is used to highlight data points that deviate from the baseline, and the flexibility of polynomial fitting is used to achieve more accurate Raman spectrum baseline correction through intelligent iterative optimization. The specific correction method is as follows: Step 1: Data preprocessing: preliminary observation and analysis of the original Raman spectrum S(x) to determine possible outliers or noise points. If there are outliers, use robust statistical methods to eliminate them. Step 2: Morphological rough extraction, select the structural element E(x), perform a combination of morphological opening and closing operations on the original Raman spectrum S(x), and obtain a rough estimated baseline B1(x), where: The opening operation is defined as The closing operation is defined as S·E(x)=max{S(xt)-E(t)}; In the above formula, t represents a variable parameter, which is used to perform translation operation during morphological operation; After the combination operation, we get Where m represents the number of opening operations, and n represents the number of closing operations; Step 3: Adaptive weight calculation: calculate the difference between the original Raman spectrum S(x) and the rough estimated baseline B1(x) D1(x) = S(x) - B1(x), and design the adaptive weight function w(x) = 1 + γ × exp(δ × |D1(x)| ò ), where γ, δ, and ò are tuning parameters; Step 4: Polynomial fine fitting, using weighted polynomial fitting method, assuming the polynomial function is Minimize the weighted function By solving the system of equations Determination coefficient a i ; Step 5: Iterative optimization and convergence judgment. The obtained polynomial fitting function is used as the new baseline estimate B2(x)=P(x), and the new difference D2(x)=S(x)-B2(x) is calculated. The weight ω(x) is updated and steps 4 and 5 are repeated until the convergence condition is met, that is, the baseline change obtained from two consecutive iterations is less than the threshold τ, B k+1 (x)-B k (x)<τ, where k is the number of iterations; Step 6: Post-processing and result output. When the iteration converges, the final baseline function B(x) is obtained. The baseline-corrected spectrum S corrected (x) = S(x) - B(x) is further smoothed to output the corrected Raman spectrum.

6. The in-situ pH measurement method for high-temperature hydrothermal fluid based on the Raman spectrum characteristics of hydrogen sulfide and hydrogen sulfide ion ionization equilibrium according to claim 2 is characterized in that: The method for setting the exposure time and accumulation times according to the quality of the collected signal is as follows: First, collect an initial Raman spectrum and observe the signal intensity and signal-to-noise ratio. The signal-to-noise ratio is the ratio of the Raman signal intensity to the background noise intensity. The larger the ratio, the better the signal quality. When the signal intensity decreases, it means that the signal-to-noise ratio is low. The signal quality can be improved by increasing the exposure time and the number of accumulations. According to the characteristics of the sample, different samples have different responses to the laser. For samples that are prone to photobleaching or thermal damage, shorten the exposure time. If the sample has fluorescence interference, adjust the laser wavelength or use fluorescence suppression technology. At the same time, adjust the exposure time and the number of accumulations according to the fluorescence intensity. Gradually adjust the parameters. First increase the exposure time and observe the changes in signal intensity and signal-to-noise ratio. If the signal intensity increases, but the noise also increases, average out the random noise by increasing the number of accumulations. After each parameter adjustment, re-collect the spectrum and evaluate the signal quality until a high signal-to-noise ratio is reached, that is, the signal-to-noise ratio is greater than 10, and the signal-to-noise ratio remains stable in multiple measurements, and the experiment can be repeated. The collected Raman spectrum is baseline corrected to obtain a corrected spectrum. In the corrected spectrum, H2S and HS are determined. - The Raman peak positions are integrated to calculate the H2S and HS - The Raman peak area and And at the same time calculate the water level is 2800-3900cm -1 The area of ​​the OH stretching vibration peak

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