A comprehensive testing and evaluating method for environmental protection performance of green drilling fluid

Abstract

The present application relates to the technical field of drilling fluid detection, in particular to a green drilling fluid environmental protection performance comprehensive test evaluation method, comprising: configuring a standardized environment simulation reactor, injecting a green drilling fluid sample to be tested and a simulated environment medium containing fresh water sediments, salt water sediments and land soil, separating the whole system liquid-solid mixture after leaching reaction under constant temperature and frequency conditions to obtain filtrate and solid residue. The filtrate is subjected to full component spectrum scanning, compared with a standard spectrum library to identify target pollutants and preliminary concentration interval; the residue is subjected to thermal analysis and gas phase capture, data is imported into a pollutant migration and transformation prediction model, combined with medium physicochemical parameters to calculate solid phase adsorption retention and long-term release potential, and the solid phase occurrence state of pollutants is evaluated. The method can adapt to multi-element environment simulation, completely detect liquid-solid two-phase pollutants, accurately identify pollutants and quantify solid phase occurrence characteristics, and realize comprehensive evaluation of drilling fluid environmental protection performance.

Description

Technical Field

[0001] This invention relates to the field of drilling fluid testing technology, and in particular to a comprehensive testing and evaluation method for the environmental performance of green drilling fluids. Background Technology

[0002] Conventional testing methods for the environmental performance of green drilling fluids often rely on leaching tests conducted in a single environmental medium. Only routine spectral analysis is performed on the leachate phase, and solid residues are typically treated with simple extraction or incineration. Standardized multi-media simulation systems covering freshwater sediments, saline sediments, and terrestrial soils are not established, nor are specific gaseous component capture operations performed on solid residues. These testing methods can only obtain rough information on liquid-phase contaminants in drilling fluids under a single environment, which is incompatible with the actual working conditions where drilling fluids come into contact with multiple environmental media, thus limiting the applicability of the testing scenarios.

[0003] Conventional spectroscopic detection can only provide a rough qualitative analysis of liquid-phase contaminants, and cannot determine the type and concentration range of contaminants through precise peak shape comparison. Conventional treatment methods for solid-phase residues cannot capture volatile and semi-volatile contaminant components, nor can they determine the occurrence form of contaminants in the solid phase. At the same time, existing detection methods do not incorporate predictive models for quantitative analysis of solid-phase contaminants, making it impossible to calculate the adsorption and retention capacity and long-term release potential of contaminants, and thus failing to fully reflect the environmental occurrence characteristics of drilling fluid contaminants.

[0004] It is necessary to build a multi-type standard environmental medium simulation leaching system, separate all liquid-solid mixtures in the reaction system, identify liquid phase pollutants through full component spectral scanning, perform thermal desorption and gas phase capture on solid phase residues, and combine the trained prediction model to calculate the adsorption and retention capacity and long-term release potential of solid phase pollutants, forming a complete assessment result of solid phase occurrence state. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a comprehensive testing and evaluation method for the environmental performance of green drilling fluids.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a comprehensive testing and evaluation method for the environmental performance of green drilling fluid, comprising:

[0007] A set of standardized environmental simulation reactors is configured, and the green drilling fluid sample to be tested and a preset volume of simulated environmental medium are injected into the environmental simulation reactors respectively. The simulated environmental medium includes standard samples of freshwater sediments, saline sediments and terrestrial soils.

[0008] Under a preset constant temperature and constant oscillation frequency, the mixture in the environmental simulation reactor is subjected to a leaching reaction for a specified time. After the reaction is completed, all liquid and solid mixtures in the reactor are subjected to solid-liquid separation to obtain filtrate containing pollutants and solid residue.

[0009] The filtrate containing contaminants is subjected to full-component spectral scanning, and the solid residue is simultaneously subjected to thermal desorption and gas phase component capture to obtain spectral characteristic data of the filtrate and gas phase data of the residue desorption.

[0010] The spectral feature data of the filtrate is compared peak by peak with the standard spectra of a variety of known toxic and harmful substances pre-stored in the standard spectral library, and similarity calculation is performed to identify one or more target pollutants and their corresponding preliminary concentration ranges in the pollutant-containing filtrate.

[0011] The gas phase data of the residue analysis is imported into the trained pollutant migration and transformation prediction model. Combined with the physicochemical parameters of the current simulated environmental medium, the adsorption and retention amount and long-term release potential of the target pollutant in the solid residue are simulated and calculated to obtain the evaluation results of the occurrence state of the pollutant in the solid phase.

[0012] As a further aspect of the present invention, the mixture in the environmental simulation reactor is subjected to a leaching reaction for a specified duration at a preset constant temperature and constant oscillation frequency. After the reaction, all liquid and solid mixtures in the reactor are subjected to solid-liquid separation to obtain a filtrate containing pollutants and solid residue, including:

[0013] The environmental simulation reactor containing the green drilling fluid sample and the simulated environmental medium is placed in a constant temperature oscillator;

[0014] Set the temperature control parameters of the constant temperature oscillator to maintain the reaction temperature at a preset constant temperature value, and set the oscillation control parameters of the constant temperature oscillator to maintain the oscillation frequency at a preset constant oscillation frequency value.

[0015] The constant-temperature oscillator is started to conduct a continuous oscillating leaching reaction of the mixture in the environmental simulation reactor for a specified duration.

[0016] After the specified time has elapsed, the environmental simulation reactor is removed from the constant temperature oscillator, and all liquid and solid mixtures in the environmental simulation reactor are transferred to a high-speed centrifuge.

[0017] The high-speed centrifuge is operated at the set speed and centrifugation time to achieve complete separation of solid particles and liquid in the mixture. The supernatant is collected as the filtrate containing contaminants, and the bottom precipitate is collected as the solid residue.

[0018] As a further aspect of the present invention, the filtrate containing contaminants is subjected to full-component spectral scanning, and the solid residue is simultaneously subjected to thermal desorption and gas phase component capture, including:

[0019] The contaminated filtrate is introduced into a flow analysis cell equipped with a broadband light source and an array detector. Continuous spectral scanning is performed in the ultraviolet, visible, and near-infrared regions to record the absorbance change curves within the complete wavelength range and generate spectral characteristic data of the filtrate.

[0020] The solid residue is evenly spread in the quartz sample boat of the thermal desorption furnace, and heated according to a preset gradient heating program under the protection of inert carrier gas.

[0021] During the heating process, a low-temperature cold trap connected to the outlet of the thermal desorption furnace is used to condense and capture the released volatile and semi-volatile components. Simultaneously, a mass spectrometer is used to perform real-time component analysis on the uncondensed gas. The signal intensity and mass-to-charge ratio information of each component are collected throughout the heating process to generate the residual desorption gas phase data.

[0022] As a further aspect of the present invention, the spectral characteristic data of the filtrate are compared peak by peak with the standard spectra of various known toxic and harmful substances pre-stored in a standard spectral library, and similarity calculations are performed, including:

[0023] The spectral characteristic data of the filtrate are subjected to baseline correction and smoothing filtering to eliminate instrument background noise and scattering interference. The processed spectral data are then subjected to second derivative transformation to enhance the characteristic peak information in the spectrum, and the position, intensity and half-width of the characteristic peaks are calibrated.

[0024] The sub-library corresponding to the current simulated environment medium type is called from the standard spectral library, and the standard spectrum of each known toxic and harmful substance in the sub-library is extracted one by one;

[0025] The position matching degree and contour similarity of each characteristic peak of the filtrate spectral characteristic data with the characteristic peak of each standard spectrum called are calculated. When both the position matching degree and contour similarity exceed the preset matching threshold, it is determined that the match is successful, and the name of the matched toxic and harmful substance and the corresponding characteristic peak intensity ratio are recorded.

[0026] Based on the matched characteristic peak intensity ratio, combined with the standard concentration-intensity curve of the toxic and harmful substance, the preliminary concentration range of the substance in the filtrate is estimated.

[0027] As a further aspect of the present invention, the gas phase data of the residue analysis is imported into a pre-trained pollutant migration and transformation prediction model. Combined with the physicochemical parameters of the current simulated environmental medium, the adsorption and retention capacity and long-term release potential of the target pollutant in the solid residue are simulated and calculated, including:

[0028] The gas phase data of the residue analysis were normalized and feature extracted to obtain feature vectors characterizing the pollutant release intensity sequence at different temperatures;

[0029] Read the organic carbon content, cation exchange capacity, and clay mineral composition of the standard sample of freshwater sediment, saline sediment, or terrestrial soil used in the current test from the environmental media physicochemical parameter database;

[0030] The feature vector, along with the organic carbon content, cation exchange capacity, and clay mineral component content, are input into the pollutant migration and transformation prediction model, which is a multi-task learning model based on a deep neural network.

[0031] The pollutant migration and transformation prediction model outputs the predicted adsorption isotherm parameters of the target pollutant in the solid residue, as well as the predicted long-term cumulative release kinetic parameters.

[0032] The adsorption retention amount is calculated based on the predicted adsorption isotherm parameters, and the long-term release potential is calculated based on the predicted long-term cumulative release kinetic parameters. Together, these constitute the assessment result of the contaminant's occurrence state in the solid phase.

[0033] As a further aspect of the present invention, the method for constructing and training the pollutant migration and transformation prediction model includes:

[0034] Collect historical experimental datasets, which include thermal desorption gas phase data of various pollutants in different environmental media, physicochemical parameters of the corresponding environmental media, and adsorption and release data obtained by standard isothermal adsorption experiments and long-term leaching experiments.

[0035] The thermal desorption gas phase data in the historical experimental dataset are subjected to the same normalization and feature extraction processes as the residue desorption gas phase data to form a training feature vector set.

[0036] The training feature vector set and the corresponding environmental medium physicochemical parameters are used as input features, and the measured adsorption and release data are used as training labels to construct a complete training sample set for supervised learning.

[0037] The initialized deep neural network is trained iteratively through the complete training sample set. The network weights are optimized by minimizing the loss function between the model's predicted values ​​and the measured training labels until the model converges, thus obtaining the trained pollutant migration and transformation prediction model.

[0038] As a further aspect of the present invention, the method further includes a comprehensive toxicity index calculation step:

[0039] Based on the preliminary concentration range, the midpoint is taken as the representative calculated concentration of the target pollutant;

[0040] The baseline toxicity value of each of the target pollutants is identified by querying the pollutant toxicity database, and the baseline toxicity value includes the median lethal concentration, the concentration with no observed effect, or the chronic baseline value;

[0041] The single toxicity quotient for each target pollutant is calculated by dividing the representative calculated concentration by the corresponding baseline toxicity value.

[0042] A comprehensive toxicity index is obtained by taking the square root of the sum of squares of the individual toxicity quotients of all identified target pollutants contained in the green drilling fluid sample.

[0043] The comprehensive toxicity index is compared with a preset toxicity risk classification threshold to determine the toxicity risk level of the green drilling fluid sample.

[0044] As a further aspect of the present invention, the method further includes an environmental durability scoring step:

[0045] The adsorption retention amount and the long-term release potential are extracted from the evaluation results of the occurrence state of the pollutants in the solid phase.

[0046] A scoring scale is set for the adsorption retention amount. The greater the adsorption retention amount, the less likely the pollutant is to dissociate from the solid phase, and the higher the individual score is assigned.

[0047] A scoring scale is set for the long-term release potential. The greater the long-term release potential, the higher the risk of pollutants being released into the environment in the long term, and the lower the individual score is assigned.

[0048] The environmental durability score of the green drilling fluid sample in a specific simulated environmental medium is calculated by weighting and summing the individual scores corresponding to the adsorption retention amount and the long-term release potential.

[0049] For different simulated environmental media, all steps of the leaching reaction to environmental durability scoring were repeated to obtain independent environmental durability scores for the green drilling fluid samples in fresh water, saline water and soil environments.

[0050] As a further aspect of the present invention, the method further includes a comprehensive environmental performance grading step:

[0051] The comprehensive toxicity index is standardized and mapped to a standardized toxicity score between zero and one hundred, with a lower score indicating a lower toxicity risk.

[0052] The environmental durability score is standardized and mapped to a standardized durability score between zero and one hundred. The lower the score, the lower the environmental durability risk.

[0053] Preset weighting coefficients are assigned to the standardized toxicity score and the standardized persistence score, and the weighted scores are summed to obtain a preliminary total environmental performance score.

[0054] The biodegradation rate data of the green drilling fluid sample obtained in the biodegradability standard test is retrieved, and the preliminary environmental performance score is corrected according to the biodegradation rate data. The higher the biodegradation rate, the larger the correction coefficient, and finally the corrected comprehensive environmental performance score is obtained.

[0055] Based on the numerical range of the overall environmental performance score and referring to the preset environmental performance grading table, the final environmental performance level of the green drilling fluid sample is determined.

[0056] As a further aspect of the present invention, the processed spectral data is subjected to a second-order derivative transformation to enhance the characteristic peak information in the spectrum, and the position, intensity, and half-width of the characteristic peaks are calibrated, including:

[0057] The spectral characteristic data of the filtrate after baseline correction and smoothing filtering are processed by applying the central difference algorithm to calculate the second derivative, thereby obtaining the second derivative spectral data.

[0058] Based on the second derivative spectral data, the masked shoulder peaks and overlapping peaks in the original spectrum are identified, and the enhanced spectral feature peak information is obtained.

[0059] On the second derivative spectral data, locate the zero-crossing position corresponding to each characteristic peak, and mark the zero-crossing position as the center wavelength of the characteristic peak in the original spectrum, i.e., the characteristic peak position;

[0060] Calculate the intensity difference between the positive and negative peaks corresponding to each characteristic peak in the second derivative spectral data, and calibrate the intensity difference as the relative intensity of the characteristic peak;

[0061] The wavelength width corresponding to the positive peak of each characteristic peak in the second derivative spectral data is measured when the peak height drops from the peak apex to half the peak height, and the wavelength width is calibrated as the half-peak width of the characteristic peak.

[0062] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0063] A standardized environmental simulation reactor is configured, into which the green drilling fluid sample to be tested, along with standard simulated media of freshwater sediments, saline sediments, and terrestrial soil, are injected. The leaching reaction is completed for a specified duration under constant temperature and constant oscillation frequency. Solid-liquid separation is performed on all liquid and solid mixtures within the reactor. This method can simultaneously simulate the leaching conditions of drilling fluid in three typical environmental media, fully preserving the contaminant morphology in both the liquid and solid phases after leaching. The obtained filtrate and solid residue comprehensively reflect the leaching distribution of drilling fluid contaminants in different environmental media, avoiding environmental adaptation bias caused by single-media simulation. The complete solid-liquid separation system retains all contaminant components within the reaction system, preventing detection bias caused by component loss and ensuring the integrity of contaminant information in subsequent sample testing.

[0064] A full-component spectral scan was performed on the filtrate containing contaminants. The spectral characteristics of the filtrate were compared peak by peak with the spectra of known harmful substances in a standard spectral library, and the similarity was calculated to determine the target contaminants and their corresponding preliminary concentration ranges in the filtrate. Thermal desorption and gas phase component capture were performed on the solid residue. The gas phase data of the residue desorption were imported into a trained contaminant migration and transformation prediction model. Combined with the physicochemical parameters of the simulated environmental medium, the adsorption and retention amount and long-term release potential of the target contaminants in the solid residue were simulated and calculated to obtain the solid phase occurrence state assessment results. The types and concentration ranges of liquid phase contaminants can be accurately determined, and the gas phase contaminant components in the solid residue can be completely captured. Based on the prediction model, the relevant parameters of solid phase contaminants can be quantitatively calculated, and the retention and release characteristics of contaminants in the solid phase can be intuitively presented, fully presenting the occurrence, migration and transformation characteristics of drilling fluid contaminants in the liquid and solid phases. Attached Figure Description

[0065] Figure 1 This is a flowchart of a comprehensive testing and evaluation method for the environmental performance of green drilling fluid as described in this invention;

[0066] Figure 2 This is a flowchart of the leaching reaction and solid-liquid separation process;

[0067] Figure 3 This is a flowchart for spectral comparison and concentration estimation. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0069] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0070] See Figure 1 This invention provides a comprehensive testing and evaluation method for the environmental performance of green drilling fluids, the specific method including:

[0071] A set of standardized environmental simulation reactors were configured, and the green drilling fluid sample to be tested and a predetermined volume of simulated environmental media, including standard samples of freshwater sediments, saline sediments, and terrestrial soil, were injected into these reactors. Under predetermined constant temperature and constant oscillation frequency, the mixture in the environmental simulation reactors underwent a leaching reaction for a specified duration. After the reaction, all liquid and solid mixtures in the reactors were subjected to solid-liquid separation to obtain a filtrate containing contaminants and solid residue. Full-component spectral scanning was performed on the contaminant-containing filtrate, and thermal desorption and gas phase component capture were simultaneously performed on the solid residue to obtain spectral characteristic data of the filtrate and gas phase data of the residue. The spectral characteristic data of the filtrate were compared peak-by-peak with the standard spectra of various known toxic and hazardous substances pre-stored in a standard spectral library, and similarity calculations were performed to identify one or more target contaminants present in the contaminant-containing filtrate and their corresponding preliminary concentration ranges. The gas phase data of the residue analysis is imported into the trained pollutant migration and transformation prediction model. Combined with the physicochemical parameters of the current simulated environmental medium, the adsorption and retention of the target pollutant in the solid residue and its long-term release potential are simulated and calculated to obtain the assessment results of the pollutant's occurrence state in the solid phase.

[0072] In one embodiment of the present invention, see [reference] Figure 2An environmental simulation reactor, containing a green drilling fluid sample and a simulated environmental medium, was placed in a thermostatic oscillator. The temperature control parameters of the oscillator were set to maintain the reaction temperature at a preset constant value, and the oscillation control parameters were set to maintain the oscillation frequency at a preset constant value. The oscillator was then started to continuously oscillate and leach the mixture in the environmental simulation reactor for a specified duration. After the specified duration, the environmental simulation reactor was removed from the oscillator, and all the liquid and solid mixture within was transferred to a high-speed centrifuge. The high-speed centrifuge was run at a set speed and centrifugation time to achieve complete separation of solid particles and liquid in the mixture. The supernatant was collected as the contaminated filtrate, and the bottom precipitate was collected as the solid residue. The contaminated filtrate was then introduced into a flow analysis cell equipped with a broadband light source and an array detector. Continuous spectral scanning was performed in the ultraviolet, visible, and near-infrared regions, recording the absorbance variation curves across the entire wavelength range to generate spectral characteristic data of the filtrate. The solid residue was evenly spread in the quartz sample boat of the thermal desorption furnace. Under the protection of inert carrier gas, the solid residue was heated according to the preset gradient heating program. During the heating process, the released volatile and semi-volatile components were condensed and captured by the low-temperature cold trap connected to the outlet of the thermal desorption furnace. At the same time, the uncondensed gas was analyzed in real time by a mass spectrometer. The signal intensity and mass-to-charge ratio information of each component were collected throughout the heating process to generate gas phase data of residue desorption.

[0073] In specific implementation, an environmental simulation reactor containing a green drilling fluid sample and a simulated environmental medium is placed in a thermostatic oscillator. The temperature control parameters of the thermostatic oscillator are set to maintain the reaction temperature at a preset constant temperature value, and the oscillation control parameters are set to maintain the oscillation frequency at a preset constant oscillation frequency value. The thermostatic oscillator is started to continuously oscillate and leach the mixture in the environmental simulation reactor for a specified duration. After the specified duration, the environmental simulation reactor is removed from the thermostatic oscillator, and all liquid and solid mixtures within the reactor are transferred to a high-speed centrifuge. The high-speed centrifuge is run at a set speed and centrifugation time to achieve complete separation of solid particles and liquid in the mixture. The supernatant is collected as the contaminated filtrate, and the bottom precipitate is collected as solid residue. In some embodiments, the preset constant temperature value of the thermostatic oscillator is set to 25 degrees Celsius, the preset constant oscillation frequency value is set to 150 rpm, the specified leaching reaction lasts for 24 hours, and the set speed of the high-speed centrifuge is 10,000 rpm with a centrifugation time of 15 minutes. It can be understood that these parameters are adjusted according to the type of simulated environmental medium.

[0074] In practice, the contaminated filtrate is introduced into a flow analysis cell equipped with a broadband light source and an array detector. Continuous spectral scanning is performed in the ultraviolet, visible, and near-infrared regions, recording the absorbance variation curves across the entire wavelength range to generate spectral characteristic data of the filtrate. In some embodiments, the formula for the absorbance variation curve is:

[0075]

[0076] in: This represents the absorbance at wavelength λ. This represents the intensity of transmitted light received by the detector at wavelength λ. This represents the reference intensity of incident light at wavelength λ. It can be understood that the spectral scan covers a wavelength range from 200 nm to 2500 nm. In practice, the solid residue is uniformly spread in a quartz sample boat within the thermal desorption furnace. Under the protection of an inert carrier gas, the solid residue is heated according to a preset gradient heating program. During heating, a low-temperature cold trap connected to the furnace outlet is used to condense and capture the released volatile and semi-volatile components. Simultaneously, a mass spectrometer is used to perform real-time component analysis of the uncondensed gas. The signal intensity and mass-to-charge ratio information of each component are collected throughout the heating process to generate residue desorption gas phase data. Optionally, high-purity nitrogen is used as the inert carrier gas, with a flow rate controlled at 50 mL / min. The gradient heating program increases the temperature from 50°C to 300°C at a rate of 10°C / min.

[0077] In one embodiment of the present invention, see [reference] Figure 3The spectral characteristic data of the filtrate were subjected to baseline correction and smoothing filtering to eliminate instrument background noise and scattering interference. The spectral characteristic data of the filtrate after baseline correction and smoothing filtering were then processed using the central difference algorithm to calculate the second derivative, resulting in second derivative spectral data. Based on the second derivative spectral data, masked shoulder peaks and overlapping peaks in the original spectrum were identified, yielding enhanced spectral characteristic peak information. The zero-crossing position corresponding to each characteristic peak was located on the second derivative spectral data, and this position was calibrated as the center wavelength of the characteristic peak in the original spectrum, i.e., the characteristic peak position. The intensity difference between the positive and negative peaks corresponding to each characteristic peak in the second derivative spectral data was calculated, and this intensity difference was calibrated as the relative intensity of the characteristic peak. The wavelength width corresponding to the positive peak of each characteristic peak in the second derivative spectral data was measured when the peak height decreased from the peak apex to half the peak height, and this wavelength width was calibrated as the half-peak width of the characteristic peak. The standard spectral library is used to retrieve the sub-library corresponding to the current simulated environmental medium type. The standard spectrum of each known toxic and harmful substance in the sub-library is extracted one by one. The position matching degree and contour similarity of each characteristic peak of the filtrate spectral characteristic data are calculated with the characteristic peak of each retrieved standard spectrum. When the position matching degree and contour similarity both exceed the preset matching threshold, it is determined to be a successful match. The name of the matched toxic and harmful substance and the corresponding characteristic peak intensity ratio are recorded. Based on the characteristic peak intensity ratio of the successful match, combined with the standard concentration-intensity curve of the toxic and harmful substance, the preliminary concentration range of the substance in the filtrate is estimated.

[0078] In practice, baseline correction and smoothing filtering are performed on the spectral characteristic data of the filtrate. Baseline correction uses a polynomial fitting method to remove instrument background noise and scattering interference, while smoothing filtering uses the Savitzky-Golay convolution algorithm to reduce random noise. The second derivative spectral data is obtained by applying the central difference algorithm to the baseline-corrected and smoothed spectral characteristic data. Based on the second derivative spectral data, masked shoulder peaks and overlapping peaks in the original spectrum are identified to obtain enhanced spectral characteristic peak information. The zero-crossing position corresponding to each characteristic peak is located on the second derivative spectral data, and the zero-crossing position is calibrated as the center wavelength of the characteristic peak in the original spectrum, i.e., the characteristic peak position. The intensity difference between the positive and negative peaks corresponding to each characteristic peak in the second derivative spectral data is calculated, and the intensity difference is calibrated as the relative intensity of the characteristic peak. The wavelength width corresponding to the positive peak of each characteristic peak in the second derivative spectral data is measured when the peak height drops from the peak apex to half the peak height, and the wavelength width is calibrated as the half-peak width of the characteristic peak.

[0079] In practical implementation, a sub-library corresponding to the current simulated environmental medium type is called from the standard spectral library. For example, when the simulated environmental medium is saline sediment, the saline sediment sub-library is called. The standard spectra of each known toxic or harmful substance in the sub-library are extracted one by one. It can be understood that the standard spectra are obtained by scanning pure substance standards under the same analytical conditions and then stored in the standard spectral library. The position matching degree and contour similarity of each characteristic peak of the filtrate spectral characteristic data with the characteristic peak of each called standard spectrum are calculated. In some embodiments, the overall similarity is considered... formula:

[0080]

[0081] in: This represents the position matching degree calculated based on the wavelength difference at the center of the characteristic peak. This represents the contour matching degree calculated based on the relative intensity of the characteristic peaks and the half-width at half-maximum. and These are the preset weighting coefficients assigned to the position matching degree and the contour matching degree, and they satisfy... The combined similarity calculated from position matching and contour similarity... A successful match is determined when the value exceeds a preset matching threshold, and the name of the matched toxic or hazardous substance and its corresponding characteristic peak intensity ratio are recorded. The preset matching threshold is 0.85.

[0082] In practice, the initial concentration range of the toxic or hazardous substance in the filtrate is estimated based on the matched characteristic peak intensity ratio and the standard concentration-intensity curve. The standard concentration-intensity curve is established beforehand by measuring the spectral characteristic peak intensities of a series of standard solutions with known concentrations and then fitting the curve, for example, a linear fitting curve. Optionally, the initial concentration range is calculated by substituting the measured characteristic peak intensity ratio into the standard concentration-intensity curve and considering instrument measurement uncertainty, resulting in a range containing the lowest and highest estimated concentrations. In some embodiments, for multiple matched target pollutants, the above process is repeated to obtain the initial concentration range for each target pollutant.

[0083] In one embodiment of the present invention, the gas phase data of the residue analysis are normalized and feature extracted to obtain feature vectors characterizing the pollutant release intensity sequence at different temperatures. The organic carbon content, cation exchange capacity, and clay mineral component content of standard samples of freshwater sediments, saline sediments, or terrestrial soils used in the current test are read from an environmental media physicochemical parameter database. The feature vectors, along with the organic carbon content, cation exchange capacity, and clay mineral component content, are input into a pollutant migration and transformation prediction model. This model is a multi-task learning model based on a deep neural network. The model outputs predicted adsorption isotherm parameters of the target pollutant in the solid residue, as well as predicted long-term cumulative release kinetic parameters. The adsorption retention is calculated based on the predicted adsorption isotherm parameters, and the long-term release potential is calculated based on the predicted long-term cumulative release kinetic parameters. These together constitute the assessment result of the pollutant's occurrence state in the solid phase. The construction and training method of the pollutant migration and transformation prediction model includes collecting historical experimental datasets. These datasets contain thermal desorption gas phase data of various pollutants in different environmental media, the corresponding physicochemical parameters of the environmental media, and adsorption and release data obtained through standard isothermal adsorption experiments and long-term leaching experiments. The thermal desorption gas phase data in the historical experimental dataset undergoes the same normalization and feature extraction processing as the residue desorption gas phase data to form a training feature vector set. The training feature vector set and the corresponding physicochemical parameters of the environmental media are used as input features, and the measured adsorption and release data are used as training labels to construct a complete training sample set for supervised learning. The initialized deep neural network is trained iteratively using the complete training sample set. The network weights are optimized by minimizing the loss function between the model prediction value and the measured training labels until the model converges, resulting in a trained pollutant migration and transformation prediction model.

[0084] In specific implementation, the residual gas phase data is normalized and feature extracted. Normalization uses a minimum-maximum scaling method to map signal intensity values ​​at different temperatures to a range of zero to one. Feature extraction calculates the mean, variance, and skewness of the signal intensity within each temperature interval from the normalized data, forming a set of statistical descriptors. These statistical descriptors are then arranged in ascending temperature order and concatenated to form a feature vector characterizing the pollutant release intensity sequence at different temperatures. The organic carbon content, cation exchange capacity, and clay mineral composition content of standard samples of freshwater sediments, saline sediments, or terrestrial soils used in the current test are retrieved from the environmental media physicochemical parameter database. It can be understood that these physicochemical parameters are pre-determined using standard methods and stored in the database. In some embodiments, environmental media physicochemical parameters are stored and retrieved in tabular form; see Table 1, which shows a set of exemplary parameters:

[0085] Table 1: Examples of Physicochemical Parameters of Standard Samples for Environmental Media

[0086]

[0087] In specific implementation, the feature vector, along with organic carbon content, cation exchange capacity, and clay mineral component content, is input into the pollutant migration and transformation prediction model. This model is a multi-task learning model built on a deep neural network, featuring a shared hidden layer and two independent output branches: one predicting adsorption isotherm parameters and the other predicting long-term cumulative release kinetic parameters. The pollutant migration and transformation prediction model outputs the predicted adsorption isotherm parameters of the target pollutant in the solid residue, as well as the predicted long-term cumulative release kinetic parameters. Based on the predicted adsorption isotherm parameters, the adsorption retention capacity is calculated; based on the predicted long-term cumulative release kinetic parameters, the long-term release potential is calculated, collectively constituting the assessment result of the pollutant's occurrence state in the solid phase. In some embodiments, the adsorption retention capacity... Using the Langmuir isotherm model formula:

[0088]

[0089] in: and These are the predicted adsorption isotherm parameters output by the pollutant migration and transformation prediction model, representing the binding constant and affinity coefficient, respectively. The equilibrium concentration is represented, either experimentally set or estimated from the initial concentration. Optionally, the long-term release potential is characterized by the maximum potential release among the predicted long-term cumulative release kinetic parameters.

[0090] In practical implementation, the construction and training method of the pollutant migration and transformation prediction model includes collecting historical experimental datasets. These datasets contain thermal desorption gas-phase data of various pollutants in different environmental media, the corresponding physicochemical parameters of the environmental media, and adsorption and release data obtained through standard isothermal adsorption experiments and long-term leaching experiments. The thermal desorption gas-phase data in the historical experimental dataset undergoes the same normalization and feature extraction processing as the residue desorption gas-phase data to form a training feature vector set. This training feature vector set and the corresponding environmental media physicochemical parameters are used as input features, and the measured adsorption and release data are used as training labels to construct a complete training sample set for supervised learning. This complete training sample set is randomly divided into a training set, a validation set, and a test set. The initialized deep neural network is trained iteratively using the complete training sample set. The network weights are optimized by minimizing the loss function between the model's predicted values ​​and the measured training labels until the model's performance on the validation set stabilizes, resulting in a well-trained pollutant migration and transformation prediction model.

[0091] In one embodiment of the present invention, based on the preliminary concentration range, the median value is taken as the representative calculated concentration of the target pollutant. The baseline toxicity value of each target pollutant identified is queried from the pollutant toxicity database. The baseline toxicity value includes the median lethal concentration, the concentration with no observed effect, or the chronic baseline value. The representative calculated concentration is divided by the corresponding baseline toxicity value to calculate the single toxicity quotient of each target pollutant. The sum of squares and the square root of the single toxicity quotients of all identified target pollutants contained in the green drilling fluid sample are calculated to obtain a comprehensive toxicity index. The comprehensive toxicity index is compared with a preset toxicity risk classification threshold to determine the toxicity risk level of the green drilling fluid sample. From the assessment results of the contaminant's occurrence state in the solid phase, adsorption retention and long-term release potential are extracted. A scoring scale is set for adsorption retention; the greater the adsorption retention, the less likely the contaminant is to dissociate from the solid phase, and the higher the individual score is assigned. A scoring scale is set for long-term release potential; the greater the long-term release potential, the higher the risk of the contaminant being released into the environment in the long term, and the lower the individual score is assigned. The individual scores corresponding to adsorption retention and long-term release potential are weighted and summed to calculate the environmental persistence score of the green drilling fluid sample in a specific simulated environmental medium. For different simulated environmental media, all steps from the leaching reaction to the environmental persistence score are repeated to obtain independent environmental persistence scores of the green drilling fluid sample in freshwater, saline water, and soil environments.

[0092] In practice, the median of the initial concentration range is taken as the representative calculated concentration of the target pollutant. The baseline toxicity value for each identified target pollutant is retrieved from the pollutant toxicity database. Baseline toxicity values ​​include median lethal concentration, no-observable-effect concentration, or chronic baseline value. The representative calculated concentration is divided by the corresponding baseline toxicity value to calculate the single toxicity quotient for each target pollutant. A comprehensive toxicity index is calculated by taking the square root of the sum of the squares of the single toxicity quotients of all identified target pollutants contained in the green drilling fluid sample. The calculation formula is:

[0093]

[0094] in: Indicates the overall toxicity index. This indicates the number of identified target pollutant types. This represents the single toxicity quotient of the i-th target pollutant. The overall toxicity index is compared with a preset toxicity risk grading threshold to determine the toxicity risk level of the green drilling fluid sample. It can be understood that the toxicity risk grading threshold is preset based on different environmental management standards; for example, refer to Table 2 for the risk grading correspondence.

[0095] Table 2: Correspondence between Comprehensive Toxicity Index and Toxicity Risk Level

[0096]

[0097] In practice, the adsorption retention and long-term release potential are extracted from the assessment results of the pollutant's occurrence state in the solid phase. A scoring scale is set for the adsorption retention. In some embodiments, the adsorption retention scoring scale is set using a linear interpolation method. The larger the adsorption retention, the less likely the pollutant is to dissociate from the solid phase, and the higher the individual score is assigned. For example, when the adsorption retention is between 0 and 100 mg / kg, the individual score is assigned 0-50 points. A scoring scale is set for the long-term release potential. The larger the long-term release potential, the higher the risk of the pollutant being released into the environment in the long term, and the lower the individual score is assigned. For example, when the long-term release potential is between 0 and 50 mg / kg, the individual score is assigned 100-0 points. The environmental durability score of the green drilling fluid sample in a specific simulated environmental medium is calculated by weighting and summing the individual scores corresponding to adsorption retention and long-term release potential. Optionally, the weighting coefficients for the weighted summation are determined according to the type of environmental medium. For example, for freshwater sediments, the weighting coefficient for the adsorption retention score is 0.4, and the weighting coefficient for the long-term release potential score is 0.6. For different simulated environmental media, all steps from the leaching reaction to the environmental durability score are repeated to obtain independent environmental durability scores for the green drilling fluid sample in freshwater, saline water, and soil environments. It can be understood that a complete testing and calculation process must be performed independently for each simulated environmental medium.

[0098] In one embodiment of the present invention, the comprehensive toxicity index is standardized and mapped to a standardized toxicity score between zero and one hundred, with a lower score indicating a lower toxicity risk. The environmental persistence score is also standardized and mapped to a standardized persistence score between zero and one hundred, with a lower score indicating a lower environmental persistence risk. Preset weighting coefficients are assigned to the standardized toxicity score and the standardized persistence score, and the weighted scores are summed to obtain a preliminary environmental performance score. The biodegradability rate data of the green drilling fluid sample obtained in the biodegradability standard test is queried, and the preliminary environmental performance score is corrected based on the biodegradability rate data. The higher the biodegradability rate, the larger the correction coefficient, and finally, a corrected comprehensive environmental performance score is obtained. Based on the numerical range of the comprehensive environmental performance score and referring to a preset environmental performance grading table, the final environmental performance level of the green drilling fluid sample is determined.

[0099] In practice, the composite toxicity index is standardized and mapped to a standardized toxicity score between zero and one hundred. The standardization process uses a linear transformation function. This function's parameters are set based on the maximum and minimum values ​​of the composite toxicity index from historical test data; a lower score indicates a lower toxicity risk. In some embodiments, the standardized toxicity score... Through the formula:

[0100]

[0101] in: This represents the overall toxicity index to be converted. and These represent the minimum and maximum values ​​of the preset comprehensive toxicity index transition range, respectively. This formula ensures that the standardized toxicity score is 100 when the comprehensive toxicity index reaches the minimum value of the transition range, and 0 when the comprehensive toxicity index reaches the maximum value of the transition range. In practice, the environmental persistence score is standardized and mapped to a standardized persistence score between zero and 100, similar to the standardized toxicity score. A lower score indicates a lower environmental persistence risk. Optionally, the standardized persistence score and the standardized toxicity score can share the same linear transition function structure but use independent parameter ranges.

[0102] In practice, preset weighting coefficients are assigned to the standardized toxicity score and the standardized persistence score, and the weighted scores are summed to obtain the preliminary environmental performance score. It can be understood that the weighting coefficients reflect the relative importance of toxicity risk and persistence risk in the overall environmental performance evaluation. In some embodiments, the weighting coefficient for the standardized toxicity score is set to 0.6, and the weighting coefficient for the standardized persistence score is set to 0.4, resulting in the preliminary environmental performance score. The calculation formula is:

[0103]

[0104] in: Indicates the standardized toxicity score. Indicates the standardized persistence score. and These are the preset weighting coefficients assigned to the standardized toxicity score and the standardized persistence score, respectively, and satisfying the following conditions: The process involves querying the biodegradability rate data of green drilling fluid samples obtained from standard biodegradability tests. Based on this data, the initial environmental performance score is corrected; a higher biodegradability rate results in a larger correction coefficient. The final corrected overall environmental performance score is then obtained. (Optional, correction coefficient...) With biodegradation rate The relationships between these factors are determined using a pre-defined lookup table. For example, a correction factor of 1.2 corresponds to a biodegradation rate between 90% and 100%, a correction factor of 1.0 corresponds to a biodegradation rate between 60% and 90%, and a correction factor of 0.8 corresponds to a biodegradation rate below 60%. The adjusted overall environmental performance score is then calculated. The calculation formula is Based on the numerical range of the overall environmental performance score and referring to the preset environmental performance grading table, the final environmental performance level of the green drilling fluid sample is determined.

[0105] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A comprehensive testing and evaluation method for the environmental performance of green drilling fluid, characterized in that, The method includes: A set of standardized environmental simulation reactors is configured, and the green drilling fluid sample to be tested and a preset volume of simulated environmental medium are injected into the environmental simulation reactors respectively. The simulated environmental medium includes standard samples of freshwater sediments, saline sediments and terrestrial soils. Under a preset constant temperature and constant oscillation frequency, the mixture in the environmental simulation reactor is subjected to a leaching reaction for a specified time. After the reaction is completed, all liquid and solid mixtures in the reactor are subjected to solid-liquid separation to obtain filtrate containing pollutants and solid residue. The filtrate containing contaminants is subjected to full-component spectral scanning, and the solid residue is simultaneously subjected to thermal desorption and gas phase component capture to obtain spectral characteristic data of the filtrate and gas phase data of the residue desorption. The spectral feature data of the filtrate is compared peak by peak with the standard spectra of a variety of known toxic and harmful substances pre-stored in the standard spectral library, and similarity calculation is performed to identify one or more target pollutants and their corresponding preliminary concentration ranges in the pollutant-containing filtrate. The gas phase data of the residue analysis is imported into the trained pollutant migration and transformation prediction model. Combined with the physicochemical parameters of the current simulated environmental medium, the adsorption and retention amount and long-term release potential of the target pollutant in the solid residue are simulated and calculated to obtain the evaluation results of the occurrence state of the pollutant in the solid phase.

2. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 1, characterized in that, Under a preset constant temperature and constant oscillation frequency, the mixture in the environmental simulation reactor is subjected to a leaching reaction for a specified duration. After the reaction, all liquid and solid mixtures in the reactor are subjected to solid-liquid separation to obtain a filtrate containing pollutants and solid residue, including: The environmental simulation reactor containing the green drilling fluid sample and the simulated environmental medium is placed in a constant temperature oscillator; Set the temperature control parameters of the constant temperature oscillator to maintain the reaction temperature at a preset constant temperature value, and set the oscillation control parameters of the constant temperature oscillator to maintain the oscillation frequency at a preset constant oscillation frequency value. The constant-temperature oscillator is started to conduct a continuous oscillating leaching reaction of the mixture in the environmental simulation reactor for a specified duration. After the specified time has elapsed, the environmental simulation reactor is removed from the constant temperature oscillator, and all liquid and solid mixtures in the environmental simulation reactor are transferred to a high-speed centrifuge. The high-speed centrifuge is operated at the set speed and centrifugation time to achieve complete separation of solid particles and liquid in the mixture. The supernatant is collected as the filtrate containing contaminants, and the bottom precipitate is collected as the solid residue.

3. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 1, characterized in that, The filtrate containing contaminants is subjected to full-component spectral scanning, and the solid residue is simultaneously subjected to thermal desorption and gas phase component capture, including: The contaminated filtrate is introduced into a flow analysis cell equipped with a broadband light source and an array detector. Continuous spectral scanning is performed in the ultraviolet, visible, and near-infrared regions to record the absorbance change curves within the complete wavelength range, thereby generating spectral characteristic data of the filtrate. The solid residue is evenly spread in the quartz sample boat of the thermal desorption furnace, and heated according to a preset gradient heating program under the protection of inert carrier gas. During the heating process, a low-temperature cold trap connected to the outlet of the thermal desorption furnace is used to condense and capture the released volatile and semi-volatile components. Simultaneously, a mass spectrometer is used to perform real-time component analysis on the uncondensed gas. The signal intensity and mass-to-charge ratio information of each component are collected throughout the heating process to generate the residual desorption gas phase data.

4. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 3, characterized in that, The spectral characteristic data of the filtrate are compared peak by peak with the standard spectra of various known toxic and harmful substances pre-stored in a standard spectral library, and similarity calculations are performed, including: The spectral characteristic data of the filtrate are subjected to baseline correction and smoothing filtering to eliminate instrument background noise and scattering interference. The processed spectral data are then subjected to second derivative transformation to enhance the characteristic peak information in the spectrum, and the position, intensity and half-width of the characteristic peaks are calibrated. The sub-library corresponding to the current simulated environment medium type is called from the standard spectral library, and the standard spectrum of each known toxic and harmful substance in the sub-library is extracted one by one; The position matching degree and contour similarity of each characteristic peak of the filtrate spectral characteristic data with the characteristic peak of each standard spectrum called are calculated. When both the position matching degree and contour similarity exceed the preset matching threshold, it is determined that the match is successful, and the name of the matched toxic and harmful substance and the corresponding characteristic peak intensity ratio are recorded. Based on the matched characteristic peak intensity ratio, combined with the standard concentration-intensity curve of the toxic and harmful substance, the preliminary concentration range of the substance in the filtrate is estimated.

5. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 4, characterized in that, The gas phase data from the residue analysis is imported into a pre-trained pollutant migration and transformation prediction model. Combined with the physicochemical parameters of the current simulated environmental medium, the adsorption and retention capacity and long-term release potential of the target pollutant in the solid residue are simulated and calculated, including: The gas phase data of the residue analysis were normalized and feature extracted to obtain feature vectors characterizing the pollutant release intensity sequence at different temperatures; Read the organic carbon content, cation exchange capacity, and clay mineral composition of the standard sample of freshwater sediment, saline sediment, or terrestrial soil used in the current test from the environmental media physicochemical parameter database; The feature vector, along with the organic carbon content, cation exchange capacity, and clay mineral component content, are input into the pollutant migration and transformation prediction model, which is a multi-task learning model based on a deep neural network. The pollutant migration and transformation prediction model outputs the predicted adsorption isotherm parameters of the target pollutant in the solid residue, as well as the predicted long-term cumulative release kinetic parameters. The adsorption retention amount is calculated based on the predicted adsorption isotherm parameters, and the long-term release potential is calculated based on the predicted long-term cumulative release kinetic parameters. Together, these constitute the assessment result of the contaminant's occurrence state in the solid phase.

6. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 5, characterized in that, The method for constructing and training the pollutant migration and transformation prediction model includes: Collect historical experimental datasets, which include thermal desorption gas phase data of various pollutants in different environmental media, physicochemical parameters of the corresponding environmental media, and adsorption and release data obtained by standard isothermal adsorption experiments and long-term leaching experiments. The thermal desorption gas phase data in the historical experimental dataset are subjected to the same normalization and feature extraction processes as the residue desorption gas phase data to form a training feature vector set. The training feature vector set and the corresponding environmental medium physicochemical parameters are used as input features, and the measured adsorption and release data are used as training labels to construct a complete training sample set for supervised learning. The initialized deep neural network is trained iteratively through the complete training sample set. The network weights are optimized by minimizing the loss function between the model's predicted values ​​and the measured training labels until the model converges, thus obtaining the trained pollutant migration and transformation prediction model.

7. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 6, characterized in that, The method also includes a comprehensive toxicity index calculation step: Based on the preliminary concentration range, the midpoint is taken as the representative calculated concentration of the target pollutant; The baseline toxicity value of each of the target pollutants is identified by querying the pollutant toxicity database, and the baseline toxicity value includes the median lethal concentration, the concentration with no observed effect, or the chronic baseline value; The single toxicity quotient for each target pollutant is calculated by dividing the representative calculated concentration by the corresponding baseline toxicity value. A comprehensive toxicity index is obtained by taking the square root of the sum of squares of the individual toxicity quotients of all identified target pollutants contained in the green drilling fluid sample. The comprehensive toxicity index is compared with a preset toxicity risk classification threshold to determine the toxicity risk level of the green drilling fluid sample.

8. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 7, characterized in that, The method also includes an environmental persistence scoring step: The adsorption retention amount and the long-term release potential are extracted from the evaluation results of the occurrence state of the pollutants in the solid phase. A scoring scale is set for the adsorption retention amount. The greater the adsorption retention amount, the less likely the pollutant is to dissociate from the solid phase, and the higher the individual score is assigned. A scoring scale is set for the long-term release potential. The greater the long-term release potential, the higher the risk of pollutants being released into the environment in the long term, and the lower the individual score is assigned. The environmental durability score of the green drilling fluid sample in a specific simulated environmental medium is calculated by weighting and summing the individual scores corresponding to the adsorption retention amount and the long-term release potential. For different simulated environmental media, all steps of the leaching reaction to environmental durability scoring were repeated to obtain independent environmental durability scores for the green drilling fluid samples in fresh water, saline water and soil environments.

9. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 8, characterized in that, The method also includes a comprehensive environmental performance grading step: The comprehensive toxicity index is standardized and mapped to a standardized toxicity score between zero and one hundred, with a lower score indicating a lower toxicity risk. The environmental durability score is standardized and mapped to a standardized durability score between zero and one hundred. The lower the score, the lower the environmental durability risk. Preset weighting coefficients are assigned to the standardized toxicity score and the standardized persistence score, and the weighted scores are summed to obtain a preliminary total environmental performance score. The biodegradation rate data of the green drilling fluid sample obtained in the biodegradability standard test is retrieved, and the preliminary environmental performance score is corrected according to the biodegradation rate data. The higher the biodegradation rate, the larger the correction coefficient, and finally the corrected comprehensive environmental performance score is obtained. Based on the numerical range of the overall environmental performance score and referring to the preset environmental performance grading table, the final environmental performance level of the green drilling fluid sample is determined.

10. The comprehensive testing and evaluation method for the environmental performance of green drilling fluid according to claim 4, characterized in that, The processed spectral data undergoes a second-order derivative transformation to enhance the characteristic peak information in the spectrum, and the position, intensity, and full width at half maximum (FWHM) of the characteristic peaks are determined, including: The spectral characteristic data of the filtrate after baseline correction and smoothing filtering are processed by applying the central difference algorithm to calculate the second derivative, thereby obtaining the second derivative spectral data. Based on the second derivative spectral data, the masked shoulder peaks and overlapping peaks in the original spectrum are identified, and the enhanced spectral feature peak information is obtained. On the second derivative spectral data, locate the zero-crossing position corresponding to each characteristic peak, and mark the zero-crossing position as the center wavelength of the characteristic peak in the original spectrum, i.e., the characteristic peak position; Calculate the intensity difference between the positive and negative peaks corresponding to each characteristic peak in the second derivative spectral data, and calibrate the intensity difference as the relative intensity of the characteristic peak; The wavelength width corresponding to the positive peak of each characteristic peak in the second derivative spectral data is measured when the peak height drops from the peak apex to half the peak height, and the wavelength width is calibrated as the half-peak width of the characteristic peak.

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