Method for measuring oil content of oil-based drilling cuttings and application thereof

Abstract

The invention relates to the technical field of oil content measurement, in particular to a method for measuring the oil content of oil-based drilling cuttings and application of the method. The method comprises the following steps: querying a dynamic extraction curve database according to sample lithology and a processing method, and determining an optimal extraction time point by calculating a concentration change rate; multi-point sampling is carried out in the extraction process, the environment temperature and pressure are measured at the same time, an environment influence model comprising a temperature influence sub-model and a pressure influence sub-model is established, and an environment correction factor is obtained; performing infrared spectrum measurement on the extract sample, performing data correction, and calculating an average value and a standard deviation to remove an abnormal value; and finally, calculating the final oil content by adopting a piecewise linear equation aiming at different concentration ranges. By considering the lithologic characteristics, the environmental influence and the segmented linear relation, the measurement precision and reliability are remarkably improved.

Description

Technical Field

[0001] This application relates to the technical field of oil content measurement, and in particular to a method for measuring the oil content of oil-based drill cuttings and its application. Background Technology

[0002] With the development of oil drilling technology, oil-based drilling fluids are increasingly widely used in drilling operations. Oil-based drilling fluids possess excellent inhibition, lubrication, and carrying capacity; however, the resulting oil-based drill cuttings contain a large amount of oil, which can cause serious environmental pollution if not properly handled. Therefore, accurately determining the oil content of oil-based drill cuttings is crucial for assessing treatment effectiveness and environmental risks.

[0003] Currently, infrared spectroscopy has become one of the main methods for determining the oil content of oil-based drill cuttings due to its speed and simplicity. This method calculates the oil content by measuring the absorbance of the extract at the characteristic absorption wavelength of hydrocarbons and establishing a linear equation, and is widely used in industrial applications.

[0004] However, the existing extraction process lacks specificity, and the measurement results are easily affected by fluctuations in external conditions, leading to deviations in the measurement results and affecting the measurement accuracy. This situation needs further improvement. Summary of the Invention

[0005] To address the shortcomings of existing oil content measurement methods, such as the lack of specificity in the extraction process and the susceptibility of measurement results to fluctuations in external conditions, leading to deviations and affecting measurement accuracy, this application provides a method for measuring the oil content of oil-based drill cuttings and its application, employing the following technical solution: In a first aspect, this application provides a method for measuring the oil content of oil-based drill cuttings, comprising the following steps: Obtain the lithological type and processing method of the sample, and determine the optimal extraction time point based on the dynamic extraction curve corresponding to the lithological type and processing method; During the optimal extraction time, multiple samples are taken at preset time intervals to obtain extract samples at multiple time points. Measure the ambient temperature and pressure, input the ambient temperature and pressure into a preset environmental impact model, and obtain the environmental correction factor; Infrared spectroscopy measurements were performed on multiple extract samples to obtain absorbance data sequences, and the absorbance data were corrected according to the environmental correction factor. Based on the corrected absorbance data sequence, the mean and standard deviation are calculated, and the valid measurement results are obtained after removing outliers. Substituting the effective measurement results into the pre-established segmented working curve, the final oil content is obtained, wherein the segmented working curve includes multiple linear equations for different concentration ranges.

[0006] By adopting the above technical solution, in actual operations, drill cuttings samples of different lithologies often require different extraction times, and fluctuations in ambient temperature and pressure can affect the accuracy of measurement results. This application first queries a dynamic extraction curve database based on sample lithology and processing methods, and determines the optimal extraction time point by calculating the concentration change rate. During the extraction process, multiple samples are taken, and ambient temperature and pressure are measured simultaneously to establish an environmental impact model that includes temperature and pressure sub-models, obtaining an environmental correction factor. Infrared spectroscopy is performed on the extract sample, and data correction is performed, calculating the average value and standard deviation to remove outliers. Finally, piecewise linear equations for different concentration ranges are used to calculate the final oil content. By considering lithological characteristics, environmental impact, and piecewise linear relationships, the measurement accuracy and reliability are significantly improved.

[0007] Optionally, the lithological type and processing method of the sample are obtained, and the optimal extraction time point is determined based on the dynamic extraction curve corresponding to the lithological type and processing method. This specifically includes the following steps: Obtain the lithological type of the sample, and query the preset lithological classification table according to the lithological type to obtain the corresponding processing method; Based on the processing method, a pre-established dynamic extraction curve database is queried to obtain the corresponding dynamic extraction curve; The average concentration change rate before and after each time point is calculated based on the dynamic extraction curve. When the average concentration change rate is less than a preset threshold within a continuous time interval of a preset length, the starting time point of the continuous time interval is determined as the optimal extraction time point.

[0008] By adopting the above technical solution, in practice, drill cuttings samples of different lithologies such as shale and sandstone have different physicochemical properties. Using a fixed extraction time often leads to insufficient or excessive extraction. For example, for dense lithological samples, a conventional 15-minute extraction may not be sufficient to achieve adequate extraction, while for loose and porous samples, an excessively long extraction time will introduce other interfering substances. This application first determines the lithology of the collected oil-based drill cuttings samples to obtain basic lithological information, including rock type and structural characteristics. Then, based on the lithological information, it queries a pre-established lithological classification table to obtain corresponding processing methods, such as particle size and extractant selection. Next, it queries a dynamic extraction curve database to obtain the standard dynamic extraction curve for this type of sample. Finally, by calculating the average concentration change rate over a continuous time period, when the change rate is less than a set threshold within a certain time interval, the starting point of that interval is determined as the optimal extraction time point. This achieves precise control of the extraction time and avoids the problems caused by uniformly setting the extraction time in traditional methods.

[0009] Optionally, the ambient temperature and pressure are measured, and the ambient temperature and pressure are input into a preset environmental impact model to obtain an environmental correction factor. This specifically includes the following steps: Acquire current ambient temperature and pressure measurements; The measured temperature and pressure values ​​are compared with standard temperature and standard pressure, respectively, to obtain the temperature deviation and pressure deviation; Based on the temperature deviation and pressure deviation, temperature correction coefficients and pressure correction coefficients are calculated using a preset environmental impact model. The environmental impact model includes a temperature impact sub-model and a pressure impact sub-model. The input parameters of the temperature impact sub-model include temperature deviation and sample moisture content, and the input parameters of the pressure impact sub-model include pressure deviation and sample density. Multiplying the temperature correction factor and the pressure correction factor together yields the environmental correction factor.

[0010] By adopting the above technical solution, this application first obtains the actual temperature and pressure measurements of the on-site environment, compares them with standard test conditions, and calculates the temperature deviation and pressure deviation. Then, these deviation values ​​are input into a pre-established environmental influence model, which is divided into a temperature influence sub-model and a pressure influence sub-model. The temperature influence sub-model not only considers the temperature deviation but also takes the sample moisture content as an important parameter, while the pressure influence sub-model combines the pressure deviation and sample density for calculation. Finally, by multiplying the temperature correction coefficient and the pressure correction coefficient, a comprehensive environmental correction factor is obtained. This approach considers the coupling effect between environmental factors such as temperature and pressure and the physical properties of the sample, making the measurement results more accurate and reliable.

[0011] Optionally, based on the temperature deviation and pressure deviation, temperature correction coefficients and pressure correction coefficients are calculated using a preset environmental impact model, specifically including the following steps: Measure the moisture content and density of the sample; The temperature deviation and sample moisture content are input into the temperature influence sub-model to obtain temperature correction coefficients for different moisture contents. The pressure deviation and sample density are input into the pressure influence sub-model to obtain the pressure correction coefficients under different densities; Specifically, when the sample moisture content is greater than a preset threshold, the temperature correction coefficient is weighted and corrected; when the sample density is greater than a preset threshold, the pressure correction coefficient is weighted and corrected.

[0012] By adopting the above technical solution, this application first measures the moisture content and density of the sample to obtain basic physical property parameters; then, the temperature deviation and sample moisture content are input into the temperature influence sub-model to calculate the temperature correction coefficient for different moisture content conditions. Simultaneously, the pressure deviation and sample density are input into the pressure influence sub-model to obtain the pressure correction coefficient for different density conditions. When the sample moisture content exceeds a preset threshold, the system performs a weighted correction on the temperature correction coefficient to reflect the sensitivity of high moisture content samples to temperature changes. Similarly, when the sample density exceeds a preset threshold, the pressure correction coefficient is also adjusted accordingly. By employing threshold judgment and weighted correction mechanisms, the correction coefficients are dynamically adjusted according to sample characteristics, improving the pertinence and accuracy of environmental correction and making the measurement results more reliable.

[0013] Optionally, the absorbance data can be corrected according to the environmental correction factor, specifically including the following steps: Obtain absorbance data of multiple characteristic peaks in the absorption region of hydrocarbon functional groups in the extract sample; Calculate the absorbance deviation of each characteristic peak under environmental influence based on the environmental correction factor. The absorbance deviation is corrected by calculating the absorbance data of the corresponding characteristic peak to obtain the corrected absorbance value of the characteristic peak. The corrected characteristic peak absorbance values ​​were normalized based on the concentration of the extract to obtain the final corrected result.

[0014] By adopting the above technical solution, this application first selects multiple characteristic absorption peaks in the absorption region of hydrocarbon characteristic functional groups and obtains their absorbance data, including different types of absorption such as CH stretching vibration and CH bending vibration; then, using the obtained environmental correction factor, the absorbance deviation that each characteristic peak may produce under the current environmental conditions is calculated; next, the original absorbance data of each characteristic peak is corrected to eliminate measurement errors caused by environmental influences; finally, considering the differences in absorbance data ranges of samples with different concentrations, a normalization method is adopted to make the correction results more comparable and improve the reliability and accuracy of the measurement.

[0015] Optionally, the effective measurement results are substituted into the pre-established segmented working curve to obtain the final oil content, specifically including the following steps: Based on the numerical range of the effective measurement results, select the corresponding concentration range interval; Within the concentration range, obtain the corresponding linear equation parameters; Substitute the effective measurement results into the selected linear equation to calculate the preliminary oil content; Based on the sample mass and extractant volume, the preliminary oil content is corrected by volume to obtain the final oil content.

[0016] By adopting the above technical solution, this application first determines the concentration range to which the effective measurement results belong based on the corrected results. These ranges may include multiple levels such as low concentration, medium concentration, and high concentration. Then, within the determined concentration range, the corresponding linear equation parameters are called. These parameters are obtained through optimization by testing a large number of standard samples. Next, the effective measurement results are substituted into the selected linear equation to obtain a preliminary oil content value. Finally, considering that the mass of the actual sample and the volume of the extractant used may differ from the standard conditions, the preliminary oil content is corrected by a volume correction coefficient to obtain the final oil content result.

[0017] Optionally, within the concentration range, the corresponding linear equation parameters are obtained, specifically including the following steps: The absorbance and oil content data of the standard sample were obtained according to the concentration range. Linear fitting was performed on the absorbance and oil content to obtain the slope and intercept parameters; Calculate the goodness of fit of the standard sample in the corresponding interval. When the goodness of fit is greater than a preset threshold, determine that the slope and intercept parameters are valid. Specifically, for different concentration ranges, the values ​​of the slope and intercept parameters satisfy preset range limiting conditions.

[0018] By adopting the above technical solution, this application first selects standard samples within each concentration range for measurement, obtaining a series of corresponding data pairs of absorbance and oil content; then, it performs linear fitting analysis on these data pairs to obtain the slope and intercept parameters specific to that range; next, it calculates the goodness-of-fit index of the linear fit, such as the correlation coefficient, and only when the goodness-of-fit exceeds a preset threshold is the validity of the set of parameters confirmed; at the same time, to ensure the rationality and continuity of parameters in different ranges, corresponding value range restrictions are set for the slope and intercept parameters; the parameter validity judgment mechanism ensures the calculation accuracy of each range, while the parameter value restrictions ensure a smooth transition between different ranges, improving the accuracy and reliability of oil content calculation.

[0019] Secondly, this application provides the application of the above method in measuring and / or processing oil-based drill cuttings for real-time monitoring of oil content during the oil-based drilling fluid recovery process.

[0020] By adopting the above technical solution, the problems of untimely monitoring and inaccurate results in the existing oil-based drilling fluid recovery and treatment process can be solved, and the treatment efficiency and recovery effect can be significantly improved.

[0021] Optionally, the above method can also be used for environmental compliance assessment of oil-based drill cuttings during drilling operations.

[0022] By adopting the above technical solutions, the changes in oil content of oil-based drill cuttings can be accurately monitored, and any exceedances can be detected in a timely manner, providing a reliable basis for environmental compliance management.

[0023] Optionally, the above method can also be used to evaluate the effectiveness of different processing techniques on oil-based drill cuttings.

[0024] By adopting the above technical solutions, the effects of different treatment processes can be accurately evaluated and compared.

[0025] In summary, this application includes at least one of the following beneficial technical effects: This application first queries a dynamic extraction curve database based on sample lithology and processing methods, and determines the optimal extraction time point by calculating the concentration change rate. During the extraction process, multiple samples are taken, and ambient temperature and pressure are measured simultaneously. An environmental impact model is established, incorporating temperature and pressure sub-models, and an environmental correction factor is obtained. Infrared spectroscopy measurements are performed on the extract samples, and data corrections are performed, calculating the mean and standard deviation to eliminate outliers. Finally, piecewise linear equations for different concentration ranges are used to calculate the final oil content. By considering lithological characteristics, environmental impacts, and piecewise linear relationships, the measurement accuracy and reliability are significantly improved. This application first determines the lithology of the collected oil-based drill cuttings samples to obtain basic lithological information, including rock type and structural characteristics. Then, based on the lithological information, it queries a pre-established lithological classification table to obtain corresponding processing methods, such as particle size and extractant selection. Next, it queries a dynamic extraction curve database to obtain the standard dynamic extraction curve for this type of sample. Finally, by calculating the average concentration change rate over a continuous time period, when the change rate is less than a set threshold within a certain time interval, the starting point of that interval is determined as the optimal extraction time point. This achieves precise control of the extraction time, avoiding the problems caused by uniformly setting the extraction time in traditional methods. This application first obtains the actual temperature and pressure measurements of the on-site environment, compares them with standard test conditions, and calculates the temperature and pressure deviations. Then, these deviation values ​​are input into a pre-established environmental influence model, which consists of a temperature influence sub-model and a pressure influence sub-model. The temperature influence sub-model considers not only the temperature deviation but also the sample moisture content as an important parameter, while the pressure influence sub-model combines the pressure deviation and sample density for calculation. Finally, by multiplying the temperature correction coefficient and the pressure correction coefficient, a comprehensive environmental correction factor is obtained. This approach considers the coupling effect of environmental factors such as temperature and pressure with the physical properties of the sample, making the measurement results more accurate and reliable. Attached Figure Description

[0026] Figure 1 This is a schematic flowchart of a method for measuring the oil content of oil-based drill cuttings according to an embodiment of this application; Figure 2 This is a flowchart illustrating step S100 in a method for measuring the oil content of oil-based drill cuttings according to an embodiment of this application. Figure 3 This is a flowchart illustrating step S300 in a method for measuring the oil content of oil-based drill cuttings according to an embodiment of this application. Figure 4 This is a flowchart illustrating step S330 in a method for measuring the oil content of oil-based drill cuttings according to an embodiment of this application. Figure 5 This is a flowchart illustrating step S400 in a method for measuring the oil content of oil-based drill cuttings according to an embodiment of this application. Figure 6 This is a flowchart illustrating step S600 in a method for measuring the oil content of oil-based drill cuttings according to an embodiment of this application. Figure 7 This is a flowchart illustrating step S620 in a method for measuring the oil content of oil-based drill cuttings according to an embodiment of this application. Detailed Implementation

[0027] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0028] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0029] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0030] Firstly, this application provides a method for measuring the oil content of oil-based drill cuttings, referring to... Figure 1 It includes the following steps: S100. Obtain the lithological type and processing method of the sample, and determine the optimal extraction time point based on the dynamic extraction curve corresponding to the lithological type and processing method.

[0031] In this embodiment, the lithological types include shale, sandstone, mudstone, and limestone; the processing methods include centrifugation, extraction, and washing. The dynamic extraction curve refers to the relationship between the oil concentration in the extract and extraction time under fixed extraction conditions; the optimal extraction time is the time when the curve reaches a stable plateau.

[0032] Specifically, this invention establishes a mapping table of lithology type, treatment method, and extraction curve. The corresponding dynamic extraction curve parameters, including the time points of the rising phase, stable phase, and decay phase, are obtained by querying this mapping table. The start of the stable phase is selected as the optimal extraction time. For shale, the optimal extraction time is 10-15 minutes; for sandstone, the optimal extraction time is 8-12 minutes.

[0033] S200. During the optimal extraction time, multiple samples are taken at preset time intervals to obtain extract samples at multiple time points.

[0034] In this embodiment, the preset time interval refers to the time interval between sampling within the optimal extraction time range, and multi-point sampling is to improve the reliability of the measurement.

[0035] S300. Measure the ambient temperature and pressure, input the ambient temperature and pressure into a preset environmental impact model, and obtain the environmental correction factor.

[0036] In this embodiment, the environmental impact model is a mathematical model that describes the influence of temperature and pressure on the infrared spectroscopy measurement results, and the environmental correction factor is used to correct the measurement results.

[0037] Specifically, thermometers and pressure gauges were used to measure the temperature and pressure of the experimental environment, respectively. A temperature-pressure-correction factor lookup table was established, and the environmental correction factors were obtained by looking up the table.

[0038] S400. Infrared spectroscopy measurements are performed on multiple extract samples to obtain absorbance data sequences, and the absorbance data are corrected according to the environmental correction factor.

[0039] In this embodiment, infrared spectroscopy measurement employs the transmission method to measure the absorbance of the extract at a characteristic wavelength. The absorbance data sequence refers to the set of measurement results for samples at multiple time points.

[0040] Specifically, measurements were performed within the 2920-2940 cm⁻¹ wavenumber range, using carbon tetrachloride as a reference. The extract was placed in a measurement cell with a path length of 0.5-1 mm, and the number of scans was 16-32. The measured absorbance was corrected according to an environmental correction factor.

[0041] S500: Based on the corrected absorbance data sequence, calculate the average value and standard deviation, and obtain the valid measurement results after removing outliers.

[0042] In this embodiment, outliers refer to measurement data whose deviation from the average value exceeds a preset threshold. Valid measurement results are the average value of the data after removing outliers.

[0043] Specifically, the arithmetic mean and standard deviation of the absorbance data sequence are calculated, and data points deviating from the mean by more than twice the standard deviation are marked as outliers and removed. The mean of the remaining data is recalculated and used as the valid measurement result.

[0044] S600. Substitute the effective measurement results into the pre-established segmented working curve to obtain the final oil content.

[0045] The segmented working curves include multiple linear equations for different concentration ranges.

[0046] In this embodiment, the segmented working curve refers to the linear relationship equation between absorbance and oil content established in different concentration ranges.

[0047] Specifically, the oil content range is divided into low-concentration, medium-concentration, and high-concentration ranges. Linear equations for each range are established using standard samples, and the corresponding working curve is selected for calculation based on the range in which the effective measurement results fall.

[0048] In one embodiment, refer to Figure 2 In step S100, the lithological type and processing method of the sample are obtained, and the optimal extraction time point is determined based on the dynamic extraction curve corresponding to the lithological type and processing method. This specifically includes the following steps: S110. Obtain the lithological type of the sample, and query the preset lithological classification table according to the lithological type to obtain the corresponding processing method.

[0049] In this embodiment, the lithology classification table is a classification system based on the physical properties of rocks, which includes the correspondence between lithology types and recommended treatment methods. This classification table categorizes rocks according to their grain size, porosity, permeability, and mineral composition, with each lithology type corresponding to one or more applicable treatment methods.

[0050] Specifically, the lithological classification table divides rocks into three categories based on grain size: coarse-grained, medium-grained, and fine-grained; three categories based on porosity: high-porosity, medium-porosity, and low-porosity; and three categories based on permeability: high-permeability, medium-permeability, and low-permeability. These physical parameters form a multi-dimensional classification matrix, with each combination corresponding to a specific treatment method. For example, high-porosity, high-permeability sandstone corresponds to centrifugation treatment, while low-porosity, low-permeability shale corresponds to extraction treatment. The classification table also includes the process parameter ranges for each treatment method, facilitating operators to quickly determine the treatment conditions.

[0051] S120. Based on the processing method, query the pre-established dynamic extraction curve database to obtain the corresponding dynamic extraction curve.

[0052] In this embodiment, the dynamic extraction curve database stores extraction process data under different treatment methods, including extraction time, extract concentration, and extraction efficiency. This database was established through statistical analysis of a large amount of experimental data.

[0053] Specifically, the database is indexed according to processing methods, with multiple sets of extraction curve data under each method. Data collection covers the entire extraction process, including the initial stage, rapid rise stage, steady-state stage, and decay stage. Extract concentration and extraction efficiency are expressed as relative percentages.

[0054] S130. Calculate the average concentration change rate before and after each time point based on the dynamic extraction curve. When the average concentration change rate is less than a preset threshold within a continuous time interval of a preset length, determine the starting time point of the continuous time interval as the optimal extraction time point.

[0055] In this embodiment, the average concentration change rate refers to the ratio of the change in extract concentration between adjacent time points to the time interval. The preset length of the continuous time interval refers to the time window used to determine whether the extraction process has reached a stable state. The preset threshold is the critical value of the concentration change rate for determining whether the extraction process is stable.

[0056] Specifically, a continuous time interval of a certain length is selected, and the concentration change rate per unit time within that interval is calculated. When the concentration change rate of multiple consecutive data points is lower than a preset critical value, the extraction process is considered to have reached stability, and the starting time point of this continuous interval is determined as the optimal extraction time point. A sliding time window method is used for calculation to ensure that the earliest stable time point is obtained, effectively avoiding false stability judgments caused by random fluctuations.

[0057] In one embodiment, refer to Figure 3 In step S300, the ambient temperature and pressure are measured, and the ambient temperature and pressure are input into a preset environmental impact model to obtain an environmental correction factor. Specifically, this includes the following steps: S310: Obtain the current ambient temperature and pressure measurements.

[0058] In this embodiment, the temperature measurement value refers to the actual temperature reading obtained using a thermometer in the measurement environment, and the pressure measurement value refers to the actual pressure reading obtained using a pressure gauge in the measurement environment. Standard temperature and standard pressure refer to the reference environmental parameters specified by the laboratory.

[0059] Specifically, a mercury thermometer was used to measure the ambient temperature, with measurements taken at four points around the sample placement point, and the average value was recorded as the temperature reading. A digital pressure gauge was used to measure the ambient pressure, and data was recorded at fixed intervals during the experiment. The laboratory-specified standard temperature and pressure were recorded as fixed reference values ​​in the work manual.

[0060] S320. The measured temperature and pressure values ​​are compared with the standard temperature and standard pressure, respectively, to obtain the temperature deviation and pressure deviation.

[0061] In this embodiment, temperature deviation represents the difference between the actual measured temperature and the standard temperature, and pressure deviation represents the difference between the actual measured pressure and the standard pressure.

[0062] Specifically, a temperature-pressure deviation record table is established to compare the measured values ​​with standard values. The record table includes five data items: measurement time, temperature measurement value, pressure measurement value, temperature deviation value, and pressure deviation value. When the temperature or pressure deviation exceeds the preset range, the system issues an alert signal to prompt the operator to pay attention to changes in environmental conditions.

[0063] S330. Based on the temperature deviation and pressure deviation, the temperature correction coefficient and pressure correction coefficient are calculated using a preset environmental impact model.

[0064] The environmental impact model includes a temperature impact sub-model and a pressure impact sub-model. The input parameters of the temperature impact sub-model include temperature deviation and sample moisture content, and the input parameters of the pressure impact sub-model include pressure deviation and sample density.

[0065] In this embodiment, the temperature effect sub-model describes the influence of temperature changes on the measurement results, and the pressure effect sub-model describes the influence of pressure changes on the measurement results. Sample moisture content and density are important parameters affecting the effectiveness of environmental factors.

[0066] Specifically, the temperature influence sub-model adopts a piecewise linear correction method to establish a correspondence table between temperature deviation and correction coefficient. This correspondence table is divided into multiple intervals according to the moisture content of the sample, and different correction coefficients are used in each interval. The pressure influence sub-model obtains the correction coefficient by querying the pressure-density correction curve graph. The abscissa of the curve graph is the pressure deviation, and the ordinate is the correction coefficient. Different density intervals correspond to different curves. The temperature influence sub-model is expressed by a piecewise linear function. For example, when the moisture content W ≤ 5%, Kt = 0.002×ΔT + 1.0; when 5% < W ≤ 15%, Kt = 0.004×ΔT + 1.0; when W > 15%, Kt = 0.006×ΔT + 1.0, where Kt is the temperature correction coefficient and ΔT is the temperature deviation. When the moisture content of the sample exceeds the preset threshold of 15%, a weighted correction formula is adopted, Kt correction = Kt×[1 + 0.05×(W - 15%)], so as to adapt to the sensitive characteristics of high-moisture-content samples to temperature changes. The pressure influence sub-model adopts a density sub-region linear correction method. For example, when the density ρ ≤ 1.2 g / cm³, Kp = 0.001×ΔP + 1.0; when 1.2 g / cm³ < ρ ≤ 2.0 g / cm³, Kp = 0.002×ΔP + 1.0; when ρ > 2.0 g / cm³, Kp = 0.003×ΔP + 1.0, where Kp is the pressure correction coefficient and ΔP is the pressure deviation. When the density of the sample exceeds the preset threshold of 2.0 g / cm³, a weighted correction formula is adopted, Kp correction = Kp×[1 + 0.08×(ρ - 2.0)].

[0067] Furthermore, the environmental influence model of this embodiment also introduces a time response characteristic to consider the dynamic process of environmental parameter changes. Specifically, through continuous monitoring, it is found that the changes in environmental temperature and pressure do not instantaneously affect the measurement results, but there is a certain response lag. This application establishes a correspondence table between the change rate of environmental parameters and the response time, and selects the corresponding delay correction coefficient according to the change rates of temperature and pressure. For the case where the temperature change rate is greater than the first preset threshold or the pressure change rate is greater than the second preset threshold, a sub-period correction method is adopted, that is, the environmental parameters at the initial, intermediate, and final states are respectively recorded during the measurement process, and the actual correction coefficients at each time point are obtained through interpolation calculation. This dynamic correction method considering the time response characteristic avoids the lag error that may be brought by traditional single-point correction.

[0068] Furthermore, this embodiment records the temperature correction coefficient, pressure correction coefficient and their corresponding measurement accuracies under different working conditions by establishing a historical correction coefficient database. When the cumulative measurement times of a certain working condition reach the preset threshold, the system automatically analyzes the distribution characteristics of the correction coefficients under this working condition and establishes a mapping model between the working condition characteristics and the correction coefficients.

[0069] Specifically, the calculation formula for the mapping model is Ki = ΣWj·Fj(Pi), where Ki is the predicted value of the correction coefficient under a certain working condition, Wj is the weight coefficient of different feature parameters, Fj(Pi) is the influence function corresponding to each feature parameter, and Pi is the characteristic parameter of the working condition. When the similarity between the characteristics of a new measurement working condition and a certain working condition in the historical database exceeds a preset threshold, the system will use the mapping model under that working condition to predict the correction coefficient and compare it with the real-time calculated value. If the deviation between the two exceeds the allowable range, the anomaly analysis process will be triggered, including retesting of sample feature parameters and judgment of environmental impact anomalies. The influence function Fj(Pi) adopts the form of a linear similarity function: F1(P1)=1-|P1-P1ref| / R1, F2(P2)=1-|P2-P2ref| / R2, F3(P3)=1-|P3-P3ref| / R3, F4(P4)=1-|P4-P4ref| / R4, where P1, P2, P3, and P4 are the temperature deviation, pressure deviation, moisture content, and density values ​​under the current operating conditions, respectively; P1ref, P2ref, P3ref, and P4ref are the corresponding reference values ​​under historical operating conditions; and R1, R2, R3, and R4 are the maximum tolerance ranges for each parameter, taking 0 when the influence function value is less than 0. The weighting coefficients are set according to the importance of the parameters: temperature weight W1=0.4, pressure weight W2=0.3, moisture content weight W3=0.2, and density weight W4=0.1.

[0070] S340. Multiply the temperature correction coefficient and the pressure correction coefficient to obtain the environmental correction factor.

[0071] In this embodiment, the environmental correction factor is the combined effect of the temperature correction coefficient and the pressure correction coefficient, and is used to correct the measurement data as a whole.

[0072] Specifically, a correction factor calculation table is established, and the temperature correction factor and pressure correction factor are substituted into the calculation formula. When the product of the two correction factors is within a reasonable range, this value is directly used as the environmental correction factor; when the product exceeds a reasonable range, a secondary correction mechanism is activated, and a piecewise function is used for correction to ensure that the final correction factor has physical meaning.

[0073] In one embodiment, refer to Figure 4 In step S330, based on the temperature deviation and pressure deviation, the temperature correction coefficient and pressure correction coefficient are calculated using a preset environmental impact model, specifically including the following steps: S331. Measure the moisture content and density of the sample.

[0074] In this embodiment, the sample moisture content refers to the percentage of water content in the sample relative to its total weight, and the density refers to the mass per unit volume of the sample.

[0075] S332. Input the temperature deviation and sample moisture content into the temperature influence sub-model to obtain the temperature correction coefficients under different moisture contents.

[0076] In this embodiment, the temperature influence sub-model describes the influence of temperature changes on the measurement results under different moisture contents. It is established based on a large amount of experimental data and uses a piecewise linear fitting method to describe the relationship between the temperature correction coefficient and the temperature deviation.

[0077] Specifically, a moisture content grading correction table is established, dividing the moisture content into low, medium, and high ranges. Each range corresponds to a different temperature influence curve, with the curve slope increasing as the moisture content increases. The temperature correction coefficient is calculated using a lookup table interpolation method; first, the range to which the moisture content belongs is determined, and then the correction coefficient is calculated based on the temperature deviation.

[0078] S333. Input the pressure deviation and sample density into the pressure influence sub-model to obtain the pressure correction coefficients under different densities.

[0079] Specifically, when the sample moisture content is greater than a preset threshold, the temperature correction coefficient is weighted and corrected; when the sample density is greater than a preset threshold, the pressure correction coefficient is weighted and corrected.

[0080] In this embodiment, the pressure influence sub-model describes the influence of pressure changes on the measurement results under different density conditions. The density regional correction method is used to establish the correspondence between the pressure correction coefficient and the pressure deviation.

[0081] Specifically, a density-pressure correction matrix is ​​established, with the horizontal axis representing the pressure deviation range and the vertical axis representing the density range. Matrix elements are the corresponding pressure correction coefficients. Initial correction coefficients are obtained by querying the matrix, and then linear interpolation is performed based on the actual density values ​​to obtain the final pressure correction coefficients.

[0082] When the sample moisture content exceeds a preset threshold, it indicates that the sample is more sensitive to the influence of ambient temperature and requires special treatment. A weighted coefficient table is established, and appropriate weighted coefficients are selected based on the degree to which the moisture content exceeds the threshold to correct the temperature correction coefficient. Similarly, when the sample density exceeds a preset threshold, it indicates that pressure changes have a greater impact on the sample, and the pressure correction coefficient needs to be adjusted using weighted coefficients.

[0083] In one embodiment, refer to Figure 5 In step S400, the absorbance data is corrected according to the environmental correction factor, specifically including the following steps: S410. Obtain absorbance data of multiple characteristic peaks in the absorption region of hydrocarbon characteristic functional groups of the extract sample.

[0084] In this embodiment, the absorption region of characteristic functional groups of hydrocarbons refers to the wavenumber range in the infrared spectrum that reflects the structural characteristics of hydrocarbon compounds. Characteristic peak absorbance data refers to the absorbance values ​​measured at these specific wavenumber positions.

[0085] Specifically, a hydrocarbon characteristic peak identification table is established, including characteristic wavenumbers of three main absorption regions: the CH stretching vibration band, the CH bending vibration band, and the C=C stretching vibration band. Multiple characteristic wavenumber points are selected in each region for measurement, forming a characteristic peak dataset.

[0086] S420. Calculate the absorbance deviation of each characteristic peak under environmental influence based on the environmental correction factor.

[0087] In this embodiment, the absorbance deviation represents the degree to which the absorbance measurement deviates from the true value due to environmental factors. The deviation is related to the environmental correction factor, the wavenumber position of the characteristic peak, and the magnitude of the absorbance.

[0088] Specifically, a characteristic peak-environment response table is established to record the sensitivity of different characteristic peaks to environmental changes. The response coefficient of each characteristic peak is obtained by looking up the table, and then multiplied by an environmental correction factor to obtain the absorbance deviation of each characteristic peak. Different response coefficients are used for characteristic peaks in different wavenumber ranges to reflect the wavelength dependence of environmental influences.

[0089] S430. The absorbance deviation is corrected by calculating the absorbance data of the corresponding characteristic peak to obtain the corrected absorbance value of the characteristic peak.

[0090] In this embodiment, correction calculation refers to the process of correcting the original absorbance data based on the calculated deviation. Different characteristic peaks may require different correction methods.

[0091] Specifically, a characteristic peak correction scheme library is established, including linear correction, exponential correction, and piecewise correction. An appropriate correction scheme is selected based on the wavenumber position and absorbance of the characteristic peak. Piecewise correction is used for the main peak with high absorbance, while linear correction is used for the secondary peaks with lower absorbance, ensuring the reasonableness of the correction results.

[0092] S440. Normalize the corrected characteristic peak absorbance values ​​according to the concentration of the extract to obtain the final correction result.

[0093] In one embodiment, refer to Figure 6 In step S600, the effective measurement results are substituted into the pre-established segmented working curve to obtain the final oil content, which specifically includes the following steps: S610. Select the corresponding concentration range interval based on the numerical range of the effective measurement results.

[0094] In this embodiment, the numerical range refers to the interval between the maximum and minimum values ​​of the valid measurement results. The concentration range refers to the interval of measurement results corresponding to different oil content levels, which are pre-defined.

[0095] Specifically, a measurement result zoning table is established, dividing the entire measurement range into low-concentration, medium-concentration, and high-concentration intervals. Upper and lower thresholds are set for each interval, and the interval is determined by comparing the relationship between the effective measurement results and these thresholds. The zoning table is based on test data from a large number of standard samples, ensuring a good linear relationship between the measurement results and oil content within each interval.

[0096] S620. Within the concentration range, obtain the corresponding linear equation parameters.

[0097] In this embodiment, the linear equation parameters include slope and intercept, which are used to describe the quantitative relationship between the measurement results and the oil content. Each concentration range corresponds to a unique set of parameter values.

[0098] Specifically, a partitioned parameter matrix is ​​established to record the linear equation parameters for each concentration interval. The parameter matrix is ​​obtained through calibration using standard samples, and the slope and intercept of each interval are obtained by least squares fitting. To improve the reliability of the parameters, they are periodically verified and updated using standard samples to ensure calculation accuracy.

[0099] S630. Substitute the effective measurement results into the selected linear equation to calculate the preliminary oil content.

[0100] In this embodiment, the preliminary oil content refers to the result calculated only considering the linear relationship, without volume correction, which reflects the basic correspondence between the measurement result and the oil content.

[0101] Specifically, based on the selected concentration range, the corresponding slope and intercept are extracted from the parameter matrix. The effective measurement results are substituted into the linear equation, and the preliminary oil content is obtained through simple multiplication and addition operations. For measurement results close to the range boundary, a weighted average method is used to calculate the oil content, avoiding abrupt changes at the range transition.

[0102] S640. Based on the sample mass and extractant volume, the preliminary oil content is corrected by volume to obtain the final oil content.

[0103] In this embodiment, volume correction refers to the correction of the calculation results considering the ratio of sample mass to extractant volume.

[0104] Specifically, a volume correction factor table is established to record the correction factors corresponding to different mass-to-volume ratios. The correction factors are obtained by looking up the table, and the initial oil content is multiplied by the correction factor to obtain the final oil content. The correction factor table is established based on the principle of mass conservation, taking into account the relationship between extraction efficiency and mass-to-volume ratio.

[0105] In one embodiment, refer to Figure 7 In step S620, within the concentration range, the corresponding linear equation parameters are obtained, specifically including the following steps: S621. Obtain the absorbance and oil content data of the standard sample according to the concentration range.

[0106] In this embodiment, the standard sample refers to a calibration sample with a known accurate oil content, and the data pair refers to the data combination consisting of the absorbance measurement value of the standard sample and its corresponding actual oil content value.

[0107] Specifically, a standard sample database is established, containing standard sample information for low, medium, and high concentration ranges. Multiple standard samples with varying concentration gradients are selected for each range, and their absorbance measurements and actual oil content are recorded. The selection of standard samples follows a uniform distribution principle to ensure that the data pairs fully reflect the variation patterns across the entire range.

[0108] S622. Perform linear fitting on the absorbance and oil content to obtain the slope and intercept parameters.

[0109] In this embodiment, linear fitting refers to determining the optimal slope and intercept using the least squares method to minimize the overall deviation between the fitted line and the actual data points.

[0110] Specifically, a table for calculating fitting parameters is established to record the data processing methods for different intervals. Weighted least squares is used for fitting, assigning larger weights to data points with lower measurement uncertainty. Optimal solutions for slope and intercept are obtained through matrix operations, and their confidence intervals are recorded.

[0111] S623. Calculate the goodness of fit of the standard sample in the corresponding interval. When the goodness of fit is greater than the preset threshold, determine that the slope and intercept parameters are valid.

[0112] Specifically, for different concentration ranges, the values ​​of the slope and intercept parameters satisfy preset range limiting conditions.

[0113] In this embodiment, goodness of fit refers to the degree to which the fitted straight line interprets the actual data, reflecting the reliability of the linear relationship. A preset threshold is used to determine whether the fitting result meets the accuracy requirements.

[0114] Specifically, a goodness-of-fit evaluation system is established, including three evaluation indicators: correlation coefficient, sum of squared residuals, and prediction error. The reliability of the fitting results is judged by a comprehensive scoring method. When the score exceeds a preset threshold, the fitting parameters are accepted; otherwise, standard samples need to be reselected or the fitting method needs to be adjusted.

[0115] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0116] Secondly, this application provides the application of the above-mentioned method in measuring and / or treating oil-based drill cuttings. At the oil-based drilling fluid recovery and treatment site, the above-mentioned measurement method is used for real-time monitoring of oil content. Sampling points are set at the inlet and outlet of the treatment device, and samples are collected and measured every 30 minutes. The measurement results are displayed in real-time through the on-site control system and are linked to the treatment process parameters. Specifically, when the oil content of the inlet sample exceeds the design value of the treatment system, the system automatically adjusts the feed rate; when the oil content of the outlet sample exceeds the environmental protection limit, the system issues an alarm signal and automatically increases the treatment time. Through this real-time monitoring and linked control, the treatment process is always kept in an optimal state, improving treatment efficiency and recovery effect.

[0117] In the environmental management of drilling sites, the aforementioned measurement methods are used to assess the compliance of oil-based drill cuttings. Multiple monitoring points are set up in the temporary storage and processing areas for drill cuttings, and samples are taken and measured regularly according to sampling specifications. Specifically, an on-site monitoring record form is established, including four basic information items: sample number, sampling location, measurement time, and oil content value. When monitoring results show that the oil content at a certain point is close to the limit, the sampling frequency at that point is increased. Through standardized monitoring and recording, complete data support is provided for environmental compliance assessment.

[0118] During the optimization of the treatment process, the aforementioned measurement methods were applied to evaluate the treatment effects of different processes. Three typical processes—thermal desorption, chemical extraction, and microwave treatment—were selected for comparative experiments. Specifically, a process evaluation index system was established, including three core indicators: oil content after treatment, oil recovery rate, and energy consumption level. By continuously monitoring and recording the operating data of each process, the measurement methods of this invention were used to accurately obtain the changes in oil content before and after treatment. Based on the evaluation results, the treatment process scheme most suitable for the site conditions was selected.

[0119] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for measuring the oil content of oil-based drill cuttings, characterized in that, Includes the following steps: Obtain the lithological type and processing method of the sample, and determine the optimal extraction time point based on the dynamic extraction curve corresponding to the lithological type and processing method; During the optimal extraction time, multiple samples are taken at preset time intervals to obtain extract samples at multiple time points. Measure the ambient temperature and pressure, input the ambient temperature and pressure into a preset environmental impact model, and obtain the environmental correction factor; Infrared spectroscopy measurements were performed on multiple extract samples to obtain absorbance data sequences, and the absorbance data were corrected according to the environmental correction factor. Based on the corrected absorbance data sequence, the mean and standard deviation are calculated, and the valid measurement results are obtained after removing outliers. Substituting the effective measurement results into the pre-established segmented working curve, the final oil content is obtained, wherein the segmented working curve includes multiple linear equations for different concentration ranges.

2. The method for measuring the oil content of oil-based drill cuttings according to claim 1, characterized in that, The lithological type and processing method of the sample are obtained, and the optimal extraction time point is determined based on the dynamic extraction curve corresponding to the lithological type and processing method. This process specifically includes the following steps: Obtain the lithology type of the sample, and query the preset lithology classification table according to the lithology type to obtain the corresponding processing method; Based on the processing method, a pre-established dynamic extraction curve database is queried to obtain the corresponding dynamic extraction curve; The average concentration change rate before and after each time point is calculated based on the dynamic extraction curve. When the average concentration change rate is less than a preset threshold within a continuous time interval of a preset length, the starting time point of the continuous time interval is determined as the optimal extraction time point.

3. The method for measuring the oil content of oil-based drill cuttings according to claim 1, characterized in that, Measuring ambient temperature and pressure, and inputting the ambient temperature and pressure into a preset environmental impact model to obtain environmental correction factors, specifically includes the following steps: Acquire current ambient temperature and pressure measurements; The measured temperature and pressure values ​​are compared with standard temperature and standard pressure, respectively, to obtain the temperature deviation and pressure deviation; Based on the temperature deviation and pressure deviation, temperature correction coefficients and pressure correction coefficients are calculated using a preset environmental impact model. The environmental impact model includes a temperature impact sub-model and a pressure impact sub-model. The input parameters of the temperature impact sub-model include temperature deviation and sample moisture content, and the input parameters of the pressure impact sub-model include pressure deviation and sample density. Multiplying the temperature correction factor and the pressure correction factor together yields the environmental correction factor.

4. The method for measuring the oil content of oil-based drill cuttings according to claim 3, characterized in that, Based on the temperature and pressure deviations, temperature and pressure correction coefficients are calculated using a preset environmental impact model, specifically including the following steps: Measure the moisture content and density of the sample; The temperature deviation and sample moisture content are input into the temperature influence sub-model to obtain temperature correction coefficients for different moisture contents. The pressure deviation and sample density are input into the pressure influence sub-model to obtain the pressure correction coefficients under different densities; Specifically, when the sample moisture content is greater than a preset threshold, the temperature correction coefficient is weighted and corrected; when the sample density is greater than a preset threshold, the pressure correction coefficient is weighted and corrected.

5. The method for measuring the oil content of oil-based drill cuttings according to claim 1, characterized in that, The absorbance data is corrected according to the environmental correction factor, specifically including the following steps: Obtain absorbance data of multiple characteristic peaks in the absorption region of hydrocarbon functional groups in the extract sample; Calculate the absorbance deviation of each characteristic peak under environmental influence based on the environmental correction factor. The absorbance deviation is corrected by calculating the absorbance data of the corresponding characteristic peak to obtain the corrected absorbance value of the characteristic peak. The corrected characteristic peak absorbance values ​​were normalized based on the concentration of the extract to obtain the final corrected result.

6. The method for measuring the oil content of oil-based drill cuttings according to claim 1, characterized in that, Substituting the valid measurement results into the pre-established segmented working curve, the final oil content is obtained, specifically including the following steps: Based on the numerical range of the effective measurement results, select the corresponding concentration range interval; Within the concentration range, obtain the corresponding linear equation parameters; Substitute the effective measurement results into the selected linear equation to calculate the preliminary oil content; Based on the sample mass and extractant volume, the preliminary oil content is corrected by volume to obtain the final oil content.

7. The method for measuring the oil content of oil-based drill cuttings according to claim 6, characterized in that, Within the concentration range, the corresponding linear equation parameters are obtained, specifically including the following steps: The absorbance and oil content data of the standard sample were obtained according to the concentration range. Linear fitting was performed on the absorbance and oil content to obtain the slope and intercept parameters; Calculate the goodness of fit of the standard sample in the corresponding interval. When the goodness of fit is greater than a preset threshold, determine that the slope and intercept parameters are valid. Specifically, for different concentration ranges, the values ​​of the slope and intercept parameters satisfy preset range limiting conditions.

8. The application of the method according to any one of claims 1-7 in measuring and / or treating oil-based drill cuttings, characterized in that, Used for real-time monitoring of oil content during the recovery and treatment of oil-based drilling fluids.

9. The application of the method according to any one of claims 1-7 in measuring and / or treating oil-based drill cuttings, characterized in that, Used for environmental compliance assessment of oil-based drill cuttings during drilling operations.

10. The application of the method according to any one of claims 1-7 in measuring and / or treating oil-based drill cuttings, characterized in that, Used to evaluate the effectiveness of different processing techniques on oil-based drill cuttings.

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