A method and system for detecting the concentration of a polymer in a ternary composite system

Abstract

The application relates to the technical field of polymer concentration detection, in particular to a polymer concentration detection method and system of a ternary composite system, which comprises the following steps: collecting an oil reservoir core sample, determining a linear relationship between polymer concentration and water saturation of an oil layer, and obtaining an ideal polymer concentration; fitting a relationship between the absorbance of a polymer solution and the polymer concentration of the polymer solution at each characteristic wavelength, and determining the degree of linear change of the fitted relationship at each characteristic wavelength; determining the distribution deviation value of the absorbance of all turbid liquids at each characteristic wavelength, which is used for evaluating the turbid liquid distribution difference sensitivity of each characteristic wavelength, and obtaining the polymer concentration detection weight of each characteristic wavelength; and determining the polymer concentration of a ternary composite flooding sample solution at each characteristic wavelength by using the relationship, and obtaining a polymer concentration measurement value after weighted summation. The accuracy of polymer concentration detection is improved.

Description

Technical Field

[0001] This application relates to the field of polymer concentration detection technology, specifically to a method and system for detecting polymer concentration in a ternary composite system. Background Technology

[0002] With the continuous development of domestic oil fields, the difficulty of developing oil reservoirs has further increased. At the same time, low-permeability oil reservoirs account for a considerable proportion of my country's proven geological reserves, and this proportion continues to rise with the deepening of exploration. Due to the characteristics of low permeability, small porosity, and high seepage resistance, conventional extraction methods result in low recovery rates and high costs for low-permeability oil reservoirs.

[0003] For the development of low-permeability reservoirs, traditional methods utilize waterflooding. However, waterflooding suffers from limitations in swept volume, low oil displacement efficiency, and unbalanced mobility control. Therefore, ternary composite flooding is currently being explored to address the development of low-permeability reservoirs. Ternary composite flooding involves injecting polymers, surfactants, and alkalis into the reservoir formation. The polymers increase the viscosity of the injected mixture, reduce the mobility ratio, and expand the swept area of ​​the ternary composite flooding.

[0004] In the development of ternary composite flooding technology, the concentration of the polymer has a crucial impact on the oil displacement effect and produced fluid treatment. The polymer concentration directly affects the viscosity of the ternary composite system. Furthermore, high polymer concentrations increase the viscosity of the produced fluid, making oil-water separation more difficult and leading to scaling and emulsification problems in the equipment. Therefore, it is necessary to monitor the polymer concentration in real time based on the actual reservoir conditions.

[0005] Existing technologies reduce the influence of surfactants in ternary composite flooding mixtures by adding petroleum ether and reduce the influence of alkali by using acetic acid. Finally, quantitative analysis of polymer concentration is performed using a spectrophotometer based on Beer-Lambert's law. The turbidimetric method mainly utilizes the reaction of the polymer with sodium hypochlorite under acidic conditions to form insoluble ammonium chlorate, causing turbidity in the solution, thus enabling quantitative analysis based on turbidity. However, in practice, the influence of additives on spectrophotometer absorbance and the distribution of the insoluble ammonium chlorate leads to deviations between the measured absorbance and the true absorbance of the polymer, affecting the repeatability and accuracy of quantitative analysis of polymer concentration, resulting in low precision in polymer concentration detection. Summary of the Invention

[0006] To address the aforementioned technical problems, the purpose of this application is to provide a method and system for detecting polymer concentration in a ternary composite system. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a method for detecting polymer concentration in a ternary composite system, the method comprising the following steps: By collecting reservoir core samples, the linear relationship between polymer concentration and water saturation of the oil layer was determined based on experimental measurement methods, and the ideal polymer concentration was obtained. The relationship between the absorbance of polymer solutions and their polymer concentration at each selected characteristic wavelength was fitted experimentally, and the degree to which the fitted relationship at each characteristic wavelength conformed to the linear change was determined. The absorbance of each turbid liquid in the ternary composite flooding sample solution after turbidity treatment was measured by turbidity method at each characteristic wavelength; the distribution deviation of absorbance of all turbid liquids at each characteristic wavelength was determined to evaluate the sensitivity of turbid liquid distribution difference at each characteristic wavelength; and the polymer concentration detection weight at each characteristic wavelength was obtained by combining the degree of linear change of the relationship. Using the aforementioned relationship, the polymer concentration of the ternary composite flooding sample solution at each characteristic wavelength is determined. After weighted summation, the measured polymer concentration value is obtained. The deviation from the ideal polymer concentration is compared to adjust the polymer concentration accordingly.

[0007] In one embodiment, determining the linear relationship between polymer concentration and water saturation of the oil layer includes: By measuring the relative permeability of the water phase and the relative permeability of the oil phase in the core sample, the water-oil mobility ratio is calculated to determine the correlation between water saturation and the water-oil mobility ratio. By conducting mobility tests on core samples, the correlation between polymer concentration and drag coefficient was determined. Combined with the correlation between water saturation and water-oil mobility ratio, a linear relationship between polymer concentration and water saturation of the oil reservoir was derived under set critical conditions. The specific expression is as follows: ;in, For the ideal polymer concentration, This indicates the water saturation level of the oil layer.

[0008] In one embodiment, the selection of the characteristic wavelengths includes: The absorbance of a polymer solution with a known polymer concentration at various wavelengths across the entire spectrum is measured, and the characteristic wavelengths are obtained after principal component analysis.

[0009] In one embodiment, determining the degree to which the fitted relationship at each characteristic wavelength conforms to a linear change includes: Determine the linear correlation coefficient after fitting the relationship at each characteristic wavelength, and the sum of squares of all fitting residuals. The degree to which the fitted relationship at each characteristic wavelength conforms to linear change is the ratio of the linear correlation coefficient to the sum of squares.

[0010] In one embodiment, determining the distribution deviation value of absorbance of all turbid liquids at each characteristic wavelength includes: Calculate the mean absorbance of all turbid liquids at each characteristic wavelength, determine the degree of deviation of the absorbance of each turbid liquid at each characteristic wavelength from the mean, and the distribution deviation value of the absorbance of all turbid liquids at each characteristic wavelength is the mean of the degree of deviation of all turbid liquids at each characteristic wavelength.

[0011] In one embodiment, the degree of deviation is the absolute value of the difference between the absorbance of each turbid liquid at each characteristic wavelength and the mean value.

[0012] In one embodiment, the assessment of the sensitivity to differences in turbidity distribution at each characteristic wavelength includes: Calculate the average value of the distribution deviation values ​​at all characteristic wavelengths. The sensitivity of the turbidity distribution difference at each characteristic wavelength is the ratio of the distribution deviation value at each characteristic wavelength to the average value.

[0013] In one embodiment, the polymer concentration detection weight is a normalized result of the ratio of the degree to which the fitted relationship at each characteristic wavelength conforms to a linear change to the sensitivity of the turbidity distribution difference.

[0014] In one embodiment, adjusting the polymer concentration includes: If the deviation between the measured polymer concentration and the ideal polymer concentration is within the allowable error range, the polymer concentration of the ternary composite flooding sample solution will not be adjusted; otherwise, the polymer concentration of the ternary composite flooding sample solution will be adjusted until it is less than the allowable error.

[0015] Secondly, embodiments of this application also provide a polymer concentration detection system for a ternary composite system, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0016] This application has at least the following beneficial effects: This application uses experimental methods to determine the linear relationship between polymer concentration and reservoir water saturation, ensuring a closer match between the ideal polymer concentration and the actual reservoir conditions. This provides a reliable basis for polymer concentration correction before ternary composite flooding injection. By fitting the relationship between absorbance and polymer concentration at multiple characteristic wavelengths, the linearity of the fitting relationship at each wavelength is determined, enhancing the quantitative analysis of polymer solution concentration. This ensures that the measured values ​​at different wavelengths exhibit a good linear trend, providing a stable basis for subsequent polymer concentration detection and avoiding errors that may be caused by nonlinear changes, thus ensuring the stability and reliability of each polymer concentration detection. Turbidity methods are used to measure the absorbance at different characteristic wavelengths... The absorbance of the turbid liquid was measured, and the distribution deviation of each absorbance was analyzed to help assess the sensitivity of each characteristic wavelength in the polymer concentration detection process. The wavelength most sensitive to changes in the composition of the turbid liquid was identified, enhancing the selectivity and accuracy of polymer concentration detection, avoiding dependence on inapplicable characteristic wavelengths, and improving the measurement efficiency and accuracy of polymer concentration. By obtaining the polymer concentration detection weight of each characteristic wavelength, the polymer concentration at each characteristic wavelength was weighted and summed to differentiate the contribution of polymer concentration measured at different characteristic wavelengths. This reduced the interference of highly sensitive wavelengths on polymer concentration measurement, enhanced the flexibility and applicability of polymer concentration detection, and improved the accuracy of polymer concentration detection. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating the steps of a polymer concentration detection method for a ternary composite system provided in one embodiment of this application; Figure 2 This is a diagram of relative permeability curves; Figure 3 A graph showing the relationship between water saturation and water-oil mobility ratio; Figure 4 This is a graph showing the relationship between polymer concentration and drag coefficient. Figure 5 This is a graph showing the relationship between water saturation and polymer concentration. Detailed Implementation

[0019] To further illustrate the technical means and effects adopted by this application to achieve the intended inventive purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a polymer concentration detection method and system for a ternary composite system proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0021] The following description, in conjunction with the accompanying drawings, details the specific scheme of the polymer concentration detection method and system for a ternary composite system provided in this application.

[0022] Please see Figure 1 The diagram illustrates a flowchart of a polymer concentration detection method for a ternary composite system according to an embodiment of this application. The method includes the following steps: S1. By collecting reservoir core samples, the linear relationship between polymer concentration and water saturation of the oil layer was determined based on experimental measurement methods to obtain the ideal polymer concentration.

[0023] Low-permeability reservoirs, characterized by numerous layers, low permeability, high clay content, and high water saturation, often exhibit poor performance with traditional waterflooding. Therefore, ternary composite flooding is employed for these reservoirs. In ternary composite flooding, the concentrations of polymers and surfactants significantly impact the sweep efficiency and reservoir recovery of the mixture. Since different low-permeability reservoirs exhibit varying characteristics, customized ternary composite flooding schemes are required for different reservoirs. Current technologies primarily address the specific conditions of high water saturation and high clay content in low-permeability reservoirs, lacking a dynamic adjustment mechanism for polymer concentration and a compensation method for surfactant adsorption loss, resulting in limited interfacial tension.

[0024] Therefore, in order to achieve high recovery rates, a reasonable ternary composite flooding scheme needs to be developed for low-permeability reservoirs.

[0025] The key role of polymers is to regulate the mobility of the mixture, and mobility control capability is a crucial parameter for expanding the swept volume of an oil displacement system. Based on prior knowledge of the oil displacement process, the higher the water saturation in the reservoir, the greater the corresponding water-oil mobility ratio, thus requiring a higher polymer concentration to achieve mobility control. To address this issue, we aim to establish a relationship between reservoir water saturation and injected polymer concentration based on prior knowledge, thereby enabling the quantitative design of polymer concentrations.

[0026] This embodiment obtains the corresponding relative permeability curve by collecting reservoir core samples and determining it using experimental methods (steady-state method or centrifugation method), as detailed below. Figure 2 As shown, Figure 2 The left vertical axis represents relative permeability, the right vertical axis represents water cut, and the horizontal axis represents water saturation. Here, Kro represents the relative permeability of the oil phase, Krw represents the relative permeability of the water phase, and Fw represents the water cut. Figure 2 The results reflect the correlation between water saturation and the three factors. In this embodiment, the steady-state method was used for experimental determination; however, the implementer may choose other methods, such as centrifugation.

[0027] In the relative permeability curve diagram, the ratio of the measured relative permeability of the water phase to the relative permeability of the oil phase is calculated to obtain the corresponding water-oil mobility ratio, i.e., the water-oil mobility ratio. for From this, the correlation between water saturation and water-oil mobility ratio can be deduced. Figure 3 This is a graph showing the relationship between water saturation and water-oil mobility ratio. Figure 3 The horizontal axis represents water saturation, and the vertical axis represents the water-oil mobility ratio, which is a dimensionless quantity.

[0028] Furthermore, by using the mobility test of reservoir core samples, the corresponding polymer concentration and drag coefficient can be obtained. The relationship between polymer concentration and drag coefficient is shown in the graph below. Figure 4 As shown, Figure 4 The horizontal axis represents the polymer concentration in mg / L, and the vertical axis represents the drag coefficient, a dimensionless quantity. Based on this, the relationship between the polymer-to-oil mobility ratio, water-to-oil mobility, and drag coefficient can be established. The polymer-to-oil mobility ratio represents the ratio of polymer mobility to oil mobility. The specific relationship is as follows:

[0029] In the formula, This represents the oil-to-polymer mobility ratio, a dimensionless quantity. , , These represent polymer flow rate, oil flow rate, and aqueous flow rate, respectively, in units of D·m / mPa·s. This represents the drag coefficient, a dimensionless quantity. This represents the water-oil mobility ratio. This formula establishes the correlation between the oil-oil mobility ratio and the water-oil mobility ratio.

[0030] Based on the critical design conditions in mobility control theory, when the polymer-to-oil mobility ratio is 1, the water-to-oil mobility ratio is equal to the drag coefficient. Therefore, in this embodiment, the relationship between polymer concentration and drag coefficient is transformed to obtain the water saturation. and polymer concentration Relationship diagram, specifically as follows Figure 5 As shown, Figure 5 The horizontal axis represents water saturation, and the vertical axis represents polymer concentration. This allows for the quantitative design of polymer concentration based on the water saturation of the core sample.

[0031] Furthermore, this embodiment is based on water saturation. and polymer concentration Relationship diagram, for Figure 5 By performing linear fitting on the discrete points in the matrix, the design formula for the corresponding polymer concentration is obtained, and the specific expression is as follows: In the formula, To design the polymer concentration, i.e. the ideal polymer concentration, the unit is mg / L. This indicates the water saturation of the oil layer, expressed as a percentage. It should be noted that the water saturation value in the polymer concentration calculation is the percentage before the percentage. For example, if the water saturation of the oil layer is 53.21%, then the specific value calculated in the formula will be... .

[0032] Because low-permeability reservoirs often contain high levels of clay, and clay minerals have high adsorption properties, it is necessary to increase the concentration of surfactants in the ternary system to compensate for adsorption losses in the reservoir and improve the oil displacement efficiency of the ternary composite system. This embodiment, based on the traditional oilfield ternary composite flooding scheme, quantifies the surfactant concentration using a formula based on the amount of surfactant adsorption losses in the reservoir. Specifically: In the formula, This indicates the adjusted concentration of the surfactant, in mg / L. This indicates the concentration of the surfactant before adjustment, in mg / L. This represents the loss of surfactant in low-permeability oil reservoirs compared to conventional oil reservoirs, expressed as a percentage. The specific value is obtained through static adsorption tests on core samples, measuring the current reservoir's surfactant consumption.

[0033] Thus, it is possible to design a ternary composite flooding scheme for oil reservoirs, and to achieve dynamic compensation of polymer concentration and surfactant concentration for different reservoir conditions, thereby improving the accuracy of ternary composite flooding flow control and oil recovery rate.

[0034] S2, using experiments to fit the relationship between the absorbance of the polymer solution and its polymer concentration at each characteristic wavelength, and determining the degree to which the fitted relationship at each characteristic wavelength conforms to a linear change.

[0035] In ternary composite flooding processes, dynamic monitoring of polymer concentrations in both the injected and produced fluids is crucial for guiding production and dynamic analysis and adjustments. Specifically, prior to injection, polymer concentration testing of the ternary composite system is necessary to determine if it meets design requirements and to assess whether adjustments are needed.

[0036] In ternary composite flooding mixtures, turbidimetric methods are commonly used to determine the polymer concentration. The main principle is that the polymer reacts with sodium hypochlorite in an acidic solution to form insoluble ammonium chlorate, causing turbidity. The degree of turbidity in the mixture is directly proportional to the polymer concentration. Therefore, by measuring the absorbance of the mixture using a spectrophotometer, quantitative analysis of the polymer concentration is achieved based on Beer-Lambert's law.

[0037] Currently, existing technologies reduce the influence of surfactants in the mixed solution by introducing petroleum ether extraction, and utilize hypochlorous acid to reduce the influence of alkali on the measurement. Finally, polymer concentration is directly determined based on the absorbance of a spectrophotometer. However, in this method, the addition of extra components affects the spectrophotometer's absorbance measurement. Furthermore, traditional methods measure absorbance at multiple wavelengths and use the average concentration as the result for quantitative analysis of polymer concentration. However, in practice, different wavelengths have varying sensitivities to the components in the mixed solution, which further amplifies the deviation in polymer concentration measurement, affecting the final measurement results.

[0038] Based on the above analysis, this embodiment first uses an analytical balance to weigh a fixed mass of polymer powder (polyacrylamide HPAM), requiring the analytical balance to have an accuracy of no more than 0.1 mg. In addition, using distilled water as a solvent, the polymer powder is dissolved to a specific volume to prepare standard polymer solutions with fixed concentrations of 100 mg / L, 200 mg / L, 300 mg / L, ..., 2400 mg / L, and 2500 mg / L, for a total of 25 fixed concentrations.

[0039] Then, a standard polymer solution of fixed concentration is arbitrarily selected, and the absorbance is measured using a spectrophotometer to select characteristic wavelengths. Specifically, the absorbance of the standard polymer solution is measured across the entire wavelength range of 190 nm to 1100 nm. Principal component analysis (PCA) is used to select characteristic wavelengths, with the number of selected characteristic wavelengths set between 2 and 10. In a preferred embodiment, the number of characteristic wavelengths is set to 3, denoted as follows: , , PCA (Principal component analysis) algorithm is a well-known existing technology. Implementers can choose other feasible characteristic wavelength selection methods, and this embodiment does not impose any restrictions on this.

[0040] Finally, based on the configured standard polymer solutions of fixed concentration, the insoluble matter in the mixture was obtained by turbidimetry. The absorbance of each standard polymer solution was measured using three characteristic wavelengths. For each characteristic wavelength, the absorbance of each standard polymer solution was obtained. Combined with the polymer concentration of the standard polymer solutions, a data set for each standard polymer solution was obtained, containing both the absorbance and polymer concentration. Linear fitting was performed on the data sets of all standard polymer solutions at each characteristic wavelength to obtain the relationship between absorbance and polymer concentration at each characteristic wavelength. For example... A and c represent absorbance and polymer concentration, respectively. Indicates at the characteristic wavelength The relationship between absorbance and polymer concentration. Using the same method, the following can be obtained: and ,in, Indicates at the characteristic wavelength The relationship between absorbance and polymer concentration. Indicates at the characteristic wavelength The relationship between absorbance and polymer concentration is presented. In this embodiment, the least squares method is used for linear fitting. Implementers may choose other existing feasible linear fitting algorithms, and this embodiment does not impose any restrictions on this.

[0041] Based on Beer-Lambert's law, it is known that there is a linear relationship between absorbance measured by spectrophotometer and polymer concentration. However, the introduction of additional components in the quantitative determination process of turbidimetric method will interfere with the absorbance measurement of polymer insoluble matter and may cause deviations during the measurement process. This results in different characteristic wavelengths having different sensitivities to additional components in the mixture. Consequently, the actual measured absorbance is not only related to polymer concentration but also affected by other components in the turbid solution, which may interfere with the linear relationship. Therefore, this embodiment performs a linear correlation analysis on the absorbance changes of different characteristic wavelengths in standard polymer solutions.

[0042] In obtaining the relationship between absorbance and polymer concentration at each characteristic wavelength, statistical analysis was performed on the data sets of all standard polymer solutions. For the linear correlation between absorbance and polymer concentration data in the data set, the stronger the linear correlation between the two, the lower the sensitivity of the characteristic wavelength to additional components.

[0043] Based on the above analysis, the linear correlation degree of each characteristic wavelength is calculated, which represents the degree to which the fitted absorbance and polymer concentration at each characteristic wavelength conform to a linear change. The specific expression is as follows: ,in, denoted by , r represents the linear correlation degree at the i-th characteristic wavelength, and r represents the linear correlation coefficient after fitting the relationship at the i-th characteristic wavelength. This represents the sum of squares of all fitting residuals for the fitted relation at the i-th characteristic wavelength. The calculation of the linear correlation coefficient is a well-known technique, and the specific process will not be elaborated here. It should be noted that, to avoid the denominator becoming meaningless when the sum of squares of the fitting residuals is 0, when the sum of squares of all fitting residuals S = 0, let... .

[0044] The calculation of linear correlation is mainly based on the statistical analysis of the data set of standard polymer solutions at the characteristic wavelength and the fitting deviation after linear fitting. This allows for the analysis of the interference of other components in the turbid liquid on the determination of polymer absorbance from two perspectives. If the interference at the characteristic wavelength is small, the linear correlation coefficient for the data set of standard polymer solutions will be larger. Simultaneously, the overall fitting error during the data set fitting process will be smaller. Therefore, a larger linear correlation coefficient at the characteristic wavelength indicates a more significant degree of linearity in the fitted relationship at the characteristic wavelength.

[0045] S3. The absorbance of each turbid liquid in the ternary composite flooding sample solution after turbidity treatment is measured by turbidity method at each characteristic wavelength; the distribution deviation value of the absorbance of all turbid liquids at each characteristic wavelength is determined to evaluate the sensitivity of the turbid liquid distribution difference at each characteristic wavelength; and the polymer concentration detection weight of each characteristic wavelength is obtained by combining the degree of linear change of the relationship.

[0046] In ternary composite flooding, based on the design scheme of the corresponding reservoir, it is necessary to detect the polymer concentration in the configured ternary composite flooding system. Therefore, in this embodiment, a ternary composite flooding sample solution is collected, and the absorbance is measured using the turbidimetric method, as follows: Extraction: Add 100 ml of ternary composite flooding sample solution to a 500 ml sorting funnel, add 5 g NaCl and 50 ml petroleum ether, shake, and let stand for 15-20 min. This extracts the surfactant from the ternary composite flooding sample solution into the petroleum ether, thereby reducing the influence of the surfactant.

[0047] Turbidity treatment: Transfer the ternary composite flooding sample solution with surfactant removed to a beaker. Use a pipette to add 5 ml of the ternary composite flooding sample solution with surfactant removed to a 150 ml Erlenmeyer flask. Then use a pipette to add 20 ml of acetic acid solution to the Erlenmeyer flask, shake, and let stand for 2-5 min. Next, use a pipette to add 10 ml of sodium hypochlorite solution to the Erlenmeyer flask, shake, and let stand for 15-25 min.

[0048] Spectrophotometer data collection: After turbidity treatment, a turbid solution of the ternary composite flooding sample solution was obtained. This turbid solution was evenly distributed into N cuvettes of the spectrophotometer, and the N cuvettes were labeled 1 to N. Further, the selected cuvettes were used... , , The absorbance of each cuvette at each characteristic wavelength was measured using three characteristic wavelengths. Indicates at the characteristic wavelength The absorbance value was measured for the turbid sample in cuvette No. 1. In this embodiment, N=10, but the implementer can set it according to the actual situation; this embodiment does not impose any restrictions on it.

[0049] When determining the polymer concentration in a ternary composite flooding mixture using the turbidimetric method, the primary basis is the formation of insoluble substances by the polymer with sodium hypochlorite under acidic conditions, resulting in a turbid solution. This allows for quantitative analysis of the polymer concentration using a spectrophotometer based on the absorbance reading. However, the insoluble substances are mainly chloramine precipitates, typically distributed in the solution as colloidal particles. Therefore, measuring absorbance requires strict control of experimental conditions; otherwise, over-chlorination, precipitation dissolution, or uneven colloidal aggregation may occur. Consequently, differences in the distribution of insoluble substances during absorbance testing will introduce additional measurement bias.

[0050] Therefore, this embodiment prepares N labeled cuvettes simultaneously to ensure the repeatability of measurement results and to evaluate the distribution of insoluble matter and its sensitivity at different characteristic wavelengths. By analyzing the absorbance distribution of a single characteristic wavelength across N labeled cuvettes, the distribution of insoluble matter can be assessed.

[0051] Ideally, the distribution of insoluble matter in the turbid liquids of N labeled cuvettes is uniform, resulting in consistent absorbance measurements. However, due to differences in the distribution of insoluble matter, there may be some deviation in absorbance. The greater the deviation in absorbance distribution at a single characteristic wavelength, the greater the difference in component distribution in the turbid liquid.

[0052] Based on the above analysis, this embodiment calculates the distribution deviation of absorbance of all turbid liquids at each characteristic wavelength, and the specific expression is as follows: In the formula, This represents the distribution deviation of absorbance of all turbid liquids at the i-th characteristic wavelength, where N represents the number of cuvettes; in this embodiment, N=10. This represents the absorbance measured at the i-th wavelength in the k-th labeled cuvette. This represents the average absorbance measured by all cuvettes at the i-th wavelength.

[0053] It should be noted that, This indicates the degree of deviation between the absorbance measured at the i-th wavelength in the k-th cuvette and the average absorbance measured in all cuvettes. In another embodiment, the degree of deviation can be measured by calculating the square of the difference between the absorbance measured at the i-th wavelength in the k-th cuvette and the average absorbance measured in all cuvettes.

[0054] In the calculation of distribution deviation, it is expressed by the average absolute deviation of absorbance. If the distribution difference of insoluble matter in each cuvette is greater, the absorbance fluctuation at a single characteristic wavelength will be greater, thus resulting in a larger distribution deviation.

[0055] Because multiple characteristic wavelengths are measured simultaneously on N cuvettes of different labels, in practice, different wavelengths have varying sensitivities to differences in the distribution of turbidity. If a single characteristic wavelength is more sensitive to the distribution differences of insoluble matter in the turbidity, the corresponding distribution deviation will be larger. Conversely, if a single characteristic wavelength is less sensitive to the distribution differences of insoluble matter in the turbidity, the overall fluctuation of the absorbance of the turbidity will be smaller across all labels, indicating a more accurate measured absorbance and a smaller corresponding distribution deviation.

[0056] Based on the above analysis, this embodiment calculates the sensitivity of turbidity distribution differences at each characteristic wavelength. The specific calculation method is as follows: In the formula, This represents the sensitivity to the difference in turbidity distribution at the i-th characteristic wavelength. This represents the distribution deviation of absorbance of all turbid liquids at the i-th characteristic wavelength. This represents the distribution deviation of absorbance of all turbid liquids at the j-th characteristic wavelength. Let M represent the j-th characteristic wavelength, and M represent the number of characteristic wavelengths. In this embodiment, M=3. This represents the average value of the absorbance distribution deviation for all turbid liquids at all characteristic wavelengths. It should be noted that when the absorbance distribution deviation for all turbid liquids at all characteristic wavelengths is 0, the sensitivity of the turbid liquid distribution difference at each characteristic wavelength is set to 0.

[0057] In calculating the sensitivity to turbidity distribution differences, the distribution deviation value measures the overall distribution difference of insoluble matter in the turbidity when measuring the ternary composite flooding sample solution. If the overall distribution is relatively uniform, the obtained distribution deviation value is smaller than the mean; if the distribution difference is large, the obtained distribution deviation value is larger than the mean. The ratio of the distribution deviation value to the mean of the distribution deviation values ​​is used to assess the sensitivity of the characteristic wavelength to the current insoluble matter distribution differences. The more sensitive the characteristic wavelength is to the insoluble matter distribution, the greater the sensitivity to turbidity distribution differences.

[0058] Finally, this embodiment combines the linear correlation of each characteristic wavelength with the sensitivity to turbidity distribution differences to obtain the polymer concentration detection weight for each characteristic wavelength. The linear correlation can assess the correlation between polymer concentration and absorbance of the characteristic wavelength. The larger the linear correlation, the higher the accuracy of the characteristic wavelength's absorbance in characterizing changes in polymer concentration. In addition, the sensitivity to turbidity distribution differences assesses the sensitivity of a single characteristic wavelength to the distribution differences of insoluble matter in the turbidity. The more sensitive the current characteristic wavelength is, the greater the influence of the distribution differences of insoluble matter on that characteristic wavelength, and the lower the authenticity of the polymer concentration characterization.

[0059] Therefore, in this embodiment, the normalized result of the ratio of the linear correlation degree of each characteristic wavelength to the sensitivity of turbidity distribution difference is used as the polymer concentration detection weight for each characteristic wavelength. The normalization method in this embodiment is as follows: the ratio of the linear correlation degree of each characteristic wavelength to the sensitivity of turbidity distribution difference is calculated and denoted as the first ratio. The ratio of the first ratio of each characteristic wavelength to the sum of the first ratios of all characteristic wavelengths is used as the normalized result of the first ratio of each characteristic wavelength, i.e., the polymer concentration detection weight for each characteristic wavelength. Implementers can choose other existing feasible normalization methods; this embodiment does not impose any restrictions on this. It should be noted that, to avoid the denominator being meaningless when the sensitivity of turbidity distribution difference for a characteristic wavelength is 0, when the sensitivity of turbidity distribution difference for a characteristic wavelength is 0, the normalized result of the linear correlation degree of that characteristic wavelength is used as the polymer concentration detection weight for that characteristic wavelength.

[0060] S4. Using the relationship between the absorbance of the polymer solution at each characteristic wavelength and its polymer concentration, the polymer concentration of the ternary composite flooding sample solution at each characteristic wavelength is determined. After weighted summation, the polymer concentration measurement value is obtained. The deviation from the ideal polymer concentration is compared to adjust the polymer concentration.

[0061] For the absorbance of each characteristic wavelength in N cuvettes, the absorbance between the first quartile and the third quartile is selected. The mean of all absorbances in this interval is substituted into the relationship between absorbance and polymer concentration at each characteristic wavelength in step S2. The polymer concentration corresponding to each characteristic wavelength at the mean absorbance is obtained as the polymer concentration of the ternary composite flooding sample solution at each characteristic wavelength. The polymer concentration of the ternary composite flooding sample solution at each characteristic wavelength is weighted using the polymer concentration detection weight of each characteristic wavelength. The weighted sum of the polymer concentrations of the ternary composite flooding sample solution at all characteristic wavelengths is taken as the final measured polymer concentration of the ternary composite flooding sample solution.

[0062] The final polymer concentration measured in the ternary composite flooding sample solution is the polymer concentration before ternary composite flooding injection. This is achieved by comparing the polymer concentration before ternary composite flooding injection with the ideal polymer concentration in step S1. To determine whether the polymer concentration of the injected ternary composite flooding needs adjustment, the following steps are taken: calculate the polymer concentration before injection and the ideal polymer concentration in step S1. The absolute value of the difference is taken. If the absolute value of the difference is within the allowable error range, the polymer concentration of the ternary composite flooding is not adjusted; otherwise, the polymer concentration of the ternary composite flooding is adjusted until it is less than the allowable error, thereby improving the wavelength efficiency and sweep area of ​​the mixture in the ternary composite flooding. In this embodiment, the allowable error is set to 2%. Implementers can set it according to actual conditions, and this embodiment does not impose any restrictions on it.

[0063] Furthermore, in oilfield development, addressing the challenges of surface development, numerous layers, poor connectivity, and difficulty in mobilizing three types of oil reservoirs, this application ensures balanced and efficient reservoir utilization through precise implementation of fracturing-layer synergistic control. Specifically: To improve the utilization rate of thin and poor oil layers and the injection and production capacity of single wells, 100% injection wells and 50% production wells were fracturing and put into production.

[0064] During the injection process, the principles and methods for selecting injection well fracturing zones are formulated, specifically as follows: The principle for selecting fracture layers in injection wells is to primarily fracture surface reservoirs, small layers with an effective thickness of less than 0.5m and a permeability of less than 0.08. Small layers are selected, and reservoir wells that meet the conditions are fracturing.

[0065] Injection well fracturing method: mainly multi-fracture fracturing, fracturing 3 to 5 layers in a single well, and implementing short and wide fracture fracturing.

[0066] Secondly, it is necessary to achieve stratified control of injection wells to alleviate inter-layer conflicts; establish stratified control technology boundaries, and combine stratified injection, alternating injection of layers with polymer concentration adjustment to improve the utilization rate of small layers.

[0067] After the test area enters the period of gradual effectiveness, in the early stage of chemical flooding, wells with developed channel sand and dominant water-absorbing sections are injected in layers; in the middle stage of chemical flooding, the injection wells are layered in a timely manner according to the water absorption status of each sub-layer of the injection wells in the test area and the effectiveness of the oil wells.

[0068] The stratification technique is defined as follows: 4 to 8 units with similar developmental characteristics form a stratum; the effective thickness of the stratum is greater than 1 meter, and the injection volume is greater than 10. The thickness of the interlayer spacing in the composite layer is greater than 1m; the relative water absorption difference between the layers is greater than 30%. To address the uneven water absorption between the sublayers within the layer, a polymer concentration adjustment measure is adopted. When the injection pressure space is above 1.5MPa, the polymer concentration is increased by 150mg / L~250mg / L.

[0069] In summary, to improve the actual recovery rate of low-permeability reservoirs in the test area, this application firstly designs a ternary composite flooding scheme based on reservoir characteristic analysis, achieving dynamic compensation for polymer concentration and surfactant in traditional ternary composite flooding; secondly, before actual ternary composite flooding injection, to guide production and conduct dynamic analysis, it is necessary to detect the polymer concentration in the ternary composite flooding to verify whether the polymer concentration of the actual injected mixture meets the design concentration; finally, during the injection process, mainly to address the problems of reservoir characteristics such as well-developed oil layers, numerous layers, and poor connectivity, pressure-stratification system regulation is implemented to ensure that the oil layers are polymerized and efficiently utilized.

[0070] Based on the same inventive concept as the above method, this application embodiment also provides a polymer concentration detection system for a ternary composite system, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described methods for detecting polymer concentration in a ternary composite system.

[0071] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0072] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0073] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for detecting polymer concentration in a ternary composite system, characterized in that, The method includes the following steps: By collecting reservoir core samples, the linear relationship between polymer concentration and water saturation of the oil layer was determined based on experimental measurement methods, and the ideal polymer concentration was obtained. The relationship between the absorbance of polymer solutions and their polymer concentration at each selected characteristic wavelength was fitted experimentally, and the degree to which the fitted relationship at each characteristic wavelength conformed to the linear change was determined. The absorbance of each turbid liquid in the ternary composite flooding sample solution after turbidity treatment was measured by turbidity method at each characteristic wavelength; the distribution deviation of absorbance of all turbid liquids at each characteristic wavelength was determined to evaluate the sensitivity of turbid liquid distribution difference at each characteristic wavelength; and the polymer concentration detection weight at each characteristic wavelength was obtained by combining the degree of linear change of the relationship. Using the aforementioned relationship, the polymer concentration of the ternary composite flooding sample solution at each characteristic wavelength is determined. After weighted summation, the measured polymer concentration value is obtained. The deviation from the ideal polymer concentration is compared to adjust the polymer concentration accordingly. The determination of the degree to which the fitted relationship at each characteristic wavelength conforms to a linear change includes: Determine the linear correlation coefficient after fitting the relationship at each characteristic wavelength, and the sum of squares of all fitting residuals. The degree to which the fitted relationship at each characteristic wavelength conforms to linear change is the ratio of the linear correlation coefficient to the sum of squares. The determination of the distribution deviation value of absorbance of all turbid liquids at each characteristic wavelength includes: Calculate the mean absorbance of all turbid liquids at each characteristic wavelength, determine the degree of deviation of the absorbance of each turbid liquid at each characteristic wavelength from the mean, and the distribution deviation value of the absorbance of all turbid liquids at each characteristic wavelength is the mean of the degree of deviation of all turbid liquids at each characteristic wavelength. The sensitivity of assessing the differences in turbidity distribution at each characteristic wavelength includes: Calculate the average value of the distribution deviation values ​​at all characteristic wavelengths. The sensitivity of the turbidity distribution difference at each characteristic wavelength is the ratio of the distribution deviation value at each characteristic wavelength to the average value.

2. The method for detecting polymer concentration in a ternary composite system as described in claim 1, characterized in that, Determining the linear relationship between polymer concentration and water saturation of the oil layer includes: By measuring the relative permeability of the water phase and the relative permeability of the oil phase in the core sample, the water-oil mobility ratio is calculated to determine the correlation between water saturation and the water-oil mobility ratio. By conducting mobility tests on core samples, the correlation between polymer concentration and drag coefficient was determined. Combined with the correlation between water saturation and water-oil mobility ratio, a linear relationship between polymer concentration and water saturation of the oil reservoir was derived under set critical conditions. The specific expression is as follows: ;in, For the ideal polymer concentration, This indicates the water saturation level of the oil layer.

3. The method for detecting polymer concentration in a ternary composite system as described in claim 1, characterized in that, The selection of the characteristic wavelengths includes: The absorbance of a polymer solution with a known polymer concentration at various wavelengths across the entire wavelength range is measured, and the characteristic wavelengths are obtained after principal component analysis.

4. The method for detecting polymer concentration in a ternary composite system as described in claim 1, characterized in that, The degree of deviation is the absolute value of the difference between the absorbance of each turbid liquid at each characteristic wavelength and the mean value.

5. The method for detecting polymer concentration in a ternary composite system as described in claim 1, characterized in that, The polymer concentration detection weight is the normalized result of the ratio of the degree of linear change of the fitted relationship at each characteristic wavelength to the sensitivity of the turbidity distribution difference.

6. The method for detecting polymer concentration in a ternary composite system as described in claim 1, characterized in that, The adjustment of polymer concentration includes: If the deviation between the measured polymer concentration and the ideal polymer concentration is within the allowable error range, the polymer concentration of the ternary composite flooding sample solution will not be adjusted; otherwise, the polymer concentration of the ternary composite flooding sample solution will be adjusted until it is less than the allowable error.

7. A polymer concentration detection system for a ternary composite system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-6.

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