Simulated crude oil emulsion optimization preparation method based on response surface analysis and prediction

Abstract

The invention relates to the technical field of petrochemical engineering, in particular to a response surface analysis and prediction-based simulated crude oil emulsion optimization preparation method which comprises the following steps: preparing a crude oil emulsion by adopting a high-speed homogeneous emulsification method; and determining the target total oil outlet amount through the target model and the target emulsification parameters. According to the method, three factors, namely the emulsification temperature, the emulsification time and the stirring strength, of secondary emulsification are adjusted, the secondary emulsification process of the thick oil is optimized, and it is found through a laboratory secondary emulsification simulation field produced liquid test that under certain conditions, the state of the prepared crude oil emulsion is more stable, and the stability of the crude oil emulsion is improved. And a guarantee is provided for smooth proceeding of a subsequent demulsification test.

Description

Technical Field

[0001] The invention relates to the technical field of petrochemical engineering, in particular to an optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction. Background Art

[0002] Thermal recovery of crude oil is a method used in oil production, especially when facing high-temperature, high-pressure, and high-viscosity crude oil resources such as Xinjiang Karamay Oilfield. Due to the high density and viscosity of crude oil itself, as well as the colloid and asphaltene components contained in it, fluid components need to be injected during the production process to reduce the viscosity of crude oil and improve its fluidity. However, these injected fluid components, such as CO2, N2, water vapor, and chemical additives, are easily mixed with crude oil to form a complex emulsion system under high temperature and high pressure. The state of the emulsion will change after production, and the ground processing process is extremely difficult. The high-temperature and high-pressure produced fluid of Xinjiang Karamay Oilfield crude oil is a water-in-oil foamy emulsion, which is a viscous solid at room temperature and pressure. It is difficult to carry out emulsion property analysis and demulsification process research in the laboratory, and it is also easy to form a viscous solid during the transportation or storage of the emulsion. Therefore, secondary emulsification of Xinjiang Karamay Oilfield crude oil and studying the influence of secondary emulsification conditions on simulated emulsions are important links in the laboratory to carry out research related to crude oil demulsification.

[0003] There are many emulsification technologies, such as self-emulsification, gel emulsification, mechanical emulsification and other emulsification methods. However, these methods have certain limitations for the emulsification of viscous crude oil. The characteristics of crude oil emulsions show extremely high complexity and diversity, and their characteristics are closely related to key factors such as the characteristics of the water phase, the characteristics of the oil phase, and the oil-water volume ratio. The main external factors affecting the stability of crude oil emulsions are stirring speed, emulsification time and emulsification temperature. In the laboratory, crude oil demulsification research is carried out, and the crude oil samples used often form viscous solids during transportation or transfer. Its emulsification conditions and emulsion types are difficult to determine, which hinders the subsequent research work. Summary of the invention

[0004] In view of the above problems or problems existing in the prior art, the present invention is proposed.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction, which comprises preparing crude oil emulsion by high-speed homogenization emulsification method;

[0006] The target total oil yield is determined by the target model and target emulsification parameters.

[0007] As a preferred embodiment of the method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis prediction of the present invention, the crude oil emulsion is prepared by a high-speed homogenization emulsification method, comprising:

[0008] Take the target mass of crude oil and prepare it according to the target oil-water mass ratio to obtain a preliminary emulsion;

[0009] The preliminary emulsion is homogenized using a high-speed dispersing homogenizer to form a crude oil emulsion.

[0010] As a preferred solution of the optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction of the present invention, the target oil-water mass ratio is 1:19,

[0011] Take the target mass of crude oil and prepare the preliminary emulsion according to the target oil-water mass ratio, including:

[0012] The crude oil and water are placed in a water bath and heated for a preset time, and the heated crude oil and water are mixed in a mass ratio of 1:19 to form a target emulsion.

[0013] As a preferred solution of the optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction of the present invention, the preset time includes 30 minutes.

[0014] As a preferred embodiment of the method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis prediction of the present invention, the target emulsification parameters include:

[0015] Emulsification temperature, emulsification time and stirring intensity.

[0016] As a preferred embodiment of the method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis prediction of the present invention, before determining the target total oil yield by using the target model and the target emulsification parameters, the method includes:

[0017] Obtain historical emulsification parameters and historical total oil output corresponding to each historical emulsification parameter;

[0018] According to the historical emulsification parameters and the historical total oil yields corresponding to the historical emulsification parameters, a target model is established, and the target model is used to obtain the total oil yield according to the emulsification parameters.

[0019] As a preferred solution of the optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction of the present invention, the historical emulsification parameters include historical emulsification temperature, historical emulsification time and historical stirring intensity. According to the historical emulsification parameters and the historical total oil yield corresponding to each historical emulsification parameter, a target model is established, including:

[0020] Taking different historical emulsification temperatures, historical emulsification times and historical stirring intensities as experimental parameters, the first target software was used to conduct quadratic regression analysis and construct a multivariate quadratic equation regression model;

[0021] The multivariate quadratic regression model was determined as the target model.

[0022] As a preferred solution of the method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis prediction of the present invention, after constructing the multivariate quadratic regression model, the method includes:

[0023] According to the regression model, the response surface analysis diagram of the interaction among emulsification temperature, emulsification time and stirring intensity was drawn using the second objective software.

[0024] As a preferred solution of the method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis prediction of the present invention, wherein: the first target software includes Design-Expert;

[0025] The second target software includes Design-Expert 12.

[0026] As a preferred solution of the optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction of the present invention, wherein: the multivariate quadratic equation regression model includes total oil yield = 2704.81 + 383.89A + 82.28B + 357.91C + 27.98AB - 25.97AC - 91.71BC - 242.81A 2 -103.08B 2 -67.73C 2

[0027] Among them, A is the emulsification temperature, B is the emulsification time and C is the stirring intensity.

[0028] Beneficial effects of the present invention: The present invention optimizes the secondary emulsification process of heavy oil by adjusting three factors of secondary emulsification: emulsification temperature, emulsification time and stirring intensity, and through laboratory secondary emulsification simulation field produced fluid test, it is found that under the conditions of secondary emulsification temperature of 78.8°C, time of 19.5min and stirring intensity of 9596r / min, the prepared crude oil emulsion is in a more stable state, which provides a guarantee for the smooth progress of subsequent demulsification test. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0030] Figure 1 Schematic diagram of the effect of emulsification temperature on emulsification effect.

[0031] Figure 2 Schematic diagram of the effect of emulsification time on emulsification effect.

[0032] Figure 3 Schematic diagram of the effect of stirring intensity on emulsification effect.

[0033] Figure 4 Schematic diagram of the effect of emulsification temperature and emulsification time on the oil content of simulated heavy oil produced fluid.

[0034] Figure 5 Schematic diagram of the effect of emulsification temperature and stirring intensity on the oil content of simulated heavy oil produced fluid.

[0035] Figure 6 Schematic diagram of the effect of emulsification time and stirring intensity on the oil content of simulated heavy oil produced fluid. DETAILED DESCRIPTION

[0036] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0037] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0038] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0039] Example

[0040] Reference Figure 1 to Figure 6 , is an embodiment of the present invention, which provides an optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction, comprising:

[0041] S1. The crude oil emulsion is prepared by high-speed homogenization and emulsification method.

[0042] Furthermore, the crude oil emulsion is prepared by a high-speed homogenization emulsification method, comprising:

[0043] Take the target mass of crude oil and prepare it according to the target oil-water mass ratio to obtain a preliminary emulsion;

[0044] The preliminary emulsion is homogenized using a high-speed dispersing homogenizer to form a crude oil emulsion.

[0045] Furthermore, the target oil-water mass ratio is 1:19.

[0046] Take the target mass of crude oil and prepare the preliminary emulsion according to the target oil-water mass ratio, including:

[0047] The crude oil and water are placed in a water bath and heated for a preset time, and the heated crude oil and water are mixed in a mass ratio of 1:19 to form a target emulsion.

[0048] Furthermore, the preset time includes 30 minutes.

[0049] In this disclosure, 15g crude oil and 285g oilfield water were weighed, placed in a 500mL beaker, and moved to a constant temperature water bath for preheating for 30 minutes. The preheating temperature was consistent with the secondary emulsification setting temperature. A high-speed dispersing homogenizer was used to prepare the crude oil emulsion, and the data on the crude oil emulsion being able to maintain for 3 days were recorded.

[0050] S2. Determine the target total oil output through the target model and target emulsification parameters.

[0051] Further, the target emulsification parameters include,

[0052] Emulsification temperature, emulsification time and stirring intensity.

[0053] In this disclosure, specific variables are controlled as follows:

[0054] Emulsification temperature: 75℃, 80℃, 85℃;

[0055] Emulsification time: 15min, 20min, 25min;

[0056] Stirring intensity: 9000r / min, 10000r / min, 11000r / min.

[0057] Further, before determining the target total oil yield through the target model and the target emulsification parameters, including:

[0058] Obtain historical emulsification parameters and historical total oil output corresponding to each historical emulsification parameter;

[0059] According to the historical emulsification parameters and the historical total oil yields corresponding to the historical emulsification parameters, a target model is established, and the target model is used to obtain the total oil yield according to the emulsification parameters.

[0060] It should be noted that the oil content of crude oil after secondary emulsification was used as the response value for response surface optimization, with emulsification temperature (°C) recorded as factor A, emulsification time (min) recorded as factor B, and stirring intensity (r / min) recorded as factor C. The specific experimental factors and levels are as follows:

[0061]

[0062] The experimental results are as follows:

[0063]

[0064]

[0065] Specifically, when the emulsification time is 20 minutes, the stirring intensity is 10000r / min, the preheating temperature is consistent with the secondary emulsification setting temperature, and a high-speed dispersing homogenizer is used to prepare the crude oil emulsion. Figure 1 It can be seen that as the temperature increases, the emulsification effect becomes better, but if the temperature is too high, it may cause droplets to aggregate.

[0066] It reduces the emulsification effect and has a counter-effect on the emulsification state. When the emulsification temperature is 70℃, the oil content of the emulsion after the secondary emulsification is relatively low, indicating that the emulsification degree is low at this temperature. When the emulsification temperature is between 75℃ and 90℃, the oil content of the emulsion after the secondary emulsification is relatively close, especially at 80℃ and 85℃. Although the temperature is increased, the oil content does not increase much. Considering the energy consumption and economic factors, 80℃ is selected as the optimal emulsification temperature;

[0067] The emulsification temperature is 80℃, the stirring intensity is 10000r / min, the preheating temperature is consistent with the secondary emulsification setting temperature, and a high-speed disperser homogenizer is used to prepare the crude oil emulsion. Figure 2 It can be seen that the oil content after the secondary emulsification increases with the increase of emulsification time. The longer the emulsification time, the more the homogenizer can make the oil and water fully contact and mix evenly, so that the oil content increases. Increasing the emulsification time can obtain a more stable emulsion. When the emulsification time is 10 minutes, the oil content after the secondary emulsification is relatively low, which also verifies the problem that the emulsification time is not enough and the emulsion is unstable, resulting in low oil content. When the emulsification time reaches 20 minutes, the oil content begins to stabilize. As the time increases, the oil content does not increase significantly. Therefore, 20 minutes is selected as the optimal emulsification time;

[0068] The emulsification temperature is 80℃, the emulsification time is 20min, the preheating temperature is consistent with the secondary emulsification setting temperature, and a high-speed disperser homogenizer is used to prepare the crude oil emulsion. Figure 3 As shown. When preparing emulsions through homogenization technology, the greater the stirring intensity, the easier it is to physically break the oil-water interface, so that the oil and water mix to form a uniform emulsion. As can be seen from the figure, the stronger the stirring intensity, the higher the oil content of the emulsion after secondary emulsification. When the stirring intensity reaches 10000r / min, the oil content begins to stabilize. Considering energy consumption and economic factors, the higher the stirring intensity, the higher the energy consumption, so 10000r / min is selected as the optimal stirring intensity.

[0069] Furthermore, the historical emulsification parameters include historical emulsification temperature, historical emulsification time and historical stirring intensity. According to the historical emulsification parameters and the historical total oil output corresponding to each historical emulsification parameter, a target model is established, including:

[0070] Taking different historical emulsification temperatures, historical emulsification times and historical stirring intensities as experimental parameters, the first target software was used to conduct quadratic regression analysis and construct a multivariate quadratic equation regression model;

[0071] The multivariate quadratic regression model was determined as the target model.

[0072] Further, the first target software includes Design-Expert;

[0073] The second target software includes Design-Expert 12.

[0074] Furthermore, the multivariate quadratic regression model includes total oil output = 2704.81 + 383.89A + 82.28B + 357.91C + 27.98AB - 25.97AC - 91.71BC - 242.81A 2 -103.08B 2 -67.73C 2

[0075] Among them, A is the emulsification temperature, B is the emulsification time and C is the stirring intensity.

[0076] The fitting results of the secondary emulsification data model for crude oil from Xinjiang Karamay Oilfield are shown in the following table:

[0077]

[0078]

[0079] From the data in the table, it can be seen that the F value of the model is 32.33, F is much greater than P, and P < 0.0001, indicating that the model is extremely significant and has a good fit. The P of the lack of fit term of this model is 0.0683, indicating that the model has a high degree of fit with the experiment, there is no lack of fit phenomenon, and the fitting equation is close to the actual data. The fitting coefficient R2 = 0.9732 > 0.95. It shows that 97.32% of the changes in oil content obtained from the experiment can be explained by the model simulated by the above formula. Therefore, combined with the above, it can also be determined that the response surface model can effectively predict the changes in oil content in the field of secondary emulsification research. From the significance test of the regression equation, it can be seen that the first-order terms A and C of the model are extremely significant, and the B term is slightly less significant; the second-order term A2 is extremely significant, and B2 and C2 are relatively insignificant; the interaction terms BC, AB and AC are not significant, and the BC term is slightly significant compared with other interaction terms.

[0080] It can be seen from the table that the F value of emulsification temperature (A) is 128.49, the F value of emulsification time (B) is 5.90, and the F value of stirring intensity (C) is 111.68, so F(B)<F(C)<F(A), so the influence of the three factors of emulsification temperature, emulsification time, and stirring intensity on the laboratory secondary emulsification simulated crude oil produced liquid from large to small is emulsification temperature, stirring intensity, and emulsification time. That is, compared with time, the influence of emulsification temperature and stirring intensity on the secondary emulsification effect is more significant. In summary, through response surface analysis, under laboratory conditions, for the treatment of secondary emulsification simulated crude oil produced liquid, the influence of the three factors of emulsification temperature, emulsification time, and stirring intensity shows an obvious hierarchical relationship, that is, the influence of emulsification time is the smallest, followed by stirring intensity, and the influence of emulsification temperature is the most significant. This conclusion provides a reference for optimizing the emulsification treatment process of crude oil produced liquid. By rationally regulating these key factors, the effect of laboratory secondary emulsification simulated crude oil produced liquid can be more effectively improved.

[0081] Furthermore, after constructing the multivariate quadratic regression model, including,

[0082] According to the regression model, the response surface analysis diagram of the interaction among emulsification temperature, emulsification time and stirring intensity was drawn using the second objective software.

[0083] It should be noted that the response surface analysis results are as follows Figures 4 to 6 As shown, Figure 4 It shows that within the tested range, the effect of emulsification temperature on secondary emulsification is more significant than that of time, which corresponds to the above-mentioned Xinjiang Karamay Oilfield crude oil secondary emulsification data model fitting results F(A)>F(B). Among them, the emulsification temperature is close to 81℃, the emulsification time is between 20-21min, and the response value tends to the maximum.

[0084] from Figure 5 It can be seen that when the emulsification temperature is close to 81°C and the stirring intensity is close to 10250r / min, the response value tends to the maximum. In general, it cannot be fully determined through the response surface image whether the temperature or the stirring intensity has a stronger influence on the secondary emulsification effect. In the fitting result table of the secondary emulsification data model of crude oil in Karamay Oilfield, Xinjiang, although F(A) is greater than F(C), the difference between the two is small, which is also consistent with the response surface results.

[0085] Depend on Figure 6 It is found that in this range, the influence of stirring intensity on secondary emulsification is more significant, which corresponds to F(B)<F(C) in the fitting result table of the secondary emulsification data model of crude oil in Xinjiang Karamay Oilfield. Among them, when the emulsification time is between 19-20min and the stirring intensity is close to 10000r / min, the response surface tends to the maximum value.

[0086] Comparing the three pictures, Figure 6 The surface of is the smallest, so the interaction between stirring intensity and emulsification time is weak. Figure 5 The surface curvature is the largest, and the interaction between the surface emulsification temperature and the stirring intensity is the strongest. According to the theory that the curvature of the response surface diagram is closely related to the strength of the interaction between each factor, the greater the curvature, the stronger the interaction, that is, compared with time, the influence of emulsification temperature and stirring intensity on the secondary emulsification effect is more significant.

[0087] That is, according to the size of the significant influencing factors, in order to improve the effect of laboratory secondary emulsification simulated crude oil production fluid, a certain emulsification temperature can be determined first, and the stirring intensity and emulsification time can be changed, so as to obtain the best method for preparing laboratory secondary emulsified crude oil simulated crude oil production fluid.

[0088] The composition characteristics of the crude oil emulsion disclosed in the present invention are measured in the laboratory, and the saturated fraction accounts for 39.07%, the aromatic fraction accounts for 25.72%, the colloid accounts for 26.61%, and the asphaltene accounts for 5.62%, which is consistent with the characteristics of Xinjiang Karamay heavy oil.

[0089]

[0090]

[0091] In summary, the beneficial effect of the optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction of the present invention is that the secondary emulsification process of heavy oil is optimized by adjusting the three factors of secondary emulsification: emulsification temperature, emulsification time and stirring intensity, and through laboratory secondary emulsification simulation field produced fluid test, it is found that under the conditions of secondary emulsification temperature of 78.8°C, time of 19.5min and stirring intensity of 9596r / min, the prepared crude oil emulsion is more stable, which provides a guarantee for the smooth progress of subsequent demulsification test.

[0092] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for optimizing the preparation of a simulated crude oil emulsion based on response surface analysis prediction, characterized in that: include, The crude oil emulsion is prepared by high-speed homogenization and emulsification method; The target total oil yield is determined by the target model and target emulsification parameters.

2. The method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis and prediction according to claim 1, characterized in that: The high-speed homogenization emulsification method is used to prepare the crude oil emulsion, comprising: Take the target mass of crude oil and prepare it according to the target oil-water mass ratio to obtain a preliminary emulsion; The preliminary emulsion is homogenized using a high-speed dispersing homogenizer to form the crude oil emulsion.

3. The optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction according to claim 2, characterized in that: The target oil-water mass ratio is 1:19, The method of taking a target mass of crude oil and preparing a preliminary emulsion according to a target oil-water mass ratio comprises: The crude oil and water are placed in a water bath and heated for a preset time, and the heated crude oil and water are mixed in a mass ratio of 1:19 to form the target emulsion.

4. The optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction according to claim 3, characterized in that: The preset time includes 30 minutes.

5. The optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction according to claim 3 or 4, characterized in that: The target emulsification parameters, include, Emulsification temperature, emulsification time and stirring intensity.

6. The optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction according to claim 5, characterized in that: Before determining the target total oil yield through the target model and target emulsification parameters, including, Obtaining historical emulsification parameters and historical total oil output corresponding to each of the historical emulsification parameters; The target model is established according to the historical emulsification parameters and the historical total oil yields corresponding to the historical emulsification parameters. The target model is used to obtain the total oil yield according to the emulsification parameters.

7. The method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis and prediction according to claim 6, characterized in that: The historical emulsification parameters include historical emulsification temperature, historical emulsification time and historical stirring intensity. The target model is established based on the historical emulsification parameters and the historical total oil output corresponding to each of the historical emulsification parameters, including: Using different historical emulsification temperatures, historical emulsification times, and historical stirring intensities as experimental parameters, a quadratic regression analysis was performed using the first target software to construct a multivariate quadratic equation regression model; The multivariate quadratic regression model is determined as the target model.

8. The method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis and prediction according to claim 7, characterized in that: After constructing the multivariate quadratic regression model, including: According to the regression model, a response surface analysis diagram of the interaction among emulsification temperature, emulsification time and stirring intensity was drawn using the second target software.

9. The method for optimizing the preparation of simulated crude oil emulsion based on response surface analysis and prediction according to claim 8, characterized in that: The first target software includes Design-Expert; The second target software includes Design-Expert 12.

10. The optimized preparation method of simulated crude oil emulsion based on response surface analysis prediction according to any one of claims 7 to 9, characterized in that: The multivariate quadratic regression model includes Total oil output = 2704.81 + 383.89A + 82.28B + 357.91C + 27.98AB - 25.97AC - 91.71BC - 242.81A 2 -103.08B 2 -67.73C 2 Among them, A is the emulsification temperature, B is the emulsification time and C is the stirring intensity.

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