A method for selecting the particle size of nanoparticles in a biological nanometer pressure-reducing and injection-increasing technology

Abstract

The application discloses a selection method of the particle size of nanoparticles in biological nanometer pressure reduction and injection technology, and relates to the technical field of offshore oil fields.The pore throat radius of a reservoir is determined through a pore throat radius formula based on production dynamic data of the reservoir; the pore throat radius distribution standard deviation is determined based on geological data, and the pore throat radius of the reservoir is determined through the pore throat radius formula based on the production dynamic data of the reservoir, so that the actual maximum radius of the nanoparticles is determined; and finally, the average nanoparticle size is selected based on the theoretical maximum radius of the nanoparticles.The scheme realizes the selection of the particle size of the nanoparticles in the biological nanometer pressure reduction and injection technology of offshore oil fields, matches the particle size of the nanoparticles with the pore throat diameter of the reservoir rock, and thus better pressure reduction and injection effect is achieved.

Description

Technical Field

[0001] This invention relates to the field of offshore oilfield technology, specifically to a method for selecting the particle size of nanoparticles in a bio-nano depressurization and injection enhancement technology. Background Technology

[0002] As offshore oilfields enter a high water-cut stage, the use of large pumps for water injection development leads to high injection pressures, enormous energy consumption, and difficulties in water injection, hindering further crude oil extraction. To address this, bio-nano-based depressurization and injection enhancement fluids have been developed. These fluids primarily consist of dispersants and nanoparticles. However, the nanoparticles only achieve their optimal depressurization and injection enhancement effect when their particle size matches the pore throat diameter of the reservoir rock. Therefore, selecting nanoparticle sizes suitable for the specific pore size of the reservoir based on the actual formation pore throat size is crucial for achieving better depressurization and injection enhancement. Currently, however, methods for selecting and matching nanoparticle sizes are still lacking and remain in the exploratory stage.

[0003] Therefore, how to select the particle size of nanoparticles in the bio-nano depressurization and injection enhancement technology for offshore oil fields is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a method for selecting the particle size of nanoparticles in a bio-nano depressurization and injection enhancement technology. The method selects a nanoparticle size suitable for the pore size of the reservoir based on the actual pore throat size of the formation, thereby enabling the nanoparticles to exert their optimal depressurization and injection enhancement effect.

[0005] This invention provides a method for selecting the particle size of nanoparticles in a bio-nano-based depressurization and infusion enhancement technology. The selection method includes the following steps:

[0006] Step S1: Determine the reservoir's pore throat radius using the one-dimensional linear flow reservoir average pore throat radius formula based on the reservoir's production dynamics data;

[0007] Step S2: Based on the standard deviation of the pore throat radius distribution obtained from geological data and the pore throat radius obtained in step S1, determine the actual maximum radius of the nanoparticles;

[0008] Step S3: Based on step S2, determine the selected average nanoparticle size based on the theoretical maximum radius of nanoparticles.

[0009] Furthermore, the throat radius is equivalent to n capillaries with the same radius.

[0010] Furthermore, the formula for the average pore throat radius of a one-dimensional linear flow reservoir in step S1 is as follows:

[0011]

[0012] In the formula: r t Δp is the reservoir pore throat radius, μm; Δp is the production pressure differential, MPa; μ o φ is the crude oil viscosity, mPa·s; L is the seepage distance, m; φ is the porosity, %; A is the cross-sectional area of ​​the oil layer, m². 2 Q o For total output, m 3 / d.

[0013] Furthermore, step S2 specifically includes the following sub-steps:

[0014] S21. Determine a throat percentage N, and then obtain the corresponding Z for N from the standard normal distribution table;

[0015] S22. Calculate the theoretical maximum radius of nanoparticles according to the formula for the theoretical maximum radius of nanoparticles.

[0016] Furthermore, the percentage of the pore throat, N, is greater than 90%.

[0017] Furthermore, the theoretical maximum radius formula for the nanoparticles in step S2 is as follows:

[0018] r = 0.292 × (Z·σ + r) t )

[0019] In the formula, r is the theoretical maximum radius of the nanoparticle, Z is the value corresponding to the probability N selected under the standard normal distribution, and r t Let σ be the pore throat radius of the reservoir, and σ be the standard deviation of the pore throat radius distribution.

[0020] Furthermore, the average nanoparticle size in step S3 is determined by the following formula:

[0021]

[0022] In the formula, The average nanoparticle size to be selected is r, where r is the theoretical maximum radius of the nanoparticle, and σ is the average nanoparticle size to be selected. nano It is the standard deviation of the nanoparticle size.

[0023] The beneficial effects of this invention are:

[0024] This invention solves the problem of nanoparticle size selection in offshore oilfield bio-nano-based depressurization and injection enhancement technology. First, based on reservoir production dynamics data, the pore throat radius of the reservoir is determined using a pore throat radius formula. Then, based on geological data, the standard deviation of the pore throat radius distribution is determined, and the reservoir's pore throat radius is further determined using the same formula based on reservoir production dynamics data, thus determining the actual maximum radius of the nanoparticles. Finally, based on the theoretical maximum radius of the nanoparticles, the average nanoparticle size is selected. By selecting a nanoparticle size suitable for the pore size of the reservoir according to the actual formation pore throat size, a better depressurization and injection enhancement effect can be achieved. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments will be briefly described below. Obviously, the drawings described below only relate to some embodiments of the present invention and are not intended to limit the present invention.

[0026] Figure 1 This is a flowchart illustrating a method for selecting the particle size of nanoparticles in a bio-nano depressurization and injection enhancement technology, as provided in an embodiment of the present invention.

[0027] Figure 2 This is a schematic diagram illustrating the first scenario of particle blockage and retention in the reservoir in an embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram illustrating the second scenario of particle blockage and retention in the reservoir in an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram illustrating the third scenario of particle blockage and retention in the reservoir in an embodiment of the present invention;

[0030] Figure 5 This is a schematic diagram illustrating the fourth scenario of particle blockage and retention in the reservoir in an embodiment of the present invention;

[0031] Figure 6 This is a schematic diagram illustrating the fifth scenario of particle blockage and retention in the reservoir in an embodiment of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] This application proposes a method for selecting the particle size of nanoparticles in a bio-nano-based depressurization and infusion enhancement technology, such as... Figure 1The diagram shown is a flowchart illustrating the selection of nanoparticle size for a bio-nano-based depressurization and infusion enhancement technology proposed in this application. The method includes the following steps:

[0034] Step S1: Determine the pore throat radius of the reservoir using the pore throat radius formula based on the reservoir's production dynamics data.

[0035] Specifically, regarding the formula for calculating the pore throat radius, due to the complexity of the pore structure and the tortuous nature of the actual seepage process, a capillary bundle seepage model is used to determine the pore throat radius for ease of analysis. The capillary bundle seepage model is a simplification of the actual reservoir structure, consisting of n capillaries of the same radius, whose radius is equivalent to the pore throat radius of the actual reservoir. The main assumptions are:

[0036] 1) The capillary bundle seepage model has the same external geometry as the actual reservoir;

[0037] 2) The capillary bundle seepage model has the same pore volume as the actual oil reservoir, that is, the same porosity;

[0038] 3) Following the principle of equivalent seepage resistance, under the same seepage conditions (production pressure difference, fluid viscosity, etc.), if the capillary bundle seepage model and the actual reservoir seepage resistance are equal, then the production will also be equal.

[0039] Suppose that crude oil flows linearly in a reservoir with a cross-sectional area of ​​A and a seepage distance of L, and the production pressure difference is Δp. Based on the assumptions of the capillary bundle seepage model, the flow process is equivalent to n parallel capillaries with a radius of r.

[0040] From Poiseuille's equation, the yield q0 in a single capillary tube can be obtained as:

[0041]

[0042] By definition of porosity:

[0043]

[0044] Therefore, the equivalent number of capillaries, n, is:

[0045]

[0046] Total output Q0 equals the number of capillaries multiplied by the output per capillary:

[0047]

[0048] By transforming formulas (1)-(4), we can obtain the formula for the average pore throat radius of a one-dimensional linear flow reservoir calculated based on dynamic data of production and production pressure differential:

[0049]

[0050] In formula (1)-(5): q o For the yield of a single capillary, m 3 / d;r t Δp is the reservoir pore throat radius, μm; Δp is the production pressure differential, mPa; μ o φ is the crude oil viscosity, mPa·s; L is the seepage distance, m; φ is the porosity, %; n is the number of capillaries, roots; A is the cross-sectional area of ​​the oil layer, m². 2 Q o For total output, m 3 / d.

[0051] Step S2: Based on the standard deviation of the pore throat radius distribution obtained from geological data and the pore throat radius determined by the pore throat radius formula based on reservoir production dynamics data, the actual maximum radius of the nanoparticles is determined.

[0052] Step S2 specifically includes the following sub-steps:

[0053] S21. Determine a pore throat percentage N, and then obtain the corresponding Z from the standard normal distribution table.

[0054] S22. Calculate the theoretical maximum radius of nanoparticles according to the formula for the theoretical maximum radius of nanoparticles.

[0055] Specifically, particle blockage and retention in reservoirs generally fall into five categories, such as... Figure 2 The image shows the first case, with the corresponding radius: r > r t ;like Figure 3 The image shows the second case, with a corresponding radius of 0.46r. t <r<r t ;like Figure 4 The image shows the third case, with a corresponding radius of r = 0.46r. t ;like Figure 5 The image shows the fourth case, with a corresponding radius of 0.292r. t <r<0.46r t ;like Figure 6 The image shows the fifth case, with a corresponding radius of r = 0.292r. t ;

[0056] Where, r t denoted as pore throat radius of the reservoir; r is the theoretical maximum radius of nanoparticles in the reservoir.

[0057] The bio-nanoparticles used must be free from blockage; therefore, the theoretical maximum radius of the nanoparticles in the reservoir is r = 0.292r. t .

[0058] However, it is clearly impractical and economically unrealistic to require all pores to be satisfied; and the reservoir pore throat radius follows a normal distribution to a certain extent. Its mathematical expectation, i.e., the pore throat radius r, is... t The standard deviation of the reservoir pore throat radius distribution is σ, where x equals any pore throat radius, which varies between different oilfields and can be derived from geological data; therefore, the probability density function is:

[0059]

[0060] In this patent, the probability of the size of the throat radius is also in the range x = r t The maximum value is reached at this point.

[0061] Therefore, from an economic perspective, the throat radius r corresponding to N can be determined based on the probability density function. ti This results in a number of orifice throat radii greater than r such that N (a percentage, which should be greater than 90%) are found. ti .

[0062] Therefore, the theoretical maximum radius formula for nanoparticles in reservoirs is:

[0063] r = 0.292r ti (7)

[0064] To easily find the throat radius r corresponding to N ti The value can be transformed into a standard normal distribution by introducing the following Z-transform formula:

[0065]

[0066] At this point, for each N, there is a corresponding Z such that it is greater than the corresponding probability. The Z corresponding to each probability can be found by looking up the standard normal distribution table.

[0067] After determining the required N, perform an inverse transformation on formula (8) to obtain x = Z·σ + r t At this time, x = r ti, Then, by combining equation (7), the corresponding theoretical maximum radius formula for nanoparticles can be obtained:

[0068] r = 0.292 × (Z·σ + r) t (9)

[0069] In the formula, r is the theoretical maximum radius of the nanoparticle, Z is the value corresponding to the probability N selected under the standard normal distribution, and r t Let σ be the pore throat radius of the reservoir, and σ be the standard deviation of the pore throat radius distribution.

[0070] Step S3: Based on steps S1 and S2, the average nanoparticle size is selected based on the theoretical maximum radius of nanoparticles.

[0071] In fact, during the fabrication of nanoparticles, it is difficult to guarantee that every particle size is exactly the same; the specifications usually provided are the average nanoparticle size. However, the average nanoparticle size and the maximum nanoparticle size generally also follow a normal distribution, with the following probability density:

[0072]

[0073] Its corresponding Z-transform is:

[0074]

[0075] Similarly, at this time for each N nano (Percentages should be greater than 90%) all have corresponding Z values. nano Z corresponding to each probability nano This can be found by consulting the standard normal distribution table.

[0076] In practical applications, N is generally... nano =99%, at this time the corresponding Z nano =2.33, x nano Substituting r into formula (11) and performing an inverse transformation, we can obtain the formula for the average nanoparticle size:

[0077]

[0078] In the formula, The average nanoparticle size to be selected is r, where r is the theoretical maximum radius of the nanoparticle, and σ is the average nanoparticle size to be selected. nano It is the standard deviation of the nanoparticle size.

[0079] Example

[0080] In specific application scenarios, the well group of the target block is set as A1, and the daily production Q is obtained from the production dynamic data. o Crude oil viscosity μ o The production pressure differential Δp is obtained from the well location distribution, the seepage distance L is obtained from the geological data, the oil layer cross-sectional area A is obtained from the geological data, and the standard deviation σ of porosity φ and formation pore throat radius is obtained from the experiment; the standard deviation σ of nanoparticle size distribution can be obtained from the experiment. nano Table 1 includes the parameter values ​​for specific application scenarios.

[0081] Table 1. Parameter values ​​for specific application scenarios.

[0082] value 200 500 1 6.28 15％ 5 6 97.72％ 2

[0083] Using formula (5), r can be calculated. t =12.95327616μm.

[0084] To make the pore throat radius greater than r in 97.72% of cases... ti According to the standard normal distribution probability table, the corresponding Z = -2.

[0085] Using formula (9), the maximum particle size of the nanoparticles is calculated to be 278 nm.

[0086] Finally, using formula (12), the appropriate nanoparticle size can be calculated as follows:

[0087] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for selecting the particle size of nanoparticles in a bio-nano-based depressurization and injection enhancement technology, characterized in that, The selection method includes the following steps: Step S1: Determine the reservoir's pore throat radius using the one-dimensional linear flow reservoir average pore throat radius formula based on the reservoir's production dynamics data; Step S2: Based on the standard deviation of the pore throat radius distribution obtained from geological data and the pore throat radius obtained in step S1, determine the theoretical maximum radius of the nanoparticles. This includes the following sub-steps: S21. Determine a throat percentage N, and then obtain the corresponding Z for N from the standard normal distribution table; S22. Calculate the theoretical maximum radius of the nanoparticles according to the formula for the theoretical maximum radius of nanoparticles. The formula for the theoretical maximum radius of nanoparticles is as follows: In the formula, r is the theoretical maximum radius of the nanoparticle, Z is the value corresponding to the probability N selected under the standard normal distribution, and r t Let σ be the pore throat radius of the reservoir, and σ be the standard deviation of the pore throat radius distribution of the reservoir. Step S3: Based on step S2, the selected average nanoparticle size is determined according to the theoretical maximum radius of nanoparticles. The average nanoparticle size is determined by the following formula: In the formula, The average nanoparticle size to be selected is r, where r is the theoretical maximum radius of the nanoparticle. It is the standard deviation of the nanoparticle size.

2. The method for selecting the particle size of nanoparticles in the bio-nano-hypertensive and infusion-enhancing technology according to claim 1, characterized in that, The throat radius is equivalent to n capillaries with the same radius.

3. The method for selecting the particle size of nanoparticles in the bio-nano-hypertensive and infusion-enhancing technology according to claim 1, characterized in that, The formula for the average pore throat radius of a one-dimensional linear flow reservoir in step S1 is as follows: In the formula: r t Δp is the reservoir pore throat radius, μm; Δp is the production pressure differential, MPa; μ o Where L is the viscosity of crude oil, mPa·s; and L is the seepage distance, m. φ is porosity, %; A is the cross-sectional area of ​​the oil layer, m. 2 Q o For total output, m 3 / d.

4. The method for selecting the particle size of nanoparticles in the bio-nano-hypertensive and infusion-enhancing technology according to claim 1, characterized in that, The percentage of the pore throat, N, is greater than 90%.

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