Method for judging main control factors of water drive efficiency of low-permeability reservoir based on relative permeability

Abstract

The invention relates to the technical field of oil exploitation, in particular to a method for judging a main control factor of water drive efficiency of a low-permeability reservoir based on relative permeability, which comprises the following steps: determining a target reservoir condition, carrying out an unsteady-state method relative permeability experiment, testing a starting pressure gradient and fitting a formula, and determining the main control factor by adopting grey correlation analysis. Through systematic experimental design and data analysis, the influence degree of each factor on the oil displacement efficiency is quantified, and the movable fluid saturation, irreducible water saturation and starting pressure gradient are determined as main influence factors. According to the method, the main control factors of low-permeability reservoir water drive development can be quickly and accurately identified.

Description

Technical Field

[0001] This invention relates to the field of petroleum extraction technology, and in particular to a method for determining the main controlling factors of water drive efficiency in low-permeability reservoirs based on relative permeability. Background Technology

[0002] Low-permeability reservoirs typically have characteristics such as low porosity, low permeability, low abundance, and strong heterogeneity, and their development process faces many challenges. In particular, during waterflooding development, the recovery rate is often less than 25%. Therefore, accurately identifying the main controlling factors affecting development efficiency is the key to optimizing well pattern design, water injection strategy, and improving recovery rate.

[0003] Existing technologies fail to fully consider the impact of reservoir energy on the development process when analyzing the main controlling factors of waterflood efficiency in low-permeability reservoirs, resulting in inaccurate analysis results. At the same time, existing analytical methods often exhibit diverse solutions, requiring additional information to determine the final solution. They cannot effectively extract hidden reservoir characteristics or refine the main controlling factors of various reservoirs, thus failing to provide clear guidance for the refined development of low-permeability reservoirs. Summary of the Invention

[0004] The purpose of this invention is to provide a method for determining the main controlling factors of waterflooding efficiency in low-permeability reservoirs based on relative permeability, in order to solve the technical problem that existing technologies cannot quickly and accurately determine the main controlling factors in the development of waterflooding in low-permeability reservoirs.

[0005] This invention provides a method for determining the main controlling factors of waterflooding efficiency in low-permeability reservoirs based on relative permeability, comprising:

[0006] The target reservoir conditions and core sampling were clearly defined. The target reservoir conditions included at least the following: temperature set at 78℃, crude oil viscosity set at 5 mPa·s, and formation water salinity set at 8000 mg / L.

[0007] Unsteady-state phase permeability experiments were conducted and the experimental data were processed to plot oil-water phase permeability curves for core samples with different permeability levels. The starting pressure gradient was tested and a fitting formula was constructed. The fitting formula is in the form of:

[0008] y = 0.6974x 0.598

[0009] Where y represents the starting pressure gradient, in MPa / m; and x represents the permeability, in mD.

[0010] Grey relational analysis was used to determine the main controlling factors.

[0011] In some embodiments, core sampling includes: testing the porosity and permeability of the core, and establishing a porosity-permeability curve of the core.

[0012] In some embodiments, the method includes: selecting representative core samples, wherein the selection of representative core samples is based on covering different permeability ranges.

[0013] In some embodiments, the unsteady-state phase permeation experiment includes: vacuum saturating the core with formation water, displacing the core at a constant flow rate of 0.1 mL / min to achieve saturated oil operation, and aging the core at 78°C for 48 hours.

[0014] In some embodiments, the experiment includes: conducting a displacement experiment at a flow rate of 0.33 mL / min, recording the displacement pressure, oil production, and liquid production, and processing the experimental data using a normalization method.

[0015] In some embodiments, the starting pressure gradient test includes: selecting a portion of the core samples and determining their true starting pressure gradient under low-speed water injection conditions, wherein the seepage rate under the low-speed water injection conditions is set to 0.01 mL / min to 0.1 mL / min.

[0016] In some embodiments, the grey relational analysis includes: extracting porosity, permeability, starting pressure gradient, bound water saturation, and mobile fluid saturation, and calculating the degree of influence of each factor on the oil displacement efficiency using the grey relational method.

[0017] In some embodiments, the method includes: constructing a reference sequence and a comparison sequence, calculating the correlation coefficient, and generating a correlation matrix.

[0018] In some embodiments, the fit of the fitting formula is R. 2 =0.9857, which is used to characterize the relationship between permeability and the starting pressure gradient.

[0019] Compared with existing technologies, this invention has the following advantages: it quantifies the influence of various factors on oil displacement efficiency through grey relational analysis, avoiding the errors of subjective judgment in traditional methods; the method of this invention is applicable to low-permeability reservoirs of different permeability levels; the method of this invention identifies mobile fluid saturation, bound water saturation, and starting pressure gradient as the main influencing factors, providing strong support for the refined development of low-permeability reservoirs. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1This is a flowchart of the method of the present invention;

[0022] Figure 2 This is a diagram illustrating the technical route of the present invention;

[0023] Figure 3 This is a graph showing the relationship between permeability and starting pressure gradient according to the present invention; where the horizontal axis represents permeability (mD); the vertical axis represents the starting pressure gradient (MPa / m); the red diamonds mark the actual measured data points; and the black solid line is the fitted curve, expressed as y = 0.6974x. 0.598 Goodness of fit R 2 =0.9857. Detailed Implementation

[0024] The following will refer to the appendices in the embodiments of the present invention. Figure 1-3 The technical solutions in the embodiments of the present invention will be clearly and completely described together. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0025] Example

[0026] This embodiment provides a method for determining the main controlling factors of waterflooding efficiency in low-permeability reservoirs based on relative permeability, specifically:

[0027] First, in clarifying the target reservoir conditions and core sampling procedures, it is necessary to determine the basic parameters of the target reservoir, including a temperature set at 78℃, crude oil viscosity set at 5 mPa·s, and formation water salinity set at 8000 mg / L. These parameters are derived from typical conditions in actual oilfield development to ensure the representativeness and application value of the experimental results. Natural core samples are collected from the target reservoir, and the porosity and permeability of the cores are determined using conventional laboratory testing methods. Porosity-permeability curves are then plotted. During this process, representative core samples of different permeability levels are selected to construct a core assemblies covering the range from low to high permeability for subsequent experimental analysis. The selection of these representative cores is based on the permeability gradient distribution to ensure that the experimental data can comprehensively reflect the actual characteristics of low-permeability reservoirs.

[0028] Specifically, representative core samples with different permeability levels were selected in this embodiment, as shown in the table below:

[0029]

[0030]

[0031] Furthermore, in the process of conducting unsteady-state phase permeation experiments and processing experimental data to plot oil-water phase permeation curves for cores with different permeability levels, oil-water phase permeation curves for cores with different permeability levels were obtained, and three key parameters—bound water saturation, mobile fluid saturation, and oil displacement efficiency—were further extracted. Specifically, the cores were first placed in a vacuum environment for vacuuming to ensure that no gas residue remained in the cores; then, formation water was used to saturate the cores, simulating the initial state under formation conditions. After saturation, crude oil was injected into the cores at a constant flow rate of 0.1 mL / min to achieve oil saturation. Next, the cores were placed in a high-temperature aging chamber at 78°C for 48 hours of aging treatment to simulate the interaction between the fluid inside the core and the rock surface under reservoir conditions. After aging, a displacement experiment was conducted at a seepage rate of 0.33 mL / min, and data such as displacement pressure, oil production, and fluid production were recorded during the experiment. After the experiment, the experimental data were standardized using the normalization method, and oil-water phase permeability curves for core samples with different permeability levels were plotted. The normalization method, by making the raw data dimensionless, eliminates the influence of experimental errors, thereby improving the accuracy of the phase permeability curves. Finally, by analyzing the experimental data, the bound water saturation, mobile fluid saturation, and oil displacement efficiency of each core sample were calculated. It should be noted that the calculation formulas for the aforementioned parameters were all derived based on experimental data to avoid interference from subjective judgment.

[0032] Specifically, the data table for the three parameters of bound water saturation, mobile fluid saturation, and oil displacement efficiency of cores with different permeability in this embodiment is as follows:

[0033]

[0034]

[0035] Furthermore, in the start-up pressure gradient test step, the actual start-up pressure gradient of core samples with different permeability levels is quantified, and a fitting formula is constructed to characterize the relationship between permeability and the start-up pressure gradient. Specifically, a selection of core samples are tested under low-rate water injection conditions. The seepage rate under low-rate water injection conditions is set between 0.01 mL / min and 0.1 mL / min to simulate the actual seepage environment of low-permeability reservoirs. During the test, the flow response of the core samples under different injection pressures is recorded to determine the minimum pressure gradient required to initiate flow. Finally, based on the test results, a fitting formula between the start-up pressure gradient and permeability is constructed. After data fitting, the formula is obtained as follows:

[0036] y = 0.6974x 0.598

[0037] Where y represents the starting pressure gradient, in MPa / m; x represents the permeability, in mD; and the goodness of fit R of the formula is... 2 =0.9857, indicating that it accurately describes the negative correlation between permeability and the starting pressure gradient. It should be noted that the established fitting formula provides important basic data for subsequent grey relational analysis.

[0038] Specifically, the core initiation pressure gradient data table in this embodiment is as follows:

[0039]

[0040]

[0041] Finally, in the step of determining the main controlling factors using grey relational analysis, based on the aforementioned data, five influencing factors are extracted: porosity, permeability, starting pressure gradient, bound water saturation, and mobile fluid saturation. The grey relational method is used to calculate the degree of influence of each factor on the oil displacement efficiency and quantify it in percentage form. Specifically, a reference sequence and a comparison sequence are constructed. The reference sequence contains the oil displacement efficiency data, and the comparison sequence contains the data of each influencing factor. The correlation coefficient is calculated, which reflects the similarity between the comparison sequence and the reference sequence. A correlation degree matrix is ​​generated. By analyzing the correlation degree matrix, the proportion of influence of each factor on the oil displacement efficiency is obtained. The calculated proportions of influence of each factor are as follows: porosity 9%, permeability 17.4%, starting pressure gradient 23.5%, mobile fluid saturation 25.2%, and bound water saturation 24.9%.

[0042] Based on the aforementioned analysis, it can be understood that, under the same conditions, the saturation of movable fluid has the greatest impact on oil displacement efficiency, followed by the saturation of bound water, and then the starting pressure gradient. The introduction of grey relational analysis overcomes the errors of subjective judgment in traditional methods, providing a scientific basis for the refined development of low-permeability reservoirs.

[0043] The technical solution of this invention achieves full-process coverage from identifying target reservoir conditions to analyzing key control factors, ensuring the accuracy of experimental data and the reliability of analysis results. Through standardized experimental design and data analysis processes, it clarifies the key control factors for water drive efficiency in low-permeability reservoirs, providing technical support for optimizing well network design and water injection strategies.

[0044] In practical applications, technicians can prioritize the two main factors of mobile fluid saturation and bound water saturation based on the results of grey relational analysis, and adjust the water injection strategy to improve water drive efficiency. The fitting formula for the starting pressure gradient can be used to predict the starting pressure gradient of cores with different permeability, providing guidance for the design of water injection development schemes.

[0045] In summary, this invention is applicable to low-permeability reservoirs of different permeability levels, has strong promotional value, and provides strong support for the efficient development of low-permeability reservoirs.

[0046] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0047] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for determining the main controlling factors of waterflooding efficiency in low-permeability reservoirs based on relative permeability, characterized in that, include: The target reservoir conditions and core sampling were clearly defined. The target reservoir conditions included at least the following: temperature set at 78℃, crude oil viscosity set at 5 mPa·s, and formation water salinity set at 8000 mg / L. Unsteady-state phase permeability experiments were conducted and the experimental data were processed to plot oil-water phase permeability curves for cores with different permeability levels. The test initiates the pressure gradient and a fitting formula is constructed, the fitting formula being of the following form: y=0.6974x 0.598 Where y represents the starting pressure gradient, in MPa / m; and x represents the permeability, in mD. Grey relational analysis was used to determine the main controlling factors.

2. The method according to claim 1, characterized in that, The core sampling includes: testing the porosity and permeability of the core, and establishing a porosity-permeability curve of the core.

3. The method according to claim 2, characterized in that, include: Representative core samples were selected, and the selection criteria for representative core samples were based on covering different permeability ranges.

4. The method according to claim 1, characterized in that, The unsteady-state phase permeation experiment includes: vacuum saturation of the core with formation water, displacement of the core at a constant flow rate of 0.1 mL / min to achieve saturated oil operation, and aging treatment of the core at 78°C for 48 hours.

5. The method according to claim 4, characterized in that, include: Displacement experiments were conducted at a flow rate of 0.33 mL / min. Displacement pressure, oil production, and liquid production were recorded, and the experimental data were processed using the normalization method.

6. The method according to claim 1, characterized in that, The starting pressure gradient test includes: selecting a portion of core samples and measuring their true starting pressure gradient under low-speed water injection conditions, wherein the seepage rate under the low-speed water injection conditions is set to 0.01 mL / min to 0.1 mL / min.

7. The method according to claim 1, characterized in that, The grey relational analysis includes: extracting porosity, permeability, starting pressure gradient, bound water saturation, and mobile fluid saturation, and calculating the degree of influence of each factor on the oil displacement efficiency using the grey relational method.

8. The method according to claim 7, characterized in that, include: Construct a reference sequence and a comparison sequence, calculate the correlation coefficient, and generate a correlation matrix.

9. The method according to claim 1, characterized in that, The goodness of fit of the fitting formula is R 2 =0.9857, which is used to characterize the relationship between permeability and the starting pressure gradient.

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