A method for evaluating sensitivity of rock permeability model parameters based on variance decomposition

Abstract

The application provides a rock permeability model parameter sensitivity evaluation method based on variance decomposition. According to parameter analysis of factors influencing rock gas logging permeability, the parameter and the parameter value range are determined. The Sobol sequence sampling method is used to generate the input parameters of the calculation model, the input parameters are substituted into the gas logging permeability theoretical model extended according to the Darcy law, and the calculation value of the permeability is obtained. The influence degree of different parameters on the result is calculated by the variance decomposition method.

Description

Technical Field

[0001] This application relates to the field of rock physics, and in particular to a method for evaluating the sensitivity of parameters in rock permeability models based on variance decomposition. Background Technology

[0002] Permeability describes the ability of fluids to migrate in oil and gas reservoirs, and is of great significance for the production properties and capabilities of reservoir development. Currently, the helium gas method for measuring rock permeability is quite mature, essentially obtaining rock permeability by processing experimental data using a gas permeability theoretical model extended from Darcy's law. In actual rock permeability testing, the results are often affected by factors such as the design of the testing instrument system, the temperature and pressure environment, and the settings of the experimental parameters. Parameter sensitivity analysis of rock gas permeability is very helpful for evaluating the uncertainty of experimental results and adjusting the test results.

[0003] Although many calculation models have been proposed for permeability testing, the sensitivity analysis of permeability testing parameters is still somewhat lacking. In mathematical statistical analysis, existing sensitivity analysis methods mainly employ local sensitivity analysis. Local methods primarily analyze the local influence of factors on the model and can obtain the gradient of parameters with respect to the output. They are generally used for system models with relatively simple mathematical expressions, easily derived differential equations of sensitivity, and fewer uncertainties. Summary of the Invention

[0004] This application provides a method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition, aiming to solve the problem of inaccurate sensitivity analysis of existing permeability test parameters.

[0005] The technical solution of this application is:

[0006] A method for evaluating the sensitivity of parameters in a rock permeability model based on variance decomposition includes the following steps:

[0007] S1. Identify the factors affecting permeability and define the input parameter range of the rock permeability calculation model: Determine the factors affecting gas flow using empirical methods. These factors include fluid viscosity, pressure, temperature, gas flow rate, length of the plunger sample, and cross-sectional area of ​​the plunger sample. Set large-value sampling boundaries for each of the factors to determine the value range of the input parameters for each factor.

[0008] S2, The input parameters of the rock permeability calculation model are obtained by using the Sobol sequence sampling method: Based on the type and value range of the input parameters of the determined influencing factors, the input parameters of the rock permeability calculation model are sampled using the Sobol method with low difference sequence sampling.

[0009] S3, Apply the rock permeability calculation model to obtain the rock permeability calculation result: Use the gas permeability calculation model corresponding to the pulse decay method to calculate and simulate the input parameters to obtain the rock permeability calculation result;

[0010] S4. The parameter sensitivity of the rock permeability calculation model is evaluated by variance decomposition: the results of the input and output parameters of the permeability calculation model are evaluated based on the variance decomposition method, and the sensitivity of the output result to the input variable is measured by the variance caused by the corresponding input parameter in the output result; in the calculation, the Monte Carlo method is used to solve the integral form of the variance to obtain the ratio of the variance of different variable parameter combinations to the total variance, determine the parameter sensitivity of different orders, and calculate the overall global sensitivity of the variable.

[0011] As a technical solution of this application, in step S3, the rock permeability is determined using the pulse decay method: the plunger sample is saturated with gas at a specified pressure. After the pressure of the plunger sample stabilizes, the pressure difference between the upstream and downstream ends of the core of the plunger sample is established by reducing the downstream pressure of the plunger sample. During the gas seepage process in the plunger sample, the upstream pressure of the plunger sample continuously decreases, the downstream pressure continuously increases, and gradually tends to equilibrium. The rock permeability is calculated by establishing a functional relationship between the upstream average pressure, the downstream average pressure of the plunger sample, and time.

[0012] As one technical solution of this application, in step S3, the rock permeability is determined using a global sensitivity factor analysis method:

[0013]

[0014] In the formula, k is the rock permeability, S1 is the pressure drop slope, and u g Where L is the gas viscosity, f is the test length of the plunger-shaped sample, and f is the gas viscosity. z f1 is the gas compressibility correction factor, f1 is the mass flow rate correction factor, A is the core cross-sectional area, and P is the mass flow rate correction factor. m V1 represents the average pressure, V2 represents the volume of the upstream container, and V1 represents the volume of the downstream container.

[0015] As a technical solution of this application, in step S4, the variance decomposition method decomposes the rock permeability calculation model into multiple parameters and functions combining these parameters; wherein, it is assumed that the rock permeability calculation model is y = f(x), where x = (x1, x2, ..., x...). k ) is the input value of the rock permeability calculation model, and xi Given a uniform distribution [0, 1], where y is the corresponding output value; if f(x) is decomposed into the sum of functions of different dimensions:

[0016]

[0017] Where f0 is a constant, and the integral of each decomposition term with respect to any factor contained within the decomposition term is 0; i is the variable index; k is the total number of variables; f i (x i ) represents the penetration rate of the i-th x-th variable; j is the index of another variable; f ij (x i x j f is the penetration rate calculated using two variables as input parameters; 1、2…k (x1, x2…x k This is the penetration rate calculated from multiple variables;

[0018]

[0019]

[0020] s i1...ik =∑S i1...is (k≤s),

[0021] In the formula, f i1、i2…is (x i1 x i2 , ...x is ) represent the penetration rates calculated from the combinations of various variables; x ij The variable is the integral variable; i is the variable index; j is the variable index; s is the number of variables; S i1、i2…is These are the sensitivity coefficients of each order; D i1、i2…is These are the partial variances of each order; S i1、i2…ik It is the sensitivity coefficient;

[0022] Calculate the total variance D of the rock permeability calculation model y = f(x), and then calculate the variance D of each sub-term. i1、…、is That is, the partial variances of each order; through the partial variances D of each order i1、…、is Dividing the total variance D of the rock permeability calculation model by the variance yields the variable x. i1、…、xik Sensitivity coefficient S i1…ik Wherein, the total variance D is the sum of the partial variances of each order; in the Sobol sequence sampling method, the integral of the variance can be obtained by the Monte Carlo method;

[0023]

[0024]

[0025]

[0026] In the formula, It is a constant; n is the number of simulations in the simulation set; m is the index of the number of simulations; f(X) m ) represents the calculation model result corresponding to the m-th simulation number; It is variance; It is the variance of the i-th variable; It is the numerical value of the function calculated for the m-th variable i; It is the function value calculated for the m-th variable other than the i-th variable; (-i) are the other variables other than i.

[0027] Based on the calculation results, the influencing parameters and their value ranges in the permeability testing process are determined. The parameters are then randomly sampled using the Sobol sequence sampling method. The simulation results are substituted into the rock permeability calculation model, and the sensitivity of each parameter in the rock permeability calculation model is evaluated using the variance decomposition method.

[0028] The beneficial effects of this application are:

[0029] This application provides a method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition. This method solves the problem of difficulty in evaluating the sensitivity of key parameters in rock permeability testing models, and provides guidance for parameter setting in rock permeability testing. Furthermore, this method allows for the simple and convenient determination of the sensitivity of rock permeability testing parameters. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0031] Figure 1 A flowchart illustrating the sensitivity evaluation method for rock permeability model parameters based on variance decomposition provided in this application embodiment;

[0032] Figure 2 This is a schematic diagram of rock pulse attenuation permeability testing provided in an embodiment of this application;

[0033] Figure 3 This is a schematic diagram of input parameter sampling provided in an embodiment of this application;

[0034] Figure 4 A graph showing the results of the overall order exponential sensitivity analysis of penetration provided in the embodiments of this application;

[0035] Figure 5 The diagram shows the results of a first-order exponential sensitivity analysis of penetration provided in the embodiments of this application. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can typically be arranged and designed in various different configurations.

[0037] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0038] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0039] In the description of this application, it should be noted that the terms "upper" and "lower" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use. They are only used to facilitate the description of this application and to simplify the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0040] Furthermore, in this application, unless otherwise expressly specified and limited, "above or below" the first feature may include direct contact between the first and second features, or contact between the first and second features through another feature between them. Moreover, "above," "over," and "on" the first feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the first feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0041] Furthermore, terms such as "horizontal" and "vertical" do not imply that components must be absolutely horizontal or suspended, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0042] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set up," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0043] Example:

[0044] Please refer to Figure 1 (Refer to) Figures 2 to 5 This application provides a method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition. The main purpose is to address the problem of evaluating parameter sensitivity in rock property testing due to the influence of various factors. In the specific permeability model calculation process, by analyzing the parameter sensitivity of the testing system, the aim is to provide a method for evaluating the sensitivity of rock permeability model parameters that can adjust the rock property testing process and results. It mainly includes the following steps:

[0045] S1. Determine the influencing factors of permeability and define the input parameter range for the rock permeability calculation model: In the process of rock gas permeability measurement, it is necessary to analyze the influencing factors involved in the experiment. In gas permeability measurement, helium, with its relatively small atomic number, is generally used as the test fluid. According to Boyle's law, the volume of a gas is mainly affected by pressure and temperature. In addition, the flow rate of the gas under pressure difference and the viscosity of the fluid also need to be considered. Besides the test gas, the measurement errors of the length of the plunger sample and its corresponding cross-sectional area during the experiment will also affect the calculation of the permeability model. In actual testing, while maintaining data rationality, the sampling boundary should be set with the largest possible value, defining the range of input parameter variations. Therefore, the influencing factors affecting gas flow are determined empirically, including fluid viscosity, pressure, temperature, gas flow rate, the length of the plunger sample, and the cross-sectional area of ​​the plunger sample. For each influencing factor, a large sampling boundary (i.e., using the range of parameter settings in conventional practices as the input parameter boundary) is set to determine the value range of the input parameters for the influencing factors.

[0046] S2, the Sobol sequence sampling method is used to obtain the input parameters of the rock permeability calculation model: the Sobol sequence focuses on generating a uniform distribution in the probability space, using an essentially random but clever method to fill the probability space, that is, the random numbers generated later will be distributed to areas that were not sampled before; therefore, according to the parameter type and value range determined in step S1, the Sobol sequence sampling method is used to perform low difference sequence sampling on the input parameters of the rock permeability calculation model (low difference sequence sampling means that the difference between the input parameters is small, so the data sampling distribution is more uniform).

[0047] S3, Applying the rock permeability calculation model to obtain permeability calculation results: The gas permeability calculation model corresponding to the pulse decay method is used to calculate and simulate the input parameters to obtain the permeability calculation results; Among them, the gas permeability calculation model is calculated based on the sample porosity, length, cross-sectional area and fluid compressibility correction factor, and the mass flow rate correction factor is calculated based on the upstream container volume, downstream container volume and sample information.

[0048] S4. Evaluate the parameter sensitivity of the rock permeability calculation model using variance decomposition: The results of the input and output parameters of the permeability calculation model are evaluated based on the variance decomposition method, and the sensitivity of the output result to the input variable is measured by the variance caused by the corresponding input parameter in the output result; In the calculation, the Monte Carlo method is used to solve the integral form of the variance to obtain the ratio of the variance of different variable parameter combinations to the total variance, determine the parameter sensitivity of different orders, and calculate the overall global sensitivity of the variable.

[0049] This method considers the global influence of multiple factors and can be used to study the sensitivity analysis of nonlinear, non-superposition, and non-monotonic models. In rock permeability testing, it fully considers the influencing factors such as the test temperature and pressure environment, system design, and experimental setting parameters, and conducts sensitivity analysis of rock permeability test parameters to guide the parameter setting in the rock permeability test process.

[0050] It should be noted that in step S3, the rock permeability is determined using the pulse decay method: a saturated gas at a specified pressure is introduced into the plunger sample. After the pressure of the plunger sample stabilizes, the pressure difference between the upstream and downstream ends of the plunger sample is established by reducing the downstream pressure of the plunger sample (i.e., the pressure at the lower part of the core end of the permeability testing instrument). During the gas seepage process in the plunger sample, the upstream pressure continuously decreases and the downstream pressure continuously increases, gradually approaching equilibrium. The rock permeability is calculated by establishing a functional relationship between the upstream average pressure, the downstream average pressure of the plunger sample, and time.

[0051] Furthermore, in step S3, the principle of permeability testing involves the seepage equation and requires the elimination of the gas slippage effect. Since there are many influencing factors, the conventional Darcy formula can only roughly reflect the permeability testing range, and its influencing factors and uncertainty analysis are relatively difficult. Therefore, a global sensitivity factor analysis method is adopted here:

[0052]

[0053] In the formula, k is the rock permeability, S1 is the pressure drop slope, and u g Where is the gas viscosity, L is the test length of the plunger-shaped rock sample, and f is the gas viscosity. z f1 is the gas compressibility correction factor, f1 is the mass flow rate correction factor, A is the core cross-sectional area, and P is the mass flow rate correction factor. m V1 represents the average pressure, V2 represents the volume of the upstream container, and V1 represents the volume of the downstream container.

[0054] Meanwhile, in step S4, the core of the variance decomposition method is to decompose the model into functions of individual parameters and combinations of these parameters; assuming the model is y = f(x), where x = (x1, x2, ..., x... k ) is the input value of the model, and x i Given a uniform distribution [0, 1], where y is the corresponding output value; if f(x) is decomposed into the sum of functions of different dimensions:

[0055]

[0056] Where f0 is a constant, and the integral of each decomposition term with respect to any factor contained within the decomposition term is 0; i is the variable index; k is the total number of variables; f i (x i ) represents the penetration rate of the i-th x-th variable; j is the index of another variable; f ij (x i x j f is the penetration rate calculated using two variables as input parameters; 1、2…k (x1, x2…x k This is the penetration rate calculated from multiple variables;

[0057]

[0058]

[0059] s i1…ik =∑s i1…is (k≤s),

[0060] In the formula, f i1、i2…is (x i1 x i2 , ...x is) represent the penetration rates calculated from the combinations of various variables; x ij The variable is the integral variable; i is the variable index; j is the variable index; s is the number of variables; S i1、i2…is These are the sensitivity coefficients of each order; D i1、i2…is These are the partial variances of each order; S i1、i2…ik It is the sensitivity coefficient;

[0061] The decomposition of f(x) is unique; according to statistical theory, the total variance D of the rock permeability calculation model y=f(x) is obtained, and then the variance D of each sub-term is calculated. i1、…、is That is, the partial variances of each order; by dividing each partial variance by the total variance of the model, we can obtain the variable x. i1、…、xik Sensitivity coefficient S i1…ik The total variance is the sum of the partial variances of each order; in the Sobol sequence sampling method, the integral of the variance can be obtained by the Monte Carlo method.

[0062]

[0063]

[0064]

[0065] In the formula, It is a constant; n is the number of simulations in the simulation set; m is the index of the number of simulations; f(X) m ) represents the calculation model result corresponding to the m-th simulation number; It is variance; It is the variance of the i-th variable; It is the numerical value of the function calculated for the m-th variable i; It is the function value calculated for the m-th variable other than the i-th variable; (-i) are the other variables other than i.

[0066] Based on the above principles, the parameters and their ranges that affect the test results during the permeability test are determined. Using the Sobol sequence sampling method, the parameters are randomly simulated and sampled. The simulation results are then substituted into the rock permeability calculation model. Finally, the variance decomposition method is used to evaluate the sensitivity of each parameter in the rock permeability calculation model.

[0067] Specifically, the method is used in conjunction with the SLP-II ultra-low permeability testing instrument for analysis.

[0068] The fluid viscosity affecting helium was determined empirically, taking temperature into account. Values ​​were obtained by combining experimental measurements of the upstream and downstream containers, and the statistical range of variation across multiple measurements was provided. The pressure difference value was set considering the fluid's motion pattern; in gas permeability measurements, the pressure difference is generally considered to be greater than the pneumatic valve pressure gradient, while remaining within the linear flow range. The data error for the length and cross-sectional area of ​​the plunger sample should fluctuate within a reasonable range. The slope of the pressure drop was determined based on the variation observed in actual tests. This experiment considered nine parameters affecting permeability calculations, and the numerical ranges for these nine parameters were defined.

[0069] By combining the Sobol sequence sampling method with the input parameter sampling design, a random distribution of input parameters is obtained. Figure 3 This is a sampling distribution diagram of the pressure drop slope parameter. After organizing the sampling of the nine parameters, substituting them into the calculation model yields the simulated permeability value.

[0070] By combining a global sensitivity analysis method based on variance decomposition to evaluate the sensitivity of the output variables, the results of the overall exponential sensitivity analysis of penetration can be obtained. Figure 4 ) and the results of the first-order exponential sensitivity analysis of penetration ( Figure 5 Analysis reveals that the average pressure, pressure drop slope, and sample porosity are highly sensitive to the experimental results, while temperature and the testing system itself are less sensitive. The analysis indicates that the permeability results are largely reflected in the pressure difference of the tested fluid and the porosity characteristics of the sample itself.

[0071] In summary, this application provides a method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition. This method solves the problem of difficulty in evaluating the sensitivity of key parameters in rock permeability testing models and provides guidance for parameter setting in rock permeability testing. Furthermore, this method allows for the simple and convenient determination of the sensitivity of rock permeability testing parameters.

[0072] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition, characterized in that, Includes the following steps: S1. Identify the factors affecting permeability and define the input parameter range of the rock permeability calculation model: determine the factors affecting gas flow, including fluid viscosity, pressure, temperature, gas flow rate, length of the plunger sample, and cross-sectional area of ​​the plunger sample; set values ​​for each of the factors and determine the range of values ​​for the input parameters of the factors. S2, The input parameters of the rock permeability calculation model are obtained by using the Sobol sequence sampling method: Based on the type and value range of the input parameters of the determined influencing factors, the input parameters of the rock permeability calculation model are sampled using the Sobol method with low difference sequence sampling. S3, Apply the rock permeability calculation model to obtain the rock permeability calculation result: Use the gas permeability calculation model corresponding to the pulse decay method to calculate and simulate the input parameters to obtain the rock permeability calculation result; S4. The parameter sensitivity of the rock permeability calculation model is evaluated by variance decomposition: the results of the input and output parameters of the permeability calculation model are evaluated based on the variance decomposition method, and the sensitivity of the output result to the input variable is measured by the variance caused by the corresponding input parameter in the output result; in the calculation, the Monte Carlo method is used to solve the integral form of the variance to obtain the ratio of the variance of different variable parameter combinations to the total variance, determine the parameter sensitivity of different orders, and calculate the overall global sensitivity of the variable.

2. The method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition according to claim 1, characterized in that, In step S3, the rock permeability is determined using the pulse decay method: the plunger sample is saturated with gas at a specified pressure. After the pressure of the plunger sample stabilizes, the pressure difference between the upstream and downstream ends of the core is established by reducing the downstream pressure of the plunger sample. During the gas seepage process in the plunger sample, the upstream pressure continuously decreases and the downstream pressure continuously increases, gradually approaching equilibrium. The rock permeability is calculated by establishing a functional relationship between the average upstream pressure, the average downstream pressure, and time.

3. The method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition according to claim 1, characterized in that, In step S3, the rock permeability is determined using a global sensitivity factor analysis method: In the formula, k is the rock permeability, S1 is the pressure drop slope, and u g Where L is the gas viscosity, f is the test length of the plunger-shaped sample, and f is the gas viscosity. z f1 is the gas compressibility correction factor, f1 is the mass flow rate correction factor, A is the core cross-sectional area, and P is the mass flow rate correction factor. m V1 represents the average pressure, V2 represents the volume of the upstream container, and V1 represents the volume of the downstream container.

4. The method for evaluating the sensitivity of rock permeability model parameters based on variance decomposition according to claim 1, characterized in that, In step S4, the variance decomposition method decomposes the rock permeability calculation model into multiple parameters and functions combining these parameters; wherein, it is assumed that the rock permeability calculation model is y = f(x), where x = (x1, x2, ..., x...). k ) is the input value of the rock permeability calculation model, and x i Given a uniform distribution [0, 1], where y is the corresponding output value; if f(x) is decomposed into the sum of functions of different dimensions: Where f0 is a constant, and the integral of each decomposition term with respect to any factor contained within the decomposition term is 0; i is the variable index; k is the total number of variables; f i (x i ) represents the penetration rate of the i-th x-th variable; j is the index of another variable; f ij (x i x j f is the penetration rate calculated using two variables as input parameters; 1、2…k (x1, x2…x k This is the penetration rate calculated from multiple variables; S i1…ik =∑S i1…is (k≤s), In the formula, f i1、i2…is (x i1 x i2 , ...x is ) represent the penetration rates calculated from the combinations of various variables; x ij The variable is the integral variable; i is the variable index; j is the variable index; s is the number of variables; S i1、i2…is These are the sensitivity coefficients of each order; D i1、i2…is These are the partial variances of each order; S i1、i2…ik It is the sensitivity coefficient; Calculate the total variance D of the rock permeability calculation model y = f(x), and then calculate the variance D of each sub-term. i1、…、is That is, the partial variances of each order; through the partial variances D of each order i1、…、is Dividing the total variance D of the rock permeability calculation model by the variance yields the variable x. i1、…、xik Sensitivity coefficient S i1…ik Wherein, the total variance D is the sum of the partial variances of each order; in the Sobol sequence sampling method, the integral of the variance can be obtained by the Monte Carlo method; In the formula, It is a constant; n is the number of simulations in the simulation set; m is the index of the number of simulations; f(X) m ) represents the calculation model result corresponding to the m-th simulation number; It is variance; It is the variance of the i-th variable; It is the numerical value of the function calculated for the m-th variable i; It is the function value calculated for the m-th variable other than the i-th variable; (-i) is the other variable other than i. Based on the calculation results, the influencing parameters and their value ranges in the permeability testing process are determined. The parameters are then randomly sampled using the Sobol sequence sampling method. The simulation results are substituted into the rock permeability calculation model, and the sensitivity of each parameter in the rock permeability calculation model is evaluated using the variance decomposition method.

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