Method and device for determining permeability of shale and electronic equipment

Abstract

The present application provides a shale permeability determination method, device and electronic equipment. The method comprises: obtaining a plurality of nitrogen adsorption amounts and a plurality of nitrogen desorption amounts collected under different relative pressure values of the shale to be measured; based on the plurality of nitrogen adsorption amounts and the plurality of nitrogen desorption amounts, generating a nitrogen adsorption curve and a nitrogen desorption curve; wherein the nitrogen adsorption curve represents the change trend of the nitrogen adsorption amount with the increase of the relative pressure, and the nitrogen desorption curve represents the change trend of the nitrogen desorption amount with the increase of the relative pressure; according to the nitrogen adsorption curve and the nitrogen desorption curve, a hysteresis loop is generated in a plane coordinate system shared by the nitrogen adsorption curve and the nitrogen desorption curve, and a hysteresis loop parameter of the hysteresis loop is determined; the hysteresis loop parameter is a parameter representing the shape of the hysteresis loop; and according to the hysteresis loop parameter, the permeability range of the shale to be measured is determined. The method of the present application improves the efficiency and accuracy of determining the permeability of shale.

Description

Technical Field

[0001] This application relates to oil and gas exploration technology, and more particularly to a method, apparatus and electronic equipment for determining the permeability of shale. Background Technology

[0002] Currently, China's national economy is growing rapidly, and the demand for oil and natural gas resources is also increasing. Therefore, the exploration of unconventional oil and gas resources has become a key research focus in my country. As an important component of unconventional oil and gas, shale oil and gas has achieved initial industrial-scale development in my country, and the country has made significant innovations and progress in geological theory, development methods, and engineering technology.

[0003] Shale exhibits unique characteristics compared to conventional rocks: its pore structure is complex, multi-scale, and highly heterogeneous, with a wide pore size distribution and intricate pore structure. Therefore, understanding the seepage characteristics of fluids within the shale pore network has always been a challenging research area, such as evaluating shale permeability.

[0004] However, shale reservoirs are denser and have a more complex pore structure than conventional reservoirs. Conventional permeability evaluation and prediction methods have limitations for shale reservoirs, and cannot accurately and efficiently evaluate and predict the permeability of shale reservoirs. Summary of the Invention

[0005] This application provides a method, apparatus, and electronic device for determining the permeability of shale, in order to solve the current problem of being unable to accurately and efficiently evaluate and predict the permeability of shale reservoirs.

[0006] In a first aspect, this application provides a method for determining the permeability of shale, comprising:

[0007] Multiple nitrogen adsorption and desorption values ​​were collected from the shale under different relative pressure values; each relative pressure corresponds to one nitrogen adsorption and one nitrogen desorption value.

[0008] Based on the multiple nitrogen adsorption amounts and the multiple nitrogen desorption amounts, nitrogen adsorption curves and nitrogen desorption curves are generated; wherein, the nitrogen adsorption curve characterizes the trend of nitrogen adsorption amount with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption amount with increasing relative pressure.

[0009] Based on the nitrogen adsorption curve and the nitrogen desorption curve, a hysteresis loop is generated in the plane coordinate system where the nitrogen adsorption curve and the nitrogen desorption curve coexist, and the hysteresis loop parameters are determined; the hysteresis loop parameters are parameters characterizing the shape of the hysteresis loop.

[0010] The permeability range of the shale to be tested is determined based on the hysteresis loop parameters.

[0011] Secondly, this application provides a shale permeability determination device, comprising:

[0012] The acquisition module is used to acquire multiple nitrogen adsorption amounts and multiple nitrogen desorption amounts collected from the shale under different relative pressure values; wherein, each relative pressure corresponds to one nitrogen adsorption amount and one nitrogen desorption amount;

[0013] The curve generation module is used to generate a nitrogen adsorption curve and a nitrogen desorption curve based on the plurality of nitrogen adsorption amounts and the plurality of nitrogen desorption amounts; wherein, the nitrogen adsorption curve characterizes the trend of nitrogen adsorption amount with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption amount with increasing relative pressure.

[0014] The hysteresis loop generation module is used to generate a hysteresis loop in the plane coordinate system where the nitrogen adsorption curve and the nitrogen desorption curve coexist, based on the nitrogen adsorption curve and the nitrogen desorption curve, and to determine the hysteresis loop parameters; the hysteresis loop parameters are parameters characterizing the shape of the hysteresis loop.

[0015] The determination module is used to determine the permeability range of the shale to be tested based on the hysteresis parameters.

[0016] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method described in the first aspect.

[0017] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the shale permeability determination method described in the first aspect.

[0018] The method, apparatus, and electronic equipment for determining the permeability of shale provided in this application acquire multiple nitrogen adsorption and desorption values ​​of the shale under different relative pressures. Each relative pressure corresponds to one nitrogen adsorption and desorption value. Based on these multiple nitrogen adsorption and desorption values, nitrogen adsorption curves and nitrogen desorption curves are generated. The nitrogen adsorption curve characterizes the trend of nitrogen adsorption with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption with increasing relative pressure. Based on the nitrogen adsorption and desorption curves, a hysteresis loop is generated in the plane coordinate system where the nitrogen adsorption and desorption curves coexist, and the hysteresis loop parameters are determined. The hysteresis loop parameters characterize the shape of the hysteresis loop. Based on the hysteresis loop parameters, the permeability range of the shale under test is determined. In other words, by establishing nitrogen adsorption and desorption curves for the shale to be tested, and generating a hysteresis loop based on these curves, the range of permeability of the shale to be tested can be determined quickly and accurately by using the hysteresis loop parameters, since there is a correlation between the hysteresis loop parameters characterizing the shape of the hysteresis loop and the permeability of the shale to be tested. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] Figure 1 This is a flowchart illustrating a method for determining the permeability of shale according to an exemplary embodiment;

[0021] Figure 2 It is based on Figure 1 An example illustrates a planar coordinate system including a nitrogen adsorption curve and a nitrogen desorption curve;

[0022] Figure 3 It is based on Figure 1 A schematic diagram of the hysteresis loop shown in the embodiment;

[0023] Figure 4 This is a flowchart illustrating a method for determining the permeability of shale according to another exemplary embodiment;

[0024] Figure 5 It is based on Figure 4 An example illustration shows a schematic diagram of the linear relationship between various hysteresis parameters and permeability parameters;

[0025] Figure 6 It is based on Figure 4 A schematic diagram illustrating the distribution of multiple sample groups in the embodiment;

[0026] Figure 7 It is based on Figure 4 An example illustration shows the clustering results of multiple sample groups;

[0027] Figure 8 This is a block diagram illustrating a shale permeability determination device according to an exemplary embodiment;

[0028] Figure 9 This is a schematic diagram of the structure of an electronic device according to an exemplary embodiment.

[0029] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0030] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0031] Shale pore structure is more unique than that of conventional rocks: it is complex, multi-scale, and highly heterogeneous, with a wide range of pore sizes. Therefore, the seepage characteristics of fluids within the shale pore network have always been a research challenge. In-depth research on the seepage characteristics in shale is of great significance for the efficient, scientific, and rational exploration and development of shale oil and gas reservoirs.

[0032] Among the relevant technologies, the main methods for evaluating reservoir permeability include: porosity-permeability relationship method, flow unit index method, neural network method, and digital core method.

[0033] Among them, the porosity-permeability relationship method mainly involves establishing an empirical formula for estimating permeability using conventional logging based on the analysis of the porosity-permeability relationship of core samples from various strata, and then using methods such as nuclear magnetic resonance logging to calculate permeability.

[0034] The flow unit index method mainly involves analyzing the correlation between the flow unit index and the logging response to identify sensitive parameters of the flow unit index. Through multiple regression statistical analysis, a fitting equation for the flow unit index is established. Porosity-permeability relationships are established for different types of reservoirs. The porosity values ​​obtained by the optimization method are substituted into the fitting formulas to obtain the interpreted permeability values ​​of the formation.

[0035] The neural network method mainly utilizes the nonlinear relationships between reservoir physical parameters such as porosity, pore fluid composition, lithology, median grain size, and bound water saturation to establish a neural network model to predict permeability.

[0036] The digital core method mainly uses the lattice Boltzmann method based on mesoscopic theory to simulate and reconstruct digital cores. It evaluates the similarity between the reconstructed digital cores and real cores in terms of pore geometry and conductivity characteristics. The permeability of digital cores constructed by stochastic methods, process simulation methods and X-CT methods is calculated using the finite difference method and the lattice Boltzmann method.

[0037] However, while the aforementioned methods can predict and simulate the permeability of conventional reservoirs, they still have the following drawbacks: The porosity-permeability relationship method requires a massive amount of data. Current methods require reservoir physical property data and a large amount of empirical data to support the accuracy of predictions. The flow unit index method lacks sufficient theoretical support. Different models need to be established for permeability prediction, but the theoretical basis of the models themselves is insufficient, leading to certain inaccuracies and errors in the model results. When using neural network methods, due to the special characteristics of shale reservoirs—shale reservoirs are denser and have a very complex pore structure than conventional reservoirs—conventional permeability evaluation methods, although widely validated and applicable, still have limitations for shale reservoirs. To date, no literature reports a permeability model or prediction method with good adaptability and high accuracy for well logging evaluation of shale reservoir permeability. The digital core method is time-consuming. Separate models need to be created for each core sample for estimation and prediction. While this method can be used to obtain permeability data when the sample size is small, it is time-consuming for large-scale data. Therefore, the current evaluation methods are difficult to promote on a large scale and cannot be widely applied nationwide.

[0038] The method for determining shale permeability provided in this application aims to solve the aforementioned technical problems of existing technologies. Specifically, it provides a new, efficient, convenient, large-scale applicable, time-saving, quantitatively characterizing, and graded evaluation method for shale reservoir permeability assessment. This method overcomes the limitations of conventional reservoir permeability assessment techniques by establishing a multivariate comprehensive classification coefficient for reservoir permeability assessment through the hysteresis loop parameter of the nitrogen adsorption-desorption curve. Reservoir permeability is then classified and evaluated based on the magnitude of this comprehensive classification coefficient. Different permeability classifications correspond to different ranges, and the permeability range can be determined based on the evaluation structure of the classification assessment. This provides a new approach and method for solving the permeability assessment of shale reservoirs.

[0039] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0040] Figure 1 This is an exemplary embodiment illustrating a method for determining the permeability of shale, such as... Figure 1 As shown, the method for determining the permeability of this shale may include:

[0041] 110. Obtain multiple nitrogen adsorption and desorption values ​​of the shale under different relative pressure values; wherein, each relative pressure corresponds to one nitrogen adsorption and one nitrogen desorption value.

[0042] For example, the method for determining the permeability of shale can be applied to electronic devices, which may include, but are not limited to, mobile terminals, computers, servers, etc.

[0043] In some embodiments, the electronic device may include an experimental database containing experimental data performed on the shale to be tested. This experimental data may include multiple nitrogen adsorption and desorption values ​​collected from the shale under different relative pressures. Therefore, the electronic device can directly retrieve these multiple nitrogen adsorption and desorption values ​​from the experimental database. Optionally, the experimental database may be located locally on the electronic device or on a cloud server communicatively connected to the electronic device, so that the electronic device can retrieve it from the cloud server when needed.

[0044] For example, a user can conduct a low-temperature nitrogen adsorption experiment on the shale to be tested to obtain the above-mentioned experimental data and store the experimental data in an experimental database. For instance, when conducting the low-temperature nitrogen adsorption experiment on the sample, the size of the shale to be tested (hereinafter also referred to as the sample) can be between 80 and 100 mesh. Before the experiment, it needs to be vacuum dried at 110°C for 24 hours to remove moisture and volatile gases from the shale. The sample mass must be accurately weighed, and the sample tube and sample mass must be recorded to an accuracy of 0.0001 g. As an example, this embodiment uses a shale sample from the Fengcheng Formation in the Mahu Depression of the Junggar Basin as an example. The depth range of the sample can be 4000-5660 meters.

[0045] Optionally, when performing a low-temperature nitrogen adsorption experiment on a sample, the sample mass should be accurately weighed and the sample tube and sample mass should be recorded to an accuracy of 0.0001g.

[0046] Alternatively, the low-temperature nitrogen adsorption experiment can be conducted at a temperature of -195.8℃.

[0047] 120. Based on multiple nitrogen adsorption amounts and multiple nitrogen desorption amounts, generate nitrogen adsorption curves and nitrogen desorption curves; wherein, the nitrogen adsorption curve characterizes the trend of nitrogen adsorption amount with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption amount with increasing relative pressure.

[0048] For example, when obtaining the nitrogen adsorption-desorption curve of a sample, high-purity nitrogen is required as the adsorbate, and adsorption isotherms should be obtained at a temperature of -195.8℃ and under different relative pressures.

[0049] As an example, an electronic device can use different relative pressure values ​​as the horizontal axis and multiple nitrogen adsorption amounts collected under different relative pressure values ​​as the vertical axis to obtain coordinate points corresponding to multiple nitrogen adsorption amounts in a plane coordinate system. Then, the above multiple coordinate points are connected to obtain a nitrogen adsorption curve.

[0050] Following the above example, the electronic device can, in the plane coordinate system containing the nitrogen adsorption curve, use different relative pressure values ​​as the abscissa and multiple nitrogen desorption amounts collected at different relative pressure values ​​as the ordinate. Using this plane coordinate system, it obtains coordinate points corresponding to multiple nitrogen desorption amounts, and then connects these coordinate points to obtain the nitrogen desorption curve. Exemplarily, the plane coordinate system including the nitrogen adsorption curve and the nitrogen desorption curve (hereinafter also referred to as the nitrogen adsorption-desorption curve) can be as follows: Figure 2 As shown, where, Figure 2 Curve 1 in the diagram represents the nitrogen adsorption curve, and curve 2 represents the nitrogen desorption curve. According to... Figure 2 It can be seen that the amount of nitrogen adsorbed and the amount of nitrogen attached generally increase with the increase of relative pressure.

[0051] 130. Based on the nitrogen adsorption curve and the nitrogen desorption curve, generate a hysteresis loop in the plane coordinate system where the nitrogen adsorption curve and the nitrogen desorption curve coexist, and determine the hysteresis loop parameters; the hysteresis loop parameters are parameters that characterize the shape of the hysteresis loop.

[0052] Optionally, the hysteresis parameters include perimeter, area, maximum height, maximum width, and minimum circumscribed circle area.

[0053] For example, the electronic device may be equipped with data analysis software. Optionally, the data analysis software may be MATLAB software. For instance, the electronic device can use MATLAB software to analyze... Figure 2The hysteresis loop parameters in the nitrogen adsorption-desorption curve are calculated. During the calculation, MATLAB software can be used to calculate the hysteresis loop's perimeter, area, maximum height, maximum width, and minimum circumscribed circle area through shape recognition. Specifically, for... Figure 2 The hysteresis loop obtained from the nitrogen adsorption-desorption curve can be as follows: Figure 3 As shown, where, Figure 3 The horizontal axis represents relative pressure, and the vertical axis represents the amount of nitrogen adsorption for the nitrogen adsorption curve and the amount of nitrogen desorption for the nitrogen desorption curve. Figure 3 The 1 in the figure represents the nitrogen adsorption curve. Figure 3 The 2 in the figure represents the nitrogen desorption curve. Figure 3 The 3 in the figure represents a hysteresis loop.

[0054] 140. Determine the permeability range of the shale to be tested based on the hysteresis loop parameters.

[0055] In some implementations, the electronic device can process the hysteresis parameters using a preset algorithm to obtain a multivariate comprehensive classification coefficient for shale reservoir permeability evaluation (hereinafter referred to as the classification coefficient). Different numerical ranges of the classification coefficients correspond to different permeability ranges in advance, and the correspondence between the numerical ranges of different classification coefficients and different permeability ranges can be stored in the electronic device. Therefore, the electronic device can determine the permeability range of the shale to be tested based on the numerical range of the classification coefficient corresponding to the hysteresis parameters.

[0056] As can be seen, in this embodiment, multiple nitrogen adsorption and desorption values ​​are collected from the shale under different relative pressure values; each relative pressure corresponds to one nitrogen adsorption and desorption value; based on the multiple nitrogen adsorption and desorption values, nitrogen adsorption curves and nitrogen desorption curves are generated; the nitrogen adsorption curve characterizes the trend of nitrogen adsorption with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption with increasing relative pressure; based on the nitrogen adsorption and desorption curves, a hysteresis loop is generated in the plane coordinate system where the nitrogen adsorption and desorption curves coexist, and the hysteresis loop parameters are determined; the hysteresis loop parameters are parameters characterizing the shape of the hysteresis loop; based on the hysteresis loop parameters, the permeability range of the shale under test is determined. In other words, by establishing nitrogen adsorption and desorption curves for the shale to be tested, and generating a hysteresis loop based on these curves, the range of permeability of the shale to be tested can be determined quickly and accurately by using the hysteresis loop parameters, since there is a correlation between the hysteresis loop parameters characterizing the shape of the hysteresis loop and the permeability of the shale to be tested.

[0057] Figure 4This is another method for determining the permeability of shale, as illustrated in an exemplary embodiment, such as... Figure 4 As shown, the method for determining the permeability of this shale may include:

[0058] 210. Obtain multiple nitrogen adsorption and desorption values ​​of the shale under different relative pressure values; wherein, each relative pressure corresponds to one nitrogen adsorption and one nitrogen desorption value.

[0059] 220. Based on multiple nitrogen adsorption amounts and multiple nitrogen desorption amounts, generate nitrogen adsorption curves and nitrogen desorption curves; wherein, the nitrogen adsorption curve characterizes the trend of nitrogen adsorption amount with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption amount with increasing relative pressure.

[0060] 230. Based on the nitrogen adsorption curve and the nitrogen desorption curve, generate a hysteresis loop in the plane coordinate system where the nitrogen adsorption curve and the nitrogen desorption curve coexist, and determine the hysteresis loop parameters; the hysteresis loop parameters are parameters that characterize the shape of the hysteresis loop; there are multiple types of hysteresis loop parameters.

[0061] The specific implementation methods of steps 210 to 230 can be referred to steps 110 to 130, and therefore will not be repeated here.

[0062] 240. Using a preset feature selection algorithm, determine the evaluation contribution of each hysteresis parameter among multiple hysteresis parameters to the permeability of the shale under test; wherein, the evaluation contribution characterizes the degree of influence of the hysteresis parameter on the permeability.

[0063] Optionally, the preset feature selection algorithm may include the Relief feature weighting algorithm.

[0064] For example, various hysteresis parameters include the hysteresis area, perimeter, minimum circumscribed circle radius, minimum circumscribed circle area, maximum height, maximum diameter, minimum diameter, area ratio, length ratio, inverse length ratio, shape factor, and area-to-perimeter ratio. Electronic devices can use the Relief feature weighting algorithm to evaluate the contribution of each of these hysteresis parameters to the penetration rate.

[0065] Optionally, when calculating the evaluation contribution of each of the aforementioned hysteresis parameters to permeability, the calculation can be combined with the influence of each hysteresis parameter on some related parameters associated with permeability. For example, the calculated evaluation contribution of the hysteresis parameter to permeability can be used as the first contribution, and the calculated evaluation contribution of the hysteresis parameter to the related parameters can be used as the second contribution. Then, the final evaluation contribution of permeability can be determined by combining the first and second contributions. Optionally, the related parameters may include, but are not limited to, porosity, macropore ratio, mesopore ratio, and micropore ratio.

[0066] 250. Sort the various hysteresis parameters according to the order of their evaluation contribution from largest to smallest to obtain the sorted hysteresis parameters.

[0067] Continuing with the above example, for instance, sorting various hysteresis parameters according to their contribution from largest to smallest, the sorted hysteresis parameters are: maximum hysteresis height l r The minimum circumcircle area of ​​the hysteresis loop is m a The ratio of the hysteresis loop's perimeter to its area, a r Hysteresis loop shape factor f x ...

[0068] 260. Determine the top N hysteresis parameters from the sorted hysteresis parameters, which are the hysteresis parameters to be evaluated; where N is a positive integer greater than or equal to 1.

[0069] Continuing with the example above, for instance, if N is 4, then the electronic device can achieve a maximum hysteresis height of l. r The minimum circumcircle area of ​​the hysteresis loop is m a The ratio of the hysteresis loop's perimeter to its area, a r Hysteresis loop shape factor f x The hysteresis parameters to be evaluated were identified.

[0070] 270. Determine the permeability range of the shale to be tested based on the hysteresis parameters to be evaluated.

[0071] Using the example above, the electronic device can perform calculations on the hysteresis parameters to be evaluated using a preset algorithm to obtain the classification coefficients corresponding to the hysteresis parameters, and determine the permeability range of the shale to be tested based on the numerical range of the classification coefficients corresponding to the hysteresis parameters to be evaluated.

[0072] In this embodiment, feature selection is used to choose a subset of features that are more important for classification from multiple variable relationships, while redundant variables with less importance for evaluation are removed. This improves the accuracy and efficiency of determining the permeability of the shale to be tested.

[0073] In some implementations, step 270 may include the following specific implementations:

[0074] 271. Determine the classification coefficient based on the hysteresis parameters to be evaluated.

[0075] In some implementations, the specific implementation of step 271 may include:

[0076] 2711. Obtain the correlation between each hysteresis parameter to be evaluated and the penetration rate; where the correlation includes positive and negative correlation.

[0077] For example, electronic devices can use software such as SPSS and MATLAB to obtain the linear relationship between various hysteresis parameters and permeability parameters through correlation analysis. As an example, this linear relationship can be as follows: Figure 5 As shown, in Figure 5 This includes multiple correlation coefficients (also called relationship coefficients) characterizing the linear relationship between the hysteresis loop parameter and the permeability parameter. The positive or negative sign of these coefficients indicates the correlation between the hysteresis loop parameter and the permeability parameter. For example, according to... Figure 5 As can be seen, the coefficient of correlation between the hysteresis loop shape factor and permeability is -0.12, therefore, the correlation between the hysteresis loop shape factor and permeability can be determined to be negative. For example, the coefficient of correlation between the minimum circumscribed circle radius of the hysteresis loop and permeability is 0.10, therefore, the correlation between the minimum circumscribed circle radius of the hysteresis loop and permeability can be determined to be positive.

[0078] 2712. Determine the hysteresis parameter that is positively correlated with permeability among various hysteresis parameters to be evaluated, and designate it as the first hysteresis parameter to be evaluated; and calculate the quotient between the first hysteresis parameter to be evaluated and its corresponding calibrated hysteresis parameter to obtain at least one first calculation result.

[0079] 2713. Determine the hysteresis parameter that is negatively correlated with permeability among the various hysteresis parameters to be evaluated, and designate it as the second hysteresis parameter to be evaluated; calculate the quotient between the second hysteresis parameter to be evaluated and its corresponding calibrated hysteresis parameter to obtain at least one second calculation result.

[0080] 2714. Calculate the product between at least one first operation result to obtain the first product value; calculate the product between at least one second operation result to obtain the second product value; and determine the quotient between the first product value and the second product value as the third operation result.

[0081] 2715. The classification coefficient is obtained by performing a logarithmic function on the result of the third operation.

[0082] For example, the hysteresis parameters to be evaluated include: the maximum hysteresis height lr , the minimum circumscribed circle area m of the hysteresis loop a , the ratio a of the perimeter of the hysteresis loop to the area of the hysteresis loop r , the shape factor f of the hysteresis loop x as an example, it is assumed that the correlation between the maximum height l of the hysteresis loop r and the permeability is a positive correlation, the correlation between the minimum circumscribed circle area m of the hysteresis loop a , the ratio a of the perimeter of the hysteresis loop to the area of the hysteresis loop r , the shape factor f of the hysteresis loop x and the permeability is a negative correlation. Then the calculation formula of the classification coefficient can be obtained as follows:

[0083]

[0084] wherein, is the classification coefficient, is the maximum height of the nitrogen adsorption hysteresis loop, is the calibrated maximum height of the hysteresis loop; is the minimum circumscribed circle area of the hysteresis loop, is the calibrated minimum circumscribed circle area of the hysteresis loop; is the ratio of the perimeter of the hysteresis loop to the area of the hysteresis loop, is the calibrated ratio of the perimeter of the hysteresis loop to the area of the hysteresis loop; is the shape factor of the hysteresis loop,

[0085] is the calibrated shape factor of the hysteresis loop.

[0086] 272. Determine the permeability category of the shale to be tested from a plurality of preset permeability categories according to the classification coefficient; wherein the plurality of permeability categories are in one-to-one correspondence with a plurality of preset permeability ranges.

[0087] Exemplarily, for example, the plurality of preset permeability categories may include: Category I, Category II, Category III, and Category IV, wherein Category I: Fk>x1; Category II: x1<Fk <x2; Category III: x2<Fk<x3; Category IV: Fk<x3. Therefore, the permeability category of the shale to be tested can be determined according to the numerical range of the classification coefficient, and then the permeability range can be determined according to the permeability category of the shale to be tested.

[0088] In some embodiments, before step 272, the method may further include:

[0089] Multiple classification coefficient samples and multiple permeability samples of the shale to be tested are obtained, with a one-to-one correspondence between the classification coefficient samples and the permeability samples. The corresponding classification coefficient samples and permeability samples are identified as sample groups, resulting in multiple sample groups. The classification coefficient samples and permeability samples in each sample group are normalized and mapped to the same Cartesian coordinate system, obtaining the coordinate values ​​corresponding to each sample group. A preset clustering algorithm is used to cluster the coordinate values ​​corresponding to each sample group, resulting in multiple clustering results. These multiple clustering results are then identified as preset permeability categories.

[0090] For example, the correspondence between multiple classification coefficient samples and multiple penetration rate samples, i.e., the distribution diagram of multiple sample groups, can be shown as follows: Figure 6 As shown, Figure 6 The horizontal axis in the graph represents the classification coefficient, and the vertical axis represents the penetration rate. Figure 6 Each coordinate point in the diagram can represent a sample group.

[0091] The electronic device can normalize the classification coefficient samples and permeability samples in each of multiple sample groups. Then, it uses the K-Means algorithm to cluster the normalized reservoir comprehensive classification coefficients (i.e., cluster the coordinate values ​​corresponding to each sample group). The classification is performed in an unsupervised mode that minimizes the intra-group sample distance and maximizes the inter-group distance. The normalized results of the calculated comprehensive classification coefficients and permeability are used as the coordinate values ​​of the samples. Euclidean distance is used to measure the intra-cluster distance, and the maximum number of iterations is set to 100,000. The samples (i.e., the aforementioned sample groups) are then subjected to cluster analysis. The K-Means clustering results are as follows: Figure 7 As shown, Figure 7 This is a clustering result diagram of the comprehensive classification coefficients of the samples using the K-Means algorithm, which is the established graded evaluation result of the permeability of the shale reservoir to be tested. Figure 7 The horizontal axis represents the normalized penetration rate, and the vertical axis represents the normalized comprehensive evaluation system (i.e., the normalized classification coefficient). According to... Figure 7 It can be seen that the multiple penetration rate categories can include: Category I, Category II, Category III and Category IV. Among them, the penetration rate range corresponding to Category I is approximately 0-0.2; the penetration rate range corresponding to Category II is approximately 0.3-0.5; the penetration rate range corresponding to Category III is approximately 0.6-0.8; and the penetration rate range corresponding to Category IV is approximately 0.8-1.

[0092] 273. Determine the permeability range corresponding to the permeability category of the shale to be tested, which is the permeability range of the shale to be tested.

[0093] Using the above example, if the permeability category of the shale to be tested is Class II, then the permeability range of the shale to be tested can be determined to be 0.3-0.5. This allows for efficient and accurate determination of the permeability of the shale to be tested.

[0094] In some implementations, after step 270, the method may further include:

[0095] Based on the permeability range, the acquisition equipment is controlled to perform oil and gas extraction processing on the shale reservoir corresponding to the shale being tested.

[0096] For example, electronic equipment can determine the extraction cycle for oil and gas extraction from the shale reservoir corresponding to the tested shale based on the permeability range, and control the acquisition equipment to extract oil and gas from the shale reservoir according to this extraction cycle. Alternatively, electronic equipment can determine the extraction rate for oil and gas extraction from the shale reservoir corresponding to the tested shale based on the permeability range, and control the acquisition equipment to extract oil and gas from the shale reservoir according to this extraction rate. Since the permeability range is precisely related to the structure of the shale reservoir corresponding to the tested shale, controlling the acquisition equipment to extract oil and gas from the shale reservoir according to the permeability range ensures safe and efficient oil and gas extraction from the shale reservoir corresponding to the tested shale. The acquisition equipment is installed at the oil and gas field for oil and gas extraction, and this acquisition equipment can be connected to the aforementioned electronic equipment.

[0097] Figure 8 This is an exemplary embodiment illustrating a shale permeability determination device, such as... Figure 8 As shown, the device 300 may include:

[0098] The acquisition module 310 is used to acquire multiple nitrogen adsorption amounts and multiple nitrogen desorption amounts collected from the shale under different relative pressure values; wherein, each relative pressure corresponds to one nitrogen adsorption amount and one nitrogen desorption amount;

[0099] The curve generation module 320 is used to generate nitrogen adsorption curves and nitrogen desorption curves based on multiple nitrogen adsorption amounts and multiple nitrogen desorption amounts; wherein, the nitrogen adsorption curve characterizes the trend of nitrogen adsorption amount with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption amount with increasing relative pressure.

[0100] Hysteresis loop generation module 330 is used to generate a hysteresis loop in the plane coordinate system where the nitrogen adsorption curve and the nitrogen desorption curve coexist, based on the nitrogen adsorption curve and the nitrogen desorption curve, and to determine the hysteresis loop parameters; the hysteresis loop parameters are parameters that characterize the shape of the hysteresis loop.

[0101] The determination module 340 is used to determine the permeability range of the shale to be tested based on the hysteresis loop parameters.

[0102] In some implementations, there are multiple types of hysteresis parameters. The determining module 340 is specifically used to determine the evaluation contribution of each hysteresis parameter to the permeability of the shale under test using a preset feature selection algorithm. The evaluation contribution characterizes the degree of influence of the hysteresis parameter on permeability. The multiple hysteresis parameters are sorted according to their evaluation contribution from largest to smallest to obtain the sorted hysteresis parameters. The top N hysteresis parameters in the sorted hysteresis parameters are determined as the hysteresis parameters to be evaluated, where N is a positive integer greater than or equal to 1. Based on the hysteresis parameters to be evaluated, the permeability range of the shale under test is determined.

[0103] In some implementations, the feature selection algorithm includes the Relief feature weighting algorithm.

[0104] In some implementations, the determining module 340 is further configured to determine a classification coefficient based on the hysteresis parameters to be evaluated; and, based on the classification coefficient, determine the permeability category of the shale to be tested from a set of preset permeability categories; wherein the multiple permeability categories correspond one-to-one with multiple preset permeability ranges. The permeability range corresponding to the determined permeability category of the shale to be tested is the permeability range of the shale to be tested.

[0105] In some implementations, there are multiple types of hysteresis parameters to be evaluated. Specifically, the determining module 340 is further used to obtain the correlation between each hysteresis parameter to be evaluated and the permeability; wherein the correlation includes positive and negative correlation; determining the hysteresis parameter positively correlated with permeability among the multiple hysteresis parameters to be evaluated as the first hysteresis parameter to be evaluated; and calculating the quotient between the first hysteresis parameter to be evaluated and its corresponding calibration hysteresis parameter to obtain at least one first calculation result; determining the hysteresis parameter negatively correlated with permeability among the multiple hysteresis parameters to be evaluated as the second hysteresis parameter to be evaluated; and calculating the quotient between the second hysteresis parameter to be evaluated and its corresponding calibration hysteresis parameter to obtain at least one second calculation result; calculating the product between at least one first calculation result to obtain a first product value; calculating the product between at least one second calculation result to obtain a second product value; and determining the quotient between the first product value and the second product value as a third calculation result; and processing the third calculation result using a logarithmic function to obtain a classification coefficient.

[0106] In some embodiments, the device 300 further includes:

[0107] The permeability category determination module 340 is used to acquire multiple classification coefficient samples and multiple permeability samples of the shale to be tested, with a one-to-one correspondence between the multiple classification coefficient samples and the multiple permeability samples; determine the corresponding classification coefficient samples and permeability samples as sample groups, resulting in multiple sample groups; normalize the classification coefficient samples and permeability samples in each sample group and map them to the same rectangular coordinate system to obtain the coordinate values ​​corresponding to each sample group; perform clustering processing on the coordinate values ​​corresponding to each sample group using a preset clustering algorithm to obtain multiple clustering results, and determine the multiple clustering results as multiple preset permeability categories.

[0108] In some implementations, the hysteresis parameters include perimeter, area, maximum height, maximum width, and minimum circumscribed circle area.

[0109] In some embodiments, the device 300 further includes a control module for controlling the acquisition equipment to perform oil and gas extraction processing on the shale reservoir corresponding to the shale to be tested, based on the permeability range.

[0110] Figure 9 This is a schematic diagram of the structure of an electronic device according to an exemplary embodiment. The electronic device may be a computer, a server, etc.

[0111] Electronic device 800 may include one or more of the following components: processing component 802, memory 804, power supply component 806, multimedia component 808, audio component 810, input / output (I / O) interface 812, sensor component 814, and communication component 816.

[0112] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0113] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of such data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0114] Power supply component 806 provides power to various components of electronic device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0115] Multimedia component 808 includes a screen that provides an output interface between electronic device 800 and user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When electronic device 800 is in an operating mode, such as a shooting mode or video mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0116] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0117] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0118] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 can detect the on / off state of electronic device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0119] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0120] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0121] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0122] In an exemplary embodiment, a non-transitory computer-readable storage medium is also provided, which, when the instructions in the storage medium are executed by the processor of a terminal device, enables the terminal device to execute the shale permeability determination method of the aforementioned electronic device.

[0123] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0124] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for determining the permeability of shale, characterized in that, include: Multiple nitrogen adsorption and desorption values ​​were collected from the shale under different relative pressure values; each relative pressure corresponds to one nitrogen adsorption and one nitrogen desorption value. Based on the plurality of nitrogen adsorption amounts and the plurality of nitrogen desorption amounts, nitrogen adsorption curves and nitrogen desorption curves are generated; wherein, the nitrogen adsorption curve characterizes the trend of nitrogen adsorption amount with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption amount with increasing relative pressure. Based on the nitrogen adsorption curve and the nitrogen desorption curve, a hysteresis loop is generated in the plane coordinate system where the nitrogen adsorption curve and the nitrogen desorption curve coexist, and the hysteresis loop parameters are determined; the hysteresis loop parameters are parameters characterizing the shape of the hysteresis loop; there are multiple types of hysteresis loop parameters; the hysteresis loop parameters include perimeter, area, maximum height, maximum width, and minimum circumscribed circle area; The evaluation contribution of each hysteresis parameter among various hysteresis parameters to the permeability of the shale under test is determined by a preset feature selection algorithm; wherein the evaluation contribution represents the degree of influence of the hysteresis parameter on the permeability. The various hysteresis parameters are sorted according to their contribution from largest to smallest to obtain the sorted hysteresis parameters; The top N hysteresis parameters among the sorted hysteresis parameters are identified as the hysteresis parameters to be evaluated; where N is a positive integer greater than or equal to 1; and there are multiple types of hysteresis parameters to be evaluated. Obtain the correlation between each of the hysteresis parameters to be evaluated and the penetration rate; wherein the correlation includes positive and negative correlations; Among the various hysteresis parameters to be evaluated, the hysteresis parameter that is positively correlated with the permeability is identified as the first hysteresis parameter to be evaluated; and the quotient between the first hysteresis parameter to be evaluated and its corresponding calibrated hysteresis parameter is calculated to obtain at least one first calculation result. Among the various hysteresis parameters to be evaluated, the hysteresis parameter that is negatively correlated with the permeability is identified as the second hysteresis parameter to be evaluated; and the quotient between the second hysteresis parameter to be evaluated and its corresponding calibrated hysteresis parameter is calculated to obtain at least one second calculation result. Calculate the product between the at least one first operation result to obtain a first product value; calculate the product between the at least one second operation result to obtain a second product value; and determine the quotient between the first product value and the second product value as a third operation result; The classification coefficient is obtained by performing a logarithmic function on the third operation result. Based on the classification coefficient, the permeability category of the shale to be tested is determined from a plurality of preset permeability categories; wherein, the plurality of permeability categories correspond one-to-one with a plurality of preset permeability ranges; The permeability range corresponding to the permeability category of the shale to be tested is determined as the permeability range of the shale to be tested.

2. The method according to claim 1, characterized in that, The feature selection algorithm includes the Relief feature weighting algorithm.

3. The method according to claim 1, characterized in that, The method further includes: Multiple classification coefficient samples and multiple permeability samples of the shale to be tested are obtained, and the multiple classification coefficient samples and multiple permeability samples correspond one-to-one; By identifying corresponding classification coefficient samples and penetration rate samples as sample groups, multiple sample groups are obtained. The classification coefficient samples and penetration rate samples in each of the multiple sample groups are normalized and mapped to the same rectangular coordinate system to obtain the coordinate values ​​corresponding to each sample group. The coordinate values ​​corresponding to each sample group are clustered using a preset clustering algorithm to obtain multiple clustering results, and the multiple clustering results are determined to be the preset multiple penetration rate categories.

4. The method according to any one of claims 1 to 3, characterized in that, After determining the permeability range of the shale to be tested based on the hysteresis parameters, the process further includes: Based on the permeability range, the acquisition equipment is controlled to perform oil and gas extraction processing on the shale reservoir corresponding to the shale to be tested.

5. A device for determining the permeability of shale, comprising: The acquisition module is used to acquire multiple nitrogen adsorption amounts and multiple nitrogen desorption amounts collected from the shale under different relative pressure values; wherein, each relative pressure corresponds to one nitrogen adsorption amount and one nitrogen desorption amount; The curve generation module is used to generate a nitrogen adsorption curve and a nitrogen desorption curve based on the plurality of nitrogen adsorption amounts and the plurality of nitrogen desorption amounts; wherein, the nitrogen adsorption curve characterizes the trend of nitrogen adsorption amount with increasing relative pressure, and the nitrogen desorption curve characterizes the trend of nitrogen desorption amount with increasing relative pressure. The hysteresis loop generation module is used to generate a hysteresis loop in the plane coordinate system where the nitrogen adsorption curve and the nitrogen desorption curve coexist, based on the nitrogen adsorption curve and the nitrogen desorption curve, and to determine the hysteresis loop parameters; the hysteresis loop parameters are parameters characterizing the shape of the hysteresis loop; there are multiple types of hysteresis loop parameters; the hysteresis loop parameters include perimeter, area, maximum height, maximum width, and minimum circumscribed circle area; The determination module is used to determine the evaluation contribution of each of the various hysteresis parameters to the permeability of the shale under test by using a preset feature selection algorithm; wherein the evaluation contribution characterizes the degree of influence of the hysteresis parameter on the permeability. The various hysteresis parameters are sorted according to their contribution from largest to smallest to obtain the sorted hysteresis parameters; The top N hysteresis parameters among the sorted hysteresis parameters are identified as the hysteresis parameters to be evaluated; where N is a positive integer greater than or equal to 1; and there are multiple types of hysteresis parameters to be evaluated. Obtain the correlation between each of the hysteresis parameters to be evaluated and the penetration rate; wherein the correlation includes positive and negative correlations; Among the various hysteresis parameters to be evaluated, the hysteresis parameter that is positively correlated with the permeability is identified as the first hysteresis parameter to be evaluated; and the quotient between the first hysteresis parameter to be evaluated and its corresponding calibrated hysteresis parameter is calculated to obtain at least one first calculation result. Among the various hysteresis parameters to be evaluated, the hysteresis parameter that is negatively correlated with the permeability is identified as the second hysteresis parameter to be evaluated; and the quotient between the second hysteresis parameter to be evaluated and its corresponding calibrated hysteresis parameter is calculated to obtain at least one second calculation result. Calculate the product between the at least one first operation result to obtain a first product value; calculate the product between the at least one second operation result to obtain a second product value; and determine the quotient between the first product value and the second product value as a third operation result; The classification coefficient is obtained by performing a logarithmic function on the third operation result. Based on the classification coefficient, the permeability category of the shale to be tested is determined from a plurality of preset permeability categories; wherein, the plurality of permeability categories correspond one-to-one with a plurality of preset permeability ranges; The permeability range corresponding to the permeability category of the shale to be tested is determined as the permeability range of the shale to be tested.

6. An electronic device, comprising: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 4.

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