A certain clastic rock particle size calculation method, system, medium, device and terminal

Abstract

The present application belongs to the technical field of oil and gas exploration and development, and discloses a specific clastic rock particle size calculation method, system, medium, equipment and terminal. Based on the statistical result of the clastic particle size, the MATCH, OFFSET and TREND functions in Excel are called, the function is relied on to obtain the clastic particle size value corresponding to a specific cumulative weight percentage, used for analyzing the particle size parameters of the sediment, and the position of the obtained point on the cumulative curve can be visually expressed. The analysis result is used for analyzing the hydrodynamic condition and the deposition environment when the clastic particles are deposited, and analyzing the initial porosity of the clastic rock, used for guiding the oil and gas exploration and development. The present application builds a patterned calculation method in Excel, can quickly and accurately obtain the clastic particle size at a certain cumulative weight percentage, and can visually express the position of the corresponding point on the cumulative curve, effectively improving the accuracy and convenience of the clastic rock particle size distribution and characteristic research.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas exploration and development technology, and in particular relates to a method, system, medium, equipment and terminal for calculating the particle size of specific clastic rocks. Background Technology

[0002] Clastic grain size is controlled by factors such as transport medium, transport method, and depositional environment. Therefore, the size and characteristics of clastic grains are good indicators for judging the depositional environment and hydrodynamic conditions. Currently, clastic grain size distribution and characteristics are usually displayed visually using graphs such as grain size distribution histograms, frequency curves, cumulative curves, and probability value cumulative curves. Quantitative analysis can also be performed using grain size parameters, such as average grain size, median grain size, and sorting coefficient. Individual grain size parameters and their combinations can serve as references for judging depositional hydrodynamic conditions and depositional environments, thereby predicting oil reservoir distribution and guiding oil and gas exploration.

[0003] Currently, the main method for calculating the detrital grain size corresponding to a specific cumulative weight percentage is the graphical method. This involves reading the detrital grain size values ​​on the x-axis corresponding to the cumulative weight percentage on the y-axis from a cumulative curve generated by plotting software (such as Origin and Grapher). Examples of detrital grain sizes at cumulative weight percentages of 5%, 16%, 25%, 50%, 75%, 84%, and 95% are given. Grain size parameters, such as mean grain size, median grain size, standard deviation, sorting factor, skewness, and kurtosis, are then calculated using relevant mathematical formulas. Finally, the sedimentary environment is determined based on the grain size parameters of the sandstone and their combinations.

[0004] Most domestic and international scholars calculate clastic rock grain size parameters using the methods proposed by Trask, Fock, and Ward, which requires knowledge of the clastic grain size at certain cumulative weight percentages on the cumulative curve. Currently, graphical methods are commonly used to determine the clastic grain size at these cumulative percentages, i.e., visually observing the clastic grain size values ​​corresponding to specific cumulative weight percentages on the cumulative curves of plotting software (such as Origin and Grapher). The disadvantages of this approach are that it is time-consuming and prone to errors, thus failing to process large amounts of data quickly and accurately. Therefore, a systematic and procedural method for determining the clastic grain size corresponding to a specific cumulative weight percentage is urgently needed.

[0005] Based on the above analysis, the problems and defects of the existing technology are as follows: Currently, the main method for obtaining the detrital particle size corresponding to a specific cumulative weight percentage in the sedimentary rock grain size analysis process is to read the data from the graph, that is, to visually observe the detrital particle size corresponding to a specific cumulative weight percentage from the cumulative curve of the graphing software (such as Origin and Grapher). This process is time-consuming and prone to errors, and therefore cannot process large amounts of data quickly and accurately. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides a method for calculating the particle size of specific clastic rocks, and particularly relates to a method, system, medium, device and terminal for calculating the particle size of clastic rocks corresponding to a specific cumulative weight percentage based on Excel data processing.

[0007] This invention is implemented as follows: a method for calculating the particle size of specific clastic rocks, the method comprising:

[0008] Based on the statistical results of detrital grain size, the MATCH, OFFSET, and TREND functions in Excel are used to obtain the detrital grain size ∮ value corresponding to a specific cumulative weight percentage. This value is used to analyze the grain size parameters of the sediment and to visualize the position of the point with the desired cumulative weight percentage on the cumulative curve. The analysis results are then used to analyze the hydrodynamic conditions and sedimentary environment during detrital particle deposition, thereby guiding oil and gas exploration and development.

[0009] Furthermore, the method for calculating the specific clastic rock grain size includes the following steps:

[0010] Step 1: Perform grain size analysis on the sandstone sample to obtain grain size data and convert the grain size values ​​into ∮ values; classify the clastic grain size according to the ∮ values, calculate the relative percentage content of clastic grains in each grain size class, and start from the coarse grain size to count the cumulative weight percentage data of clastic grains in each grain size class.

[0011] Step 2: Insert three rows of data into Excel, including the location range, the ∮ value range, and the cumulative weight percentage range; based on the cumulative percentage content data corresponding to each particle size debris, draw a scatter plot with smooth lines and data labels in Excel, and the scatter plot is a cumulative curve plot.

[0012] Step 3: Insert two rows of data into Excel, one containing the desired ∮ value and the other containing the given cumulative weight percentage; for the given cumulative weight percentage y... i Perform positioning and find values ​​greater than or equal to y. i The position corresponding to the minimum value; the position is the value within the position range of the first row in step two;

[0013] Step 4: Calculate the cumulative weight percentage y over distance. i The x and y coordinates of the two nearest endpoints; construct a linear equation based on the debris particle size (∮) and corresponding cumulative weight percentage (y) of the two adjacent points, and then, based on the given cumulative weight percentage (y). i Calculate the corresponding debris particle size ∮ i ;

[0014] Step 5, according to the requirements of clastic rock grain size analysis, in step 3, yi Enter the cumulative weight percentage at the respective positions and calculate the corresponding debris particle size ∮ value; add a scatter plot, and draw the cumulative curve and the composite graph formed by the points moving on the cumulative curve in Excel;

[0015] Step Six: Based on the formulas of Fock and Ward, and combined with the ∮ obtained in Step Five... i The median grain size, average grain size, sorting, skewness, and kurtosis are calculated. Based on the calculated grain size parameters, the sedimentary environment of the clastic rocks is determined using the Sahu sedimentary environment discriminant function.

[0016] Furthermore, the formula for converting the particle size value to the ∮ value in step one is: ∮=-log2 D, where D is the diameter of the debris in millimeters.

[0017] In step two, three rows of data are inserted into Excel. The first row is named "Position Range," and in the same row, 1, 2, 3, ..., n are entered, where n represents the number of debris particle size grades plus 1. The second row is named "∮ Value Range," and in the same row, the debris particle size ∮ values ​​are entered, with the range being (∮... n ,…,∮ i ,∮2,∮1), where ∮ i Let be any ∮ value within the statistical interval, ∮ n The first line represents the maximum ∮ value within the statistical interval; the second line is named the cumulative weight percentage range, and the third line contains the cumulative weight percentage corresponding to the ∮ value, with a range of 100%, ..., y. i y2, y1; the second and third rows of data are sorted in descending order.

[0018] Furthermore, in step three, two rows of data are inserted into Excel. The first row is named the desired ∮ value, and the following blank is the required debris particle size ∮. i The second line is named "Given Cumulative Weight Percentage," followed by an empty input field containing the given cumulative weight percentage y. i , including specific values ​​such as 5%, 16% and 25%.

[0019] In Excel, the MATCH function returns the relative position of a lookup value within a referenced cell and takes three arguments. When applying this function to clastic rock grain size analysis, the first argument is the input cumulative weight percentage (y). i The second parameter is the cumulative weight percentage range corresponding to each particle size, which is the cumulative weight percentage range (100%, ..., y) in the third row of step two. i The data range is y1, y2, y1; the third parameter is -1, indicating that the search term is ≥y1. i The minimum value.

[0020] Furthermore, in step four, the OFFSET function is called in Excel. The OFFSET function uses a specified reference as a reference frame and obtains a new reference by a given offset. It has five parameters, representing: the starting point, the number of rows to move up or down, the number of columns to move left or right, the number of rows to return to the reference range, and the number of columns to return to the reference range. When applying this function to clastic rock grain size analysis, the fourth and fifth parameters are omitted. When calculating the x-coordinate of endpoint 1, the first parameter is the range of ∮ values ​​from step two; the second parameter is omitted, indicating it is in the same row as the ∮ value range; the third parameter represents the number of columns to move, using ≥y. i The minimum value corresponds to the position value; here, the OFFSET function returns the x-coordinate of endpoint 1. b When calculating the y-coordinate of endpoint 1, the first parameter is the cumulative weight percentage range, the second parameter is omitted (indicating it's in the same row as the cumulative weight percentage range), and the third parameter indicates the number of columns to move, using ≥y. i The minimum value corresponds to the position value; here, the OFFSET function returns the y-coordinate of endpoint 1. b The x and y coordinates of endpoint 2 can be obtained using the same method (∮). a y a However, when calling the OFFSET function, the value of the third parameter needs to be incremented by 1, indicating that it is less than or equal to y. i The position corresponding to the maximum value.

[0021] Based on the debris particle size ∮ value and the corresponding cumulative weight percentage y value of two adjacent points (∮ a y a ), (∮ b y b Construct a linear equation based on the given cumulative weight percentage y. i Calculate the corresponding debris particle size ∮ i y i Between y a y b Between; the linear equation is: In the formula, ∮ i For the unknown detrital particle size ∮ value, ∮ a The value of the debris particle size ∮ at endpoint 2, ∮ b Let ∮ be the particle size of the debris at endpoint 1, where ∮ b ≥∮ i ≥∮ a ;y a y represents the cumulative weight percentage of endpoint 2. b y represents the cumulative weight percentage of endpoint 1. i It is a given cumulative weight percentage value between two adjacent points, where y b≥y i ≥y a ;

[0022] In Excel, use the TREND function to calculate a given cumulative weight percentage (y). i The corresponding debris particle size ∮ i The TREND function is a linear trend prediction function. Based on the known values ​​of the x and y sequences, a linear regression equation is constructed. Then, based on the constructed equation and the given y values, the corresponding unknown x values ​​are calculated. The TREND function has four parameters. When applied to clastic rock grain size analysis, the first parameter is the known ∮ value of the clastic grain size between two adjacent points. a 、∮ b The region is defined by the first parameter, and the second parameter is the known cumulative weight percentage of two adjacent points (y). a y b The region is specified, and the third parameter is the given y. i The fourth parameter is omitted, and the function returns the required debris particle size (∮). i .

[0023] Furthermore, the cumulative weight percentages in step five include 5%, 16%, 25%, 50%, 75%, 84%, and 95%; a scatter plot is added to the cumulative curve in step two, with the x-coordinate of the points being the ∮ calculated in step five. i The ordinate is the y-axis given in step five. i .

[0024] In step six, based on the formula of Fock and Ward, and combined with the ∮ obtained in step five... i Calculate the following parameters, including the median particle size: M d =∮ 50 Average particle size: Sorting capability: Skewness: Kuroshi:

[0025] Another object of the present invention is to provide a specific clastic rock grain size calculation system applying the aforementioned specific clastic rock grain size calculation method, the specific clastic rock grain size calculation system comprising:

[0026] The cumulative weight percentage acquisition module is used to perform grain size analysis on sandstone samples, acquire grain size data, and convert grain size values ​​into ∮ values; based on the ∮ values, the clastic grain size is classified, the relative percentage content of clastic grains in each grain size class is calculated, and the cumulative weight percentage data corresponding to each grain size class is statistically analyzed starting from the coarse grain size.

[0027] The data insertion module is used to insert three rows of data into Excel, including the location range, the ∮ value range, and the cumulative weight percentage range; based on the cumulative percentage content data corresponding to each particle size debris, a scatter plot with smooth lines and data labels is drawn in Excel, and the scatter plot is a cumulative curve plot.

[0028] The cumulative weight percentage positioning module is used to insert two rows of data into Excel, one containing the desired ∮ value and the other containing the given cumulative weight percentage; for the given cumulative weight percentage y... i Perform positioning and find values ​​greater than or equal to y. i The position corresponding to the minimum value;

[0029] The debris particle size calculation module is used to calculate the cumulative weight percentage y over distance. i The x and y coordinates of the two nearest endpoints; construct a linear equation based on the debris particle size (∮) and corresponding cumulative weight percentage (y) of the two adjacent points, and then, based on the given cumulative weight percentage (y). i Calculate the corresponding debris particle size ∮ i ;

[0030] The clastic grain size calculation module is used to calculate the grain size of clastic rocks according to the requirements of clastic rock grain size analysis in step y. i Enter the cumulative weight percentage at the respective positions and calculate the corresponding debris particle size ∮ value; add a scatter plot, and draw the cumulative curve and the composite graph formed by the points moving on the cumulative curve in Excel;

[0031] The clastic rock sedimentary environment determination module is used to calculate the median, average, sorting, skewness, and kurtosis of clastic rocks based on the formulas of Fock and Ward and the obtained clastic grain size. Based on the calculated grain size parameters, the module combines the Sahu sedimentary environment discrimination function to determine the sedimentary environment of the clastic rocks.

[0032] Another object of the present invention is to provide a computer device including a memory and a processor, the memory storing a computer program, which, when executed by the processor, causes the processor to perform the specific clastic rock particle size calculation method.

[0033] Another object of the present invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the specific clastic rock particle size calculation method.

[0034] Another objective of this invention is to provide an information data processing terminal for implementing the aforementioned specific clastic rock particle size calculation system.

[0035] Based on the above technical solutions and the technical problems solved, please analyze the advantages and positive effects of the technical solution to be protected by this invention from the following aspects:

[0036] First, addressing the technical problems existing in the prior art and the difficulty in solving them, this paper closely analyzes, in conjunction with the technical solution to be protected by this invention and the results and data obtained during the research and development process, how the technical solution of this invention solves the technical problems, and the inventive technical effects brought about by solving these problems. The specific description is as follows:

[0037] This invention provides a method for calculating the clastic grain size corresponding to a specific cumulative weight percentage. Based on statistical results of clastic grain size, it utilizes the MATCH, OFFSET, and TREND functions in Excel to accurately obtain the ∮ value of the clastic grain size corresponding to a specific cumulative weight percentage (e.g., 5%, 16%, 25%). This value is used to analyze the grain size parameters of sediments and to visualize the position of the desired point (the point at the specific cumulative weight percentage) on the cumulative curve. This clastic grain data processing method allows for large-scale, systematic quantitative analysis of clastic grain size parameters, providing a basis for judging sedimentary environments and hydrodynamic conditions, and effectively improving the accuracy and convenience of clastic grain size distribution and characteristic research.

[0038] This invention constructs a standardized calculation method in Excel. This method can quickly and accurately determine the particle size of clastic rocks at a specific cumulative weight percentage, and also visualize the position of the corresponding point on the cumulative curve. The analytical results of this invention can be used to analyze the hydrodynamic conditions and sedimentary environment during clastic particle deposition, and can also be used to analyze the initial porosity of clastic rocks, thereby guiding oil and gas exploration and development.

[0039] Second, considering the technical solution as a whole or from a product perspective, the technical effects and advantages of the technical solution to be protected by this invention are specifically described as follows:

[0040] The method for calculating specific clastic rock particle size provided by this invention can visualize the position of the point corresponding to a specific cumulative weight percentage on the cumulative curve, and accurately obtain the clastic particle size value corresponding to a certain cumulative weight percentage (5%, 16%, 25%, 50%, 75%, 84%, 95%, etc.) on the cumulative curve.

[0041] Third, as supplementary evidence of the inventive step of the claims of this invention, it is also reflected in the following important aspects:

[0042] The technical solution of this invention solves a long-standing but unsolved technical problem: currently, the main method for determining the detrital particle size corresponding to a specific cumulative weight percentage in sedimentary rock grain size analysis is to visually observe the data from a cumulative curve plot in graphing software (such as Origin and Grapher). This method is slow, prone to errors, and therefore cannot process data in batches. Therefore, a quantitative data processing method and technology are urgently needed to determine the detrital particle size corresponding to a specific cumulative weight percentage. This invention, based on Excel, first performs grain size analysis on sandstone samples to obtain grain size data and converts the grain size values ​​to π values; then, based on the π values, the detrital grain size is classified, the relative percentage content of each grain size is calculated, and the cumulative weight percentage data corresponding to each grain size is statistically analyzed starting from the coarse grain size. Finally, the distance from the specific cumulative weight percentage y is determined. i For the two nearest endpoints, a linear equation is constructed based on the debris particle size (∮) values ​​and the corresponding cumulative weight percentage (y) values ​​of the two adjacent endpoints. The given cumulative weight percentage (y) is then calculated based on this linear equation. i The corresponding detrital grain size. This calculation method and technique are relatively objective, less prone to errors, and fast. It can calculate a large number of grain diameters corresponding to a specific cumulative weight percentage, thereby improving the accuracy and speed of obtaining sedimentary rock grain size parameters and facilitating the analysis of sedimentary rock formation environments. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart of a specific clastic rock grain size calculation method provided in an embodiment of the present invention;

[0045] Figure 2 This is a cumulative curve of YN4 36-16 sample provided in an embodiment of the present invention;

[0046] Figure 3 This is a composite image of the cumulative curve of sample YN4 36-16 and the location of a certain point provided in the embodiment of the present invention;

[0047] Figure 4 This is a flowchart of the process for obtaining the particle size ∮ value of debris corresponding to a specific cumulative weight percentage value of YN4 36-16 sample, provided in an embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0049] To address the problems existing in the prior art, the present invention provides a method, system, medium, device and terminal for calculating specific clastic rock particle size. The present invention will be described in detail below with reference to the accompanying drawings.

[0050] I. Explanation and Description of Embodiments. To enable those skilled in the art to fully understand how the present invention is specifically implemented, this section provides an explanation and description of the embodiments that expand upon the technical solutions of the claims.

[0051] like Figure 1 As shown, the specific clastic rock grain size calculation method provided in this embodiment of the invention includes the following steps:

[0052] S101, perform grain size analysis on sandstone samples, obtain grain size data, and convert grain size values ​​into ∮ values; classify clastic grains according to ∮ values, calculate the relative percentage content of clastic grains in each grain size class, and start from the coarse grain size class to count the cumulative weight percentage data of clastic grains in each grain size class.

[0053] S102, insert three rows of data into Excel, including the position range, the ∮ value range, and the cumulative weight percentage range; based on the cumulative percentage content data corresponding to each particle size debris, draw a scatter plot with smooth lines and data labels in Excel, and the scatter plot is a cumulative curve plot.

[0054] S103, insert two rows of data into Excel, one containing the desired ∮ value and the other containing the given cumulative weight percentage; for the given cumulative weight percentage y... i Perform positioning and find values ​​greater than or equal to y. i The position corresponding to the minimum value; where the position is the value within the position range described in the first row of S102;

[0055] S104, calculate the cumulative weight percentage y over distance. i The x and y coordinates of the two nearest endpoints; construct a linear equation based on the debris particle size (∮) and corresponding cumulative weight percentage (y) of the two adjacent points, and then, based on the given cumulative weight percentage (y). i Calculate the corresponding debris particle size;

[0056] S105, according to the requirements of clastic rock grain size analysis, in S103 y i Enter the cumulative weight percentage at each location and calculate the corresponding debris particle size (∮) value for that cumulative weight percentage; add a scatter plot to the cumulative curve in S102, where the ordinate of each point is the given cumulative weight percentage (y).i The x-axis is y i The corresponding debris diameter values ​​ultimately form a composite chart consisting of the cumulative curve and the points moving on the cumulative curve;

[0057] S106: Based on the formula of Fock and Ward, and combined with the clastic grain size obtained from S105, the median grain size, average grain size, sorting, skewness, and kurtosis are calculated. Based on the calculated grain size parameter characteristics, the sedimentary environment of the clastic rocks is determined by combining the Sahu sedimentary environment discriminant function.

[0058] As a preferred embodiment, the method for calculating the specific clastic rock grain size provided by this invention specifically includes the following steps:

[0059] (1) Perform grain size analysis on sandstone samples to obtain grain size data, and convert the grain size value into ∮ value according to the formula: ∮=-log2 D, where D is the diameter of the debris in millimeters.

[0060] (2) According to the ∮ value in step (1), the particle size of the debris is classified, the relative percentage content of debris in each particle size is calculated, and the cumulative weight percentage of each particle size is calculated starting from the coarse particle size.

[0061] (3) Insert three rows of data into Excel. The first row is named "Location Range". Then, in the same row, enter 1, 2, 3, ..., n, where n represents the number of detritus particle size grades plus 1. The second row is named "∮Value Range". Then, in the same row, enter the detritus particle size ∮ values, with a range of (∮... n ,…,∮ i ,∮2,∮1), where ∮ i Let be any ∮ value within the statistical interval, ∮ n The first line represents the maximum ∮ value within the statistical interval; the third line is named "Cumulative Weight Percentage Range," followed by the cumulative weight percentage corresponding to the ∮ value on the same line, with a range of 100%, ..., y. i y2, y1. The second and third rows of data are sorted in descending order.

[0062] (4) Based on the cumulative percentage content data of each particle size debris in step (2), draw a scatter plot with smooth lines and data labels in Excel. This plot is the cumulative curve.

[0063] (5) Insert two rows of data into Excel. The first row is named "Desired Value", and the second row is the particle size of the debris to be calculated. i The second line is named "Given Cumulative Weight Percentage", followed by an empty input field containing the given cumulative weight percentage y. i For example, 5%, 16%, 25%, etc.

[0064] (6) For a given cumulative weight percentage yi Perform positioning and find values ​​greater than or equal to y. i The position corresponding to the minimum value is the specific value in the "Position Range" of the first row in step (3). To achieve this, the MATCH function is called in Excel. This function returns the relative position of the lookup value in the referenced cell and has three parameters. When this function is applied to clastic rock grain size analysis, the first parameter is the input cumulative weight percentage y. i The second parameter is the cumulative weight percentage range corresponding to each particle size, which is the "cumulative weight percentage range" in the third row of step (3) (100%, ..., y). i The data range is y1, y2, y1), and the third parameter is -1, meaning it searches for values ​​≥ y2. i The minimum value.

[0065] (7) Calculate the cumulative weight percentage y over distance i The x and y coordinates of the two nearest endpoints need to be obtained by calling the OFFSET function in Excel. The OFFSET function uses a specified reference as a reference and obtains a new reference by a given offset. It has five parameters, which represent: the starting point, the number of rows to move up or down, the number of columns to move left or right, the number of rows to return to the reference area, and the number of columns to return to the reference area. When applying this function to the analysis of clastic rock grain size, the fourth and fifth parameters can be omitted. When calculating the x-coordinate of endpoint 1, the first parameter (starting point) is the "∮ value range" in step (3), the second parameter is omitted, that is, it means that it is in the same row as the "∮ value range", and the third parameter represents the number of columns to move. At this time, greater than or equal to y is used. i The minimum value corresponds to the position value, which is the value returned in step (6). Here, the OFFSET function returns the x-coordinate of endpoint 1. b When calculating the y-coordinate of endpoint 1, the first parameter (starting point) is the "cumulative weight percentage range," the second parameter is omitted (meaning it's in the same row as the "cumulative weight percentage range"), and the third parameter indicates the column number to move. In this case, a value greater than or equal to y is also used. i The minimum value corresponds to the position value; here, the OFFSET function returns the y-coordinate of endpoint 1. b The x and y coordinates of endpoint 2 can be obtained using the same method (∮). a y a However, there's a slight difference when calling the OFFSET function: the third parameter is incremented by 1 to indicate that it's less than or equal to y. i The position corresponding to the maximum value.

[0066] (8) Based on the debris particle size ∮ value and the corresponding cumulative weight percentage y value of two adjacent points (∮... a y a ), (∮b y b Construct a linear equation to determine the cumulative weight percentage y. i (y i Between y a y b Calculate the corresponding debris particle size (between) ∮ i The specific linear equation is as follows: The ∮ in the formula i For the unknown detrital particle size ∮ value, ∮ a The value of the debris particle size ∮ at endpoint 2, ∮ b Let ∮ be the particle size of the debris at endpoint 1, where ∮ b ≥∮ i ≥∮ a y a y represents the cumulative weight percentage of endpoint 2. b y represents the cumulative weight percentage of endpoint 1. i It is a given cumulative weight percentage value between two adjacent points, where y b ≥y i ≥y a The requirement is to obtain a given cumulative weight percentage y. i The corresponding debris particle size ∮ i This requires calling the TREND function in Excel. This function is a linear trend prediction function. Based on known x-series and y-series values, it constructs a linear regression equation, and then calculates the corresponding unknown x-values ​​based on the constructed equation and the given y-values. This function has four parameters. When applied to clastic rock grain size analysis, the first parameter is the known ∮ value of the clastic grain size between two adjacent points (∮...). a 、∮ b The region is defined by the first parameter, and the second parameter is the known cumulative weight percentage of two adjacent points (y). a y b The region is specified, and the third parameter is the given y. i The fourth parameter is omitted; the function returns the required debris particle size (∮). i .

[0067] (9) According to the requirements of clastic rock grain size analysis, in step (5) y i At the specified positions, input the cumulative weight percentages of 5%, 16%, 25%, 50%, 75%, 84%, and 95%, respectively, and calculate the corresponding particle size ∮ values ​​of these cumulative weight percentages according to the method in step (8).

[0068] (10) Add a scatter plot to the cumulative curve (point-line graph) in step (4), where the x-coordinate of the point is the x-coordinate calculated in step (9). i The ordinate is the y-axis given in step (9).i At this point, Excel displays a composite graph consisting of a cumulative curve and points moving along the cumulative curve.

[0069] (11) Based on the formula of Fock and Ward, combined with the result of step (9), the ∮ i Calculate the following parameters, including the median particle size: M d =∮ 50 Average particle size: Sorting capability: Skewness: Kuroshi:

[0070] (12) Based on the grain size parameter characteristics calculated in step (11), the sedimentary environment of the clastic rocks is determined by combining the Sahu sedimentary environment discrimination function.

[0071] The specific clastic rock grain size calculation system provided in this embodiment of the invention includes:

[0072] The cumulative weight percentage acquisition module is used to perform grain size analysis on sandstone samples, acquire grain size data, and convert grain size values ​​into ∮ values; based on the ∮ values, the clastic grain size is classified, the relative percentage content of clastic grains in each grain size class is calculated, and the cumulative weight percentage data corresponding to each grain size class is statistically analyzed starting from the coarse grain size.

[0073] The data insertion module is used to insert three rows of data into Excel, including the location range, the ∮ value range, and the cumulative weight percentage range; based on the cumulative percentage content data corresponding to each particle size debris, a scatter plot with smooth lines and data labels is drawn in Excel, and the scatter plot is a cumulative curve plot.

[0074] The cumulative weight percentage positioning module is used to insert two rows of data into Excel, one containing the desired ∮ value and the other containing the given cumulative weight percentage; for the given cumulative weight percentage y... i Perform positioning and find values ​​greater than or equal to y. i The position corresponding to the minimum value;

[0075] The debris particle size calculation module is used to calculate the cumulative weight percentage y over distance. i The x and y coordinates of the two nearest endpoints; construct a linear equation based on the debris particle size (∮) and corresponding cumulative weight percentage (y) of the two adjacent points, and then, based on the given cumulative weight percentage (y). i Calculate the corresponding debris particle size ∮ i ;

[0076] The clastic grain size calculation module is used to calculate the grain size of clastic rocks according to the requirements of clastic rock grain size analysis in step y. iEnter the cumulative weight percentage at the respective positions and calculate the corresponding debris particle size ∮ value; add a scatter plot, and draw the cumulative curve and the composite graph formed by the points moving on the cumulative curve in Excel;

[0077] The clastic rock sedimentary environment determination module is used to calculate the median, average, sorting, skewness, and kurtosis of clastic rocks based on the formulas of Fock and Ward and the obtained clastic grain size. Based on the calculated grain size parameters, the module combines the Sahu sedimentary environment discrimination function to determine the sedimentary environment of the clastic rocks.

[0078] II. Application Examples. To demonstrate the inventiveness and technical value of the technical solution of this invention, this section provides application examples of the technical solution of the claims on specific products or related technologies.

[0079] This invention focuses on the Lower Jurassic Ahe Formation sandstone (sample number YN4 36-16) at a depth of 4647.7m in the Yinan 4 well, located in the Yiqikelike tectonic belt of the eastern Kuqa Depression in the Tarim Basin. Excel is used to calculate the given cumulative weight percentage y. i The corresponding detrital particle size (∮) value is used to determine the grain size parameter and the deposition environment. Furthermore, an accumulation curve and the specific locations (∮) of points on the accumulation curve representing a given cumulative weight percentage are plotted in Excel. i y i The specific steps are as follows:

[0080] (1) Count the diameter of the debris particles under a microscope. There should be no less than 300 debris particles counted. Convert the debris diameter to ∮ value. The formula is ∮=-log2D, where D is the debris diameter in millimeters. The data is shown in Table 1.

[0081] Table 1. Particle size of YN4 36-16 sample debris

[0082]

[0083]

[0084]

[0085] (2) Based on the sandstone clast particle size ∮ value calculated in the previous step, the clast particles are classified into different sizes. The relative percentage content of clast particles in each size size is calculated, and the cumulative weight percentage of each size size is calculated starting from the coarse size size. The calculation results are shown in Table 2.

[0086] Table 2. Weight percentage and cumulative weight percentage for each particle size range

[0087] -0.50～-0.25 3 0.99％ 0.99％ -0.25～0.00 1 0.33％ 1.32％ 0.00～0.25 9 2.97％ 4.29％ 0.25～0.50 22 7.26％ 11.55％ 0.50～0.75 49 16.17％ 27.72％ 0.75～1.00 66 21.78％ 49.50％ 1.00～1.25 49 16.17％ 65.68％ 1.25～1.50 40 13.20％ 78.88％ 1.50～1.75 30 9.90％ 88.78％ 1.75～2.00 16 5.28％ 94.06％ 2.00～2.25 12 3.96％ 98.02％ 2.25～2.50 4 1.32％ 99.34％ 2.50～2.75 1 0.33％ 99.67％ 2.75～3.00 1 0.33％ 100.00％ 3.00～3.25 0 0.00％ 100.00％

[0088] (3) Insert three rows of data into Excel. The first row is named "Location Range", and then enter 1, 2, 3, ..., 16 in the same row. The second row is named "∮ Value Range", and then enter the ∮ values ​​of the debris particle size in the same row. The third row is named "Cumulative Weight Percentage Range", and then enter the cumulative weight percentage corresponding to the ∮ value in the same row. Sort the second and third rows of data in descending order, as shown in Table 3.

[0089] Table 3. Cumulative weight percentage and corresponding location values ​​for each debris particle size (∮).

[0090]

[0091]

[0092] (4) Based on the cumulative percentage content data corresponding to each particle size of debris, plot a scatter plot with smooth lines and data labels in Excel. This plot is the cumulative curve plot, as shown below. Figure 2 As shown.

[0093] (5) Insert two rows of data into Excel. The first row is named "Desired Value", and the second row is the particle size of the debris to be calculated. i The second line is named "Given Cumulative Weight Percentage", followed by an empty input field containing the given cumulative weight percentage y. i For example, 5%, 16%, 25%, etc., as shown in Table 4.

[0094] Table 4 Given cumulative weight percentage y i The value corresponds to the particle size ∮ value of the debris.

[0095] Given cumulative weight percentage Yield values ​​(e.g., 5%, 16%, 25%, etc.)

[0096] (6) For a given cumulative weight percentage y i To locate, that is, to find values ​​greater than or equal to y. i The minimum value corresponds to the position in the referenced cell. To achieve this, the MATCH function is called in Excel. This function returns the relative position of the lookup value in the referenced cell. It has three parameters, the first of which is the entered cumulative weight percentage y. i The second parameter is the cumulative weight percentage range corresponding to each particle size, which is the data range of "cumulative weight percentage range" (100%, 100%, 99.67%, ..., 0.99%, 0.00%) in the third row of step (3). The third parameter is -1, that is, to find ≥y i The minimum value. Taking a cumulative weight percentage of 5% as an example, the minimum value of the cumulative probability range greater than or equal to 5% is 11.55%, and the position corresponding to 11.55% is 12.

[0097] (7) Calculate the cumulative weight percentage y over distance i To find the x and y coordinates of the two nearest endpoints, you need to use the OFFSET function in Excel. When calculating the x-coordinate of endpoint 1, the first parameter (starting point) is the "∮ value range", the second parameter is omitted (meaning it's in the same row as the "∮ value range"), and the third parameter indicates the column number to move to. In this case, a value greater than or equal to y is used. i The minimum value corresponds to the position value; here, the OFFSET function returns the x-coordinate of endpoint 1. b When calculating the y-coordinate of endpoint 1, the first parameter (starting point) is the "cumulative weight percentage range," the second parameter is omitted (meaning it's in the same row as the "cumulative weight percentage range"), and the third parameter indicates the column number to move. In this case, a value greater than or equal to y is also used. i The minimum value corresponds to the position value; here, the OFFSET function returns the y-coordinate of endpoint 1. b The x and y coordinates of endpoint 2 can be obtained using the same method (∮). a y a However, there's a slight difference when calling the OFFSET function: the third parameter is incremented by 1 to indicate that it's less than or equal to y. i The position corresponding to the maximum value. Taking a cumulative weight percentage of 5% as an example, the two endpoints closest to 5% within the statistical probability cumulative percentage interval are: endpoint 1 (0.50, 11.55%) and endpoint 2 (0.25, 4.29%).

[0098] (8) Based on the debris particle size ∮ value and the corresponding cumulative weight percentage y value of two adjacent points (∮... a y a ), (∮ b y b Construct a linear equation to determine the cumulative weight percentage y. i (y i Between y a y b Calculate the corresponding debris particle size (between) ∮ i The value, specifically the linear equation, is: The ∮ in the formula i For the unknown detrital particle size ∮ value, ∮ a The value of the debris particle size ∮ at endpoint 2, ∮ b Let ∮ be the particle size of the debris at endpoint 1, where ∮ b ≥∮ i ≥∮ a y a y represents the cumulative weight percentage of endpoint 2. b y represents the cumulative weight percentage of endpoint 1. iIt is a given cumulative weight percentage value between two adjacent points, where y b ≥y i ≥y a Given the cumulative weight percentage y, the following is required. i The corresponding debris particle size ∮ value needs to be obtained by calling the TREND function in Excel. The first parameter of this function is the known debris particle size ∮ value between two adjacent points (∮). a 、∮ b The region is defined by the first parameter, and the second parameter is the known cumulative weight percentage of two adjacent points (y). a y b The region is specified, and the third parameter is the given y. i The fourth parameter is omitted, and the function returns the requested ∮ value. i Here, taking a cumulative weight percentage of 5% as an example, the ∮ values ​​of the two endpoints adjacent to 5% are 0.50 and 0.25, respectively, resulting in cumulative weight percentages of 11.55% and 4.29%. The calculation format is shown in Table 5. (The last part, "∮," appears to be incomplete and requires further context.) i The TREND function is called at the location to calculate ∮ i It is 0.27.

[0099] Table 5. Debris particle size ∮ values ​​corresponding to 5% of cumulative weight.

[0100] Given cumulative weight percentage 5％

[0101] (9) According to the requirements of clastic rock grain size analysis, in y i Enter the cumulative weight percentages of 5%, 16%, 25%, 50%, 75%, 84%, and 95% at the specified positions, and calculate the corresponding particle size values ​​(∮) for these cumulative weight percentages, which are 0.27, 0.57, 0.71, 1.01, 1.43, 1.63, and 2.06, respectively.

[0102] (10) Add a scatter plot to the cumulative curve (point-line graph), where the x-coordinate of each point is the calculated x-coordinate. i The vertical axis is a given y i At this point, in Excel, a composite chart consisting of a cumulative curve and points moving along the cumulative curve is drawn, such as... Figure 3 As shown.

[0103] (11) Calculate the following parameters and the median particle size according to the formulas of Fock and Ward: M d =∮ 50 =1.01; Average particle size: Sorting capability: Skewness: Kuroshi:

[0104] (12) Based on the grain size parameter characteristics calculated in step (10), and combined with the Sahu sedimentary environment discrimination function, it is determined that the sedimentary environment of the sandstone is deltaic river sedimentation.

[0105] (13) The flowchart for obtaining the particle size ∮ value of debris in Excel is as follows: Figure 4 As shown.

[0106] III. Evidence of the Relevant Effects of the Embodiments. The embodiments of the present invention have achieved some positive effects during research and development or use, and indeed possess significant advantages compared to existing technologies. The following description, in conjunction with data, charts, and other materials from the experimental process, illustrates these advantages.

[0107] Based on the relevant research on the Lower Jurassic Ahe Formation sandstone (sample number YN4 36-16) at a depth of 4647.7m in the Yinan 4 well of the Yiqikelike tectonic belt in the eastern part of the Kuqa Depression in the Tarim Basin, it can be found that when analyzing the clastic grain size values ​​corresponding to different cumulative weight percentages, the calculation is mainly performed using function calls. Therefore, the processing speed and accuracy are greatly increased, making the analysis of clastic rock grain size parameters more accurate and faster, and significantly improving the accuracy and speed of sedimentary environment determination.

[0108] It should be noted that embodiments of the present invention can be implemented using hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented using hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or using software executed by various types of processors, or using a combination of the above-described hardware circuitry and software, such as firmware.

[0109] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for calculating the grain size of a specific clastic rock, characterized in that, The specific clastic rock grain size calculation method includes: Based on the statistical results of debris particle size, the MATCH, OFFSET, and TREND functions in Excel are used to obtain the debris particle size corresponding to a specific cumulative weight percentage. The values ​​are used to analyze the grain size parameters of sediments and visualize the position of the point on the cumulative curve representing a specific cumulative weight percentage. The analysis results are used to analyze the hydrodynamic conditions and sedimentary environment during clastic particle deposition, and to analyze the initial porosity of clastic rocks, thereby guiding oil and gas exploration and development. The method for calculating the specific clastic rock grain size includes the following steps: Step 1: Perform grain size analysis on the sandstone sample to obtain grain size data, and convert the grain size values ​​to... Value; according to the stated The particle size of the debris is classified, the relative percentage content of debris in each particle size is calculated, and the cumulative weight percentage data of debris in each particle size is calculated starting from the coarse particle size. Step 2, insert position ranges in Excel respectively. The data consists of three rows, including the value range and the cumulative weight percentage range; based on the cumulative percentage content data corresponding to each particle size of debris, a scatter plot with smooth lines and data labels is plotted in Excel, and the scatter plot is a cumulative curve. Step 3: Insert the desired values ​​into Excel. Two rows of data, including the value and the given cumulative weight percentage; for the given cumulative weight percentage Perform positioning and find values ​​greater than or equal to. The position corresponding to the minimum value; the position is the value within the position range of the first row in step two; Step 4: Calculate the cumulative weight percentage over distance. The x and y coordinates of the two nearest endpoints; based on the particle size of the debris at the two adjacent points. Value and corresponding cumulative weight percentage The values ​​construct a linear equation based on the given cumulative weight percentage. Calculate the corresponding debris particle size ; Step 5, according to the requirements of clastic rock grain size analysis, in step 3 Enter the cumulative weight percentage at each location and calculate the corresponding particle size of the debris. Values; Add a scatter plot to draw a cumulative curve and a composite chart of points moving along the cumulative curve in Excel; Step Six: Based on the formulas of Fock and Ward, combined with the results obtained in Step Five... The median grain size, average grain size, sorting, skewness, and kurtosis are calculated. Based on the calculated grain size parameters, the sedimentary environment of the clastic rocks is determined using the Sahu sedimentary environment discriminant function. In step one, the particle size value is converted to... The formula for the value is: Where D is the diameter of the debris, in millimeters; In step two, three rows of data are inserted into Excel. The first row is named the location range, and the data is entered in the same row. This represents the number of debris particle size classifications plus 1; the name in the second line is... Value range, enter the particle size of the debris on the same line. Values, range of ,in For any within the statistical interval value, The largest within the statistical interval Value; the third line name is the cumulative weight percentage range, entered on the same line as... The value corresponds to the cumulative weight percentage, and the range is: The second and third rows of data are sorted in descending order.

2. The method for calculating the specific clastic rock grain size as described in claim 1, characterized in that, In step three, two rows of data are inserted into Excel, with the first row named "as required". The value is followed by a blank space to determine the particle size of the debris. ; The second line is named "Given Cumulative Weight Percentage," followed by an empty field to input the given cumulative weight percentage. These include 5%, 16%, and 25%; In Excel, the MATCH function returns the relative position of a lookup value within a referenced cell and takes three arguments. When applying this function to clastic rock grain size analysis, the first argument is the input cumulative weight percentage. The second parameter is the cumulative weight percentage range corresponding to each particle size, which is the cumulative weight percentage range in the third row of step two. Data area; The third parameter is -1, indicating a search. The minimum value.

3. The method for calculating the specific clastic rock grain size as described in claim 1, characterized in that, In step four, the OFFSET function is called in Excel. The OFFSET function uses a specified reference as a reference frame and obtains a new reference by a given offset. It has five parameters, representing: the starting point, the number of rows to move up or down, the number of columns to move left or right, the number of rows to return to the reference area, and the number of columns to return to the reference area. When applying this function to clastic rock grain size analysis, the fourth and fifth parameters are omitted. When calculating the x-coordinate of endpoint 1, the first parameter is the one from step two. Value range, the second parameter is omitted, indicating a sum. The values ​​are within the same row, and the third parameter indicates the number of columns to move, using values ​​greater than or equal to... The minimum value corresponds to the position value; here, the OFFSET function returns the x-coordinate of endpoint 1. When calculating the ordinate of endpoint 1, the first parameter is the cumulative weight percentage range, the second parameter is omitted (indicating it's in the same row as the cumulative weight percentage range), and the third parameter indicates the column number to move, using a value greater than or equal to... The minimum value corresponds to the position value; here, the OFFSET function returns the ordinate of endpoint 1. The x and y coordinates of endpoint 2 can be obtained using the same method. When calling the OFFSET function, the value of the third parameter is incremented by 1, indicating that it is less than or equal to... The position corresponding to the maximum value; Based on the particle size of the debris at two adjacent points Value and corresponding cumulative weight percentage value Construct a linear equation based on a given cumulative weight percentage. Calculate the corresponding debris particle size Between Between; the linear equation is: In the formula, For unknown debris particle size value, The particle size of the debris at endpoint 2 value, The particle size of the debris at endpoint 1 Value, of which This represents the cumulative weight percentage of endpoint 2. This represents the cumulative weight percentage of endpoint 1. It is a given cumulative weight percentage value between two adjacent points, where ; In Excel, use the TREND function to calculate a given cumulative weight percentage. Corresponding debris particle size The TREND function is a linear trend prediction function. Based on the known values ​​of the x and y sequences, it constructs a linear regression equation. Then, based on the constructed equation and the given y values, it calculates the corresponding unknown x values. The TREND function has four parameters. When applied to clastic rock grain size analysis, the first parameter is the known grain size of two adjacent points. value The region is defined by the first parameter, which is the known cumulative weight percentage between two adjacent points. The location, the third parameter is given. The fourth parameter is omitted, and the function returns the required particle size of the debris. .

4. The method for calculating the specific clastic rock grain size as described in claim 1, characterized in that, The cumulative weight percentages in step five include 5%, 16%, 25%, 50%, 75%, 84%, and 95%; a scatter plot is added to the cumulative curve in step two, with the x-axis of the points calculated in step five. The ordinate is the value given in step five. ; In step six, based on the formula of Fock and Ward, combined with the result obtained in step five... Calculate the following parameters, including the median particle size: Average particle size: Sorting ability: Skewness: kurtosis: .

5. A specific clastic rock grain size calculation system applying the specific clastic rock grain size calculation method as described in any one of claims 1 to 4, characterized in that, The specific clastic rock grain size calculation system includes: The cumulative weight percentage acquisition module is used for grain size analysis of sandstone samples, acquiring grain size data, and converting the grain size values ​​to... Value; according to The particle size of the debris is classified, the relative percentage content of debris in each particle size is calculated, and the cumulative weight percentage data of debris in each particle size is calculated starting from the coarse particle size. The data insertion module is used to insert position ranges in Excel. The data consists of three rows, including the value range and the cumulative weight percentage range; based on the cumulative percentage content data corresponding to each particle size of debris, a scatter plot with smooth lines and data labels is plotted in Excel, and the scatter plot is a cumulative curve. The cumulative weight percentage positioning module is used to insert the desired values ​​into Excel. Two rows of data, including the value and the given cumulative weight percentage; for the given cumulative weight percentage Perform positioning and find values ​​greater than or equal to. The position corresponding to the minimum value; The debris particle size calculation module is used to calculate the cumulative weight percentage over distance. The x and y coordinates of the two nearest endpoints; based on the particle size of the debris at the two adjacent points. Construct a linear equation based on the given cumulative weight percentage and the corresponding cumulative weight percentage y-value. Calculate the corresponding debris particle size ; The clastic grain size calculation module is used to calculate the grain size of clastic rocks according to the requirements of clastic rock grain size analysis. Enter the cumulative weight percentage at each location and calculate the corresponding particle size of the debris. Values; Add a scatter plot to draw a cumulative curve and a composite chart of points moving along the cumulative curve in Excel; The clastic rock sedimentary environment determination module is used to calculate the median, average, sorting, skewness, and kurtosis of clastic rocks based on the formulas of Fock and Ward and the obtained clastic grain size. Based on the calculated grain size parameters, the module combines the Sahu sedimentary environment discrimination function to determine the sedimentary environment of the clastic rocks.

6. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the specific clastic rock grain size calculation method as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the specific clastic rock grain size calculation method as described in any one of claims 1 to 4.

8. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the specific clastic rock particle size calculation system as described in claim 5.

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