A data analysis method for fluid density and related equipment

Abstract

The present application discloses a fluid density data analysis method and related equipment, which relate to the field of surveying technology. In the process of fluid density data analysis, the data credibility can be reflected and the reference value of the data analysis results can be improved. The fluid density data analysis method includes: performing logging operations based on a cable formation pressure test method to obtain depth data and pressure data; calculating a confidence value based on the depth data and the pressure data; comparing the confidence value with a confidence threshold; if the confidence value is greater than or equal to the confidence threshold, obtaining fluid density data based on the depth data and the pressure data; and drawing a fluid density chart based on the depth data, the pressure data, and the fluid density data.

Description

Technical Field

[0001] The present application relates to the field of surveying technology, and in particular to a fluid density data analysis method and related equipment. Background Art

[0002] Wireline formation pressure testing is a crucial logging method in oil and gas exploration and development, crucial for early oilfield evaluation and dynamic monitoring. One application of wireline formation pressure testing is to plot formation pressure profiles, determine fluid density, and identify fluid types. However, calculating fluid density using multi-point linear regression not only loses significant information, but also renders the calculated results, displayed as the slope of the line, unclear, particularly for distinguishing between oil and water. Fluid density charts address the shortcomings of multi-point linear regression in pressure profile interpretation, allowing the fluid density data axis to be incorporated into the chart, allowing fluid type identification.

[0003] However, the application of fluid density maps lacks a factor for interpreting confidence. Confidence can be defined as the trustworthiness of the logging data, reflecting the quality of the data. Therefore, existing fluid density data analysis methods struggle to reflect the trustworthiness of the data, reducing the relevance of the analysis results. Summary of the Invention

[0004] The embodiments of the present application provide a fluid density data analysis method and related equipment, which can reflect the credibility of data and improve the reference value of data analysis results during the fluid density data analysis process.

[0005] According to a first aspect of an embodiment of the present application, a method for analyzing fluid density data is provided, comprising:

[0006] Based on the wireline formation pressure testing method, perform logging operations to obtain depth data and pressure data;

[0007] Calculating a confidence value based on the depth data and the pressure data;

[0008] comparing the confidence value with a confidence threshold;

[0009] If the confidence value is greater than or equal to the confidence threshold, obtaining fluid density data according to the depth data and the pressure data;

[0010] A fluid density map is drawn according to the depth data, the pressure data, and the fluid density data.

[0011] In some embodiments, the method further comprises:

[0012] If the confidence value is less than the confidence threshold, checking whether there is abnormal data in the depth data and the pressure data;

[0013] If the abnormal data exists in the depth data and the pressure data, the abnormal data is removed and a corrected confidence value is obtained;

[0014] The modified confidence value is compared with the confidence threshold.

[0015] In some embodiments, the method further comprises:

[0016] If the revised confidence value is less than the confidence threshold, the logging operation is re-executed.

[0017] In some embodiments, the method further comprises:

[0018] According to the fluid density plate, an analysis result of the fluid type is obtained.

[0019] In some embodiments, drawing a fluid density map based on the depth data, the pressure data, and the fluid density data includes:

[0020] Drawing the fluid density map according to the depth data, the pressure data and the fluid density data;

[0021] The sinusoidal curve lines in the fluid density map are removed to simplify the graphics in the fluid density map.

[0022] In some embodiments, drawing a fluid density map based on the depth data, the pressure data, and the fluid density data further includes:

[0023] Adding a one-dimensional concentration curve of density points to the fluid density plate;

[0024] A two-dimensional density contour curve of the density point is added to the fluid density map, wherein different areas surrounded by the two-dimensional density contour curves are marked with different colors.

[0025] In some embodiments, obtaining a confidence value based on the depth data and the pressure data includes:

[0026] The confidence value is calculated according to the depth data and the pressure data according to the following formula:

[0027]

[0028]

[0029] Among them, R 2is the confidence value, x i is the pressure data of the ith item, y i is the i-th depth data, n is the total number of the pressure data, n is also the total number of the depth data, 1≤i≤n, is the average value of the depth data, f(x i ) is the regression equation, is the corresponding value calculated according to the regression equation.

[0030] According to a second aspect of an embodiment of the present application, a fluid density data analysis device is provided, comprising:

[0031] The test module is used to perform well logging operations based on the wireline formation pressure test method to obtain depth data and pressure data;

[0032] A data processing module, configured to calculate a confidence value based on the depth data and the pressure data;

[0033] a comparison module, configured to compare the confidence value with a confidence threshold;

[0034] The data processing module is further configured to obtain fluid density data based on the depth data and the pressure data if the confidence value is greater than or equal to the confidence threshold;

[0035] A drawing module is used to draw a fluid density map based on the depth data, the pressure data and the fluid density data.

[0036] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the fluid density data analysis method as described in the first aspect when executing the computer program stored in the memory.

[0037] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the fluid density data analysis method as described in the first aspect is implemented.

[0038] The data analysis method and related equipment for fluid density provided in the embodiment of the present application, by introducing a confidence value, the confidence value is obtained based on the depth data and pressure data obtained by the logging operation, and can characterize the credibility of the depth data and pressure data. By comparing the confidence value and the confidence threshold, it is determined whether the credibility of the data obtained by the current test meets the standard. If the confidence value is greater than or equal to the confidence threshold, it means that the depth data and pressure data obtained by the current test can meet the credibility standard, and then the fluid density plate can be drawn based on the depth data and pressure data to analyze the fluid density. Therefore, the data analysis method for fluid density provided in the embodiment of the present application, by introducing a confidence value, can reflect the credibility of the data. By comparing the size of the confidence value and the confidence threshold, it is determined whether the depth data and pressure data obtained by the current test meet the credibility standard, which can improve the reference value of the data analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic flow chart of a method for analyzing fluid density data provided in an embodiment of the present application;

[0040] Figure 2 A schematic diagram of a fluid density map provided in an embodiment of the present application;

[0041] Figure 3 A schematic diagram of another fluid density map provided in an embodiment of the present application;

[0042] Figure 4 A schematic diagram of another fluid density map provided in an embodiment of the present application;

[0043] Figure 5 A schematic diagram of another fluid density plate provided in an embodiment of the present application;

[0044] Figure 6 A schematic diagram of a fluid density map provided in an embodiment of the present application;

[0045] Figure 7 A schematic structural block diagram of a fluid density data analysis device provided in an embodiment of the present application;

[0046] Figure 8 A schematic structural block diagram of an electronic device provided in an embodiment of the present application;

[0047] Figure 9 A schematic structural block diagram of a computer-readable storage medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to better understand the technical solutions provided by the embodiments of this specification, the technical solutions of the embodiments of this specification are described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.

[0049] In this article, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also include elements inherent to such process, method, article or equipment. In the absence of further restrictions, the elements defined by the statement "comprising a ..." do not exclude the presence of other identical elements in the process, method, article or equipment comprising the elements. The term "two or more" includes two or more than two cases.

[0050] Wireline formation pressure testing is a crucial logging method in oil and gas exploration and development, crucial for early oilfield evaluation and dynamic monitoring. One application of wireline formation pressure testing is to plot formation pressure profiles, determine fluid density, and identify fluid type. However, the multi-point linear regression method used to calculate fluid density not only loses a lot of information, but also makes the slope of the line unclear, particularly for distinguishing between oil and water. Fluid density charts address the shortcomings of multi-point linear regression in pressure profile interpretation, allowing the fluid density data axis to be incorporated into the chart and used to identify fluid type. However, the application of fluid density charts lacks a factor for interpreting confidence, which can be defined as the reliability of the logging data and reflects the quality of the data. Therefore, existing fluid density data analysis methods struggle to reflect data reliability, reducing the relevance of the analysis results.

[0051] In view of this, an embodiment of the present application provides a fluid density data analysis method and related equipment, which can reflect the credibility of the data and improve the reference value of the data analysis results during the fluid density data analysis process.

[0052] In a first aspect of an embodiment of the present application, a method for analyzing fluid density data is provided. Figure 1 This is a schematic flow chart of a method for analyzing fluid density data provided in an embodiment of the present application. Figure 1As shown, the data analysis method for fluid density provided in the embodiment of the present application includes:

[0053] S100: Performing well logging based on a wireline formation pressure test method to obtain depth data and pressure data. It is easy to understand that the depth data is the test depth data, and the pressure data is the test pressure data. The depth data and pressure data can be obtained in pairs, which is not specifically limited in this embodiment of the application.

[0054] S200: Calculate a confidence value based on the depth data and pressure data. The depth data and pressure data may be processed accordingly, such as by calculation or other data processing methods, to obtain a confidence value. The confidence value can reflect the quality of the depth data and pressure data obtained in the current test and can represent the credibility of the data.

[0055] S300: Compare the confidence value with the confidence threshold. The confidence threshold can be set based on experience and specific geological environment factors, and is not specifically limited in this embodiment of the application. The confidence threshold can be regarded as a standard for evaluating the credibility of data.

[0056] S400: If the confidence value is greater than or equal to the confidence threshold, fluid density data is obtained based on the depth data and pressure data. If the confidence value is greater than or equal to the confidence threshold, it can be determined that the depth data and pressure data obtained in the current test are reliable and can be used as a reference. The depth data and pressure data can then be used to further calculate fluid density data.

[0057] S500: Draw a fluid density map based on the depth data, pressure data, and fluid density data. Drawing a fluid density map requires three types of data: depth data, pressure data, and fluid density data. The fluid density data can be calculated based on the depth data and pressure data. The fluid density map typically uses a polar coordinate system.

[0058] For example, Figure 2 A schematic diagram of a fluid density map provided in an embodiment of the present application; Figure 3 A schematic diagram of another fluid density map provided in an embodiment of the present application. Figure 2 The density points in the fluid density plate shown are poorly concentrated. Figure 3 The density points in the fluid density map shown have a good concentration. The density points are the data points in the fluid density map. Due to the characteristics of the polar coordinate system, each density point corresponds to a sine curve. The concentration of the density points is strongly correlated with the confidence value of the corresponding data. Figure 2 The confidence value of the data corresponding to the fluid density plate shown is lower than Figure 3 The fluid density plates shown correspond to the confidence values ​​of the data.

[0059] The data analysis method for fluid density provided in the embodiment of the present application, by introducing a confidence value, the confidence value is obtained based on the depth data and pressure data obtained by the logging operation, and can characterize the credibility of the depth data and pressure data. By comparing the confidence value and the confidence threshold, it is determined whether the credibility of the data obtained by the current test meets the standard. If the confidence value is greater than or equal to the confidence threshold, it means that the depth data and pressure data obtained by the current test can meet the credibility standard. Then, the fluid density map can be drawn based on the depth data and pressure data to analyze the fluid density. Therefore, the data analysis method for fluid density provided in the embodiment of the present application, by introducing a confidence value, can reflect the credibility of the data. By comparing the confidence value and the confidence threshold, it is determined whether the depth data and pressure data obtained by the current test meet the credibility standard. If the confidence value is greater than or equal to the confidence threshold, it means that the depth data and pressure data obtained by the current test can meet the credibility standard. Then, the fluid density map can be drawn based on the depth data and pressure data to analyze the fluid density, which can improve the referenceability of the data analysis results.

[0060] In some embodiments, the data analysis method for fluid density provided in the embodiments of the present application further includes:

[0061] According to the fluid density plate, the analysis results of the fluid type are obtained.

[0062] For example, Figure 4 This is a schematic diagram of another fluid density map provided in the embodiment of the present application. Figure 4 As shown in the figure, different fluid density ranges correspond to different fluid types. All density points with a fluid density less than P1 correspond to gas, density points with a fluid density between P1 and P2 correspond to oil, density points with a fluid density between P2 and P3 correspond to water, and density points with a fluid density greater than P3 correspond to mud. <P1<0.6g / cm 3 , 0.8 <P2<0.9g / cm 3 , 1.2 <P3<1.3g / cm 3 . refer to Figure 4 The fluid density chart can be used to obtain the analysis results of the fluid type. Figure 4 The corresponding data shows that there are two main types of fluids in this test, one is mud and the other is gas, with more mud and less gas.

[0063] The fluid density data analysis method provided in the embodiment of the present application can intuitively identify the fluid density type based on the fluid density range where the density points are concentrated, through the fluid density chart.

[0064] In some embodiments, the data analysis method for fluid density provided in the embodiments of the present application further includes:

[0065] If the confidence value is less than the confidence threshold, check whether there is abnormal data in the depth data and pressure data;

[0066] If there are abnormal data in the depth data and pressure data, the abnormal data is removed and a corrected confidence value is obtained. Exemplarily, the abnormal data may include pressure abnormal data and depth abnormal data. The pressure abnormal data may be data whose pressure value exceeds the pressure range. For example, if the pressure data is a negative number, it represents negative pressure. Negative pressure does not usually exist. Therefore, when the pressure data is a negative number, possible reasons include abnormalities in the test equipment or instrument, errors in the test operation steps, etc. The pressure abnormal data may also be data that exceeds the limit pressure value, such as pressure data that exceeds the equipment range, etc., which are not specifically limited in this application. If the measured depth data is 0, it is depth abnormal data. Possible reasons include equipment abnormality, test step errors, etc., which are not specifically limited in this application. After removing the abnormal data, the confidence value can be recalculated to obtain a corrected confidence value.

[0067] Compare the corrected confidence value with the confidence threshold. The corrected confidence value obtained after removing the abnormal data is again compared with the confidence threshold. If the corrected confidence value is equal to or greater than the confidence threshold, the depth and pressure data after removing the abnormal data can be used to draw the fluid density map.

[0068] The fluid density data analysis method provided in the embodiment of the present application can check whether there is abnormal data in the depth data and pressure data when the confidence value is less than the confidence threshold. If abnormal data exists, the confidence threshold can be increased by eliminating the abnormal data, thereby improving the reference value of the data analysis results.

[0069] In some embodiments, the data analysis method for fluid density provided in the embodiments of the present application further includes:

[0070] If the corrected confidence value is less than the confidence threshold, the logging operation is repeated. If the corrected confidence value after removing the anomalous data is still less than the confidence threshold, the reason for the substandard confidence value cannot be eliminated by removing the anomalous data. The logging operation must be repeated to obtain a new confidence value. This new confidence value is then compared with the confidence threshold until the confidence value remains greater than or equal to the confidence threshold, resulting in a fluid density map. Re-logging can be combined with repairing testing equipment, adjusting testing methods, and other methods to improve test accuracy.

[0071] The data analysis method of fluid density provided in the embodiment of the present application is:

[0072] In some implementations, step S500 may include:

[0073] Draw a fluid density map based on depth data, pressure data and fluid density data;

[0074] Remove the sinusoidal curve lines in the fluid density map to simplify the fluid density map. Figure 5 A schematic diagram of another fluid density map provided in an embodiment of the present application. Figure 4 and Figure 5 , compared to Figure 4 The fluid density plate shown, Figure 5 The fluid density plate in the figure removes the sine curve corresponding to each density point. Figure 4 The fluid density diagram shown has too many lines and is too messy due to the presence of the sine curve. Figure 5 After removing the sine curve, the graph becomes simpler and easier to observe.

[0075] Add a one-dimensional concentration curve of density points to the fluid density map. Figure 6 This is a schematic diagram of a fluid density map provided in an embodiment of the present application. Figure 5 and Figure 6 As shown, a one-dimensional concentration curve L of density points is added to the fluid density plate. The one-dimensional concentration curve L can reflect the concentration degree of density points in the dimension of fluid density, such as Figure 5 and Figure 6 As shown, the fluid density area corresponding to the fixed point in the one-dimensional concentration curve L concentrates more density points. The concentration degree of the fluid density is strongly correlated with the confidence level. The fluid density type corresponding to the position with the largest fluid density concentration is the analysis result of the fluid type obtained by the current test. The one-dimensional concentration curve can be obtained by the following steps: calculating the number of data points within the fixed window length of the fluid density data, obtaining the data of the number of data points corresponding to each fixed window length corresponding to the fluid density data according to the fixed step length, and connecting the data of the number of data points corresponding to each fixed window length corresponding to the fluid density data obtained according to the fixed step length into a line to obtain a one-dimensional concentration curve. It should be noted that the window length and step length correspond to the horizontal coordinate representing the fluid density in the fluid density plate.

[0076] Add two-dimensional density contour curves of density points to the fluid density map, where the areas surrounded by different two-dimensional density contour curves are marked with different colors. Figure 6 As shown, two-dimensional density contour curves are drawn for density points, and the areas surrounded by different two-dimensional density contour curves are marked with different colors. This allows for more intuitive observation of the concentration of density points and the changing trend of the concentration, which is beneficial for analyzing fluid types and obtaining analysis results. Figure 6Different colors are not shown, but different grayscales are used to represent different colors. Color differences can also be used to represent them. Figure 6 The grayscale of the area surrounded by the two-dimensional density curve in the fluid density plate shown is only for reference and is not intended to be a specific limitation of the present application.

[0077] The fluid density data analysis method provided in the embodiments of the present application removes the sine curve from the fluid density chart, simplifies the chart, removes the interference of excessive lines, and makes the distribution of density points in the chart clearer. By adding a one-dimensional concentration curve and a two-dimensional density contour curve, and marking the areas surrounded by different two-dimensional density contour curves with different colors, the concentration degree and concentration area of ​​the density points can be more intuitively observed. The fluid density corresponding to the density point with the highest concentration is the fluid density corresponding to this test, thereby obtaining the corresponding fluid density type, i.e., the analysis result of the fluid type.

[0078] In some implementations, step S200 may include:

[0079] Based on the depth data and pressure data, the confidence value is calculated according to the following formula:

[0080]

[0081] RSS (Residual Sum of Squares) is the residual sum of squares, and ESS (Explained Sum of Squares) is the regression sum of squares. The smaller the residual sum of squares, the better the correlation between the independent variable and the dependent variable.

[0082]

[0083] Among them, R 2 is the confidence value, x i is the i-th pressure data, y i is the i-th depth data, n is the total number of pressure data, n is also the total number of depth data, 1≤i≤n, is the average value of the depth data, f(x i ) is the regression equation, is the corresponding value calculated according to the regression equation.

[0084] It should be noted that the confidence threshold can be set to 0.6-0.7, and this application does not make any specific limitation.

[0085] The data analysis method for fluid density provided in the embodiment of the present application can calculate an accurate confidence value based on pressure data and depth data through a specific calculation formula for the confidence value. The calculation formula for the confidence value provided in the embodiment of the present application uses the coefficient of determination in Russian statistics to represent the confidence value. The principle is simple and the reference is strong.

[0086] In a second aspect of the embodiments of the present application, a fluid density data analysis device is provided. Figure 7 This is a schematic structural block diagram of a fluid density data analysis device provided in an embodiment of the present application. Figure 7 As shown, the fluid density data analysis device provided in the embodiment of the present application includes:

[0087] The testing module 100 is used to perform well logging operations based on the wireline formation pressure testing method to obtain depth data and pressure data;

[0088] The data processing module 200 is used to calculate the confidence value based on the depth data and the pressure data;

[0089] a comparison module 300 for comparing the confidence value with a confidence threshold;

[0090] The data processing module 200 is further configured to obtain fluid density data based on the depth data and the pressure data if the confidence value is greater than or equal to the confidence threshold;

[0091] The drawing module 400 is used to draw a fluid density map based on the depth data, pressure data and fluid density data.

[0092] The data analysis device for fluid density provided in the embodiment of the present application introduces a confidence value. The confidence value is obtained based on the depth data and pressure data obtained by the logging operation, and can characterize the credibility of the depth data and pressure data. By comparing the confidence value and the confidence threshold, it is determined whether the credibility of the data obtained by the current test meets the standard. If the confidence value is greater than or equal to the confidence threshold, it means that the depth data and pressure data obtained by the current test can meet the credibility standard. Then, the fluid density map can be drawn based on the depth data and pressure data to analyze the fluid density. Therefore, the data analysis method for fluid density provided in the embodiment of the present application can reflect the credibility of the data by introducing the confidence value. By comparing the confidence value and the confidence threshold, it is determined whether the depth data and pressure data obtained by the current test meet the credibility standard. If the confidence value is greater than or equal to the confidence threshold, it means that the depth data and pressure data obtained by the current test can meet the credibility standard. Then, the fluid density map can be drawn based on the depth data and pressure data to analyze the fluid density, which can improve the referenceability of the data analysis results.

[0093] According to a third aspect of the present application, an electronic device is provided. Figure 8 A schematic structural block diagram of an electronic device provided in an embodiment of the present application, the electronic device 500, includes: a memory 510, a processor 520, and a computer program stored in the memory 510 and executable on the processor 520, the processor 520 being configured to implement the fluid density data analysis method as described in the first aspect when executing the computer program stored in the memory 510.

[0094] The steps of the method are as follows:

[0095] Based on the wireline formation pressure testing method, perform logging operations to obtain depth data and pressure data;

[0096] Calculate the confidence value based on the depth data and pressure data;

[0097] Compare the confidence value with the confidence threshold;

[0098] If the confidence value is greater than or equal to the confidence threshold, the fluid density data is obtained based on the depth data and pressure data;

[0099] Draw a fluid density map based on depth data, pressure data and fluid density data.

[0100] A fourth aspect of the embodiments of the present application provides a computer-readable storage medium. Figure 9 This is a schematic structural block diagram of a computer-readable storage medium provided in an embodiment of the present application. Figure 9 As shown, a computer program 611 is stored on the computer-readable storage medium 600. When the computer program 611 is executed by the processor, the data analysis method for fluid density as described in the first aspect is implemented.

[0101] The steps of the method are as follows:

[0102] Based on the wireline formation pressure testing method, perform logging operations to obtain depth data and pressure data;

[0103] Calculate the confidence value based on the depth data and pressure data;

[0104] Compare the confidence value with the confidence threshold;

[0105] If the confidence value is greater than or equal to the confidence threshold, the fluid density data is obtained based on the depth data and pressure data;

[0106] Draw a fluid density map based on depth data, pressure data and fluid density data.

[0107] Although the preferred embodiments of this specification have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of this specification.

[0108] Obviously, those skilled in the art may make various changes and modifications to this specification without departing from the spirit and scope of this specification. Thus, if such changes and modifications fall within the scope of the claims of this specification and their equivalents, this specification is intended to include such changes and modifications.

Claims

1. A method for analyzing fluid density data, characterized in that: include: Based on the wireline formation pressure testing method, perform logging operations to obtain depth data and pressure data; Calculating a confidence value based on the depth data and the pressure data; comparing the confidence value with a confidence threshold; If the confidence value is greater than or equal to the confidence threshold, obtaining fluid density data according to the depth data and the pressure data; Drawing a fluid density map based on the depth data, the pressure data, and the fluid density data; removing the sinusoidal curve lines in the fluid density map to simplify the graphics in the fluid density map; Adding a one-dimensional concentration curve of density points to the fluid density plate; A two-dimensional density contour curve of the density point is added to the fluid density map, wherein different areas surrounded by the two-dimensional density contour curves are marked with different colors.

2. The method for analyzing fluid density data according to claim 1, wherein: Also includes: If the confidence value is less than the confidence threshold, checking whether there is abnormal data in the depth data and the pressure data; If the abnormal data exists in the depth data and the pressure data, the abnormal data is removed and a corrected confidence value is obtained; The modified confidence value is compared with the confidence threshold.

3. The data analysis method for fluid density according to claim 2, characterized in that: Also includes: If the revised confidence value is less than the confidence threshold, the logging operation is re-executed.

4. The method for analyzing fluid density data according to claim 1, wherein: Also includes: According to the fluid density plate, an analysis result of the fluid type is obtained.

5. The method for analyzing fluid density data according to claim 1, wherein: Obtaining a confidence value according to the depth data and the pressure data includes: The confidence value is calculated according to the depth data and the pressure data according to the following formula: Among them, R 2 is the confidence value, x i is the pressure data of the ith item, y i is the i-th depth data, n is the total number of the pressure data, n is also the total number of the depth data, 1≤i≤n, is the average value of the depth data, f(x i ) is the regression equation, is the corresponding value calculated according to the regression equation.

6. A fluid density data analysis device, characterized in that: include: The test module is used to perform well logging operations based on the wireline formation pressure test method to obtain depth data and pressure data; A data processing module, configured to calculate a confidence value based on the depth data and the pressure data; a comparison module, configured to compare the confidence value with a confidence threshold; The data processing module is further configured to obtain fluid density data based on the depth data and the pressure data if the confidence value is greater than or equal to the confidence threshold; A drawing module is used to draw a fluid density map based on the depth data, the pressure data and the fluid density data; remove the sinusoidal curve lines in the fluid density map to simplify the graphics in the fluid density map; add a one-dimensional concentration curve of the density points in the fluid density map; add a two-dimensional density contour curve of the density points in the fluid density map, wherein different areas surrounded by the two-dimensional density contour curves are marked with different colors.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the fluid density data analysis method according to any one of claims 1 to 5 when executing the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the data analysis method for fluid density according to any one of claims 1 to 5 is implemented.

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