A well logging method and system for identifying and quantitatively calculating nodular chalk.

Abstract

This invention proposes a well logging identification and quantitative calculation method and system for nodular chalk. The method includes: dividing the target stratigraphic interval into chalk-developing sections within the cored well; establishing a well logging identification baseline for the chalk-developing sections based on the reservoir rock type within the target stratigraphic interval; automatically identifying and calibrating the chalk-developing sections in non-cored wells based on the well logging identification baseline; identifying all chalk in non-cored wells based on the color values ​​of the chalk-developing section images from the cored wells; calculating the chalk area percentage in non-cored wells; establishing a regression linear relationship curve between the chalk area percentage and well logging parameters; and calculating the chalk content in each chalk-developing section. This method is widely applicable to the characterization of nodular chalk. Through stepwise calibration using thin sections, cores, and well logging, it completes the expansion from cored wells to non-cored wells, which is of great significance for clarifying the development law and spatial distribution of chalk, and lays the foundation for the fine characterization of effective reservoirs.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas field development geology, and specifically relates to a well logging identification and quantitative calculation method and system for nodular chalk. Background Technology

[0002] Nodular chalk is formed when sea-level drop interrupts sedimentation during the carbonate rock depositional stage. High-magnesium calcite and aragonite minerals in the carbonate rocks undergo neomorphic deformation, transforming into low-magnesium calcite microcrystals and microsparkling lattices. Under strong cementation, these microcrystals lithify into dense, nodular calcareous sediments. The exposed chalk base is often subjected to various bioburden formations and crusting, while calcium carbonate is frequently replaced by glauconite and phosphates, forming shallow mineralization zones. In many cases, the processes of sedimentation, cementation, exposure, and mineralization are repeated several times, forming a composite hard base consisting of a series of cemented and mineralized chalk layers, exhibiting a significant rhythmic characteristic in the sequence stratigraphy. (WJ Kennedy and REGarris)

[0003] The formation of nodular chalk is influenced by multiple sedimentary environmental factors, including depth, irradiance, temperature, salinity, and dissolved oxygen, as well as diagenetic processes such as cementation and compaction (Marcelo Checoli Mantelatto). Compared to carbonate matrices, nodular chalk is denser and has poorer reservoir properties, even acting as a barrier in the accumulation of oil and gas reservoirs. Due to the influence of bio-drilling, these carbonate reservoirs have a certain positive modification effect on the surrounding reservoirs (John R. Cooper), resulting in increased permeability differences and stronger heterogeneity. That is, the spatial arrangement of non-reservoirs and reservoirs is not a conventional vertical stacking distribution, but rather consists of dense, non-oil-containing white chalk clumps interspersed with bio-disturbed, oil-bearing brown reservoirs. The most prominent feature observed in core studies is a mottled pattern. Core data from numerous marine porous carbonate oilfields in the Middle East show nodular chalk formations. In recent years, many scholars both domestically and internationally have conducted extensive research on the identification and characterization of non-reservoir carbonate formations. The main methods involve comprehensive analysis of thin section, core testing, well logging, and carbon and oxygen isotope data to study distribution characteristics, petrological features, and physical properties. Liao Mingguang et al. used well logging charts, Yan Xiaofang et al. used lithofacies identification techniques and multivariate regression analysis of seismic attributes, and Li Fengfeng et al. determined the distribution of different well logging value ranges through calibration to identify non-reservoir carbonate formations. However, research on the well logging characteristics and development content identification of strongly heterogeneous, patchy nodular chalk is relatively limited, essentially a blank area, lacking guidance in the well logging identification and quantitative calculation of nodular chalk. Summary of the Invention

[0004] To address the above problems, this invention proposes a well logging identification method for nodular chalk, the identification method comprising the following steps:

[0005] Delineate the chalk-developed sections within the target stratigraphic interval of the core well;

[0006] Establish logging identification baselines for different rock types in the Cretaceous development sections based on the reservoir rock types within the target section;

[0007] Based on the logging identification baseline of the chalk development section of different rock types, the chalk development section of non-cored wells is automatically identified, and the location of the chalk development section is marked on the non-cored wells.

[0008] Identify all chalk in non-core wells based on the color values ​​of images of chalk-developed sections in core wells.

[0009] Furthermore, the identification baselines for the Cretaceous developmental segments of the different rock types were obtained using the following method:

[0010] Classify the rock types of the target stratigraphic section;

[0011] Select the curves that are most sensitive to the logging response at the top and bottom of the Cretaceous development section, and establish a graph showing the relationship between the logging parameters of the target section and depth.

[0012] Mark the top and bottom depths of the divided Cretaceous development sections on the relationship diagram, and the logging parameter values ​​corresponding to the intersections with the curves are the logging identification baselines;

[0013] Establish well logging identification baselines for different rock types in the Cretaceous development sections.

[0014] Furthermore, the identification method also includes:

[0015] Before delineating the chalk-developed section within the target layer of the core well, select representative core wells within the target area;

[0016] After identifying the chalk-developed sections within the target layer, record the top and bottom depths of each chalk-developed section and mark them on the core logging chart.

[0017] Furthermore, the step of identifying all chalk in non-cored wells based on the color values ​​of chalk-developed sections in the cored well images specifically involves:

[0018] Extract the color value of chalk pixel A from the image of the chalk-developed section in the core well;

[0019] Calculate the chalk identification standard value based on the color value of pixel A, and set the identification range based on the identification standard value;

[0020] Compare the pixels to be identified and the identification range in the images of the Cretaceous developmental segment;

[0021] If the pixel to be identified is within the identification range, then the pixel to be identified is identified as chalk, until all pixels to be identified are identified;

[0022] If the pixel to be identified is outside the identification range, then the pixel to be identified is identified as non-white chalk, until all pixels to be identified are identified.

[0023] Furthermore, the formula for calculating pixel A is as follows:

[0024] A=0.3×μ(H)+0.4×μ(I)+0.3×μ(S)

[0025] Where H represents the chromaticity of the Cretaceous development segment image, S represents the saturation of the Cretaceous development segment image, I represents the brightness of the Cretaceous development segment image, A represents the number of pixels in the Cretaceous development segment image, and μ represents the weighting coefficient.

[0026] This invention also proposes a well logging identification system for nodular chalk, the identification system comprising:

[0027] The segmentation module is used to segment the chalk-developed sections within the target formation in the core well;

[0028] The baseline establishment module is used to establish identification baselines for Cretaceous development sections of different rock types based on the reservoir rock types within the target section;

[0029] The calibration module is used to automatically identify the chalk development section of the non-cored well based on the well logging identification baseline of the chalk development section of the different rock types, and to mark the location of the chalk development section on the non-cored well.

[0030] The identification module is used to identify all chalk in non-core wells based on the color values ​​of chalk development sections in the images of the core wells.

[0031] Furthermore, the identification system also includes:

[0032] The selection module is used to select representative core wells in the target area before delineating the chalky development section within the target layer of the core well;

[0033] The marking module is used to record the top and bottom depths of each chalk development segment after the target layer is delineated and mark them on the core well logging chart.

[0034] Based on the identification method, this invention also proposes a quantitative calculation method for nodular chalk in well logging, the calculation method comprising the following steps:

[0035] Calculate the percentage of chalk area in non-cored wells;

[0036] Establish a regression linear relationship curve between chalk area percentage and logging parameters, and select the logging parameters with the best correlation to characterize chalk development content;

[0037] Establish charts of chalk development content and logging parameters for different rock types, and derive calculation formulas; calculate the chalk development content of each chalk development segment at the identified development locations in the well using the calculation formulas.

[0038] Furthermore, the logging parameter with the best correlation is selected by the following method:

[0039] Calculate the correlation coefficient of the regression linear relationship curves between different well logging parameters and the chalk area percentage;

[0040] The logging parameters with the best correlation are determined based on the magnitude of the correlation coefficient.

[0041] Furthermore, the logging parameters include density, acoustic waves, neutrons, gamma rays, and resistivity.

[0042] This invention also proposes a well logging quantitative calculation system for nodular chalk, the calculation system comprising:

[0043] The area calculation module is used to calculate the proportion of chalk area in non-cored wells;

[0044] The characterization parameter selection module is used to establish a regression linear relationship curve between chalk area percentage and logging parameters, and select the logging parameters with the best correlation to characterize chalk development content;

[0045] The chalk content calculation module is used to establish chalk content and logging parameter charts for different rock types and derive calculation formulas; based on the calculation formulas, the chalk content of each chalk development segment is calculated at the identified development locations on the well.

[0046] The beneficial effects of this invention are:

[0047] This invention evaluates the logging response sensitivity by comparing the top and bottom sections of chalk development in core samples with the corresponding logging curves, establishing a chart of chalk area proportion and logging characteristic parameters, creating a regression linear relationship curve, and calculating the correlation coefficient. This effectively improves the accuracy of core-to-logging calibration.

[0048] This invention establishes logging identification standards based on different rock types, overcomes the influence of lithology on logging parameters, solves the problem of inconsistent electrical characteristics of multiple sets of Cretaceous development sections within the target layer, and forms an automatic well-ground identification technology for Cretaceous development sections.

[0049] This invention establishes a chalk color identification standard to accurately identify chalk in the core within the target layer. By establishing a relationship between chalk development area and logging parameters, it realizes the calculation of nodular chalk development content in wells without core sampling.

[0050] The method proposed in this invention can be widely applied to the characterization of nodular chalk. Through stepwise calibration of thin sections, cores, and well logging, it completes the expansion from cored wells to non-cored wells, which is of great significance for clarifying the development law and spatial distribution of chalk and lays the foundation for the fine characterization of effective reservoirs.

[0051] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 The flowchart of the well logging identification and quantitative calculation method for nodular chalk proposed in this invention is shown;

[0054] Figure 2 This invention presents a logging diagram showing the division of the chalky development sections in the core sample well QXJ-1 and displaying the top and bottom positions of each section in an embodiment of the invention.

[0055] Figure 3 This diagram illustrates the classification of reservoir rock types in the target section of core well QXJ-1 in an embodiment of the present invention.

[0056] Figure 4 This invention presents a graph showing the density curve of the target layer Cretaceous development section of core well QXJ-1 as a function of depth, and the logging identification baseline for each Cretaceous development section is determined based on different rock types.

[0057] Figure 5 This invention illustrates cross-sectional views of some uncorked wells that were not identified in the Cretaceous development section in an embodiment of the invention.

[0058] Figure 6 This invention illustrates the identification of the proportion of chalky development area in core well QXJ-1 in an embodiment of the invention;

[0059] Figure 7This invention illustrates a linear graph showing the proportion of chalk area in the chalk-developed section and the logging parameters of each section in an embodiment of the invention.

[0060] Figure 8 The following are calculation formulas for the chalk content of different rock types in embodiments of the present invention;

[0061] Figure 9 This invention presents a cross-sectional view of chalk development content in some uncorked wells in an embodiment of the invention. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] The purpose of this invention is to establish a logging identification standard for nodular chalk based on different rock types, using thin section analysis of cored wells and fine rock-electric calibration, to identify the location of chalk development in uncorked wells. This involves establishing color standards for pixels of chalk development in each development segment of the target layer core, using image analysis technology to identify nodular chalk and calculate its development content, and establishing a relationship between chalk development content and logging parameters for that segment, thus enabling the calculation of chalk development content within chalk development segments of uncorked wells.

[0064] like Figure 1 As shown, the well logging identification and quantitative calculation method for nodular chalk proposed in this invention mainly follows these steps:

[0065] Step 1: Select representative core wells in the target area, delineate the chalky development sections within the target layer, record the top and bottom depths of each chalky development section and mark them on the core well logging chart, and evaluate the sensitivity of the logging response characteristics at the top and bottom positions of each chalky development section. The sensitivity of the logging response characteristics is evaluated based on the degree of fluctuation of the logging identification curve; the greater the fluctuation, the higher the sensitivity.

[0066] Step 2: Select the logging identification curve that is most sensitive to the logging response at the top and bottom of the Cretaceous development section, establish a scatter plot of logging parameters of the target layer of the core well as the change of depth, and mark the top and bottom depths of the Cretaceous development section on the core well at the corresponding depth positions. The logging parameter value corresponding to the intersection with the logging identification curve is the logging identification baseline; through microscopic thin section feature analysis of the target reservoir, classify the rock type (RT), and establish the logging identification baseline of the Cretaceous development section based on different rock types;

[0067] Step 3: Using the established logging identification baselines for chalk development in different rock types, automatically identify logging parameters of non-cored wells and pinpoint the location of chalk development sections;

[0068] Step 4: Select images of the chalk-developed section from the core sample well. Extract the RGB color value of a specific pixel on the chalk. Using the HIS color recognition standard, calculate the chalk recognition standard value and set the chalk recognition range. Evaluate and calculate the chalk identification value for each pixel in the chalk-developed section image based on the chalk recognition range. If the pixel is within the recognition range N, it is identified as chalk; if it is outside the recognition range, it is identified as non-chalk. This process continues until every pixel in the image is identified, completing the identification of all chalk within this chalk-developed section. After identification, use statistical methods to calculate the area percentage of all chalk.

[0069] Since pixels are affected by a variety of factors, multiple factors are considered when calculating the chalk identification standard value, including the image's chroma, saturation, and brightness. At the same time, weighting coefficients are set to adjust the pixels according to the actual situation, with pixel A as the chalk identification standard value.

[0070] The formula for calculating pixel A is:

[0071] A=0.3×μ(H)+0.4×μ(I)+0.3×μ(S)

[0072] In the above formula, H represents the chromaticity of the chalk development segment image, S represents the saturation of the chalk development segment image, I represents the brightness of the chalk development segment image, A represents the number of pixels in the chalk development segment image, and μ represents the weighting coefficient, which can be adjusted to obtain the optimal weighting coefficient based on the chalk recognition effect.

[0073] in,

[0074]

[0075]

[0076]

[0077]

[0078] Step 5: Extract logging parameters of the chalk section, establish a two-dimensional planar chart of chalk area proportion and logging parameters, establish a regression linear relationship curve and calculate the correlation coefficient, and select the logging parameter with the best correlation coefficient to characterize the chalk development content;

[0079] Step 6: Establish a graph of chalk development content and logging parameters for different rock types, obtain the calculation formula, calculate the development content of chalk in each segment at the identified development locations on the well, and complete the quantitative calculation of chalk in each segment.

[0080] Because the main oil reservoir in a certain oil field in the Middle East is a carbonate reservoir dominated by bioturbation limestone, and due to the strong cementation during the depositional stage, multiple sets of nodular chalk have developed in the target layer, making the reservoir extremely heterogeneous in the vertical direction.

[0081] In this embodiment of the invention, more than 80 wells in the main oil reservoir of an oilfield in the Middle East were used as test objects. The method proposed in this invention was used to identify and quantitatively characterize the nodular chalk in more than 80 wells in the main oil reservoir of an oilfield in the Middle East through well logging.

[0082] Step 1: Select the representative QXJ-1 coring well as the test object.

[0083] like Figure 2 As shown, eight Cretaceous developmental sections can be identified from top to bottom between MDC-1 and MDC-2 in the target layer of core well QXJ-1; as Figure 2 The left side shows sections 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, and 1.8, respectively. The top and bottom depths of each Cretaceous development section were recorded and marked on the well logging chart. The marking results are shown below. Figure 2 As shown on the right, the top and bottom of section 1.1 are marked as 1.1 upper and 1.1 lower, respectively. The curves in the vertical direction of the figure are logging curves (the logging curves are measured during the drilling process). It can be seen that there are obvious fluctuations in the logging curves at the upper and lower positions of each section, indicating that the logging curve response characteristics are in good agreement with the core, laying the foundation for the calibration from the core to the logging.

[0084] Step 2: Through microscopic thin section analysis of the target reservoir in Step 1, the analysis revealed that the target reservoir exhibits four rock types (RT), such as... Figure 3 As shown, micritic bioclastic sandstone and limestone with casting pores and intergranular pores as the main pore types (RT1), micritic bioclastic sandstone and limestone with casting pores and intragranular pores as the main pore types (RT2), micritic bioclastic limestone with casting pores and intragranular pores as the main pore types (RT3), and micritic bioclastic limestone with cavity pores and micropores as the main pore types (RT4).

[0085] Select the density curve most sensitive to the chalk response from step 1, and establish a scatter plot of the density logging parameters (RHOB) of the target layer in the core well QXJ-1 as a function of depth (MD). Mark the depths of the chalk-developed sections on the core of this core well at the corresponding depth locations. Figure 4 As shown in the figure, the vertical bars represent the locations of the Cretaceous development sections, and the dots represent density points. The density values ​​corresponding to the intersections of the bars and density points are logging identification baselines for different rock types.

[0086] Step 3: Based on the logging identification baselines for different rock types obtained in Step 2, identify the chalky development sections in all non-cored wells (the density value in the logging curve is greater than the identification baseline for that rock type), and mark their locations on the non-cored wells to complete the extension from cored wells to non-cored wells. For example... Figure 5 As shown, the chalk development sections in the non-cored wells on the right are identified based on the known different rock types of chalk development sections on the left side of the figure. The rightmost line of each well in the figure indicates the identified development location.

[0087] Step 4: As Figure 6 As shown, images of the Cretaceous development section were selected from the core sample of well QXJ-1 (e.g., Figure 6 As shown in (a), extract the color value of a certain pixel in the white patch in image (a) to establish a recognition standard (according to the HIS color recognition standard in this segment, obtain pixel A of chalk). Identify all pixels that are similar to the chalk pixel to complete the identification of all chalk in this chalk development segment (e.g. Figure 6 (as shown in (b)); calculate the area percentage of Cretaceous development (as shown in (b)); Figure 6 (as shown in (c)).

[0088] Step 5: Extract the logging characteristic parameters of density (RHOB), sonic logging (DT), neutron logging (NPHI), gamma logging (GR), and resistivity (ILD) of the chalky development section in Step 2, establish a two-dimensional planar plot of chalky area proportion and logging characteristic parameters, establish a regression linear relationship curve and calculate the correlation coefficient.

[0089] The regression linear relationship curves between the proportion of chalk area and the RHOB, DT, NPHI, GR, and ILD of the chalk development stage are shown in the figure below. Figure 7 As shown:

[0090] The regression linear relationship curve between the proportion of chalky area and the RHOB of the chalky development stage is as follows:

[0091] y = 2.8304x - 6.3751, R 2 =0.9054

[0092] The regression linear relationship curve between the area percentage of chalk and the DT of the chalk development stage is as follows:

[0093] y = -0.0298x + 2.5066, R 2 =0.7854

[0094] The regression linear relationship curve between the area percentage of chalk and the NPHI of the chalk development stage is as follows:

[0095] y = -3.6936x + 1.0687, R 2 =0.6296

[0096] The regression linear relationship curve between the area percentage of chalk and the GR of the chalk development stage is as follows:

[0097] y = -0.0079x + 0.3301, R 2 =0.1187

[0098] The regression linear relationship curve between the area percentage of chalk and the ILD in the chalk development stage is as follows:

[0099] y = -0.008x + 0.2308, R 2 =0.0361

[0100] As can be seen from the above regression linear relationship curves, the proportion of chalk area has the best correlation with the chalk development stage. Therefore, the density parameter with the best correlation is selected to characterize the chalk development content.

[0101] Step 6: Calculate the chalk content and density parameters for different rock types, and establish regression linear relationship curves. The regression linear relationship curves between chalk content and density for different rock types are shown below. Figure 8 As shown:

[0102] in,

[0103] The regression linear relationship curve between the chalky development content and density of RT1 is as follows:

[0104] y = 1.7445x - 3.7351, R 2 =0.8699

[0105] The regression linear relationship curve between the chalky development content and density of RT2 is as follows:

[0106] y = 2.216x - 5.176, R 2 =0.9488

[0107] The regression linear relationship curve between the chalky development content and density of RT3 is as follows:

[0108] y = 2.089x - 4.6367, R 2 =0.7873

[0109] The regression linear relationship curve between the chalky development content and density of RT4 is as follows:

[0110] y = 1.6047x - 3.5054, R 2 =0.8097

[0111] Based on the regression linear relationship curves between the chalk content and density of different rock types, the calculation formulas for the chalk content of different rock types were obtained, and the results are shown in Table 1:

[0112]

[0113] like Figure 9 As shown, the chalk development locations identified in non-cored wells are used to calculate the chalk content of each segment using appropriate calculation formulas for different rock types, thus completing the quantitative characterization of each chalk segment. The white boxes in the right-hand side of each well represent the calculated chalk content within the chalk development segment.

[0114] Based on the well logging identification and quantitative calculation method for nodular chalk proposed in this invention, a well logging identification and quantitative calculation system for nodular chalk is proposed. This system is used to execute the identification and calculation method and specifically includes the following modules:

[0115] Select the module and choose representative coring wells within the target area;

[0116] The segmentation module is used to segment the chalk-developed sections within the target formation in the core well;

[0117] The marking module is used to record the top and bottom depths of each section and mark them on the core logging chart.

[0118] The baseline establishment module is used to establish logging identification baselines for different rock types of Cretaceous development sections based on the reservoir rock types within the target section;

[0119] The calibration module is used to automatically identify the chalk development section of the non-cored well based on the well logging identification baseline of the chalk development section of the different rock types, and to mark the location of the chalk development section on the non-cored well.

[0120] The marking module is used to record the top and bottom depths of each segment after the chalk-developed segments within the target layer are identified and to mark them on the core logging chart accordingly.

[0121] The area calculation module is used to calculate the proportion of chalk area in non-cored wells;

[0122] The characterization parameter selection module is used to establish a regression linear relationship curve between chalk area percentage and logging parameters, and select the logging parameters with the best correlation to characterize chalk development content;

[0123] The chalk development content calculation module is used to establish a graph of chalk development content and logging parameters for different rock types, obtain a calculation formula, and calculate the chalk development content of each chalk development segment at the identified development location on the well according to the calculation formula.

[0124] Based on the above-mentioned methods and systems, this invention, through precise rock-electrical calibration of cored wells and the application of image analysis and logging curve fitting, characterizes the location and content of nodular chalk development in non-cored wells, forming an understanding of the development patterns and spatial distribution of the entire area. This provides reliable geological basis for the fine characterization of effective reservoirs, the formulation of reasonable development plans, and the understanding of the oil-water movement patterns in water injection development.

[0125] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A well logging method for identifying nodular chalk, characterized in that, The identification method includes the following steps: Delineate the chalk-developed sections within the target stratigraphic interval of the core well; Establish logging identification baselines for different rock types in the Cretaceous development sections based on the reservoir rock types within the target section; Based on the logging identification baseline of the chalk development section of different rock types, the chalk development section of non-cored wells is automatically identified, and the location of the chalk development section is marked on the non-cored wells. Identifying all chalk in non-cored wells based on color values ​​from images of chalk-developed sections in cored wells includes: extracting the color value of chalk pixel A from images of chalk-developed sections in cored wells; calculating a chalk identification standard value based on the color value of pixel A and setting an identification range based on the identification standard value; comparing the pixel to be identified in the chalk-developed section image with the identification range; if the pixel to be identified is within the identification range, then the pixel to be identified is identified as chalk, until all pixels to be identified are identified; if the pixel to be identified is outside the identification range, then the pixel to be identified is identified as non-chalcedony, until all pixels to be identified are identified.

2. The well logging identification method for nodular chalk according to claim 1, characterized in that, The identification baselines for the Cretaceous developmental sections of different rock types were obtained using the following method: Classify the rock types of the target stratigraphic section; Select the curves that are most sensitive to the logging response at the top and bottom of the Cretaceous development section, and establish a graph showing the relationship between the logging parameters of the target section and depth. Mark the top and bottom depths of the divided Cretaceous development sections on the relationship diagram, and the logging parameter values ​​corresponding to the intersections with the curves are the logging identification baselines; Establish well logging identification baselines for different rock types in the Cretaceous development sections.

3. A well logging identification method for nodular chalk according to claim 1 or 2, characterized in that, The identification method further includes: Before delineating the chalk-developed section within the target layer of the core well, select representative core wells within the target area; After identifying the chalk-developed sections within the target layer, record the top and bottom depths of each chalk-developed section and mark them on the core logging chart.

4. The well logging identification method for nodular chalk according to claim 1, characterized in that, The formula for calculating pixel A is: A=0.3×μ(H)+0.4×μ(I)+0.3×μ(S) Where H represents the chromaticity of the Cretaceous development segment image, S represents the saturation of the Cretaceous development segment image, I represents the brightness of the Cretaceous development segment image, A represents the number of pixels in the Cretaceous development segment image, and μ represents the weighting coefficient.

5. A well logging identification system for nodular chalk, characterized in that, The identification system includes: The segmentation module is used to segment the chalk-developed sections within the target formation in the core well; The baseline establishment module is used to establish identification baselines for Cretaceous development sections of different rock types based on the reservoir rock types within the target section; The calibration module is used to automatically identify the chalk development section of the non-cored well based on the well logging identification baseline of the chalk development section of the different rock types, and to mark the location of the chalk development section on the non-cored well. The identification module is used to identify all chalk in non-cored wells based on the color values ​​of chalk development section images in cored wells. This includes: extracting the color value of chalk pixel A from the chalk development section image in the cored well; calculating a chalk identification standard value based on the color value of pixel A and setting an identification range based on the identification standard value; comparing the pixel to be identified in the chalk development section image with the identification range; if the pixel to be identified is within the identification range, then the pixel to be identified is identified as chalk, until all pixels to be identified are identified; if the pixel to be identified is outside the identification range, then the pixel to be identified is identified as non-chalcedony, until all pixels to be identified are identified.

6. The well logging identification system for nodular chalk according to claim 5, characterized in that, The identification system also includes: The selection module is used to select representative core wells in the target area before delineating the chalky development section within the target layer of the core well; The marking module is used to record the top and bottom depths of each chalk development segment after the target layer is delineated and mark them on the core well logging chart.

7. A method for quantitative calculation of nodular chalk in well logging, characterized in that, The calculation method is performed after identifying nodular chalk using the identification method described in any one of claims 1-4 or the identification system described in any one of claims 5-6; The calculation method includes the following steps: Calculate the percentage of chalk area in non-cored wells; Establish a regression linear relationship curve between chalk area percentage and logging parameters, and select the logging parameters with the best correlation to characterize chalk development content; Establish charts of chalk development content and logging parameters for different rock types, and derive calculation formulas; calculate the chalk development content of each chalk development segment at the identified development locations in the well using the calculation formulas.

8. The method for quantitative calculation of nodular chalk in well logging according to claim 7, characterized in that, The logging parameters with the best correlation were selected using the following method: Calculate the correlation coefficient of the regression linear relationship curves between different well logging parameters and the chalk area percentage; The logging parameters with the best correlation are determined based on the magnitude of the correlation coefficient.

9. The method for quantitative calculation of nodular chalk in well logging according to claim 7, characterized in that, The logging parameters include density, acoustic waves, neutrons, gamma rays, and resistivity.

10. A well logging quantitative calculation system for nodular chalk, characterized in that, The calculation system is performed after identifying nodular chalk using the identification system according to any one of claims 5-6. The calculation system includes: The area calculation module is used to calculate the proportion of chalk area in non-cored wells; The characterization parameter selection module is used to establish a regression linear relationship curve between chalk area percentage and logging parameters, and select the logging parameters with the best correlation to characterize chalk development content; The chalk content calculation module is used to establish chalk content and logging parameter charts for different rock types and derive calculation formulas; based on the calculation formulas, the chalk content of each chalk development segment is calculated at the identified development locations on the well.

Images