A carbonate rock diagenetic facies reservoir prediction method based on diagenetic coefficients

Abstract

The present application relates to the field of carbonate reservoir prediction, and particularly relates to a carbonate diagenetic facies reservoir prediction method based on diagenetic coefficients, which comprises establishing a diagenetic coefficient and porosity fitting relationship; establishing a fitting relationship between wave impedance and porosity; calculating the diagenetic coefficient according to wave impedance inversion data; determining the distribution characteristics of diagenetic facies according to the relationship between the diagenetic coefficient and the diagenetic facies type, and realizing the prediction of carbonate diagenetic facies reservoirs. The carbonate diagenetic facies seismic method based on diagenetic coefficients solves the problem of difficult quantitative identification of carbonate diagenetic facies, and clearly defines the distribution characteristics of different types of diagenetic facies in the vertical and horizontal directions, which is conducive to improving the success rate of exploration and development.

Description

Technical Field

[0001] This invention relates to the field of carbonate reservoir prediction, and more specifically to a method for predicting carbonate diagenetic facies reservoirs based on diagenetic coefficients. Background Technology

[0002] As a comprehensive reflection of reservoir characteristics, diagenetic facies encompasses various aspects such as rock grains, cement, texture, and pores and fractures. It represents the final morphology of sediments after multiple stages of diagenesis and tectonic activity under specific sedimentary environments and physicochemical conditions. Diagenetic facies not only reveals the essential attributes and classification of reservoirs but also serves as an important indicator for evaluating reservoir quality. Therefore, in-depth research into diagenetic facies helps to accurately locate high-quality reservoirs closely related to reservoir performance, providing more precise guidance for oil and gas exploration.

[0003] However, current research mainly focuses on core analysis, thin section microscopy, and well logging identification of clastic rocks, while relatively little work is done on directly predicting diagenetic facies using seismic data. Specifically, core analysis typically relies on thin section microscopy to provide a detailed description using indicators such as apparent compaction rate, apparent cementation rate, apparent dissolution rate, microporosity, and diagenetic coefficient; well logging identification involves matching the response characteristics of core data with those of well logging curves. However, both methods are primarily used for describing diagenetic facies in single wells, making it difficult to achieve high-precision prediction of the planar distribution of diagenetic facies.

[0004] Especially in carbonate reservoirs, the diverse types of diagenesis have complex and variable effects on the reservoir's spatial structure, and the seismic reflection characteristics differ significantly between different regions and stratigraphic groups. This makes it extremely difficult to directly establish the correlation between diagenesis and the distribution of diagenetic facies using seismic data.

[0005] In conclusion, developing a reservoir prediction method capable of accurately predicting the diagenetic facies of carbonate rocks is of significant practical importance. Summary of the Invention

[0006] The purpose of this invention is to provide a method for predicting carbonate rock diagenetic facies reservoirs based on diagenetic coefficients. The method calculates the diagenetic coefficient by establishing a fitting relationship between the diagenetic coefficient and porosity, and a fitting relationship between wave impedance and porosity. Then, based on the relationship between the diagenetic coefficient and the diagenetic facies type, the distribution characteristics of the diagenetic facies are determined, and carbonate rock diagenetic facies reservoirs are predicted.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for predicting carbonate diagenetic reservoirs based on diagenetic coefficients includes the following steps:

[0009] Establish a fitting relationship between diagenesis coefficient and porosity;

[0010] Establish a fitting relationship between wave impedance and porosity;

[0011] Wave impedance inversion data are obtained from the seismic data of the well to be logged;

[0012] The porosity of the well to be logged is obtained based on the wave impedance inversion data and the fitting relationship between wave impedance and porosity.

[0013] The diagenesis coefficient of the well to be logged is obtained by fitting the porosity and diagenesis coefficient to the porosity.

[0014] The diagenetic facies type of the well to be logged is determined based on the diagenetic coefficient, and the distribution characteristics of the diagenetic facies are determined based on the diagenetic facies type to predict carbonate rock diagenetic facies reservoirs.

[0015] Furthermore, establishing the fitting relationship between the diagenesis coefficient and porosity includes:

[0016] Core analysis was conducted to statistically analyze the apparent compaction rate, apparent cementation rate, and microporosity of different well sections in the well to be tested. The diagenesis coefficient was calculated based on the core analysis, and the porosity of the corresponding well section was calculated using the sonic transit time curve. A fitting relationship between the diagenesis coefficient and porosity was established based on the diagenesis coefficient and the corresponding porosity of different well sections.

[0017] Furthermore, the formula for calculating the diagenesis coefficient is: Diagenesis coefficient = Porosity / (Apparent compaction rate + Apparent cementation rate + Microporosity).

[0018] Furthermore, the fitting relationship between the diagenesis coefficient and porosity is obtained through linear fitting. The fitting relationship between the diagenesis coefficient and porosity is Cd=a1+b1Φ, where Cd is the diagenesis coefficient, Φ is the porosity, a1 and b1 are obtained through linear fitting, a1 is the intercept of the fitting relationship between the diagenesis coefficient and porosity, and b1 is the slope of the fitting relationship between the diagenesis coefficient and porosity.

[0019] Furthermore, establishing the fitting relationship between wave impedance and porosity includes:

[0020] The inverted wave impedance is obtained by performing a single-line inversion based on the parameters of the well to be logged and the dominant frequency of the seismic data.

[0021] Single-line inversion includes the following steps:

[0022] 1. Well data collection:

[0023] The well parameter data obtained mainly includes the sonic transit time curve and the compensated density curve; the well data provides high-resolution information on formation physical parameters.

[0024] 2. Seismic data collection:

[0025] Acquire pre-stack time-migrated seismic data to ensure that the well is within the seismic data range in order to achieve well-seismic integration.

[0026] 3. Single-line wave impedance inversion:

[0027] A seismic profile is extracted from a well, and the wave impedance is inverted using the preferred inversion method.

[0028] Determine if the formation thickness is less than λ / 8;

[0029] If the formation thickness is less than λ / 8, the fitting relationship between wave impedance and porosity is the fitting relationship between corrected wave impedance and porosity. Wave impedance and porosity are obtained by well logging calculation. The difference between the inverted wave impedance and the wave impedance calculated by well logging is compared to obtain the difference value. The difference value is arithmetically averaged to obtain the correction value. Corrected wave impedance = inverted wave impedance + correction value. Then, a fitting relationship between corrected wave impedance and porosity is established based on the corrected wave impedance and the porosity calculated by well logging. The parameters to be logged include the time difference curve and the compensated density curve.

[0030] and / or;

[0031] If the formation thickness is greater than λ / 8, the fitting relationship between wave impedance and porosity is the same as the fitting relationship between inverted wave impedance and porosity. The fitting relationship between inverted wave impedance and porosity is established using the inverted wave impedance and porosity calculated by well logging.

[0032] λ is the wavelength of the seismic wave.

[0033] Furthermore, when the formation thickness is greater than λ / 8, the fitting relationship between the inverted wave impedance and porosity is obtained through linear fitting. The fitting relationship between the inverted wave impedance and porosity is Z. 反演波阻抗 =a² + b²Φ, Z 反演波阻抗 Φ is the inverted wave impedance, Φ is the porosity, and a2 and b2 are obtained through linear fitting. a2 is the intercept of the fitting relationship between the inverted wave impedance and porosity, and b2 is the slope of the wave impedance and porosity.

[0034] When the formation thickness is less than λ / 8, the corrected wave impedance and porosity fitting relationship is obtained through linear fitting. The fitting relationship between the corrected wave impedance and porosity is Z. 校正后波阻抗 = a³ + b³Φ, where Φ is porosity, Z 校正后波阻抗 To correct the wave impedance, a3 and b3 are obtained through linear fitting, where a3 is the intercept of the fitted relationship between the corrected wave impedance and porosity, and b3 is the slope of the wave impedance versus porosity.

[0035] Furthermore, the corrected wave impedance is calculated as follows:

[0036] Calculate the difference between the inverted wave impedance and the logging wave impedance of multiple wells. The average value of the difference is the correction value. Then, based on the inverted wave impedance of the well to be logged, the corrected wave impedance of the well to be logged is obtained.

[0037] Furthermore, determining the diagenetic facies type of the well to be logged based on the diagenetic coefficient includes the following steps:

[0038] Core analysis was used to classify the rocks into lithofacies types.

[0039] Establish the correspondence between diagenetic coefficients and diagenetic facies types;

[0040] The diagenetic facies type is obtained based on the diagenetic coefficient;

[0041] Based on the diagenetic facies type, determine the distribution characteristics of the diagenetic facies and predict carbonate rock diagenetic facies reservoirs.

[0042] Furthermore, the diagenetic facies types include: strong dissolution during the surface stage, moderate dissolution during the surface stage, weak dissolution during the surface stage, and dolomitization during the burial stage.

[0043] Furthermore,

[0044] When the diagenesis coefficient is less than 3, it corresponds to the dolomitization diagenesis facies during the burial period;

[0045] When the diagenesis coefficient is 3-5, it corresponds to a weakly dissolved diagenetic facies in the supergene stage;

[0046] When the diagenesis coefficient is 5-7, it corresponds to a moderately dissolved diagenetic facies in the supergene stage;

[0047] When the diagenetic coefficient is greater than 7, it corresponds to the moderate dissolution diagenetic facies of the epigenetic period.

[0048] This invention also provides a method for predicting carbonate rock diagenetic reservoirs based on diagenetic coefficients:

[0049] (1) Based on core analysis, establish the fitting relationship between diagenesis coefficient and porosity.

[0050] Diagenesis is an essential process in the development and formation of carbonate reservoirs, ultimately determining their reservoir performance. Apparent compaction rate, apparent cementation rate, and apparent dissolution rate characterize the intensity of compaction, cementation, and dissolution, respectively. To quantitatively characterize the comprehensive impact of various diagenetic processes on reservoir performance and fully reflect the degree of influence on reservoir storage space after various diagenetic evolutions, a diagenetic coefficient Cd is introduced. Cd = porosity / (apparent compaction rate + apparent cementation rate + microporosity). When compaction is strong, there are no visible pores under a microscope (porosity is 0), so logging porosity is used instead; therefore, Cd = logging porosity / (apparent compaction rate + apparent cementation rate + microporosity) — Formula 1.

[0051] Step 1: In the core section, observe the thin section under a microscope, and statistically analyze parameters such as apparent compaction rate, apparent cementation rate, and microporosity. Calculate the porosity of the corresponding section and calculate the diagenetic coefficient Cd according to Formula 1.

[0052] Step 2: Calculate the porosity of the same well section observed under the microscope using the sonic transit time curve. Based on this, establish the fitting relationship between the diagenesis coefficient and porosity, i.e., Cd=a1+b1Φ—Formula 2, where a1 and b1 are constants, a1 is the intercept of the above relationship, and b1 is the slope of the above relationship.

[0053] (2) Based on well logging calculations and inversion simulations, a fitting relationship between wave impedance and porosity for different thicknesses is established.

[0054] There are many methods for predicting porosity. Conventional methods often use the fitting relationship between wave impedance calculated from well logging and porosity to convert the inverted wave impedance into porosity. However, since the wave impedance obtained by inversion is affected by the formation thickness, when the formation thickness is less than λ / 8, the inverted wave impedance differs significantly from the actual wave impedance. Therefore, it is necessary to establish a fitting relationship between wave impedance and porosity under different thickness conditions.

[0055] When the thickness of the stratum reaches λ / 4, a maximum amplitude value appears. This phenomenon is called the tuning effect of the thin layer, and the thickness at this point is called the tuning thickness. When the thickness of the thin layer is less than 3λ / 16, the thickness information can be obtained from the amplitude value. When the thickness is less than λ / 8, the amplitude-thickness relationship is approximately a straight line.

[0056] Step 1: When the formation thickness is greater than λ / 8, since the difference between the wave impedance obtained by inversion and the wave impedance calculated by well logging is small, a fitting relationship can be established between the wave impedance calculated by well logging and porosity, that is, Z=a2+b2Φ—Formula 3, where a2 and b2 are constants, a2 is the intercept of the above relationship, and b2 is the slope of the above relationship.

[0057] Step 2: When the formation thickness is less than λ / 8, the following procedure is used to establish the fitting relationship between wave impedance and porosity: A wedge model is established. Based on the relevant parameters of a well W1 with a formation thickness less than λ / 8 in the region and the dominant frequency of actual seismic data, a single-line inversion is performed. The difference between the inverted wave impedance and the wave impedance calculated from the well logging of W1 is compared to obtain this difference value E1. Then, based on the relevant parameters of the remaining wells with formation thickness less than λ / 8 in the region, a single-line inversion is performed, which similarly yields the difference Ei between the inverted wave impedance and the wave impedance calculated from the well logging. To reduce the error of the single-well inversion wave impedance results, the error results obtained from all these single-well inversions are arithmetically averaged to obtain the correction value E, thus obtaining Z. 校正后波阻抗 =Z 反演波阻抗 +E—Formula 4. Then, a fitting relationship is established based on the corrected true wave impedance and the porosity calculated using well logging, i.e., Z 校正后波阻抗 =a3+b3Φ—Formula 5, where a3 and b3 are constants, a3 is the intercept of the above relation, and b3 is the slope of the above relation.

[0058] (3) Calculate the diagenetic coefficient based on the wave impedance inversion data.

[0059] Based on 3D seismic data, well logging data, and stratigraphic data, the optimal inversion method can obtain wave impedance data with high resolution in both the vertical and horizontal directions.

[0060] Step 1: For areas with a stratigraphic thickness greater than λ / 8, inversion data is obtained using the preferred inversion method. The inverted wave impedance data is calculated according to Formula 3 and converted to obtain porosity data. Then, according to Formula 2, the diagenetic coefficient data is calculated and converted to obtain diagenetic coefficient data.

[0061] Step 2: For areas where the stratum thickness is less than λ / 8, the inverted wave impedance data is corrected according to Formula 4 to obtain the corrected wave impedance data. Then, the porosity data is calculated and converted according to Formula 5, and the diagenetic coefficient data is calculated and converted according to Formula 2.

[0062] (4) Determine the distribution characteristics of diagenetic facies based on the relationship between diagenetic coefficient and diagenetic facies type.

[0063] By observing core thin sections, we summarized the characteristics of different types of diagenesis, classified diagenetic facies types, and established the relationship between diagenetic coefficients and diagenetic facies types. Based on this relationship, we determined the distribution characteristics of different types of diagenetic facies using the diagenetic coefficient data obtained after inversion and formula transformation.

[0064] The beneficial effects of this invention include the following:

[0065] The seismic method for carbonate rock diagenetic facies based on diagenetic coefficients solves the problem of quantitative identification of carbonate rock diagenetic facies, clarifies the vertical and horizontal distribution characteristics of different types of diagenetic facies, and is conducive to improving the success rate of exploration and development. The method has shown good application results and provides a reference for the prediction of carbonate rock diagenetic facies in other similar areas. Attached Figure Description

[0066] 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.

[0067] Figure 1 Flowchart for predicting carbonate rock diagenetic facies reservoirs based on diagenetic coefficient in a specific embodiment of this application;

[0068] Figure 2 This is a diagram showing the fitting relationship between the diagenetic coefficient and porosity of the Carboniferous system in a specific embodiment of this application;

[0069] Figure 3This is a graph showing the fitting relationship between wave impedance and porosity in a specific embodiment of this application;

[0070] Figure 4 This is a waveform impedance profile in a specific embodiment of this application;

[0071] Figure 5 This is a porosity profile diagram in a specific embodiment of this application;

[0072] Figure 6 This is a diagenetic coefficient profile diagram in a specific embodiment of this application;

[0073] Figure 7 This is a plan view showing the distribution of different types of diagenetic facies in the Carboniferous system according to a specific embodiment of this application. Detailed Implementation

[0074] 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.

[0075] Example 1

[0076] (1) Based on core analysis, establish the fitting relationship between diagenesis coefficient and porosity:

[0077] Step 1: In the core section, observe the thin section under a microscope, and count parameters such as apparent compaction rate, apparent cementation rate, and microporosity. Calculate the porosity of the corresponding section, and calculate the diagenetic coefficient Cd according to Cd = logging porosity / (apparent compaction rate + apparent cementation rate + microporosity).

[0078] Step 2: Calculate the porosity of the same well section observed in the above-mentioned thin sections using the sonic transit time curve. Based on this, establish a fitting relationship between the Carboniferous diagenesis coefficient and porosity. (See [link to Carboniferous diagenesis coefficient and porosity fitting relationship]). Figure 2 .

[0079] (2) Based on well logging calculations and inversion simulations, a fitting relationship between wave impedance and porosity for different formation thicknesses is established:

[0080] When the stratum thickness is less than λ / 8, a wedge model is established, and single-line inversion is performed based on relevant parameters from multiple single wells and the dominant frequency of actual seismic data. The inversion data can be found in [reference needed]. Figure 4The wave impedance profile is used to compare the differences between the inverted wave impedance and the wave impedance calculated from well logging, obtaining multiple difference values. The arithmetic mean of these differences is used to obtain a correction value. The corrected true wave impedance is then obtained using the formula Zcorrected wave impedance = Zinverted wave impedance + E. Finally, a fitting relationship is established between the corrected true wave impedance and the porosity calculated from well logging. (The calculated porosity is described in [reference needed]). Figure 5 Porosity profile;

[0081] When the formation thickness is greater than λ / 8, a fitting relationship is directly established between the wave impedance calculated from well logging and the porosity. See the fitting relationship diagram for wave impedance versus porosity. Figure 3 .

[0082] (3) Calculate the diagenetic coefficient based on the wave impedance inversion data.

[0083] When the stratum thickness is less than λ / 8, according to Figure 5 Porosity data in the porosity profile diagram, through Figure 2 The fitting relationship between the diagenetic coefficient and porosity of the Middle Carboniferous system was used to calculate the diagenetic coefficient.

[0084] When the stratum thickness is greater than λ / 8, according to Figure 3 Porosity data was obtained by fitting the relationship between wave impedance and porosity in Carboniferous materials, and then... Figure 2 The relationship between the diagenetic coefficient and porosity of the Middle Carboniferous strata was fitted, and the diagenetic coefficient was calculated; see [link to relevant documentation] for the diagenetic coefficient. Figure 6 Diagenetic coefficient profile.

[0085] (4) Determine the distribution characteristics of diagenetic facies based on the relationship between diagenetic coefficient and diagenetic facies type.

[0086] By observing core thin sections, we summarized the characteristics of different types of diagenesis, classified diagenetic facies types, and established the relationship between diagenetic coefficient and diagenetic facies type. The relationship between diagenetic coefficient and diagenetic facies type is shown in Table 1.

[0087] Table 1

[0088]

[0089] Based on Table 1, the distribution characteristics of different types of diagenetic facies were determined using the diagenetic coefficient data obtained after inversion and formula transformation, forming the distribution of different types of diagenetic facies in the Carboniferous system. (See Table 1 for the distribution of different types of diagenetic facies in the Carboniferous system.) Figure 7 .

Claims

1. A method for predicting carbonate rock diagenetic facies reservoirs based on diagenetic coefficients, comprising the following steps: Establish a fitting relationship between diagenesis coefficient and porosity; Establish a fitting relationship between wave impedance and porosity; Wave impedance inversion data are obtained from seismic data based on the parameters of the well to be logged; The porosity of the well to be logged is obtained based on the wave impedance inversion data and the fitting relationship between wave impedance and porosity. The diagenesis coefficient of the well to be logged is obtained by fitting the porosity and diagenesis coefficient to the porosity. The diagenetic facies type is determined based on the diagenetic coefficient of the well to be logged, and the distribution characteristics of the diagenetic facies are determined based on the diagenetic facies type of the well to be logged, so as to predict the carbonate rock diagenetic facies reservoir.

2. The prediction method according to claim 1, characterized in that, The establishment of the fitting relationship between diagenesis coefficient and porosity includes: Core analysis was conducted to statistically analyze the apparent compaction rate, apparent cementation rate, and microporosity of different well sections in the well to be tested. The diagenesis coefficient was calculated based on the core analysis, and the porosity of the corresponding well section was calculated using the sonic transit time curve. A fitting relationship between the diagenesis coefficient and porosity was established based on the diagenesis coefficient and the corresponding porosity of different well sections.

3. The prediction method according to claim 2, characterized in that, The formula for calculating the diagenesis coefficient is: Diagenesis coefficient = Porosity / (Apparent compaction rate + Apparent cementation rate + Microporosity).

4. The prediction method according to claim 1, characterized in that, The fitting relationship between the diagenesis coefficient and porosity is obtained by linear fitting. The fitting relationship between the diagenesis coefficient and porosity is Cd=a1+b1Φ, where Cd is the diagenesis coefficient, Φ is the porosity, a1 and b1 are obtained by linear fitting, a1 is the intercept of the fitting relationship between the diagenesis coefficient and porosity, and b1 is the slope of the fitting relationship between the diagenesis coefficient and porosity.

5. The prediction method according to claim 1, characterized in that, The establishment of the fitting relationship between wave impedance and porosity includes: The inverted wave impedance is obtained by performing a single-line inversion based on the parameters of the well to be logged and the dominant frequency of the seismic data. Determine if the formation thickness is less than λ / 8; If the formation thickness is less than λ / 8, the fitting relationship between wave impedance and porosity is the fitting relationship between corrected wave impedance and porosity. Wave impedance and porosity are obtained by well logging calculation. The difference between the inverted wave impedance and the wave impedance calculated by well logging is compared to obtain the difference value. The correction value is obtained based on the difference value. Corrected wave impedance = inverted wave impedance + correction value. Then, the fitting relationship between corrected wave impedance and porosity is established based on the corrected wave impedance and the porosity calculated by well logging. The parameters to be logged include the time difference curve and the compensated density curve. and / or; If the formation thickness is greater than λ / 8, the fitting relationship between wave impedance and porosity is the same as the fitting relationship between inverted wave impedance and porosity. The fitting relationship between inverted wave impedance and porosity is established using the inverted wave impedance and porosity calculated by well logging. λ is the wavelength of the seismic wave.

6. The prediction method according to claim 5, characterized in that, When the formation thickness is greater than λ / 8, the fitting relationship between the inverted wave impedance and porosity is obtained through linear fitting. The fitting relationship between the inverted wave impedance and porosity is Z. 反演波阻抗 =a² + b²Φ, Z 反演波阻抗 Φ is the inverted wave impedance, Φ is the porosity, and a2 and b2 are obtained through linear fitting. a2 is the intercept of the fitting relationship between the inverted wave impedance and porosity, and b2 is the slope of the wave impedance and porosity. When the formation thickness is less than λ / 8, the corrected wave impedance and porosity fitting relationship is obtained through linear fitting. The fitting relationship between the corrected wave impedance and porosity is Z. 校正后波阻抗 = a³ + b³Φ, where Φ is porosity, Z 校正后波阻抗 To correct the wave impedance, a3 and b3 are obtained through linear fitting, where a3 is the intercept of the fitted relationship between the corrected wave impedance and porosity, and b3 is the slope of the wave impedance versus porosity.

7. The prediction method according to claim 6, characterized in that, The corrected wave impedance is calculated as follows: Calculate the difference between the inverted wave impedance and the logging wave impedance of multiple wells, and use the average value of the difference as the correction value. Then, based on the inverted wave impedance of the well to be logged, obtain the corrected wave impedance of the well to be logged.

8. The prediction method according to claim 1, characterized in that, Determining the diagenetic facies type of the well to be logged based on the diagenetic coefficient includes the following steps: Core analysis was used to classify the rocks into lithofacies types. Establish the correspondence between diagenetic coefficients and diagenetic facies types; The diagenetic facies type is obtained based on the diagenetic coefficient; Based on the diagenetic facies type, determine the distribution characteristics of the diagenetic facies and predict carbonate rock diagenetic facies reservoirs.

9. The prediction method according to claim 8, characterized in that, The diagenetic facies types include: strong dissolution during the surface stage, moderate dissolution during the surface stage, weak dissolution during the surface stage, and dolomitization during the burial stage.

10. The prediction method according to claim 9, characterized in that, The correspondence between diagenetic coefficient and diagenetic facies type includes: When the diagenesis coefficient is less than 3, it corresponds to the dolomitization diagenesis facies during the burial period; When the diagenesis coefficient is 3-5, it corresponds to a weakly dissolved diagenetic facies in the supergene stage; When the diagenesis coefficient is 5-7, it corresponds to a moderately dissolved diagenetic facies in the supergene stage; When the diagenetic coefficient is greater than 7, it corresponds to the moderate dissolution diagenetic facies of the epigenetic period.

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