Carbonate formation porosity calculation method and system based on electrical imaging logging

Abstract

The application discloses a kind of based on electrical imaging logging carbonate formation porosity calculation method and system, constructs the quantitative characterization of carbonate formation porosity, realizes the accurate evaluation of carbonate formation porosity, improves the precision of carbonate reservoir physical property parameter evaluation.Precision evaluation of carbonate reservoir physical property parameter is improved.It includes the following steps: based on the polar plate data of electrical imaging logging data, calculate the full bore coverage image and carry out lateral resistivity scale after inverting, obtain the full bore coverage borehole resistivity data;According to borehole resistivity data, calculate the average value of borehole resistivity, based on the average value of borehole resistivity, calculate to obtain cementation index and lithology coefficient;Mud correction is carried out to the average value of borehole resistivity, according to the mud corrected borehole resistivity, cementation index and lithology coefficient, a formation porosity calculation model is constructed;Based on formation porosity calculation model, the porosity of carbonate formation is calculated.

Description

Technical Field

[0001] This invention belongs to the field of reservoir evaluation technology, specifically relating to a method and system for calculating the porosity of carbonate formations based on electrical imaging logging. Background Technology

[0002] Carbonate reservoirs are one of the three major oil and gas reservoirs. Due to their complex lithology, well-developed secondary porosity, and diverse reservoir space types, the complex geological characteristics of carbonate reservoirs make it difficult to accurately calculate reservoir porosity. The required precision is high but difficult to achieve.

[0003] Currently, commonly used methods for evaluating the porosity of carbonate formations include:

[0004] Quantitative evaluation of reservoir porosity based on conventional logging data typically employs a method of pairwise intersection of density logging, compensated neutron logging, and sonic transit time logging to quantitatively evaluate the porosity of carbonate reservoirs. However, this method has low accuracy. Due to the complex composition of carbonate reservoir rocks, density and compensated neutron logging results are easily affected by variations in rock composition. The development of secondary porosity, gravel, and bedding structures leads to strong porosity heterogeneity, while sonic transit time logging has a weak response to porosity. Therefore, using three-porosity logging to evaluate carbonate reservoir porosity has certain limitations. It can only provide quantitative evaluation and lacks an accurate quantitative parameter characterizing reservoir porosity. Furthermore, the evaluation results are greatly affected by the formation environment, resulting in low accuracy in evaluating carbonate formation porosity. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method and system for calculating the porosity of carbonate rock formations based on electrical imaging logging. It constructs a quantitative characterization of the porosity of carbonate rock formations, realizes accurate evaluation of the porosity of carbonate rock formations, and improves the accuracy of evaluation of the physical property parameters of carbonate rock reservoirs.

[0006] This invention is achieved through the following technical solution:

[0007] A method for calculating the porosity of carbonate formations based on electrical imaging logging includes the following steps:

[0008] Based on the electrode data of the electrical imaging logging data, the full borehole coverage image is calculated and the lateral resistivity is calibrated. The reciprocal is then taken to obtain the full borehole coverage wellbore resistivity data.

[0009] The average wellbore resistivity is calculated based on the wellbore resistivity data, and the cementation index and lithology coefficient are then calculated based on the average wellbore resistivity.

[0010] The average wellbore resistivity was corrected for clay content, and a formation porosity calculation model was constructed based on the clay-corrected wellbore resistivity, cementation index, and lithology coefficient.

[0011] The porosity of carbonate rock formations is calculated based on a formation porosity calculation model.

[0012] Preferably, after calculating the full wellbore coverage image and performing lateral resistivity calibration, each depth sampling point includes multiple data bits, some of which are displayed as null values, and null values ​​are assigned to the data bits that are displayed as null values.

[0013] Preferably, the null value assignment is set to 10000Ω·m.

[0014] Preferably, the calculation of the cementation index and lithology coefficient based on the average wellbore resistivity specifically includes:

[0015] The average wellbore resistivity was correlated one-to-one with the core analysis porosity obtained from the core repositioning experiment. Correlation analysis was used to obtain the power function relationship between the average wellbore resistivity and the core analysis porosity. Based on the power function relationship, the cementation index and lithology coefficient were calculated by inputting the mud filtrate resistivity.

[0016] Preferably, the power function relationship between the average wellbore resistivity and the core analysis porosity includes obtaining a piecewise power function relationship after performing piecewise correlation analysis based on porosity or resistivity intervals.

[0017] Preferably, the step of correcting the average resistivity of the wellbore for clay content includes:

[0018] Tight carbonate rock formations were selected as the benchmark formations, and a mudstone response equation was established based on the relationship between uranium-depleted gamma and the average wellbore resistivity.

[0019] The resistivity calculated based on the mud response equation is subtracted from the average wellbore resistivity. The difference is the resistivity value that needs to be compensated, thus completing the mud correction of the average wellbore resistivity.

[0020] Preferably, in the process of correcting the average resistivity of the wellbore wall for clay content, the formula for calculating the resistivity for clay content correction is as follows:

[0021]

[0022] In the formula, The resistivity is the resistivity after correction for clay content. This represents the average resistivity of the wellbore. The resistivity is obtained from the calculation of the mud response equation.

[0023] Preferably, the formation porosity calculation model expression is as follows:

[0024]

[0025] In the formula, Where is porosity, m is cementation index, and a is lithology coefficient. The resistivity is the resistivity after correction for clay content. The resistivity of the mud filtrate.

[0026] A system for calculating the porosity of carbonate formations based on electrical imaging logging includes:

[0027] The data acquisition module is used to calculate the full borehole coverage image based on the electrode data of the electrical imaging logging data, and after calibrating the lateral resistivity, take the reciprocal to obtain the full borehole coverage wellbore resistivity data.

[0028] The data calculation module is used to calculate the average wellbore resistivity based on the wellbore resistivity data, and to calculate the cementation index and lithology coefficient based on the average wellbore resistivity.

[0029] The model building module is used to correct the average wellbore resistivity for clay content, and to build a formation porosity calculation model based on the clay-corrected wellbore resistivity, cementation index and lithology coefficient.

[0030] The porosity calculation module is used to calculate the porosity of carbonate rock formations based on the formation porosity calculation model.

[0031] Preferably, the model building module further includes a clay correction module, which is used to correct the average wellbore resistivity using clay correction, including:

[0032] Tight carbonate rock formations were selected as the benchmark formations, and a mudstone response equation was established based on the relationship between uranium-depleted gamma and the average wellbore resistivity.

[0033] The resistivity calculated based on the mud response equation is subtracted from the average wellbore resistivity. The difference is the resistivity value that needs to be compensated, thus completing the mud correction of the average wellbore resistivity.

[0034] Compared with the prior art, the present invention has the following beneficial technical effects:

[0035] This invention provides a method for calculating the porosity of carbonate formations based on electro-imaging logging. Utilizing electrode data from electro-imaging logging, resistivity is calibrated, and the entire wellbore is covered. The reciprocal is then calculated to obtain the full-wellbore resistivity data. Because electro-imaging logging is performed at shallow depths, the wellbore is affected by mud intrusion during resistivity measurement, resulting in pores filled with mud filtrate. The full-wellbore resistivity data used in this invention conforms to the formation factor formula. Based on this formula, using mud filtrate resistivity as a coefficient, the inverse of the cementation index as an exponent, and porosity as the independent variable, an analytical method is established to analyze the relationship between porosity and average wellbore resistivity. Using the power function as a calculation model for the porosity of carbonate formations, a quantitative characterization of porosity can be obtained. Furthermore, to further improve calculation accuracy, this invention, based on dense carbonate formations with high clay content, utilizes the relationship between regional clay content and resistivity to perform clay correction on the obtained wellbore average resistivity. Finally, based on clay content, a porosity calculation model is selected for each zone and layer, and the porosity of the carbonate formation is calculated according to the corrected wellbore average resistivity. This completes the continuous calculation of carbonate formation porosity, achieving accurate evaluation of carbonate formation porosity and improving the accuracy of carbonate reservoir physical property parameter evaluation.

[0036] Compared to traditional conventional three-porosity logging for calculating formation porosity, this invention has the advantage of heterogeneous dissolved porosity. It achieves quantitative calculation of carbonate formation porosity through four steps, with higher accuracy than conventional logging. Compared to nuclear magnetic resonance logging, the method for calculating porosity is not affected by formation gas content, and has higher vertical resolution and calculation accuracy. It has a wider range of applications, strong practicality, and guiding significance for well logging exploration and evaluation. Attached Figure Description

[0037] Figure 1 This is a flowchart of the calculation process for the porosity of carbonate rock formations according to the present invention;

[0038] Figure 2 This is a graph showing the relationship between the average resistivity and porosity in an embodiment of the present invention (R). t (Full range)

[0039] Figure 3 This is a graph showing the relationship between the average resistivity and porosity in an embodiment of the present invention (R). t <1500Ω·m);

[0040] Figure 4 This is a graph showing the relationship between the average resistivity and the deionized gamma in an embodiment of the present invention (area A).

[0041] Figure 5 This is a graph showing the relationship between the average resistivity and the deionized gamma in an embodiment of the present invention (region B).

[0042] Figure 6 This is a diagram showing the calculated porosity of the dolomite layer in an embodiment of the present invention;

[0043] Figure 7 This is a diagram showing the calculated porosity of the entire carbonate rock formation in an embodiment of the present invention. Detailed Implementation

[0044] The principles and features of the present invention will be further described in detail below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clearly illustrate the purpose of the embodiments of the present invention.

[0045] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or it can be in a centered component. When a component is said to be "connected to" another component, it can be directly connected to the other component or it may also be in a centered component. When a component is said to be "set to" another component, it can be directly set on the other component or it may also be in a centered component.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0047] This invention provides a method for calculating the porosity of carbonate formations based on electrical imaging logging, such as... Figure 1 As shown, it includes the following steps:

[0048] Based on the electrode data of the electrical imaging logging data, the full borehole coverage image is calculated and the lateral resistivity is calibrated. The reciprocal is then taken to obtain the full borehole coverage wellbore resistivity data.

[0049] The average wellbore resistivity is calculated based on the wellbore resistivity data, and the cementation index and lithology coefficient are then calculated based on the average wellbore resistivity.

[0050] The average wellbore resistivity was corrected for clay content, and a formation porosity calculation model was constructed based on the clay-corrected wellbore resistivity, cementation index, and lithology coefficient.

[0051] The porosity of carbonate rock formations is calculated based on a formation porosity calculation model.

[0052] This invention designs a method for calculating the porosity of carbonate formations based on electro-imaging logging. Utilizing electrode data from electro-imaging logging, resistivity is calibrated, and the entire wellbore is covered. The reciprocal is then taken to obtain the full-wellbore resistivity data. Because electro-imaging logging is shallow, the wellbore is affected by mud intrusion during resistivity measurement, and the pores are saturated with mud filtrate. The full-wellbore resistivity data used in this invention conforms to the formation factor formula. Based on this formula, using mud filtrate resistivity as a coefficient, the inverse of the cementation index as an exponent, and porosity as the independent variable, an analytical method is established to analyze the relationship between porosity and average wellbore resistivity. Using the power function of the coefficient of performance as a calculation model for the porosity of carbonate formations, a quantitative characterization of porosity can be obtained. Furthermore, to further improve calculation accuracy, this invention, based on dense carbonate formations with high clay content, utilizes the relationship between regional clay content and resistivity to perform clay correction on the obtained wellbore average resistivity. Finally, based on clay content, a porosity calculation model is selected for each zone and layer, and the porosity of the carbonate formation is calculated according to the corrected wellbore average resistivity. This completes the continuous calculation of carbonate formation porosity, achieving accurate evaluation of carbonate formation porosity and improving the accuracy of carbonate reservoir physical property parameter evaluation.

[0053] This invention also provides a system for calculating the porosity of carbonate formations based on electrical imaging logging, comprising:

[0054] The data acquisition module is used to calculate the full borehole coverage image based on the electrode data of the electrical imaging logging data, and after calibrating the lateral resistivity, take the reciprocal to obtain the full borehole coverage wellbore resistivity data.

[0055] The data calculation module is used to calculate the average wellbore resistivity based on the wellbore resistivity data, and to calculate the cementation index and lithology coefficient based on the average wellbore resistivity.

[0056] The model building module is used to correct the average wellbore resistivity for clay content, and to build a formation porosity calculation model based on the clay-corrected wellbore resistivity, cementation index and lithology coefficient.

[0057] The porosity calculation module is used to calculate the porosity of carbonate rock formations based on the formation porosity calculation model.

[0058] Specifically, the technical principle of the present invention regarding a method for calculating the porosity of carbonate formations based on electrical imaging logging is as follows:

[0059] Using electrode data from electrical imaging logging, resistivity is calibrated across the entire wellbore. The reciprocal is then taken to obtain the wellbore resistivity data covering the entire wellbore. The average wellbore resistivity at each depth point is then calculated. In pure dolomite formations, based on formation factor formulas, a power function is established between analytical porosity and average wellbore resistivity using mud filtrate resistivity, average wellbore resistivity, and core analysis porosity. This yields the cementation index *m* and the lithology coefficient *a*. This power function is the porosity calculation formula for pure dolomite formations and can be used to calculate the porosity of dolomite formations.

[0060] In carbonate rock formations with high clay content, wellbore resistivity depends on clay content, porosity, and mud filtrate resistivity. By utilizing the relationship between regional clay content and resistivity, clay correction is applied to the average wellbore resistivity. Then, based on the porosity formula for pure dolomite formations, the porosity of clay carbonate rock formations is calculated using the clay-corrected average wellbore resistivity.

[0061] Finally, based on the mud content, porosity formulas were selected for dolomite and argillaceous dolomite strata to achieve continuous calculation of porosity in carbonate rock strata.

[0062] Example

[0063] This invention provides an embodiment, the specific implementation of which is as follows:

[0064] Step 1: Using the electrode data from electrical imaging logging, after resistivity calibration, the entire wellbore is covered to obtain the wellbore resistivity data, and the average wellbore resistivity at each depth point is calculated.

[0065] On the existing software platform, calculate the full borehole coverage image of electrical imaging, and then perform lateral resistivity calibration. 360 calibration data are obtained for each depth point. Take the reciprocal to obtain 360 resistivity data. Calculate the average value of the 360 ​​resistivity data, where the null value is assigned a value of 10000 Ω·m.

[0066] It should be further clarified that after full wellbore coverage processing, each sampling point has 360 data bits. However, not all data bits are actual data. In tight carbonate rock formations, some electrode measurements are very low and appear as null values. During the conversion of the reciprocal to resistivity, this cannot be calculated. Therefore, when a measurement is null, the converted resistivity of that electrode is assigned a value of 10000 Ω·m. The reason for using 10000 Ω·m is that the porosity corresponding to 10000 Ω·m is less than 1 P.U., indicating extremely low rock porosity. Using 10000 Ω·m to replace the porosity assessment error conforms to industry standards. Secondly, it ensures uniformity in null value selection and facilitates calculation.

[0067] Step 2: In the pure dolomite strata, the cementation index and lithology coefficient are obtained by using the power function relationship between the mean resistivity of electrical imaging and the porosity of core analysis.

[0068] After the core was returned to its original position, the average resistivity of the wellbore calculated by well logging was matched one-to-one with the porosity of the core analysis, and then the power function relationship was obtained through correlation analysis.

[0069] It should be further noted that, for a specific reservoir, the power function relationship obtained over the entire porosity or resistivity range may not be optimal. Power function correlation analysis can be performed for each porosity or resistivity interval to obtain the optimal relationship. In other words, the relationship between the mean resistivity of electrical imaging and the porosity of core analysis can be expressed as a piecewise power function.

[0070] like Figure 2 As shown, the cementation index m is 2.732 over the entire resistivity range.

[0071] Because the calculation error is relatively large for low resistivity and high porosity reservoirs across the entire resistivity range, a piecewise power function relationship is established for the mean resistivity of electrical imaging and the analysis of porosity below 1500 Ω·m. This yields a cementation index m value of 2.092. Figure 3 As shown.

[0072] Depend on Figure 3 It can be seen that when the resistivity is less than 1500 Ω·m, The value is 0.6969;

[0073] Depend on Figure 2 It can be seen that the total resistivity range The value is 0.3856. The lithology coefficient can be obtained by inputting the resistivity of the mud filtrate. a .

[0074] The cementation index m and lithology coefficient were obtained. a Then, the relationship between porosity and average resistivity of the wellbore is obtained: ;

[0075] In the formula, Where is porosity, m is cementation index, and a is lithology coefficient. The resistivity is the resistivity after correction for clay content. The resistivity of the mud filtrate.

[0076] Step 3: In carbonate rock formations with high clay content, the average resistivity of the wellbore is corrected for clay content by utilizing the relationship between clay content and resistivity in the dense carbonate rock formations of this region.

[0077] A tight dolomite formation with a porosity of 0.5 PU and an average wellbore resistivity of 7155 Ω·m was selected as the benchmark formation. Then, based on the relationship between uranium-removed gamma (instead of clay content) and the mean resistivity, clay response equations were established for each zone.

[0078] It should be further clarified that the principle for selecting the benchmark formation is that the benchmark formation must be a tight carbonate rock formation. Only by using this formation as a reference can the extent of the resistivity decrease caused by the clay content be determined. The tight dolomite formation with a porosity of 0.5 PU and an average wellbore resistivity of 7155 Ω·m is only a standard formation selected in this area, and the standard formation does not have to be uniform in all areas.

[0079] The reason for choosing uranium-reduced gamma (instead of clay content) to establish its relationship with the mean resistivity, instead of natural gamma, is that high uranium content in some carbonate rock formations leads to high natural gamma, and the increase in natural gamma is not a response to high clay content. Choosing uranium-reduced gamma instead of clay content avoids the aforementioned problems.

[0080] like Figure 4 As shown, the mud response equation for region A is resistivity. ,like Figure 5 As shown, the mud response equation for region B is resistivity. The resistivity calculated based on the clay response equation is the decrease in resistivity caused by clay content compared to dense dolomite formations. This value is the resistivity value that needs to be compensated for compared to the reference formation for the current measured resistivity.

[0081] Therefore, the formula for calculating resistivity for mud correction (compensation) is:

[0082] ;

[0083] In the formula, The mean resistivity of the wellbore measured by electrical imaging, in Ω·m; ν is the resistivity after correction for mud quality, in Ω·m.

[0084] After clay correction, the clay strata are converted into dolomite strata. Then, based on the corrected resistivity and the relationship between dolomite porosity and resistivity, the porosity of the clay-dolomite strata is calculated.

[0085] Step 4: Based on the mud content, select the porosity formula for dolomite and argillaceous dolomite strata to achieve continuous calculation of the porosity of carbonate rock strata.

[0086] Using uranium-depleted gamma ray (GAR) of 20 API as a boundary, when the GAR is below 20 API, the porosity calculation formula for pure dolomite formations is selected; when the GAR is not below 20 API, the wellbore average resistivity is first corrected for clay content, and then the porosity is calculated using the pure dolomite formation porosity formula. This achieves porosity calculation for the entire formation. The calculation results obtained in this embodiment are as follows: Figure 6 and Figure 7 The figures shown are the porosity calculation results for the dolomite layer and the entire carbonate rock strata, respectively.

[0087] It should be further noted that when the clay content is low, the resistivity change caused by clay content is small, and the resistivity change caused by porosity is dominant. In this case, clay content correction is not required. When the clay content is high, clay content correction is necessary. The uranium-depleted gamma-20API was chosen as the correction starting point for the study area, but this is only an empirical parameter for this region, and the parameters may vary for reservoirs in different areas.

[0088] This invention determines the average wellbore resistivity at each depth point in the formation through step 1. Through step 2, in pure dolomite formations, the cementation index and lithology coefficient are obtained by utilizing the power function relationship between the average resistivity of electrical imaging and the porosity of core analysis. Through step 3, the clay content is corrected for the average wellbore resistivity. Through step 4, based on the clay content, porosity formulas are selected for dolomite and argillaceous dolomite formations to achieve continuous calculation of porosity in carbonate rock formations.

[0089] In well logging series, conventional three-porosity logging can calculate formation porosity, nuclear magnetic resonance logging can calculate formation porosity, and electrical imaging logging can identify the porosity of carbonate formations. This invention leverages the advantage of electrical imaging logging in identifying carbonate reservoir porosity, especially heterogeneous dissolution porosity, and achieves quantitative calculation of carbonate formation porosity through four steps. Compared with conventional logging, it offers higher accuracy. Compared with nuclear magnetic resonance logging, this porosity calculation method is unaffected by formation gas content and features higher vertical resolution and calculation accuracy.

[0090] In summary, this invention provides a method for calculating the porosity of carbonate formations based on electrical imaging logging. This method can accurately and quantitatively evaluate the porosity of carbonate reservoirs, overcoming the shortcomings of conventional three-porosity logging methods for evaluating carbonate reservoir porosity. Core analysis verification confirms that this invention can accurately evaluate the porosity of carbonate reservoirs.

[0091] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Those skilled in the art can readily implement the present invention based on the accompanying drawings and the above description. However, any modifications, alterations, or variations made by those skilled in the art without departing from the scope of the present invention, utilizing the disclosed technical content, are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, or variations made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the present invention.

Claims

1. A method for calculating the porosity of carbonate formations based on electrical imaging logging, characterized in that, Includes the following steps: Based on the electrode data of the electrical imaging logging data, the full borehole coverage image is calculated and the lateral resistivity is calibrated. The reciprocal is then taken to obtain the full borehole coverage wellbore resistivity data. The average wellbore resistivity is calculated based on the wellbore resistivity data, and the cementation index and lithology coefficient are then calculated based on the average wellbore resistivity. The average wellbore resistivity was corrected for clay content, and a formation porosity calculation model was constructed based on the clay-corrected wellbore resistivity, cementation index, and lithology coefficient. Calculate the porosity of carbonate rock formations based on a formation porosity calculation model; The calculation of the cementation index and lithology coefficient based on the average wellbore resistivity specifically includes: The average wellbore resistivity is matched one-to-one with the core analysis porosity obtained from the core repositioning experiment. Correlation analysis is used to obtain the power function relationship between the average wellbore resistivity and the core analysis porosity. Based on the power function relationship, the cementation index and lithology coefficient are calculated by inputting the mud filtrate resistivity. The power function relationship between the average resistivity of the wellbore and the porosity of the core analysis includes a piecewise power function relationship obtained after performing piecewise correlation analysis based on the porosity interval or resistivity interval. The mud correction for the average resistivity of the wellbore includes: Tight carbonate rock formations were selected as the benchmark formations, and a mudstone response equation was established based on the relationship between uranium-depleted gamma and the average wellbore resistivity. The resistivity calculated based on the mud response equation is subtracted from the average wellbore resistivity. The difference is the resistivity value that needs to be compensated, thus completing the mud correction of the average wellbore resistivity. The expression for the formation porosity calculation model is as follows: In the formula, Where is porosity, m is cementation index, and a is lithology coefficient. The resistivity is the resistivity after correction for clay content. The resistivity of the mud filtrate.

2. The method for calculating the porosity of carbonate formations based on electrical imaging logging according to claim 1, characterized in that, After calculating the full wellbore coverage image and performing lateral resistivity calibration, each depth sampling point includes multiple data bits, some of which are displayed as null values. Null values ​​are assigned to the data bits that are displayed as null values.

3. The method for calculating the porosity of carbonate formations based on electrical imaging logging according to claim 2, characterized in that, The null value is set to 10000Ω·m.

4. The method for calculating the porosity of carbonate formations based on electrical imaging logging according to claim 1, characterized in that, In the process of correcting the average resistivity of the wellbore for clay content, the formula for calculating the resistivity for clay content correction is as follows: In the formula, The resistivity is the resistivity after correction for clay content. This represents the average resistivity of the wellbore. The resistivity is obtained from the calculation of the mud response equation.

5. A system for calculating the porosity of carbonate formations based on electrical imaging logging, characterized in that, include: The data acquisition module is used to calculate the full borehole coverage image based on the electrode data of the electrical imaging logging data, and after calibrating the lateral resistivity, take the reciprocal to obtain the full borehole coverage wellbore resistivity data. The data calculation module is used to calculate the average wellbore resistivity based on the wellbore resistivity data, and to calculate the cementation index and lithology coefficient based on the average wellbore resistivity. The model building module is used to correct the average wellbore resistivity for clay content, and to build a formation porosity calculation model based on the clay-corrected wellbore resistivity, cementation index and lithology coefficient. The porosity calculation module is used to calculate the porosity of carbonate rock formations based on the formation porosity calculation model. The calculation of the cementation index and lithology coefficient based on the average wellbore resistivity specifically includes: The average wellbore resistivity is matched one-to-one with the core analysis porosity obtained from the core repositioning experiment. Correlation analysis is used to obtain the power function relationship between the average wellbore resistivity and the core analysis porosity. Based on the power function relationship, the cementation index and lithology coefficient are calculated by inputting the mud filtrate resistivity. The power function relationship between the average resistivity of the wellbore and the porosity of the core analysis includes a piecewise power function relationship obtained after performing piecewise correlation analysis based on the porosity interval or resistivity interval. The mud correction for the average resistivity of the wellbore includes: Tight carbonate rock formations were selected as the benchmark formations, and a mudstone response equation was established based on the relationship between uranium-depleted gamma and the average wellbore resistivity. The resistivity calculated based on the mud response equation is subtracted from the average wellbore resistivity. The difference is the resistivity value that needs to be compensated, thus completing the mud correction of the average wellbore resistivity. The expression for the formation porosity calculation model is as follows: In the formula, Where is porosity, m is cementation index, and a is lithology coefficient. The resistivity is the resistivity after correction for clay content. The resistivity of the mud filtrate.

6. The system for calculating the porosity of carbonate formations based on electrical imaging logging according to claim 5, characterized in that, The model building module also includes a clay correction module, which is used to correct the average wellbore resistivity using clay correction, including: Tight carbonate rock formations were selected as the benchmark formations, and a mudstone response equation was established based on the relationship between uranium-depleted gamma and the average wellbore resistivity. The resistivity calculated based on the mud response equation is subtracted from the average wellbore resistivity. The difference is the resistivity value that needs to be compensated, thus completing the mud correction of the average wellbore resistivity.

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