A method and system for constructing a carbonate pore diameter spectrum based on electro-imaging logging

Abstract

The application discloses a kind of based on electrical imaging logging carbonate rock pore diameter spectrum construction method and system, can improve the accuracy of carbonate rock reservoir physical property identification, accurately realize carbonate rock reservoir pore diameter evaluation. Including the following steps: based on formation factor formula, utilize the mean of electrical resistivity in electrical imaging logging data, porosity, reservoir lithology coefficient to calculate pore cementation index;Pore cementation index is scaled with pore diameter in homogeneous pore formation, and the relationship between pore cementation index and pore diameter is established;Based on the relationship between pore cementation index and pore diameter, pore diameter data are calculated and obtained;According to pore diameter data, pore diameter spectrum data are calculated and obtained, in logarithmic channel display, pore diameter spectrum construction is completed.

Description

Technical Field

[0001] This invention belongs to the field of reservoir evaluation technology, specifically relating to a method and system for constructing pore diameter spectra of carbonate rocks based on electrical imaging logging. Background Technology

[0002] Carbonate reservoirs are characterized by a variety of reservoir space types, large variations in pore size, and difficulty in quantitatively evaluating reservoir physical parameters.

[0003] Currently, in existing technologies, the methods for evaluating the physical properties of carbonate reservoirs based on well logging data are generally based on density logging, compensated neutron logging, and sonic transit time three-porosity logging. Three-porosity logging has relatively high accuracy in evaluating the porosity of carbonate reservoirs, but it has low accuracy in constructing pore diameter spectra and evaluating permeability. This is because the pore size of the reservoir varies greatly, making it difficult to accurately construct a pore diameter spectrum that can reflect the changes in pore size.

[0004] Therefore, there is currently no way to accurately evaluate the pore diameter of carbonate reservoirs. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method and system for constructing carbonate reservoir pore diameter spectra based on electrical imaging logging, which can improve the accuracy of carbonate reservoir property identification and accurately evaluate the pore diameter of carbonate reservoirs.

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

[0007] A method for constructing pore diameter spectra of carbonate rocks based on electrical imaging logging includes the following steps:

[0008] Based on the formation factor formula, the porosity cementation index is calculated using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data.

[0009] The relationship between the pore cementation index and pore diameter was established by calibrating the pore cementation index and pore diameter in homogeneous porous formations.

[0010] Based on the relationship between pore cementation index and pore diameter, pore diameter data is calculated and obtained.

[0011] The pore diameter spectrum data is calculated based on the pore diameter data and displayed in logarithmic channels, thus completing the construction of the pore diameter spectrum.

[0012] Preferably, the calculation of the porosity cementation index based on the formation factor formula and using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data includes:

[0013] Based on rock electrical experiments, the average resistivity of the wellbore in carbonate reservoirs was obtained, and the porosity and lithology coefficients were analyzed.

[0014] The relationship between average resistivity of the wellbore in carbonate reservoirs, porosity, lithology coefficient and cementation index was obtained by using the formation factor formula.

[0015] The porosity cementation index is calculated based on the relational formula.

[0016] Preferably, the formula for calculating the porosity cementation index is:

[0017]

[0018] In the formula, m is the porosity cementation index, φ is the porosity, and R is the porosity index. a R is the average resistivity of the wellbore at a certain depth in the formation. a <1500, 0.6969 is the product of the resistivity of the mud filtrate and the lithology coefficient.

[0019] Preferably, obtaining the average resistivity of the electro-imaging includes:

[0020] After calibrating the lateral resistivity of the electrical imaging logging data and covering the entire wellbore, the reciprocal is calculated. Then, the average value of the 360 ​​wellbore resistivity data points at each depth point is obtained to obtain the mean electrical imaging resistivity.

[0021] Preferably, in the calibration of the pore cementation index and pore diameter in a homogeneous porous formation, the acquisition of the pore diameter includes:

[0022] For rock samples with pore diameters less than 1 μm, the pore diameter is obtained by calculating the displacement pressure in the mercury intrusion porosimetry experiment;

[0023] For rock samples with pore diameters between 1 μm and 1000 μm, the pore diameter is obtained by reading the pore diameter of the pore casting thin section;

[0024] For rock samples with pore diameters greater than 1000 μm, the pore diameters are obtained through on-site core measurements.

[0025] Preferably, the relationship between the pore cementation index and the pore diameter is expressed as follows:

[0026] D por =43276e -3.156m

[0027] In the formula D por denoted as pore diameter, and m as cementation index.

[0028] Preferably, the step of calculating and obtaining pore diameter spectrum data based on pore diameter data, displaying it in logarithmic channels, and completing the pore diameter spectrum construction specifically includes:

[0029] The pore diameter data at each depth point in the formation were divided into 25 intervals, and the distribution of pore diameter data in each interval was statistically analyzed.

[0030] The statistical results for each interval are normalized.

[0031] The statistical result of each interval is multiplied by the porosity component of the corresponding interval and summed to obtain the porosity of that interval;

[0032] Based on the distribution of pore diameter data and porosity, the data is displayed in the logarithmic interval to form a pore diameter spectrum.

[0033] A system for constructing pore diameter spectra of carbonate rocks based on electrical imaging logging includes:

[0034] The cementation index calculation module is used to calculate the pore cementation index based on the formation factor formula and using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data.

[0035] The cementation index-pore diameter relationship module is used to calibrate the pore cementation index and pore diameter in homogeneous porous formations and establish the relationship between the pore cementation index and pore diameter.

[0036] The pore diameter data acquisition module is used to calculate and acquire pore diameter data based on the relationship between pore cementation index and pore diameter.

[0037] The pore diameter spectrum construction module is used to calculate and obtain pore diameter spectrum data based on pore diameter data, and display it in logarithmic channels. Once the pore diameter spectrum construction is complete, the pore diameter spectrum is constructed.

[0038] Compared with the prior art, the present invention has the following beneficial technical effects:

[0039] This invention provides a method for constructing a pore diameter spectrum for carbonate rocks based on electro-imaging logging. Among existing logging series, electro-imaging logging images can intuitively reflect the pore size of carbonate reservoirs, offering a direct and reliable representation. According to electro-imaging logging data, the resistivity of carbonate formations is determined by porosity, mud filtrate resistivity, and cementation index. The cementation index reflects the tortuosity of reservoir pores. In carbonate formations, porosity tortuosity depends on the pore type, i.e., pore size. Therefore, based on formation factor formulas, the pore cementation index is calculated using the mean resistivity, porosity, and reservoir lithology coefficient from electro-imaging logging data. Then, the cementation index and pore diameter are calibrated in homogeneous porous formations to establish a relationship between the cementation index and pore diameter, allowing for the calculation of the pore diameter. At the same depth point, the frequency distribution of pores is statistically analyzed according to their size, normalized, and then multiplied by porosity to obtain pore diameter spectrum data. This data is then displayed in logarithmic channels to construct a pore diameter spectrum for pore size evaluation. This approach enables accurate evaluation of pore size in carbonate formations and improves the accuracy of evaluating the physical properties of carbonate reservoirs. Attached Figure Description

[0040] Figure 1 This is a flowchart of the construction process of the carbonate rock pore diameter spectrum of the present invention;

[0041] Figure 2 This is a graph showing the relationship between the bonding index and the pore diameter in an embodiment of the present invention;

[0042] Figure 3 This is a diagram showing the calculated pore diameter spectrum of dolomite reservoirs in an embodiment of the present invention;

[0043] Figure 4 This is a diagram showing the calculated pore diameter spectrum of carbonate rocks across the entire 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 constructing pore diameter spectra of carbonate rocks based on electrical imaging logging, such as... Figure 1 As shown, it includes the following steps:

[0048] Based on the formation factor formula, the porosity cementation index is calculated using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data.

[0049] The relationship between the pore cementation index and pore diameter was established by calibrating the pore cementation index and pore diameter in homogeneous porous formations.

[0050] Based on the relationship between pore cementation index and pore diameter, pore diameter data is calculated and obtained.

[0051] The pore diameter spectrum data is calculated based on the pore diameter data and displayed in logarithmic channels, thus completing the construction of the pore diameter spectrum.

[0052] This invention designs a method for constructing pore diameter spectra in carbonate rocks based on electro-imaging logging. Among existing logging series, electro-imaging logging images can intuitively reflect the pore size of carbonate reservoirs, offering a direct and reliable representation. According to electro-imaging logging data, the resistivity of carbonate formations is determined by porosity, mud filtrate resistivity, and cementation index. The cementation index reflects the tortuosity of reservoir pores; in carbonate formations, porosity tortuosity depends on pore type, i.e., pore size. Therefore, based on formation factor formulas, the pore cementation index is calculated using the mean resistivity, porosity, and reservoir lithology coefficient from electro-imaging logging data. Then, the cementation index and pore diameter are calibrated in homogeneous porous formations to establish the relationship between the cementation index and pore diameter, allowing for the calculation of the pore diameter. At the same depth point, the frequency distribution of pores is statistically analyzed according to their size, normalized, and then multiplied by porosity to obtain pore diameter spectrum data. This data is then displayed in logarithmic channels to construct a pore diameter spectrum for pore size evaluation. This approach enables accurate evaluation of pore size in carbonate formations and improves the accuracy of evaluating the physical properties of carbonate reservoirs.

[0053] Specifically, this invention utilizes electrode data from electrical imaging logging, calibrated with resistivity, and covers the entire wellbore to obtain the average resistivity of the wellbore wall. A homogeneous pore size formation is selected, and based on the formation factor formula, the core cementation index is calculated using the lithology coefficient of the dolomite reservoir in this area, analytical porosity, and the average resistivity of the wellbore wall. Then, a relationship is established between the cementation index and the average pore diameter of the cast thin section, which can be used to calculate the pore size. After full wellbore coverage by electrical imaging, 360 resistivity data points are obtained at each depth. Based on the formation factor formula and the porosity calculated from the average resistivity, 360 cementation indices can be calculated for each depth point, which are then converted into 360 pore diameter data points. At the same depth point, the frequency distribution of these data is statistically analyzed according to pore size, normalized, and then multiplied by the porosity to obtain the pore diameter spectrum data. This spectrum is then displayed in logarithmic channels.

[0054] The specific implementation steps are divided into the following five steps:

[0055] Step one: Based on rock electrical experiments, the relationship between the average resistivity of the wellbore, analytical porosity, lithology coefficient, and cementation index of carbonate reservoirs can be obtained through formation factor formulas, and the cementation index can be calculated. In the study area of ​​this invention, the average resistivity of the wellbore R... a When the lithology coefficient is less than 1500 Ω·m, and the average value of the regional reservoir is taken as the lithology coefficient, the empirical formulas for the average porosity and resistivity relative to the m value are as follows:

[0056]

[0057] In the formula, φ is porosity (%); Ra is the average resistivity of the wellbore (Ω·m); and 0.6969 is the product of the resistivity of the mud filtrate and the lithology coefficient, which is taken as the average value of the regional reservoir.

[0058] Step 2: Based on homogeneous porous formations, establish the relationship between the cementation index and pore diameter.

[0059] Select homogeneous porous formations and read the pore diameters from reservoir pore castings. For reservoirs with large variations in pore diameter, or those whose pore diameters exceed the observation range of pore castings, the principle of "what you see is what you get" should be followed, and the pore diameters should be determined by combining mercury intrusion porosimetry, pore casting, and core observations.

[0060] During the specific operation, attention should be paid to matching the pore size with the rock sample size and the observation field of the polarizing microscope for different experimental data. The sampling size of the pore casting thin section is a 25mm×5mm plunger sample or a 25mm×25mm×5mm non-plunger sample, and the observation field is 1~1.5mm.

[0061] The pore diameter is read as follows: for rock samples with a pore diameter less than 1 μm, the pore diameter is calculated from the displacement pressure in the mercury intrusion porosimetry experiment; for rock samples with a pore diameter between 1 μm and 1000 μm, the pore diameter is obtained from the pore casting thin section; for rock samples with a pore diameter greater than 1000 μm, the pore diameter is obtained from the core sample measured in the field.

[0062] After obtaining the pore diameter of the homogeneous porous rock sample, the relationship between the cementation index obtained in step one and the pore diameter is established. The relationship between pore diameter and cementation index in the study area is as follows:

[0063] D por =43276e -3.156m .

[0064] In the formula D por Where is the pore diameter, in μm; m is the rock sample cementation index;

[0065] Step 3: Calculate the cementation index and pore diameter based on the electrical imaging resistivity data.

[0066] The entire stratum is divided into multiple depth points. Based on the resistivity data and average porosity of each depth point, the cementation index corresponding to each depth point is calculated according to the above relationship.

[0067] In one embodiment of the present invention, the formula for calculating the bonding index is as follows:

[0068] In the formula, m1-360 represents 360 cementation indices calculated at the same depth point in one embodiment of the present invention; R1-360 represents 360 wellbore resistivity data (Ω·m) obtained by electrical imaging logging at each depth point of the formation after shallow lateral calibration in one embodiment of the present invention. The average porosity calculated for point electrical imaging at this depth is %.

[0069] Based on the relationship between the cementation index and the pore diameter obtained in step two, the corresponding pore diameter can be obtained for each depth point.

[0070] Step 4: Calculate the frequency according to the pore diameter and perform normalization processing.

[0071] After obtaining the corresponding pore diameter at each depth point, divide it into 10... -1 10 0 10 1 10 2 10 3 10 4Five intervals were created, and each interval was further divided into five intervals, for a total of 25 intervals. The pore diameter distribution corresponding to each depth point was statistically analyzed. After the statistics were compiled, the statistical value of each interval was divided by the total number of depth points, and the sum of the statistical values ​​of each interval was 1. The statistical result of each interval was then multiplied by the porosity component (decimal), and the sum of the porosity (decimal) of each interval was obtained.

[0072] Step 5: Display the aperture distribution spectrum in the logarithmic interval.

[0073] In this invention, step one, based on the formation factor formula from rock electrical experiments, yields a method for calculating the cementation index. Step two, based on homogeneous porous formations, establishes the relationship between the cementation index and pore diameter, which is the core technology of this invention. Step three, based on 360 electrical imaging resistivity data points at each depth, calculates 360 cementation indices (the number of depth points divided in one embodiment of this invention) and pore diameters. Step four then generates a pore diameter spectrum, where the horizontal axis represents the pore diameter of the rock sample, and the vertical axis represents the porosity component corresponding to each pore diameter interval. Unlike existing methods that qualitatively characterize carbonate rock pore structures through electrical imaging logging or by using logging parameters, this invention achieves a method for quantitatively characterizing carbonate rock formation pore structure parameters through electrical imaging logging.

[0074] In summary, this invention provides a carbonate rock pore diameter spectrum constructed based on an electrical imaging logging method. This spectrum can determine the pore diameter distribution of carbonate rock formations and the porosity of different pore diameter ranges, and can accurately determine the pore structure parameters of carbonate rock formations.

[0075] This invention also provides a system for constructing carbonate rock pore diameter spectra based on electrical imaging logging, used to implement the method for constructing carbonate rock pore diameter spectra based on electrical imaging logging described in this invention, comprising:

[0076] The cementation index calculation module is used to calculate the pore cementation index based on the formation factor formula and using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data.

[0077] The cementation index-pore diameter relationship module is used to calibrate the pore cementation index and pore diameter in homogeneous porous formations and establish the relationship between the pore cementation index and pore diameter.

[0078] The pore diameter data acquisition module is used to calculate and acquire pore diameter data based on the relationship between pore cementation index and pore diameter.

[0079] The pore diameter spectrum construction module is used to calculate and obtain pore diameter spectrum data based on pore diameter data, and display it in logarithmic channels. Once the pore diameter spectrum construction is complete, the pore diameter spectrum is constructed. Specific Implementation

[0081] Step 1: Calculate the cementation index based on the relationship between the average resistivity of the wellbore, analytical porosity, lithology coefficient, and cementation index of the carbonate reservoir. In the study area of ​​this invention, the average resistivity of the wellbore R... a When the value is <1500Ω·m, the empirical formulas for the mean porosity and resistivity relative to the value of m are:

[0082]

[0083] In the formula, φ is porosity (%); Ra is the average resistivity of the wellbore (Ω·m); and 0.6969 is the product of the resistivity of the mud filtrate and the lithology coefficient, which is taken as the average value of the regional reservoir.

[0084] Step two, based on homogeneous porous formations, establish the relationship between the cementation index and pore diameter, such as... Figure 2 As shown.

[0085] Select homogeneous porous formations and read the pore diameter of reservoir thin sections. For reservoirs with large variations in pore diameter, or those whose pore diameter exceeds the observation range of thin sections, the principle of "what you see is what you get" should be followed, and the pore diameter should be determined by combining mercury intrusion porosimetry, cast thin sections, and core observations.

[0086] In the study area of ​​this invention, based on the characteristics of carbonate reservoirs, the Ma Wu reservoir in area E was selected. 1+2 Dense dolomite strata with a porosity of less than 3% were selected as the fine intercrystalline pore grading strata. These strata have a small number of intercrystalline pores with small diameters and are relatively homogeneous. The Ma-5 dolomite strata in S area were selected as the medium-sized intercrystalline solution pore grading strata. Ma-54, Ma-56, and Ma-59 in S area were selected as the solution pore and cavern grading strata with the largest pore sizes.

[0087] Based on the above method for determining pore diameter, the cementation index and pore diameter are matched and calculated to establish the relationship between the cementation index and pore diameter.

[0088] The formula for calculating pore diameter is D. por =43276e -3.156m , μm, where D por denoted as pore diameter in μm; m is the rock sample cementation index.

[0089] Step 3: Calculate the cementation index and pore diameter based on the electrical imaging resistivity data.

[0090] Based on the resistivity data and average porosity of 360 points at each depth, and based on the above relationship, 360 cementation indices are calculated for each depth.

[0091] Formula for calculating 360 bonding indices:

[0092] In the formula, m1-360 represents 360 cementation indices calculated at the same depth point; R1-360 represents 360 wellbore resistivity data (Ω·m) obtained from electrical imaging logging at each depth point of the formation after shallow lateral calibration. The average porosity calculated for point electrical imaging at this depth is %.

[0093] Based on the relationship between the cementation index and the pore diameter obtained in step two, 360 pore diameters can be obtained for each depth point.

[0094] Step 4: Calculate the frequency according to the pore diameter and perform normalization processing.

[0095] After obtaining 360 pore diameters at each depth point, divide into 10 -1 10 0 10 1 10 2 10 3 10 4 Five intervals were created, and each interval was further divided into five intervals, for a total of 25 intervals. The distribution of 360 pore diameters was statistically analyzed, as shown in the table below. After statistical analysis, the statistical value of each interval was divided by 360, and the sum of the statistical values ​​for each interval was 1. The statistical result of each interval was then multiplied by the porosity component (decimal), and the sum of the porosity (decimal) for each interval was obtained.

[0096] Aperture Range Statistics Table

[0097]

[0098] Step 5: Display the aperture distribution spectrum in the logarithmic interval.

[0099] The technical implementation steps involved in this patent are completed in independent software. Through the above steps, a pore diameter spectrum of carbonate rock formations is formed, such as... Figure 3 and Figure 4 The figures shown are the calculated pore diameter spectrum of the dolomite reservoir and the calculated pore diameter spectrum of the entire carbonate formation, respectively, in this embodiment.

[0100] 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 constructing pore diameter spectra of carbonate rocks based on electrical imaging logging, characterized in that, The steps include the following: Based on the formation factor formula, the porosity cementation index is calculated using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data. The relationship between the pore cementation index and pore diameter was established by calibrating the pore cementation index and pore diameter in homogeneous porous formations. Based on the relationship between pore cementation index and pore diameter, pore diameter data is calculated and obtained. The pore diameter spectrum data is calculated based on the pore diameter data and displayed in logarithmic channels, thus completing the construction of the pore diameter spectrum. The calculation of the pore cementation index based on the formation factor formula, using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data, includes: Based on rock electrical experiments, the average resistivity of the wellbore in carbonate reservoirs was obtained, and the porosity and lithology coefficients were analyzed. The relationship between average resistivity of the wellbore in carbonate reservoirs, porosity, lithology coefficient and cementation index was obtained by using the formation factor formula. The porosity cementation index is calculated based on the relational formula. The acquisition of the average resistivity of the electro-imaging includes: After calibrating the lateral resistivity and covering the entire wellbore using electrical imaging logging data, the reciprocal is calculated. Then, the average value of the 360 ​​wellbore resistivity data points at each depth point is obtained to get the mean electrical imaging resistivity. In the process of calibrating the pore cementation index and pore diameter in a homogeneous porous formation, the acquisition of the pore diameter includes: For pore diameter less than 1 The pore diameter of the rock sample was obtained by calculating the displacement pressure in the mercury intrusion porosimetry experiment. For pore diameters between 1 m-1000 For rock samples between m, the pore diameter is obtained by reading the pore diameter of the pore casting thin section; For pore diameter greater than 1000 The pore diameter of the rock sample was obtained through on-site core measurement. The process of calculating and obtaining pore diameter spectrum data based on pore diameter data, displaying it in logarithmic channels, and completing the pore diameter spectrum construction specifically includes: The pore diameter data at each depth point in the formation were divided into 25 intervals, and the distribution of pore diameter data in each interval was statistically analyzed. The statistical results for each interval are normalized. The statistical result of each interval is multiplied by the porosity component of the corresponding interval and summed to obtain the porosity of that interval; Based on the distribution of pore diameter data and porosity, the data is displayed in the logarithmic interval to form a pore diameter spectrum.

2. A system for constructing pore diameter spectra of carbonate rocks based on electrical imaging logging, characterized in that, The method for constructing carbonate rock pore diameter spectra based on electrical imaging logging as described in claim 1 includes: The cementation index calculation module is used to calculate the pore cementation index based on the formation factor formula and using the mean resistivity, porosity, and reservoir lithology coefficient from electrical imaging logging data. The cementation index-pore diameter relationship module is used to calibrate the pore cementation index and pore diameter in homogeneous porous formations and establish the relationship between the pore cementation index and pore diameter. The pore diameter data acquisition module is used to calculate and acquire pore diameter data based on the relationship between pore cementation index and pore diameter. The pore diameter spectrum construction module is used to calculate and obtain pore diameter spectrum data based on pore diameter data, and display it in logarithmic channels. Once the pore diameter spectrum construction is complete, the pore diameter spectrum is constructed.

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