Porosity reading method, device, equipment and medium

Abstract

The invention discloses a porosity reading method, device, equipment and medium, and relates to the technical field of petroleum logging, and the porosity reading method comprises the steps: calculating logging parameters to obtain each logging interval transit time value, each logging neutron value and each logging density value; determining an interval transit time boundary range, a neutron boundary range and a density boundary range based on each logging interval transit time value, each logging neutron value and each logging density value; calculating the actual logging curve based on the interval transit time boundary range, the neutron boundary range and the density boundary range to obtain each porosity; and determining a natural gamma curve based on the logging calculation data so as to perform shale content calculation to obtain a stratum shale content value, performing shale content correction on each porosity to obtain a target porosity curve graph, and sending the target porosity curve graph to a client so that the client can read the porosity. According to the method, the porosity can be visually, rapidly and accurately read, the usability of the logging map is improved, and the subsequent on-site interpretation time is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum well logging, and in particular to a porosity reading method, device, equipment and medium. Background Art

[0002] Porosity is the ratio of the pore volume of a formation to the total volume of rock. It is one of the important parameters for studying reservoir physical properties. In the prior art, the quantitative evaluation method for the porosity of oil and gas reservoirs is mainly based on the Wyllie formula (Wyllie formula), using the acoustic logging, density logging, and neutron porosity logging curves to mainly reflect the change in porosity. This is achieved through corresponding calculations or computer operation of specific professional software. The prior art has the following disadvantages: the processing and interpretation takes a long time, and requires indoor technicians to complete the operation on the computer and then provide it; the curves are not easy to use. When geologists use logging maps, they can only simply obtain the numerical information of the three porosity curves of the formation, and cannot intuitively obtain important parameters such as formation porosity. Even logging workers can only estimate the porosity based on the curve values, with poor accuracy.

[0003] As can be seen from the above, how to achieve intuitive, fast and accurate reading of porosity, improve the usability of logging images, and thus reduce the subsequent field interpretation time is a problem to be solved in this field. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a porosity reading method, device, equipment and medium, which can realize intuitive, fast and accurate porosity reading, improve the usability of logging maps, and thus reduce the subsequent field interpretation time. The specific scheme is as follows:

[0005] In a first aspect, the present application discloses a porosity reading method, which is applied to a well logging map, comprising:

[0006] Determine the lithology of the rock reservoir, determine the well logging parameters based on the lithology, calculate the well logging parameters to obtain each well logging acoustic time difference value, each well logging neutron value and each well logging density value, and determine the acoustic time difference boundary range, the neutron boundary range and the density boundary range respectively based on each well logging acoustic time difference value, each well logging neutron value and each well logging density value;

[0007] Acquire an actual well logging curve and well logging calculation data, and calculate the actual well logging curve based on the acoustic wave time difference boundary range, the neutron boundary range, and the density boundary range to obtain various porosities;

[0008] A natural gamma curve is determined based on the logging calculation data, and the mud content is calculated using the natural gamma curve to obtain a formation mud content value. The formation mud content value is used to perform mud content correction on each porosity to obtain a target porosity curve graph, and the target porosity curve graph is sent to a client so that the client can read the porosity based on the target porosity curve graph.

[0009] Optionally, determining the lithology of the rock reservoir includes:

[0010] The lithology of rock reservoirs is determined using the neutron density cross plot method;

[0011] Or, the lithology of the rock reservoir is determined based on the method of well cuttings description; wherein the lithology includes sandstone, mudstone and limestone reservoirs.

[0012] Optionally, the logging parameters include rock skeleton acoustic wave time difference, fluid acoustic wave time difference, rock skeleton neutron value, fluid neutron value, rock skeleton density and fluid density.

[0013] Optionally, the step of using the formation shale content value to perform shale content correction on each of the porosities to obtain a target porosity curve diagram includes:

[0014] Determine the mudstone acoustic time difference based on the lithology, and calculate the ratio between the difference between the mudstone acoustic time difference and the rock skeleton acoustic time difference and the difference between the fluid acoustic time difference and the rock skeleton acoustic time difference to obtain a mud correction coefficient;

[0015] The shale correction coefficient and the shale content value of the formation are used to perform shale content correction on each of the porosities to obtain each target porosity.

[0016] Optionally, the calculating the actual well logging curve based on the acoustic wave time difference boundary range, the neutron boundary range and the density boundary range to obtain various porosities includes:

[0017] According to the arrangement principle of equal porosity, the actual logging curve is matched with the acoustic time difference boundary range, the neutron boundary range and the density boundary range, and then the weighted average method is used to calculate the actual logging curve in the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain each porosity.

[0018] Optionally, determining a natural gamma curve based on the well logging calculation data includes:

[0019] Obtaining a preset natural gamma relative value calculation formula, and determining a boundary value of a natural gamma curve based on the natural gamma relative value calculation formula;

[0020] A natural gamma curve is generated based on the boundary value of the natural gamma curve and the logging calculation data, and the natural gamma curve is sent and displayed to a client, so that the client can read out a natural gamma relative value based on the natural gamma curve.

[0021] Optionally, the calculating of the shale content by using the natural gamma curve to obtain the shale content value of the formation includes:

[0022] Determine whether the rock reservoir is a new formation. If the rock reservoir is a new formation, calculate the mud content by using a preset new formation empirical coefficient of the formation mud content and the natural gamma curve to obtain the formation mud content value;

[0023] If the rock reservoir is not a new formation, the mud content is calculated using the preset old formation empirical coefficient of the formation mud content and the natural gamma curve to obtain the formation mud content value.

[0024] In a second aspect, the present application discloses a porosity reading device, which is applied to well logging maps, comprising:

[0025] A range determination module is used to determine the lithology of the rock reservoir, determine the logging parameters based on the lithology, calculate the logging parameters to obtain each logging acoustic time difference value, each logging neutron value and each logging density value, and determine the acoustic time difference boundary range, the neutron boundary range and the density boundary range based on each logging acoustic time difference value, each logging neutron value and each logging density value;

[0026] A calculation module, used for obtaining actual logging curves and logging calculation data, and calculating the actual logging curves based on the acoustic wave time difference boundary range, the neutron boundary range and the density boundary range to obtain various porosities;

[0027] A porosity reading module is used to determine a natural gamma curve based on the logging calculation data, calculate the mud content using the natural gamma curve to obtain a formation mud content value, perform mud content correction on each porosity using the formation mud content value to obtain a target porosity curve graph, and send the target porosity curve graph to a client so that the client can perform porosity reading based on the target porosity curve graph.

[0028] In a third aspect, the present application discloses an electronic device, comprising:

[0029] Memory, used to store computer programs;

[0030] A processor is used to execute the computer program to implement the aforementioned porosity reading method.

[0031] In a fourth aspect, the present application discloses a computer storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the porosity reading method disclosed above are implemented.

[0032] It can be seen that the present application provides a porosity reading method, including determining the lithology of the rock reservoir, determining the logging parameters based on the lithology, calculating the logging parameters to obtain each logging acoustic time difference value, each logging neutron value and each logging density value, and determining the acoustic time difference boundary range, the neutron boundary range and the density boundary range based on each logging acoustic time difference value, each logging neutron value and each logging density value; obtaining the actual logging curve and logging calculation data, calculating the actual logging curve based on the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain each porosity; determining the natural gamma curve based on the logging calculation data, calculating the mud content using the natural gamma curve to obtain the formation mud content value, and correcting the mud content of each porosity using the formation mud content value to obtain a target porosity curve diagram, and sending the target porosity curve diagram to the client so that the client can read the porosity based on the target porosity curve diagram. The present application determines the sonic time difference boundary range, neutron boundary range and density boundary range to calculate each porosity, which can eliminate the error caused by using a single method, and the result is more reliable, with better operability, innovation and applicability. The porosity is corrected for mud content to obtain a target porosity curve, which reduces the complexity of establishing an interpretation model required for porosity calculation, and considers the influence of mud content on porosity, providing a simple, fast and practical method for porosity interpretation of sandstone, mudstone and limestone reservoirs, which can realize intuitive, fast and accurate reading of porosity, improve the usability of logging maps, and thus reduce the subsequent field interpretation time. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0034] Figure 1 A flow chart of a porosity reading method disclosed in the present application;

[0035] Figure 2 A flow chart of a porosity reading method disclosed in the present application;

[0036] Figure 3A numerical relationship diagram between the relative value of natural gamma and the mud content of the formation disclosed in this application;

[0037] Figure 4 This is a X1 well logging combination result diagram disclosed in this application;

[0038] Figure 5 This is a X2 well logging combination result diagram disclosed in this application;

[0039] Figure 6 This is a X3 well logging combination result diagram disclosed in this application;

[0040] Figure 7 This is a schematic diagram of the structure of a porosity reading device disclosed in this application;

[0041] Figure 8 A structural diagram of an electronic device provided for this application. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] Porosity is the ratio of the pore volume of the formation to the total volume of the rock. It is one of the important parameters for studying reservoir physical properties. In the prior art, the quantitative evaluation method of oil and gas reservoir porosity is mainly based on the Wyllie formula, using acoustic logging, density logging, and neutron porosity logging curves to mainly reflect the change in porosity. This characteristic is achieved through corresponding calculations or computer operation of specific professional software. The shortcomings of the prior art are as follows: the processing and interpretation takes a long time, and requires indoor technicians to provide after completing the computer operation; the curves are not easy to use. When geologists use logging maps, they can only simply obtain the numerical information of the three porosity curves of the formation, and cannot intuitively obtain important parameters such as formation porosity. Even logging workers can only estimate porosity based on the curve values, with poor accuracy. As can be seen from the above, how to achieve intuitive, fast, and accurate reading of porosity, improve the ease of use of logging maps, and thus reduce the subsequent field interpretation time is a problem to be solved in this field.

[0044] See also Figure 1 As shown, the embodiment of the present invention discloses a porosity reading method, which is applied to well logging images and may specifically include:

[0045] Step S11: Determine the lithology of the rock reservoir, determine the logging parameters based on the lithology, calculate the logging parameters to obtain each logging acoustic time difference value, each logging neutron value and each logging density value, and determine the acoustic time difference boundary range, neutron boundary range and density boundary range based on each logging acoustic time difference value, each logging neutron value and each logging density value.

[0046] In this embodiment, the lithology of the rock reservoir is determined by using the neutron density cross plot method; or, the lithology of the rock reservoir is determined based on the method of well cuttings description; wherein the lithology includes sandstone, mudstone and limestone reservoirs, and then the logging parameters are determined based on the lithology, and the logging parameters are calculated to obtain each logging acoustic wave time difference value, each logging neutron value and each logging density value, and the acoustic wave time difference boundary range, the neutron boundary range and the density boundary range are respectively determined based on each of the logging acoustic wave time difference values, each of the logging neutron values ​​and each of the logging density values; wherein the logging parameters include rock skeleton acoustic wave time difference, fluid acoustic wave time difference, rock skeleton neutron value, fluid neutron value, rock skeleton density and fluid density.

[0047] Step S12: acquiring actual well logging curves and well logging calculation data, and calculating the actual well logging curves based on the acoustic wave time difference boundary range, the neutron boundary range, and the density boundary range to obtain various porosities.

[0048] In this embodiment, the specific method for quickly and accurately calculating the porosity based on the boundary range is as follows: the porosity calculation is realized according to the Wei Li formula. The Wei Li formula is a linear porosity model that directly establishes the relationship between the porosity and the logging curve. The formula used to calculate the logging acoustic wave time difference value is as follows:

[0049]

[0050] Among them, Δt is the logging acoustic wave time difference; Δt ma is the acoustic time difference of the rock skeleton; Δt f is the time difference of fluid sound waves, μs / ft or μs / m; C p is the compaction coefficient, which is 1 for normal compacted formation and is dimensionless; φ is the porosity.

[0051] The formula used to calculate the logging neutron value is as follows:

[0052]

[0053] Among them, Φ n , Φ ma , Φ f They are well logging neutron value, rock skeleton neutron value, and fluid neutron value respectively;

[0054] The formula used to calculate the logging density value is as follows:

[0055]

[0056] Among them, ρ, ρ ma , f They are logging density, rock skeleton density, and fluid density, g / cm3 respectively.

[0057] Specifically, taking a sandstone-mudstone reservoir as an example, for the sandstone-mudstone reservoir, the physical property curve of the logging map is divided into 10 equally spaced areas by 11 scale lines (right boundary, 9 scale lines, left boundary). In order to ensure the ease of use of the method and consider the rationality of the curve distribution, the porosity is matched with the 11 scale lines from -10% to 90%, that is, the rightmost boundary corresponds to a porosity of -10%, with a porosity step of 10% at equal intervals, and the leftmost boundary corresponds to a porosity value of 90%.

[0058] By formula It can be obtained that: Δt=φ*(Δt f -Δt ma )+Δt ma ;

[0059] Freshwater slurry fluid acoustic time difference Δt f The value is 189μs / ft, and the acoustic time difference value of the sandstone skeleton is 55μs / ft. According to the formula, when the porosity is -10%, the corresponding logging acoustic time difference is 41.6μs / ft, and when the porosity is 90%, the corresponding logging acoustic time difference is 175.6μs / ft. In actual use, the logging map needs to consider the reading value of the logging curve. Obviously, the non-integer left and right boundary values ​​are not suitable for the curve numerical reading. The porosity of various types of reservoirs in major oil fields in my country usually does not exceed 30%. Therefore, the left and right boundaries are rounded. Under the premise of ensuring the accurate reading of the porosity within 30%, the map is beautiful and the curve is easy to use. Therefore, it is determined that the left and right boundary values ​​of the acoustic time difference in the sandstone mudstone formation are 40μs / ft and 180μs / ft (that is, the acoustic time difference boundary range is 40μs / ft and 180μs / ft). At this time, all the scale lines in the figure correspond linearly to the porosity values.

[0060] By formula We can get: Φ n =φ*(Φ f -Φ ma )+Φ ma ;

[0061] Fluid neutron value Φ fWhen the porosity is 100%, the neutron value of the sandstone skeleton is -4%. By calculating with the formula, when the porosity is -10%, the corresponding logging neutron value is -14%. When the porosity is 90%, the corresponding logging neutron value is 86%. Therefore, it is determined that in the sandstone-mudstone formation, the left and right boundary values ​​of the neutron curve are 86% and -14% (that is, the neutron boundary range is 86% and -14%).

[0062] By formula We can get: ρ=φ*(ρ f -ρ ma )+ρ ma ;

[0063] The fluid density is 1.0 g / cm 3 The sandstone skeleton density is 2.65g / cm 3 According to the formula, when the porosity is -10%, the corresponding logging density value is 2.815g / cm 3 When the porosity is 90%, the corresponding logging density value is 1.165g / cm 3 Similar to the acoustic time difference curve, the ease of reading the curve needs to be considered. Therefore, the left and right boundary values ​​of the density curve in the sandstone stratum are determined to be 1.20 g / cm 3 , 2.80g / cm 3 (That is, the density boundary range is 1.20g / cm 3 , 2.80g / cm 3 ).

[0064] Taking a limestone reservoir as an example, in order to ensure the ease of use of the method and consider the rationality of the curve distribution and the beauty of the drawing, the porosity is matched with 11 scale lines from -20% to 80%, that is, the rightmost boundary corresponds to a porosity of -20%, with a porosity step of 10% at equal intervals, and the leftmost boundary corresponds to a porosity value of 80%.

[0065] Freshwater slurry fluid acoustic time difference Δt fThe value is 189μs / ft, and the acoustic time difference of the limestone skeleton is 47.5μs / ft. According to the formula, when the porosity is -20%, the corresponding logging acoustic time difference is 19.2μs / ft, and when the porosity is 80%, the corresponding logging acoustic time difference is 160.7μs / ft. In actual use, the logging map needs to consider the reading of the logging curve. Obviously, the non-integer left and right boundary values ​​are not suitable for the curve numerical reading. The porosity of various types of reservoirs in major oil fields in my country usually does not exceed 30%. Therefore, the left and right boundaries are rounded to ensure the accuracy of the reading of the porosity within 30%, while ensuring the beauty of the map and the ease of use of the curve. Therefore, it is determined that in the sandstone and mudstone formations, the left and right boundary values ​​of the acoustic time difference are 20μs / ft and 160μs / ft. At this time, all the scale lines in the figure correspond linearly to the porosity values. The porosity can be quickly and accurately obtained by observing the position of the acoustic time difference curve in the physical property curve. The acoustic time difference curve is based on the logging parameters and the acoustic time difference values ​​of each logging. Similarly, the neutron curve and density curve can be obtained.

[0066] Neutron logging is calibrated in limestone formations, so the logging values ​​correspond to the porosity values ​​one by one, that is, when the porosity is -20%, the corresponding logging neutron value is -20%, and when the porosity is 80%, the corresponding logging neutron value is 80%. Therefore, it is determined that in sandstone and mudstone formations, the left and right boundary values ​​of the neutron curve are 80% and -20%.

[0067] The fluid density value ρ is 1.0g / cm 3 The sandstone skeleton density is 2.71g / cm 3 According to the formula, when the porosity is -20%, the corresponding logging density value is 3.052g / cm 3 When the porosity is 80%, the corresponding logging density value is 1.342 g / cm 3 Similar to the acoustic time difference curve, the ease of reading the curve needs to be considered. Therefore, the left and right boundary values ​​of the density curve in the sandstone limestone formation are determined to be 1.35 g / cm 3 、3.05g / cm 3 .

[0068] Well logging curves are affected by various factors, and the positions of the three physical property curves may not coincide. Therefore, the weighted average method is used to eliminate the error caused by using a single curve, and the result is more reliable.

[0069] Step S13: Determine a natural gamma curve based on the logging calculation data, use the natural gamma curve to calculate the mud content to obtain the formation mud content value, use the formation mud content value to perform mud content correction on each porosity to obtain a target porosity curve graph, and send the target porosity curve graph to the client so that the client can read the porosity based on the target porosity curve graph.

[0070] In this embodiment, a natural gamma curve is determined based on the logging calculation data, and then the mudstone acoustic time difference is determined based on the lithology, and the ratio of the difference between the mudstone acoustic time difference and the rock skeleton acoustic time difference to the difference between the fluid acoustic time difference and the rock skeleton acoustic time difference is calculated to obtain a mud correction coefficient; the mud content of each porosity is corrected using the mud correction coefficient and the mud content value of the formation to obtain a target porosity curve graph, and the target porosity curve graph is sent to the client so that the client can read the porosity based on the target porosity curve graph.

[0071] In this embodiment, the lithology of the rock reservoir is determined, and the logging parameters are determined based on the lithology. The logging parameters are calculated to obtain each logging acoustic time difference value, each logging neutron value and each logging density value. The acoustic time difference boundary range, the neutron boundary range and the density boundary range are respectively determined based on each logging acoustic time difference value, each logging neutron value and each logging density value; the actual logging curve and logging calculation data are obtained, and the actual logging curve is calculated based on the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain each porosity; the natural gamma curve is determined based on the logging calculation data, and the natural gamma curve is used to calculate the mud content to obtain the formation mud content value, and the formation mud content value is used to perform mud content correction on each porosity to obtain a target porosity curve graph, and the target porosity curve graph is sent to the client so that the client can read the porosity based on the target porosity curve graph. The present application determines the sonic time difference boundary range, the neutron boundary range and the density boundary range to calculate each porosity, which can eliminate the error caused by using a single method, and the result is more reliable, with better operability, innovation and applicability. The porosity is corrected for mud content to obtain a target porosity curve, which reduces the complexity of establishing an interpretation model required for porosity calculation, and considers the influence of mud content on porosity, providing a simple, fast and practical method for porosity interpretation of sandstone, mudstone and limestone reservoirs, which can realize intuitive, fast and accurate reading of porosity, improve the usability of logging maps, and thus reduce the subsequent field interpretation time.

[0072] See also Figure 2 As shown, the embodiment of the present invention discloses a porosity reading method, which is applied to well logging images and may specifically include:

[0073] Step S21: Determine the lithology of the rock reservoir, determine the logging parameters based on the lithology, calculate the logging parameters to obtain each logging sonic time difference value, each logging neutron value and each logging density value, and determine the sonic time difference boundary range, the neutron boundary range and the density boundary range based on each logging sonic time difference value, each logging neutron value and each logging density value.

[0074] Step S22: Acquire actual logging curves and logging calculation data, match the actual logging curves with the acoustic time difference boundary range, the neutron boundary range, and the density boundary range according to the arrangement principle of equal porosity, and then use the weighted average method to calculate the actual logging curves in the acoustic time difference boundary range, the neutron boundary range, and the density boundary range to obtain each porosity.

[0075] In this embodiment, after obtaining the actual logging curve and logging calculation data, in the logging curve diagram, the actual logging curve is matched with the acoustic time difference boundary range, the neutron boundary range and the density boundary range, arranged according to the principle of equal porosity, and reasonable intervals are set to match the equally spaced grid lines of the logging diagram to achieve a quick and accurate preliminary estimate of the porosity.

[0076] Step S23: obtaining a preset natural gamma relative value calculation formula, determining a boundary value of a natural gamma curve based on the natural gamma relative value calculation formula, generating a natural gamma curve based on the boundary value of the natural gamma curve and the logging calculation data, and sending and displaying the natural gamma curve to a client, so that the client can read the natural gamma relative value based on the natural gamma curve.

[0077] In this embodiment, the logging readings of mudstone (GR max ) represents the measurement result of 100% shale content, while the logging reading of pure sandstone rock (GR min ) represents the measurement result when the mud content is 0, and the difference between the two is taken as the change in logging readings caused by the mud content being 100%. The ratio of the measured value to the difference between the two is the relative value of natural gamma:

[0078]

[0079] Among them, SH is the relative value of natural gamma; GR, GR min , GR maxThey are well logging natural gamma, pure formation natural gamma, and pure mudstone layer natural gamma. Based on the above natural gamma relative value calculation formula, the boundary value of the natural gamma curve is determined, and then the natural gamma curve is generated according to the boundary value of the natural gamma curve and the well logging calculation data, and the natural gamma curve is sent and displayed to the client. The client can quickly read the natural gamma relative value through the natural gamma curve displayed on the well logging map.

[0080] Step S24: Calculate the mud content using the natural gamma curve to obtain the formation mud content value, perform mud content correction on each porosity using the formation mud content value to obtain a target porosity curve graph, and send the target porosity curve graph to the client so that the client can read the porosity based on the target porosity curve graph.

[0081] In this embodiment, it is determined whether the rock reservoir is a new formation. If the rock reservoir is a new formation, the mud content is calculated using the preset new formation empirical coefficient of the formation mud content and the relative value of natural gamma to obtain the formation mud content value; if the rock reservoir is not a new formation, the mud content is calculated using the preset old formation empirical coefficient of the formation mud content and the relative value of natural gamma to obtain the formation mud content value, and then the mud content of each porosity is corrected using the formation mud content value to obtain a target porosity curve.

[0082] In this embodiment, according to the reservoir characteristics, the boundary value of the natural gamma curve is determined to obtain the boundary value range, and a reasonable interval is set to match the equally spaced grid lines of the logging map. The mud content is calculated using the natural gamma relative value to achieve a rapid and accurate preliminary estimate of the mud content.

[0083] In this embodiment, the calculation formula for mud content is:

[0084] Among them, GCUR is the empirical coefficient, the empirical coefficient of new strata is 3.7, and the empirical coefficient of old strata is 2; V SH The mud content of the formation.

[0085] According to the regional and segment characteristics, select the appropriate natural gamma value of pure formations and pure mudstone layers, and use the natural gamma relative value calculation formula to determine the left and right boundary values ​​of the natural gamma curve. At this time, the natural gamma relative value SH can be accurately obtained according to the position of the natural gamma curve. Usually, the effective reservoir has a low shale content, and its natural gamma relative value SH is less than 30%. In old formations, V can be quickly obtained based on the SH value. SH , the numerical simulation of the mud content calculation formula can be obtained in Table 1, Table 1 is the relationship between SH and V SH Numerical relationship table (GCUR = 2):

[0086] Table 1

[0087] Serial number Natural gamma relative value SH (%) Calculate the mud content Vsh (%) 1 5 2.4 2 10 5.0 3 15 7.7 4 20 10.7 5 25 13.8 6 30 17.2 7 35 20.8 8 40 24.7 9 45 28.9 10 50 33.3

[0088] In most cases, in the low SH value area (SH≤25), V SH The value is about 0.5 times the SH value; second, in a few medium and high SH value areas (SH>25), the power exponential relationship that is not suitable for oral calculation is converted into a linear relationship, SH and V SH The numerical relationship diagram of Figure 3 As shown, V SH The value is approximately SH*0.7-2.

[0089] In this embodiment, the porosity is corrected for the shale content to obtain the corrected reservoir porosity value, and a target porosity curve is generated based on the corrected reservoir porosity value, and the formula is as follows:

[0090]

[0091] Among them, Δt sh is the mudstone acoustic time difference, φ e is the reservoir porosity value after mud correction.

[0092] φ and V have been obtained in the above process SH , it is known that sandstone formation Δt sh is 88μs / ft. Based on the above, the porosity value of the sandstone-mudstone reservoir after mud correction is For the convenience of calculation, V SH The coefficient before is rounded, that is, the calculation is

[0093] Known limestone formation Δt sh is 62μs / ft, and the porosity of the reservoir after the shale correction in the limestone formation is

[0094] For example, the accuracy of the present invention is verified by referring to the sandstone-shale formation porosity result calculated by the well logging of Well X1. Figure 4This is the result of the well logging combination of Well X1. The reservoir of Well X1 is a sandstone formation of the Middle Permian System. The natural gamma of the pure sandstone formation is 20API, and the natural gamma of the pure mudstone formation is 150API. The three porosity curves use the left and right boundary values ​​of the above sandstone, namely the acoustic time difference curve (180, 40), the density curve (1.2, 2.8), and the neutron curve (86, -14). Layer 1 at 2716 meters, Layer 2 at 2720 meters, and Layer 3 at 2741 meters were selected for rapid reading of mud content and porosity. (1) According to the position of the three porosity curves, read the porosity value. Layer 1 at 2716 meters, read φ as 15%; Layer 2 at 2720 meters, read φ as 13%; Layer 3 at 2746 meters, read φ as 9%. (2) According to the position of the natural gamma curve, read the mud content. Layer 1 at 2716 meters, SH value is 20%, V SH The value is 10%; Layer 2 is 2720 meters, the SH value is 25%, V SH The value is 12.5%; Layer 3 is 2746 meters, the SH value is 18%, V SH The value is 9%. (3) The porosity is corrected for the shale content. The porosity of these three depth points is calculated as e (keep one decimal place) are 15-10 / 4=12.5%, 13-12.5 / 4≈9.9%, 9-9 / 4≈6.9% respectively.

[0095] The accuracy of the present invention is verified by referring to the limestone formation porosity result calculated by well logging of Well X2. Figure 5 This is the result of the X2 well logging combination. The reservoir of the X2 well is the Ordovician limestone formation. The three porosity curves use the left and right boundary values ​​of the above-mentioned limestone, namely the sonic time difference curve (160, 20), the density curve (1.35, 3.05), and the neutron curve (80, -20). The 32nd layer at 3016 meters and the 33rd layer at 3025 meters were selected for quick reading of the mud content and porosity. (1) According to the position of the three porosity curves, read the porosity value. At 3016 meters in the 32nd layer, φ is read as 8%; at 3025 meters in the 33rd layer, φ is read as 4%. (2) According to the position of the natural gamma curve, read the mud content. At 3016 meters in the 32nd layer, the SH value is 14%, and the V SH The value is 7%; Layer 33, 3025 meters, SH value is 8%, V SH The value is 4%. (3) The porosity is corrected for the shale content. The porosity of these two depth points is calculated as e (keep one decimal place) are 8-7 / 10=7.3% and 4-4 / 10=3.6% respectively.

[0096] The accuracy of the present invention is verified by referring to the porosity results of the sandstone-mudstone formation calculated by the well logging of Well X3. Figure 6This is the result of the X3 well logging combination. The reservoir of the X3 well is a Cretaceous sandstone formation with good physical properties. The natural gamma of the pure sandstone formation is 50API, and the natural gamma of the pure mudstone formation is 115API. The three porosity curves use the left and right boundary values ​​of the above sandstone, namely the sonic time difference curve (180, 40), the density curve (1.2, 2.8), and the neutron curve (86, -14). The 2457 meters of layer 5, the 2459.5 meters of layer 5, and the 2465 meters of layer 6 were selected for rapid reading of mud content and porosity. (1) According to the position of the three porosity curves, read the porosity value. At 2457 meters in layer 5, the φ is read as 27%; at 2459.5 meters in layer 5, the φ is read as 28%; at 2465 meters in layer 6, the φ is read as 26%. (2) According to the position of the natural gamma curve, read the mud content. At 2457 meters in layer 5, the SH value is 40%, and the V SH The value is 26%; Layer 5 is 2459.5 meters, the SH value is 15%, V SH The value is 7.5%; Layer 6 is 2465 meters, the SH value is 50%, V SH The value is 33%. (3) The porosity is corrected for the shale content. The porosity of these three depth points is calculated as e (keep one decimal place) are 27-26 / 4≈20.5%, 28-7.5 / 4≈26.1%, and 26-33 / 4≈17.7% respectively.

[0097] The porosity readings of the above three wells X1, X2 and X3 are compared with the porosity calculated by logging, as shown in Table 2:

[0098] Table 2

[0099]

[0100] In this embodiment, the lithology of the rock reservoir is determined, and the logging parameters are determined based on the lithology. The logging parameters are calculated to obtain each logging acoustic time difference value, each logging neutron value and each logging density value. The acoustic time difference boundary range, the neutron boundary range and the density boundary range are respectively determined based on each logging acoustic time difference value, each logging neutron value and each logging density value; the actual logging curve and logging calculation data are obtained, and the actual logging curve is calculated based on the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain each porosity; the natural gamma curve is determined based on the logging calculation data, and the natural gamma curve is used to calculate the mud content to obtain the formation mud content value, and the formation mud content value is used to perform mud content correction on each porosity to obtain a target porosity curve graph, and the target porosity curve graph is sent to the client so that the client can read the porosity based on the target porosity curve graph. The present application determines the sonic time difference boundary range, the neutron boundary range and the density boundary range to calculate each porosity, which can eliminate the error caused by using a single method, and the result is more reliable, with better operability, innovation and applicability. The porosity is corrected for mud content to obtain a target porosity curve, which reduces the complexity of establishing an interpretation model required for porosity calculation, and considers the influence of mud content on porosity, providing a simple, fast and practical method for porosity interpretation of sandstone, mudstone and limestone reservoirs, which can realize intuitive, fast and accurate reading of porosity, improve the usability of logging maps, and thus reduce the subsequent field interpretation time.

[0101] See also Figure 7 As shown, the embodiment of the present invention discloses a porosity reading device, which is applied to well logging maps and may specifically include:

[0102] The range determination module 11 is used to determine the lithology of the rock reservoir, determine the logging parameters based on the lithology, calculate the logging parameters to obtain each logging acoustic time difference value, each logging neutron value and each logging density value, and determine the acoustic time difference boundary range, the neutron boundary range and the density boundary range based on each logging acoustic time difference value, each logging neutron value and each logging density value;

[0103] A calculation module 12 is used to obtain actual well logging curves and well logging calculation data, and calculate the actual well logging curves based on the acoustic wave time difference boundary range, the neutron boundary range and the density boundary range to obtain various porosities;

[0104] The mud content correction module 13 is used to determine the natural gamma curve based on the logging calculation data, use the natural gamma curve to calculate the mud content to obtain the formation mud content value, use the formation mud content value to perform mud content correction on each porosity to obtain a target porosity curve graph, and send the target porosity curve graph to the client so that the client can read the porosity based on the target porosity curve graph.

[0105] In this embodiment, the lithology of the rock reservoir is determined, and the logging parameters are determined based on the lithology. The logging parameters are calculated to obtain each logging acoustic time difference value, each logging neutron value and each logging density value. The acoustic time difference boundary range, the neutron boundary range and the density boundary range are respectively determined based on each logging acoustic time difference value, each logging neutron value and each logging density value; the actual logging curve and logging calculation data are obtained, and the actual logging curve is calculated based on the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain each porosity; the natural gamma curve is determined based on the logging calculation data, and the natural gamma curve is used to calculate the mud content to obtain the formation mud content value, and the formation mud content value is used to perform mud content correction on each porosity to obtain a target porosity curve graph, and the target porosity curve graph is sent to the client so that the client can read the porosity based on the target porosity curve graph. The present application determines the sonic time difference boundary range, neutron boundary range and density boundary range to calculate each porosity, which can eliminate the error caused by using a single method, and the result is more reliable, with better operability, innovation and applicability. The porosity is corrected for mud content to obtain a target porosity curve, which reduces the complexity of establishing an interpretation model required for porosity calculation, and considers the influence of mud content on porosity, providing a simple, fast and practical method for porosity interpretation of sandstone, mudstone and limestone reservoirs, which can realize intuitive, fast and accurate reading of porosity, improve the usability of logging maps, and thus reduce the subsequent field interpretation time.

[0106] In some specific embodiments, the range determination module 11 may specifically include:

[0107] The first lithology determination module is used to determine the lithology of the rock reservoir using a neutron density cross plot method;

[0108] The second lithology module is used to determine the lithology of the rock reservoir based on the method of well cuttings description; wherein the lithology includes sandstone, mudstone and limestone reservoirs.

[0109] In some specific embodiments, the logging parameters include rock skeleton acoustic wave time difference, fluid acoustic wave time difference, rock skeleton neutron value, fluid neutron value, rock skeleton density and fluid density.

[0110] In some specific embodiments, the mud content correction module 13 may specifically include:

[0111] A mud correction coefficient determination module is used to determine the mudstone acoustic time difference based on lithology, and calculate the ratio between the difference between the mudstone acoustic time difference and the rock skeleton acoustic time difference and the difference between the fluid acoustic time difference and the rock skeleton acoustic time difference to obtain a mud correction coefficient;

[0112] The shale content correction module is used to perform shale content correction on each of the porosities using the shale correction coefficient and the stratum shale content value to obtain a target porosity curve.

[0113] In some specific embodiments, the calculation module 12 may specifically include:

[0114] A calculation module is used to match the actual logging curve with the acoustic time difference boundary range, the neutron boundary range and the density boundary range according to the arrangement principle of equal porosity, and then use the weighted average method to calculate the actual logging curve in the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain each porosity.

[0115] In some specific embodiments, the mud content correction module 13 may specifically include:

[0116] A boundary value determination module, used to obtain a preset natural gamma relative value calculation formula, and determine the boundary value of the natural gamma curve based on the natural gamma relative value calculation formula;

[0117] The natural gamma relative value reading module is used to generate a natural gamma curve based on the boundary value of the natural gamma curve and the logging calculation data, and send and display the natural gamma curve to the client so that the client can read the natural gamma relative value based on the natural gamma curve.

[0118] In some specific embodiments, the mud content correction module 13 may specifically include:

[0119] A first formation mud content value calculation module is used to determine whether the rock reservoir is a new formation. If the rock reservoir is a new formation, the mud content is calculated using a preset new formation empirical coefficient of the formation mud content and the natural gamma curve to obtain the formation mud content value;

[0120] The second formation mud content value calculation module is used to calculate the mud content by using the preset old formation empirical coefficient of the formation mud content and the natural gamma curve to obtain the formation mud content value if the rock reservoir is not a new formation.

[0121] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the porosity reading method performed by the electronic device disclosed in any of the aforementioned embodiments.

[0122] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0123] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon include an operating system 221, a computer program 222 and data 223, etc. The storage method can be temporary storage or permanent storage.

[0124] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, so as to realize the operation and processing of the data 223 in the memory 22 by the processor 21, which can be Windows, Unix, Linux, etc. In addition to including a computer program that can be used to complete the porosity reading method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program that can be used to complete other specific tasks. In addition to data transmitted from an external device received by the porosity reading device, the data 223 can also include data collected by its own input and output interface 25.

[0125] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0126] Furthermore, an embodiment of the present application also discloses a computer-readable storage medium, in which a computer program is stored. When the computer program is loaded and executed by a processor, the porosity reading method steps disclosed in any of the aforementioned embodiments are implemented.

[0127] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0128] The porosity reading method, device, equipment and storage medium provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A porosity reading method, characterized in that: Applied to well logging diagrams, including: Determine the lithology of the rock reservoir, determine the well logging parameters based on the lithology, calculate the well logging parameters to obtain each well logging acoustic time difference value, each well logging neutron value and each well logging density value, and determine the acoustic time difference boundary range, the neutron boundary range and the density boundary range respectively based on each well logging acoustic time difference value, each well logging neutron value and each well logging density value; Acquire an actual well logging curve and well logging calculation data, and calculate the actual well logging curve based on the acoustic wave time difference boundary range, the neutron boundary range, and the density boundary range to obtain various porosities; A natural gamma curve is determined based on the logging calculation data, and the mud content is calculated using the natural gamma curve to obtain a formation mud content value. The formation mud content value is used to perform mud content correction on each porosity to obtain a target porosity curve graph, and the target porosity curve graph is sent to a client so that the client can read the porosity based on the target porosity curve graph.

2. The porosity reading method according to claim 1, characterized in that: The lithology of the rock reservoir is determined, including: The lithology of rock reservoirs is determined using the neutron density cross plot method; Or, the lithology of the rock reservoir is determined based on the method of well cuttings description; wherein the lithology includes sandstone, mudstone and limestone reservoirs.

3. The porosity reading method according to claim 1, characterized in that: The logging parameters include rock skeleton acoustic wave time difference, fluid acoustic wave time difference, rock skeleton neutron value, fluid neutron value, rock skeleton density and fluid density.

4. The porosity reading method according to claim 3, characterized in that: The method of using the formation mud content value to perform mud content correction on each porosity to obtain a target porosity curve diagram includes: Determine the mudstone acoustic time difference based on the lithology, and calculate the ratio between the difference between the mudstone acoustic time difference and the rock skeleton acoustic time difference and the difference between the fluid acoustic time difference and the rock skeleton acoustic time difference to obtain a mud correction coefficient; The shale correction coefficient and the stratum shale content value are used to perform shale content correction on each of the porosities to obtain a target porosity curve.

5. The porosity reading method according to claim 1, characterized in that: The actual logging curve is calculated based on the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain various porosities, including: According to the arrangement principle of equal porosity, the actual logging curve is matched with the acoustic time difference boundary range, the neutron boundary range and the density boundary range, and then the weighted average method is used to calculate the actual logging curve in the acoustic time difference boundary range, the neutron boundary range and the density boundary range to obtain each porosity.

6. The porosity reading method according to any one of claims 1 to 5, characterized in that: Determining a natural gamma curve based on the well logging calculation data includes: Obtaining a preset natural gamma relative value calculation formula, and determining a boundary value of a natural gamma curve based on the natural gamma relative value calculation formula; A natural gamma curve is generated based on the boundary value of the natural gamma curve and the logging calculation data, and the natural gamma curve is sent and displayed to a client, so that the client can read out a natural gamma relative value based on the natural gamma curve.

7. The porosity reading method according to claim 6, characterized in that: The method of calculating the shale content by using the natural gamma curve to obtain the shale content value of the formation includes: Determine whether the rock reservoir is a new formation. If the rock reservoir is a new formation, calculate the mud content by using a preset new formation empirical coefficient of the formation mud content and the natural gamma curve to obtain the formation mud content value; If the rock reservoir is not a new formation, the mud content is calculated using the preset old formation empirical coefficient of the formation mud content and the natural gamma curve to obtain the formation mud content value.

8. A porosity reading device, characterized in that: Applied to well logging diagrams, including: A range determination module is used to determine the lithology of the rock reservoir, determine the logging parameters based on the lithology, calculate the logging parameters to obtain each logging acoustic time difference value, each logging neutron value and each logging density value, and determine the acoustic time difference boundary range, the neutron boundary range and the density boundary range based on each logging acoustic time difference value, each logging neutron value and each logging density value; A calculation module, used for obtaining actual logging curves and logging calculation data, and calculating the actual logging curves based on the acoustic wave time difference boundary range, the neutron boundary range and the density boundary range to obtain various porosities; A porosity reading module is used to determine a natural gamma curve based on the logging calculation data, calculate the mud content using the natural gamma curve to obtain a formation mud content value, perform mud content correction on each porosity using the formation mud content value to obtain a target porosity curve graph, and send the target porosity curve graph to a client so that the client can perform porosity reading based on the target porosity curve graph.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the porosity reading method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program; wherein, when the computer program is executed by a processor, the porosity reading method according to any one of claims 1 to 7 is implemented.

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