Method and apparatus for analyzing shale reservoir capacity

Abstract

The application discloses a shale reservoir capacity analysis method and device, and relates to the technical field of shale gas geological exploration, wherein the method comprises the following steps: obtaining logging data and geothermal data of a shale reservoir; the logging data comprises mineral element logging data, density logging data, total organic carbon content and resistivity logging data of each depth point of the shale reservoir; determining pore volume indexes of each depth point of the shale reservoir according to the mineral element logging data and the density logging data; the pore volume indexes reflect actual pore volume values of the shale reservoir; determining specific surface area indexes of each depth point of the shale reservoir according to the geothermal data, the total organic carbon content and the resistivity logging data; the specific surface area indexes reflect actual specific surface area values of the shale reservoir; and determining a shale reservoir capacity analysis result according to the pore volume indexes and the specific surface area indexes. The application can improve the analysis accuracy of the shale reservoir capacity.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of shale gas geological exploration, and particularly relates to a shale reservoir capacity analysis method and device. BACKGROUND

[0002] This section is intended to provide background or context to the embodiments of the application recited in the claims. The description herein does not constitute admission that the prior art is prior art nor, that anything in this section is "prior art" with respect to the application.

[0003] As a new type of clean energy, shale gas has large reserves and wide distribution. In order to effectively develop shale gas, it is necessary to analyze the shale reservoir capacity in the early stage.

[0004] In the prior art, shale reservoir capacity analysis is mostly achieved through sample experiments and test analysis. For example, by collecting core samples, selecting organic matter pore development areas, and quantitatively characterizing the morphology of organic matter pores, the purpose of evaluating shale reservoir capacity is achieved. This method relies on core data, and the cost of coring is high, and the sample is limited, and the coverage rate of the work area is low. For example, by quantitatively analyzing the types and quantities of hydrocarbon-forming organisms, and combining experimental data such as shale organic geochemical characteristics, an evaluation model of the influence of hydrocarbon-forming organisms on reservoir capacity is established, and the influence of different biogenic organic matters on pore structure and the difference of reservoir capacity are analyzed. This method also relies on core data, and the cost of coring is high, and the sample is limited, and the coverage rate of the work area is low. For example, by experimentally analyzing shale samples to obtain total organic carbon TOC content, the shale reservoir capacity is evaluated. This method relies on laboratory testing, and the reservoir capacity is analyzed by a single total organic carbon TOC content, and the accuracy is low. There are some other shale reservoir capacity analysis methods in the prior art, for example, using seismic data to evaluate reservoir capacity, but this method is only suitable for planar large-area reservoir evaluation and cannot be used for single-well vertical reservoir capacity evaluation. At the same time, it is limited by the vertical resolution of seismic data, and the accuracy of reservoir capacity analysis is low.

[0005] In summary, the shale reservoir capacity analysis in the prior art has high cost and low accuracy. SUMMARY

[0006] The shale reservoir capacity analysis method provided by the embodiments of the present application is used to reduce the cost of shale reservoir capacity analysis and improve the accuracy of shale reservoir capacity analysis. The method comprises the following steps:

[0007] Obtain the logging data and geothermal data of the shale reservoir. The logging data comprises mineral element logging data, density logging data, total organic carbon content, and resistivity logging data of each depth point of the shale reservoir.

[0008] According to the mineral element logging data and the density logging data of each depth point of the shale reservoir, a pore volume index of each depth point of the shale reservoir is determined; the pore volume index reflects an actual value of a pore volume of the shale reservoir;

[0009] According to the geothermal data and the total organic carbon content and the resistivity logging data of each depth point of the shale reservoir, a specific surface area index of each depth point of the shale reservoir is determined; the specific surface area index reflects an actual value of a specific surface area of the shale reservoir;

[0010] According to the pore volume index and the specific surface area index of each depth point of the shale reservoir, a shale reservoir capacity analysis result is determined, the shale reservoir capacity analysis result including a capacity effect grade of a plurality of different shale reservoir regions.

[0011] In one embodiment, the mineral element logging data includes dolomite content, and the density logging data includes rock framework density and rock bulk density;

[0012] According to the mineral element logging data and the density logging data of each depth point of the shale reservoir, a pore volume index of each depth point of the shale reservoir is determined, including:

[0013] According to the rock framework density and the rock bulk density of each depth point of the shale reservoir, a first parameter of each depth point of the shale reservoir is determined; the first parameter reflects an actual value of porosity of the shale reservoir;

[0014] According to the dolomite content and the first parameter of each depth point of the shale reservoir, a pore volume index of each depth point of the shale reservoir is determined.

[0015] In one embodiment, according to the rock framework density and the rock bulk density of each depth point of the shale reservoir, a first parameter of each depth point of the shale reservoir is determined, including:

[0016] According to the rock framework density and the rock bulk density of each depth point of the shale reservoir, a first parameter P of each depth point of the shale reservoir is determined according to the following formula:

[0017]

[0018] In the formula, ρ ma is the rock framework density, and ρ b is the rock bulk density.

[0019] In one embodiment, according to the dolomite content and the first parameter of each depth point of the shale reservoir, a pore volume index of each depth point of the shale reservoir is determined, including:

[0020] According to the dolomite content and the first parameter of each depth point of the shale reservoir, a pore volume index F V of each depth point of the shale reservoir is determined according to the following formula:

[0021] F V =W DOL ×P

[0022] In the formula, W DOL is the dolomite content.

[0023] In one embodiment, the resistivity logging data comprises rock resistivity, and the geothermal data comprises surface temperature and geothermal gradient.

[0024] According to the geothermal data and the total organic carbon content and the rock resistivity of each depth point of the shale reservoir, a specific surface area index of each depth point of the shale reservoir is determined, comprising:

[0025] According to the surface temperature, the geothermal gradient and the rock resistivity of each depth point of the shale reservoir, a second parameter of each depth point of the shale reservoir is determined; the second parameter reflects an actual thermal evolution degree of the shale reservoir.

[0026] According to the total organic carbon content and the second parameter of each depth point of the shale reservoir, a specific surface area index of each depth point of the shale reservoir is determined.

[0027] In one embodiment, according to the surface temperature, the geothermal gradient and the rock resistivity of each depth point of the shale reservoir, a second parameter of each depth point of the shale reservoir is determined, comprising:

[0028] According to the surface temperature, the geothermal gradient and the rock resistivity of each depth point of the shale reservoir, a second parameter Y of each depth point of the shale reservoir is determined according to the following formula:

[0029]

[0030]

[0031] In the formula, R t is the rock resistivity, T is the formation temperature, T0 is the surface temperature, g is the geothermal gradient, and D is the depth of the calculation point.

[0032] In one embodiment, according to the total organic carbon content and the second parameter of each depth point of the shale reservoir, a specific surface area index of each depth point of the shale reservoir is determined, comprising:

[0033] According to the total organic carbon content and the second parameter of each depth point of the shale reservoir, a specific surface area index F S of each depth point of the shale reservoir is determined according to the following formula:

[0034] F S =TOC×Y

[0035] In the formula, TOC is the total organic carbon content.

[0036] In one embodiment, before determining the shale reservoir capacity analysis result according to the pore volume index and the specific surface area index of each depth point of the shale reservoir, the method further comprises:

[0037] The pore volume index and the specific surface area index of each depth point of the shale reservoir are normalized.

[0038] In one embodiment, the shale reservoir capacity analysis result is determined according to the pore volume index and the specific surface area index of each depth point of the shale reservoir, comprising:

[0039] A well logging crossplot is established according to the pore volume index and the specific surface area index of a plurality of same depth points of the shale reservoir.

[0040] The total gas content of a plurality of depth points of the shale reservoir is collected.

[0041] The shale reservoir is divided into a plurality of regions by using the total gas content of the plurality of depth points of the shale reservoir on the well logging crossplot; wherein different regions have different reservoir capacity effect grades.

[0042] The embodiment of the present application also provides a shale reservoir capacity analysis device for reducing the shale reservoir capacity analysis cost and improving the shale reservoir capacity analysis accuracy, comprising:

[0043] A data acquisition module is configured to acquire well logging data and geothermal data of the shale reservoir; the well logging data comprises mineral element well logging data, density well logging data, total organic carbon content and resistivity well logging data of each depth point of the shale reservoir.

[0044] A pore volume index determination module is configured to determine the pore volume index of each depth point of the shale reservoir according to the mineral element well logging data and the density well logging data of each depth point of the shale reservoir; the pore volume index reflects the pore volume actual value of the shale reservoir.

[0045] A specific surface area index determination module is configured to determine the specific surface area index of each depth point of the shale reservoir according to the geothermal data, the total organic carbon content and the resistivity well logging data of each depth point of the shale reservoir; the specific surface area index reflects the specific surface area actual value of the shale reservoir.

[0046] A result output module is configured to determine the shale reservoir capacity analysis result according to the pore volume index and the specific surface area index of each depth point of the shale reservoir; the shale reservoir capacity analysis result comprises reservoir capacity effect grades of a plurality of different shale reservoir regions.

[0047] The embodiment of the present application also provides a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the shale reservoir capacity analysis method is realized.

[0048] The embodiment of the present application also provides a computer readable storage medium, the computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the shale reservoir capacity analysis method.

[0049] The embodiment of the present application also provides a computer program product, the computer program product comprises a computer program, and the computer program is executed by a processor to realize the shale reservoir capacity analysis method.

[0050] The present application has the following advantages:

[0051] Firstly, in the embodiment of the present application, the logging data and the ground temperature data of the shale reservoir are acquired, and the logging data and the ground temperature data are directly analyzed and processed, so that the shale reservoir capacity analysis is realized, and compared with the prior art, the dependence on samples and experimental tests is eliminated, and the shale reservoir capacity analysis cost is greatly reduced.

[0052] Secondly, in the embodiment of the present application, the influencing factors of the shale reservoir capacity are fully considered, including the pore volume and the specific surface area. The pore volume can reflect the free gas storage capacity of the shale reservoir, the larger the pore volume of the shale reservoir is, the stronger the free gas storage capacity is, and this part of the storage capacity is mainly contributed by the large aperture pore. The specific surface area can reflect the adsorbed gas storage capacity of the shale reservoir, the larger the specific surface area of the shale is, the stronger the adsorbed gas storage capacity is, and this part of the storage capacity is provided by the small aperture pore. Compared with the prior art, the shale reservoir capacity for free gas and adsorbed gas is considered respectively in the embodiment of the present application, the pore volume index is determined according to the mineral element logging data and the density logging data of each depth point of the shale reservoir, and the specific surface area index is determined according to the ground temperature data and the total organic carbon content and the resistivity logging data of each depth point of the shale reservoir, so that the shale reservoir capacity analysis accuracy is greatly improved.

[0053] Finally, although the pore volume and the specific surface area are considered in the embodiment of the present application, the actual values thereof are not really calculated by complex means, but the pore volume index which can reflect the actual value of the pore volume of the shale reservoir and the specific surface area index which can reflect the actual value of the specific surface area of the shale reservoir are proposed, and the two indexes can be directly calculated by using the logging data, so that the method is simple, effective and easy to popularize. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings. In the drawings:

[0055] Figure 1 A flowchart of a shale reservoir capacity analysis method in an embodiment of the present application is shown in FIG. 1.

[0056] Figure 2 A specific embodiment of the shale reservoir capacity analysis method in an embodiment of the present application is shown in FIG. 2.

[0057] Figure 3 A specific embodiment of the shale reservoir capacity analysis method in an embodiment of the present application is shown in FIG. 3.

[0058] Figure 4 A specific embodiment of the shale reservoir capacity analysis method in an embodiment of the present application is shown in FIG. 4.

[0059] Figure 5 A specific embodiment of the shale reservoir capacity analysis method in an embodiment of the present application is shown in FIG. 5.

[0060] Figure 6 A schematic diagram of a shale reservoir capacity analysis device in an embodiment of the present application is shown in FIG. 6. DETAILED DESCRIPTION

[0061] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, further detailed description will be given to the embodiments of the present application in combination with the drawings. Herein, the schematic embodiments of the present application and the description thereof are used to explain the present application, but not as a limitation to the present application.

[0062] First of all, it needs to be stated that the acquisition, storage, use, processing and the like of data in the technical solution of the present application all comply with the relevant provisions of the national laws and regulations.

[0063] Figure 1 A flowchart of a shale reservoir capacity analysis method in an embodiment of the present application is shown in FIG. 1. Figure 1 As shown in FIG. 1, the method comprises the following steps.

[0064] Step 101, acquiring logging data and geothermal data of a shale reservoir; the logging data comprises mineral element logging data, density logging data, total organic carbon content and resistivity logging data of each depth point of the shale reservoir;

[0065] Step 102, determining a pore volume index of each depth point of the shale reservoir according to the mineral element logging data and the density logging data of each depth point of the shale reservoir; the pore volume index reflects an actual value of the pore volume of the shale reservoir;

[0066] Step 103, determining a specific surface area index of each depth point of the shale reservoir according to the geothermal data, the total organic carbon content and the resistivity logging data of each depth point of the shale reservoir; the specific surface area index reflects an actual value of the specific surface area of the shale reservoir;

[0067] Step 104: Determine the shale reservoir capacity analysis results based on the pore volume index and specific surface area index at each depth point of the shale reservoir. The shale reservoir capacity analysis results include the reservoir capacity effect levels of multiple different shale reservoir regions.

[0068] from Figure 1 As shown in the flowchart, in this embodiment of the invention, by acquiring well logging data and geothermal data of shale reservoirs and directly analyzing and processing these data, shale reservoir capacity analysis can be achieved. Compared with existing technologies, this eliminates the dependence on samples and experimental testing, significantly reducing the cost of shale reservoir capacity analysis. Secondly, this embodiment of the invention fully considers multiple factors affecting shale reservoir capacity, including pore volume and specific surface area. Pore volume reflects the shale reservoir's ability to store free gas; the larger the pore volume, the stronger the ability to store free gas. This portion of the reservoir capacity is mainly contributed by large-diameter pores. Specific surface area reflects the shale reservoir's ability to store adsorbed gas; the larger the specific surface area, the stronger the ability to store adsorbed gas. This portion of the reservoir capacity is provided by small-diameter pores. Compared to existing technologies, this invention considers the storage capacity of shale reservoirs for both free and adsorbed gas. It determines the pore volume index based on mineral element and density logging data at various depths of the shale reservoir, and the specific surface area index based on geothermal data and total organic carbon content and resistivity logging data at various depths of the shale reservoir. This significantly improves the accuracy of shale reservoir capacity analysis. Finally, although this invention considers pore volume and specific surface area, it does not actually calculate their actual values ​​using complex methods. Instead, it proposes a pore volume index that reflects the actual pore volume of the shale reservoir, and a specific surface area index that reflects the actual specific surface area. These two indices can be directly calculated using logging data, making the method simple, effective, and easy to promote.

[0069] In practice, the first step is to acquire data, including well logging data and geothermal data of shale reservoirs. Well logging data includes, for example, mineral element logging data, density logging data, total organic carbon content, and resistivity logging data at various depths of shale reservoirs. Geothermal data can include, for example, geothermal gradient and surface temperature data.

[0070] Then, based on the mineral element logging data and density logging data at each depth point of the shale reservoir, the pore volume index at each depth point of the shale reservoir is determined. The pore volume index reflects the actual pore volume of the shale reservoir. That is, in this embodiment of the invention, it is not necessary to calculate the actual pore volume. It is only necessary to determine the pore volume index that can reflect the actual pore volume through the mineral element logging data and density logging data.

[0071] The mineral element logging data contains the content of main minerals in the formation, such as quartz content, feldspar content, calcite content, dolomite content, anhydrite content and clay mineral content, and in addition, the element logging can also provide the framework density of the rock, such as the rock framework density and the rock bulk density, so that the pore volume index can be calculated according to the mineral element logging data and the data in the density logging data which is positively correlated with the pore volume.

[0072] Figure 2 As shown in FIG. 1, the shale reservoir capacity analysis method according to the embodiment of the present application can include the following steps. Figure 2 As shown in FIG. 1, the shale reservoir capacity analysis method according to the embodiment of the present application can include the following steps.

[0073] Step 201, determining the first parameter of each depth point of the shale reservoir according to the rock framework density and the rock bulk density of each depth point of the shale reservoir; the first parameter reflects the actual value of the porosity of the shale reservoir;

[0074] Step 202, determining the pore volume index of each depth point of the shale reservoir according to the dolomite content and the first parameter of each depth point of the shale reservoir.

[0075] In step 201, the first parameter of each depth point of the shale reservoir is determined by using the rock framework density and the rock bulk density, and the first parameter can be expressed as a porosity index, which reflects the actual value of the porosity of the shale reservoir.

[0076] In one embodiment, the first parameter of each depth point of the shale reservoir can be determined according to the rock framework density and the rock bulk density of each depth point of the shale reservoir, which can include:

[0077] According to the rock framework density and the rock bulk density of each depth point of the shale reservoir, the first parameter P of each depth point of the shale reservoir can be determined according to the following formula:

[0078]

[0079] In the formula, ρ ma is the rock framework density, and ρ b is the rock bulk density.

[0080] Then in step 202, the pore volume index of each depth point of the shale reservoir is determined according to the dolomite content and the first parameter of each depth point of the shale reservoir, for example, calculated according to the following formula:

[0081] F V = W DOL × P

[0082] In the formula, F V is the pore volume index, and W DOLDolomite content.

[0083] Therefore, in the embodiment of the present application, the dolomite content and the porosity index (the first parameter) are used to represent the pore volume index, and then the shale reservoir capacity is analyzed. The larger the pore volume of the shale reservoir is, the stronger the capacity of the reservoir to store free gas is, which is mainly contributed by the large aperture pores. The dolomite can provide a large number of intercrystalline pores, and these intercrystalline pores have a larger aperture in the shale reservoir and can store free gas. The porosity is the ratio of the sum of the pore space volume in the rock to the volume of the rock sample. It is found through experimental analysis that the porosity and the pore volume have a very good positive correlation. Therefore, by using the dolomite content and the porosity to represent the pore volume and then representing the capacity of the rock to store free gas, the accuracy of the analysis of the free gas storage capacity can be greatly improved.

[0084] In one embodiment, the logging data further includes acoustic logging data of each depth point of the shale reservoir, such as rock skeleton P-wave slowness and rock P-wave slowness.

[0085] In the embodiment of the present application, the following can also be included:

[0086] According to the mineral element logging data, the rock skeleton P-wave slowness and the rock P-wave slowness of each depth point of the shale reservoir, the pore volume index of each depth point of the shale reservoir is determined. That is, in the above step 201, the first parameter can be calculated in the following way:

[0087] According to the rock skeleton P-wave slowness and the rock P-wave slowness of each depth point of the shale reservoir, the first parameter P of each depth point of the shale reservoir is determined according to the following formula:

[0088]

[0089] In the formula, AC ma is the rock skeleton P-wave slowness, AC c is the rock P-wave slowness.

[0090] The porosity can not only be represented by the rock skeleton density and the rock bulk density, but also be represented by the acoustic slowness. By calculating the porosity index in different ways, the pore volume index can be calculated in different ways, and the method is more flexible.

[0091] After the pore volume index is determined, according to the geothermal data and the total organic carbon content and the resistivity logging data of each depth point of the shale reservoir, the specific surface area index of each depth point of the shale reservoir is determined. The specific surface area index reflects the actual value of the specific surface area of the shale reservoir, that is, the specific surface area index is not the real specific surface area, but is calculated and solved by using the data that are positively correlated with the specific surface area.

[0092] Figure 3This is a specific embodiment of the shale reservoir capacity analysis method in the present invention, such as... Figure 3 As shown, based on geothermal data and logging data of total organic carbon content and resistivity at various depths in the shale reservoir, the specific surface area index at each depth is determined, including:

[0093] Step 301: Resistivity logging data includes rock resistivity; based on surface temperature, geothermal gradient, and rock resistivity at various depths of the shale reservoir, determine the second parameter at each depth of the shale reservoir; the second parameter reflects the actual thermal evolution of the shale reservoir.

[0094] Step 302: Determine the specific surface area index of the shale reservoir at each depth point based on the total organic carbon content and the second parameter.

[0095] The second parameter Y at each depth of the shale reservoir is determined according to the following formula, based on surface temperature, geothermal gradient, and rock resistivity at each depth. This second parameter Y can also be expressed as a thermal evolution degree index:

[0096]

[0097]

[0098] In the formula, R t Let T be the rock resistivity, T be the formation temperature, T0 be the surface temperature, g be the geothermal gradient, and D be the depth of the calculation point.

[0099] The specific surface area index of shale reservoirs at various depths can be determined based on the total organic carbon content and a second parameter. This can include:

[0100] The specific surface area index F at each depth point of the shale reservoir is determined using the following formula, based on the total organic carbon content and the second parameter. S :

[0101] F S =TOC×Y

[0102] In the formula, TOC represents the total organic carbon content.

[0103] In the embodiment of the present application, total organic carbon content and thermal evolution degree index (second parameter) are used to represent specific surface area index, and then shale reservoir capacity is analyzed. The specific surface area is positively correlated with total organic carbon content and thermal evolution degree. The greater the specific surface area of shale is, the stronger the capacity of adsorbing gas is, which is mainly provided by small-diameter organic matter pores. The more the organic matter pores are, the greater the specific surface area of shale is. The organic matter pores of shale reservoir are important pore types of source-reservoir integrated and low-porosity and low-permeability reservoirs, and are one of important marks of shale reservoirs distinguishing from conventional sandstone and carbonate reservoirs. The organic matter pores are positively correlated with total organic carbon content, so the higher the total organic carbon content is, the stronger the capacity of adsorbing gas of shale is. In the process of organic matter hydrocarbon generation, the number of organic matter pores increases continuously with the increase of thermal evolution degree of reservoirs, so the thermal evolution degree can be used to represent the organic matter pores and then the capacity of adsorbing gas of shale. The thermal evolution degree can be represented by resistivity logging and formation temperature, and then the capacity of adsorbing gas of shale reservoir can be evaluated by logging data in combination with total organic carbon content, so that the accuracy of analysis of the capacity of adsorbing gas can be greatly improved.

[0104] In one embodiment, in order to improve the efficiency of shale reservoir capacity analysis, according to the pore volume index and the specific surface area index of each depth point of the shale reservoir, the shale reservoir capacity analysis result can be determined, and the shale reservoir capacity analysis result can further include:

[0105] The pore volume index and the specific surface area index of each depth point of the shale reservoir are normalized.

[0106] The pore volume index and the specific surface area index are normalized to obtain a normalized pore volume index and a normalized specific surface area index.

[0107] Then, the normalized pore volume index and the normalized specific surface area index are used to obtain the shale reservoir capacity analysis result.

[0108] In one embodiment, according to the pore volume index and the specific surface area index of each depth point of the shale reservoir, the shale reservoir capacity analysis result can be determined, and the shale reservoir capacity analysis result can include:

[0109] A well logging crossplot is established according to the pore volume index and the specific surface area index of a plurality of same depth points of the shale reservoir.

[0110] Total gas content of a plurality of depth points of the shale reservoir is collected.

[0111] A plurality of regions of the shale reservoir are divided on the well logging crossplot by using the total gas content of the plurality of depth points of the shale reservoir, and different regions have different reservoir capacity effect levels.

[0112] In the first analysis in this example, the total gas content of multiple depth points of the shale reservoir is obtained, and a reservoir capacity evaluation chart, i.e., a well logging crossplot, is established by using the normalized pore volume index and the normalized specific surface area index corresponding to the depth where the total gas content data is located. The total gas content data of the data points in the well logging crossplot is classified, and the total gas content data points in different numerical ranges are divided into corresponding reservoir capacity levels according to actual needs, i.e., the areas of different reservoir capacity effect levels can be obtained in the chart. When analyzing the reservoir capacity of the shale in the subsequent stage, only the pore volume index and the specific surface area index corresponding to the depth points of the shale reservoir need to be calculated, and the reservoir capacity effect level of the depth points of the shale reservoir in the well logging crossplot is determined.

[0113] The well logging reservoir capacity analysis method in the embodiment of the present application is described in detail below by taking the Neogene formation K1 well in K area as an example.

[0114] 1. Basic address situation.

[0115] The Neogene formation in K area is a set of lacustrine shale formation, and the geological conditions are suitable for the application of the embodiment of the present application.

[0116] 2. Obtaining data.

[0117] The well logging data of the K1 well can be obtained by using a well logging series instrument, including the dolomite content, the rock skeleton density, the rock bulk density, the rock skeleton compressional wave time difference, the rock compressional wave time difference, the total organic carbon content of the rock, and the rock resistivity. At the same time, the surface temperature and the geothermal gradient of the K1 well are obtained.

[0118] 3. Calculating the pore volume index.

[0119] The well logging data of the depth point is substituted into the following formula to obtain the pore volume index corresponding to the depth:

[0120]

[0121] For example, the dolomite content W_DOL = 60%, the rock skeleton density p ma = 2.75 g / cm3, the rock bulk density p b = 2.65 g / cm3, and the pore volume index F V = 2.18 is calculated.

[0122] Alternatively, the well logging data of the depth point is substituted into the following formula to obtain the pore volume index corresponding to the depth:

[0123]

[0124] For example, the dolomite content W DOL = 60%, the rock skeleton compressional wave time difference AC ma = 50 s / ft, the rock compressional wave time difference ACc = 55 μs / ft, calculate pore volume index F V = 6.0.

[0125] 4, calculate specific surface area index.

[0126] The logging data at the depth point is substituted into the following formula to calculate the specific surface area index corresponding to the depth.

[0127]

[0128]

[0129] For example, total organic carbon content TOC = 2.0%, rock resistivity R t = 20 ohm-m, surface temperature T0 = 20℃, geothermal gradient g = 2.5℃ / 100m, formation depth D = 2000m, calculate specific surface area index F S = 14.49.

[0130] 5, establish a reservoir capacity evaluation chart.

[0131] A plurality of pore volume indexes and specific surface area indexes are calculated in advance, and the plurality of pore volume indexes and specific surface area indexes are normalized to obtain normalized pore volume indexes and normalized specific surface area indexes. Then, a reservoir capacity evaluation chart is established by using the normalized pore volume index and the normalized specific surface area index corresponding to the depth of the total gas content data, and the total gas content data points of different numerical ranges are divided into corresponding reservoir capacity effect grades according to actual needs, that is, the regions of different reservoir capacity effect grades can be obtained in the chart. Figure 4 For a specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present application, as shown in Figure 4 The shale reservoir capacity effect in K area can be divided into three grades, namely, class I, class II and class III. The reservoir capacity of class I is the best, that of class II is the second, and that of class III is the worst. The basis for classification is the total gas content value corresponding to each data point. The data points with total gas content greater than 3.5 m 3 / t represent class I, the data points with total gas content of 2.0-3.5 m 3 / t represent class II, and the data points with total gas content less than 2.0 m 3 / t represent class III.

[0132] 6, analyze reservoir capacity by using single well logging data.

[0133] When analyzing the reservoir capacity of any shale reservoir depth point in the range of the area in the subsequent process, the reservoir capacity thereof can be determined according to the classification grade into which the pore volume index and the specific surface area index thereof fall.

[0134] Figure 5As shown in a specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present application, Figure 5 The normalized pore volume index curve and the normalized specific surface area index curve of the K1 well are calculated by using the K1 well data and the formula, as shown in the formula (1) and the formula (2). According to the calculation result, it is considered that the reservoir capacity of the layers 1 and 2 is good. Then, the layer 1 is tested for gas production, and the daily gas production of 25000m 3 The high-yield industrial gas flow is obtained, which proves that the reservoir capacity of the layer 1 is good, and indicates that the shale reservoir capacity analysis result in the embodiment of the present application is accurate.

[0135] In summary, the beneficial effects of the present application are as follows:

[0136] Firstly, in the embodiment of the present application, the logging data of the shale reservoir is obtained, and the logging data is directly analyzed and processed, so that the shale reservoir capacity analysis can be realized. Compared with the prior art, the present application does not rely on samples and experimental tests, and greatly reduces the cost of shale reservoir capacity analysis.

[0137] Secondly, in the embodiment of the present application, multiple influencing factors of shale reservoir capacity are fully considered, including pore volume and specific surface area. The pore volume can reflect the reservoir capacity of free gas in the shale reservoir, and the larger the pore volume of the shale reservoir is, the stronger the reservoir capacity of free gas is. This part of the reservoir capacity is mainly contributed by large-aperture pores. In the embodiment of the present application, the dolomite content and the porosity are fully considered in the pore volume index, and the two are used to analyze the reservoir capacity of free gas in the shale reservoir. The specific surface area can reflect the reservoir capacity of adsorbed gas in the shale reservoir, and the larger the specific surface area of the shale is, the stronger the reservoir capacity of adsorbed gas is. This part of the reservoir capacity is provided by small-aperture pores. In the embodiment of the present application, the total organic carbon content and the thermal evolution degree are fully considered in the specific surface area index, and the two are used to analyze the reservoir capacity of adsorbed gas in the shale reservoir. Compared with the prior art, the embodiment of the present application considers the reservoir capacity of free gas and adsorbed gas in the shale reservoir respectively, and considers multiple influencing factors, including pore volume, porosity, dolomite content, specific surface area, total organic carbon content and thermal evolution degree, which greatly improves the accuracy of shale reservoir capacity analysis.

[0138] Finally, although the pore volume and the specific surface area are considered in the embodiment of the present application, the actual values thereof are not really calculated by complex means, but the pore volume index which can reflect the actual value of the pore volume of the shale reservoir and the specific surface area index which can reflect the actual value of the specific surface area of the shale reservoir are proposed. The two indexes can be directly calculated by using the logging data, and the method is simple, effective and easy to popularize.

[0139] In the embodiment of the present application, a shale reservoir capacity analysis device is also provided, as described in the following embodiment. Since the principle of solving the problem of the device is similar to that of the shale reservoir capacity analysis method, the implementation of the device can be referred to the implementation of the shale reservoir capacity analysis method, and the repeated parts will not be described again.

[0140] Figure 6 This is a schematic diagram of a shale reservoir capacity analysis device in an embodiment of the present invention, as shown below. Figure 6 As shown, the device includes:

[0141] The data acquisition module 601 is used to acquire well logging data and geothermal data of shale reservoirs; the well logging data includes mineral element logging data, density logging data, total organic carbon content, and resistivity logging data at various depth points of the shale reservoir.

[0142] The pore volume index determination module 602 is used to determine the pore volume index of the shale reservoir at each depth point based on the mineral element logging data and density logging data of the shale reservoir; the pore volume index reflects the actual pore volume of the shale reservoir.

[0143] The specific surface area index determination module 603 is used to determine the specific surface area index of the shale reservoir at each depth point based on geothermal data and total organic carbon content and resistivity logging data at each depth point of the shale reservoir; the specific surface area index reflects the actual value of the specific surface area of ​​the shale reservoir.

[0144] The result output module 604 is used to determine the shale reservoir capacity analysis results based on the pore volume index and specific surface area index at each depth point of the shale reservoir. The shale reservoir capacity analysis results include the reservoir capacity effect levels of multiple different shale reservoir regions.

[0145] In one embodiment, the mineral element logging data includes dolomite content, and the density logging data includes rock skeleton density and rock bulk density;

[0146] The pore volume index determination module 602 is specifically used for:

[0147] Based on the rock skeleton density and rock bulk density at each depth point of the shale reservoir, the first parameter of the shale reservoir at each depth point is determined; the first parameter reflects the actual porosity value of the shale reservoir.

[0148] Based on the dolomite content and the first parameter at each depth point of the shale reservoir, the pore volume index at each depth point of the shale reservoir is determined.

[0149] In one embodiment, the pore volume index determination module 602 is specifically used for:

[0150] The first parameter P of the shale reservoir at each depth is determined using the following formula, based on the rock skeleton density and rock bulk density at each depth point:

[0151]

[0152] In the formula, ρ mais the rock skeleton density, p b is the rock bulk density.

[0153] In one embodiment, the pore volume index determination module 602 is specifically configured to:

[0154] According to the dolomite content of each depth point of the shale reservoir, the first parameter, the pore volume index F of each depth point of the shale reservoir is determined according to the following formula V :

[0155] F V = W DOL × P

[0156] In the formula, W DOL is the dolomite content.

[0157] In one embodiment, the resistivity logging data includes rock resistivity, and the geothermal data includes surface temperature and geothermal gradient.

[0158] The specific surface area index determination module 603 is specifically configured to:

[0159] According to the surface temperature, the geothermal gradient and the rock resistivity of each depth point of the shale reservoir, a second parameter of each depth point of the shale reservoir is determined; the second parameter reflects the actual thermal evolution degree of the shale reservoir.

[0160] According to the total organic carbon content of each depth point of the shale reservoir and the second parameter, a specific surface area index of each depth point of the shale reservoir is determined.

[0161] In one embodiment, the specific surface area index determination module 603 is specifically configured to:

[0162] According to the surface temperature, the geothermal gradient and the rock resistivity of each depth point of the shale reservoir, a second parameter Y of each depth point of the shale reservoir is determined according to the following formula:

[0163]

[0164]

[0165] In the formula, R t is the rock resistivity, T is the formation temperature, T0 is the surface temperature, g is the geothermal gradient, and D is the depth of the calculation point.

[0166] In one embodiment, the specific surface area index determination module 603 is specifically configured to:

[0167] According to the total organic carbon content of each depth point of the shale reservoir and the second parameter, a specific surface area index F of each depth point of the shale reservoir is determined according to the following formula S :

[0168] FS = TOC x Y

[0169] In the formula, TOC is the total organic carbon content.

[0170] In one embodiment, further comprising:

[0171] The normalization processing module is configured to normalize the pore volume index and the specific surface area index of each depth point of the shale reservoir before the result output module 604 determines the shale reservoir capacity analysis result based on the pore volume index and the specific surface area index of each depth point of the shale reservoir.

[0172] In one embodiment, the result output module 604 is specifically configured to:

[0173] establish a well logging crossplot based on the pore volume index and the specific surface area index of the plurality of same depth points of the shale reservoir;

[0174] collect the total gas content of the plurality of depth points of the shale reservoir;

[0175] divide the shale reservoir into a plurality of regions by using the total gas content of the plurality of depth points of the shale reservoir on the well logging crossplot; wherein different regions have different reservoir capacity effect grades.

[0176] The embodiment of the present application further provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the shale reservoir capacity analysis method when executing the computer program.

[0177] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the shale reservoir capacity analysis method.

[0178] The embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program is executable on a processor to implement the shale reservoir capacity analysis method.

[0179] Compared with the prior art, the shale reservoir capacity analysis cost is greatly reduced. Secondly, in the embodiment of the present application, multiple influencing factors of shale reservoir capacity are fully considered, including pore volume and specific surface area. The pore volume can reflect the free gas storage capacity of the shale reservoir, the larger the pore volume of the shale reservoir is, the stronger the free gas storage capacity is, and this part of the storage capacity is mainly contributed by large-aperture pores; the specific surface area can reflect the adsorbed gas storage capacity of the shale reservoir, the larger the specific surface area of the shale is, the stronger the adsorbed gas storage capacity is, and this part of the storage capacity is provided by small-aperture pores. Compared with the prior art, the shale reservoir capacity analysis accuracy is greatly improved by considering the free gas and adsorbed gas storage capacities of the shale reservoir respectively, determining the pore volume index according to the mineral element logging data and density logging data of each depth point of the shale reservoir, and determining the specific surface area index according to the ground temperature data and the total organic carbon content and resistivity logging data of each depth point of the shale reservoir. Finally, although the pore volume and specific surface area are considered in the embodiment of the present application, the actual values thereof are not really calculated by complex means, but the pore volume index reflecting the actual value of the pore volume of the shale reservoir and the specific surface area index reflecting the actual value of the specific surface area of the shale reservoir are proposed, and the two indexes can be directly calculated by using logging data, which is simple, effective and easy to popularize.

[0180] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer-readable program code.

[0181] The present application is described in reference to the flowcharts and / or block diagrams of the method, device (system) and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks.

[0182] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0183] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0184] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method of shale reservoir capacity analysis, characterized by, The method comprises the following steps: obtaining logging data and geothermal data of the shale reservoir; the logging data comprises mineral element logging data, density logging data, total organic carbon content and resistivity logging data of each depth point of the shale reservoir; determining a pore volume index of each depth point of the shale reservoir according to the mineral element logging data and the density logging data of each depth point of the shale reservoir; the pore volume index reflects an actual pore volume value of the shale reservoir; the mineral element logging data comprises dolomite content, and the density logging data comprises rock skeleton density and rock volume density; determining a specific surface area index of each depth point of the shale reservoir according to the total organic carbon content and the resistivity logging data of each depth point of the shale reservoir and the geothermal data; the specific surface area index reflects an actual specific surface area value of the shale reservoir; the resistivity logging data comprises rock resistivity, and the geothermal data comprises surface temperature and geothermal gradient; determining a shale reservoir capacity analysis result according to the pore volume index and the specific surface area index of each depth point of the shale reservoir; the shale reservoir capacity analysis result comprises a capacity effect grade of a plurality of different shale reservoir regions; wherein, the pore volume index of each depth point of the shale reservoir is determined according to the mineral element logging data and the density logging data of each depth point of the shale reservoir, comprising: a first parameter P of each depth point of the shale reservoir is determined according to the rock skeleton density and the rock volume density of each depth point of the shale reservoir by the following formula, and the first parameter P reflects an actual porosity value of the shale reservoir: wherein p ma is the rock matrix density, p b is the rock bulk density; According to the dolomite content and the first parameter of each depth point of the shale reservoir, the pore volume index F of each depth point of the shale reservoir is determined according to the following formula V : F V = W DOL x P In the formula, W DOL dolomite content; wherein, the specific surface area index of each depth point of the shale reservoir is determined according to the total organic carbon content and the resistivity logging data of each depth point of the shale reservoir and the geothermal data, comprising: a second parameter Y of each depth point of the shale reservoir is determined according to the surface temperature, the geothermal gradient and the rock resistivity of each depth point of the shale reservoir by the following formula, and the second parameter Y reflects an actual thermal evolution degree of the shale reservoir: In the formula, R t Where is the rock resistivity, T is the formation temperature, T0 is the surface temperature, g is the geothermal gradient, and D is the depth of the calculation point; According to the total organic carbon content of each depth point of the shale reservoir and the second parameter, the specific surface area index of each depth point of the shale reservoir is determined according to the following formula : F S = TOC x Y in the formula, TOC is the total organic carbon content.

2. The method of claim 1, wherein, Before the shale reservoir capacity analysis result is determined according to the pore volume index and the specific surface area index of each depth point of the shale reservoir, the method further comprises: normalizing the pore volume index and the specific surface area index of each depth point of the shale reservoir.

3. The method of claim 1, wherein, The shale reservoir capacity analysis result is determined according to the pore volume index and the specific surface area index of each depth point of the shale reservoir, comprising: a logging crossplot is established according to the pore volume index and the specific surface area index of a plurality of same depth points of the shale reservoir; total gas content of a plurality of depth points of the shale reservoir is collected; the shale reservoir is divided into a plurality of regions by using the total gas content of the plurality of depth points of the shale reservoir on the logging crossplot; different regions have different capacity effect grades.

4. A shale reservoir capacity analysis device characterized by, The device is suitable for the shale reservoir capacity analysis method of claim 1, and the device comprises: a data acquisition module configured to acquire logging data and geothermal data of the shale reservoir; the logging data comprises mineral element logging data, density logging data, total organic carbon content and resistivity logging data of each depth point of the shale reservoir; The pore volume index determination module is configured to determine a pore volume index of each depth point of the shale reservoir according to the mineral element logging data and the density logging data of the shale reservoir, and the pore volume index reflects an actual value of a pore volume of the shale reservoir. The specific surface area index determination module is configured to determine a specific surface area index of each depth point of the shale reservoir according to the geothermal data and the total organic carbon content and the resistivity logging data of the shale reservoir, and the specific surface area index reflects an actual value of a specific surface area of the shale reservoir. The result output module is configured to determine a shale reservoir capacity analysis result according to the pore volume index and the specific surface area index of each depth point of the shale reservoir, and the shale reservoir capacity analysis result includes a capacity effect level of a plurality of different shale reservoir regions.

5. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1 to 3.

7. A computer program product, characterised in that, The computer program product includes a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1 to 3.

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