Shale reservoir capacity analysis method and device

Abstract

The invention discloses a shale reservoir capacity analysis method and device, and relates to the technical field of shale gas geological exploration, and the method comprises the steps: obtaining the logging data and ground temperature 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 the pore volume index of each depth point of the shale reservoir according to the mineral element logging data and the density logging data; the pore volume index reflects an actual pore volume value of the shale reservoir; according to the ground temperature data, the total organic carbon content and the resistivity logging data, 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; and determining a shale reservoir capacity analysis result according to the pore volume index and the specific surface area index. The shale reservoir capacity analysis accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of shale gas geological exploration, and in particular to a shale gas storage capacity analysis method and device. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No description herein is admitted to be prior art by inclusion in this section.

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

[0004] In the prior art, shale storage capacity analysis is mostly achieved through sample experiments and test analysis. For example, by collecting core samples, selecting areas with organic pore development, and performing quantitative morphological characterization of organic pores, the purpose of evaluating shale storage capacity is achieved. This method relies on core data, has high coring costs, and has limited samples, and has low coverage of the work area. For example, by quantitatively counting the types and numbers of hydrocarbon-forming organisms, combined with experimental data such as shale organic geochemical characteristics, an evaluation model for the impact of hydrocarbon-forming organisms on storage capacity is established, and the impact of organic matter from different biological sources on pore structure and the differences in storage capacity are analyzed. This method also relies on core data, has high coring costs, and has limited samples, and has low coverage of the work area. For another example, by conducting experimental analysis on shale samples, the total organic carbon TOC content is obtained, and then the shale storage capacity is evaluated. This method relies on laboratory tests, and the storage capacity is analyzed through 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, reservoir capacity evaluation using seismic data. However, this method is only applicable to reservoir evaluation in large planar areas and cannot be used for vertical reservoir capacity evaluation of a single well. At the same time, it is limited by the vertical resolution of seismic data, so the reservoir capacity analysis accuracy of this method is relatively low.

[0005] In summary, the shale reservoir capacity analysis in the existing technology has high cost and low accuracy. Summary of the invention

[0006] The embodiment of the present invention provides a shale reservoir capacity analysis method, which is used to reduce the cost of shale reservoir capacity analysis and improve the accuracy of shale reservoir capacity analysis. The method includes:

[0007] Acquire logging data and geothermal data of shale reservoirs; the logging data include mineral element logging data, density logging data, total organic carbon content, and resistivity logging data at each depth point of the shale reservoir;

[0008] Determine the pore volume index at each depth point of the shale reservoir according to the mineral element logging data and density logging data at each depth point of the shale reservoir; the pore volume index reflects the actual value of the pore volume of the shale reservoir;

[0009] Determine the specific surface area index at each depth point of the shale reservoir according to the geothermal data and the 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;

[0010] The shale reservoir capacity analysis result is determined according to the pore volume index and specific surface area index at each depth point of the shale reservoir, and the shale reservoir capacity analysis result includes the reservoir capacity effect levels of multiple different shale reservoir areas.

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

[0012] According to 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, including:

[0013] Determine a first parameter at each depth point of the shale reservoir according to the rock skeleton density and rock volume density at each depth point of the shale reservoir; the first parameter reflects the actual value of the porosity of the shale reservoir;

[0014] The pore volume index at each depth point of the shale reservoir is determined according to the dolomite content and the first parameter at each depth point of the shale reservoir.

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

[0016] According to the following formula, the first parameter P at each depth point of the shale reservoir is determined based on the rock skeleton density and rock volume density at each depth point of the shale reservoir:

[0017]

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

[0019] In one embodiment, determining the pore volume index at each depth point of the shale reservoir according to the dolomite content at each depth point of the shale reservoir and the first parameter includes:

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

[0021] F V =W DOL ×P

[0022] Where W DOL For the dolomite content.

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

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

[0025] Determine a second parameter at each depth point of the shale reservoir according to the surface temperature, the geothermal gradient and the rock resistivity at each depth point of the shale reservoir; the second parameter reflects the actual thermal evolution degree of the shale reservoir;

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

[0027] In one embodiment, the second parameter 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, including:

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

[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, the specific surface area index at each depth point of the shale reservoir is determined according to the total organic carbon content at each depth point of the shale reservoir and the second parameter, including:

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

[0034] F S =TOC×Y

[0035] Where 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 specific surface area index at each depth point of the shale reservoir, the method further includes:

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

[0038] In one embodiment, the shale reservoir capacity analysis results are determined based on the pore volume index and specific surface area index at each depth point of the shale reservoir, including:

[0039] A well logging cross-plot is established based on the pore volume index and specific surface area index of multiple points at the same depth in the shale reservoir;

[0040] Collect the total gas content at multiple depths in shale reservoirs;

[0041] On the well logging intersection diagram, the shale reservoir is divided into multiple areas using the total gas content at multiple depth points of the shale reservoir; different areas have different levels of storage capacity effect.

[0042] The embodiment of the present invention further provides a shale storage capacity analysis device, which is used to reduce the cost of shale storage capacity analysis and improve the accuracy of shale storage capacity analysis. The device includes:

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

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

[0045] A specific surface area index determination module is used to determine the specific surface area index of each depth point of the shale reservoir according to geothermal data and the total organic carbon content and resistivity logging data of 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;

[0046] The result output module is used to determine the shale reservoir capacity analysis results according to the pore volume index and specific surface area index at each depth point of the shale reservoir, and the shale reservoir capacity analysis results include the reservoir capacity effect levels of multiple different shale reservoir areas.

[0047] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned shale reservoir capacity analysis method when executing the computer program.

[0048] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned shale reservoir capacity analysis method is implemented.

[0049] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above-mentioned shale reservoir capacity analysis method is implemented.

[0050] The beneficial effects of the present invention are as follows:

[0051] First, in the embodiment of the present invention, by acquiring the logging data and geothermal data of the shale reservoir, the logging data and geothermal data are directly analyzed and processed to achieve shale storage capacity analysis. Compared with the prior art, it gets rid of the dependence on samples and experimental tests, and greatly reduces the cost of shale storage capacity analysis.

[0052] Secondly, the embodiments of the present invention fully consider the influencing factors of multiple shale storage capacity, including pore volume and specific surface area. Among them, the pore volume can reflect the storage capacity of the shale reservoir for free gas. The larger the pore volume of the shale reservoir, the stronger the ability to store free gas, and this part of the storage capacity is mainly contributed by large-diameter pores; the specific surface area can reflect the storage capacity of the shale reservoir for adsorbed gas. The larger the specific surface area of ​​shale, the stronger the ability to store adsorbed gas, and this part of the storage capacity is provided by small-diameter pores. Compared with the prior art, the embodiments of the present invention consider the storage capacity of the shale reservoir for free gas and adsorbed gas respectively, and determine the pore volume index according to the mineral element logging data and density logging data at each depth point of the shale reservoir, and determine the specific surface area index according to the geothermal data and the total organic carbon content and resistivity logging data at each depth point of the shale reservoir, which greatly improves the accuracy of shale storage capacity analysis.

[0053] Finally, although the embodiments of the present invention take pore volume and specific surface area into consideration, they do not actually calculate their actual values ​​through complex means. Instead, they propose a pore volume index that can reflect the actual value of the pore volume of the shale reservoir and a specific surface area index that can reflect the actual value of the specific surface area of ​​the shale reservoir. These two indices can be directly calculated using logging data. The method is simple, effective, and easy to promote. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0055] Figure 1 Schematic diagram of the process of shale reservoir capacity analysis method in an embodiment of the present invention;

[0056] Figure 2 This is a specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present invention;

[0057] Figure 3 This is a specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present invention;

[0058] Figure 4 This is a specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present invention;

[0059] Figure 5 This is a specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present invention;

[0060] Figure 6 Schematic diagram of a shale storage capacity analysis device in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0062] First of all, it should be noted that the acquisition, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations.

[0063] Figure 1 FIG. 1 is a flow chart of a shale reservoir capacity analysis method according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0064] Step 101, obtaining well logging data and geothermal data of the shale reservoir; the well logging data includes mineral element well logging data, density well logging data, total organic carbon content, and resistivity well logging data at each depth point of the shale reservoir;

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

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

[0067] Step 104: Determine the shale reservoir capacity analysis result according to the pore volume index and specific surface area index at each depth point of the shale reservoir, wherein the shale reservoir capacity analysis result includes the reservoir capacity effect levels of multiple different shale reservoir regions.

[0068] from Figure 1 It can be seen from the process shown that in the embodiment of the present invention, by obtaining the logging data and geothermal data of the shale reservoir, the logging data and geothermal data are directly analyzed and processed to realize the shale storage capacity analysis. Compared with the prior art, it gets rid of the dependence on samples and experimental tests, and greatly reduces the cost of shale storage capacity analysis. Secondly, the embodiment of the present invention fully considers multiple factors affecting shale storage capacity, including pore volume and specific surface area. Among them, the pore volume can reflect the storage capacity of the shale reservoir for free gas. The larger the pore volume of the shale reservoir, the stronger the ability to store free gas. This part of the storage capacity is mainly contributed by large-diameter pores; the specific surface area can reflect the storage capacity of the shale reservoir for adsorbed gas. The larger the specific surface area of ​​shale, the stronger the ability to store adsorbed gas. This part of the storage capacity is provided by small-diameter pores. Compared with the prior art, the embodiments of the present invention consider the storage capacity of shale reservoirs for free gas and adsorbed gas respectively, and determine the pore volume index based on the mineral element logging data and density logging data at each depth point of the shale reservoir, and determine the specific surface area index based on the geothermal data and the total organic carbon content and resistivity logging data at each depth point of the shale reservoir, thereby greatly improving the accuracy of shale storage capacity analysis. Finally, although the embodiments of the present invention consider the pore volume and specific surface area, they do not actually calculate their actual values ​​through complex means, but propose a pore volume index that can reflect the actual value of the pore volume of the shale reservoir and a specific surface area index that can reflect the actual value of the specific surface area of ​​the shale reservoir. These two indices can be directly calculated using logging data, and the method is simple, effective, and easy to promote.

[0069] In the specific implementation, first, data is acquired, including logging data and geothermal data of the shale reservoir. The logging data includes, for example, mineral element logging data, density logging data, total organic carbon content, and resistivity logging data at each depth point of the shale reservoir. The geothermal data may include, for example, geothermal gradient, surface temperature and other data.

[0070] Then, the pore volume index of each depth point of the shale reservoir is determined according to the mineral element logging data and density logging data of each depth point of the shale reservoir, wherein the pore volume index reflects the actual value of the pore volume of the shale reservoir, that is, in the embodiment of the present invention, there is no need to calculate the true pore volume, and it is only necessary to determine the pore volume index that can reflect the actual value of the pore volume through the mineral element logging data and density logging data.

[0071] Mineral element logging data include the contents of major minerals in the formation, such as quartz content, feldspar content, calcite content, dolomite content, anhydrite content and clay mineral content. In addition, element logging can also provide the skeleton density of rocks, such as rock skeleton density and rock volume density. Thus, the pore volume index can be calculated based on the data in the mineral element logging data and density logging data that are positively correlated with the pore volume.

[0072] Figure 2 A specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present invention is as follows: Figure 2 As shown, according to 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 can be determined, which may include:

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

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

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

[0076] In one embodiment, determining the first parameter at each depth point of the shale reservoir according to the rock skeleton density and rock volume density at each depth point of the shale reservoir may include:

[0077] According to the following formula, the first parameter P at each depth point of the shale reservoir is determined based on the rock skeleton density and rock volume density at each depth point of the shale reservoir:

[0078]

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

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

[0081] F V =W DOL ×P

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

[0083] Therefore, in the embodiment of the present invention, the dolomite content and the porosity index (first parameter) are used to characterize the pore volume index, and then the shale storage capacity is analyzed. The larger the pore volume of the shale reservoir, the stronger the ability to store free gas, which is mainly contributed by large-diameter pores. Dolomite can provide a large number of intercrystalline pores, and these intercrystalline pores have a large pore size in the shale reservoir, which can store free gas. Porosity refers to the ratio of the sum of the volumes of all pore spaces in the rock to the volume of the rock sample. Experimental analysis found that there is a very good positive correlation between porosity and pore volume. Therefore, characterizing the pore volume by dolomite content and porosity, and then characterizing the storage capacity of the rock for free gas, can greatly improve the accuracy of the analysis of the free gas storage capacity.

[0084] In one embodiment, the logging data also includes acoustic logging data at various depth points of the shale reservoir, such as rock skeleton P-wave time difference and rock P-wave time difference;

[0085] In the embodiment of the present invention, the following may also be included:

[0086] According to the mineral element logging data, rock skeleton P-wave time difference, and rock P-wave time difference at each depth point of the shale reservoir, the pore volume index at 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 following formula, the first parameter P at each depth point of the shale reservoir is determined based on the rock skeleton P-wave time difference and rock P-wave time difference at each depth point of the shale reservoir:

[0088]

[0089] In the formula, AC ma is the rock skeleton longitudinal wave time difference, AC c It is the rock longitudinal wave time difference.

[0090] Porosity can be characterized not only by rock skeleton density and rock volume density, but also by acoustic wave time difference. The porosity index can be calculated in different ways, and the pore volume index can be calculated in different ways, which is more flexible.

[0091] After determining the pore volume index, the specific surface area index at each depth point of the shale reservoir is determined based on the geothermal data, the total organic carbon content at each depth point of the shale reservoir, and the resistivity logging data. 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 true specific surface area, but is calculated and solved using the data obtained that is positively correlated with the specific surface area.

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

[0093] Step 301, the resistivity logging data includes rock resistivity; according to the surface temperature, geothermal gradient and rock resistivity at each depth point of the shale reservoir, a second parameter at each depth point of the shale reservoir is determined; the second parameter reflects the actual thermal evolution degree of the shale reservoir;

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

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

[0096]

[0097]

[0098] 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.

[0099] Determining the specific surface area index at each depth point of the shale reservoir according to the total organic carbon content at each depth point of the shale reservoir and the second parameter may include:

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

[0101] F S =TOC×Y

[0102] Where TOC is the total organic carbon content.

[0103] In the embodiment of the present invention, the total organic carbon content and the thermal evolution degree index (second parameter) are used to characterize the specific surface area index, and then the shale storage capacity is analyzed. The specific surface area is positively correlated with the total organic carbon content and the thermal evolution degree. The larger the specific surface area of ​​shale, the stronger the ability of the reservoir to absorb gas, which is mainly provided by small-diameter organic pores. The more organic pores there are, the larger the specific surface area of ​​shale. The organic pores in shale reservoirs are an important pore type of source-reservoir integrated, low-porosity and permeability reservoirs, and are also one of the important signs that distinguish shale reservoirs from conventional sandstone and carbonate reservoirs. The organic pores are positively correlated with the total organic carbon content, so the higher the total organic carbon content, the stronger the ability of shale reservoirs to absorb gas. In the process of hydrocarbon generation from organic matter, as the degree of thermal evolution of the reservoir continues to increase, the hydrocarbon generation reaction continues, and the number of organic pores continues to increase. Therefore, the degree of thermal evolution can be used to characterize the organic pores, and then the ability of shale reservoirs to absorb gas. The degree of thermal evolution can be characterized by resistivity logging and formation temperature. Combined with the total organic carbon content, the logging data can be used to evaluate the storage capacity of shale reservoirs for adsorbed gas, which can greatly improve the accuracy of the analysis of adsorbed gas storage capacity.

[0104] In one embodiment, in order to improve the efficiency of shale reservoir capacity analysis, before determining the shale reservoir capacity analysis result according to the pore volume index and specific surface area index at each depth point of the shale reservoir, the following steps may also be included:

[0105] The pore volume index and specific surface area index at 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 normalized specific surface area index were used to obtain the shale storage capacity analysis results.

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

[0109] A well logging cross-plot is established based on the pore volume index and specific surface area index of multiple points at the same depth in the shale reservoir;

[0110] Collect the total gas content at multiple depths in shale reservoirs;

[0111] On the well logging intersection diagram, the shale reservoir is divided into multiple areas using the total gas content at multiple depth points of the shale reservoir; different areas have different levels of storage capacity effect.

[0112] In this example, in the first analysis, the total gas content of multiple depth points of the shale reservoir is obtained, and the normalized pore volume index and normalized specific surface area index corresponding to the depth of the total gas content data are used to establish a reservoir capacity evaluation chart, that is, a well logging intersection chart, and the total gas content data of the data points in the well logging intersection chart are classified. According to actual needs, the total gas content data points in different numerical ranges are divided into corresponding reservoir capacity levels, that is, the areas where different reservoir capacity effect levels are located can be obtained in the chart. In the subsequent shale reservoir capacity analysis, it is only necessary to calculate the pore volume index and specific surface area index corresponding to the shale reservoir depth point, and determine the reservoir capacity effect level of the shale reservoir depth point in the well logging intersection chart.

[0113] Taking the K1 well of the Neogene formation in the K area as an example, the well logging reservoir capacity analysis method in the embodiment of the present invention is described in detail:

[0114] 1. Basic address information.

[0115] The Neogene strata in the K region are a set of lacustrine shale strata, and the geological conditions are suitable for the application of the embodiments of the present invention.

[0116] 2. Get data.

[0117] The logging data of K1 well can be obtained by using the logging instruments, including dolomite content, rock skeleton density, rock volume density, rock skeleton P-wave time difference, rock P-wave time difference, rock total organic carbon content, rock resistivity. At the same time, the surface temperature and geothermal gradient of K1 well can be obtained.

[0118] 3. Calculate the pore volume index.

[0119] Substitute the logging data at the depth point into the following formula to obtain the pore volume index at the corresponding depth:

[0120]

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

[0122] Alternatively, the logging data at the depth point can be substituted into the following formula to obtain the pore volume index at the corresponding depth:

[0123]

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

[0125] 4. Calculate the specific surface area index.

[0126] Substitute the logging data at the depth point into the following formula to obtain the specific surface area index at the corresponding depth.

[0127]

[0128]

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

[0130] 5. Establish a reservoir capacity evaluation chart.

[0131] Pre-calculate multiple pore volume indexes and specific surface area indexes, normalize the multiple pore volume indexes and specific surface area indexes, and obtain normalized pore volume index and normalized specific surface area index. Then, use the normalized pore volume index and normalized specific surface area index corresponding to the depth of the total gas content data to establish a reservoir capacity evaluation chart, and divide the total gas content data points in different value ranges into corresponding reservoir capacity effect levels according to actual needs, that is, the areas where different reservoir capacity effect levels are located can be obtained in the chart. Figure 4 A specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present invention is as follows: Figure 4 As shown in the figure, the shale reservoir capacity of the K area can be divided into three levels, namely Class I, Class II and Class III. Class I has the best reservoir capacity, Class II is second, and Class III is relatively poor. The basis for classification is the total gas content corresponding to each data point. The total gas content is greater than 3.5m 3 The data points of / t represent Class I, with a total gas content of 2.0-3.5m 3 The data points with / t represent Class II, with a total gas content of less than 2.0m 3 Data points with / t represent Class III.

[0132] 6. Analyze reservoir capacity using single well logging data.

[0133] When the storage capacity of any shale reservoir depth point within the adaptability range of the region is subsequently analyzed, its storage capacity can be determined based on the classification level to which its pore volume index and specific surface area index fall.

[0134] Figure 5A specific embodiment of the shale reservoir capacity analysis method in the embodiment of the present invention is as follows: Figure 5 As shown in the figure, the normalized pore volume index curve and normalized specific surface area index curve of K1 well were calculated using the above K1 well data and formula. According to the calculation results, it is believed that the storage capacity of layers 1 and 2 in this well section is good. Later, gas testing was carried out on layer 1, and a daily gas production of 25,000 m 3 High-yield industrial gas flow. It is confirmed that the storage capacity of layer 1 is good, indicating that the shale storage capacity analysis results in the embodiment of the present invention are accurate.

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

[0136] First, in the embodiment of the present invention, shale storage capacity analysis can be achieved by acquiring logging data of shale reservoirs and directly analyzing and processing the logging data. Compared with the existing technology, it gets rid of the dependence on samples and experimental tests, and greatly reduces the cost of shale storage capacity analysis.

[0137] Secondly, the embodiments of the present invention fully consider the influencing factors of multiple shale storage capacity, including pore volume and specific surface area. Among them, the pore volume can reflect the storage capacity of shale reservoir for free gas. The larger the pore volume of the shale reservoir, the stronger the ability to store free gas. This part of the storage capacity is mainly contributed by large-diameter pores. The pore volume index in the embodiments of the present invention fully considers the dolomite content and porosity, and uses these two to analyze the storage capacity of shale reservoir for free gas; the specific surface area can reflect the storage capacity of shale reservoir for adsorbed gas. The larger the specific surface area of ​​shale, the stronger the ability to store adsorbed gas. This part of the storage capacity is provided by small-diameter pores. The specific surface area index in the embodiments of the present invention fully considers the total organic carbon content and the degree of thermal evolution, and uses these two to analyze the storage capacity of shale reservoir for adsorbed gas. Compared with the prior art, the embodiments of the present invention take into account the storage capacity of shale reservoirs for free gas and adsorbed gas respectively, and consider 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 storage capacity analysis.

[0138] Finally, although the embodiments of the present invention take pore volume and specific surface area into consideration, they do not actually calculate their actual values ​​through complex means. Instead, they propose a pore volume index that can reflect the actual value of the pore volume of the shale reservoir and a specific surface area index that can reflect the actual value of the specific surface area of ​​the shale reservoir. These two indices can be directly calculated using logging data. The method is simple, effective, and easy to promote.

[0139] The present invention also provides a shale storage capacity analysis device, as described in the following embodiments. Since the principle of the device to solve the problem is similar to that of the shale storage capacity analysis method, the implementation of the device can refer to the implementation of the shale storage capacity analysis method, and the repeated parts will not be repeated.

[0140] Figure 6 FIG. 1 is a schematic diagram of a shale storage capacity analysis device according to an embodiment of the present invention. Figure 6 As shown, the device comprises:

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

[0142] The pore volume index determination module 602 is used to determine the pore volume index of each depth point of the shale reservoir according to the mineral element logging data and density logging data of each depth point of the shale reservoir; the pore volume index reflects the actual value of the 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 each depth point of the shale reservoir according to the geothermal data and the total organic carbon content and resistivity logging data of 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 according to the pore volume index and specific surface area index at each depth point of the shale reservoir, and the shale reservoir capacity analysis results include the reservoir capacity effect levels of multiple different shale reservoir areas.

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

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

[0147] Determine a first parameter at each depth point of the shale reservoir according to the rock skeleton density and rock volume density at each depth point of the shale reservoir; the first parameter reflects the actual value of the porosity of the shale reservoir;

[0148] The pore volume index at each depth point of the shale reservoir is determined according to the dolomite content and the first parameter at each depth point of the shale reservoir.

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

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

[0151]

[0152] In the formula, ρ mais the rock skeleton density, ρ 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 following formula, the pore volume index F at each depth point of the shale reservoir is determined based on the dolomite content and the first parameter at each depth point of the shale reservoir: V :

[0155] F V =W DOL ×P

[0156] Where W DOL For 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 used for:

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

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

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

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

[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 used to:

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

[0168] FS =TOC×Y

[0169] Where TOC is the total organic carbon content.

[0170] In one embodiment, it further includes:

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

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

[0173] A well logging cross-plot is established based on the pore volume index and specific surface area index of multiple points at the same depth in the shale reservoir;

[0174] Collect the total gas content at multiple depths in shale reservoirs;

[0175] On the well logging intersection diagram, the shale reservoir is divided into multiple areas using the total gas content at multiple depth points of the shale reservoir; different areas have different levels of storage capacity effect.

[0176] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned shale reservoir capacity analysis method when executing the computer program.

[0177] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned shale reservoir capacity analysis method is implemented.

[0178] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above-mentioned shale reservoir capacity analysis method is implemented.

[0179] In the embodiment of the present invention, by acquiring the logging data and geothermal data of the shale reservoir, the logging data and geothermal data are directly analyzed and processed to realize the shale storage capacity analysis. Compared with the prior art, it gets rid of the dependence on samples and experimental tests, and greatly reduces the cost of shale storage capacity analysis. Secondly, the embodiment of the present invention fully considers multiple factors affecting the shale storage capacity, including pore volume and specific surface area. Among them, the pore volume can reflect the storage capacity of the shale reservoir for free gas. The larger the pore volume of the shale reservoir, the stronger the ability to store free gas. This part of the storage capacity is mainly contributed by large-diameter pores; the specific surface area can reflect the storage capacity of the shale reservoir for adsorbed gas. The larger the specific surface area of ​​shale, the stronger the ability to store adsorbed gas. This part of the storage capacity is provided by small-diameter pores. Compared with the prior art, the embodiments of the present invention consider the storage capacity of shale reservoirs for free gas and adsorbed gas respectively, and determine the pore volume index based on the mineral element logging data and density logging data at each depth point of the shale reservoir, and determine the specific surface area index based on the geothermal data and the total organic carbon content and resistivity logging data at each depth point of the shale reservoir, thereby greatly improving the accuracy of shale storage capacity analysis. Finally, although the embodiments of the present invention consider the pore volume and specific surface area, they do not actually calculate their actual values ​​through complex means, but propose a pore volume index that can reflect the actual value of the pore volume of the shale reservoir and a specific surface area index that can reflect the actual value of the specific surface area of ​​the shale reservoir. These two indices can be directly calculated using logging data, and the method is simple, effective, and easy to promote.

[0180] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0181] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a 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 generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0182] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0183] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0184] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is 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 in the scope of protection of the present invention.

Claims

1. A shale reservoir capacity analysis method, characterized in that: include: Acquire logging data and geothermal data of shale reservoirs; the logging data include mineral element logging data, density logging data, total organic carbon content, and resistivity logging data at each depth point of the shale reservoir; Determine the pore volume index at each depth point of the shale reservoir based on the mineral element logging data and density logging data at each depth point of the shale reservoir; The pore volume index reflects the actual value of the pore volume of the shale reservoir; Determine the specific surface area index at each depth point of the shale reservoir according to the geothermal data and the 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; The shale reservoir capacity analysis result is determined according to the pore volume index and specific surface area index at each depth point of the shale reservoir, and the shale reservoir capacity analysis result includes the reservoir capacity effect levels of multiple different shale reservoir areas.

2. The method according to claim 1, characterized in that The mineral element logging data includes dolomite content, and the density logging data includes rock skeleton density and rock volume density; According to 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, including: Determine a first parameter at each depth point of the shale reservoir according to the rock skeleton density and rock volume density at each depth point of the shale reservoir; the first parameter reflects the actual value of the porosity of the shale reservoir; The pore volume index at each depth point of the shale reservoir is determined according to the dolomite content and the first parameter at each depth point of the shale reservoir.

3. The method according to claim 2, characterized in that According to the rock skeleton density and rock volume density at each depth point of the shale reservoir, the first parameter of each depth point of the shale reservoir is determined, including: According to the following formula, the first parameter P at each depth point of the shale reservoir is determined based on the rock skeleton density and rock volume density at each depth point of the shale reservoir: In the formula, ρ ma is the rock skeleton density, ρ b is the rock bulk density.

4. The method according to claim 3, characterized in that According to 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, including: According to the following formula, the pore volume index F at each depth point of the shale reservoir is determined based on the dolomite content and the first parameter at each depth point of the shale reservoir: V : F V =W DOL ×P Where W DOL For the dolomite content.

5. The method according to claim 1, characterized in that The resistivity logging data includes rock resistivity, and the geothermal data includes surface temperature and geothermal gradient; According to the geothermal data, the total organic carbon content at each depth point of the shale reservoir, and the resistivity logging data, the specific surface area index at each depth point of the shale reservoir is determined, including: Determine a second parameter at each depth point of the shale reservoir according to the surface temperature, the geothermal gradient and the rock resistivity at each depth point of the shale reservoir; the second parameter reflects the actual thermal evolution degree of the shale reservoir; The specific surface area index at each depth point of the shale reservoir is determined according to the total organic carbon content at each depth point of the shale reservoir and the second parameter.

6. The method according to claim 5, characterized in that According to the surface temperature, geothermal gradient and rock resistivity at each depth point of the shale reservoir, the second parameter at each depth point of the shale reservoir is determined, including: According to the following formula, the second parameter Y at each depth point of the shale reservoir is determined based on the surface temperature, geothermal gradient and rock resistivity at each depth point of the shale reservoir: 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.

7. The method according to claim 6, characterized in that According to the total organic carbon content and the second parameter at each depth point of the shale reservoir, the specific surface area index at each depth point of the shale reservoir is determined, including: According to the following formula, the specific surface area index F at each depth point of the shale reservoir is determined based on the total organic carbon content at each depth point of the shale reservoir and the second parameter: S : F S =TOC×Y Where TOC is the total organic carbon content.

8. The method according to claim 1, characterized in that According to the pore volume index and specific surface area index at each depth point of the shale reservoir, before determining the shale storage capacity analysis results, it also includes: The pore volume index and specific surface area index at each depth point of the shale reservoir are normalized.

9. The method according to claim 1, characterized in that According to the pore volume index and specific surface area index at each depth point of the shale reservoir, the shale storage capacity analysis results are determined, including: A well logging cross-plot is established based on the pore volume index and specific surface area index of multiple points at the same depth in the shale reservoir; Collect the total gas content at multiple depths in shale reservoirs; On the well logging intersection diagram, the shale reservoir is divided into multiple areas using the total gas content at multiple depth points of the shale reservoir; different areas have different levels of storage capacity effect.

10. A shale reservoir capacity analysis device, characterized in that: include: A data acquisition module is used to acquire well logging data and geothermal data of the shale reservoir; the well logging data includes mineral element well logging data, density well logging data, total organic carbon content, and resistivity well logging data at each depth point of the shale reservoir; A pore volume index determination module is used to determine the pore volume index of each depth point of the shale reservoir according to the mineral element logging data and density logging data of each depth point of the shale reservoir; The pore volume index reflects the actual value of the pore volume of the shale reservoir; A specific surface area index determination module is used to determine the specific surface area index of each depth point of the shale reservoir according to geothermal data and the total organic carbon content and resistivity logging data of 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; The result output module is used to determine the shale reservoir capacity analysis results according to the pore volume index and specific surface area index at each depth point of the shale reservoir, and the shale reservoir capacity analysis results include the reservoir capacity effect levels of multiple different shale reservoir areas.

11. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

13. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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