Method and apparatus for determining minimum horizontal principal stress of shale oil reservoir

Abstract

The present invention relates to the technical field of oil-gas exploration. Provided are a method and apparatus for determining the minimum horizontal principal stress of a shale oil reservoir. The method comprises: using a shallow resistivity curve to calibrate a conductivity curve, so as to obtain a high-resolution resistivity curve; using oil porosity information to calibrate nuclear-magnetic-resonance-logging data, so as to determine a continuous oil saturation curve; determining a continuous saturation index curve according to elemental capture spectroscopy data and rock electrical-experiment data; determining a high-resolution full-water-saturation resistivity curve according to the high-resolution resistivity curve, the continuous oil saturation curve and the continuous saturation index curve; using a high-resolution static Young's modulus calculation model to determine a high-resolution static Young's modulus; and further determining a continuous minimum horizontal principal stress. The present invention can improve the resolution of the minimum horizontal principal stress of a shale oil reservoir.

Description

Method and device for determining minimum horizontal principal stress of shale oil reservoir Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration, and in particular to a method and device for determining the minimum horizontal principal stress of a shale oil reservoir. Background Art

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

[0003] In the exploration and development of shale oil and gas, geostress is an essential parameter for drilling and fracturing. Accurate minimum horizontal principal stress can effectively guide horizontal wellbore trajectory design, shale sweet spot prediction, and the evaluation of reservoir fracture compressibility. However, shale reservoirs are characterized by significant heterogeneity and well-developed laminae. The thickness of individual laminae is far less than the vertical resolution of well logging curves. Due to the influence of the laminae structure, well logging curves measured by conventional logging instruments cannot reflect true formation information. Therefore, the resolution of minimum horizontal principal stress determined using conventional logging data is low and cannot meet the technical requirements of shale oil and gas exploration and development.

[0004] Summary of the Invention

[0005] An embodiment of the present invention provides a method for determining the minimum horizontal principal stress of a shale oil reservoir, for improving the resolution of the determined minimum horizontal principal stress of the shale oil reservoir. The method includes:

[0006] Obtain shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data, and overlying formation pressure of a specified shale oil reservoir; the overlying formation pressure is determined by a density integration method;

[0007] The conductivity curve in the microresistivity imaging logging data is calibrated using the shallow resistivity curve in the shallow resistivity logging data to obtain a high-resolution resistivity curve for the specified shale oil reservoir;

[0008] Using the oil-bearing porosity information from core analysis data, the NMR logging data is calibrated to determine the continuous oil saturation curve for a specified shale oil reservoir;

[0009] Determine the continuous saturation index curve of the specified shale oil reservoir based on the different mineral content information in the element logging data and the rock electrical experimental data;

[0010] Determine the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir based on the high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir;

[0011] Analyzing the lithology of the designated shale oil reservoir based on the core analysis data to determine the lithology type of the designated shale oil reservoir, wherein the lithology type is plastic rock or brittle rock;

[0012] According to the lithologic type and fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir, a high-resolution static Young's modulus calculation model corresponding to the lithologic type of the specified shale oil reservoir is selected to determine the high-resolution static Young's modulus of the specified shale oil reservoir;

[0013] The high-resolution static Young's modulus and overlying formation pressure of a specified shale oil reservoir are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

[0014] An embodiment of the present invention further provides a device for determining the minimum horizontal principal stress of a shale oil reservoir, for improving the resolution of the determined minimum horizontal principal stress of a shale oil reservoir. The device comprises:

[0015] An acquisition module is used to obtain shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data, and overlying formation pressure of a specified shale oil reservoir; the overlying formation pressure is determined by a density integration method;

[0016] The resistivity determination module is used to calibrate the conductivity curve in the microresistivity imaging logging data using the shallow resistivity curve in the shallow resistivity logging data to obtain a high-resolution resistivity curve for the specified shale oil reservoir;

[0017] The oil saturation determination module is used to use the oil porosity information in the core analysis data to calibrate the nuclear magnetic resonance logging data and determine the continuous oil saturation curve of the specified shale oil reservoir;

[0018] The saturation index determination module is used to determine the continuous saturation index curve of the specified shale oil reservoir based on the different mineral content information in the element logging data and the rock electrical experimental data;

[0019] The first processing module is configured to determine a completely water-bearing high-resolution resistivity curve of the specified shale oil reservoir based on the high-resolution resistivity curve, the continuous oil saturation curve, and the continuous saturation index curve of the specified shale oil reservoir;

[0020] A lithology determination module is used to analyze the lithology of a specified shale oil reservoir based on core analysis data and determine the lithology type of the specified shale oil reservoir, wherein the lithology type is plastic rock or brittle rock;

[0021] The second processing module is configured to select a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir according to the lithology type and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir, and determine the high-resolution static Young's modulus of the specified shale oil reservoir;

[0022] The third processing module is used to input the high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

[0023] An embodiment of the present invention also provides a computer device, including 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 method for determining the minimum horizontal principal stress of a shale oil reservoir is implemented.

[0024] An embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned method for determining the minimum horizontal principal stress of a shale oil reservoir.

[0025] An embodiment of the present invention also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the above-mentioned method for determining the minimum horizontal principal stress of a shale oil reservoir.

[0026] In the embodiment of the present invention, compared with the existing technical solution of determining the minimum horizontal principal stress using conventional logging data, the advantage of high resolution of microresistivity imaging logging data is utilized to calibrate the conductivity curve in the microresistivity imaging logging data according to the shallow resistivity curve in the shallow resistivity logging data of the specified shale oil reservoir, thereby obtaining a high-resolution resistivity curve of the specified shale oil reservoir. In addition, the oil-bearing porosity information in the core analysis data of the specified shale oil reservoir is utilized to calibrate the nuclear magnetic resonance logging data to determine the continuous oil saturation curve of the specified shale oil reservoir. The continuous oil saturation curve of the specified shale oil reservoir is determined according to the different mineral content information in the element logging data of the specified shale oil reservoir and the rock electrical experimental data. Saturation index curve; based on the high-resolution resistivity curve, continuous oil saturation curve, and continuous saturation index curve of the specified shale oil reservoir, determine the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir; then, after determining the lithologic type of the specified shale oil reservoir, determine the high-resolution static Young's modulus of the specified shale oil reservoir through the predetermined correlation between the fully water-bearing high-resolution resistivity curve and the high-resolution static Young's modulus, i.e., the high-resolution static Young's modulus calculation model; then, input the high-resolution static Young's modulus of the specified shale oil reservoir and the overlying formation pressure into the predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir. In this way, the problem of low resolution in determining the minimum horizontal principal stress using conventional well logging data in the existing technology can be solved, the resolution of the determined minimum horizontal principal stress of the shale oil reservoir can be improved, and a technical tool can be provided for the exploration and development of shale oil and gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0028] FIG1 is a flow chart of a method for determining the minimum horizontal principal stress of a shale oil reservoir provided in an embodiment of the present invention;

[0029] FIG2( a ) is a schematic diagram of a high-resolution static Young's modulus calculation model for plastic rock provided in an embodiment of the present invention;

[0030] FIG2( b ) is a schematic diagram of a high-resolution static Young's modulus calculation model for brittle rock provided in an embodiment of the present invention;

[0031] FIG3 is a schematic diagram of the error of the static Young's modulus corresponding to Table 1 provided in an embodiment of the present invention;

[0032] FIG4 is a schematic diagram of the calculated continuous minimum horizontal principal stress provided in an embodiment of the present invention;

[0033] FIG5 is a schematic diagram of the error of the minimum horizontal principal stress corresponding to Table 2 provided in an embodiment of the present invention;

[0034] FIG6 is a schematic diagram of a device for determining the minimum horizontal principal stress of a shale oil reservoir provided in an embodiment of the present invention;

[0035] FIG7 is a schematic diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to 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.

[0037] The term "and / or" herein simply describes an association relationship, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, and the existence of B alone. In addition, the term "at least one" herein refers to any combination of at least two of any one or more of a plurality of items. For example, "at least one of A, B, and C" can represent any one or more elements selected from the set consisting of A, B, and C.

[0038] In the description of this specification, the terms "include", "including", "have", "contain", etc. are all open terms, which mean including but not limited to. The descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. The order of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of steps therein is not limited and can be appropriately adjusted as needed.

[0039] Research has found that in the exploration and development of shale oil and gas, geostress is an essential parameter for drilling and fracturing. Accurate minimum horizontal principal stress can effectively guide horizontal wellbore trajectory design, shale sweet spot prediction, and the evaluation of reservoir fracture compressibility. However, shale reservoirs are significantly heterogeneous, with well-developed laminae. The thickness of individual laminae is far less than the vertical resolution of logging curves. Due to the influence of laminae, logging curves measured by conventional logging instruments cannot reflect true formation information. Therefore, the resolution of minimum horizontal principal stress determined using conventional logging data is low and cannot meet the technical requirements of shale oil and gas exploration and development.

[0040] In response to the above research, an embodiment of the present invention proposes a method and device for determining the minimum horizontal principal stress of a shale oil reservoir, which can solve the problem of low resolution in determining the minimum horizontal principal stress using conventional logging data in the prior art.

[0041] FIG1 is a flow chart of a method for determining the minimum horizontal principal stress of a shale oil reservoir provided by an embodiment of the present invention. The method includes the following steps:

[0042] Step 101, obtaining shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data, and overlying formation pressure of a specified shale oil reservoir; the overlying formation pressure is determined by a density integration method;

[0043] Step 102, calibrating the conductivity curve in the microresistivity imaging logging data using the shallow resistivity curve in the shallow resistivity logging data to obtain a high-resolution resistivity curve of the specified shale oil reservoir;

[0044] Step 103, using the oil-bearing porosity information in the core analysis data, calibrate the nuclear magnetic resonance logging data to determine a continuous oil saturation curve for the specified shale oil reservoir;

[0045] Step 104, determining a continuous saturation index curve for a specified shale oil reservoir based on different mineral content information in the element logging data and rock electrical experimental data;

[0046] Step 105, determining a completely water-bearing high-resolution resistivity curve of the specified shale oil reservoir based on the high-resolution resistivity curve, the continuous oil saturation curve, and the continuous saturation index curve of the specified shale oil reservoir;

[0047] Step 106: Analyze the lithology of the designated shale oil reservoir based on the core analysis data to determine the lithology type of the designated shale oil reservoir, wherein the lithology type is plastic rock or brittle rock;

[0048] Step 107, selecting a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir and a fully water-bearing high-resolution resistivity curve, and determining the high-resolution static Young's modulus of the specified shale oil reservoir;

[0049] Step 108 , inputting the high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

[0050] In the embodiment of the present invention, compared with the existing technical solution of determining the minimum horizontal principal stress using conventional logging data, the advantage of high resolution of microresistivity imaging logging data is utilized to calibrate the conductivity curve in the microresistivity imaging logging data according to the shallow resistivity curve in the shallow resistivity logging data of the specified shale oil reservoir, thereby obtaining a high-resolution resistivity curve of the specified shale oil reservoir. In addition, the oil-bearing porosity information in the core analysis data of the specified shale oil reservoir is utilized to calibrate the nuclear magnetic resonance logging data to determine the continuous oil saturation curve of the specified shale oil reservoir. The continuous oil saturation curve of the specified shale oil reservoir is determined according to the different mineral content information in the element logging data of the specified shale oil reservoir and the rock electrical experimental data. Saturation index curve; based on the high-resolution resistivity curve, continuous oil saturation curve, and continuous saturation index curve of the specified shale oil reservoir, determine the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir; then, after determining the lithologic type of the specified shale oil reservoir, determine the high-resolution static Young's modulus of the specified shale oil reservoir through the predetermined correlation between the fully water-bearing high-resolution resistivity curve and the high-resolution static Young's modulus, i.e., the high-resolution static Young's modulus calculation model; then, input the high-resolution static Young's modulus of the specified shale oil reservoir and the overlying formation pressure into the predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir. In this way, the problem of low resolution in determining the minimum horizontal principal stress using conventional well logging data in the existing technology can be solved, the resolution of the determined minimum horizontal principal stress of the shale oil reservoir can be improved, and a technical tool can be provided for the exploration and development of shale oil and gas.

[0051] The following is a detailed description of the method for determining the minimum horizontal principal stress of a shale oil reservoir shown in FIG1 .

[0052] In the above step 101, logging data of the specified shale oil reservoir can be obtained, including: shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data and overlying formation pressure of the specified shale oil reservoir.

[0053] Among them, the shallow resistivity curve is extracted from the shallow resistivity logging data; the conductivity curve is extracted from the microresistivity imaging logging data; the element logging data includes information on the content of different minerals; and the overlying formation pressure is determined by the density integration method.

[0054] In the above step 102, the shallow resistivity curve can be used to calibrate the conductivity curve in the microresistivity imaging logging data to obtain a high-resolution resistivity curve Rhr of the specified shale oil reservoir.

[0055] In the above step 103, the oil-bearing porosity information in the core analysis data can be used to calibrate the nuclear magnetic resonance logging data to determine the continuous oil saturation curve So of the specified shale oil reservoir.

[0056] In specific implementation, the core of the specified shale oil reservoir is analyzed to determine the discrete oil porosity information of the specified shale oil reservoir. The discrete oil porosity information is used to calibrate the continuous nuclear magnetic resonance logging data to obtain the continuous oil saturation curve So of the specified shale oil reservoir.

[0057] In the above step 104, a continuous saturation index curve of a specified shale oil reservoir can be determined based on different mineral content information in the element logging data and rock electrical experimental data.

[0058] In practice, the mineral type and mineral content of shale oil reservoirs will affect the saturation index value. Therefore, it is necessary to combine rock electrical experimental data and elemental logging mineral content processing results to select sensitive minerals and then determine the continuous saturation index curve. Specifically, the discrete saturation index information of the rock electrical experimental data of a specific shale oil reservoir can be obtained and matched with the different mineral content information to obtain the continuous saturation index curve n for the specified shale oil reservoir.

[0059] In the above step 105, the fully water-containing high-resolution resistivity curve of the specified shale oil reservoir can be determined based on the high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the above-mentioned specified shale oil reservoir.

[0060] During specific implementation, a complete water-containing high-resolution resistivity calculation model can be constructed, and the complete water-containing high-resolution resistivity curve of the specified shale oil reservoir can be determined based on the complete water-containing high-resolution resistivity calculation model.

[0061] In one embodiment, step 105 may specifically include:

[0062] The high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir are input into a pre-built complete water-bearing high-resolution resistivity calculation model to determine the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir.

[0063] In one embodiment, the pre-built fully water-containing high-resolution resistivity calculation model is as follows: Ro = (1-So) n ×Rhr

[0064] Among them, Ro is the high-resolution resistivity of the fully water-bearing area; So is the continuous oil saturation curve; n is the continuous saturation index curve; Rhr is the high-resolution resistivity curve.

[0065] In practice, by substituting the high-resolution resistivity curve, continuous oil saturation curve, and continuous saturation index curve of a specified shale oil reservoir into the above formula 1, the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir can be calculated. This eliminates the influence of oil and gas on the static Young's modulus, retaining only the influence of minerals and lithology on the static Young's modulus.

[0066] In the above step 106, in order to classify the lithology of the shale oil reservoir, the lithology of the designated shale oil reservoir is analyzed based on the core analysis data to determine whether the lithology type of the designated shale oil reservoir is plastic rock or brittle rock.

[0067] In specific implementation, depth retrieval can be performed based on the core analysis data of the core sampled from the drilling, and the logging lithology sensitive parameters of the corresponding depth points can be read to determine whether the specified shale oil reservoir is a plastic rock mainly composed of plastic minerals such as illite, chlorite, and kerogen, or a brittle rock mainly composed of brittle minerals such as quartz and dolomite.

[0068] In the above step 107, after determining the lithologic type of the specified shale oil reservoir, a high-resolution static Young's modulus calculation model corresponding to the lithologic type of the specified shale oil reservoir can be selected, and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir can be input into the high-resolution static Young's modulus calculation model corresponding to the lithologic type of the shale oil reservoir to determine the high-resolution static Young's modulus E of the specified shale oil reservoir. sta .

[0069] In one embodiment, before step 107, the following steps may also be included:

[0070] The high-resolution static Young's modulus calculation model for plastic rock and the high-resolution static Young's modulus calculation model for brittle rock are established in the following way:

[0071] By conducting triaxial compression tests on shale oil reservoirs with known plastic rock lithology, static Young's modulus data and a fully water-bearing high-resolution resistivity curve of the experimentally analyzed plastic rock were obtained. A first correlation relationship was established between the static Young's modulus data of the plastic rock and the fully water-bearing high-resolution resistivity curve. An intersection analysis was performed on the first correlation relationship to establish a high-resolution static Young's modulus calculation model for plastic rock.

[0072] By conducting triaxial compression experiments on shale oil reservoirs with known brittle rock lithology, the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock were obtained. A second correlation was established between the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock. An intersection analysis was performed on the second correlation to establish a high-resolution static Young's modulus calculation model corresponding to brittle rock.

[0073] In specific implementation, after analysis, it was found that the different contents of mineral components in the shale oil reservoir will lead to changes in the static Young's modulus. The higher the content of brittle minerals such as quartz and dolomite, the greater the static Young's modulus of the reservoir; the higher the content of clay plastic minerals such as illite and chlorite, the smaller the static Young's modulus of the reservoir. Different mineral component contents also lead to changes in the resistivity of the shale oil reservoir. The higher the content of brittle minerals such as quartz and dolomite, the greater the resistivity of the reservoir; the higher the content of clay plastic minerals such as illite and chlorite, the smaller the resistivity of the reservoir. Therefore, it can be obtained that the resistivity of the shale oil reservoir is well correlated with the static Young's modulus of plastic rock and brittle rock. Based on the above analysis, the experimental data of the triaxial compression mechanical experiment can be used to obtain the experimentally analyzed Young's modulus and the fully water-containing high-resolution resistivity curve R O , and establish high-resolution static Young's modulus calculation models for plastic rock and brittle rock respectively.

[0074] In specific implementation, the fully water-containing high-resolution resistivity curve R O A correlation, i.e., a first correlation or a second correlation, is established with the static Young's modulus data, and a high-resolution static Young's modulus calculation model is established through intersection analysis. It should be noted that the above analysis of plastic minerals primarily focuses on clay plastic minerals such as illite and chlorite. When the plastic mineral is kerogen, the higher the kerogen content, the smaller the static Young's modulus of the reservoir, but the greater the resistivity of the reservoir. Since the kerogen content of the shale reservoir in the embodiment of the present invention is low, its impact on the fully water-bearing high-resolution resistivity is negligible. Therefore, the established high-resolution static Young's modulus calculation model for plastic rock is primarily a high-resolution static Young's modulus calculation model for plastic rock composed primarily of clay plastic minerals such as illite and chlorite.

[0075] In one embodiment, the high-resolution static Young's modulus calculation model for plastic rock is as follows: E sta1 =a1×lnRo+m1

[0076] Where Ro is the high-resolution resistivity of fully hydrated water; E sta1 is the high-resolution static Young's modulus of plastic rock, a1 and m1 are different constants; E sta1 Negatively correlated with Ro.

[0077] In one embodiment, the high-resolution static Young's modulus calculation model for brittle rock is as follows: Equation 3: sta2 =a2×lnRo+m2

[0078] Where Ro is the high-resolution resistivity of fully hydrated water; E sta2 is the high-resolution static Young's modulus of brittle rock; a2 and m2 are different constants; E sta2 Positively correlated with Ro.

[0079] In specific implementation, the high-resolution static Young's modulus of the specified shale oil reservoir can be calculated by substituting the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir into the above formula 2 or formula 3 according to the lithologic type of the specified shale oil reservoir.

[0080] It should be noted that since the high-resolution static Young's modulus corresponding to plastic rock is negatively correlated with the high-resolution resistivity of fully water-bearing rock, a1 is less than 0; since the high-resolution static Young's modulus corresponding to brittle rock is positively correlated with the high-resolution resistivity of fully water-bearing rock, a2 is greater than 0.

[0081] In the above step 108, the high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir can be input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

[0082] In specific implementation, determine the minimum horizontal principal stress SH min The required parameters are: overlying formation pressure S v , static Young's modulus E sta , and the power theorem index B (first power theorem index), N (second power theorem index). Among them, B is about the static Young's modulus E sta function of , N is a function of the exponent B.

[0083] In one embodiment, the above step 108 may specifically include:

[0084] determining a first power theorem exponent based on a high-resolution static Young's modulus of a specified shale oil reservoir and a predefined functional expression of the first power theorem exponent and the static Young's modulus;

[0085] determining a second power theorem exponent based on a high-resolution static Young's modulus of a specified shale oil reservoir, a first power theorem exponent, and a predefined functional expression of the first power theorem exponent and the static Young's modulus and the second power theorem exponent;

[0086] The second power theorem exponent, the high-resolution static Young's modulus of the specified shale oil reservoir and the overlying formation pressure are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

[0087] In one embodiment, the continuous minimum horizontal principal stress calculation model is as follows:

[0088] Among them, SH min is the continuous minimum horizontal principal stress, in MPa;

[0089] S v is the overlying formation pressure, in MPa;

[0090] E sta is the high-resolution static Young's modulus;

[0091] B is the first power theorem index, the unit is MPa, the predefined first power theorem index and the functional expression of the static Young's modulus are:

[0092] N is the second power theorem index, the unit is MPa, the predefined first power theorem index and the static Young's modulus and the second power theorem index function expression is N = s × log (E sta , B)+t;

[0093] c, d, e, f, g, h, r, s, and t are different constants.

[0094] In specific implementation, the coefficient of Formula 4 in the continuous minimum horizontal principal stress calculation model can be adjusted by analyzing the degree of consistency between the minimum horizontal principal stress calculated by the plastic geostress model and the minimum horizontal principal stress obtained by the Kaiser effect experiment. After the numerical values ​​of the minimum horizontal principal stress calculated by the plastic geostress model and the minimum horizontal principal stress obtained by the Kaiser effect experiment are consistent, the continuous minimum horizontal principal stress calculation model is obtained.

[0095] In specific implementation, the high-resolution static Young's modulus of a specified shale oil reservoir can be substituted into the formula Obtain the first power theorem index B; Substitute the high-resolution static Young's modulus and the first power theorem index B of the specified shale oil reservoir into the formula N = s × log (E sta , B)+t, and obtain the second power theorem index N. Then, the second power theorem index N and the high-resolution static Young's modulus E of the specified shale oil reservoir are combined. sta and the overlying formation pressure S v Substituting into formula 4, the continuous minimum horizontal principal stress SH of the specified shale oil reservoir is obtained min .

[0096] In this way, the above-mentioned method for determining the minimum horizontal principal stress of a shale oil reservoir can solve the problem of low resolution in determining the minimum horizontal principal stress using conventional logging data in the prior art, and improve the resolution of the determined minimum horizontal principal stress of a shale oil reservoir; moreover, in the embodiment of the present invention, all parameters used to determine the minimum horizontal principal stress can be calculated from other logging data without adding new costs.

[0097] In order to more clearly understand the method for determining the minimum horizontal principal stress of a shale oil reservoir provided in an embodiment of the present invention, a specific example is used below to illustrate.

[0098] Take the shale oil reservoir of a certain well in a certain basin as an example. The specific steps are as follows:

[0099] (1) Calibrate the microresistivity imaging logging data of a shale oil reservoir in a well to generate a high-resolution resistivity curve R hr

[0100] The conductivity curve in the microresistivity imaging logging data is calibrated using the conventional logging shallow resistivity curve of a shale oil reservoir (the shallow resistivity curve in the shallow resistivity logging data) to generate a high-resolution resistivity curve R hr .

[0101] (2) Continuously calculate the continuous oil saturation curve using the nuclear magnetic resonance logging data of a shale oil reservoir in a certain well

[0102] The oil-bearing porosity of a shale oil reservoir in a well was analyzed using core data, and the nuclear magnetic resonance logging data was calibrated to obtain the continuous oil saturation So.

[0103] (3) Continuously calculate the continuous saturation index curve using the element logging data of a shale oil reservoir in a certain well

[0104] Combining the rock electrical experimental data and the different mineral content information in the element logging data, sensitive minerals are selected and the continuous saturation index curve n is determined.

[0105] (4) Constructing a fully water-containing high-resolution resistivity R O

[0106] Construct a fully water-bearing high-resolution resistivity calculation model as shown in Formula 1, and use the high-resolution resistivity curve R hr , continuous oil saturation So, continuous saturation index curve n, determine the complete water-bearing high-resolution resistivity curve R of a shale oil reservoir in a well O .

[0107] (5) Select sensitive parameters to classify the lithology of shale oil reservoir in a certain well

[0108] Depth retrieval is performed based on the core analysis data of the core sampled from the drilling, and the logging lithology sensitive parameters at the corresponding depth points are read to determine whether the shale oil reservoir of a certain well is a plastic rock mainly composed of plastic minerals such as illite, chlorite, and kerogen, or a brittle rock mainly composed of brittle minerals such as quartz and dolomite.

[0109] (6) Using the data from triaxial compression experiments, high-resolution static Young's modulus calculation models are established for plastic rock and brittle rock respectively.

[0110] A correlation was established between the fully water-bearing high-resolution resistivity curve of the triaxial compression test and the static Young's modulus data. The correlation was cross-analyzed, and the high-resolution static Young's modulus under plastic rock and brittle rock conditions was established according to Formula 2 and Formula 3.

[0111] As shown in Figure 2(a), it is a schematic diagram of the high-resolution static Young's modulus calculation model for plastic rock. In Figure 2(a), the formula for the high-resolution static Young's modulus calculation model for plastic rock is:

[0112] E sta =-1.68×lnRo+36.823, R=0.83.

[0113] As shown in Figure 2(b), it is a schematic diagram of the high-resolution static Young's modulus calculation model for brittle rock. In Figure 2(b), the formula for the high-resolution static Young's modulus calculation model for brittle rock is:

[0114] E sta =2.8909×lnRo+15.835, R=0.87.

[0115] The high-resolution static Young's modulus calculated in accordance with the present invention is compared with the static Young's modulus obtained from core experimental analysis to obtain an error analysis table for the static Young's modulus calculation model shown in Table 1. FIG3 is a schematic diagram of the error of the static Young's modulus corresponding to Table 1. It can be seen that the absolute error is small (1.54 GPa), and the accuracy is fully capable of meeting the technical requirements of shale oil and gas exploration and development.

[0116] Table 1 Error analysis table of static Young's modulus calculation model

[0117] (7) Calculation of continuous minimum horizontal principal stress using high-resolution static Young's modulus N=0.0073×log(E sta , B)+0.0088;

[0118] First, high-resolution static Young's modulus is used to calculate B and N respectively, and then the continuous minimum horizontal principal stress SH is calculated. min .

[0119] FIG4 is a schematic diagram of the calculated continuous minimum horizontal principal stress provided by an embodiment of the present invention.

[0120] The continuous minimum horizontal principal stress calculated by the embodiment of the present invention is compared with the minimum horizontal principal stress obtained by core experimental analysis, and an error analysis table of the minimum horizontal principal stress calculation model is obtained as shown in Table 2. As shown in Figure 5, which is a schematic diagram of the error of the minimum horizontal principal stress corresponding to Table 2, it can be seen that the absolute error is small (2.65 MPa), and the accuracy can fully meet the technical requirements of shale oil and gas exploration and development.

[0121] Table 2 Error analysis table of minimum horizontal principal stress calculation model

[0122] The present invention also provides an apparatus for determining the minimum horizontal principal stress of a shale oil reservoir, as described in the following embodiments. Because the principles underlying the apparatus are similar to those of the method for determining the minimum horizontal principal stress of a shale oil reservoir, the implementation of the apparatus can be referenced to the implementation of the method for determining the minimum horizontal principal stress of a shale oil reservoir, and any repetitions will not be repeated.

[0123] FIG6 is a schematic diagram of a device for determining the minimum horizontal principal stress of a shale oil reservoir provided by an embodiment of the present invention. The device may include:

[0124] Acquisition module 601 is used to acquire shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data, and overlying formation pressure of the specified shale oil reservoir; the overlying formation pressure is determined by density integration method;

[0125] The resistivity determination module 602 is used to calibrate the conductivity curve in the microresistivity imaging logging data using the shallow resistivity curve in the shallow resistivity logging data to obtain a high-resolution resistivity curve of the specified shale oil reservoir;

[0126] The oil saturation determination module 603 is used to use the oil porosity information in the core analysis data to calibrate the nuclear magnetic resonance logging data and determine the continuous oil saturation curve of the specified shale oil reservoir;

[0127] The saturation index determination module 604 is used to determine the continuous saturation index curve of the specified shale oil reservoir based on the different mineral content information in the element logging data and the rock electrical experimental data;

[0128] The first processing module 605 is configured to determine a completely water-bearing high-resolution resistivity curve of the specified shale oil reservoir based on the high-resolution resistivity curve, the continuous oil saturation curve, and the continuous saturation index curve of the specified shale oil reservoir;

[0129] The lithology determination module 606 is used to analyze the lithology of the specified shale oil reservoir according to the core analysis data and determine the lithology type of the specified shale oil reservoir, wherein the lithology type is plastic rock or brittle rock;

[0130] The second processing module 607 is configured to select a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir based on the lithology type and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir, and determine the high-resolution static Young's modulus of the specified shale oil reservoir;

[0131] The third processing module 608 is used to input the high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

[0132] In one embodiment, the first processing module may be specifically configured to:

[0133] The high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir are input into a pre-built complete water-bearing high-resolution resistivity calculation model to determine the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir.

[0134] In one embodiment, the pre-built fully water-containing high-resolution resistivity calculation model is as follows: Ro = (1-So) n ×Rhr

[0135] Among them, Ro is the high-resolution resistivity of the fully water-bearing area; So is the continuous oil saturation curve; n is the continuous saturation index curve; Rhr is the high-resolution resistivity curve.

[0136] In one embodiment, a model building module may also be included, which is used before the second processing module selects a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir based on the lithology type and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir to determine the high-resolution static Young's modulus of the specified shale oil reservoir:

[0137] By conducting triaxial compression tests on shale oil reservoirs with known plastic rock lithology, static Young's modulus data and a fully water-bearing high-resolution resistivity curve of the experimentally analyzed plastic rock were obtained. A first correlation relationship was established between the static Young's modulus data of the plastic rock and the fully water-bearing high-resolution resistivity curve. An intersection analysis was performed on the first correlation relationship to establish a high-resolution static Young's modulus calculation model for plastic rock.

[0138] By conducting triaxial compression experiments on shale oil reservoirs with known brittle rock lithology, the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock were obtained. A second correlation was established between the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock. An intersection analysis was performed on the second correlation to establish a high-resolution static Young's modulus calculation model corresponding to brittle rock.

[0139] In one embodiment, the high-resolution static Young's modulus calculation model for plastic rock is as follows: sta1 =a1×lnRo+m1

[0140] Where Ro is the high-resolution resistivity of fully hydrated water; E sta1 is the high-resolution static Young's modulus of plastic rock, a1 and m1 are different constants; E sta1 Negatively correlated with Ro.

[0141] In one embodiment, the high-resolution static Young's modulus calculation model for brittle rock is as follows: E sta2 =a2×lnRo+m2

[0142] Where Ro is the high-resolution resistivity of fully hydrated water; E sta2 is the high-resolution static Young's modulus of brittle rock; a2 and m2 are different constants; E sta2 Positively correlated with Ro.

[0143] In one embodiment, the third processing module may be specifically configured to:

[0144] determining a first power theorem exponent based on a high-resolution static Young's modulus of a specified shale oil reservoir and a predefined functional expression of the first power theorem exponent and the static Young's modulus;

[0145] determining a second power theorem exponent based on a high-resolution static Young's modulus of a specified shale oil reservoir, a first power theorem exponent, and a predefined functional expression of the first power theorem exponent and the static Young's modulus and the second power theorem exponent;

[0146] The second power theorem exponent, the high-resolution static Young's modulus of the specified shale oil reservoir and the overlying formation pressure are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

[0147] In one embodiment, the continuous minimum horizontal principal stress calculation model is as follows:

[0148] Among them, SH min is the continuous minimum horizontal principal stress;

[0149] S v is the overlying formation pressure;

[0150] E sta is the high-resolution static Young's modulus;

[0151] B is the first power theorem index. The predefined first power theorem index and the functional expression of the static Young's modulus are:

[0152] N is the second power theorem index, and the predefined first power theorem index and the functional expression of the static Young's modulus and the second power theorem index are N=s×log(E sta , B)+t;

[0153] c, d, e, f, g, h, r, s, and t are different constants.

[0154] An embodiment of the present invention also provides a computer device, as shown in Figure 7, which is a schematic diagram of a computer device in an embodiment of the present invention. The computer device 700 includes a memory 710, a processor 720, and a computer program 730 stored in the memory 710 and executable on the processor 720. When the processor 720 executes the computer program 730, the above-mentioned method for determining the minimum horizontal principal stress of the shale oil reservoir is implemented.

[0155] An embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned method for determining the minimum horizontal principal stress of a shale oil reservoir.

[0156] An embodiment of the present invention also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the above-mentioned method for determining the minimum horizontal principal stress of a shale oil reservoir.

[0157] In the embodiment of the present invention, compared with the existing technical solution of determining the minimum horizontal principal stress using conventional logging data, the advantage of high resolution of microresistivity imaging logging data is utilized to calibrate the conductivity curve in the microresistivity imaging logging data according to the shallow resistivity curve in the shallow resistivity logging data of the specified shale oil reservoir, thereby obtaining a high-resolution resistivity curve of the specified shale oil reservoir. In addition, the oil-bearing porosity information in the core analysis data of the specified shale oil reservoir is utilized to calibrate the nuclear magnetic resonance logging data to determine the continuous oil saturation curve of the specified shale oil reservoir. The continuous oil saturation curve of the specified shale oil reservoir is determined according to the different mineral content information in the element logging data of the specified shale oil reservoir and the rock electrical experimental data. Saturation index curve; based on the high-resolution resistivity curve, continuous oil saturation curve, and continuous saturation index curve of the specified shale oil reservoir, determine the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir; then, after determining the lithologic type of the specified shale oil reservoir, determine the high-resolution static Young's modulus of the specified shale oil reservoir through the predetermined correlation between the fully water-bearing high-resolution resistivity curve and the high-resolution static Young's modulus, i.e., the high-resolution static Young's modulus calculation model; then, input the high-resolution static Young's modulus of the specified shale oil reservoir and the overlying formation pressure into the predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir. In this way, the problem of low resolution in determining the minimum horizontal principal stress using conventional well logging data in the existing technology can be solved, the resolution of the determined minimum horizontal principal stress of the shale oil reservoir can be improved, and a technical tool can be provided for the exploration and development of shale oil and gas.

[0158] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, 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 magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0159] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes 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 produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0160] These computer program instructions may also be stored in a computer-readable memory that can direct 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 a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0161] 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, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0162] 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 method for determining the minimum horizontal principal stress of a shale oil reservoir, characterized in that: include: Obtain shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data and overlying formation pressure of the specified shale oil reservoir; the overlying formation pressure is determined by density integration method; The conductivity curve in the microresistivity imaging logging data is calibrated using the shallow resistivity curve in the shallow resistivity logging data to obtain a high-resolution resistivity curve for the specified shale oil reservoir; Using the oil-bearing porosity information in the core analysis data, the NMR logging data is calibrated to determine the continuous oil saturation curve for the specified shale oil reservoir; Determine the continuous saturation index curve of the specified shale oil reservoir based on the different mineral content information in the element logging data and the rock electrical experimental data; Determine a completely water-bearing high-resolution resistivity curve of the designated shale oil reservoir according to the high-resolution resistivity curve, the continuous oil saturation curve and the continuous saturation index curve of the designated shale oil reservoir; Analyze the lithology of the specified shale oil reservoir according to the core analysis data to determine the lithology type of the specified shale oil reservoir, wherein the lithology type is plastic rock or brittle rock; According to the lithology type and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir, a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir is selected to determine the high-resolution static Young's modulus of the specified shale oil reservoir; The high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

2. The method according to claim 1, characterized in that According to the high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir, the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir is determined, including: The high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir are input into a pre-built complete water-bearing high-resolution resistivity calculation model to determine the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir.

3. The method according to claim 2, characterized in that The pre-built fully water-containing high-resolution resistivity calculation model is as follows: Ro = (1-So) n ×Rhr Among them, Ro is the high-resolution resistivity of complete water content; So is the continuous oil saturation curve; n is the continuous saturation index curve; Rhr is the high-resolution resistivity curve.

4. The method according to claim 1, characterized in that According to the lithology type and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir, a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir is selected, and before the high-resolution static Young's modulus of the specified shale oil reservoir is determined, the method further includes: By conducting triaxial compression experiments on shale oil reservoirs with known lithology types as plastic rock, static Young's modulus data of the plastic rock and a high-resolution resistivity curve of complete water content are obtained; a first correlation relationship is established between the static Young's modulus data of the plastic rock and the high-resolution resistivity curve of complete water content; an intersection analysis is performed on the first correlation relationship to establish a high-resolution static Young's modulus calculation model corresponding to the plastic rock; By conducting triaxial compression experiments on shale oil reservoirs with known brittle rock lithology, the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock are obtained; a second correlation relationship is established between the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock; an intersection analysis is performed on the second correlation relationship to establish a high-resolution static Young's modulus calculation model corresponding to brittle rock.

5. The method according to claim 4, characterized in that The calculation model of high-resolution static Young's modulus for plastic rock is as follows: sta1 =a1×lnRo+m1 Where Ro is the high-resolution resistivity of fully water-containing sta1 is the high-resolution static Young's modulus corresponding to plastic rock, a1 and m1 are different constants; E sta1 Negatively correlated with Ro.

6. The method according to claim 4, characterized in that The high-resolution static Young's modulus calculation model for brittle rock is as follows: sta2 =a2×lnRo+m2 Where Ro is the high-resolution resistivity of fully water-containing sta2 is the high-resolution static Young's modulus of brittle rock; a2 and m2 are different constants; E sta2 Positively correlated with Ro.

7. The method according to claim 1, characterized in that The high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir, including: Determine a first power theorem exponent based on a high-resolution static Young's modulus of a specified shale oil reservoir and a predefined functional expression of the first power theorem exponent and the static Young's modulus; determining a second power theorem index based on a high-resolution static Young's modulus of a specified shale oil reservoir, a first power theorem index, and a predefined first power theorem index and a functional expression of the static Young's modulus and the second power theorem index; The second power theorem exponent, high-resolution static Young's modulus of a specified shale oil reservoir, and overlying formation pressure are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

8. The method according to claim 7, characterized in that The continuous minimum horizontal principal stress calculation model is as follows: Among them, SH min is the continuous minimum horizontal principal stress; S v is the overlying formation pressure; E sta is the high-resolution static Young's modulus; B is the first power theorem index. The predefined first power theorem index and the functional expression of the static Young's modulus are: N is the second power theorem index, and the predefined first power theorem index and the functional expression of the static Young's modulus and the second power theorem index are N = s × log (E sta , B)+t; c, d, e, f, g, h, r, s, and t are different constants.

9. 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 following method is implemented: Obtain shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data and overlying formation pressure of the specified shale oil reservoir; the overlying formation pressure is determined by density integration method; The conductivity curve in the microresistivity imaging logging data is calibrated using the shallow resistivity curve in the shallow resistivity logging data to obtain a high-resolution resistivity curve for the specified shale oil reservoir; Using the oil-bearing porosity information in the core analysis data, the NMR logging data is calibrated to determine the continuous oil saturation curve for the specified shale oil reservoir; Determine the continuous saturation index curve of the specified shale oil reservoir based on the different mineral content information in the element logging data and the rock electrical experimental data; Determine a completely water-bearing high-resolution resistivity curve of the designated shale oil reservoir according to the high-resolution resistivity curve, the continuous oil saturation curve and the continuous saturation index curve of the designated shale oil reservoir; Analyze the lithology of the specified shale oil reservoir according to the core analysis data to determine the lithology type of the specified shale oil reservoir, wherein the lithology type is plastic rock or brittle rock; According to the lithology type and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir, a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir is selected to determine the high-resolution static Young's modulus of the specified shale oil reservoir; The high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

10. The computer device according to claim 9, characterized in that According to the high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir, the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir is determined, including: The high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir are input into a pre-built complete water-bearing high-resolution resistivity calculation model to determine the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir.

11. The computer device according to claim 9, characterized in that When the processor executes the computer program, the following method is also implemented: Before selecting a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir according to the lithology type and the high-resolution resistivity curve of the fully water-bearing shale oil reservoir, and determining the high-resolution static Young's modulus of the specified shale oil reservoir, a triaxial compression experiment is performed on a shale oil reservoir whose lithology type is known to be plastic rock, to obtain static Young's modulus data of the plastic rock and a high-resolution resistivity curve of the fully water-bearing shale oil reservoir analyzed by the experiment; a first correlation relationship is established between the static Young's modulus data of the plastic rock and the high-resolution resistivity curve of the fully water-bearing shale oil reservoir; an intersection analysis is performed on the first correlation relationship, and a high-resolution static Young's modulus calculation model corresponding to the plastic rock is established; By conducting triaxial compression experiments on shale oil reservoirs with known brittle rock lithology, the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock are obtained; a second correlation relationship is established between the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock; an intersection analysis is performed on the second correlation relationship to establish a high-resolution static Young's modulus calculation model corresponding to brittle rock.

12. The computer device of claim 9, wherein: The high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir, including: Determine a first power theorem exponent based on a high-resolution static Young's modulus of a specified shale oil reservoir and a predefined functional expression of the first power theorem exponent and the static Young's modulus; determining a second power theorem index based on a high-resolution static Young's modulus of a specified shale oil reservoir, a first power theorem index, and a predefined first power theorem index and a functional expression of the static Young's modulus and the second power theorem index; The second power theorem exponent, high-resolution static Young's modulus of a specified shale oil reservoir, and overlying formation pressure are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

13. 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 following method is implemented: Obtain shallow resistivity logging data, microresistivity imaging logging data, nuclear magnetic resonance logging data, element logging data, core analysis data, rock electrical experimental data and overlying formation pressure of the specified shale oil reservoir; the overlying formation pressure is determined by density integration method; The conductivity curve in the microresistivity imaging logging data is calibrated using the shallow resistivity curve in the shallow resistivity logging data to obtain a high-resolution resistivity curve for the specified shale oil reservoir; Using the oil-bearing porosity information in the core analysis data, the NMR logging data is calibrated to determine the continuous oil saturation curve for the specified shale oil reservoir; Determine the continuous saturation index curve of the specified shale oil reservoir based on the different mineral content information in the element logging data and the rock electrical experimental data; Determine a completely water-bearing high-resolution resistivity curve of the designated shale oil reservoir according to the high-resolution resistivity curve, the continuous oil saturation curve and the continuous saturation index curve of the designated shale oil reservoir; Analyze the lithology of the specified shale oil reservoir according to the core analysis data to determine the lithology type of the specified shale oil reservoir, wherein the lithology type is plastic rock or brittle rock; According to the lithology type and the fully water-bearing high-resolution resistivity curve of the specified shale oil reservoir, a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir is selected to determine the high-resolution static Young's modulus of the specified shale oil reservoir; The high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

14. The computer-readable storage medium of claim 13, wherein: According to the high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir, the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir is determined, including: The high-resolution resistivity curve, continuous oil saturation curve and continuous saturation index curve of the specified shale oil reservoir are input into a pre-built complete water-bearing high-resolution resistivity calculation model to determine the complete water-bearing high-resolution resistivity curve of the specified shale oil reservoir.

15. The computer-readable storage medium of claim 13, wherein: When the computer program is executed by a processor, the following method is also implemented: Before selecting a high-resolution static Young's modulus calculation model corresponding to the lithology type of the specified shale oil reservoir according to the lithology type and the high-resolution resistivity curve of the fully water-bearing shale oil reservoir, and determining the high-resolution static Young's modulus of the specified shale oil reservoir, a triaxial compression experiment is performed on a shale oil reservoir whose lithology type is known to be plastic rock, to obtain static Young's modulus data of the plastic rock and a high-resolution resistivity curve of the fully water-bearing shale oil reservoir analyzed by the experiment; a first correlation relationship is established between the static Young's modulus data of the plastic rock and the high-resolution resistivity curve of the fully water-bearing shale oil reservoir; an intersection analysis is performed on the first correlation relationship, and a high-resolution static Young's modulus calculation model corresponding to the plastic rock is established; By conducting triaxial compression experiments on shale oil reservoirs with known brittle rock lithology, the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock are obtained; a second correlation relationship is established between the static Young's modulus data of the brittle rock and the high-resolution resistivity curve of the fully water-bearing rock; an intersection analysis is performed on the second correlation relationship to establish a high-resolution static Young's modulus calculation model corresponding to brittle rock.

16. The computer-readable storage medium of claim 13, wherein: The high-resolution static Young's modulus and overlying formation pressure of the specified shale oil reservoir are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir, including: Determine a first power theorem exponent based on a high-resolution static Young's modulus of a specified shale oil reservoir and a predefined functional expression of the first power theorem exponent and the static Young's modulus; determining a second power theorem index based on a high-resolution static Young's modulus of a specified shale oil reservoir, a first power theorem index, and a predefined first power theorem index and a functional expression of the static Young's modulus and the second power theorem index; The second power theorem exponent, high-resolution static Young's modulus of a specified shale oil reservoir, and overlying formation pressure are input into a predetermined continuous minimum horizontal principal stress calculation model to obtain the continuous minimum horizontal principal stress of the specified shale oil reservoir.

Images