Method and device for constructing three-dimensional rock physical template for identifying dessert of shale reservoir

Abstract

The invention discloses a method and a device for constructing a three-dimensional rock physical template for identifying shale reservoir desserts. The method comprises the following steps: respectively constructing data of dessert evaluation parameters in a value range according to the actual value range of each dessert evaluation parameter of the shale oil reservoir to obtain a sample data set; the sample data set comprises a plurality of pieces of sample data, calculating each dessert evaluation parameter data of each piece of sample data, and respectively obtaining a shale equivalent stiffness coefficient corresponding to each piece of sample data; according to each shale equivalent stiffness coefficient, respectively solving elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each piece of sample data; and constructing a three-dimensional rock physical template according to the elastic parameter data and the anisotropic parameter data of the shale oil reservoir corresponding to the sample data. Elastic parameter data and anisotropic parameter data explained by well logging or seismic data of a target interval can be projected to a three-dimensional rock physical template, and shale oil reservoir desserts can be accurately identified.

Description

Technical Field

[0001] The present invention relates to the field of geophysics, and in particular to a method and device for constructing a three-dimensional rock physics template for identifying sweet spots in shale reservoirs. Background Art

[0002] Existing technologies mainly rely on the elastic parameters of seismic waves (such as longitudinal wave impedance, longitudinal and transverse wave velocity ratio, etc.) to construct rock physics templates, but a large number of studies have shown that the organic matter content, clay content, bedding fractures, and hydrocarbon expulsion fractures of shale oil reservoirs have a significant impact on the anisotropy of seismic waves. Although some scholars have proposed a mapping relationship between the anisotropy of seismic waves and key reservoir parameters, it is difficult to accurately identify many reservoir parameters using only anisotropic parameters or elastic parameters, and the multi-solution is obvious. Therefore, it is necessary to develop a three-dimensional rock physics template identification technology for shale reservoir sweet spots that combines elastic characteristics and anisotropic characteristics to accurately identify shale oil reservoir sweet spots. Summary of the invention

[0003] The existing rock physics templates have the following problems: 1. Many geological factors that affect the geology and engineering sweet spots of shale oil reservoirs (such as lithology, physical parameters, bedding fractures and other physical parameters) are coupled with each other, affecting the elastic characteristics and anisotropic characteristics. The most sensitive elastic parameters and anisotropic parameters of each geological factor are not clearly sorted out; 2. In shale oil reservoirs of different maturity, the proportion of kerogen and asphalt in organic matter is different, and their own elastic properties and organic-inorganic mechanical interactions are also different, which has a great impact on the overall elastic properties and anisotropy of the reservoir. This is not taken into account in the construction process of existing rock physics templates: 3. The construction of existing rock physics templates mainly relies on typical elastic parameters, and does not make full use of anisotropic characteristics to decouple lithology (clay content), physical parameters, and bedding fractures.

[0004] In view of the above problems, the present invention is proposed to provide a method and apparatus for constructing a three-dimensional rock physics template for identifying sweet spots in shale reservoirs, which overcomes the above problems or at least partially solves the above problems.

[0005] In a first aspect, an embodiment of the present invention provides a method for constructing a three-dimensional rock physics template, comprising:

[0006] According to the actual value range of each sweet spot evaluation parameter of the shale oil reservoir, data of the sweet spot evaluation parameter within the value range are respectively constructed to obtain a sample data set; the sample data set includes a plurality of sample data, the sample data includes data of each sweet spot evaluation parameter, and the data of each sweet spot evaluation parameter between each sample data is not completely the same;

[0007] The sweet spot evaluation parameter data of each sample data is calculated to obtain the shale equivalent stiffness coefficient corresponding to each sample data;

[0008] According to the shale equivalent stiffness coefficient corresponding to each sample data, the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data are solved respectively;

[0009] A three-dimensional rock physics template is constructed based on the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data.

[0010] In one embodiment, the sweet spot evaluation parameters include lithology parameters, physical property parameters and bedding fractures;

[0011] The shale equivalent stiffness coefficient corresponding to the sample data is determined in the following way:

[0012] According to the data of the lithology parameters in the sample data, construct the elastic stiffness coefficient of the inorganic skeleton corresponding to the sample data;

[0013] According to the data of the physical property parameters in the sample data and the elastic stiffness coefficient of the inorganic skeleton, constructing the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data;

[0014] According to the data of bedding fractures in the sample data and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter, an anisotropic equivalent stiffness coefficient is constructed as the shale equivalent stiffness coefficient corresponding to the sample data.

[0015] In one embodiment, the data of lithology parameters include clay mineral data and non-clay mineral data;

[0016] The step of constructing the elastic stiffness coefficient of the inorganic skeleton corresponding to the sample data according to the data of the lithology parameters in the sample data includes:

[0017] Calculating the clay mineral data to obtain the clay mineral equivalent elastic modulus corresponding to the data sample;

[0018] Calculating the non-clay mineral data to obtain the non-clay mineral equivalent elastic modulus corresponding to the data sample;

[0019] According to the equivalent elastic modulus of the clay mineral and the equivalent elastic modulus of the non-clay mineral, the equivalent elastic modulus of the inorganic skeleton corresponding to the sample data is obtained as the elastic stiffness coefficient of the inorganic skeleton.

[0020] In one embodiment, the clay minerals are multiple;

[0021] The step of calculating the clay mineral data to obtain the clay mineral equivalent elastic modulus corresponding to the data sample includes:

[0022] Various clay minerals are mixed to obtain mixed clay mineral data, and the mixed clay mineral data are calculated to obtain the clay mineral equivalent elastic modulus corresponding to the data sample.

[0023] In one embodiment, the data of the physical property parameters include at least one organic matter data and corresponding organic pore data;

[0024] The method of constructing an equivalent stiffness coefficient of an inorganic skeleton containing organic matter corresponding to the sample data according to the data of the physical property parameters in the sample data and the elastic stiffness coefficient of the inorganic skeleton comprises:

[0025] Calculate each organic matter data and the corresponding organic pore data to determine the equivalent elastic modulus of each organic matter containing organic pores;

[0026] According to the equivalent elastic modulus of each organic matter containing organic pores and the elastic stiffness coefficient of the inorganic skeleton, the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data is obtained.

[0027] In one embodiment, the organic matter includes kerogen and asphalt;

[0028] The equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data is obtained according to the equivalent elastic modulus of each organic matter containing organic pores and the elastic stiffness coefficient of the inorganic skeleton, including:

[0029] According to the equivalent elastic modulus of the kerogen containing organic pores and the elastic stiffness coefficient of the inorganic skeleton, an equivalent stiffness coefficient of the inorganic skeleton containing kerogen is obtained;

[0030] According to the equivalent stiffness coefficient of the inorganic skeleton containing kerogen and the equivalent elastic modulus of the asphalt containing organic pores, the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data is obtained.

[0031] In one embodiment, the anisotropic equivalent stiffness coefficient is constructed based on the data of the bedding fractures in the sample data and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter, including:

[0032] According to the bedding fracture density data and the bedding fracture aspect ratio data in the bedding fracture data and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter, an anisotropic differential equivalent medium model is used to obtain an anisotropic equivalent stiffness coefficient.

[0033] In one embodiment, the elastic parameter data includes longitudinal wave impedance data and longitudinal and shear wave velocity ratio data;

[0034] According to the shale equivalent stiffness coefficient corresponding to the sample data, the elastic parameter data of the shale oil reservoir corresponding to the sample data is solved, including:

[0035] Determining the density of the shale oil reservoir corresponding to the sample data;

[0036] Determining the longitudinal wave vertical velocity and the shear wave velocity according to the density and the shale equivalent stiffness coefficient corresponding to the sample data;

[0037] Determining longitudinal wave impedance data according to the longitudinal wave vertical velocity and the density;

[0038] The longitudinal and shear wave velocity ratio data is determined based on the longitudinal wave vertical velocity and the shear wave velocity.

[0039] In one embodiment, constructing a three-dimensional rock physics template according to the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data includes:

[0040] Construct a three-dimensional coordinate system based on the longitudinal wave impedance, the longitudinal and transverse wave velocity ratio and the anisotropy parameters;

[0041] The longitudinal wave impedance data, longitudinal and transverse wave velocity ratio data and anisotropy parameter data of the shale oil reservoir corresponding to each sample data are respectively marked in the three-dimensional coordinate system as a set of coordinate data to obtain a three-dimensional rock physics template.

[0042] In a second aspect, an embodiment of the present invention provides a method for identifying sweet spots in a shale oil reservoir, comprising:

[0043] Obtain evaluation parameter data of each sweet spot of the shale oil reservoir to be identified;

[0044] According to the evaluation parameter data of each sweet spot of the shale oil reservoir to be identified, an identification result of the sweet spot of the shale oil reservoir to be identified is obtained through a three-dimensional rock physics template;

[0045] The three-dimensional rock physics template is obtained by the aforementioned three-dimensional rock physics template construction method.

[0046] In a third aspect, an embodiment of the present invention provides a device for constructing a three-dimensional rock physics template, comprising:

[0047] A sample data module is constructed, which is used to construct the data of the sweet spot evaluation parameters within the value range according to the actual value range of each sweet spot evaluation parameter of the shale oil reservoir, so as to obtain a sample data set; the sample data set includes a plurality of sample data, the sample data includes the data of each sweet spot evaluation parameter, and the data of each sweet spot evaluation parameter between each sample data is not completely the same;

[0048] A calculation module, used to calculate the sweet spot evaluation parameter data of each sample data, and obtain the shale equivalent stiffness coefficient corresponding to each sample data;

[0049] A solution module, used for solving elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data according to the shale equivalent stiffness coefficient corresponding to each sample data;

[0050] The template construction module is used to construct a three-dimensional rock physics template according to the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data.

[0051] In a fourth aspect, an embodiment of the present invention provides a device for identifying sweet spots in a shale oil reservoir, comprising:

[0052] An acquisition module, used for acquiring evaluation parameter data of each sweet spot of the shale oil reservoir to be identified;

[0053] An identification module, used for obtaining an identification result of the sweet spot of the shale oil reservoir to be identified through a three-dimensional rock physics template according to the evaluation parameter data of each sweet spot of the shale oil reservoir to be identified;

[0054] The three-dimensional rock physics template is obtained by the aforementioned three-dimensional rock physics template construction method.

[0055] In a fifth aspect, an embodiment of the present invention provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and when the computer executable instructions are executed by a processor, the aforementioned method for constructing a three-dimensional rock physics template is implemented.

[0056] In the sixth aspect, an embodiment of the present invention provides a terminal device, characterized in that it includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned method for constructing a three-dimensional rock physics template when executing the program.

[0057] The beneficial effects of the above technical solution provided by the embodiment of the present invention include at least:

[0058] The method for constructing a three-dimensional rock physics template provided by an embodiment of the present invention constructs sweet spot evaluation parameter data within the value range according to the actual value range of each sweet spot evaluation parameter of the shale oil reservoir, as sample data. The sample data includes the sweet spot evaluation parameter data. In this way, a number of sample data with different values ​​of the sweet spot evaluation parameters are constructed to obtain a sample data set. The sweet spot evaluation parameter data of each sample data in the sample data set are calculated to obtain the shale equivalent stiffness coefficient corresponding to each sample data. Then, according to the shale equivalent stiffness coefficient corresponding to each sample data, each sample data is solved. The corresponding elastic parameter data and anisotropic parameter data of the shale oil reservoir; according to the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data, a three-dimensional rock physics template is constructed. The constructed template combines the elastic parameters and the anisotropic parameters, and uses independent elastic parameters and anisotropic parameters to decouple the evaluation parameters of each sweet spot that affects the shale oil sweet spot, overcoming the problem that it is difficult to effectively identify multiple parameters of the shale oil reservoir using a single or two elastic parameters, providing effective support for high-precision quantitative identification of shale sweet spots, and significantly improving the accuracy and efficiency of identifying shale sweet spots.

[0059] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0060] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 is a flow chart of a method for constructing a three-dimensional rock physics template in an embodiment of the present invention;

[0063] Figure 2 A comparative analysis diagram of sensitive geological factors of the ratio of longitudinal and transverse wave velocities in an embodiment of the present invention;

[0064] Figure 3 A comparative analysis diagram of sensitive geological factors of longitudinal wave impedance in an embodiment of the present invention;

[0065] Figure 4 A comparative analysis diagram of sensitive geological factors of P-wave anisotropy parameters in an embodiment of the present invention;

[0066] Figure 5It is a flow chart of a method for determining the shale equivalent stiffness coefficient corresponding to sample data in an embodiment of the present invention;

[0067] Figure 6 A flow chart of a method for constructing an elastic stiffness coefficient of an inorganic framework in an embodiment of the present invention;

[0068] Figure 7 A flow chart of a method for constructing an equivalent stiffness coefficient of an inorganic framework containing organic matter in an embodiment of the present invention;

[0069] Figure 8 A flow chart of a method for constructing a shale model in an embodiment of the present invention;

[0070] Fig. 9 is a flow chart of a method for calculating elastic parameter data in an embodiment of the present invention;

[0071] Fig.10 is a schematic diagram of a three-dimensional coordinate system in an embodiment of the present invention;

[0072] Fig.11 Flow chart of a method for identifying sweet spots in a shale oil reservoir according to an embodiment of the present invention;

[0073] Fig.12 It is a schematic structural diagram of a device for constructing a three-dimensional rock physics template in an embodiment of the present invention;

[0074] Fig.13 Schematic diagram of the structure of a device for identifying sweet spots in a shale oil reservoir according to an embodiment of the present invention;

[0075] Fig.14 Flow chart of a method for identifying sweet spots in a shale oil reservoir according to an embodiment of the present invention;

[0076] Fig.15 Schematic diagram of the value range of each sweet spot evaluation parameter in the well logging data in an embodiment of the present invention;

[0077] Figure 16-Figure 18 It is a schematic diagram of the result of identifying the reservoir sweet spot in an embodiment of the present invention. DETAILED DESCRIPTION

[0078] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0079] In order to solve the problems existing in the prior art, an embodiment of the present invention provides a method and device for constructing a three-dimensional rock physics template for identifying sweet spots in shale reservoirs.

[0080] Example

[0081] Embodiment 1 of the present invention provides a method for constructing a three-dimensional rock physics template, the process of which is as follows: Figure 1 As shown, the following steps are included:

[0082] Step S1: According to the actual value range of each sweet spot evaluation parameter of the shale oil reservoir, respectively construct the data of the sweet spot evaluation parameter within the value range to obtain a sample data set; the sample data set includes a plurality of sample data, the sample data includes the data of each sweet spot evaluation parameter, and the data of each sweet spot evaluation parameter between each sample data is not completely the same;

[0083] Step S2: Calculate the sweet spot evaluation parameter data of each sample data to obtain the shale equivalent stiffness coefficient corresponding to each sample data;

[0084] Step S3: according to the shale equivalent stiffness coefficient corresponding to each sample data, respectively solve the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data;

[0085] Step S4: construct a three-dimensional rock physics template according to the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data.

[0086] In some optional embodiments, the key geological factors affecting the evaluation of shale oil sweet spots (including lithological parameters, physical parameters and bedding fractures), also called sweet spot evaluation parameters, are analyzed through the results of experiments, logging and rock physics modeling of shale oil reservoirs to find that: 1) Figure 2 As shown in Figure 2, among the lithological parameters, clay content (clay content of shale) is most sensitive to the P-wave velocity ratio, and the P-wave velocity ratio controls the gradient of the prestack seismic AVO effect. Figure 3 As shown in the figure, among the physical parameters, porosity is the most sensitive to P-wave impedance. Among the physical parameters, organic matter content (organic matter content in shale) is also sensitive to changes in P-wave impedance. P-wave impedance controls the intercept of prestack seismic AVO (amplitude changes with offset) effect. 3) Figure 4 As shown in the figure, bedding fractures are most sensitive to the P-wave anisotropy parameter (epsilon), which controls the anisotropic characteristics of seismic data. Generally, the three parameters of P-wave impedance, P-wave velocity ratio and P-wave anisotropy parameter can be predicted from seismic data directly or indirectly. Based on this, a three-dimensional rock physics template of P-wave impedance-P-wave velocity ratio-P-wave anisotropy parameter is established. The three key evaluation factors (lithology, physical parameters and bedding fractures) that affect the sweet spots of shale oil reservoirs can be effectively identified and predicted from three dimensions.

[0087] In the above step S1, the porosity can be set to 0-Porosity (max) (maximum porosity) range, while the organic matter content is 0-TOC (max) (maximum organic matter content) range; then set the clay content in 0-f_clay (max) (maximum clay content volume fraction) range, bedding density is between 0-crack_density (max) (maximum fracture density) range, in the actual logging process, the actual value range of each sweet spot evaluation parameter can be measured, for example, refer to the following Table 1:

[0088] Table 1:

[0089] Porosity 0-0.12 Organic matter content 0-0.08 Clay content 0-50％ Crack density 0-0.1 Pore ​​aspect ratio 0.6 Crack aspect ratio 0.01

[0090] In some optional embodiments, the sweet spot evaluation parameters include lithology parameters, physical property parameters and bedding fractures. In the above step S2, Figure 5 As shown, this can be achieved by:

[0091] Step S21: constructing the elastic stiffness coefficient of the inorganic skeleton corresponding to the sample data according to the data of the lithology parameters in the sample data;

[0092] Step S22: constructing an equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data according to the data of the physical property parameters in the sample data and the elastic stiffness coefficient of the inorganic skeleton;

[0093] Step S23: construct an anisotropic equivalent stiffness coefficient according to the data of bedding fractures in the sample data and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter as the shale equivalent stiffness coefficient corresponding to the sample data.

[0094] In some optional embodiments, the composition of the inorganic phase of shale is divided into a clay part and a non-clay part, and the clay part is composed of a mixture of silicate and carbonate minerals, silicate minerals and carbonate minerals are collectively referred to as clay minerals, and the rock skeleton of the non-clay part is composed of a rock matrix and fluid-filled pores. In other words, the data of the lithology parameters include clay mineral data and non-clay mineral data. The above step S21, such as Figure 6 As shown: This can be achieved by:

[0095] Step S31: Calculate the clay mineral data to obtain the clay mineral equivalent elastic modulus corresponding to the data sample;

[0096] Optionally, the Hill algorithm is used to average the effective elastic modulus of the mixture of silicate minerals and carbonate minerals.

[0097] Step S32: Calculate the non-clay mineral data to obtain the equivalent elastic modulus of the non-clay mineral corresponding to the data sample;

[0098] Optionally, an isotropic self-consistent model is used to calculate the non-clay mineral data, that is, inorganic pores are added to the rock matrix of the non-clay minerals to obtain the equivalent elastic modulus of the non-clay part.

[0099] Step S33: according to the equivalent elastic modulus of the clay mineral and the equivalent elastic modulus of the non-clay mineral, the equivalent elastic modulus of the inorganic skeleton corresponding to the sample data is obtained as the elastic stiffness coefficient of the inorganic skeleton.

[0100] Optionally, an anisotropic self-consistent model is used to integrate the equivalent elastic modulus of clay minerals in the clay part and the equivalent elastic modulus of non-clay minerals in the non-clay part to obtain the equivalent elastic modulus of the inorganic phase of the shale oil and gas reservoir, that is, the elastic stiffness coefficient of the inorganic skeleton.

[0101] In some optional embodiments, there are multiple types of clay minerals, and the above step S31 can be implemented in the following manner:

[0102] Various clay minerals are mixed to obtain mixed clay mineral data, and the mixed clay mineral data are calculated to obtain the clay mineral equivalent elastic modulus corresponding to the data sample.

[0103] In some optional embodiments, the data of the physical property parameters include at least one organic matter data and corresponding organic pore data, and the above step S22, such as Figure 7 As shown, this can be achieved by:

[0104] Step S41: Calculating each organic matter data and the corresponding organic pore data to respectively determine the equivalent elastic modulus of each organic matter containing organic pores;

[0105] Step S42: Obtaining the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data according to the equivalent elastic modulus of each organic matter containing organic pores and the elastic stiffness coefficient of the inorganic skeleton.

[0106] As a unique rock component, the content and physical properties of organic matter have an important influence on the elastic characteristics and anisotropy of shale oil reservoirs. In shale, kerogen and asphalt are both organic matter, and in shale oil reservoirs of different maturity, the proportion of kerogen and asphalt in organic matter is different, and their own elastic properties and mechanical interactions with inorganic skeletons are also different. Kerogen is deposited together with inorganic minerals and plays the role of rock skeleton; while solid asphalt constantly migrates and fills nearby inorganic pores, playing the role of solid filling. Therefore, the different proportions of kerogen and asphalt in organic matter have a great influence on the overall elastic properties and anisotropy. Therefore, kerogen and asphalt in organic matter should be treated differently.

[0107] In some optional embodiments, the above step S42 can be implemented in the following manner:

[0108] (1) According to the equivalent elastic modulus of kerogen containing organic pores and the elastic stiffness coefficient of the inorganic skeleton, the equivalent stiffness coefficient of the inorganic skeleton containing kerogen is obtained;

[0109] According to the organic geochemical analysis method or using a scanning electron microscope, the ratio of kerogen to asphalt in organic matter is determined, and the ratio of kerogen organic pores to asphalt organic pores can be determined according to the ratio of kerogen to asphalt. Using the isotropic differential equivalent medium model, the kerogen organic pores containing fluid fillings are added to the solid kerogen, and the asphalt organic pores are added to the solid asphalt, and the equivalent elastic modulus of the kerogen containing organic pores and the equivalent elastic modulus of the asphalt containing organic pores are obtained respectively. Specifically, it can be achieved by the following formula;

[0110]

[0111]

[0112] In formula (1), K * It represents the bulk modulus of solid kerogen and solid asphalt after adding organic pores filled with fluid, in GPa, μ * It represents the shear modulus of solid kerogen and solid asphalt after adding organic pores filled with fluid, in GPa. Under initial conditions, K * (0) represents the bulk modulus of solid kerogen and solid asphalt, μ * (0) represents the shear modulus of solid kerogen and solid asphalt, K fluid Represents the bulk modulus of the fluid filling the organic pores, in GPa. fluid represents the shear modulus of the fluid filling the organic pores, in GPa, represents the volume fraction of organic pores. The ratio of organic pores in kerogen and bitumen depends on the maturity. *2 With Q*2 Both represent the shape factor of the organic pore, which is related to the aspect ratio of the organic pore.

[0113] Optionally, using an anisotropic SCA model, porous kerogen is filled into the inorganic phase skeleton to obtain a solid skeleton background containing kerogen, and the equivalent stiffness coefficient of the inorganic skeleton containing kerogen is obtained using the following formula;

[0114]

[0115] In the above formula (2), N represents the total number of phases (kerogen and inorganic skeleton phases). r represents the order of phases (kerogen and inorganic skeleton phases). r Represents the corresponding stiffness coefficient of the rth one. It is a fourth-order tensor that uses Green's function to characterize the geometric shapes of the two phases of kerogen and inorganic skeleton.

[0116] (2) Based on the equivalent stiffness coefficient of the inorganic skeleton containing kerogen and the equivalent elastic modulus of the asphalt containing organic pores, the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data is obtained.

[0117] Optionally, a solid replacement model (Gassmann model) is used to fill porous asphalt into a rock skeleton containing kerogen. Specifically, the following formula can be used to achieve this:

[0118]

[0119] In formula (3), represents the effective flexibility tensor of rock after asphalt solid replacement, represents the effective flexibility tensor of the rock after adding the empty pores occupying the asphalt positions, represents the effective flexibility tensor of the rock background containing kerogen before pores are emptied, represents the effective flexibility tensor of porous asphalt, The value of can be calculated by formula (1), V bitumen represents the volume of solid asphalt, φ bitumen Represents the pore volume of asphalt.

[0120] Specifically, the effective flexibility tensor of porous asphalt is is the inverse matrix of the effective stiffness tensor of porous asphalt.

[0121] In some optional embodiments, the above step S23 can be implemented in the following manner:

[0122] According to the bedding fracture density data and bedding fracture aspect ratio data in the bedding fracture data, and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter, the anisotropic equivalent stiffness coefficient is obtained through the anisotropic differential equivalent medium model.

[0123] Optionally, an anisotropic differential equivalent medium model (anisotropic DEM) is used, and the influence of the density of bedding fractures and the geometric shape (aspect ratio) of bedding fractures is taken into account. The anisotropic equivalent stiffness coefficient of the shale oil reservoir containing bedding fractures is constructed, specifically, using the following formula:

[0124]

[0125] In formula (4), C DEM represents the equivalent medium stiffness tensor of shale containing fractures obtained by anisotropic method; V represents the volume content of fractures and shale skeleton, C sat is the rock stiffness coefficient of the material containing organic and inorganic phases obtained by formula (3). It is a fourth-order tensor that uses Green's function to characterize the geometry of bedding fractures, and I represents the unit tensor.

[0126] By solving formula (4), we can obtain the shale equivalent stiffness coefficient corresponding to the sample data, which can be expressed by the following matrix:

[0127]

[0128] In matrix (5), C shale is the shale stiffness coefficient obtained by formula (4).

[0129] In order to more clearly illustrate the process of obtaining the anisotropic equivalent stiffness coefficient in the above steps S21 to S23, refer to Figure 8 Flowchart for constructing a shale model is shown.

[0130] In some optional embodiments, the elastic parameter data includes longitudinal wave impedance data and longitudinal and transverse wave velocity ratio data, and the above step S3, such as Fig. 9 As shown, this can be achieved through the following communication methods:

[0131] Step S51: determining the density of the shale oil reservoir corresponding to the sample data;

[0132] Step S52: Determine the longitudinal wave vertical velocity and the shear wave velocity according to the density and the shale equivalent stiffness coefficient corresponding to the sample data;

[0133] Step S53: Determine the longitudinal wave impedance data according to the longitudinal wave vertical velocity and density;

[0134] Step S54: Determine the longitudinal and transverse wave velocity ratio data according to the longitudinal wave vertical velocity and the transverse wave velocity.

[0135] Specifically, the density of the entire shale is obtained by weighted average of the volume fractions of each phase, wherein the density of each phase can be directly measured, as shown in the following Table 2;

[0136] Table 2:

[0137] Component name Density (ρ) g / cc quartz 2.65 Feldspar 2.62 Pyrite 4.81 Calcium carbonate 2.71 Dolomites 2.87 Solid kerogen 1.24 Solid asphalt 1.01 Fluid filling 0.58

[0138] The following formula is used to calculate the P-wave velocity and S-wave velocity of shale oil and gas reservoirs:

[0139]

[0140]

[0141] In formulas (6) and (7), V p and V s is the vertical velocity of longitudinal wave and shear wave of shale reservoir, in km / s, ρ is the density of shale reservoir, in g / cc;

[0142] Furthermore, the following formula is used to solve the elastic parameter longitudinal wave impedance:

[0143] P-impedance=V p *ρ (8)

[0144] In formula (8), P-impedance is the elastic parameter longitudinal wave impedance, and its unit is The other parameters in the formula have been described above and will not be described in detail in the embodiment of the present invention.

[0145] Use the following formula to solve for the ratio of longitudinal and transverse wave velocities:

[0146]

[0147] In formula (9), the parameters have been described above and will not be described in detail in the embodiment of the present invention.

[0148] Furthermore, the following formula is used to solve the longitudinal wave anisotropy parameter:

[0149]

[0150] In formula (10), ε represents the longitudinal wave anisotropy parameter, and other parameters in the formula have been explained above, and will not be described in detail in the embodiment of the present invention.

[0151] In some optional embodiments, the above step S4 can be implemented by the following method:

[0152] (1) According to the longitudinal wave impedance, the longitudinal and transverse wave velocity ratio and the anisotropy parameters, a three-dimensional coordinate system is constructed. The three-dimensional coordinate system is as follows: Fig.10 As shown;

[0153] (2) The longitudinal wave impedance data, longitudinal and transverse wave velocity ratio data and anisotropy parameter data of the shale oil reservoir corresponding to each sample data are marked as a set of coordinate data in a three-dimensional coordinate system to obtain a three-dimensional rock physics template.

[0154] Based on the above-mentioned method for constructing a three-dimensional rock physical template, an embodiment of the present invention provides a method for identifying sweet spots in shale oil reservoirs, the process of which is as follows: Fig.11 As shown, the following steps are included:

[0155] Step S111: obtaining evaluation parameter data of each sweet spot of the shale oil reservoir to be identified;

[0156] Step S112: obtaining the identification result of the sweet spot of the shale oil reservoir to be identified through the three-dimensional rock physics template according to the evaluation parameter data of each sweet spot of the shale oil reservoir to be identified;

[0157] The three-dimensional rock physics template is obtained through the aforementioned three-dimensional rock physics template construction method.

[0158] Based on the same inventive concept, the embodiment of the present invention also provides a device for constructing a three-dimensional rock physical template, the structure of which is as follows: Fig.12 As shown, including:

[0159] The sample data construction module 61 is used to construct the data of the sweet spot evaluation parameters within the value range according to the actual value range of each sweet spot evaluation parameter of the shale oil reservoir, and obtain a sample data set; the sample data set includes a plurality of sample data, the sample data includes the data of each sweet spot evaluation parameter, and the data of each sweet spot evaluation parameter between each sample data is not completely the same;

[0160] A calculation module 62 is used to calculate the sweet spot evaluation parameter data of each sample data to obtain the shale equivalent stiffness coefficient corresponding to each sample data;

[0161] A solution module 63 is used to solve the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data according to the shale equivalent stiffness coefficient corresponding to each sample data;

[0162] The template building module 64 is used to build a three-dimensional rock physics template according to the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data.

[0163] Regarding the device for constructing a three-dimensional rock physical template in the above-mentioned embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method and will not be elaborated here.

[0164] Based on the same inventive concept, the embodiment of the present invention also provides a shale oil reservoir sweet spot identification device, the structure of the device is as follows: Fig.13 As shown, including:

[0165] An acquisition module 71 is used to acquire evaluation parameter data of each sweet spot of the shale oil reservoir to be identified;

[0166] An identification module 72, for obtaining an identification result of the sweet spot of the shale oil reservoir to be identified through a three-dimensional rock physics template according to the evaluation parameter data of each sweet spot of the shale oil reservoir to be identified;

[0167] The three-dimensional rock physics template is obtained through the aforementioned three-dimensional rock physics template construction method.

[0168] Regarding the shale oil reservoir sweet spot identification device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0169] Using a specific example, refer to Fig.14 As shown, the identification method of the sweet spot of the shale oil reservoir is explained through the analysis of the logging data of well A:

[0170] 1. Obtain clay mineral data, fracture density, organic matter content and porosity range, refer to Fig.15 As shown,

[0171] 2. Obtain the elastic modulus of each component set in Well A. Among them, clay, as a mineral with anisotropic characteristics, has its elastic characteristics determined by five stiffness coefficients, namely: C11 = 44.9 GPa, C33 = 24.2 GPa, C44 = 3.7; C66 = 11.6 GPa, C13 = 18.1 GPa.

[0172] As shown in Table 3 below:

[0173] Table 3:

[0174] Component name Bulk modulus (K) GPa Shear modulus (u) GPa quartz 37.5 44 Feldspar 37.5 15 Pyrite 147 133 Calcium carbonate 76.8 32 Dolomites 95 49 Solid kerogen 4.86 2.48 Solid asphalt 2.69 1.24 Fluid filling 0.9 0

[0175] The constructed 3D rock physics template is used to interpret the logging data of Well A in the shale oil reservoir and identify the reservoir sweet spots. Fig.16 As shown in Figure 2, with the increase of clay content, the ratio of longitudinal and transverse wave velocities increases significantly, the longitudinal wave impedance shows a downward trend, and the anisotropy also shows a more obvious strengthening trend. Fig.17As shown in Figure 2, with the increase of organic matter abundance and porosity, the P-wave impedance decreases significantly, the P-wave velocity ratio shows a downward trend, and the anisotropy also shows a slight increasing trend, but it is not obvious. Fig.18 As shown in the figure, with the increase of bedding fractures, the P-wave impedance and P-S wave velocity ratio decrease, and the anisotropy shows a significant increasing trend. Among them, organic matter content and porosity are most sensitive to the change of P-wave impedance, clay content is most sensitive to the change of P-S wave velocity ratio, and bedding fractures are most sensitive to the change of anisotropy. The use of three independent elastic and anisotropic parameters effectively overcomes the problem that the traditional two elastic parameter cross plots cannot effectively distinguish the parameters of multiple shale oil reservoirs.

[0176] High organic matter content and porosity generally indicate that oil and gas are relatively rich, high fracture density indicates good connectivity, and high clay content is conducive to distinguishing the brittle and plastic development zones of shale. Overall, the shale sweet spot reservoir has low P-wave impedance, low P-wave velocity ratio and high anisotropy rock physics characteristics. Projecting the actual data of the logging data onto the template, the sweet spot reservoir of Well A is concentrated in the low P-wave impedance, low P-wave velocity ratio and high anisotropy area. The use of elastic-anisotropy parameters combined with three-dimensional rock physics templates can effectively identify the sweet spots of shale oil and gas reservoirs.

[0177] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, in which computer executable instructions are stored. When the computer executable instructions are executed by a processor, the aforementioned method for constructing a three-dimensional rock physics template is implemented.

[0178] Based on the same inventive concept, an embodiment of the present invention also provides a terminal device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned method for constructing a three-dimensional rock physics template when executing the program.

[0179] Unless otherwise specifically stated, terms such as processing, computing, calculating, determining, displaying, etc. may refer to the actions and / or processes of one or more processing or computing systems, or similar devices, which operate and convert data represented as physical (e.g., electronic) quantities within registers or memories of a processing system into other data similarly represented as physical quantities within memories, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals may be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0180] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process can be rearranged without departing from the scope of protection of the present disclosure. The attached method claims present the elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy described.

[0181] In the above detailed description, various features are grouped together in a single embodiment to simplify the disclosure. This method of disclosure should not be interpreted as reflecting an intention that the embodiments of the claimed subject matter require more features than are clearly stated in each claim. On the contrary, as reflected in the appended claims, the invention is in a state of having less than all the features of the disclosed individual embodiments. Therefore, the appended claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.

[0182] Those skilled in the art will also appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic steps described in conjunction with the embodiments herein can all be implemented as electronic hardware, computer software, or a combination thereof. In order to clearly illustrate the interchangeability between hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above around their functions. Whether such functions are implemented as hardware or software depends on specific applications and the design constraints imposed on the entire system. A skilled person can implement the described functions in an alternative manner for each specific application, but such implementation decisions should not be interpreted as departing from the scope of protection of the present disclosure.

[0183] The steps of the method or algorithm described in conjunction with the embodiments herein may be directly embodied as hardware, a software module executed by a processor, or a combination thereof. The software module may be located in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a mobile disk, a CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor so that the processor can read information from the storage medium and can write information to the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and the storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and the storage medium may also be present in a user terminal as discrete components.

[0184] For software implementation, the techniques described in this application can be implemented with modules (e.g., procedures, functions, etc.) that perform the functions described in this application. These software codes can be stored in a memory unit and executed by a processor. The memory unit can be implemented within the processor or outside the processor. In the latter case, it is coupled to the processor in a communication manner via various means, which are well known in the art.

[0185] The above description includes examples of one or more embodiments. Of course, it is impossible to describe all possible combinations of components or methods for the purpose of describing the above embodiments, but it should be recognized by those skilled in the art that the various embodiments may be further combined and arranged. Therefore, the embodiments described herein are intended to cover all such changes, modifications and variations that fall within the scope of protection of the appended claims. In addition, with respect to the term "comprising" used in the specification or claims, the word is covered in a manner similar to the term "including", just as "including," is explained as a transitional word in the claims. In addition, any term "or" used in the specification of the claims is intended to mean "non-exclusive or".

Claims

1. A method for constructing a three-dimensional rock physics template, characterized in that: include: According to the actual value range of each sweet spot evaluation parameter of the shale oil reservoir, data of the sweet spot evaluation parameter within the value range are respectively constructed to obtain a sample data set; the sample data set includes a plurality of sample data, the sample data includes data of each sweet spot evaluation parameter, and the data of each sweet spot evaluation parameter between each sample data is not completely the same; The sweet spot evaluation parameter data of each sample data is calculated to obtain the shale equivalent stiffness coefficient corresponding to each sample data; According to the shale equivalent stiffness coefficient corresponding to each sample data, the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data are solved respectively; A three-dimensional rock physics template is constructed based on the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data.

2. The method according to claim 1, characterized in that The sweet spot evaluation parameters include lithology parameters, physical property parameters and bedding fractures; The shale equivalent stiffness coefficient corresponding to the sample data is determined in the following way: According to the data of the lithology parameters in the sample data, construct the elastic stiffness coefficient of the inorganic skeleton corresponding to the sample data; According to the data of the physical property parameters in the sample data and the elastic stiffness coefficient of the inorganic skeleton, constructing the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data; According to the data of bedding fractures in the sample data and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter, an anisotropic equivalent stiffness coefficient is constructed as the shale equivalent stiffness coefficient corresponding to the sample data.

3. The method according to claim 2, characterized in that The data of lithological parameters include clay mineral data and non-clay mineral data; The step of constructing the elastic stiffness coefficient of the inorganic skeleton corresponding to the sample data according to the data of the lithology parameters in the sample data includes: Calculating the clay mineral data to obtain the clay mineral equivalent elastic modulus corresponding to the data sample; Calculating the non-clay mineral data to obtain the non-clay mineral equivalent elastic modulus corresponding to the data sample; According to the equivalent elastic modulus of the clay mineral and the equivalent elastic modulus of the non-clay mineral, the equivalent elastic modulus of the inorganic skeleton corresponding to the sample data is obtained as the elastic stiffness coefficient of the inorganic skeleton.

4. The method according to claim 3, characterized in that Clay minerals are of various kinds; The step of calculating the clay mineral data to obtain the clay mineral equivalent elastic modulus corresponding to the data sample includes: Various clay minerals are mixed to obtain mixed clay mineral data, and the mixed clay mineral data are calculated to obtain the clay mineral equivalent elastic modulus corresponding to the data sample.

5. The method according to claim 2, characterized in that The data of the physical property parameters include at least one kind of organic matter data and corresponding organic pore data; The method of constructing an equivalent stiffness coefficient of an inorganic skeleton containing organic matter corresponding to the sample data according to the data of the physical property parameters in the sample data and the elastic stiffness coefficient of the inorganic skeleton comprises: Calculate each organic matter data and the corresponding organic pore data to determine the equivalent elastic modulus of each organic matter containing organic pores; According to the equivalent elastic modulus of each organic matter containing organic pores and the elastic stiffness coefficient of the inorganic skeleton, the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data is obtained.

6. The method according to claim 5, characterized in that The organic matter includes kerogen and asphalt; The equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data is obtained according to the equivalent elastic modulus of each organic matter containing organic pores and the elastic stiffness coefficient of the inorganic skeleton, including: According to the equivalent elastic modulus of the kerogen containing organic pores and the elastic stiffness coefficient of the inorganic skeleton, an equivalent stiffness coefficient of the inorganic skeleton containing kerogen is obtained; According to the equivalent stiffness coefficient of the inorganic skeleton containing kerogen and the equivalent elastic modulus of the asphalt containing organic pores, the equivalent stiffness coefficient of the inorganic skeleton containing organic matter corresponding to the sample data is obtained.

7. The method according to claim 2, characterized in that The anisotropic equivalent stiffness coefficient is constructed according to the data of the bedding fractures in the sample data and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter, including: According to the bedding fracture density data and the bedding fracture aspect ratio data in the bedding fracture data and the equivalent stiffness coefficient of the inorganic skeleton containing organic matter, an anisotropic differential equivalent medium model is used to obtain an anisotropic equivalent stiffness coefficient.

8. The method according to claim 1, characterized in that Elastic parameter data include longitudinal wave impedance data and longitudinal and transverse wave velocity ratio data; According to the shale equivalent stiffness coefficient corresponding to the sample data, the elastic parameter data of the shale oil reservoir corresponding to the sample data is solved, including: Determining the density of the shale oil reservoir corresponding to the sample data; Determining the longitudinal wave vertical velocity and the shear wave velocity according to the density and the shale equivalent stiffness coefficient corresponding to the sample data; Determining longitudinal wave impedance data according to the longitudinal wave vertical velocity and the density; The longitudinal and shear wave velocity ratio data is determined based on the longitudinal wave vertical velocity and the shear wave velocity.

9. The method according to claim 8, characterized in that The method of constructing a three-dimensional rock physics template according to the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data includes: Construct a three-dimensional coordinate system based on the longitudinal wave impedance, the longitudinal and transverse wave velocity ratio and the anisotropy parameters; The longitudinal wave impedance data, longitudinal and transverse wave velocity ratio data and anisotropy parameter data of the shale oil reservoir corresponding to each sample data are respectively marked in the three-dimensional coordinate system as a set of coordinate data to obtain a three-dimensional rock physics template.

10. A method for identifying sweet spots in shale oil reservoirs, characterized in that: include: Obtain evaluation parameter data of each sweet spot of the shale oil reservoir to be identified; According to the evaluation parameter data of each sweet spot of the shale oil reservoir to be identified, an identification result of the sweet spot of the shale oil reservoir to be identified is obtained through a three-dimensional rock physics template; The three-dimensional rock physics template is obtained by the method for constructing a three-dimensional rock physics template described in any one of claims 1-9.

11. A device for constructing a three-dimensional rock physics template, characterized in that: include: A sample data module is constructed, which is used to construct the data of the sweet spot evaluation parameters within the value range according to the actual value range of each sweet spot evaluation parameter of the shale oil reservoir, so as to obtain a sample data set; the sample data set includes a plurality of sample data, the sample data includes the data of each sweet spot evaluation parameter, and the data of each sweet spot evaluation parameter between each sample data is not completely the same; A calculation module, used to calculate the sweet spot evaluation parameter data of each sample data, and obtain the shale equivalent stiffness coefficient corresponding to each sample data; A solution module, used for solving elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data according to the shale equivalent stiffness coefficient corresponding to each sample data; The template construction module is used to construct a three-dimensional rock physics template according to the elastic parameter data and anisotropic parameter data of the shale oil reservoir corresponding to each sample data.

12. A device for identifying sweet spots in shale oil reservoirs, characterized in that: include: An acquisition module, used for acquiring evaluation parameter data of each sweet spot of the shale oil reservoir to be identified; An identification module, used for obtaining an identification result of the sweet spot of the shale oil reservoir to be identified through a three-dimensional rock physics template according to the evaluation parameter data of each sweet spot of the shale oil reservoir to be identified; The three-dimensional rock physics template is obtained by the method for constructing a three-dimensional rock physics template described in any one of claims 1-9.

13. A computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, which, when executed by a processor, implement the method for constructing a three-dimensional rock physics template as described in any one of claims 1-9.

14. A terminal device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for constructing a three-dimensional rock physical template as described in any one of claims 1-9 when executing the program.

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