A multi-scale fractured tight reservoir scattering rock physics modeling method

Abstract

The application discloses a kind of multi-scale fissure dense reservoir scattering rock physics modeling methods, belong to deep sea oil and gas field exploration and development and dense reservoir parameter prediction technical field, the method includes based on VRH model calculation rock matrix equivalent modulus;Based on Mori-Tanaka theory and variable pressure experiment measurement estimates fissure parameter and dry rock skeleton modulus, and using Gassmann theory calculates saturated rock modulus;Based on Foldy approximation and fissure fractal distribution characteristics constructs multi-scale fissure scattering model;Based on ultrasonic experiment and well logging data establishes velocity-attenuation template and verifies;Based on template quantitative relationship and actual data inversion reservoir parameter and identify sweet spot.The application realizes the quantitative characterization and sweet spot identification of dense reservoir multi-scale fissure.

Description

Technical Field

[0001] This invention belongs to the field of deep-sea oil and gas field exploration and development and tight reservoir parameter prediction technology, and particularly relates to a multi-scale fractured tight reservoir scattering rock physics modeling method. Background Technology

[0002] Rock physics models serve as a bridge connecting reservoir microstructure and macroscopic geophysical responses, playing a crucial role in oil and gas exploration, geothermal development, and carbon sequestration monitoring. Especially in unconventional reservoirs such as tight sandstone and shale, diagenesis, tectonic movements, and dissolution create multi-scale pore systems dominated by intergranular pores, dissolution pores, and microfractures. This heterogeneity leads to significant seismic wave velocity dispersion and attenuation. Traditional rock physics theories, based on the assumption of a homogeneous medium, are only applicable to elastic wave propagation under long-wavelength conditions. However, actual reservoirs commonly exhibit multi-scale heterogeneity, such as fracture networks and differences in pore structure, making it difficult for traditional theories to accurately describe wavefield response characteristics. When the wavelength approaches the characteristic scale of the heterogeneity, scattering effects alter the wavefield energy distribution; therefore, traditional methods have inherent limitations in predicting wave propagation patterns and inverting reservoir parameters.

[0003] Currently, methods for characterizing rock microstructure are mainly divided into direct observation methods and indirect inversion methods. Direct observation techniques are limited by resolution, making it difficult to fully capture the spatial distribution characteristics of submicron-level pores and fractures. Indirect inversion methods rely on the statistical correlation between elastic parameters and pore structure, but require idealized approximations of complex pore systems, resulting in poor model adaptability to actual reservoirs. Current rock physics research generally believes that seismic wave attenuation mainly stems from the coupling effect of inherent attenuation and scattering attenuation. These two mechanisms are difficult to separate effectively in the time or frequency domain, becoming a key bottleneck for high-precision reservoir parameter inversion. Existing scattering models are mostly based on the assumption of a single-scale scatterer, which is difficult to accurately describe wave propagation behavior in complex porous media. The pore-scale distribution of subsurface media often exhibits statistical self-similarity, but existing models are insufficient in quantitatively characterizing the correlation between key fracture parameters and macroscopic wavefield response, lacking universality. Therefore, existing technologies cannot meet the urgent need for high-precision rock physics models for identifying sweet spots in tight reservoirs. It is imperative to start from the complex structure of reservoir rocks, integrate fracture-scale distribution characteristics, and construct a more universal model to promote the practical application of theoretical models. In this field, a sweet spot is a local segment or location within a reservoir that has the best quality and highest production capacity; a sweet spot area is a concentrated region where sweet spots are continuously distributed on a plane and have economies of scale. Summary of the Invention

[0004] To address the aforementioned technical challenges, this invention proposes a multi-scale fractured tight reservoir scattering rock physics modeling method, which enables high-precision inversion of reservoir parameters and accurate identification of sweet spots, providing reliable technical support for the exploration and development of tight oil and gas fields.

[0005] To achieve the above object, the application provides a multi-scale fracture dense reservoir scattering rock physics modeling method, comprising:

[0006] calculating the equivalent modulus of the rock matrix based on a Voigt-Reuss-Hill model;

[0007] estimating the fracture parameters and the dry rock skeleton modulus based on a Mori-Tanaka theory and a variable pressure experiment measurement, and calculating the saturated rock modulus using a Gassmann theory;

[0008] constructing a multi-scale fracture scattering model based on a Foldy approximation and fracture fractal distribution characteristics;

[0009] establishing a velocity-attenuation template based on ultrasonic wave experiments and logging data and verifying the template;

[0010] inverting reservoir parameters and identifying sweet spots based on the quantitative relationship of the velocity-attenuation template and actual data.

[0011] Optionally, the process of calculating the equivalent modulus of the rock matrix based on the Voigt-Reuss-Hill model comprises:

[0012] determining the quantitative composition of various minerals in the rock sample through X-ray diffraction analysis;

[0013] based on the quantitative composition, calculating the equivalent bulk modulus and equivalent shear modulus of the rock matrix using the Voigt-Reuss-Hill model.

[0014] Optionally, the process of estimating the fracture parameters and the dry rock skeleton modulus based on the Mori-Tanaka theory and the variable pressure experiment measurement comprises:

[0015] assuming that the medium contains rigid pores and flexible pores;

[0016] calculating the equivalent modulus of the rock containing rigid pores based on the Mori-Tanaka theory;

[0017] inverting the rigid porosity using the measured longitudinal wave velocity and transverse wave velocity under high effective pressure;

[0018] based on the rigid porosity and the experimentally measured elastic modulus of the dry rock under different confining pressures, estimating the fracture density through differential effective medium theory;

[0019] calculating the equivalent bulk modulus and equivalent shear modulus of the dry rock based on the fracture density.

[0020] Optionally, the process of calculating the saturated rock modulus using the Gassmann theory comprises:

[0021] Obtaining a bulk modulus of the fluid under reservoir temperature and pressure conditions;

[0022] Based on the dry rock skeleton modulus, the rock matrix equivalent modulus and the total porosity, calculating the bulk modulus and shear modulus of the saturated rock using the Gassmann equation.

[0023] Optionally, the process of constructing a multi-scale fracture scattering model based on the Foldy approximation and the fracture fractal distribution characteristics includes:

[0024] Assuming that the fluid-saturated fractures are randomly and sparsely distributed in an isotropic elastic medium, the fracture size follows a fractal distribution;

[0025] Defining the probability density function of the fracture radius based on the fractal distribution;

[0026] Based on the Foldy approximation, deriving the longitudinal wave phase velocity and scattering attenuation expression of the random-orientation fracture-saturated medium.

[0027] Optionally, the process of establishing a velocity-attenuation template based on ultrasonic experiments and logging data and verification includes:

[0028] Substituting the rock skeleton modulus, fracture parameters and fluid properties obtained from the experimental data into the multi-scale fracture scattering model, establishing a quantitative relationship between the rock porosity, fracture density and the longitudinal wave velocity and attenuation;

[0029] Using the logging data to test and correct the quantitative relationship, thereby obtaining a velocity-attenuation rock physics template in the acoustic wave band.

[0030] Optionally, the process of inverting reservoir parameters and identifying sweet spots based on the quantitative relationship of the velocity-attenuation template and actual data includes:

[0031] Obtaining the longitudinal wave velocity and attenuation data in the acoustic logging data;

[0032] Inverting the reservoir porosity and fracture density based on the quantitative relationship of the velocity-attenuation template;

[0033] Identifying sweet spot areas according to the inverted porosity and fracture density, wherein the sweet spot areas correspond to high porosity and high fracture density areas.

[0034] Optionally, the fractal distribution includes that the fracture radius follows a fractal distribution within a range of minimum and maximum values.

[0035] Technical advantages of this invention: This invention discloses a multi-scale fractured tight reservoir scattering rock physics modeling method. The established rock physics model comprehensively considers the fractal distribution characteristics of multi-scale fractures in tight reservoirs, achieving a precise connection from microscopic fracture morphology to macroscopic rock properties, and can more finely characterize the heterogeneous structure of tight reservoirs. Based on the constructed quantitative relationship template of velocity-attenuation-porosity-fracture density, it can directly identify reservoir sweet spots by combining oilfield production data, providing a technical method from theoretical modeling to practical application for tight oil and gas exploration. The integrated multi-scale fractured scattering rock physics model established by this invention can explain the physical mechanism of broadband seismic wave propagation, achieve high-precision inversion of reservoir parameters and accurate identification of sweet spots, and provide reliable technical support for the exploration and development of tight oil and gas fields. Attached Figure Description

[0036] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0037] Figure 1 This is a schematic flowchart of a multi-scale fractured tight reservoir scattering rock physics modeling method according to an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram illustrating the quantitative relationship between porosity and fracture density and longitudinal wave velocity dispersion and attenuation in the acoustic frequency band according to an embodiment of the present invention.

[0039] Figure 3 This is a schematic diagram comparing reservoir porosity and fracture density predicted based on acoustic frequency band charts with well logging curves in an embodiment of the present invention. Detailed Implementation

[0040] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0041] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0042] like Figure 1 As shown, this embodiment provides a multi-scale fractured tight reservoir scattering rock physics modeling method, including:

[0043] The equivalent modulus of the rock matrix was calculated based on the Voigt-Reuss-Hill model.

[0044] Estimate fracture parameters and dry rock matrix modulus based on Mori-Tanaka theory and variable pressure experimental measurement, and calculate saturated rock modulus using Gassmann theory;

[0045] Based on Foldy approximation and fracture fractal distribution characteristics, a multi-scale fracture scattering model is constructed;

[0046] Based on ultrasonic wave experiment and logging data, a velocity-attenuation template is established and verified;

[0047] Based on the quantitative relationship of the velocity-attenuation template and the actual data, reservoir parameters are inverted and sweet spots are identified.

[0048] Further, the process of calculating the equivalent modulus of the rock matrix based on the Voigt-Reuss-Hill model includes:

[0049] Determine the quantitative composition of various minerals in the rock sample through X-ray diffraction analysis;

[0050] Based on the quantitative composition, the equivalent bulk modulus and equivalent shear modulus of the rock matrix are calculated using the Voigt-Reuss-Hill model.

[0051] Specifically, the implementation process of the embodiment includes:

[0052] The dense reservoir studied mainly consists of dense sandstone, and its mineral composition includes quartz, feldspar, clay minerals, etc. The quantitative composition of various minerals in the sample is determined through X-ray diffraction (XRD) analysis. The elastic modulus of the rock matrix is estimated by averaging the modulus of all minerals using the Voigt-Reuss-Hill (VRH) model:

[0053] (1);

[0054] (2);

[0055] wherein, and are the bulk modulus and shear modulus of the composite mineral, , and are the volume fraction, bulk modulus and shear modulus of the i-th mineral; i is the number of mineral types. The modulus of each mineral can be queried through a rock physics manual. N

[0056] Further, the process of estimating fracture parameters and dry rock matrix modulus based on Mori-Tanaka theory and variable pressure experimental measurement includes:

[0057] Assume that the medium contains rigid pores and flexible pores;​

[0058] Calculate the effective modulus of the rock containing rigid pores based on the Mori-Tanaka theory;

[0059] Invert the rigid porosity using the measured P-wave and S-wave velocities at high effective pressure;

[0060] Estimate the fracture density based on the rigid porosity and the measured dry rock elastic modulus at different confining pressures by the differential effective medium theory;

[0061] Calculate the effective bulk modulus and effective shear modulus of the dry rock based on the fracture density.

[0062] Specifically, the implementation process of the embodiment includes:

[0063] Assume that the medium contains two types of pores: rigid pores (such as intergranular pores and dissolution pores) and flexible pores (such as fractures). According to the Mori-Tanaka theory, when the rock matrix contains only rigid pores with a single aspect ratio, the effective bulk modulus and shear modulus of the rock containing rigid pores are respectively:

[0064] (3);

[0065] (4);

[0066] wherein, and are the bulk modulus and shear modulus of the rock containing rigid pores, respectively; is the rigid porosity; P and Q are the rigid pore shape factors, which depend on the pore aspect ratio and the Poisson's ratio of the mineral grain , and the expressions are:

[0067] (5);

[0068] (6);

[0069] wherein, , .

[0070] At high effective pressure, the fractures are completely closed, and the rock only retains rigid pores. At this time, the dry rock skeleton modulus containing rigid pores can be estimated using the measured P-wave and S-wave velocities at high pressure:

[0071] (7);

[0072] (8);

[0073] wherein, and are the P-wave and S-wave velocities measured at high effective stress, respectively; is the dry rock density. Combining equations (3)-(8), the inversion of the rigid porosity is achieved.

[0074] The cracks are embedded in the dry rock matrix, and the relationship between crack density and rock elastic modulus can be established by differential effective medium theory:

[0075] (9);

[0076] (10);

[0077] where is the Poisson's ratio of the rock containing rigid porosity; is the crack density. Therefore, using the experimentally measured dry rock elastic modulus and Poisson's ratio at different confining pressures, the rock crack density can be estimated by equations (9) and (10). Ignoring the interaction between cracks and rigid pores, the equivalent bulk modulus and shear modulus of the dry rock are:

[0078] (11);

[0079] (12).

[0080] Further, the process of calculating the saturated rock modulus using Gassmann theory includes:

[0081] obtaining the fluid bulk modulus under reservoir temperature and pressure conditions;

[0082] based on the dry rock matrix modulus, rock matrix equivalent modulus, and total porosity, using the Gassmann equation to calculate the bulk modulus and shear modulus of the saturated rock.

[0083] Specifically, the implementation process of the embodiment is:

[0084] For fluid-saturated rock, the fluid bulk modulus under reservoir temperature and pressure conditions is substituted into the Gassmann equation to calculate the bulk modulus and shear modulus of the saturated rock:

[0085] (13);

[0086] (14);

[0087] where, is the total porosity; Fluid bulk modulus; Saturated rock bulk modulus; Saturated rock shear modulus.

[0088] Further, the process of constructing a multi-scale fracture scattering model based on the Foldy approximation and the fracture fractal distribution characteristics includes:

[0089] Assuming that fluid-saturated fractures are randomly and sparsely distributed in an isotropic elastic medium, the fracture sizes follow a fractal distribution;

[0090] The probability density function of the fracture radius is defined based on the fractal distribution;

[0091] Based on the Foldy approximation, the expressions of the longitudinal wave phase velocity and scattering attenuation of the random-orientation fracture-saturated medium are derived.

[0092] Specifically, the implementation process of the embodiment includes:

[0093] The pore structure in the shallow crust and reservoir rock usually has fractal characteristics. Assuming that fluid-saturated fractures are randomly and sparsely distributed in an isotropic elastic medium, the fracture sizes follow a fractal distribution. For a medium containing fractures of different scales, the probability density of the fracture radius is expressed as where a min is the minimum fracture radius, D f is the fractal dimension. The fracture density with a radius of is where is the total fracture density. The fracture thickness is determined by the fracture aspect ratio and the fracture radius. Based on the Foldy approximation, the scattering model of the fractal fracture medium is derived, and then the expressions of the longitudinal wave phase velocity and scattering attenuation of the random-orientation fracture-saturated medium are:

[0094] (15);

[0095] (16);

[0096] where the coefficient is:

[0097] (17);

[0098] where , and are the longitudinal wave and transverse wave velocities of the saturated rock, respectively; a min , amax represents the range of fracture radii; θ is the angle of incidence of the longitudinal wave; is the wave number of the longitudinal wave; and The expression is:

[0099] (18);

[0100] wherein, and is discretized as:

[0101] , (19);

[0102] , (20);

[0103] wherein ; is the dimensionless wave number normalized by the fracture radius; is the Kronecker function; is the fracture thickness; is the angular frequency; is the viscosity of the saturating fluid, and The expression can be obtained from Kawahara and Yamashita (1992).

[0104] Further, the process of establishing and verifying the velocity-attenuation template based on the ultrasonic wave experiment and the logging data comprises:

[0105] substituting the rock matrix modulus, the fracture parameters and the fluid properties obtained from the experiment data into the multi-scale fracture scattering model to establish the quantitative relationship between the rock porosity, the fracture density and the longitudinal wave velocity and attenuation;

[0106] using the logging data to test and correct the quantitative relationship, thereby obtaining the velocity-attenuation petrophysical template under the acoustic wave frequency band.

[0107] Specifically, the implementation process of the embodiment comprises:

[0108] substituting the rock matrix modulus, the fracture parameters and the reservoir fluid properties obtained from the experiment data into equations (15) and (16) to establish the quantitative relationship between the rock porosity, the fracture density and the longitudinal wave velocity and attenuation. Meanwhile, the template is tested and corrected using the logging data, thereby obtaining the velocity-attenuation petrophysical template under the acoustic wave frequency band.

[0109] Further, the process of inverting the reservoir parameters and identifying the sweet spots based on the quantitative relationship of the velocity-attenuation template and the actual data comprises:

[0110] obtaining P-wave velocity and attenuation data in sonic logging data;

[0111] inverting reservoir porosity and fracture density based on the quantitative relationship of the velocity-attenuation template;

[0112] identifying sweet spots based on the inverted porosity and fracture density, wherein the sweet spots correspond to high porosity and high fracture density regions.

[0113] An application example of the present application:

[0114] The method of the present embodiment is simulated to obtain a reservoir velocity-attenuation template in the sonic frequency band. Laboratory observations are carried out on 10 typical samples of the target layer in the study area. The estimated complex mineral bulk modulus and shear modulus using the VRH model are 47-52 GPa and 35-38 GPa, respectively. The bulk modulus used in modeling is 49 GPa and the shear modulus is 37 GPa, and the particle density is 2.68 g / cm³. The bulk modulus of the saturated rock sample is between 18-30 GPa and the shear modulus is between 17-29 GPa, the porosity is between 1%-15%, and the fracture density is between 0-0.15. The reservoir fluid density is 1.004 g / cm³, the bulk modulus is 2.273 GPa, and the viscosity is 0.981 cP. The saturated rock modulus is calculated using the Gassmann equation. It is assumed that the fracture radius is in the range of 60-600 mm and obeys the fractal distribution with a fractal dimension of 2.58, and the fracture aspect ratio is fixed at 0.01, and the fracture thickness is derived from the corresponding fracture radius. The sonic logging frequency is 10 kHz.

[0115] Figure 2 The sonic template is compared with the logging data of Well A. The modeling results are generally consistent with the velocity and attenuation trends obtained from the logging data. The velocity changes significantly with porosity, while the attenuation changes are relatively insignificant.

[0116] Figure 3 The estimated porosity and fracture density based on the logging data and the sonic template of Well A are shown. The estimated porosity is between 2%-10%, which is consistent with the logging porosity curve. The actual production report shows that the main oil-bearing regions are located at depths of 1980 m, 2014 m, and 2024 m, which correspond to high porosity and high fracture density regions, while the remaining sections are usually water-saturated. This verifies the ability of the template to estimate reservoir porosity and fracture density. It is worth noting that low P-wave velocity anomalies combined with significant scattering attenuation can serve as reliable indicators of sweet spots in tight reservoirs, which are mainly characterized by high porosity and high fracture density.

[0117] Due to the innovation and practicability of the technical solution in the fields of tight oil and gas exploration and development, carbon storage monitoring, etc., the technical solution can be widely applied in the following fields: 1. In the field of tight oil and gas exploration and development, the technical solution can quantitatively predict the porosity and fracture density of a tight reservoir through a sound wave frequency band velocity-attenuation template, and accurately identify a high-yield sweet spot area; at the same time, the technical solution can explain the differences in seismic wave responses under different frequencies, and provide reliable basis for well site deployment and reservoir productivity evaluation, and is especially suitable for main tight oil and gas production areas such as the Ordos Basin and the Sichuan Basin. 2. In the field of carbon storage monitoring, the technical solution can monitor the opening and closing state of a reservoir fracture and fluid distribution characteristics in a CO2 injection process in real time through dynamic changes of scattering attenuation; at the same time, the technical solution can predict the fracture development law of underground medium, and provide parameter support for gas storage site selection, and can also be used for seismic monitoring during carbon storage to ensure storage safety. Therefore, the technical solution has broad market prospects and application requirements.

[0118] The application discloses a multi-scale fractured tight reservoir scattering rock physics modeling method, and a rock physics model is established by comprehensively considering fractal distribution characteristics of multi-scale fractures of a tight reservoir, accurately connecting from a rock micro-fracture form to a macro rock attribute, and being capable of more finely characterizing a heterogeneous structure of the tight reservoir. Based on a velocity-attenuation-porosity-fracture density quantitative relation template constructed, a reservoir sweet spot can be directly identified in combination with oilfield production data, and a technical method from theoretical modeling to practical application is provided for tight oil and gas exploration. The integrated multi-scale fractured scattering rock physics model established by the application can explain a physical mechanism of wide-band seismic wave propagation, realize high-precision inversion of reservoir parameters and accurate identification of a sweet spot, and provides reliable technical support for exploration and development of a tight oil and gas field.

[0119] The above is only a preferred specific embodiment of the application, but the protection scope of the application is not limited to this, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the application, which should be covered in the protection scope of the application. Therefore, the protection scope of the application should be subject to the protection scope of the claims.

Claims

1. A multi-scale fractured tight reservoir scattering rock physics modeling method, characterized in that, include: The equivalent modulus of the rock matrix was calculated based on the Voigt-Reuss-Hill model. Fracture parameters and dry rock skeleton modulus were estimated based on Mori-Tanaka theory and variable pressure experimental measurements, and saturated rock modulus was calculated using Gassmann theory. A multi-scale crack scattering model is constructed based on the Foldy approximation and the fractal distribution characteristics of cracks; A velocity-attenuation template was established and validated based on ultrasonic experimental and logging data. Based on the quantitative relationship of the velocity-decay template and actual data, reservoir parameters are inverted and sweet spots are identified; The process of establishing and validating a velocity-attenuation template based on ultrasonic experimental and logging data includes: Substituting the rock skeleton modulus, fracture parameters, and fluid properties obtained from the experimental data into the multi-scale fracture scattering model, a quantitative relationship between rock porosity, fracture density, and P-wave velocity and attenuation is established. The quantitative relationship is verified and corrected using well logging data to obtain a velocity-attenuation rock physics template in the acoustic band. The process of estimating fracture parameters and dry rock skeleton modulus based on Mori-Tanaka theory and variable pressure experimental measurements includes: Assume the medium contains both rigid and flexible pores; The equivalent modulus of rocks with rigid pores was calculated based on the Mori-Tanaka theory. Rigid porosity is inverted using longitudinal wave velocity and transverse wave velocity measured under high effective pressure; Based on the rigid porosity and the dry rock elastic modulus measured experimentally under different confining pressures, the fracture density is estimated using the differential equivalent medium theory. The equivalent bulk modulus and equivalent shear modulus of the dry rock are calculated based on the fracture density. The process of constructing a multi-scale fracture scattering model based on the Foldy approximation and fracture fractal distribution characteristics includes: Assume that fluid-saturated cracks are randomly and sparsely distributed in an isotropic elastic medium, and that the crack size follows a fractal distribution; The probability density function for defining the crack radius is based on a fractal distribution; Based on the Foldy approximation, we derive the expressions for the longitudinal wave phase velocity and scattering attenuation in a saturated medium with randomly oriented fractures; The process of inverting reservoir parameters and identifying sweet spots based on the quantitative relationship of the velocity-attenuation template and actual data includes: Acquire P-wave velocity and attenuation data from acoustic logging data; Based on the quantitative relationship of the velocity-attenuation template, reservoir porosity and fracture density are inverted; Sweet spots are identified based on the inverted porosity and fracture density, where sweet spots correspond to regions with high porosity and high fracture density.

2. The multi-scale fractured tight reservoir scattering rock physics modeling method as described in claim 1, characterized in that, The process of calculating the equivalent modulus of rock matrix based on the Voigt-Reuss-Hill model includes: The quantitative composition of various minerals in the rock sample was determined by X-ray diffraction analysis; Based on the quantitative composition, the equivalent bulk modulus and equivalent shear modulus of the rock matrix were calculated using the Voigt-Reuss-Hill model.

3. The multi-scale fractured tight reservoir scattering rock physics modeling method as described in claim 1, characterized in that, The process of calculating the saturated rock modulus using Gassmann theory includes: Obtain the fluid bulk modulus under reservoir temperature and pressure conditions; Based on the dry rock skeleton modulus, the rock matrix equivalent modulus, and the total porosity, the bulk modulus and shear modulus of the saturated rock are calculated using the Gassmann equation.

4. The multi-scale fractured tight reservoir scattering rock physics modeling method as described in claim 1, characterized in that, The fractal distribution includes the fractal distribution of the crack radius within the range of minimum and maximum values.

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