A method and system for predicting fluid mobility gradient attributes of a tight sand gas reservoir

Abstract

The present application relates to oil and gas geophysical exploration technology field, specifically disclose a kind of tight sandstone gas reservoir fluid mobility gradient attribute prediction method and system, the method includes constructing fluid mobility term's reflection coefficient expression, and deduce the formula for calculating fluid mobility using dispersion attribute, construct and frequency and seismic wave incidence angle related fluid mobility gradient attribute;Establish double-pore petrophysical model, generate synthetic seismogram, apply frequency-variable AVO inversion to the synthetic seismogram, extract bulk modulus dispersion attribute and shear modulus dispersion attribute;Fluid mobility changing with frequency and incidence angle is calculated, based on gradient attribute calculation formula and fluid mobility, fluid mobility gradient attribute is calculated.The present application makes full use of the response of the seismic wave dispersion and attenuation caused by permeability and gas saturation, constructs the seismic gradient attribute and calculation method of fluid mobility, realizes the high-precision prediction of fluid mobility by applying the elastic and dispersion petrophysical information of seismic signal.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysical exploration technology, specifically a method and system for predicting the fluid mobility gradient properties of tight sandstone gas reservoirs. Background Technology

[0002] Against the backdrop of ever-increasing global energy demand, tight sandstone gas reservoirs, as important unconventional oil and gas resources, possess enormous exploration potential and broad development prospects. The primary exploration objective for tight sandstone gas reservoirs is to find tight sandstone formations with high gas content, high porosity, high permeability, high pore pressure, and well-developed microfractures. Fluid mobility, a comprehensive reflection of the fluid seepage capacity in tight reservoirs, is influenced by parameters such as reservoir permeability and fluid viscosity, and is a crucial indicator for the development and engineering sweet spot evaluation of tight sandstone gas reservoirs. Theoretical analysis and experimental measurements show that changes in fluid mobility can cause significant changes in the petrophysical properties of tight sandstone. However, due to the complex petrophysical characteristics of fluid mobility in tight sandstone gas reservoirs, and the incomplete understanding of its seismic response mechanism, predicting reservoir fluid mobility using seismic methods remains challenging. Therefore, it is necessary to conduct research on the petrophysical response characteristics related to fluid mobility in tight sandstone gas reservoirs and develop targeted methods for predicting reservoir fluid mobility.

[0003] In the field of seismic prediction techniques for reservoir fluid mobility, Silin et al. derived a linear asymptotic expression for the seismic low-frequency reflection coefficient of fluid mobility in 2004, and Goloshubin et al. further studied the calculation method of fluid mobility attributes in 2006. Building on this, Chen et al. applied this method to calculate reservoir fluid mobility parameters from seismic data in 2012. Cai Hanpeng, in 2012, discussed the selection method for the dominant seismic frequency while applying this method to calculate fluid mobility parameters. Guo Xusheng et al. analyzed the influence of formation thickness and dominant frequency on fluid mobility prediction results in 2016. Currently, research on seismic prediction methods for fluid mobility mainly focuses on improving the time-frequency resolution of calculation results through different time-frequency analysis methods. These include: Zhang Shengqiang et al. conducted research on reservoir fluid mobility parameter prediction based on high-resolution sparse inversion spectral decomposition in 2015; Yang Yadi et al. applied the high-precision matching pursuit algorithm to calculate fluid mobility attributes in 2017; Yang Jixin et al. introduced sparse adaptive S-transform into reservoir fluid mobility prediction in 2017; Luo et al. combined Bayesian adaptive seismic inversion method with time-frequency analysis to conduct reservoir fluid mobility prediction in 2018; Liu Jie et al. introduced deconvolution generalized S-transform and LRM linear fitting method to calculate fluid mobility parameters in 2019; Zhang Shengqiang et al. applied complex spectral decomposition technology based on sparse inversion to introduce phase information into fluid mobility prediction in 2019; and Zhang et al. achieved reservoir fluid mobility prediction by combining generalized S-transform and Lucy-Richardson algorithm in 2020. Furthermore, Zhang et al. in 2021 and Luo et al. in 2022 explored a post-stack seismic frequency-varying prediction method for fluid mobility. Zhou Wei et al. in 2022 established the relationship between fluid mobility and seismic wave incident angle and frequency, and applied the generalized S-transform of synchronous compression as a time-frequency analysis method to calculate fluid mobility parameters.

[0004] As mentioned above, there is currently no prediction method that fully considers fluid mobility parameters with more rock physics implications. Therefore, it is necessary to construct a prediction method for reservoir fluid mobility parameters with rock physics implications, based on the pre-stack seismic frequency-varying reflection theory framework and making full use of the pre-stack and frequency-varying reflection information in seismic data. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for predicting the fluid mobility gradient properties of tight sandstone gas reservoirs, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for predicting fluid mobility gradient properties in tight sandstone gas reservoirs, the method comprising:

[0008] Based on the earthquake frequency-varying reflection theory, an expression for the reflection coefficient containing the fluid mobility term is constructed, and a formula for calculating fluid mobility using the dispersion property is derived. Based on the fluid mobility calculation formula, a fluid mobility gradient property related to frequency and seismic wave incident angle is constructed.

[0009] A dual-porosity rock physics model was established to simulate the dispersion characteristics of P-wave and S-wave velocities under different permeability and gas saturation conditions.

[0010] Based on the P-wave and S-wave velocities, and combined with the propagation matrix theory, a synthetic seismic record is generated. Frequency-varying AVO inversion is applied to the synthetic seismic record to extract the bulk modulus dispersion attribute and the shear modulus dispersion attribute.

[0011] Based on the fluid mobility calculation formula and dispersion properties, the fluid mobility that varies with frequency and incident angle is calculated. Based on the gradient property calculation formula and fluid mobility, the fluid mobility gradient property is calculated.

[0012] As a further embodiment of the present invention, the formula for calculating the fluid mobility is as follows:

[0013] ;

[0014] , ;

[0015] Where K is the bulk modulus, µ is the shear modulus, A(θ) is the weighting coefficient of the bulk modulus term, B(θ) is the weighting coefficient of the shear modulus term, ω is the frequency, θ is the angle of incidence, and D... K For the bulk modulus dispersion property, D µ This refers to the dispersion property of the shear modulus.

[0016] As a further embodiment of the present invention, the fluid mobility gradient attribute includes a frequency gradient attribute D. Mf-F , incident angle gradient property D Mf-In And the comprehensive gradient attribute D Mf The calculation formulas are as follows:

[0017] ;

[0018] ;

[0019] ;

[0020] Where, ω H and ω L M represents high frequency and low frequency respectively. f (ω H ) and M f (ω L θ represents the fluid mobility corresponding to these frequencies.H and θ L The corresponding flow rates for large and small incident angles are M and M, respectively. f (θ H ) and M f (θ L ).

[0021] As a further embodiment of the present invention, the dual-porosity rock physics model is constructed based on Chapman's multi-scale fracture theory and is used to characterize the changes in elastic parameters of dense sandstone containing spherical pores and microcracks under frequency variation conditions.

[0022] As a further embodiment of the present invention, the synthetic seismic record is obtained by calculating the reflection coefficient frequency-by-frequency using the propagation matrix method and combining it with the source wavelet spectrum via inverse Fourier transform.

[0023] As a further embodiment of the present invention, the bulk modulus dispersion property and the shear modulus dispersion property are extracted from pre-stack seismic data through frequency-varying AVO inversion.

[0024] This invention also provides a system for predicting the fluid mobility gradient properties of tight sandstone gas reservoirs, the system comprising:

[0025] The fluid mobility gradient attribute construction module is used to construct a reflection coefficient expression containing a fluid mobility term based on the earthquake frequency-varying reflection theory, and derive a formula for calculating fluid mobility using dispersion attributes. Based on the fluid mobility calculation formula, a fluid mobility gradient attribute related to frequency and earthquake wave incident angle is constructed.

[0026] The simulation module is used to establish a dual-porosity rock physics model to simulate the dispersion characteristics of P-wave and S-wave velocities under different permeability and gas saturation conditions.

[0027] The inversion module is used to generate a synthetic seismic record based on the P-wave and S-wave velocities and in combination with the propagation matrix theory, and to apply frequency-varying AVO inversion to the synthetic seismic record to extract the bulk modulus dispersion attribute and the shear modulus dispersion attribute.

[0028] The fluid mobility gradient attribute calculation module is used to calculate the fluid mobility as a function of frequency and incident angle based on the fluid mobility calculation formula and dispersion attribute, and to calculate the fluid mobility gradient attribute based on the gradient attribute calculation formula and fluid mobility.

[0029] Compared with the prior art, the beneficial effects of the present invention are: the present invention makes full use of the seismic wave dispersion and attenuation response caused by permeability and gas saturation to construct the seismic gradient attribute and calculation method of fluid mobility, and realizes high-precision prediction of fluid mobility using the elasticity and dispersion rock physics information of seismic signals. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0031] Figure 1 The flowchart illustrates a method for predicting the fluid mobility gradient properties of tight sandstone gas reservoirs, as provided in an embodiment of the present invention.

[0032] Figure 2 The graphs showing the changes in P-wave velocity and S-wave velocity with frequency during permeability changes provided in this embodiment of the invention are shown in Figure (a) and Figure (b).

[0033] Figure 3 The following are curves showing the changes in P-wave velocity and S-wave velocity with frequency when the gas saturation changes, provided in the embodiments of the present invention: (a) P-wave velocity with frequency, and (b) S-wave velocity with frequency.

[0034] Figure 4 A three-layer geological and geophysical model provided for embodiments of the present invention.

[0035] Figure 5 Figure (a) shows the AVO response at a permeability of 0.1 mD, Figure (b) shows the AVO response at a permeability of 1 mD, Figure (c) shows the AVO response at a permeability of 5 mD, and Figure (d) shows the dispersion property D. K The graph shows the variation curves, and (e) shows the dispersion attribute D. μ Change curve graph.

[0036] Figure 6 Figure (a) shows the fluid mobility as a function of frequency when the permeability is 0.1 mD; Figure (b) shows the fluid mobility as a function of frequency when the permeability is 1 mD; Figure (c) shows the fluid mobility as a function of frequency when the permeability is 5 mD; Figure (d) shows the fluid mobility gradient attribute related to frequency; Figure (e) shows the fluid mobility as a function of incident angle when the permeability is 0.1 mD; Figure (f) shows the fluid mobility as a function of incident angle when the permeability is 1 mD; Figure (g) shows the fluid mobility as a function of incident angle when the permeability is 5 mD; Figure (h) shows the fluid mobility gradient attribute related to incident angle; and Figure (i) shows the overall fluid mobility gradient attribute.

[0037] Figure 7Figure (a) shows the AVO response when the gas saturation is 0.3 and the permeability is maintained at 1 mD; Figure (b) shows the AVO response when the gas saturation is 0.5 and the permeability is maintained at 1 mD; Figure (c) shows the AVO response when the gas saturation is 0.7 and the permeability is maintained at 1 mD; Figure (d) shows the elastic modulus dispersion property D under different gas saturation conditions. K The variation curve (e) shows the dispersion property D of the elastic modulus under different gas saturation conditions. μ Change curve graph.

[0038] Figure 8 Figure (a) shows the fluid mobility as a function of frequency when the gas saturation is 0.3 and the permeability is maintained at 1 mD; Figure (b) shows the fluid mobility as a function of frequency when the gas saturation is 0.5 and the permeability is maintained at 1 mD; Figure (c) shows the fluid mobility as a function of frequency when the gas saturation is 0.7 and the permeability is maintained at 1 mD; Figure (d) shows the frequency-dependent fluid mobility gradient; Figure (e) shows the fluid mobility as a function of incident angle when the gas saturation is 0.3 and the permeability is maintained at 1 mD; Figure (f) shows the fluid mobility as a function of incident angle when the gas saturation is 0.5 and the permeability is maintained at 1 mD; Figure (g) shows the fluid mobility as a function of incident angle when the gas saturation is 0.7 and the permeability is maintained at 1 mD; Figure (h) shows the incident angle-dependent fluid mobility gradient; and Figure (i) shows the overall fluid mobility gradient.

[0039] Figure 9 The diagram shows the calculated fluid mobility gradient properties when permeability and gas saturation change simultaneously, as provided in this embodiment of the invention.

[0040] Figure 10 This is a well profile of post-stack seismic data provided in an embodiment of the present invention.

[0041] Figure 11 A well-connected profile diagram of the calculated fluid mobility gradient properties provided for an embodiment of the present invention. Detailed Implementation

[0042] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0043] like Figure 1 As shown in the embodiment of the present invention, a method for predicting the fluid mobility gradient property of tight sandstone gas reservoirs includes:

[0044] Based on the earthquake frequency-varying reflection theory, an expression for the reflection coefficient containing the fluid mobility term is constructed, and a formula for calculating fluid mobility using the dispersion property is derived. Based on the fluid mobility calculation formula, a fluid mobility gradient property related to frequency and seismic wave incident angle is constructed.

[0045] A dual-porosity rock physics model was established to simulate the dispersion characteristics of P-wave and S-wave velocities under different permeability and gas saturation conditions.

[0046] Based on the P-wave and S-wave velocities, and combined with the propagation matrix theory, a synthetic seismic record is generated. Frequency-varying AVO inversion is applied to the synthetic seismic record to extract the bulk modulus dispersion attribute and the shear modulus dispersion attribute.

[0047] Based on the fluid mobility calculation formula and dispersion properties, the fluid mobility that varies with frequency and incident angle is calculated. Based on the gradient property calculation formula and fluid mobility, the fluid mobility gradient property is calculated.

[0048] In this embodiment, based on the theoretical framework of seismic frequency-varying reflection, the traditional method of fluid mobility prediction using post-stack seismic data and time-frequency analysis technology is extended. A seismic gradient attribute of fluid mobility with rock physics meaning, characterized by the frequency-varying elastic modulus, and its calculation method are constructed, providing a seismic time-frequency domain prediction method for reservoir fluid mobility evaluation.

[0049] The constructed fluid mobility gradient properties, combined with frequency and pre-stack seismic information, lay a theoretical foundation for the prediction of gas content and permeability.

[0050] The constructed rock physics model comprehensively considers the multiple effects of mineral composition, pore structure, fluid properties, and pre-permeability, and describes the elastic parameter characteristics of permeability and gas saturation changes.

[0051] By combining rock physics models and earthquake propagation matrix theory, a high-precision seismic forward modeling method can be established, which can realize high-precision seismic forward modeling simulation of the elastic and dispersion responses of seismic reflected waves related to permeability, laying a theoretical and pre-data foundation for calculating fluid mobility.

[0052] In a preferred embodiment of the present invention, the formula for calculating the fluid flow rate is as follows:

[0053] ;

[0054] , ;

[0055] Where K is the bulk modulus, µ is the shear modulus, A(θ) is the weighting coefficient of the bulk modulus term, B(θ) is the weighting coefficient of the shear modulus term, ω is the frequency, θ is the angle of incidence, and D... K For the bulk modulus dispersion property, D µThis refers to the dispersion property of the shear modulus.

[0056] In this embodiment, Silin et al. (2004) established a low-frequency asymptotic formula for P-wave reflection:

[0057] ;

[0058] Where R0 and R1 are real coefficients, characterizing the relationship between rock and fluid properties, κ represents reservoir permeability, η is fluid viscosity, and ρ... f It is the density of the reservoir rock.

[0059] Taking the derivative with respect to frequency ω, we get:

[0060] ;

[0061] According to the definition of fluid mobility The above formula can be expressed as:

[0062] ;

[0063] definition The fluid mobility of a frequency-varying fluid can be expressed as:

[0064] ;

[0065] Bulk modulus (K) is often used to characterize gas-bearing tight sandstone. Based on Gary (1999), the reflection coefficient equation for d-bulk modulus, shear modulus, and density is proposed:

[0066] ;

[0067] in, ;

[0068] ;

[0069] ;

[0070] in, and denoted as the ratio of P-wave to S-wave velocity in dry rock and saturated rock, respectively; μ is the shear modulus of saturated rock; θ is the angle of incidence; ρ is the density of saturated rock; and Δ represents the difference in physical properties between layers.

[0071] Considering the frequency dependence of bulk modulus and shear modulus, and assuming that density does not change with frequency, the frequency-varying AVO formula can be obtained:

[0072] ;

[0073] Taking the derivative with respect to frequency, we get:

[0074] ;

[0075] Substituting into the formula and treating the parameter P as a scale factor, we obtain the formula for calculating fluid mobility:

[0076] ;

[0077] , .

[0078] This can be further expressed as:

[0079] ;

[0080] Performing a first-order Taylor expansion at the reference frequency ω0, we obtain:

[0081] ;

[0082] in,

[0083] ;

[0084] Inversion dispersion property D K and D μ :

[0085] ;

[0086] At the same time, the calculated dispersion attribute D K and D μ Substitute the values ​​into the calculation of fluid mobility.

[0087] In a preferred embodiment of the present invention, based on the established fluid mobility calculation formula, a gradient attribute related to fluid mobility and frequency and angle is constructed, and a fluid mobility gradient attribute is further constructed, wherein the fluid mobility gradient attribute includes a frequency gradient attribute D. Mf-F , incident angle gradient property D Mf-In And the comprehensive gradient attribute D Mf The calculation formulas are as follows:

[0088] ;

[0089] ;

[0090] ;

[0091] Where, ω H and ω L M represents high frequency and low frequency respectively. f (ω H ) and M f (ω Lθ represents the fluid mobility corresponding to these frequencies. H and θ L The corresponding flow rates for large and small incident angles are M and M, respectively. f (θ H ) and M f (θ L ).

[0092] As a preferred embodiment of the present invention, the dual-porosity rock physics model is constructed based on Chapman's multi-scale fracture theory and is used to characterize the changes in elastic parameters of dense sandstone containing spherical pores and microcracks under frequency variation conditions.

[0093] In this embodiment, a rock physics model is established to simulate the variation characteristics of P-wave and S-wave velocities with permeability and gas saturation.

[0094] According to Chapman's multi-scale crack theory, the expression for the stiffness matrix of the equivalent medium is:

[0095] ;

[0096] Among them, C 0 ijkl C is the stiffness coefficient of isotropic rocks. 1 ijkl C 2 ijkl and C 3 ijkl It is an additional contribution from porosity, microcracks, and fractures, ϕ p It is porosity, ε c It is the microcrack density, ε f It refers to the crack density.

[0097] Based on scanning electron microscope images of the target layer in the study area, a dual-porosity rock physical model containing spherical pores and microfractures was established. In this model, the pore space does not contain large-scale fractures, and the fracture term ε in the formula is... f It is zero. The expression for the stiffness matrix of the equivalent medium can be further expressed as:

[0098] ;

[0099] According to the theory proposed by Chapman et al. (2002), the relaxation time τ determines the frequency range in which seismic dispersion and attenuation occur:

[0100] ;

[0101] Where μ is the shear modulus, τ is the relaxation time, υ is Poisson's ratio, η is the fluid viscosity, ς is the grain size, κ is the permeability, and a represents the crack radius.

[0102] Frequency-dependent P-wave and S-wave velocities can be calculated using the following formula:

[0103] ;

[0104] ;

[0105] In a preferred embodiment of the present invention, the synthetic seismic record is obtained by calculating the reflection coefficient frequency-by-frequency using the propagation matrix method and combining it with the source wavelet spectrum via inverse Fourier transform.

[0106] In this embodiment, the frequency-varying elastic modulus calculated by the rock physics model is used as the input of the seismic propagation matrix method. The frequency-varying reflection coefficient is obtained by calculating the reflection coefficient frequency by frequency using the propagation matrix. The spectrum of the reflected wave is calculated by adding the source wavelet spectrum. Finally, the time-domain reflection waveform is calculated by inverse Fourier transform.

[0107] In a preferred embodiment of the present invention, the bulk modulus dispersion property and the shear modulus dispersion property are extracted from pre-stack seismic data through frequency-varying AVO inversion.

[0108] Figure 2 and Figure 3 To calculate the dispersion curves of P-wave velocity and S-wave velocity based on the rock physics model, the results show that increased permeability shifts the dispersion band to higher frequencies, but has little effect on velocity amplitude. Increased gas saturation also causes the frequency band to shift to higher frequencies, while causing a decrease in both P-wave and S-wave velocities.

[0109] Figure 4 A three-layer geological and geophysical model was used. When calculating the synthetic seismic record based on the model, the thickness of the tight sandstone layer was set to 10 meters, a Ricker wavelet with a dominant frequency of 40 Hz was used, and the maximum incident angle was 30°. This method can effectively simulate the seismic response of tight sandstone under varying permeability and gas saturation.

[0110] Figure 5 (a) to Figure 5 (c) shows the AVO response with varying permeability (0.1, 1, and 5 mD) and a gas saturation of 0.7. The seismic reflection signals from the tight sandstone reservoir are mainly concentrated between 95 ms and 100 ms, corresponding to the top and bottom interfaces of the tight sandstone reservoir. The results show that the seismic reflection amplitude gradually decreases with increasing incident angle, especially at lower permeability. Figure 5 (d) and Figure 5 (e) shows the variation characteristics of dispersion properties; as permeability increases, D K Similarly, D also shows an increasing trend. μ It remains almost unchanged.

[0111] Figure 6 (a) to Figure 6 (c) and Figure 6 (e) to Figure 6 (g) shows the changes in fluid mobility with frequency and incident angle as permeability changes. M f-F and M f-In It exhibits a stronger response at higher frequencies and larger incident angles. Figure 6 (d) and Figure 6 (h) shows the fluid mobility gradient properties related to frequency and incident angle, which increase with increasing permeability.

[0112] Figure 7 (a) to Figure 7 (c) shows the AVO response at gas saturations of 0.3, 0.5, and 0.7, with a permeability of 1 mD. As gas saturation increases, the reflection amplitude decreases significantly at high incident angles. Figure 7 (d) to Figure 7 (e) represents the dispersion property of the elastic modulus D under different gas saturation conditions. K and D μ Change curve. As gas saturation increases, D K Gradually increasing, while D μ It remains essentially unchanged when the gas saturation changes.

[0113] Figure 8 (a) to Figure 8 (c) and Figure 8 (e) to Figure 8 (g) shows the changes in fluid mobility with frequency and incident angle as gas saturation changes. As gas saturation increases, M... f-F M f-In and sex D Mf All showed an increasing trend, with D being the most significant. Mf The changes were the most significant.

[0114] Figure 9 The calculated fluid mobility gradient attribute D when permeability and gas saturation vary simultaneously. Mf It can be observed that, with changes in permeability and gas saturation, D... Mf All showed significant changes, increasing with increasing permeability, porosity, and gas saturation, indicating that D... Mf It is also affected by permeability and gas saturation.

[0115] Figure 10 The image shows a post-stack seismic profile of five wells, with the two black curves representing the top and bottom interfaces of the target tight reservoir.

[0116] Figure 11The calculated fluid mobility gradient attribute D Mf The cross-sectional view, overlaid with the corresponding S g The ×κ logging curve is used to verify the accuracy of the inversion results. It can be observed that D... Mf The high-value anomalies are highly consistent with the high-gas-bearing and high-permeability areas of wells B, C, and D, while the anomaly values ​​of dry wells A and E are lower, and D... Mf The calculation results are in high agreement with the well interpretation results, which proves the applicability of the inversion method.

[0117] This invention also provides a system for predicting the fluid mobility gradient properties of tight sandstone gas reservoirs, the system comprising:

[0118] The fluid mobility gradient attribute construction module is used to construct a reflection coefficient expression containing a fluid mobility term based on the earthquake frequency-varying reflection theory, and derive a formula for calculating fluid mobility using dispersion attributes. Based on the fluid mobility calculation formula, a fluid mobility gradient attribute related to frequency and earthquake wave incident angle is constructed.

[0119] The simulation module is used to establish a dual-porosity rock physics model to simulate the dispersion characteristics of P-wave and S-wave velocities under different permeability and gas saturation conditions.

[0120] The inversion module is used to generate a synthetic seismic record based on the P-wave and S-wave velocities and in combination with the propagation matrix theory, and to apply frequency-varying AVO inversion to the synthetic seismic record to extract the bulk modulus dispersion attribute and the shear modulus dispersion attribute.

[0121] The fluid mobility gradient attribute calculation module is used to calculate the fluid mobility as a function of frequency and incident angle based on the fluid mobility calculation formula and dispersion attribute, and to calculate the fluid mobility gradient attribute based on the gradient attribute calculation formula and fluid mobility.

[0122] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predicting the fluid mobility gradient property of tight sandstone gas reservoirs, characterized in that, The method includes: Based on the earthquake frequency-varying reflection theory, an expression for the reflection coefficient containing the fluid mobility term is constructed, and a formula for calculating fluid mobility using the dispersion property is derived. Based on the fluid mobility calculation formula, a fluid mobility gradient property related to frequency and seismic wave incident angle is constructed. A dual-porosity rock physics model was established to simulate the dispersion characteristics of P-wave and S-wave velocities under different permeability and gas saturation conditions. Based on the P-wave and S-wave velocities, and combined with the propagation matrix theory, a synthetic seismic record is generated. Frequency-varying AVO inversion is applied to the synthetic seismic record to extract the bulk modulus dispersion attribute and the shear modulus dispersion attribute. Based on the fluid mobility calculation formula and dispersion properties, the fluid mobility that varies with frequency and incident angle is calculated. Based on the gradient property calculation formula and fluid mobility, the fluid mobility gradient property is calculated.

2. The method for predicting the fluid mobility gradient property of tight sandstone gas reservoirs according to claim 1, characterized in that, The formula for calculating the fluid mobility is: ； 、 ； Where K is the bulk modulus, µ is the shear modulus, A(θ) is the weighting coefficient of the bulk modulus term, B(θ) is the weighting coefficient of the shear modulus term, ω is the frequency, θ is the angle of incidence, and D... K For the bulk modulus dispersion property, D µ This refers to the dispersion property of the shear modulus.

3. The method for predicting the fluid mobility gradient attribute of tight sandstone gas reservoirs according to claim 2, characterized in that, The fluid mobility gradient attribute includes the frequency gradient attribute D. Mf-F , incident angle gradient property D Mf-In And the comprehensive gradient attribute D Mf The calculation formulas are as follows: ； ； ； in, ω H and ω L They represent high frequency and low frequency, respectively. M f ( ω H )and M f ( ω L θ represents the fluid mobility corresponding to these frequencies. H and θ L Corresponding to large and small incident angles, the corresponding flow rates are respectively M f (θ H )and M f (θ L ).

4. The method for predicting the fluid mobility gradient property of tight sandstone gas reservoirs according to claim 1, characterized in that, The dual-porosity rock physics model is constructed based on Chapman's multi-scale fracture theory and is used to characterize the changes in elastic parameters of dense sandstone containing spherical pores and microcracks under frequency-dependent conditions.

5. The method for predicting the fluid mobility gradient property of tight sandstone gas reservoirs according to claim 1, characterized in that, The synthetic seismic record is obtained by calculating the reflection coefficient frequency-by-frequency using the propagation matrix method and combining it with the source wavelet spectrum via inverse Fourier transform.

6. The method for predicting the fluid mobility gradient property of tight sandstone gas reservoirs according to claim 1, characterized in that, The bulk modulus dispersion property and shear modulus dispersion property are extracted from pre-stack seismic data through frequency-varying AVO inversion.

7. A system for predicting the fluid mobility gradient properties of tight sandstone gas reservoirs, used to implement the method for predicting the fluid mobility gradient properties of tight sandstone gas reservoirs as described in any one of claims 1-6, characterized in that, The system includes: The fluid mobility gradient attribute construction module is used to construct a reflection coefficient expression containing a fluid mobility term based on the earthquake frequency-varying reflection theory, and derive a formula for calculating fluid mobility using dispersion attributes. Based on the fluid mobility calculation formula, a fluid mobility gradient attribute related to frequency and earthquake wave incident angle is constructed. The simulation module is used to establish a dual-porosity rock physics model to simulate the dispersion characteristics of P-wave and S-wave velocities under different permeability and gas saturation conditions. The inversion module is used to generate a synthetic seismic record based on the P-wave and S-wave velocities and in combination with the propagation matrix theory, and to apply frequency-varying AVO inversion to the synthetic seismic record to extract the bulk modulus dispersion attribute and the shear modulus dispersion attribute. The fluid mobility gradient attribute calculation module is used to calculate the fluid mobility as a function of frequency and incident angle based on the fluid mobility calculation formula and dispersion attribute, and to calculate the fluid mobility gradient attribute based on the gradient attribute calculation formula and fluid mobility.

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