A method for quantitatively predicting pre-stack seismic of inclined fractures

Abstract

The present invention provides a pre-stack seismic quantitative prediction method for inclined fractures, comprising the following steps: Step 1, obtain a seismic data volume, a velocity volume, a structural interpretation horizon, and geological and logging data describing the fracture development characteristics; Step 2, convert the seismic data volume into an azimuthal gather data volume by using the velocity volume, and clarify the incident angle range of the corresponding observation system; Step 3, use the azimuthal gather data volume obtained in Step 2 to perform inversion solution on the azimuthal AVO expression of HTI media to obtain at least two intensity parameters of high-angle fractures, and use the functional relationship of at least two intensity parameters to characterize the anisotropic parameters of the inclined fracture development intensity. The optimized anisotropic parameter B<subgt;2< / subgt;(θ) of the present invention corrects the disadvantages of the Fourier coefficient r<subgt;2< / subgt;(θ). Under different incident angles, the variation relationship between B<subgt;2< / subgt;(θ) and δ<subgt;N< / subgt;, δ<subgt;T< / subgt; is more reasonable, which can improve the prediction accuracy of the inclined fracture development intensity. At the same time, B<subgt;2< / subgt;(θ) increases the proportion of the normal weakness δ<subgt;N< / subgt;, and the characterization of the gas-bearing property of fractures is also more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic exploration, and particularly relates to a pre-stack seismic quantitative prediction method for inclined fractures. Background Art

[0002] With the gradual deepening of exploration and development, the exploration environment we face has changed from simple and thick-layered visible oil and gas reservoirs to complex and hidden ones. Tight, thin, and unconventional reservoirs are the main types currently faced. For these oil and gas reservoirs, fractures are not only one of the key factors for migration channels and reservoir formation, but also often the main storage space, forming fractured reservoirs or pore-fracture composite reservoirs. Therefore, fracture prediction has become an important link in the exploration and development of complex oil and gas reservoirs. However, the uneven development scale, strong distribution heterogeneity, complex distribution law of fractures, and the resolution and multi-solution nature of seismic data have become important factors restricting the accuracy of seismic methods for identifying and describing fractures. Therefore, using seismic data for fracture prediction is still a problem that needs to be deeply solved.

[0003] Fracture seismic prediction methods are divided into post-stack prediction and pre-stack prediction according to the type of seismic data stacking. Post-stack prediction methods mainly rely on structural attributes and use the discontinuity of seismic wave fields caused by fracture development to qualitatively describe the development intensity of fractures. These methods mainly detect large-scale fractures and faults above the meter level. Pre-stack prediction methods mainly target micro-scale fracture zones and use the anisotropic properties caused by fractures to obtain quantitative results on the development intensity and azimuth of fracture zones. The research object of micro-scale fracture zones and the quantitative prediction results make pre-stack prediction methods inevitable. Moreover, with the enhancement of computing and storage capabilities and the improvement of acquisition and processing technologies, wide-azimuth data has been widely used, and the accuracy and applicability of pre-stack fracture prediction methods are also gradually improving.

[0004] Currently, pre-stack fracture prediction methods all target HTI media, that is, high-angle fractures, and use azimuthal anisotropic information such as amplitude, velocity, and frequency caused by high-angle fracture zones to quantitatively predict micro-scale fracture zones. However, there are still a large number of low-angle oblique fractures in actual exploration and development. How to consider the influence of inclined fractures on azimuthal anisotropy is crucial for improving the accuracy of fracture prediction.

[0005] In this regard, a Chinese invention patent application with the publication number CN102033242A discloses a seismic amplitude prediction method for deep inclined fracture reservoirs. This method uses pre-stack seismic amplitude data to predict the seismic amplitude of deep inclined fracture reservoirs. First, forward and inverse modeling analysis of the theoretical model of inclined fracture media is carried out according to the characteristics of the target area to obtain the optimal processing and inversion parameters. Finally, reservoir fracture inversion based on the theory of inclined fracture media is performed to obtain the dip angle of the fractures and the Thomson anisotropy parameters. This method can more accurately predict the anisotropy degree of inclined fractures, but it can only obtain the dip angle of the fractures and cannot obtain the azimuth information of the fractures. Azimuth information is an important parameter in the later exploration and development design process.

[0006] In addition, the research object of the above method is fracture reservoirs, and the gas-bearing property of fractures needs to be considered. However, the influence of fracture filling conditions on the inversion anisotropy parameters is not considered in the proposed method. Moreover, the direct relationship between the parameters used to characterize the fracture development intensity and the fracture filling conditions has not been systematically demonstrated in current methods. How to consider the influence of fracture filling conditions on azimuthal anisotropy and whether information about fracture filling conditions, such as gas-bearing property information, can be extracted from the existing prediction results to improve the description accuracy of fractures, especially fracture reservoirs, is also a research direction that needs to be explored for fracture prediction. Summary of the Invention

[0007] The purpose of the present invention is to provide a pre-stack seismic quantitative prediction method for inclined fractures to solve the problem of poor prediction accuracy of fracture intensity in existing pre-stack fracture quantitative prediction methods.

[0008] To achieve the above purpose, the pre-stack seismic quantitative prediction method for inclined fractures in the present invention adopts the following technical solutions:

[0009] A pre-stack seismic quantitative prediction method for inclined fractures, comprising the following steps:

[0010] Step 1: Obtain the pre-stack azimuth seismic data volume, velocity volume of the work area, the structural interpretation horizons of the layer section to be studied, and the geological and logging data describing the fracture development characteristics of the layer section to be studied;

[0011] Step 2: Use the velocity volume obtained in Step 1 to convert the pre-stack azimuth seismic data volume into an azimuth angle gather data volume, and clarify the incident angle range of the observation system corresponding to this azimuth angle gather data volume;

[0012] Step 3: Use the azimuth angle gather data volume obtained in Step 2 to process the azimuth AVO expression of HTI media in one of the following ways:

[0013] Method 1: Invert and solve the azimuth AVO expression of the HTI medium to obtain at least two intensity parameters of high-angle fractures, and use the functional relationship of at least two intensity parameters to characterize the anisotropic parameter of the inclined fracture development intensity;

[0014] Method 2: First, convert the Fourier expansion of the azimuth AVO expression of the HTI medium into a new expansion containing sin 2 terms, and then use the azimuth angle gather data volume obtained in step 2 to invert and solve the new expansion to obtain the coefficient of the sin 2 term, and this coefficient is the anisotropic parameter used to characterize the inclined fracture development intensity.

[0015] The beneficial effects of the above technical solutions are as follows: The present invention uses the azimuth angle gather data volume and selects a method to process the azimuth AVO expression of the HTI medium. Method 1 is to invert and solve the azimuth AVO expression of the HTI medium to obtain at least two intensity parameters of high-angle fractures, and use the functional relationship of at least two intensity parameters to characterize the anisotropic parameter of the inclined fracture development intensity. Because in the prior art, only one intensity parameter obtained by inversion and solution is selected to characterize the high-angle fracture development intensity, while the present invention uses the functional relationship of at least two intensity parameters of high-angle fractures to characterize the anisotropic parameter of the inclined fracture development intensity, fully exploiting the information carried by the existing parameters, and the relationship between the fracture development intensity and the incident angle in the data volume is more reasonable. Therefore, the prediction accuracy of the inclined fracture development intensity can be improved.

[0016] Method 2 is to first convert the Fourier expansion of the azimuth AVO expression of the HTI medium into a new expansion containing sin 2 terms, and then use the azimuth angle gather data volume obtained in step 2 to invert and solve the new expansion to obtain the coefficient of the sin 2 term, and this coefficient is the anisotropic parameter used to characterize the inclined fracture development intensity. Because in the prior art, the Fourier expansion of the azimuth AVO expression of the HTI medium is a cosine function, and the coefficient of the cosine term is used to characterize the parameter of the high-angle fracture development intensity. In the process of converting it into a new expansion containing sin 2 terms, more parameters are integrated. Therefore, the data volume obtained by solving the new expression contains richer information and can improve the prediction accuracy of the inclined fracture development intensity.

[0017] Further, when using Method 1 to process the azimuth AVO expression of the HTI medium, invert and solve the Fourier expansion of the azimuth AVO expression of the HTI medium. The Fourier expansion of the azimuth AVO expression of the HTI medium is:

[0018]

[0019] Among them, is the PP-wave reflection coefficient, r0(θ) is the conventional AVO analysis coefficient, r2(θ) and r4(θ) are the AVAZ analysis coefficients, which are called Fourier coefficients, θ is the ray incidence angle, φ is the ray azimuth angle, φ sym is the azimuth angle perpendicular to the fracture strike, δ N is the normal weakness of the fracture, δ T is the tangential weakness of the fracture, g = v S 2 / v p 2 , v p and v S are the longitudinal and transverse wave velocities respectively; Δ represents the difference in the properties of the upper and lower two layers of media;

[0020] During the inversion solution, different incidence angle intervals are selected from the incidence angle range obtained in step two to obtain different inversion results. By comparing the geological and logging data describing the fracture development characteristics of the layer to be studied obtained in step one, the final incidence angle interval is determined, and the inversion results r0(θ), r2(θ), r4(θ) and φ sym are obtained, where r2(θ) and r4(θ) are the two strength parameters of the high-angle fractures to be obtained.

[0021] Furthermore, a linear transformation is performed on the two strength parameters obtained by the solution to obtain the relationship between the anisotropic parameter B2(θ) characterizing the development intensity of inclined fractures and r2(θ) and r4(θ):

[0022] B2(θ) = 2(r2(θ) + 4r4(θ)) (4).

[0023] Furthermore, the derivation process of the relationship formula (4) is as follows:

[0024] Using

[0025] r4(θ) = 1 / 8g(Δδ T - gΔδ N )tan 2 θsin 2 θ (3),

[0026] Substitute expression (2) and expression (3) into expression (1), and rewrite the reflection coefficient expression (1) represented by the azimuth cosine function into the expression form of the azimuth sine function:

[0027]

[0028] Among them, sin 2The coefficient B2(θ) of the term is the anisotropic parameter used to characterize the development intensity of inclined fractures, and we get:

[0029] B2(θ)=gtan 2 θΔδ T -gsin 2 θ(1 - 2g + tan 2 θ)Δδ N (6).

[0030] Regarding r2(θ), r4(θ) and δ in expressions (2) and (3) N 、δ T as unknown variables, solving the linear equations, we obtain the expressions of δ N 、δ T expressed in terms of r2(θ) and r4(θ):

[0031] Δδ N =p1r2(θ) - p2r4(θ) (7),

[0032] Δδ T =p3r2(θ) - p4r4(θ) (8),

[0033] where

[0034]

[0035] Substituting expressions (7) and (8) into expression (6), we can obtain the relationship (4) between B2(θ) and r2(θ), r4(θ).

[0036] Furthermore, for the convenience of prediction, in step two, before converting the prestack azimuth seismic data volume into the azimuth angle gather data volume, first, based on the prestack azimuth seismic data volume obtained in step one, through header analysis, determine the offset range involved in fracture prediction.

[0037] Furthermore, in order to optimize the data and improve the prediction accuracy, within the determined offset range involved in fracture prediction, perform gather flattening on the obtained prestack azimuth seismic data volume to eliminate the remaining normal moveout error, obtain the prestack azimuth seismic data volume after gather flattening, and then convert the prestack azimuth seismic data volume after gather flattening into the azimuth angle gather data volume.

[0038] Furthermore, in step one, select the research layer section with low - angle inclined fractures developed as the layer section to be studied.

[0039] Furthermore, according to the obtained velocity volume type, the velocity volume in step one is the stacking velocity volume. Description of the Drawings

[0040] Figure 1 This is the flow chart of the pre-stack seismic quantitative prediction method for inclined fractures in the present invention;

[0041] Figure 2 It is the relationship curve of the optimized anisotropic parameter B2(θ) and the fracture normal weakness δ N 、the fracture tangential weakness δ T ;

[0042] Figure 3 It is the relationship curve of the inverted r2(θ) fracture normal weakness δ N 、the fracture tangential weakness δ T ;

[0043] Figure 4 It is the profile of the optimized anisotropic parameter B2(θ) of Well 1;

[0044] Figure 5 It is the profile of the inverted r2(θ) of Well 1;

[0045] Figure 6 It is the profile of the optimized anisotropic parameter B2(θ) of Well 2;

[0046] Figure 7 It is the profile of the inverted r2(θ) of Well 2. Detailed implementation manners

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, 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 only used to explain the present invention and are not used to limit the present invention, that is, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Usually, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0048] Therefore, the detailed description of the embodiments of the present invention provided in the drawings below is not intended to limit the scope of the claimed present invention, but merely represents the selected embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0049] It should be noted that relative terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0050] The features and performance of the present invention will be further described in detail below in conjunction with embodiments.

[0051] An embodiment of the pre-stack seismic quantitative prediction method for inclined fractures in the present invention: Select the Xujiahe Formation in a certain work area of the Sichuan Basin as the target research interval. Low-angle inclined fractures are developed in this research interval, and fractures are also one of the reservoir spaces. As Figure 1 shown, the pre-stack seismic quantitative prediction method for inclined fractures specifically includes the following steps:

[0052] Step 1: Obtain the pre-stack azimuth seismic data volume, velocity volume, structural interpretation horizons of the Xujiahe Formation, and geological and logging data describing the fracture development characteristics of the Xujiahe Formation, where the velocity volume is the stacking velocity volume;

[0053] Step 2: First, based on the obtained pre-stack azimuth seismic data volume, through header analysis, determine that the offset range for fracture prediction is [200, 3000], with the offset unit being meters; then, for the obtained pre-stack azimuth seismic data volume, within the determined offset range [200, 3000] for fracture prediction, use the cross-correlation method to flatten the gather, eliminate the residual normal moveout error, and obtain the pre-stack azimuth seismic data volume after gather flattening; finally, use the velocity volume obtained in Step 1 to convert the pre-stack azimuth seismic data volume after gather flattening into an azimuth angle gather data volume, and based on the distribution of angles in the azimuth angle gather data volume, determine the incident angle range of the corresponding acquisition system of this azimuth angle gather data volume, that is, the angle range for fracture prediction is [6, 30];

[0054] Step 3: Use the azimuth angle gather data volume obtained in Step 2 to process the azimuth AVO expression for HTI media according to the following Method 1: Invert and solve the azimuth AVO expression for HTI media to obtain at least two strength parameters of high-angle fractures, and use the functional relationship of at least two strength parameters to characterize the anisotropic parameters of the inclined fracture development intensity.

[0055] Specifically, in this embodiment, an inversion solution is performed on the Fourier expansion of the azimuthal AVO expression of the HTI medium. The Fourier expansion of the azimuthal AVO expression of the HTI medium is given by Downton (2011):

[0056]

[0057] Among them, is the PP-wave reflection coefficient, r0(θ) is the conventional AVO analysis coefficient, r2(θ) and r4(θ) are the AVAZ analysis coefficients, which are called Fourier coefficients, θ is the ray incidence angle, φ is the ray azimuth angle, φ sym is the azimuth angle perpendicular to the fracture strike, δ N is the fracture normal weakness, δ T is the fracture tangential weakness, g = v S 2 / v p 2 , v p and v S are the longitudinal and transverse wave velocities respectively, and Δ represents the difference in the properties of the upper and lower two layers of media;

[0058] The least-squares linear inversion method is used to solve the expression (1). Different incidence angle intervals are selected from the incidence angle range [6, 30] obtained in step two to obtain different inversion results. By comparing the geological and logging data describing the fracture development characteristics of the Xujiahe Formation obtained in step one, the final incidence angle interval is determined to be [15, 30], and the inversion results r0(θ), r2(θ), r4(θ) and φ sym are obtained. Among them, r2(θ) and r4(θ) are the two strength parameters of the high-angle fractures to be obtained, and r2(θ) is the parameter used by the Fourier series method to characterize the development strength of high-angle fractures, φ sym is the parameter used by the Fourier series method to characterize the azimuth of high-angle fractures. At the same time, in the present invention, φ sym is also used as the parameter to characterize the azimuth of inclined fractures, thereby obtaining the azimuth information of the inclined fractures.

[0059] Then, a linear transformation is performed on the two strength parameters r2(θ) and r4(θ) obtained by the solution, that is, parameter optimization is performed, and the relationship between the anisotropic parameter B2(θ) used to characterize the development strength of inclined fractures and r2(θ) and r4(θ) is obtained:

[0060] B2(θ) = 2(r2(θ) + 4r4(θ)) (4).

[0061] Among them, the derivation process of the relationship (4) is as follows:

[0062] Using the equations given by Downton (2011):

[0063] r4(θ)=1 / 8g(Δδ T -gΔδ N )tan 2 θsin 2 θ (3),

[0064] Inspired by the form of the approximate expression of the PP-wave reflection coefficient proposed by Rüger in 1998, substituting expressions (2) and (3) into expression (1), the expression of the reflection coefficient represented by the azimuth cosine function in expression (1) is rewritten into the form of an expression with the azimuth sine function:

[0065]

[0066] where the coefficient B2(θ) of the sin 2 term is the anisotropic parameter used to characterize the development intensity of inclined fractures, and we get:

[0067] B2(θ)=gtan 2 θΔδ T -gsin 2 θ(1 - 2g + tan 2 θ)Δδ N (6)

[0068] Regarding r2(θ), r4(θ) and δ N , δ T in expressions (2) and (3) as unknown variables, solving the linear equations, we obtain the expressions of δ N , δ T represented by r2(θ) and r4(θ):

[0069] Δδ N =p1r2(θ)-p2r4(θ) (7)

[0070] Δδ T =p3r2(θ)-p4r4(θ) (8)

[0071] where,

[0072] Substituting expressions (7) and (8) into expression (6), we can obtain the relationship (4) between B2(θ) and r2(θ), r4(θ).

[0073] In summary, the present invention uses the Fourier expansion of the azimuthal AVO expression for fracture development intensity and azimuth inversion. This method can calculate the Fourier coefficients using a limited offset or incidence angle range, and the prediction accuracy of the Fourier coefficients gradually improves as the incidence angle increases. This method reduces the requirements for data acquisition and can better demonstrate this advantage in the case of near-offset undersampling.

[0074] In the prior art, only one parameter r2(θ) obtained by inversion and solution is selected to characterize the high-angle fracture development intensity. The present invention optimizes the parameter r2(θ) obtained by the Fourier series method for characterizing fracture development intensity, improving the adaptability to the gas-bearing property of inclined fractures. The reason is that: starting from the fracture normal weakness and fracture tangential weakness, the present invention analyzes the relationship between the inversion parameter r2(θ) and the fracture filling situation at different ray incidence angles. The fracture normal weakness and fracture tangential weakness are two direct parameters reflecting fracture development characteristics and are proportional to the fracture density. Among them, the normal weakness δ N is mainly affected by the filling situation; the tangential weakness δ T reflects the anisotropy intensity of the fracture itself, is not affected by the change of fracture filling fluid, and when the fracture is mineral-filled, the tangential weakness is extremely low. Using expression (2) to test the variation relationship between r2(θ) and δ N 、δ T at different incidence angles θ, it is found that when both the fracture dip normal weakness and tangential weakness are not zero, r2(θ) will also show a value of 0, which is interpreted as the anisotropy intensity being zero and the fracture not developing, inconsistent with the actual situation. Therefore, inspired by the expression form of the PP-wave reflection coefficient approximation proposed by Rüger in 1998, the present invention substitutes expressions (2) and (3) into expression (1) to obtain expression (5), and defines the coefficient of the sin 2 term in expression (5) as a new anisotropy parameter for characterizing fracture development intensity, obtaining expression (6) for the new anisotropy parameter B2(θ) for characterizing fracture development intensity. Then, substituting expressions (7) and (8) obtained by solving the linear equations from expressions (2) and (3) into expression (6), the relationship formula (4) between B2(θ) and r2(θ), r4(θ) can be obtained.

[0075] The optimized anisotropy parameter B2(θ) is expressed by the functional relationship formula of the strength parameters r2(θ) and r4(θ) of two high-angle fractures, correcting the drawbacks of the Fourier coefficient r2(θ). At different incidence angles, the variation relationship between B2(θ) and δ N 、δ T is more reasonable. An inclined fracture can be regarded as the rotation of a high-angle fracture about the symmetry axis in the incidence angle direction. Then, in the case of an inclined fracture, the variation relationship between B2(θ) and δ N 、δ TThe variation relationship can be made consistent with the high-angle fracture situation by changing a certain incident angle. Therefore, the optimized anisotropic parameter B2(θ) of the present invention can improve the prediction accuracy of the development intensity of inclined fractures. At the same time, B2(θ) increases the proportion of the normal weakness δ N , and the description of the gas-bearing property of fractures is also more accurate.

[0076] For example Figure 2 and Figure 3 As shown, the optimized anisotropic parameter B2(θ) and the inversion r2(θ) are respectively given under the condition of an incident angle of 25°. The curves of their variations with the normal weakness δ N of fractures and the tangential weakness δ T of fractures can be found. It can be seen that when both the normal weakness and the tangential weakness are not zero, the optimized anisotropic parameter B2(θ) of the present invention is not zero, indicating a certain fracture development intensity, while the inversion r2(θ) will show a value of 0, which is interpreted as the fracture development intensity being zero. The comparison proves that the optimized anisotropic parameter given by the present invention is more in line with the actual situation.

[0077] Another example is through Figure 4 and Figure 5 Comparison: Select Well 1 with inclined fractures developed in the Xujiahe Formation. The profiles of the optimized anisotropic parameter B2(θ) and the inversion r2(θ) are respectively plotted. The black diagonal line below the well name is the well trajectory. The curve on the right side of the well trajectory is the depth section interpreted as gas-bearing by logging, and the black square on the left side is the depth section identification of the fractured gas reservoir interpreted by well testing. The background map is the parameter characterizing the fracture development intensity. The color from white to black indicates that the fracture development intensity increases from weak to strong and the gas-bearing property is better. The well testing interpretation result on the left shows that there are two depth sections as fractured gas reservoirs. Figure 4 In the profile of the optimized anisotropic parameter B2(θ), these two depth sections correspond to relatively dark colors, indicating that the prediction result is that inclined fractures develop and the gas-bearing property is good, which is consistent with the well testing result. At the same time, the logging interpretation on the right also shows that the two fractured gas reservoir sections in the Xujiahe Formation have good gas-bearing properties, indicating that the prediction result of the optimized anisotropic parameter is consistent with the actual drilling result, proving that the method of the present invention has high accuracy in predicting the gas-bearing property of inclined fractures. While Figure 5 in the profile of the inversion r2(θ), both depth sections of the fractured gas reservoirs correspond to white, indicating that the prediction result is that fractures do not develop, which is inconsistent with the well testing result. The comparison proves that the pre-stack seismic quantitative prediction method proposed by the present invention has stronger adaptability to the gas-bearing property detection of inclined fractures compared with the original method.

[0078] Another example is through Figure 6 and Figure 7Comparison: Select Well 2 in the Xujiahe Formation where gas testing and coring are carried out. The cored section shows the development of oblique joints. Draw the optimized anisotropic parameter B2(θ) and the inversion r2(θ) profile respectively. The black diagonal line below the well name is the well trajectory. The curve on the right side of the well trajectory is the core statistical fracture density curve. The black square on the left side is the depth section interpreted by logging as gas-bearing. The background map is the parameter characterizing the fracture development intensity. The color from white to black indicates that the fracture development intensity changes from weak to strong, and the gas-bearing property is better. The core statistical fracture density curve on the right side of the well trajectory shows that Well 2 has an oblique joint development depth section. The corresponding logging interpretation result on the left side is a fractured gas reservoir, indicating that the gas-bearing property of this inclined fracture development section is better. Figure 6 In the optimized anisotropic parameter B2(θ) profile, this depth section corresponds to a darker color, and the prediction result is consistent with the lithology and logging data. And Figure 7 In the inversion r2(θ) profile, this depth section corresponds to white, indicating that the predicted result shows no fracture development, which is inconsistent with the actual drilling result. The comparison proves that the optimized anisotropic parameter proposed by the present invention is more accurate in predicting the gas-bearing property of inclined fractures.

[0079] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, more wells can also be selected for the comparison of the optimized anisotropic parameter B2(θ) and the inversion r2(θ) profile.

[0080] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, other intervals outside the Xujiahe Formation can be selected as the intervals to be studied.

[0081] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, when drawing the variation curves of the optimized anisotropic parameter B2(θ) and the inversion r2(θ) with the fracture normal weakness δ N and the fracture tangential weakness δ T other incident angles can also be selected.

[0082] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, the angle range involved in fracture prediction specified in Step 2 and the incident angle interval finally determined in Step 3 can both be adjusted according to the actual situation.

[0083] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, the velocity volume in Step 1 can also be the root-mean-square velocity or the layer velocity.

[0084] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, the offset range involved in fracture prediction determined in Step 2 can be other ranges, and the method of flattening the gather can also be other methods.

[0085] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, it is also possible not to perform header analysis and gather flattening, but directly use the velocity volume obtained in Step 1 to convert the pre-stack azimuth seismic data volume into an azimuth angle gather data volume.

[0086] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, the functional relationships of the two intensity parameters r2(θ) and r4(θ) may not be linear, but other types of relationships.

[0087] In other embodiments of the pre-stack seismic quantitative prediction method for inclined fractures, it is not necessary to first invert and solve the azimuth AVO expression of the HTI medium to obtain at least two intensity parameters of high-angle fractures, and then optimize the parameters to obtain the functional relationship of at least two intensity parameters to characterize the anisotropic parameters of the inclined fracture development intensity. Instead, the second solution is adopted: First, convert the Fourier expansion of the azimuth AVO expression of the HTI medium into a new expansion containing sin 2 terms, such as the expression (5) in the above embodiment, and then directly invert and solve the new expansion using the azimuth angle gather data volume obtained in Step 2 to obtain the coefficient of the sin 2 term. This coefficient is the anisotropic parameter used to characterize the inclined fracture development intensity, that is, the second solution is to convert first and then directly solve, and the first solution is to solve first and then perform conversion and optimization.

[0088] The above is only the preferred embodiment of the present invention and is not intended to limit the present invention. The patent protection scope of the present invention is subject to the claims. Any equivalent structural changes made by using the description and drawings of the present invention should be included in the protection scope of the present invention by the same token.

Claims

1. A pre-stack seismic quantitative prediction method for inclined fractures, characterized in that, It includes the following steps: Step 1: Obtain the pre-stack azimuth seismic data volume, velocity volume of the work area, structural interpretation horizons of the layer section to be studied, and geological and logging data describing the fracture development characteristics of the layer section to be studied; Step 2: Use the velocity volume obtained in Step 1 to convert the pre-stack azimuth seismic data volume into an azimuth angle gather data volume, and determine the incident angle range of the observation system corresponding to this azimuth angle gather data volume; Step 3: Use the azimuth angle gather data volume obtained in Step 2 to process the azimuth AVO expression of the HTI medium in one of the following ways: Method 1: Invert and solve the azimuth AVO expression of the HTI medium to obtain at least two intensity parameters of high-angle fractures, and use the functional relationship of at least two intensity parameters to characterize the anisotropic parameters of the inclined fracture development intensity; Method 2: First, convert the Fourier expansion of the azimuthal AVO expression of the HTI medium into a formula containing sin 2 The new expansion of the term is then inverted and solved using the azimuth gather data obtained in step 2 to obtain sin 2 The coefficient of the term is the anisotropic parameter used to characterize the intensity of inclined crack development.

2. The pre-stack seismic quantitative prediction method for inclined fractures according to claim 1, wherein When using Method 1 to process the azimuth AVO expression of the HTI medium, invert and solve the Fourier expansion of the azimuth AVO expression of the HTI medium. The Fourier expansion of the azimuth AVO expression of the HTI medium is: Among them, is the PP-wave reflection coefficient, r0(θ) is the conventional AVO analysis coefficient, r2(θ) and r4(θ) are the AVAZ analysis coefficients, called Fourier coefficients, θ is the ray incident angle, φ is the ray azimuth angle, φ sym is the vertical fracture strike azimuth angle, δ N is the fracture normal weakness, δ T is the fracture tangential weakness, g = v s 2 / v p 2 , v p and v s are the P-wave and S-wave velocities respectively; Δ represents the difference in properties between the upper and lower two layers of media; During the inversion solution, different incident angle intervals are selected from the incident angle range obtained in Step 2 to obtain different inversion results. By comparing the geological and logging data describing the fracture development characteristics of the layer section to be studied obtained in Step 1, the final incident angle interval is determined, and the inversion results r0(θ), r2(θ), r4(θ) and φ are obtained. sym Among them, r2(θ) and r4(θ) are the two strength parameters of the high-angle fractures to be obtained.

3. The pre-stack seismic quantitative prediction method for inclined fractures according to claim 2, wherein, Perform a linear transformation on the two intensity parameters obtained by solving to obtain the relationship between the anisotropic parameters B2(θ), r2(θ), and r4(θ) used to characterize the inclined fracture development intensity: B2(θ) = 2(r2(θ) + 4r4(θ)) (4).

4. The pre-stack seismic quantitative prediction method for inclined fractures according to claim 3, wherein, The derivation process of formula (4) is: Utilize r4(θ) = 1 / 8g(Δδ T - gΔδ N )tan 2 θsin 2 θ (3), Substitute formula (2) and formula (3) into formula (1), and rewrite the reflection coefficient formula (1) expressed by the azimuth cosine function into the form of an expression of the azimuth sine function: where sin 2 The coefficient B2(θ) of the term is the anisotropic parameter used to characterize the development intensity of inclined cracks, and we get: B2(θ) = gtan 2 θΔδ T -gsin 2 θ(1 - 2g + tan 2 θ)Δδ N (6), Regarding \(r_2(\theta)\), \(r_4(\theta)\) and \(\delta\) in Expression (2) and Expression (3) as unknown variables, solve the system of linear equations to obtain the expressions of \(\delta\) represented by \(r_2(\theta)\) and \(r_4(\theta)\): N \(\delta\) T Regarding \(r_2(\theta)\), \(r_4(\theta)\) and \(\delta\) as unknown variables, solve the system of linear equations to obtain the expressions of \(\delta\) represented by \(r_2(\theta)\) and \(r_4(\theta)\): N \(\delta\) T The expressions of: Δδ N = p1r2(θ) - p2r4(θ) (7), Δδ T = p3r2(θ) - p4r4(θ) (8), Among them Substitute formula (7) and formula (8) into formula (6), and the relationship formula (4) of B2(θ), r2(θ), and r4(θ) can be obtained.

5. The pre-stack seismic quantitative prediction method for inclined fractures according to any one of claims 1 to 4, characterized in that In Step 2, before converting the pre-stack azimuth seismic data volume into an azimuth angle gather data volume, first determine the offset range participating in fracture prediction through header analysis according to the pre-stack azimuth seismic data volume obtained in Step 1.

6. The pre-stack seismic quantitative prediction method for inclined fractures according to claim 5, characterized in that Perform gather flattening on the obtained pre-stack azimuth seismic data volume within the determined offset range participating in fracture prediction to eliminate the residual normal moveout error, obtain the pre-stack azimuth seismic data volume after gather flattening, and then convert the pre-stack azimuth seismic data volume after gather flattening into an azimuth angle gather data volume.

7. The pre-stack seismic quantitative prediction method for inclined fractures according to any one of claims 1 to 4, characterized in that In Step 1, select the research layer section with low-angle inclined fractures as the layer section to be studied.

8. The pre-stack seismic quantitative prediction method for inclined fractures according to any one of claims 1 to 4, characterized in that The velocity volume in Step 1 is the stacking velocity volume.

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