Method and system for establishing low-frequency model based on multi-attribute fusion

Abstract

The invention discloses a method and a system for establishing a low-frequency model based on multi-attribute fusion. The method for establishing the low-frequency model based on the multi-attribute fusion comprises the following steps: establishing a work area longitudinal wave velocity compaction trend body; based on the longitudinal wave velocity compaction trend body and the seismic horizon velocity body, constructing a pre-stack parameter elastic very low frequency model; establishing a well interpolation model based on the three-dimensional constructive framework; and performing frequency domain merging on the pre-stack parameter elastic very-low-frequency model and the well interpolation model to obtain a multi-attribute fusion low-frequency model. According to the method, seismic velocity information, regional compaction trend information, logging information and geologic model information are fully fused to participate in establishment of the low-frequency model, the'bullseye 'phenomenon of a conventional well interpolation low-frequency model is improved, the overall rule is matched with the structure background, and the problems that well drilling distribution is not uniform, reservoir heterogeneity is high, and the reliability is high are solved. And the low-frequency model precision is not high due to fast transverse change.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration and development, and in particular relates to a method and system for establishing a low-frequency model based on multi-attribute fusion. Background Art

[0002] The bandwidth of seismic data is limited, and high-frequency and low-frequency information is missing. The lack of high-frequency information affects the resolution of thin layers, while the lack of low-frequency information makes it difficult to characterize the boundaries of reservoirs and make quantitative interpretations. Constrained sparse pulse inversion can increase the bandwidth of seismic data, but without a low-frequency model for boundary constraints, reliable absolute P- and S-wave impedances cannot be generated.

[0003] The conventional establishment of low-frequency models is mainly affected by two factors: one is the framework model established based on the structural interpretation of the horizon and fault; the other is the well logging data. The establishment of a seismic low-frequency reservoir model is to interpolate along the layer from the well logging data under the constraints of the geological framework model to obtain an overall initial parameter model. The interpolation method can be used for triangular interpolation, inverse distance weighted method, local kriging method and global kriging method. However, this model establishment method is generally only applicable to areas with relatively simple sedimentary environments and little lateral changes. Moreover, due to the interpolation algorithm, the constructed model often has "bull's eyes" in the lateral direction, which will directly affect the subsequent seismic inversion results. Summary of the invention

[0004] In view of the above problems, the present invention discloses a method for establishing a low-frequency model based on multi-attribute fusion, comprising the following steps:

[0005] Create a compaction trend body of longitudinal wave velocity in the work area;

[0006] Based on the P-wave velocity compaction trend body and the seismic layer velocity body, a prestack parametric elastic very low frequency model is constructed;

[0007] Based on the three-dimensional structural grid, a well interpolation model is established;

[0008] The pre-stack parameter elastic very low frequency model and the well interpolation model are combined in the frequency domain to obtain a multi-attribute fusion low frequency model.

[0009] Furthermore, the specific steps of creating the work area longitudinal wave velocity compaction trend body are as follows:

[0010] According to the linear relationship between the depth of the wells in the work area and the P-wave velocity, the compaction trend relationship of the P-wave velocity in the work area is determined;

[0011] Based on the longitudinal wave velocity compaction trend relationship, a longitudinal wave velocity compaction trend body of the work area is created.

[0012] Further, the specific steps for constructing the prestack parameter elastic very low frequency model based on the longitudinal wave velocity compaction trend body and the seismic layer velocity body are as follows:

[0013] Based on the longitudinal wave velocity compaction trend body and the longitudinal wave velocity of the target wells in the work area, correct the optimized layer velocity body to obtain the well-controlled layer velocity body;

[0014] Establish the linear function relationships between the longitudinal wave velocity and the longitudinal wave impedance, the longitudinal and transverse wave velocity ratio, and the density respectively;

[0015] Based on the linear function relationships, convert the well-controlled layer velocity body into the longitudinal wave impedance, the longitudinal and transverse wave velocity ratio, and the density elastic trend bodies, and obtain the prestack parameter elastic very low frequency model constructed based on the seismic layer velocity body.

[0016] Further, the specific steps for establishing the well interpolation model based on the three-dimensional structural framework are as follows:

[0017] Based on the three-dimensional structural framework and the well-controlled layer velocity body, perform well interpolation with the well-controlled layer velocity body constraint on the longitudinal wave impedance, the longitudinal and transverse wave velocity ratio, and the density curves to obtain the well interpolation model driven by the three-dimensional structural framework and the layer velocity.

[0018] Further, the frequency range of the prestack parameter elastic very low frequency model is 0 - 2 Hz.

[0019] Further, the frequency range of the well interpolation model is 2 - 8 Hz.

[0020] The present invention also discloses a system for establishing a low frequency model based on multi-attribute fusion, including:

[0021] A creation unit for creating the longitudinal wave velocity compaction trend body of the work area;

[0022] A construction unit for constructing the prestack parameter elastic very low frequency model based on the longitudinal wave velocity compaction trend body and the seismic layer velocity body;

[0023] An establishment unit for establishing the well interpolation model based on the three-dimensional structural framework;

[0024] A merging unit for merging the prestack parameter elastic very low frequency model and the well interpolation model in the frequency domain to obtain the multi-attribute fusion low frequency model.

[0025] Further, the creation unit is specifically used for:

[0026] Determine the longitudinal wave velocity compaction trend relationship in the work area according to the linear relationship between the depth of the wells in the work area and the longitudinal wave velocity;

[0027] Create the longitudinal wave velocity compaction trend body of the work area based on the longitudinal wave velocity compaction trend relationship.

[0028] Furthermore, the building unit is specifically configured to:

[0029] Based on the compressional wave velocity compaction trend body and the compressional wave velocity of the target wells in the work area, correct the optimized layer velocity body to obtain a well-controlled layer velocity body;

[0030] Establish linear functional relationships between the compressional wave velocity and the compressional wave impedance, the compressional-shear wave velocity ratio, and the density respectively;

[0031] Based on the linear functional relationships, convert the well-controlled layer velocity body into elastic trend bodies of compressional wave impedance, compressional-shear wave velocity ratio, and density, and obtain a pre-stack parameter elastic very low frequency model constructed based on the seismic layer velocity body.

[0032] Furthermore, the establishing unit is specifically configured to:

[0033] Based on the three-dimensional structural framework and the well-controlled layer velocity body, perform well-controlled layer velocity body constrained well interpolation on the compressional wave impedance, compressional-shear wave velocity ratio, and density curves to obtain a well interpolation model driven by the three-dimensional structural framework and layer velocity.

[0034] Compared with the prior art, the embodiments of the present invention have at least the following advantages: Seismic velocity information, regional compaction trend information, logging information, and geological model information can be fully integrated to participate in the establishment of a low-frequency model, improving the "bull's-eye" phenomenon of the conventional well interpolation low-frequency model. The overall pattern is consistent with the structural background, solving the problems of uneven drilling distribution, strong reservoir heterogeneity, and rapid lateral variation, which lead to low accuracy of the low-frequency model.

[0035] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures pointed out in the specification and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0037] Figure 1 Shows a flowchart of a method for establishing a low-frequency model based on multi-attribute fusion according to an embodiment of the present invention;

[0038] Figure 2 Shows a crossplot analysis diagram of the compressional wave velocity and different elastic parameters according to an embodiment of the present invention;

[0039] Figure 3 Shows a pre-stack parameter elastic very low frequency model according to an embodiment of the present invention;

[0040] Figure 4 Shows a three-dimensional structural framework and well interpolation profile according to an embodiment of the present invention;

[0041] Figure 5 Shows a longitudinal wave impedance low frequency model of a complex fault block according to an embodiment of the present invention;

[0042] Figure 6 Shows a low frequency model of the longitudinal and transverse wave velocity ratio of a complex fault block according to an embodiment of the present invention. Detailed implementation manners

[0043] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] When the wells in the study area are unevenly distributed, and the reservoir has strong heterogeneity and rapid lateral changes, using only well logging curves for interpolation is greatly affected by well control in the horizontal direction and has certain risks.

[0045] Seismic data can provide two aspects of information: amplitude information and velocity information. The seismic velocity obtained through seismic processing can reflect the change trend of sedimentation to a certain extent. Therefore, the present invention intends to adopt a compaction trend correction and combined well-interpolation method under the control of seismic velocity (0 - 2 Hz) to establish a low frequency model (0 - 8 Hz) required for sedimentary rock sequence inversion.

[0046] Figure 1 Shows a flow chart of a method for establishing a low frequency model based on multi-attribute fusion according to an embodiment of the present invention. As Figure 1 Shown, a method for establishing a low frequency model based on multi-attribute fusion proposed by the present invention includes the following steps:

[0047] Create a longitudinal wave velocity compaction trend body for the work area;

[0048] Based on the longitudinal wave velocity compaction trend body and the seismic layer velocity body, construct a pre-stack parameter elastic very low frequency model;

[0049] Based on the three-dimensional structural framework, establish a well interpolation model;

[0050] Merge the pre-stack parameter elastic very low frequency model and the well interpolation model in the frequency domain to obtain a multi-attribute fusion low frequency model.

[0051] The present invention obtains a low-frequency model by fusing information from different frequency bands in the frequency domain, thereby ensuring that the low-frequency model conforms to actual underground sedimentary characteristics as much as possible and providing good support for reservoir prediction inversion.

[0052] In some embodiments, the specific steps of creating a work area longitudinal wave velocity compaction trend body are as follows:

[0053] According to the linear relationship between the depth and P-wave velocity of typical wells in the work area, the P-wave velocity compaction trend relationship in the work area is determined; among them, typical wells are generally wells with complete data, long curves, and containing different reservoir types. The distribution position also tries to control the plane range of the work area, which can characterize the regional sedimentary trend;

[0054] Based on the P-wave velocity compaction trend relationship, a P-wave velocity compaction trend body of the work area is created, wherein all strata with compaction trends in the work area are applicable, such as monocline structural areas.

[0055] The compaction trend is an intrinsic relationship of the region, reflecting the relationship between the depth and elastic properties of the entire region. The frequency of this trend is lower, generally 0-1Hz, which is also a very low frequency.

[0056] The present invention is mainly aimed at areas where the target layer has a compaction trend, and the compaction trend can be taken into consideration and the information of seismic layer velocity can be fully utilized.

[0057] In some embodiments, the specific steps of constructing a prestack parametric elastic very low frequency model based on the P-wave velocity compaction trend body and the seismic layer velocity body are as follows:

[0058] The seismic layer velocity body (i.e., layer velocity body) of the work area is quality controlled and optimized to obtain an optimized layer velocity body; wherein, the quality control and optimization processing specifically includes outlier removal, smoothing, and high-cut processing of the layer velocity body; wherein, the high-cut processing is to remove all signals higher than the cutoff frequency of 3 Hz, and only retain valid signals below 3 Hz;

[0059] The optimized layer velocity body is corrected based on the P-wave velocity compaction trend body and the P-wave velocity of the target well (typical well) in the work area to obtain the well-controlled layer velocity body; wherein the correction process specifically includes performing a three-dimensional compaction trend analysis on the optimized layer velocity body based on the P-wave velocity compaction trend body; then extracting the layer velocity curve at the well point and the P-wave curve on the well for linear correlation analysis, and converting the optimized layer velocity body into a well-controlled layer velocity body based on the linear relationship;

[0060] Based on the rock physics laws of the work area, the linear functional relationship between the P-wave velocity and the P-wave impedance, P-wave velocity ratio and density of the region is established; among which, the rock physics laws can reflect the P-wave velocity and P-wave impedance, P-wave velocity ratio and density of the region; among which, the P-wave impedance, P-wave velocity ratio and density are curves that have been pre-corrected for single-well outliers and processed for consistency among multiple wells, and the laws among the wells are relatively consistent;

[0061] Based on the linear function relationship, the well-controlled layer velocity body is converted into P-wave impedance, P-wave velocity ratio and density elastic trend body, and the prestack parameter elastic very low frequency model constructed based on the seismic layer velocity body is obtained.

[0062] The effective frequency band information of the seismic layer velocity body is 0-2Hz, which belongs to very low frequency and can reflect the sedimentary laws of a large set of strata.

[0063] There are differences in the velocity ranges between the layer velocity body and the velocity on the well, and the layer velocity may also have a velocity reversal in a certain layer segment, which is inconsistent with the compaction trend. After correction by the P-wave velocity compaction trend body and the P-wave velocity of the target well in the work area, the layer velocity body is consistent with the velocity trend on the well and can also reflect the compaction trend.

[0064] By statistically analyzing the relationship between P-wave velocity and P-wave impedance, P-wave velocity ratio and density, the well-controlled layer velocity body (the well-controlled layer velocity body at this time is consistent with the P-wave velocity on the well) is converted into P-wave impedance, P-wave velocity ratio and density elastic trend body.

[0065] In some embodiments, the specific steps of establishing a well interpolation model based on a three-dimensional structural grid are as follows:

[0066] Reasonable selection of typical wells in the work area, based on the work area's three-dimensional structural grid and well-controlled layer velocity body, well-controlled layer velocity body constrained well interpolation is performed on the optimized P-wave impedance, P-S wave velocity ratio and density curve of the typical wells to obtain a three-dimensional structural grid and layer velocity driven well interpolation model. Among them, the three-dimensional structural grid is obtained by combining the three-dimensional seismic data body with the logging data to interpret the structural horizon.

[0067] The three-dimensional structural framework can characterize the sedimentary trend and ensure that when the well curve is interpolated, the interpolation results between well points follow the structural trend. Adding the well-controlled layer velocity body constraint can ensure that the interpolation results between well points are not simply mathematical interpolation but follow the layer velocity change trend.

[0068] The method of establishing a low-frequency model based on multi-attribute fusion of the present invention can fully integrate seismic velocity information, regional compaction trend, logging information and geological model information to participate in the establishment of the low-frequency model, improve the "bull's eye" phenomenon of the conventional well interpolation low-frequency model, and the overall law is consistent with the structural background, which solves the problem of uneven drilling distribution, strong reservoir heterogeneity, and rapid lateral changes leading to low accuracy of the low-frequency model.

[0069] In some embodiments, the frequency range of the prestack parametric elastic very low frequency model is 0-2 Hz.

[0070] In some embodiments, the frequency range of the well interpolation model is 2-8 Hz.

[0071] The study area is located in the slope zone of the Oriente Basin in Ecuador, South America, with an area of ​​300 square kilometers. It mainly develops low-amplitude structural-lithological traps. The reservoirs are mainly tidal flat sand bars and tidal channel deposits. The reservoirs are highly heterogeneous and change rapidly laterally. There are about 300 wells in the study area, but their locations are unevenly distributed. If the low-frequency model is interpolated only using logging curves, it will be greatly affected by well control in the lateral direction, which has certain risks.

[0072] 1) Create a compaction trend body in the monocline structural area

[0073] The analysis of the compaction trend under the monocline structure background in the central area of ​​Andes T shows that there is a certain compaction trend in the area. The compaction trend of P-wave velocity objectively reflects the sedimentary characteristics between strata in the monocline structure area with the increase of depth. According to the linear relationship between the depth and P-wave velocity of typical wells in the work area, the P-wave velocity compaction trend relationship in the area is statistically analyzed, and the P-wave velocity compaction trend body of the monocline structure area is created based on this relationship.

[0074] 2) Constructing a prestack parametric elastic very low frequency model based on seismic layer velocity volume

[0075] The geological characteristics of the study area are relatively complex, and it is necessary to make full use of the information of the seismic layer velocity body, that is, the layer velocity body. The layer velocity body is optimized to obtain the optimized layer velocity body, and then the optimized layer velocity body is corrected according to the P-wave velocity of the typical well in the work area and the P-wave velocity compaction trend body in step 1 to obtain the well-controlled layer velocity body; From the rock physics analysis on the well and in this area, it can be seen that the velocity has a certain correlation with different elastic parameters, so the relationship between P-wave impedance, density, P-S wave velocity ratio and P-wave velocity is established, and the relationship is selected as close to the mudstone trend as possible for research.

[0076] Figure 2 (a) is the intersection analysis diagram of longitudinal wave velocity and longitudinal wave impedance, as shown in Figure 2 As shown in (a), the y-axis is the longitudinal wave impedance, the x-axis is the velocity, and the specific relationship is y=3.10998x-2559.91.

[0077] Figure 2 (b) is the intersection analysis diagram of longitudinal wave velocity and density, such as Figure 2 As shown in (b), the y-axis is density and the x-axis is speed, and the specific relationship is y=0.000425x+1.05.

[0078] Figure 2 (c) is the cross analysis diagram of the longitudinal wave velocity and the ratio of longitudinal and transverse wave velocities, such as Figure 2 As shown in (c), the y-axis is the ratio of longitudinal and transverse wave velocities, and the x-axis is the velocity. The specific relationship is y=0.0000042*x^3-0.0000012*x^2-0.000175x+2.252.

[0079] Then the velocity field is converted into an elastic parameter data volume using the above relationship as a prestack parameter elastic very low frequency model. Figure 3 (a) is the low-frequency model of longitudinal wave impedance based on the layer velocity body; Figure 3 (b) is the density low-frequency model established based on the layer velocity body; Figure 3 (c) is the low-frequency model of the P-wave and S-wave velocity ratio established based on the layer velocity body; Figure 3 As shown in (a), 3(b), and 3(c), the three prestack parameter elastic very low frequency models can reflect the sedimentary change trend of a large set of strata and have a good correlation with the elastic curve on the well.

[0080] 3) Establish a 3D structural framework and well interpolation model driven by layer velocity

[0081] Reasonably select wells in the work area, and carry out well interpolation constrained by well-controlled layer velocity body based on the 3D structural grid and the well-controlled layer velocity body in step 2, the optimized P-wave impedance curves, P-S wave velocity ratio curves and density curves of these wells to obtain a well interpolation model driven by the 3D structural grid and layer velocity.

[0082] The present invention uses the logging curve interpolation method to establish a low-frequency model based on a three-dimensional structural grid. The model is interpolated along the structural trend, such as Figure 4 As shown. Figure 4 (a) is the three-dimensional structural grid of the work area; Figure 4 (b) is the low-frequency model section of the well interpolation longitudinal wave impedance. It can be seen from the figure Figure 4 (b) Well interpolation model and Figure 4 The three-dimensional structural framework in (a) has the same trend.

[0083] 4) Establishment of multi-attribute fusion low-frequency model

[0084] The prestack parameter elastic very low frequency model based on the seismic layer velocity body in step 2 and the well interpolation model driven by the three-dimensional structural grid and layer velocity in step 3 are merged in the frequency domain, wherein the very low frequency model retains the information of 0-2Hz and the well interpolation model retains the information of 2-8Hz, thereby establishing a multi-attribute fusion low-frequency model.

[0085] like Figure 5 (a) is the root mean square attribute diagram of the interpolated P-wave impedance model of the M1 layer well; Figure 5 (b) is the root mean square attribute diagram of the comprehensive longitudinal wave impedance model of the M1 layer; Figure 6 (a) is the root mean square attribute diagram of the interpolated P-wave and S-wave velocity ratio model of the M1 layer well; Figure 6 (b) is the root mean square attribute diagram of the comprehensive longitudinal and transverse wave velocity ratio model of the M1 layer. Figure 5 (a) and Figure 6 As shown in (a), the results show that the sedimentary law reflected by the low-frequency model plane map obtained by the well interpolation method alone is that there is a "bull's eye" phenomenon at the center point, and the overall law is inaccurate; Figure 5 (b) and Figure 6 As shown in (b), the velocity change reflected by the layer velocity body is consistent with the sedimentary law. From the perspective of sedimentary geological knowledge, the law reflected by the layer velocity body is more accurate. In the case of compaction trend controlled by the layer velocity body, the final multi-attribute fusion low-frequency model is obtained by using the multi-information coupling low-frequency model establishment technical process. The lithology change trend reflected by the plane map of the extracted velocity ratio is consistent with the sedimentary geological knowledge, which effectively improves the accuracy of the low-frequency model.

[0086] Based on the above-mentioned method for establishing a low-frequency model based on multi-attribute fusion, the present invention further proposes a system for establishing a low-frequency model based on multi-attribute fusion, comprising:

[0087] Create a unit to create a compaction trend body of longitudinal wave velocity in the work area;

[0088] A construction unit is used to construct a prestack parametric elastic very low frequency model based on the P-wave velocity compaction trend body and the seismic layer velocity body;

[0089] Establishing units for establishing well interpolation models based on a three-dimensional structural grid;

[0090] The merging unit is used to merge the prestack parameter elastic very low frequency model and the well interpolation model in the frequency domain to obtain a multi-attribute fusion low frequency model.

[0091] In some embodiments, the creating unit is specifically used to:

[0092] According to the linear relationship between the depth of the wells in the work area and the P-wave velocity, the compaction trend relationship of the P-wave velocity in the work area is determined;

[0093] Based on the longitudinal wave velocity compaction trend relationship, a longitudinal wave velocity compaction trend body of the work area is created.

[0094] In some embodiments, the building block is specifically used for:

[0095] Based on the P-wave velocity compaction trend body and the P-wave velocity of the target well in the work area, the optimized interval velocity body is corrected to obtain the well-controlled interval velocity body;

[0096] The linear functional relationship between the longitudinal wave velocity and the longitudinal wave impedance, the ratio of longitudinal and transverse wave velocities and the density is established;

[0097] Based on the linear function relationship, the well-controlled layer velocity body is converted into P-wave impedance, P-wave velocity ratio and density elastic trend body, and the prestack parameter elastic very low frequency model constructed based on the seismic layer velocity body is obtained.

[0098] In some embodiments, the establishing unit is specifically configured to:

[0099] Based on the 3D structural grid and well-controlled layer velocity body, well-controlled layer velocity body constrained well interpolation is performed on the P-wave impedance, P-wave velocity ratio and density curve to obtain a well interpolation model driven by the 3D structural grid and layer velocity.

[0100] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for establishing a low-frequency model based on multi-attribute fusion, characterized in that: The following steps are involved: Create a compaction trend body of longitudinal wave velocity in the work area; Based on the P-wave velocity compaction trend body and the seismic layer velocity body, a prestack parametric elastic very low frequency model is constructed; Based on the three-dimensional structural grid, a well interpolation model is established; The pre-stack parameter elastic very low frequency model and the well interpolation model are combined in the frequency domain to obtain a multi-attribute fusion low frequency model.

2. The method for establishing a low-frequency model based on multi-attribute fusion according to claim 1, characterized in that: The specific steps of creating the work area longitudinal wave velocity compaction trend body are as follows: According to the linear relationship between the depth of the wells in the work area and the P-wave velocity, the compaction trend relationship of the P-wave velocity in the work area is determined; Based on the longitudinal wave velocity compaction trend relationship, a longitudinal wave velocity compaction trend body of the work area is created.

3. The method for establishing a low-frequency model based on multi-attribute fusion according to claim 1, characterized in that: The specific steps of constructing the prestack parametric elastic very low frequency model based on the P-wave velocity compaction trend body and the seismic layer velocity body are as follows: Based on the P-wave velocity compaction trend body and the P-wave velocity of the target well in the work area, the optimized interval velocity body is corrected to obtain the well-controlled interval velocity body; The linear functional relationship between the longitudinal wave velocity and the longitudinal wave impedance, the ratio of longitudinal and transverse wave velocities and the density is established; Based on the linear function relationship, the well-controlled layer velocity body is converted into P-wave impedance, P-wave velocity ratio and density elastic trend body, and the prestack parameter elastic very low frequency model constructed based on the seismic layer velocity body is obtained.

4. The method for establishing a low-frequency model based on multi-attribute fusion according to claim 3, characterized in that: The specific steps of establishing the well interpolation model based on the three-dimensional structural grid are as follows: Based on the 3D structural grid and well-controlled layer velocity body, well-controlled layer velocity body constrained well interpolation is performed on the P-wave impedance, P-wave velocity ratio and density curve to obtain a well interpolation model driven by the 3D structural grid and layer velocity.

5. The method for establishing a low-frequency model based on multi-attribute fusion according to claim 1, characterized in that: The frequency range of the prestack parametric elastic very low frequency model is 0-2 Hz.

6. The method for establishing a low-frequency model based on multi-attribute fusion according to claim 1, characterized in that: The frequency range of the well interpolation model is 2-8 Hz.

7. A system for establishing a low-frequency model based on multi-attribute fusion, characterized in that: include: Create a unit to create a compaction trend body of longitudinal wave velocity in the work area; A construction unit, used for constructing a prestack parametric elastic very low frequency model based on the P-wave velocity compaction trend body and the seismic layer velocity body; Establishing units for establishing well interpolation models based on a three-dimensional structural grid; The merging unit is used to merge the prestack parameter elastic very low frequency model and the well interpolation model in the frequency domain to obtain a multi-attribute fusion low frequency model.

8. The system for establishing a low-frequency model based on multi-attribute fusion according to claim 7, characterized in that: The creation unit is specifically used for: According to the linear relationship between the depth of the wells in the work area and the P-wave velocity, the compaction trend relationship of the P-wave velocity in the work area is determined; Based on the longitudinal wave velocity compaction trend relationship, a longitudinal wave velocity compaction trend body of the work area is created.

9. The system for establishing a low-frequency model based on multi-attribute fusion according to claim 7, characterized in that: The building block is specifically used for: Based on the P-wave velocity compaction trend body and the P-wave velocity of the target well in the work area, the optimized interval velocity body is corrected to obtain the well-controlled interval velocity body; The linear functional relationship between the longitudinal wave velocity and the longitudinal wave impedance, the ratio of longitudinal and transverse wave velocities and the density is established; Based on the linear function relationship, the well-controlled layer velocity body is converted into P-wave impedance, P-wave velocity ratio and density elastic trend body, and the prestack parameter elastic very low frequency model constructed based on the seismic layer velocity body is obtained.

10. The system for establishing a low-frequency model based on multi-attribute fusion according to claim 7, characterized in that: The establishing unit is specifically used for: Based on the 3D structural grid and well-controlled layer velocity body, well-controlled layer velocity body constrained well interpolation is performed on the P-wave impedance, P-wave velocity ratio and density curve to obtain a well interpolation model driven by the 3D structural grid and layer velocity.

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