Weak signal separation imaging method based on reflected wave separation

Abstract

This invention discloses a weak signal separation imaging method based on reflected wave separation, relating to the field of petroleum and natural gas geophysics. The method includes: creating a synthetic record; tracing the sequence stratigraphic framework; rock physical analysis; well de-reservoirization; three-dimensional fine wave impedance modeling based on sequence stratigraphic framework constraints; obtaining the three-dimensional spatially varied reflection coefficient volume of the lithologic interface; extracting the well-side wavelet; obtaining the minimum half-wavelength transit time of seismic waves at the well-side lithologic interface; obtaining the matching factor; obtaining the dominant frequency of the spatial variation at the lithologic interface; obtaining the three-dimensional spatially varied wavelet; obtaining the three-dimensional forward model; and recovering the weak signal from the de-reservoir. This method not only establishes a three-dimensional forward model of the lithologic interface but also simultaneously performs forward modeling of the model using the Ricker wavelet in porous viscoelastic media. Finally, the forward modeling results are separated from the actual seismic data using wavefield separation.

Description

Technical Field

[0001] This invention relates to the field of petroleum and natural gas geophysics, and more specifically to the field of oil and gas field exploration and development, particularly to a weak signal imaging method based on reflected wave separation. Background Technology

[0002] With the continuous development of oil and gas field exploration and development technologies, the development level of major oil fields is constantly improving, and complex oil and gas reservoirs are attracting increasing attention from exploration and development personnel. In petroleum exploration, reflection seismic methods are widely used to detect underground geological structures, and can determine the location of traps with oil and gas potential with high accuracy and resolution.

[0003] In existing technologies, there are generally three methods for separating weak reservoir signals: matched pursuit wavelet decomposition and reconstruction, long and short cycle waveform analysis, and strong shielding removal technology based on compressed sensing. All three methods are based on seismic data and extract seismic information of lithological interfaces from seismic data to achieve the purpose of recovering weak reservoir signals. However, they all have some limitations. The separation effect of weak reservoir signals is not very good. The removed lithological interfaces contain reservoir information. The main reasons can be summarized as follows:

[0004] Firstly, regarding the reflection coefficient: (1) the variation of the reflection coefficient in the lateral direction of the lithological interface in the actual geological model is not considered; (2) the influence of the reservoir on the reflection coefficient of the lithological interface is not considered, and the seismic information of the removed lithological interface is mixed with a certain degree of reservoir information; (3) regarding the wavelet, the spatial variation of the wavelet in the lateral direction of the lithological interface in the actual geological model is not considered, while in the existing technology, when establishing the forward model of the lithological interface, the wavelet is usually fixed and cannot achieve spatial variation. Summary of the Invention

[0005] The purpose of this invention is to provide a weak signal separation imaging method based on reflected wave separation. This method makes it possible to eliminate strong lithological interfaces, highlight the weak reservoir signals under the lithological interfaces, and further advances the fine study of high-quality reservoirs using seismic data in oil and gas exploration.

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

[0007] The weak signal separation imaging method based on reflected wave separation includes the following steps:

[0008] S1. Create synthetic records to establish the link between drilling and seismic data;

[0009] S2. Track the target layer sequence interface and establish a three-dimensional layer sequence grid for the work area;

[0010] S3. Perform rock physics analysis on the logging data of all wells in the work area to obtain the critical longitudinal wave impedance value M between the reservoir and non-reservoir.

[0011] S4. Drilling reservoir removal: The P-wave impedance values ​​of all drilled reservoirs in the work area are unified to obtain new P-wave impedance curves for all drilled wells in the work area.

[0012] S5. Based on the sequence lattice constraint, a three-dimensional fine wave impedance model is obtained to obtain a three-dimensional spatially variable impedance model.

[0013] S6. Based on the three-dimensional spatially variable wave impedance model, determine the three-dimensional spatially variable reflection coefficient γ of the lithological interface;

[0014] S7. Extract well-side wavelets and establish a database of actual seismic trace wavelets from wells across the entire region.

[0015] S8. Determine the minimum half-wavelength time difference h of the seismic wave at the drilling lithology interface;

[0016] S9. Find the matching factor;

[0017] S10. Using the matching factor, determine the dominant frequency F of each lithological interface spatial variation:

[0018] S11. Calculate the three-dimensional space-variable Reichschild wavelet R according to the Reichschild wavelet formula:

[0019] S12. Obtain the three-dimensional forward modeling volume. Based on the three-dimensional spatially variable Ricker wavelet R and the three-dimensional spatially variable reflection coefficient volume γ, perform convolution forward modeling simulation to obtain the three-dimensional forward seismic traces of the lithological interface.

[0020] S13. Reservoir-removed weak signal recovery: Separate the forward seismic traces of lithological interfaces from the original 3D seismic data, subtract the original seismic data from the forward seismic traces of lithological interfaces, perform wavefield separation, and obtain the lithology-removed 3D seismic traces, ultimately achieving reservoir-removed weak signal recovery.

[0021] As a preferred technical solution, in step S1, logging data from all wells in the work area are first collected, and corresponding synthetic records are produced using the principle of ray tracing to clarify the relationship between geological stratification and seismic wave reflection axis, and to establish the connection between drilling and earthquake.

[0022] As a preferred technical solution, in step S2, based on the sequence stratigraphic division of a single well, a sequence grid profile of the interconnected wells in different directions is established. Combined with the synthetic record created in step S1, the sequence interface of the target layer is traced to establish a three-dimensional sequence grid for the work area.

[0023] As a preferred technical solution, in step S4, the P-wave impedance values ​​of all drilling reservoirs in the work area are unified to the critical P-wave impedance value M between the reservoir and non-reservoir, thereby obtaining new P-wave impedance curves for all drilling wells in the work area.

[0024] As a preferred technical solution, in step S5, the new longitudinal wave impedance curve of the well in the work area obtained in step S4 is used to perform three-dimensional fine wave impedance spatial interpolation modeling based on the three-dimensional sequence lattice constraint, with the three-dimensional sequence lattice as the spatial constraint, to obtain the three-dimensional spatially variable wave impedance model P.

[0025] As a preferred technical solution, in step S6, the three-dimensional spatially variable wave impedance model P is shifted downward by one sampling time point to obtain a new three-dimensional spatially variable wave impedance model P', and the three-dimensional spatially variable reflection coefficient γ is calculated using the following formula.

[0026] γ=(P-P')÷(P+P') Equation (1)

[0027] As a preferred technical solution, in step S7, the wavelets of all actual seismic traces near the wells in the work area are extracted, and the dominant frequency f of the wavelets near the wells is obtained, thus establishing a wavelet library of actual seismic traces near the wells in the entire area.

[0028] As a preferred technical solution, in step S8, for the well in the work area, the seismic waveform analysis of the well-side passage is performed. The time of the peak maximum point of the seismic waveform is subtracted from the time of the upper critical point to obtain the upper half-peak time difference. The time of the peak maximum point is subtracted from the time of the lower critical point to obtain the lower peak time difference. The minimum value of the two is the minimum half-waveform time difference h of the seismic wave at the lithological interface of the well.

[0029] As a preferred technical solution, in step S9, a matching analysis is performed on the dominant frequency f of the wavelet near all wells and the minimum half-wavelength time difference h of the seismic wave at the lithological interface near the well. The correlation between the dominant frequency f and the minimum half-wavelength time difference h is obtained. Among various fitting relationships, the relationship with high correlation is selected, and the matching factor α is finally obtained through the relationship with high correlation.

[0030] α = FUN(f,h) Equation (2);

[0031] Wherein, FUN(f,h) is a formula showing a good correlation between the dominant frequency f of the wellbore wavelet and the minimum half-wavelength time difference h of the seismic wave at the wellbore lithological interface.

[0032] As a preferred technical solution, in step S10, the minimum half-wavelength time difference of each trace of the actual seismic waveform is extracted along the lithological interface. Using the obtained matching factor and the extracted minimum half-wavelength time difference of each trace of the actual seismic waveform, the dominant frequency F of each trace of the lithological interface spatial variation is calculated.

[0033] F = FUN(α,H,T) Equation (3);

[0034] Where T represents the time window range, which is 50ms above and below the lithological interface.

[0035] As a preferred technical solution, the formula for the air-varying Reichschild wavelet R in step S11 is as follows:

[0036]

[0037] Where F represents the dominant frequency of each spatial variation of the lithological interface; T represents the time window range, 50ms above and below the lithological interface.

[0038] The beneficial effects of this invention are as follows:

[0039] 1. This invention not only realizes the establishment of a three-dimensional forward geological model of lithological interfaces, but also conducts forward simulation of porous viscoelastic media using Ricker wavelets on the model. Finally, the forward simulation results are separated from the actual seismic data by wavefield separation, making it possible to eliminate strong lithological interfaces. After applying this method, the weak reservoir signals under the lithological interfaces are highlighted, which further advances the fine study of high-quality reservoirs using seismic data in oil and gas exploration.

[0040] 2. This invention, through post-reservoir modeling, can realistically restore the velocity structure of the lithological interface, and by utilizing the matching relationship between drilling and seismic information, obtains the wavelet of each lattice variation, thereby reducing ambiguity by utilizing drilling information.

[0041] 3. The present invention can significantly improve the prediction accuracy of thin reservoirs, increasing the prediction accuracy from 70% to 87%.

[0042] 4. The new seismic data after lithology removal in this invention can indicate not only the presence or absence of a reservoir, but also the longitudinal position of the reservoir, i.e., the bottom boundary of the reservoir is a wave crest reflection. Attached Figure Description

[0043] Figure 1 This is a flowchart of the method of the present invention;

[0044] Figure 2 This is a schematic diagram of the reconstruction of the lithological interface wave impedance curve to eliminate reservoir influence according to the present invention.

[0045] Figure 3 This is the wave impedance interpolation profile based on the sequence constraint of the present invention;

[0046] Figure 4 This invention relates to a three-dimensional wave impedance volume under sequence constraints.

[0047] Figure 5This is a comparative cross-section before and after lithology removal in this invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0049] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0050] Example 1

[0051] This embodiment provides a weak signal imaging method based on reflected wave separation. This invention not only establishes a three-dimensional forward geological model of lithological interfaces, but also simultaneously performs forward modeling of the model using Ricker wavelet for porous viscoelastic media. Finally, the forward modeling results are separated from actual seismic data through wavefield separation, making it possible to eliminate strong lithological interfaces. (Refer to the appendix of the specification.) Figure 1 This method mainly includes the following steps:

[0052] Step 1: Create a synthesis record;

[0053] Step 2: Trace the hierarchical lattice;

[0054] Step 3: Rock physical analysis;

[0055] Step 4: Drilling to remove reservoirs;

[0056] Step 5: Three-dimensional fine wave impedance modeling based on sequence lattice constraints;

[0057] Step 6: Determine the three-dimensional spatial variation reflection coefficient of the lithological interface;

[0058] Step 7: Extract the well-side wavelet;

[0059] Step 8: Determine the minimum half-wavelength time difference of seismic waves at the lithological interface near the wellbore;

[0060] Step 9: Calculate the matching factors;

[0061] Step 10: Determine the dominant frequency of lithological interface cavitation variation;

[0062] Step 11: Obtain the three-dimensional spatially variable wavelet;

[0063] Step 12: Obtain the 3D forward volume;

[0064] Step 13: Recover weak reservoir signals.

[0065] In practical operation: The present invention eliminates strong lithological interfaces through the above steps, making the weak reservoir signals under the lithological interfaces stand out, which can greatly improve the prediction accuracy of thin reservoirs; and the new seismic data after lithological removal can not only indicate the presence or absence of reservoirs in terms of reservoir response, but also indicate the vertical location of reservoirs.

[0066] Example 2

[0067] This embodiment provides a weak signal imaging method based on reflected wave separation. This invention not only establishes a three-dimensional forward geological model of lithological interfaces, but also simultaneously performs forward modeling of the model using Ricker wavelet for porous viscoelastic media. Finally, the forward modeling results are separated from actual seismic data through wavefield separation, making it possible to eliminate strong lithological interfaces. This method mainly includes the following steps:

[0068] Step 1: Create a composite log to establish the link between drilling and seismic data.

[0069] First, collect logging data from all wells in the work area, and use the principle of ray tracing to create corresponding synthetic records, clarify the relationship between geological stratification and seismic wave reflection axis, and establish the connection between drilling and earthquakes;

[0070] Step 2: Trace the sequence grid and establish a three-dimensional sequence grid for the work area.

[0071] Based on comprehensive research and analysis, and according to the sequence stratigraphic division of a single well, a sequence stratigraphic framework profile of the wells in different directions is established. Combined with the synthetic record made in step S1, the sequence interface of the target layer is traced, and a three-dimensional sequence stratigraphic framework of the work area is established.

[0072] Step 3: Perform rock physical analysis on the logging data of all wells in the work area.

[0073] Rock physics analysis was performed on the logging data of all wells in the work area to obtain the critical P-wave impedance value M between reservoirs and non-reservoirs. If the P-wave impedance value is ≤ M, it is a reservoir; otherwise, it is a surrounding rock. Among them, rock layers with porosity ≥ 2% are reservoirs, and rock layers with porosity < 2% are non-reservoirs.

[0074] Step 4: Drilling to remove reservoir

[0075] The P-wave impedance values ​​of all wells in the work area are unified to the critical P-wave impedance value M between the reservoir and non-reservoir, that is, the reservoir section is eliminated and replaced with the P-wave impedance value of the surrounding rock, thereby obtaining the new P-wave impedance curves of all wells in the work area.

[0076] Step 5: 3D refined wave impedance modeling based on sequence lattice constraints to obtain a 3D spatially variable impedance model.

[0077] Using the new longitudinal wave impedance curves of the wells in the work area obtained in step S4, and with the three-dimensional sequence lattice as the spatial constraint, we perform three-dimensional fine wave impedance modeling based on the sequence lattice constraint to obtain the three-dimensional spatially variable wave impedance model P.

[0078] Step 6: Based on the three-dimensional spatially varied wave impedance model, determine the three-dimensional spatially varied reflection coefficient γ of the lithological interface.

[0079] First, the three-dimensional spatially variable wave impedance model P is shifted downward by one sampling time point to obtain a new three-dimensional spatially variable wave impedance model P'. Then, the three-dimensional spatially variable reflection coefficient γ is obtained through the following calculation formula.

[0080] γ=(P-P')÷(P+P') Equation (1);

[0081] Step 7: Extract well-side wavelets and establish a database of actual seismic trace wavelets near all wells in the region.

[0082] Extract wavelets from all actual seismic traces near drilling sites within the work area, and obtain the dominant frequency f of the wavelets near drilling sites. Based on the dominant frequency f, establish a wavelet library of actual seismic traces near drilling sites for the entire area.

[0083] Step 8: Determine the minimum half-wavelength time difference h of the seismic wave at the lithological interface near the wellbore.

[0084] For wells in the work area, seismic waveform analysis is performed on the wellside passage. The time of the upper critical point is subtracted from the time of the peak maximum of the seismic waveform to obtain the upper half peak time difference. The time of the lower critical point is subtracted from the time of the peak maximum to obtain the lower peak time difference. The minimum value of the two is the minimum half waveform time difference h of the seismic wave at the lithological interface next to the well.

[0085] Step 9: Calculate the matching factor α

[0086] The wellbore bypass channel can extract the wellbore bypass wavelet with a dominant frequency of f. The time difference of the minimum half-wavelength of the wellbore bypass can also be obtained as h, i.e., f1h1, f2h2, f3h3...f n h nGenerally, the matching factor α can be a constant value or a formula, and α varies in different regions. In this embodiment, a matching analysis is first performed on the dominant wavelet frequency f of all wells and the minimum half-wavelength time difference h of the seismic waves at the lithological interface near the well. The correlation between the dominant wavelet frequency f and the minimum half-wavelength time difference h is obtained. This correlation is mainly based on the fitting formula f = αh for the dominant wavelet frequency f and the minimum half-wavelength time difference h of the seismic waveform at the lithological interface. That is, the dominant wavelet frequency f and the minimum half-wavelength time difference h are fitted with data. The fitting methods include, but are not limited to, linear fitting, polynomial fitting, etc. Among various fitting relationships, the relationship with high correlation is found, and the matching factor α is finally obtained through the relationship with high correlation.

[0087] α = FUN(f,h) Equation (2);

[0088] Wherein, FUN(f,h) is the relationship between the main frequency f of the well-side wavelet and the minimum half-wavelength time difference h of the seismic wave at the lithological interface near the well.

[0089] Step 10: Determine the dominant frequency F of each lithological interface cavitation variation;

[0090] The minimum half-wavelength time difference H of each trace of the actual seismic waveform is extracted along the lithological interface. Given the correlation analysis between the actual waveforms from previous drilling and well-side traces, the minimum half-wavelength time difference H of each trace is known. Therefore, using the matching factor α obtained in step S9 and the minimum half-wavelength time difference H of each extracted actual seismic waveform, the dominant frequency F of each trace of the lithological interface spatial variation can be calculated, i.e.

[0091] F = FUN(α,H,T) Equation (3);

[0092] Where T is the time window range, within 50ms upward from the lithological interface and within 50ms downward from the lithological interface;

[0093] Step 11: Obtain the three-dimensional space-variable wavelet

[0094] The space-variable Reichschild wavelet R is obtained using the Reichschild wavelet formula. The specific calculation formula is as follows:

[0095]

[0096] Where F represents each main screen of lithological interface spatial variation; T represents the time window range, within 50ms upward from the lithological interface and within 50ms downward from the lithological interface.

[0097] Step 12: Obtain the 3D forward volume

[0098] Based on the spatially varied Reckon wavelet R and the spatially varied reflection coefficient γ, a convolution forward modeling simulation was performed to obtain the three-dimensional forward seismic traces of the lithological interface.

[0099] Step 13: Recovery of weak reservoir signals after removing the influence of lithological interfaces

[0100] The lithological interface forward-modeled seismic traces are separated from the original 3D seismic data, and then the original seismic data is subtracted from the lithological interface forward-modeled seismic traces. Wavefield separation is then performed on the two to obtain the lithology-free 3D seismic traces, ultimately achieving the recovery of weak signals from the reservoir.

[0101] By comparing and analyzing the application of the method of the present invention before and after, it was found that the reservoirs in the original seismic profile were mainly distributed in the strong seismic response reflection of the lithological interface, and the reservoirs themselves had relatively weak signal responses. Therefore, they were covered by the lithological interface and had no obvious seismic reflection characteristics. However, after applying this method, the weak signal of the reservoir under the lithological interface was highlighted, which further promoted the fine study of high-quality reservoirs using seismic data in oil and gas exploration.

[0102] Refer to the instruction manual appendix Figure 5 The first two wellbore of Well A8 did not perform well, so sidetracking was recommended. Utilizing new technologies, it was suggested to drill into the target body in the southern part of the design. After the lithology was exposed on the corresponding profile, the reservoir response was not very obvious in the original profile. This was also the first verification well to utilize the new technology. The final test result was 1.09 million cubic meters per day, which is 10 times higher than the average production of adjacent wells in the same producing layer. This supported the submission of nearly 100 billion cubic meters of proven reserves in the well area, achieving the production objective of the well site deployment.

[0103] The above description is only 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 weak signal separation imaging based on reflection wave separation, characterized in that, Includes the following steps: S1. Create synthetic records to establish the link between drilling and seismic data; S2. Track the target layer sequence interface and establish a three-dimensional layer sequence grid for the work area; S3. Perform rock physics analysis on the logging data of all wells in the work area to obtain the critical longitudinal wave impedance value M between the reservoir and non-reservoir. S4. Drilling reservoir removal: The P-wave impedance values ​​of all drilled reservoirs in the work area are unified to obtain new P-wave impedance curves for all drilled wells in the work area. S5. Based on the sequence lattice constraint, a three-dimensional fine wave impedance model is obtained to obtain a three-dimensional spatially variable impedance model. S6. Based on the three-dimensional spatially variable wave impedance model, determine the three-dimensional spatially variable reflection coefficient γ of the lithological interface; S7. Extract well-side wavelets and establish a database of actual seismic trace wavelets from wells across the entire region. S8. Determine the minimum half-wavelength time difference h of the seismic wave at the drilling lithology interface; S9. Determine the matching factor; perform matching analysis on the dominant frequency f of the wavelet near all wells and the minimum half-wavelength time difference h of the seismic wave at the lithological interface near the well, and obtain the correlation between the dominant frequency f and the minimum half-wavelength time difference h. Among various fitting relationships, find the relationship with high correlation, and finally obtain the matching factor α through the relationship with high correlation. Equation (2); Wherein, FUN(f,h) is a highly correlated relationship between the dominant frequency f of the well-side wavelet and the minimum half-wavelength time difference h of the seismic wave at the well-side lithological interface. S10. Using the matching factor, determine the dominant frequency F of each lithological interface spatial variation: S11. Calculate the three-dimensional space-variable Reichschild wavelet R according to the Reichschild wavelet formula: S12. Obtain the three-dimensional forward modeling volume. Based on the three-dimensional spatially variable Ricker wavelet R and the three-dimensional spatially variable reflection coefficient volume γ, perform convolution forward modeling simulation to obtain the three-dimensional forward seismic traces of the lithological interface. S13. Reservoir-removed weak signal recovery: Separate the forward seismic traces of lithological interfaces from the original 3D seismic data, subtract the original seismic data from the forward seismic traces of lithological interfaces, perform wavefield separation, and obtain the lithology-removed 3D seismic traces, ultimately achieving reservoir-removed weak signal recovery.

2. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S1, logging data from all wells in the work area are first collected. Using the principle of ray tracing, corresponding synthetic records are created to clarify the relationship between geological stratification and seismic wave reflection axis, and to establish the connection between drilling and earthquake.

3. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S2, based on the sequence stratigraphic division of a single well, a sequence grid profile of the wells in different directions is established. Combined with the synthetic record created in step S1, the sequence interface of the target layer is traced, and a three-dimensional sequence grid of the work area is established.

4. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S4, the P-wave impedance values ​​of all wells in the work area are unified to the critical P-wave impedance value M between the reservoir and non-reservoir, thereby obtaining the new P-wave impedance curves of all wells in the work area.

5. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S5, using the new longitudinal wave impedance curve of the well in the work area obtained in step S4, and with the three-dimensional sequence lattice as the spatial constraint, three-dimensional fine wave impedance spatial interpolation modeling based on the sequence lattice constraint is performed to obtain the three-dimensional spatially variable wave impedance model P.

6. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S6, the three-dimensional spatially variable wave impedance model P is shifted downward by one sampling time point to obtain a new three-dimensional spatially variable wave impedance model P'. The three-dimensional spatially variable reflection coefficient γ is then calculated using the following formula. Equation (1).

7. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S7, the wavelets of all actual seismic traces near the wells in the work area are extracted, and the dominant frequency f of the wavelet near the wells is obtained, thus establishing a wavelet library of actual seismic traces near the wells in the entire area.

8. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S8, for the wells in the work area, the seismic waveform analysis of the wellside passage is performed. The time of the peak maximum point of the seismic waveform is subtracted from the time of the upper critical point to obtain the upper half peak time difference. The time of the peak maximum point is subtracted from the time of the lower critical point to obtain the lower peak time difference. The minimum value of the two is the minimum half waveform time difference h of the seismic wave at the lithological interface of the well.

9. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S10, the minimum half-wavelength time difference of each trace of the actual seismic waveform is extracted along the lithological interface. Using the obtained matching factor and the minimum half-wavelength time difference of each trace of the actual seismic waveform, the dominant frequency F of each trace of the lithological interface spatial variation is calculated. Equation (3); Where T is the time window range, 50ms above and below the lithological interface, α is the matching factor, and H is the minimum half-wavelength time difference for each trace of the actual seismic waveform.

10. The weak signal separation imaging method based on reflected wave separation according to claim 1, characterized in that, In step S11, the formula for the space-variable Reichschild wavelet R is as follows: Equation (4); Where F represents the dominant frequency of each spatial variation of the lithological interface; T represents the time window range, 50ms above and below the lithological interface.

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