A deep seismic data processing method based on refraction-reflection information fusion

Abstract

The invention discloses a deep seismic data processing method based on refraction-reflection information fusion, comprising the following steps: forward modeling the acquired seismic data through a formation velocity model to identify the refraction wave information in the seismic data; cutting the seismic data, picking up the velocity of the profile seismic data based on the time-distance characteristics of the refraction wave and the reflection wave, and forming a refraction wave velocity spectrum and a reflection wave velocity spectrum; superimposing the refraction wave velocity spectrum and the reflection wave velocity spectrum, and processing the profile data of the entire seismic data using the superimposed velocity spectrum obtained by fusion of the refraction wave and the reflection wave to obtain a new superimposed profile; the invention combines the advantages of refraction wave and reflection wave seismic data processing, enriches the low-frequency information of the seismic data by introducing the refraction wave information, weakens the shielding effect of the high-speed layer, makes the deep phase axis clearer, and makes the formation structure clearer, so as to provide a strong basis for the exploration and development of deep-ultra-deep reservoirs.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic data processing, and in particular to a deep seismic data processing method based on refraction-reflection information fusion. Background Art

[0002] During seismic data acquisition, as the number of seismic traces increases and offsets increase, a set of valid information, namely refracted waves, is generated in the raw field data at far offsets. In conventional seismic records, refracted waves are often treated as invalid information and removed, rarely utilized. However, in seismic data from deep and ultra-deep reservoirs, because near-offset events are completely obscured by various types of noise, the energy of refracted waves is far greater than that of conventional reflections, and their imaging position on the time section is consistent with the normal propagation domain. Therefore, utilizing this refracted wave information can enhance the energy of the target layer's reflected waves, improving the accuracy of seismic imaging in deep and ultra-deep reservoirs.

[0003] Currently, common seismic processing of refraction data is accomplished within the framework of conventional reflection seismic data processing by improving specific modules, such as first-arrival tomographic statics, noise suppression, high-order dynamic correction, fine-grained resection, and migration parameter optimization. Because these methods rely on the data itself, the reliability of the refraction information derived depends largely on operator experience. Furthermore, because the influence of stratigraphic information is not considered from a fundamental perspective, refraction information has not been fully utilized, resulting in low accuracy in deep seismic data processing. Summary of the Invention

[0004] The purpose of the present invention is to provide a deep seismic data processing method based on refraction-reflection information fusion to solve the technical problem that the seismic processing of refraction wave data commonly used in the prior art is achieved by improving certain targeted modules within the framework of the conventional reflection seismic data processing process, and the refraction wave information is not fully utilized, thus resulting in low accuracy in deep seismic data processing.

[0005] In order to solve the above technical problems, the present invention specifically provides the following technical solutions:

[0006] A deep seismic data processing method based on refraction-reflection information fusion comprises the following steps:

[0007] Step 100: forward modeling the acquired seismic data using a formation velocity model to identify refracted wave information in the seismic data;

[0008] Step 200: segmenting the seismic data, performing velocity picking on the profile seismic data based on the time-distance characteristics of the refracted waves and the reflected waves, and forming a refracted wave velocity spectrum and a reflected wave velocity spectrum;

[0009] Step 300: Superimpose the refracted wave velocity spectrum and the reflected wave velocity spectrum, and use the superimposed velocity spectrum obtained by merging the refracted wave and the reflected wave to process the profile data of the entire seismic data to obtain a new superimposed profile.

[0010] As a preferred solution of the present invention, in step 100, the steps for identifying the refracted wave information are as follows:

[0011] Acquiring depth-domain velocity field information of a study area, and selecting a simulated earthquake source based on a high-velocity layer position according to the depth-domain velocity field information;

[0012] The staggered grid high-order finite difference numerical simulation method of the acoustic wave equation is used to perform forward simulation on the simulated earthquake source in the study area to obtain the numerical simulation profile at the location of the simulated earthquake source, and the refracted wave information is identified from the information map of the numerical simulation profile.

[0013] As a preferred solution of the present invention, the staggered grid high-order finite difference numerical simulation method based on the acoustic wave equation is implemented as follows:

[0014] First, the entire model is divided into spatial and temporal grids according to the spatial intervals dx, dy and the time interval dt;

[0015] Secondly, the high-order finite difference formula based on staggered grid technology is used to approximate the time derivative on the left side and the spatial derivative on the right side of the acoustic wave equation by difference.

[0016] Thirdly, the spatial model parameters, source location and source function are first given in space. At each time loop t, differential calculation and boundary processing are performed on the i-th grid in the x-direction and the j-th grid in the y-direction, and a wavefield snapshot is output.

[0017] Finally, the time loop ends and the simulated seismic profile is output.

[0018] As a preferred solution of the present invention, the multi-layer wave velocity of the stratum medium is obtained in sequence from top to bottom, and the reflected wave, the refracted wave and the direct wave are distinguished according to the change of the incident angle of the seismic wave;

[0019] Construct a two-dimensional time-distance coordinate axis and integrate the time-distance curves of reflected waves, refracted waves and direct waves in the same two-dimensional time-distance coordinate axis;

[0020] Based on the time-distance curves of the reflected wave, refracted wave and direct wave, in the numerical simulation section, the direct wave is used as the boundary, and the seismic information outside the direct wave is the refracted wave information.

[0021] As a preferred solution of the present invention, the depth domain velocity field information of the study area is obtained by:

[0022] The stacking velocity is obtained from the velocity analysis results of the conventional processing in the study area, and then the stacking velocity is converted into the depth domain layer velocity using Petrel software. Finally, the overall velocity field is interpolated using Matlab program to obtain the depth domain velocity field information of the study area.

[0023] As a preferred solution of the present invention, in step 200, the time-distance characteristics of the refracted wave and the reflected wave are obtained as follows:

[0024] Obtain the three-layer wave velocity of the stratum medium in order from top to bottom, and distinguish the reflected wave, refracted wave and direct wave according to the change of the incident angle of the seismic wave;

[0025] Construct a two-dimensional time-distance coordinate axis and integrate the time-distance curves of reflected waves, refracted waves and direct waves in the same two-dimensional time-distance coordinate axis;

[0026] Based on the time-distance curves of the reflected wave, refracted wave and direct wave, the time-distance characteristics of the refracted wave and the reflected wave are obtained, that is, with the direct wave as the boundary, the speed of the time-distance curve of the reflected wave within the direct wave increases with time, and the speed of the time-distance curve of the refracted wave outside the direct wave decreases with time.

[0027] As a preferred solution of the present invention, the steps for cutting the seismic data to obtain separated refracted wave data and reflected wave data are as follows:

[0028] Cutting the actual seismic data based on the direct wave as a boundary to obtain separated refracted wave data and reflected wave data;

[0029] Based on the change characteristics of the formation velocity corresponding to the reflection wave time-distance curve increasing with time, and the change characteristics of the formation velocity corresponding to the refracted wave time-distance curve decreasing with time, the refracted wave data and the reflected wave data are velocity picked up respectively to obtain the refracted wave velocity spectrum and the reflected wave velocity spectrum.

[0030] As a preferred solution of the present invention, in step 300, the specific implementation method of selecting the velocity spectrum to be used from the refracted wave velocity spectrum and the reflected wave velocity spectrum based on the intersection time is as follows:

[0031] The time corresponding to the intersection of the refracted wave velocity spectrum and the reflected wave velocity spectrum is found. The portion less than the intersection time uses the reflected wave velocity spectrum, and the portion greater than the intersection time uses the refracted wave velocity spectrum. Finally, a velocity spectrum is obtained that is a fusion of the refracted wave velocity spectrum and the reflected wave velocity spectrum.

[0032] As a preferred solution of the present invention, the seismic data of the entire study area are stacked using the refraction-reflection fusion velocity spectrum to obtain a final stacked profile of the entire study area.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention combines the advantages of refracted and reflected wave seismic data processing. By introducing refracted wave information, it enriches the low-frequency information of the seismic data, weakens the shielding effect of the high-speed layer, makes the deep phase axis clearer, and the stratigraphic structure more defined, providing a strong basis for the exploration and development of deep and ultra-deep reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other implementation drawings based on the provided drawings without inventive effort.

[0036] Figure 1 A schematic flow chart of a deep seismic data processing method provided by an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of the depth-domain velocity field information (with earthquake source location) of the Ulungu L03 line provided in an embodiment of the present invention;

[0038] Figure 3 A flowchart of a program implementation of a staggered grid finite difference numerical simulation method provided by an embodiment of the present invention;

[0039] Figure 4 A comparison result diagram of a numerical simulation profile (4a) and an actual earthquake profile (4b) at a location of the earthquake source of the Ulungur L03 line provided in an embodiment of the present invention;

[0040] Figure 5 A comparison result diagram of a numerical simulation profile (5a) and an actual earthquake profile (5b) at the second earthquake source position of the Ulungu L03 line provided in an embodiment of the present invention;

[0041] Figure 6 A schematic diagram of conventional time-distance curves of reflected and refracted waves in three-layer horizontal media of the Ulungu L03 line provided in an embodiment of the present invention;

[0042] Figure 7 A refraction wave information graph (7a) and a reflection wave information graph (7b) after data cutting and separation provided in an embodiment of the present invention;

[0043] Figure 8 The refracted wave velocity spectrum (8a) and the reflected wave velocity spectrum (8b) after data cutting and separation provided in an embodiment of the present invention;

[0044] Figure 9 A refracted wave superposition profile (9a) and a reflected wave superposition profile (9b) formed by processing the refracted wave and reflected wave velocity information respectively provided in an embodiment of the present invention;

[0045] Figure 10 Velocity spectrum of the fusion of refracted waves and reflected waves provided by an embodiment of the present invention;

[0046] Figure 11 The embodiment of the present invention provides a superimposed section (new section) of the Ulungu L03 line obtained by fusing the refraction wave and reflection wave information;

[0047] Figure 12 The superimposed section (old section) of the conventional reflection wave processing of the Ulungu L03 line provided in the embodiment of the present invention;

[0048] Figure 13 The old section (13a) and the new section (13b) of the 1-15 Hz low-frequency seismic data of the Ulungu L03 line provided in the embodiment of the present invention are shown in FIG. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0050] The Ulungu L03 line in the Ulungu area is the longest north-south survey line. The conventional seismic data stacking profile obtained by using reflection lines is shown in the following figure: Figure 12 As shown, from Figure 12 It can be seen that although the seismic acquisition technology has been improved, the low-frequency signals and far-offset data have been enhanced, and the quality of seismic data has been improved compared with before, the problems of seismic data in deep Carboniferous strata have not been completely solved: the reflection axis continuity is weak, the structure is not clear, and imaging is difficult; the fault zone is difficult to identify on the profile due to the severe stratum fragmentation and poor continuity.

[0051] It can be seen from this that in the process of conventional reflection seismic data processing, only the low-frequency signals of the near-offset data are protected, while most of the far-offset seismic data are removed, and this part of the information is not fully utilized. If the far-offset data is retained and the refraction wave seismic data processing method is introduced, the low-frequency and long-array advantages of the newly acquired seismic data can be fully utilized to effectively characterize the deep Carboniferous strata.

[0052] Therefore, in order to solve the above technical problems, this embodiment adopts the seismic data processing technology of refraction and reflection information fusion to reprocess the data in this area. Taking the L03 line as an example, the specific process is given.

[0053] Therefore, the present invention provides a deep seismic data processing method based on refraction-reflection information fusion, such as Figure 1 As shown, the following steps are included:

[0054] Step 100: forward modeling the acquired seismic data using a formation velocity model to identify refracted wave information in the seismic data;

[0055] In step 100, the steps for identifying the refracted wave information are as follows:

[0056] Step 101: Acquire depth-domain velocity field information of the study area, select a simulated earthquake source based on the high-speed layer position of the depth-domain velocity field information, and perform forward modeling on the simulated earthquake source to identify refracted wave information;

[0057] The method for obtaining the depth domain velocity field information of the study area is as follows:

[0058] The stacking velocity is obtained from the velocity analysis results of the conventional processing of the study area, and then the stacking velocity is converted into the depth domain layer velocity using Petrel software. Finally, the overall velocity field is interpolated using Matlab program to obtain the depth domain velocity field information of the study area.

[0059] Step 102: forward model the simulated earthquake source in the study area using a staggered grid high-order finite difference numerical simulation method of the acoustic wave equation to obtain a numerical simulation profile at the location of the simulated earthquake source, and identify the refracted wave information from an information graph of the numerical simulation profile.

[0060] The implementation of the staggered grid high-order finite difference numerical simulation method based on the acoustic wave equation is as follows:

[0061] First, the entire model is divided into spatial and temporal grids according to the spatial intervals dx, dy and the time interval dt;

[0062] Secondly, the high-order finite difference formula based on staggered grid technology is used to approximate the time derivative on the left side and the spatial derivative on the right side of the acoustic wave equation by difference.

[0063] Thirdly, the spatial model parameters, source location and source function are first given in space. At each time loop t, differential calculation and boundary processing are performed on the i-th grid in the x-direction and the j-th grid in the y-direction, and a wavefield snapshot is output.

[0064] Finally, the time loop ends and the simulated seismic profile is output.

[0065] When forward modeling the depth-domain velocity field information of the study area, if the stratigraphic fluctuations of the depth-domain velocity field information vary greatly, positions with deeper high-speed layers and positions with relatively shallow high-speed layers are selected as simulated earthquake sources, and forward simulation is performed on the selected simulated earthquake sources.

[0066] In this embodiment, the Ulungu L03 line in the Ulungu area is taken as the study area. Before the forward numerical simulation of the underground strata corresponding to the Ulungu L03 line in the Ulungu area is performed, the simulated earthquake source can be selected from the seismic data (the depth domain velocity field information of the Ulungu L03 line) by using the staggered grid high-order finite difference numerical simulation method based on the acoustic wave equation. According to the depth domain velocity field information of the Ulungu L03 line in the Ulungu area, it can be seen that Figure 2 As shown in the figure, due to the large north-south stratum fluctuations in the region, two earthquake source locations were selected for simulation. Source 1 is located in the southern part of the survey line, where the high-velocity layer is relatively deep; source 2 is located in the northern part of the survey line, where the high-velocity layer is relatively shallow.

[0067] A numerical simulation section of the simulated earthquake source is obtained from the simulated earthquake source, and then the refracted wave information is identified from the information diagram of the numerical simulation section. The specific implementation method is as follows: (taking a three-layer theoretical model as an example to illustrate the method of identifying refracted wave information in the numerical simulation section) the three-layer wave velocity of the stratum medium is obtained in sequence from top to bottom, and the reflected wave, refracted wave and direct wave are distinguished according to the change of the incident angle of the seismic wave;

[0068] Construct a two-dimensional time-distance coordinate axis and integrate the time-distance curves of reflected waves, refracted waves and direct waves in the same two-dimensional time-distance coordinate axis;

[0069] Based on the time-distance curves of the reflected wave, refracted wave and direct wave, in the numerical simulation section, the direct wave is used as the boundary, and the seismic information outside the direct wave is the refracted wave information.

[0070] Specifically, according to Figure 2 The velocity field information shown is as follows Figure 3 The program implementation process shown in the figure adopts the staggered grid forward numerical simulation method to simulate the underground strata corresponding to the Ulungu L03 line in the Ulungu area, and the results are as follows: Figure 4 and Figure 5 The figures show the comparison results of the numerical simulation profile at the first source position of the Ulungu L03 line and the actual earthquake profile, as well as the comparison results of the numerical simulation profile at the second source position of the Ulungu L03 line and the actual earthquake profile.

[0071] Comparison reveals that actual seismic data is rich in refraction wave information. The amplitude of this refraction wave information demonstrates high reflection intensity, minimal interference, and a high signal-to-noise ratio. Therefore, for ultra-deep underground formations, refraction wave information can be used to effectively predict and identify the structure and lithology of the subsurface. This feedback, when conducting actual seismic acquisition, maximizing the array length is crucial to capture as much wide-angle reflection information as possible.

[0072] Step 200: Cut the seismic data, perform velocity picking on the profile seismic data based on the time-distance characteristics of the refracted waves and the reflected waves, and form a refracted wave velocity spectrum and a reflected wave velocity spectrum.

[0073] In step 200, the time-distance characteristics of the refracted wave and the reflected wave are obtained as follows:

[0074] Taking the three-layer theoretical model as an example, the different characteristics of the reflected and refracted wave velocities over time are explained. Specifically, the three-layer velocities of the stratum medium are obtained sequentially from top to bottom, and the reflected, refracted, and direct waves are distinguished based on the changes in the incident angle of the seismic wave.

[0075] Construct a two-dimensional time-distance coordinate axis and integrate the time-distance curves of the reflected wave, refracted wave and direct wave in the same two-dimensional time-distance coordinate axis, such as Figure 6 As shown in the figure, the velocities of the three layers of stratum media from top to bottom are V0, V1, and V2, and V0<V1<V2. Figure 6 It can be seen that: ① the deeper the interface, the larger the blind zone (Mm2>Mm1); ② with the direct wave as the boundary, the time-distance curve velocity of the reflected wave at the near offset increases with time, while the time-distance curve velocity of the refracted wave at the far offset decreases with time.

[0076] The above analysis shows that there are obvious differences between conventional reflection waves and wide-angle reflection waves in seismic data, and they can be effectively distinguished and processed based on the direct wave.

[0077] Therefore, in step 200, when the seismic data is segmented, the steps for obtaining the separated refracted wave data and reflected wave data are as follows:

[0078] (1) The seismic data is cut based on the direct wave to obtain the separated refracted wave data and reflected wave data. Taking the Ulungu L03 line as an example, the separated refracted wave and reflected wave data are obtained by cutting the seismic data. Figure 7 (a) and Figure 7 (b) shown.

[0079] (2) Based on the temporal variation characteristics of the formation velocity corresponding to the reflection wave time-distance curve and the temporal variation characteristics of the formation velocity corresponding to the refracted wave time-distance curve, velocity picking is performed on the refracted wave data and the reflected wave data respectively to obtain the refracted wave velocity spectrum and the reflected wave velocity spectrum. Taking the Ulungu L03 line as an example, the obtained refracted wave velocity spectrum and reflected wave velocity spectrum are as follows: Figure 8 (a) and Figure 8 (b) shown.

[0080] (3) The seismic data of the entire study area are processed using the refraction wave velocity spectrum and the reflection wave velocity spectrum respectively to obtain the stacked profile obtained using the refraction wave velocity spectrum and the stacked profile obtained using the conventional reflection velocity spectrum.

[0081] According to Figure 8 The given refraction wave velocity spectrum and reflection wave velocity spectrum are used to process the seismic data of the entire section. The processing results are as follows: Figure 9 (a) and 9(b). Figure 9 (a) Figure 9 As can be seen in (b), the stacked profile obtained using the refraction velocity spectrum shows good continuity of deep events and relatively clear deep structures; whereas the stacked profile obtained using the conventional reflection velocity spectrum shows good continuity of shallow events and clear shallow structures. Therefore, it is necessary to fuse the refraction and reflection velocity spectra and use the fused velocity field to process the data for the entire profile.

[0082] Step 300: Superimpose the refracted wave velocity spectrum and the reflected wave velocity spectrum, and use the superimposed velocity spectrum obtained by merging the refracted wave and the reflected wave to process the profile data of the entire seismic data to obtain a new superimposed profile.

[0083] In step 300, the specific implementation method of selecting the velocity spectrum to be used from the refracted wave velocity spectrum and the reflected wave velocity spectrum based on the intersection time is as follows:

[0084] Will Figure 8 The refracted wave velocity spectrum and the reflected wave velocity spectrum shown in the figure are superimposed to find the time corresponding to the intersection of the refracted wave velocity spectrum and the reflected wave velocity spectrum. The part less than the intersection time uses the reflected wave velocity spectrum, and the part greater than the intersection time uses the refracted wave velocity spectrum. Finally, the fusion velocity spectrum of the two is obtained as shown in Figure 10 shown.

[0085] use Figure 10 The fusion velocity spectrum shown in FIG is used to process the seismic data of the entire section. Specifically, the refraction-reflection fusion velocity spectrum is used to stack the seismic data of the entire study area to obtain the final stacked section of the entire study area. Specifically, the new stacked section is as follows: Figure 11 By adding the new superimposed section ( Figure 11 ) and the old stacked section using only conventional reflection wave information ( Figure 12 ) Comparison shows that the deep area marked in the figure has clear strata and obvious structures. The 1-15Hz frequency band information was extracted from the new and old superimposed sections, such as Figure 13 (a) and 13(b), it is obvious from the figure that in the newly processed stacked section, due to the consideration of the refraction wave information, the low-frequency information is richer, which is the main reason for the clear deep reservoir structure.

[0086] This implementation uses the L03 line in the Ulungur region as an example to analyze the characteristics of the time-distance curves of refraction and reflection waves. It then presents a three-step seismic data processing technique for deep and ultra-deep reservoirs that fuses refraction and reflection information: forward modeling using a formation velocity model to identify refraction information; separation and processing of the refraction and reflection information to obtain refraction and reflection velocity spectra; and superimposing the refraction and reflection velocity spectra, using the fused velocity field to process data across the entire profile. This technique combines the advantages of both refraction and reflection seismic data processing. By introducing refraction information, it enriches the low-frequency information in the seismic data and reduces the shielding effect of high-velocity layers, making the deep events clearer and the stratigraphic structure more defined. This technique provides a strong basis for the exploration and development of deep and ultra-deep reservoirs.

[0087] The above embodiments are merely exemplary embodiments of the present application and are not intended to limit the scope of the present application. The scope of protection of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and scope of protection of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the scope of protection of the present application.

Claims

1. A deep seismic data processing method based on refraction-reflection information fusion, characterized in that: The steps include: Step 100: forward modeling the acquired seismic data using a formation velocity model to identify refraction wave information in the seismic data; Step 200, cutting the seismic data, performing velocity picking on the profile seismic data based on the time-distance characteristics of the refracted wave and the reflected wave, and forming a refracted wave velocity spectrum and a reflected wave velocity spectrum; Step 300: superimpose the refracted wave velocity spectrum and the reflected wave velocity spectrum, and use the superimposed velocity spectrum obtained by merging the refracted wave and the reflected wave to process the profile data of the entire seismic data to obtain a new superimposed profile.

2. The deep seismic data processing method based on refraction-reflection information fusion according to claim 1, characterized in that: In step 100, the steps for identifying the refracted wave information are: Acquire the depth domain velocity field information of the study area, and select the simulated earthquake source based on the high-speed layer position of the depth domain velocity field information; The staggered grid high-order finite difference numerical simulation method of the acoustic wave equation is used to perform forward simulation on the simulated earthquake source in the study area, obtain the numerical simulation section at the location of the simulated earthquake source, and identify the refracted wave information from the information graph of the numerical simulation section.

3. The deep seismic data processing method based on refraction-reflection information fusion according to claim 2, characterized in that: The realization method of refraction wave information recognition is as follows: The multi-layer wave velocity of the stratum medium is obtained in order from top to bottom, and the reflected wave, refracted wave and direct wave are distinguished according to the change of the incident angle of the seismic wave; Construct a two-dimensional time-distance coordinate axis, and integrate the time-distance curves of the reflected wave, the refracted wave and the direct wave in the same two-dimensional time-distance coordinate axis; Based on the time-distance curves of the reflected wave, refracted wave and direct wave, the direct wave is used as the boundary in the numerical simulation section, and the seismic information outside the direct wave is the refracted wave information.

4. The deep seismic data processing method based on refraction-reflection information fusion according to claim 2, characterized in that: The implementation of the staggered grid high-order finite difference numerical simulation method based on the acoustic wave equation is as follows: First, the entire model is divided into spatial and temporal grids according to the spatial intervals dx, dy and the time interval dt; Secondly, the time derivative on the left side and the space derivative on the right side of the acoustic wave equation are approximated by difference using a high-order finite difference formula based on staggered grid technology; Thirdly, the spatial parameters of the model, the location of the earthquake source and the earthquake source function are given first in space. At each time cycle t, the difference calculation and boundary processing are performed on the i-th grid in the x direction and the j-th grid in the y direction, and the wave field snapshot is output. Finally, the time loop ends and the simulated seismic profile is output.

5. The deep seismic data processing method based on refraction-reflection information fusion according to claim 2, characterized in that: The implementation method of obtaining the depth domain velocity field information of the study area is: The stacking velocity is obtained from the velocity analysis results of the conventional processing of the study area, and then the stacking velocity is converted into the depth domain layer velocity using petrol software. Finally, the overall velocity field is interpolated using Matlab program to obtain the depth domain velocity field information of the study area.

6. The deep seismic data processing method based on refraction-reflection information fusion according to claim 2, characterized in that: In step 200, the time-distance characteristics of the refracted wave and the reflected wave are obtained by: The multi-layer wave velocity of the stratum medium is obtained in order from top to bottom, and the reflected wave, refracted wave and direct wave are distinguished according to the change of the incident angle of the seismic wave; Construct a two-dimensional time-distance coordinate axis, and integrate the time-distance curves of the reflected wave, the refracted wave and the direct wave in the same two-dimensional time-distance coordinate axis; Based on the time-distance curves of the reflected wave, refracted wave and direct wave, the time-distance characteristics of the refracted wave and the reflected wave are obtained, that is, with the direct wave as the boundary, the speed of the time-distance curve of the reflected wave increases with time, and the speed of the time-distance curve of the refracted wave decreases with time.

7. The deep seismic data processing method based on refraction-reflection information fusion according to claim 6, characterized in that: The steps for cutting the actual seismic data to obtain the separated refraction wave data and reflection wave data are as follows: The actual seismic data is cut based on the direct wave to obtain separated refracted wave data and reflected wave data; Based on the changing characteristics that the formation velocity corresponding to the reflection wave time-distance curve increases with time, and the changing characteristics that the formation velocity corresponding to the refracted wave time-distance curve decreases with time, the refracted wave data and the reflected wave data are velocity picked up respectively to obtain the refracted wave velocity spectrum and the reflected wave velocity spectrum.

8. The deep seismic data processing method based on refraction-reflection information fusion according to claim 6, characterized in that: In step 300, the specific implementation method of selecting the velocity spectrum to be used from the refracted wave velocity spectrum and the reflected wave velocity spectrum based on the crossover time is: The time corresponding to the intersection of the refracted wave velocity spectrum and the reflected wave velocity spectrum is found, and the portion less than the intersection time uses the reflected wave velocity spectrum, and the portion greater than the intersection time uses the refracted wave velocity spectrum, ultimately obtaining a velocity spectrum that is a fusion of the refracted wave velocity spectrum and the reflected wave velocity spectrum.

9. The deep seismic data processing method based on refraction-reflection information fusion according to claim 8, characterized in that: The seismic data of the entire study area are stacked using the refraction-reflection fusion velocity spectrum to obtain the final stacked section of the entire study area.

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