Complex structure region time domain velocity modeling method and imaging method
By performing velocity scanning and spectral analysis in complex structural areas, the advantageous frequency bands are obtained and the speed is picked up along the structural direction, the problem of poor velocity modeling accuracy in complex structural areas is solved, and better stratigraphic imaging effects and data quality are achieved.
Patent Information
- Application Number
- CN202311430403.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-10-31
- Publication Date
- 2025-05-02
AI Technical Summary
In complex structural areas, it is difficult for the prior art to obtain accurate velocity fields, resulting in poor velocity modeling accuracy and unsatisfactory imaging effects.
By performing velocity scanning in complex structural areas, the macroscopic law of velocity change is obtained, the dominant frequency band is obtained using spectral analysis, the velocity spectrum and channel set are strengthened, the velocity spectrum is picked up along the structural direction, and the velocity model is established.
It improves the aggregation of the velocity spectrum and the accuracy of velocity modeling, improves the stratigraphic imaging effect in complex tectonic areas, and improves the quality of seismic data.
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Figure CN119916447A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the field of seismic data processing, and in particular relates to a time domain velocity modeling method and an imaging method for a complex structural area. Background Art
[0002] In the whole process of seismic data processing, velocity is an important parameter of seismic data processing. The main purpose of velocity analysis is to provide processing parameters for horizontal stacking, migration and other processing. The method used is based on the best estimation of multi-channel signals on the common reflection point gather. Therefore, the accuracy of velocity directly affects the quality of processing.
[0003] In order to ensure the accuracy of processing, it is necessary to obtain an accurate velocity field. Velocity analysis based on velocity spectrum is currently the main velocity analysis method for time domain processing, but in complex structural areas, the data signal-to-noise ratio is low, the terrain wave impedance interface is not obvious, the generated velocity spectrum energy group resolution is low, the velocity modeling accuracy is poor, and the imaging effect is not ideal. Summary of the invention
[0004] The purpose of the present invention is to solve the above-mentioned problems existing in the prior art and provide a time domain velocity modeling method for complex structural areas.
[0005] The present invention is achieved through the following technical solutions: A velocity modeling method in the time domain of a complex structural area, comprising the following steps:
[0006] The macroscopic law of velocity variation is obtained based on the velocity scanning profile of the complex structural area;
[0007] Obtain the dominant frequency band through spectrum analysis, and generate velocity spectrum and gathers by strengthening the dominant frequency band;
[0008] Pick up the velocity on the velocity spectrum along the structural strike under the premise of following the macroscopic law of velocity change;
[0009] A velocity model is established based on the gathers and the velocities picked up on the velocity spectrum.
[0010] Furthermore, before picking up the velocity, the density of velocity analysis points is increased in the lateral direction on the velocity spectrum.
[0011] Furthermore, a velocity scanning profile of a complex structural area is obtained by equal-proportional velocity scanning or constant velocity scanning.
[0012] Furthermore, the macroscopic law of velocity variation includes the law of velocity variation with depth and the law of lateral velocity variation.
[0013] Furthermore, fine picking is performed on the velocity spectrum, including paying attention to the target layer reflection wave group during the picking process, that is, the velocity of the reflection layer corresponding to the gathering picking interface.
[0014] Furthermore, fine picking is performed on the velocity spectrum, including taking into account the velocity trends of surrounding points during picking, to avoid the phenomenon that the velocity of the picking point changes suddenly relative to the surrounding points.
[0015] Furthermore, fine picking is performed on the velocity spectrum, including uniform spacing between picking points.
[0016] Furthermore, fine picking is performed on the velocity spectrum, including taking into account both imaging quality and picking cost, and picking up as many velocity points as possible.
[0017] The present invention also provides an imaging method for a complex structural area. According to the velocity model obtained by the velocity modeling method in the time domain of a complex structural area described in the present invention, the velocity of each reflection interface is obtained according to the velocity model, and the velocity of the reflection interface corrects the velocity scanning profile of the complex structural area.
[0018] Furthermore, the optimum imaging speed range is determined by constant speed scanning, and correction is performed based on the speed scanning profile having the optimum imaging range.
[0019] Compared with the prior art, the beneficial effects of the present invention include:
[0020] The present invention utilizes the energy enhancement technology of the dominant frequency band to effectively improve the aggregation of the velocity spectrum, and then combines the means of velocity spectrum scanning, velocity spectrum encryption, structural strike velocity picking, etc., to integrate multiple means to effectively improve the accuracy of velocity modeling and improve the imaging effect of formations in complex structural areas. It can effectively improve the accuracy of velocity modeling in complex areas of seismic data, thereby improving the imaging effect of data and improving data quality. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Figure 1 Flow chart for fine velocity modeling in complex structural areas of seismic data;
[0022] Figure 2 This is a constant velocity scanning profile of a complex structural area;
[0023] Figure 3 (a) is a schematic diagram of traditional acquisition direction speed picking;
[0024] Figure 3 (b) is a schematic diagram of geological dip velocity picking;
[0025] Figure 4 A schematic diagram of velocity analysis points in complex structural areas;
[0026] Figure 5 (a) Velocity spectrum and gathers before the dominant frequency band is enhanced;
[0027] Figure 5 (b) Velocity spectrum and gathers after the dominant frequency band is enhanced;
[0028] Figure 6 Velocity model for complex tectonic areas;
[0029] Figure 7 (a) Stratigraphic section before fine velocity modeling;
[0030] Figure 7 (b) Stratigraphic section before and after fine velocity modeling; DETAILED DESCRIPTION
[0031] Complex structural areas include limestone outcropping areas and high-steep structural belts. In the process of seismic data processing, the data quality in complex structural areas is poor, the seismic wave field is complex, and the velocity analysis accuracy directly affects the data imaging effect. For limestone areas, complex surfaces, complex structures, and low signal-to-noise ratio areas, multi-factor comprehensive velocity picking can effectively improve the accuracy of velocity modeling and improve data imaging effects.
[0032] Therefore, the present invention provides a velocity modeling method in the time domain of a complex structural area, comprising the following steps:
[0033] The macroscopic law of velocity variation is obtained based on the velocity scanning profile of the complex structural area;
[0034] Obtain the dominant frequency band through spectrum analysis, and generate velocity spectrum and gathers by strengthening the dominant frequency band;
[0035] Pick up the velocity on the velocity spectrum along the structural strike under the premise of following the macroscopic law of velocity change;
[0036] A velocity model is established based on the gathers and the velocities picked up on the velocity spectrum.
[0037] Preferably, before picking up the velocity, the density of velocity analysis points is increased in the lateral direction on the velocity spectrum.
[0038] Preferably, the velocity scanning profile of the complex structural area is obtained by equal-proportional velocity scanning or constant velocity scanning.
[0039] Preferably, the macroscopic law of velocity variation includes the law of velocity variation with depth and the law of velocity lateral variation.
[0040] Preferably, fine picking is performed on the velocity spectrum, including paying attention to the target layer reflection wave group during the picking process, that is, the velocity of the reflection layer corresponding to the gathering picking interface.
[0041] Preferably, fine picking is performed on the velocity spectrum, including taking into account the velocity trends of surrounding points during picking, so as to avoid a sudden change in the velocity of the picking point relative to the surrounding points.
[0042] Preferably, fine picking is performed on the velocity spectrum, including uniform spacing between picking points.
[0043] Preferably, fine picking is performed on the velocity spectrum, including taking into account both imaging quality and picking cost, and picking as many velocity points as possible.
[0044] The present invention also provides an imaging method for a complex structural area. A velocity model is obtained according to the velocity modeling method in the time domain of a complex structural area described in the present invention. The velocity of each reflection interface is obtained according to the velocity model. The velocity of the reflection interface corrects the velocity scanning profile of the complex structural area.
[0045] Preferably, the optimum imaging speed range is determined by constant speed scanning, and correction is performed based on a speed scanning profile having the optimum imaging range.
[0046] The present invention utilizes the energy enhancement technology of the dominant frequency band to effectively improve the aggregation of the velocity spectrum, and then combines the means of velocity spectrum scanning, velocity spectrum encryption, structural strike velocity picking, etc., to integrate multiple means to effectively improve the accuracy of velocity modeling and improve the imaging effect of formations in complex structural areas. It can effectively improve the accuracy of velocity modeling in complex areas of seismic data, thereby improving the imaging effect of data and improving data quality.
[0047] Example 1
[0048] The flowchart of this embodiment refers to Figure 1 As shown, the following steps are included:
[0049] (1) In view of the poor focusing of velocity spectra in complex structural areas, velocity scans were conducted, including proportional velocity scans and constant velocity scans, so as to understand the macroscopic velocity variation law of high-steep structures. The macroscopic velocity law refers to the law of velocity variation with depth and the law of lateral velocity variation.
[0050] Subsequent fine picking must be carried out under the guidance of macroscopic laws, which is equivalent to understanding the changing trend of speed and picking up the speed according to the speed trend.
[0051] (2) Regional velocity densification is carried out in complex structural areas to increase the density of velocity analysis points. For example, the density of velocity analysis points is changed from 400 m x 400 m to 200 m x 200 m to adapt to the dramatic changes in velocity in the lateral direction.
[0052] Encrypt the lateral speed analysis points to adapt to the drastic changes in the lateral direction. Each speed analysis point represents the speed of the position being analyzed, and the number of encrypted speed analysis points is the same as the number of encrypted speed analysis points. By encrypting the speed analysis points, the drastic changes in the lateral speed can be adapted, and the lateral speed picking accuracy can be improved.
[0053] (3) The energy of the dominant frequency band is enhanced in complex structural areas. After the dominant frequency band is enhanced, the energy of the velocity spectrum is better focused, which is conducive to velocity picking.
[0054] Through spectral analysis, the imaging advantage frequency band is optimized to generate velocity spectrum and channel gathers. The energy of energy clusters is enhanced and more concentrated, which is conducive to fine velocity picking.
[0055] This step can obtain the dominant frequency band through spectrum analysis, and is independent of the processing results of steps (1) and (2). This step can be processed in parallel with steps (1) and (2).
[0056] (4) In view of the characteristics of complex structural geological trends, the traditional acquisition direction velocity analysis method is changed. Traditionally, acquisition is performed along the detection line direction. This embodiment performs velocity analysis in steps along the structural trend, which makes it easier to grasp the velocity law.
[0057] At the same time, during the speed picking process, fine picking is performed on the speed spectrum:
[0058] ① When picking, take into account the speed trend of surrounding points to avoid sudden changes in the speed of the picking point relative to the surrounding points;
[0059] ② Perform fine picking on the velocity spectrum, including uniform spacing between picking points.
[0060] ③ Consider both imaging quality and picking cost, and pick up as many speed points as possible.
[0061] Focus on "fineness" and make meticulous carvings to strive for the best imaging effect.
[0062] Example 2
[0063] This embodiment is carried out in a limestone outcrop area in a certain region.
[0064] (1) In view of the poor focusing of the velocity spectrum in the limestone outcrop area, velocity scans were carried out, including proportional velocity scans and constant velocity scans, so as to understand the macroscopic velocity variation law of high-steep structures. The macroscopic velocity law refers to the law of velocity variation with depth and the law of lateral velocity variation.
[0065] Subsequent fine picking must be carried out under the guidance of macroscopic laws, which is equivalent to understanding the changing trend of speed and picking up the speed according to the speed trend.
[0066] (2) Regional velocity densification is carried out in the limestone outcrop area to increase the density of velocity analysis points. For example, the density of velocity analysis points is changed from 400 m x 400 m to 200 m x 200 m to adapt to the dramatic changes in velocity in the lateral direction.
[0067] Encrypt the lateral speed analysis points to adapt to the drastic changes in the lateral direction. Each speed analysis point represents the speed of the position being analyzed, and the number of encrypted speed analysis points is the same as the number of encrypted speed analysis points. By encrypting the speed analysis points, the drastic changes in the lateral speed can be adapted, and the lateral speed picking accuracy can be improved.
[0068] (3) The energy of the dominant frequency band is enhanced in the limestone outcrop area. After the dominant frequency band is enhanced, the energy focusing of the velocity spectrum is better, which is conducive to velocity picking.
[0069] Through spectral analysis, the imaging advantage frequency band is optimized to generate velocity spectrum and channel gathers. The energy of energy clusters is enhanced and more concentrated, which is conducive to fine velocity picking.
[0070] This step can obtain the dominant frequency band through spectrum analysis, and is independent of the processing results of steps (1) and (2). This step can be processed in parallel with steps (1) and (2).
[0071] (4) In view of the geological trend characteristics of the limestone outcropping area, the traditional acquisition direction velocity analysis method is changed. The traditional method is to collect along the detection line direction. This embodiment performs velocity analysis in steps along the structural trend, which makes it easier to grasp the velocity law.
[0072] At the same time, during the speed picking process, fine picking is performed on the speed spectrum:
[0073] ① When picking, take into account the speed trend of surrounding points to avoid sudden changes in the speed of the picking point relative to the surrounding points;
[0074] ② Perform fine picking on the velocity spectrum, including uniform spacing between picking points.
[0075] ③ Consider both imaging quality and picking cost, and pick up as many speed points as possible.
[0076] Focus on "fineness" and make meticulous carvings to strive for the best imaging effect.
[0077] Figure 2 This is a constant velocity scanning profile of a limestone outcrop area in a certain region. Due to poor surface excitation conditions and complex underground structures, the data imaging effect is poor. Through constant velocity scanning, the optimal imaging velocity range of the data can be determined.
[0078] The basis for judging the best imaging speed is the good continuity of the in-phase axis imaging. Figure 2 The best imaging speed is 5000~5500.
[0079] Figure 3 This is a schematic diagram of geological dip velocity picking. According to the characteristics of the high-steep structural geological trend, the traditional acquisition direction velocity analysis method is changed, and velocity analysis is performed along the structural trend, which makes it easier to grasp the velocity law.
[0080] Figure 4 A schematic diagram of velocity analysis point encryption for complex structural areas is provided. By encrypting velocity analysis points, the drastic changes in lateral velocity can be adapted and the lateral velocity picking accuracy can be improved. Figure 4The medium black shadow indicates that the velocity analysis points of the structural part have been encrypted.
[0081] Figure 5 Velocity spectra and gathers before (left) and after (right) enhancement of the dominant frequency band. For complex and steep areas, the data frequency decays quickly. The velocity spectrum and gathers produced by the traditional full-band velocity method are of poor quality. The velocity spectrum energy cluster diverges and the continuity of the gather event axis is poor. Through spectral analysis, the imaging dominant frequency band is optimized to produce velocity spectra and gathers. The energy cluster is enhanced and more concentrated, which is conducive to fine velocity picking.
[0082] Through the combination of the above methods, a velocity model for complex structural areas was established based on the velocity points that were carefully picked and satisfied the velocity law, such as Figure 6 As shown, Figure 7 Profiles before (left) and after (right) fine velocity modeling. Through fine velocity modeling, imaging in complex high-steep areas is significantly improved, diffraction wave positioning is more accurate, and the structural morphology is more reasonable.
[0083] A velocity model is obtained according to a velocity modeling method in the time domain of a complex structural area, and the velocity of each reflection interface is obtained according to the velocity model. The velocity of the reflection interface corrects the velocity scanning profile of the complex structural area. Figure 6 Get the speed of each reflection interface in Figure 7 (a) is used to correct the complex high and steep areas.
[0084] Example 3
[0085] This embodiment is carried out for a high and steep structural zone in a certain area.
[0086] (1) In view of the poor focusing of velocity spectrum in high-steep structures, velocity scans were carried out, including proportional velocity scans and constant velocity scans, so as to understand the macroscopic velocity variation law of high-steep structures. The macroscopic velocity law refers to the law of velocity variation with depth and the law of lateral velocity variation.
[0087] Subsequent fine picking must be carried out under the guidance of macroscopic laws, which is equivalent to understanding the changing trend of speed and picking up the speed according to the speed trend.
[0088] (2) Regional velocity densification is carried out for high and steep structural zones, and the density of velocity analysis points is increased. For example, the density of velocity analysis points is changed from 400 m x 400 m to 150 m x 150 m to adapt to the dramatic changes in velocity in the lateral direction.
[0089] Encrypt the lateral speed analysis points to adapt to the drastic changes in the lateral direction. Each speed analysis point represents the speed of the position being analyzed, and the number of encrypted speed analysis points is the same as the number of encrypted speed analysis points. By encrypting the speed analysis points, the drastic changes in the lateral speed can be adapted, and the lateral speed picking accuracy can be improved.
[0090] (3) The energy of the dominant frequency band is enhanced for the high-steep structural zone. After the dominant frequency band is enhanced, the energy focusing of the velocity spectrum is better, which is conducive to velocity picking.
[0091] Through spectral analysis, the imaging advantage frequency band is optimized to generate velocity spectrum and channel gathers. The energy of energy clusters is enhanced and more concentrated, which is conducive to fine velocity picking.
[0092] This step can obtain the dominant frequency band through spectrum analysis, and is independent of the processing results of steps (1) and (2). This step can be processed in parallel with steps (1) and (2).
[0093] (4) In view of the geological trend characteristics of the high-steep structural belt, the traditional acquisition direction velocity analysis method is changed. The traditional method is to collect along the detection line direction. This embodiment performs velocity analysis in steps along the structural trend, which makes it easier to grasp the velocity law.
[0094] At the same time, during the speed picking process, fine picking is performed on the speed spectrum:
[0095] ① When picking, take into account the speed trend of surrounding points to avoid sudden changes in the speed of the picking point relative to the surrounding points;
[0096] ② Perform fine picking on the velocity spectrum, including uniform spacing between picking points.
[0097] ③ Consider both imaging quality and picking cost, and pick up as many speed points as possible.
[0098] Focus on "fineness" and make meticulous carvings to strive for the best imaging effect.
[0099] Due to poor surface excitation conditions and complex underground structures, the data imaging effect is poor. By scanning at a constant speed, the optimal imaging speed range of the data can be determined. The basis for determining the optimal imaging speed is good continuity of the event axis imaging.
[0100] According to the geological trend characteristics of high-steep structures, the traditional velocity analysis method of acquisition direction is changed, and velocity analysis is carried out along the structural trend, which makes it easier to grasp the velocity law.
[0101] By encrypting the speed analysis points and adapting to the drastic changes in lateral speed, the lateral speed picking accuracy can be improved.
[0102] In complex and steep areas, the data frequency decays quickly, and the velocity spectrum and gathers produced by the traditional full-band velocity method are of poor quality. The velocity spectrum energy cluster diverges, and the continuity of the gather event axis is poor. Through spectral analysis, the imaging advantage frequency band is optimized to produce velocity spectrum and gathers. The energy of the energy cluster is enhanced and more concentrated, which is conducive to fine velocity picking.
[0103] Through the combination of the above methods, a velocity model for complex structural areas was established based on velocity points that were carefully picked and satisfied the velocity law. Through fine velocity modeling, the imaging of complex high-steep areas was significantly improved, the diffraction wave positioning was more accurate, and the structural morphology was more reasonable.
[0104] A velocity model is obtained according to a velocity modeling method in the time domain of a complex structural area, and the velocity of each reflection interface is obtained according to the velocity model. The velocity of the reflection interface corrects the velocity scanning profile of the complex structural area.
[0105] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.
[0106] In the description of the present invention, unless otherwise specified, the terms "upper", "lower", "left", "right", "inside", "outside", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they cannot be understood as limitations on the present invention.
[0107] The above technical scheme is only a specific implementation method of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the principles disclosed in the present invention, and it is not limited to the technical scheme described in the above specific embodiments of the present invention. Therefore, the above description is only preferred and does not have a restrictive meaning.
Claims
1. A velocity modeling method in the time domain of a complex structural area, characterized in that: The following steps are involved: The macroscopic law of velocity variation is obtained based on the velocity scanning profile of the complex structural area; Obtain the dominant frequency band through spectrum analysis, and generate velocity spectrum and gathers by strengthening the dominant frequency band; Pick up the velocity on the velocity spectrum along the structural strike under the premise of following the macroscopic law of velocity change; A velocity model is established based on the gathers and the velocities picked up on the velocity spectrum.
2. The velocity modeling method in the time domain of a complex structural area according to claim 1 is characterized in that: Before picking up the velocity, the density of velocity analysis points is increased in the lateral direction on the velocity spectrum.
3. The velocity modeling method in the time domain of a complex structural area according to claim 1 is characterized in that: The velocity scanning profile of the complex structural area is obtained by proportional velocity scanning or constant velocity scanning.
4. The velocity modeling method in the time domain of a complex structural area according to claim 1 is characterized in that: The macroscopic law of velocity variation includes the law of velocity variation with depth and the law of lateral velocity variation.
5. The velocity modeling method in the time domain of a complex structural area according to claim 1 is characterized in that: Fine picking is performed on the velocity spectrum, including paying attention to the target layer reflection wave group during the picking process, that is, the velocity of the reflection layer corresponding to the gathering picking interface.
6. The velocity modeling method in the time domain of a complex structural area according to claim 1 is characterized in that: Perform fine picking on the velocity spectrum, including taking into account the velocity trends of surrounding points when picking, to avoid sudden changes in the velocity of the picking point relative to the surrounding points.
7. The velocity modeling method in the time domain of a complex structural area according to claim 1 is characterized in that: Fine picking is performed on the velocity spectrum, including even spacing between picking points.
8. The velocity modeling method in the time domain of a complex structural area according to claim 1 is characterized in that: Perform fine picking on the velocity spectrum, taking into account both imaging quality and picking cost, and picking as many velocity points as possible.
9. A method for imaging a complex structural area, characterized in that: A velocity model is obtained according to the velocity modeling method in the time domain of a complex structural area according to any one of claims 1 to 8, and the velocity of each reflection interface is obtained according to the velocity model. The velocity scanning profile of the complex structural area is corrected by the velocity of the reflection interface.
10. The imaging method of complex structural areas according to claim 9, characterized in that: The optimum imaging speed range is determined by constant speed scanning, and correction is performed based on the speed scanning profile with the optimum imaging range.