Self-adaptive time window calculation method and device for offset attribute

Abstract

The invention belongs to the technical field of seismic exploration, and particularly discloses an offset attribute-oriented adaptive time window calculation method and device, and the method comprises the steps: carrying out the superposition of a pre-stack seismic channel set according to different offsets, and obtaining a plurality of offset superposition bodies; and calculating time windows of all the offset superposition bodies at all the sampling points. According to the offset attribute-oriented adaptive time window calculation method provided by the invention, the offset information in the pre-stack seismic data is fully excavated, and the time windows of a plurality of offset stack bodies at all sampling points, which are obtained by stacking the pre-stack seismic trace sets, are calculated, so that effective representation of complex geological anomalous bodies such as fractures-cracks and river channels is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of seismic exploration, and particularly relates to an adaptive time window calculation method and device for offset attributes. Background Art

[0002] Seismic data contains a large amount of relevant formation information. How to accurately extract various information in seismic data and obtain relevant reservoir information through seismic attribute analysis is one of the key research points for geological personnel at present.

[0003] In reservoir prediction, to find seismic attributes related to reservoir characteristics, it is first necessary to ensure that the seismic attributes come from the target geological body, so the selection of the time window is very crucial. If the selected time window is too small, on the one hand, the geological target will be outside the extraction range, and on the other hand, the too-small time window will affect the effectiveness of some parameters; while if the selected time window is too large, the characteristics of the geological target will be abnormally submerged in other background anomalies.

[0004] In recent years, various method technologies have been developed for the identification and description of complex oil and gas reservoirs. Many attribute calculation technologies are carried out using post-stack seismic data, including conventional amplitude attributes and complex post-stack attribute technologies such as edge detection, eigen coherence, curvature, and ant body; when calculating using these post-stack attributes, the optimal selection of the time window can often be predicted because the main frequency range of a single post-stack data volume is fixed. For the pre-stack offset gather stacked body, since the frequency of the gather decreases as the offset increases, that is, the event axis becomes fatter, the frequency band ranges of different offsets are different. For example, the main frequency range of the near offset is often higher than that of the far offset.

[0005] Based on this technical background, the present invention studies an adaptive time window calculation method and device for offset attributes. Summary of the Invention

[0006] Aiming at the deficiencies of the prior art, the present invention provides an adaptive time window calculation method and device for offset attributes. This method fully excavates the offset information in pre-stack seismic data, and realizes the effective characterization of complex geological anomalies such as faults - fractures and channels by calculating the time windows of multiple offset stacked bodies obtained by stacking pre-stack seismic gathers at all sampling points.

[0007] To achieve the above object, the first aspect of the present invention provides an adaptive time window calculation method for offset attributes, including:

[0008] Stacking pre-stack seismic gathers by different offsets respectively to obtain multiple offset stacked bodies;

[0009] Calculating the time windows of each offset stacked body at all sampling points.

[0010] The second aspect of the present invention provides an adaptive time window calculation method for offset attributes, including:

[0011] A stacking module for stacking pre-stack seismic gathers separately according to different offsets to obtain a plurality of offset stacked volumes;

[0012] A calculation module for calculating the time windows of each offset stacked volume at all sampling points.

[0013] The third aspect of the present invention provides an electronic device, which includes:

[0014] A memory storing executable instructions;

[0015] A processor that runs the executable instructions in the memory to implement the adaptive time window calculation method for offset attributes described in the first aspect.

[0016] The fourth aspect of the present invention provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the adaptive time window calculation method for offset attributes described in the first aspect.

[0017] The beneficial effects of the present invention include:

[0018] (1) The adaptive time window calculation method for offset attributes provided by the present invention fully exploits the offset information in pre-stack seismic data. By calculating the time windows of a plurality of offset stacked volumes obtained by stacking pre-stack seismic gathers at all sampling points, it realizes an effective characterization of complex geological anomalies such as faults - fractures and river channels.

[0019] (2) The adaptive time window calculation method for offset attributes provided by the present invention makes the time windows of the medium-offset stacked volume or the near-medium-offset stacked volume consistent with the time window of the three-dimensional data volume of the time window, and circularly calculates the time windows of each offset stacked volume at all sampling points, avoiding the problem of inaccurate time window calculation in the prior art.

[0020] (3) The adaptive time window calculation method for offset attributes provided by the present invention performs spectral analysis calculation within the time window of each offset stacked volume at a certain sampling point to obtain the maximum effective main frequency of each data volume, and calculates the wavelength of each offset stacked volume at this sampling point based on the maximum effective main frequency and the seismic velocity, greatly ensuring the accuracy of time window calculation.

[0021] Other features and advantages of the present invention will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and other objects, features, and advantages of the present invention will become more apparent by describing the exemplary embodiments of the present invention in more detail with reference to the accompanying drawings.

[0023] Figure 1 It is a flowchart of the adaptive time window calculation method for offset attributes proposed by the present invention.

[0024] Figure 2 It is a schematic diagram of four offset stack profiles in a certain seismic work area.

[0025] Figure 3 It is a schematic diagram of the along-layer attribute effect of the near offset obtained by using the adaptive time window calculation method for offset attributes in the first embodiment of the present invention.

[0026] Figure 4 It is a schematic diagram of the along-layer attribute effect of the medium offset obtained by using the adaptive time window calculation method for offset attributes in the first embodiment of the present invention.

[0027] Figure 5 It is a schematic diagram of the along-layer attribute effect of the far offset obtained by using the adaptive time window calculation method for offset attributes in the first embodiment of the present invention. Detailed implementation manners

[0028] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0029] The present invention proposes an adaptive time window calculation method for offset attributes, as Figure 1 shown, including:

[0030] Stacking the pre-stack seismic trace gathers by different offsets respectively to obtain multiple offset stacks;

[0031] Calculating the time windows of each offset stack at all sampling points.

[0032] The method in the present invention fully exploits the offset information in the pre-stack seismic data, and realizes the effective characterization of complex geological anomalies such as faults-fractures and channels by calculating the time windows of multiple offset stacks obtained by stacking the pre-stack seismic trace gathers at all sampling points.

[0033] According to the present invention, calculating the time windows of each offset stack at all sampling points includes:

[0034] Setting the time window of the medium offset stack or the near-medium offset stack at a certain sampling point;

[0035] Calculating the wavelength of each offset stack at this sampling point;

[0036] The time window of the remaining offset stacks at this sampling point is calculated based on the time window and the wavelengths of each offset stack.

[0037] Calculate the time windows of each offset stack at the remaining sampling points in a loop.

[0038] When the number of offset stacks is odd, set the time window of the middle offset stack at a certain sampling point.

[0039] When the number of offset stacks is even, set the time window of any near-middle offset stack at a certain sampling point.

[0040] According to the present invention, calculating the wavelength of each offset stack at this sampling point includes:

[0041] Perform spectral analysis calculation within the time window of each offset stack at this sampling point to obtain the maximum effective main frequency of each data volume.

[0042] Based on the well-side trace seismic data at this sampling point, obtain the time-depth relationship, or use the existing time-depth relationship to calculate the seismic velocity of each offset stack at this sampling point.

[0043] Calculate the wavelength of each offset stack at this sampling point based on the maximum effective main frequency and the seismic velocity.

[0044] In the present invention, by performing spectral analysis calculation within the time window of each offset stack at a certain sampling point to obtain the maximum effective main frequency of each data volume, and calculating the wavelength of each offset stack at this sampling point based on the maximum effective main frequency and the seismic velocity, the accuracy of time window calculation is greatly guaranteed.

[0045] Preferably, the time windows of each offset stack at all sampling points are subjected to rounding operations.

[0046] According to the present invention, if the values of the time windows of each offset stack after rounding operations at a certain sampling point are close or equal, reduce or increase one sampling point near the sampling point in the order from near to far offset distance.

[0047] Preferably, multiple offset stacks form a three-dimensional data volume;

[0048] The three-dimensional data volume includes multiple main survey lines, multiple connecting survey lines, and multiple seismic traces;

[0049] Multiple sampling points are provided on each seismic trace.

[0050] Preferably ， The number of sampling points on the three-dimensional data volume is the product of the numbers of the main survey lines, the connecting survey lines, and the seismic traces.

[0051] In the present invention, by making the time windows of the time-window 3D data volume of the medium-offset stack or the near-medium-offset stack consistent, the time windows of each offset stack at all sampling points are calculated cyclically, avoiding the problem of inaccurate time-window calculation in the prior art.

[0052] The present invention will be described in more detail below through embodiments.

[0053] Embodiment 1:

[0054] This embodiment presents a specific implementation process of an adaptive time-window calculation method for offset attributes, including the following steps:

[0055] 1) Form three offset stacks:

[0056] Stack the offset gather from 0 m to 1800 m, denoted as the near-offset stack;

[0057] Stack the offset gather from 1801 m to 3600 m, denoted as the medium-offset stack;

[0058] Stack the gather from 3601 m to 5400 m, denoted as the far-offset stack;

[0059] 2) Select the time window at a certain sampling point time of the medium-offset stack as Tmid:

[0060] Since the frequency band range of the medium offset is consistent with that of the 3D data volume, the time window for attribute calculation at this sampling point based on the medium offset can also be denoted as Twin;

[0061] 3) Calculate the maximum effective main frequencies at the sampling point time for different offset volumes as Fnear, Fmid, and Far:

[0062] Conduct spectral analysis within the calculation time window Twin at the sampling point time for the three data volumes respectively, and calculate the maximum effective main frequencies within the main frequency band range of the three data volumes as Fnear, Fmid, and Far;

[0063] 4) Calculate the values of λnear, λmid, and λfar at this sampling point time:

[0064] Select the well-side trace seismic data at this sampling point and conduct time-depth calibration to obtain the seismic velocity Vtime at the sampling point time;

[0065] Using the relationship between wavelength, frequency, and velocity, λ = V * f, the values of λnear, λmid, and λfar at this sampling point time can be calculated;

[0066] 5) Calculate the values of Tnear and Tfar, which are the results calculated by the wavelength method:

[0067] For pre-stack seismic gathers, as the offset increases, the frequency becomes lower and lower. Therefore, for the near, mid, and far offset stacking volumes, the relationship of their dominant frequencies is that the frequency of the near offset is the highest, the frequency of the far offset is the lowest, and the frequency of the mid offset is between the far and near offset stacking volumes;

[0068] Therefore, the optimal solution of directly obtaining Tnear by the proportional method is: Tnear / Twin = λnear / λmid; Tfar / Twin = λfarr / λmid;

[0069] Since seismic sampling is sparse, it is necessary to round the calculated values of Tnear and Tfar, that is, Tnear = INT(Tnear), Tfar = INT(Tfar);

[0070] In some cases, if the values of INT(Tnear) and Twin, INT(Tfar) are close or equal, one sampling point is reduced or one sampling point is increased according to the method of INT(Tnear) < Twin < INT(Tfar);

[0071] 6) Loop calculation for the entire 3D data volume:

[0072] For the entire 3D data volume, there are Lnum main survey lines, Xnum tie lines in total, and Npoint sampling points on a single seismic trace. Conducting loop calculation along the entire 3D data volume, a total of (Lnum multiplied by num multiplied by Npoint) points need to be calculated.

[0073] Figure 3 、 Figure 4 and Figure 5 are respectively the schematic diagrams of the layer-by-layer attribute effects of the near, mid, and far offsets obtained by the adaptive time window calculation method for offset attributes in this embodiment. Among them, the near, mid, and far offset time windows are 10ms, 14ms, and 18ms respectively.

[0074] In this embodiment, the number of offset stacking volumes is 3. In some areas where AVO changes are relatively drastic, it can also be divided into near, near-middle, mid, mid-far, far, and far-far offset stacking volumes according to the size of the offset. Figure 2 Shows the schematic diagram of the cross-section of four offset stacking volumes in a certain seismic work area.

[0075] Embodiment 2:

[0076] This embodiment provides an adaptive time window calculation method for offset attributes, as Figure 1 shown, including:

[0077] Stack the pre-stack seismic gathers separately according to different offsets to obtain multiple stacked volumes for different offsets;

[0078] Calculate the time windows of each stacked volume for different offsets at all sampling points;

[0079] Calculating the time windows of each stacked volume for different offsets at all sampling points includes:

[0080] Set the time window of the middle-offset stacked volume or the near-middle-offset stacked volume at a certain sampling point;

[0081] Calculate the wavelength of each stacked volume for different offsets at this sampling point;

[0082] Based on the time window and the wavelength of each stacked volume for different offsets, calculate the time window of the remaining stacked volumes for different offsets at this sampling point;

[0083] Loop to calculate the time windows of each stacked volume for different offsets at the remaining sampling points;

[0084] When the number of stacked volumes for different offsets is odd, set the time window of the middle-offset stacked volume at a certain sampling point;

[0085] When the number of stacked volumes for different offsets is even, set the time window of any near-middle-offset stacked volume at a certain sampling point;

[0086] Calculating the wavelength of each stacked volume for different offsets at this sampling point includes:

[0087] Perform spectral analysis calculation within the time window of each stacked volume for different offsets at this sampling point to obtain the maximum effective dominant frequency of each data volume;

[0088] Based on the seismic data of the well-side trace at this sampling point, obtain the time-depth relationship, or use the existing time-depth relationship to calculate the seismic velocity of each stacked volume for different offsets at this sampling point;

[0089] Based on the maximum effective dominant frequency and the seismic velocity, calculate the wavelength of each stacked volume for different offsets at this sampling point;

[0090] The time windows of each stacked volume for different offsets at all sampling points are all subjected to rounding operations;

[0091] If the values of the time windows of each stacked volume for different offsets after rounding operations at a certain sampling point are close or equal, reduce or increase one sampling point near the sampling point in the order of increasing offset distance;

[0092] Multiple stacked volumes for different offsets form a 3D data volume;

[0093] The 3D data volume includes multiple main survey lines, multiple connecting survey lines, and multiple seismic traces;

[0094] Multiple sampling points are set on each seismic trace;

[0095] The number of sampling points on the 3D data volume is the product of the number of main survey lines, connecting survey lines, and seismic traces.

[0096] Example 3:

[0097] This example provides an adaptive time window calculation device for offset attributes, as Figure 1 shown, including:

[0098] A stacking module for stacking the pre-stack seismic trace gathers separately by different offsets to obtain multiple offset stacks;

[0099] A calculation module for calculating the time windows of each offset stack at all sampling points;

[0100] Calculating the time windows of each offset stack at all sampling points includes:

[0101] Setting the time window of the medium offset stack or the near-medium offset stack at a certain sampling point;

[0102] Calculating the wavelength of each offset stack at this sampling point;

[0103] Calculating the time windows of the remaining offset stacks at this sampling point based on the time window and the wavelengths of each offset stack;

[0104] Cyclically calculating the time windows of each offset stack at the remaining sampling points;

[0105] When the number of offset stacks is odd, setting the time window of the medium offset stack at a certain sampling point;

[0106] When the number of offset stacks is even, setting the time window of any near-medium offset stack at a certain sampling point;

[0107] Calculating the wavelength of each offset stack at this sampling point includes:

[0108] Performing spectral analysis calculation within the time window of each offset stack at this sampling point to obtain the maximum effective main frequency of each data volume;

[0109] Obtaining the time-depth relationship based on the seismic data of the well-side trace at this sampling point, or using the existing time-depth relationship, and calculating the seismic velocity of each offset stack at this sampling point;

[0110] Calculating the wavelength of each offset stack at this sampling point based on the maximum effective main frequency and the seismic velocity;

[0111] The time windows of each offset stack at all sampling points are all subjected to rounding operations;

[0112] If the values of the time windows of the respective offset superpositions after rounding operations are close to or equal at a certain sampling point, reduce or increase one sampling point near the sampling point in the order of the offset distances from near to far.

[0113] Multiple offset superpositions form a three-dimensional data volume;

[0114] The three-dimensional data volume includes multiple main survey lines, multiple connecting survey lines, and multiple seismic traces;

[0115] Multiple sampling points are provided on each seismic trace;

[0116] The number of sampling points on the three-dimensional data volume is the product of the numbers of the main survey lines, the connecting survey lines, and the seismic traces.

[0117] Embodiment Four:

[0118] An embodiment of the present invention provides an electronic device including a memory and a processor,

[0119] The memory stores executable instructions;

[0120] The processor runs the executable instructions in the memory to implement an adaptive time window calculation method for offset attributes.

[0121] This memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and these computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. This volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. This non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0122] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In an embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0123] Those skilled in the art should understand that, in order to solve the technical problem of how to obtain a good user experience effect, this embodiment may also include well-known structures such as communication buses, interfaces, etc., and these well-known structures should also be included in the protection scope of the present invention.

[0124] For the detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details will not be repeated here.

[0125] Embodiment Five:

[0126] An embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements an adaptive time window calculation method for offset attributes.

[0127] The computer-readable storage medium according to the embodiment of the present invention stores non-temporary computer-readable instructions. When the non-temporary computer-readable instructions are run by a processor, all or part of the steps of the methods of the various embodiments of the present invention described above are executed.

[0128] The above computer-readable storage medium includes but is not limited to: optical storage media (such as CD-ROMs and DVDs), magneto-optical storage media (such as MOs), magnetic storage media (such as magnetic tapes or external hard drives), media with built-in rewritable non-volatile memories (such as memory cards), and media with built-in ROMs (such as ROM cartridges).

[0129] The adaptive time window calculation method for offset attributes provided by the embodiment of the present invention fully exploits the offset information in prestack seismic data. By calculating the time windows of multiple offset stacks obtained by stacking prestack seismic gathers at all sampling points, it realizes an effective characterization of complex geological anomalies such as faults-fractures and channels.

[0130] The various embodiments of the present invention have been described above. The above description is exemplary and not exhaustive, and is also not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art in the technical field without departing from the scope and spirit of the described embodiments.

Claims

1. An adaptive time window calculation method for offset attributes, characterized in that, it includes: Stacking the pre-stack seismic trace gathers separately according to different offsets to obtain multiple offset stacks; Calculating the time windows of each offset stack at all sampling points.

2. The method according to claim 1, characterized in that, the calculating the time windows of each offset stack at all sampling points includes: Setting the time window of the middle offset stack or the near-middle offset stack at a certain sampling point; Calculating the wavelength of each offset stack at this sampling point; Based on the time window and the wavelengths of each offset stack, calculating the time windows of the remaining offset stacks at this sampling point; Looping to calculate the time windows of each offset stack at the remaining sampling points; When the number of the offset stacks is odd, setting the time window of the middle offset stack at a certain sampling point; When the number of the offset stacks is even, setting the time window of any near-middle offset stack at a certain sampling point.

3. The method according to claim 1, characterized in that, the calculating the wavelength of each offset stack at this sampling point includes: Performing spectral analysis calculation within the time window of each offset stack at this sampling point to obtain the maximum effective main frequency of each data volume; Based on the well-side trace seismic data at this sampling point to obtain the time-depth relationship, or using the existing time-depth relationship, calculating the seismic velocity of each offset stack at this sampling point; Based on the maximum effective main frequency and the seismic velocity, calculating the wavelength of each offset stack at this sampling point.

4. The method according to claim 3, characterized in that, the time windows of each offset stack at all sampling points are all subjected to rounding operations.

5. The method according to claim 4, characterized in that, If the values of the time windows of each offset stack after rounding operations at a certain sampling point are close or equal, one sampling point is reduced or one sampling point is increased near the sampling point in the order from near to far offset distance.

6. The method according to claim 1, characterized in that, the multiple offset stacks form a three-dimensional data volume; the three-dimensional data volume includes multiple main survey lines, multiple connecting survey lines, and multiple seismic traces; There are multiple sampling points set on each seismic trace.

7. The method according to claim 6, characterized in that, the number of sampling points on the three-dimensional data volume is the product of the numbers of the main survey lines, the connecting survey lines, and the seismic traces.

8. An adaptive time window calculation device for offset attributes, characterized in that, it includes: A stacking module for stacking the pre-stack seismic trace gathers separately according to different offsets to obtain multiple offset stacks; A calculation module for calculating the time windows of each offset stack at all sampling points.

9. An electronic device, characterized in that, the electronic device includes: A memory storing executable instructions; A processor, the processor running the executable instructions in the memory to implement the adaptive time window calculation method for offset attributes according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the adaptive time window calculation method for offset attributes described in any one of claims 1-7.

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