An oil and gas detection method based on AVO attributes

Abstract

The application provides an oil and gas detection method based on AVO attributes, which comprises the following steps: collecting seismic data by using a two-wide-one-high mode; performing OVT domain data processing on the seismic data, and extracting offset distance and azimuth information of the corresponding seismic data to obtain a spiral gather; performing common-azimuth amplitude stacking on the seismic data based on the azimuth information in the spiral gather, and calculating two-way travel time of each group of common-azimuth amplitude stacking data; comparing the size of the two-way travel time of each group of common-azimuth amplitude stacking data to determine a sensitive azimuth; determining near-offset distance amplitude stacking energy and far-offset distance amplitude stacking energy on the sensitive azimuth according to a preset offset distance range; calculating an energy difference value of the near-offset distance amplitude stacking energy and the far-offset distance amplitude stacking energy to obtain sensitive azimuth AVO attributes; and performing oil and gas detection based on the sensitive azimuth AVO attributes. The AVO attributes can make more gathers beneficial to oil and gas detection participate in calculation, and the oil and gas detection result is more accurate.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of oil and gas exploration technology, and particularly relates to an oil and gas detection method based on AVO attributes. BACKGROUND

[0002] AVO (Amplitude Versus Offset) technology is a technology developed for natural gas exploration, and was used to qualitatively determine the gas-bearing property of a formation in the early stage. However, with further research, it was found that the amplitude of a common reflection point gather varies with the incident angle and the azimuth angle, and has vectorial property. That is, the variation of AVO azimuth is closely related to the anisotropy of the formation, and thus a method for identifying reservoir fractures using AVO attributes was developed. The AVO attributes used by the conventional technology and the determination method thereof include:

[0003] 1) Conventional AVO attributes and determination method thereof: the variation of the amplitude of seismic wave data in each common reflection point gather with offset is analyzed to determine the AVO attributes, and the average value of the AVO attributes of all common reflection point gathers is obtained as the conventional AVO attributes; this method can mask the information sensitive to oil and gas reservoirs.

[0004] 2) Partial azimuth gather AVO attributes and determination method thereof: the main fracture direction of the work area is determined, the azimuth angle gathers parallel to the main fracture direction are selected for stacking, and then AVO analysis is performed (for example, if the fracture is southwest, the azimuth angle gathers within a certain range in the southwest direction are selected for stacking, and then AVO analysis is performed), so that the variation of the amplitude of only a part of the gathers with offset is analyzed to detect oil and gas; this method can reduce the influence of some fractures on oil and gas detection to a certain extent, but at the same time, a lot of useful gather information is missed, and the fracture direction of each point in the subsurface changes with depth, so the partial azimuth gather AVO analysis based on the fracture direction of a point at a certain depth cannot completely avoid the interference of fractures on seismic wave data.

[0005] Therefore, a reservoir fracture identification method using some new AVO attributes is urgently needed in the field. SUMMARY

[0006] In order to retain more information sensitive to oil and gas reservoirs, the present application provides an oil and gas detection method based on AVO attributes, which comprises: collecting seismic data in a two-wide-one-high manner; performing OVT domain data processing on the seismic data, and extracting offset and azimuth information of the corresponding seismic data to obtain a spiral gather; performing common-azimuth amplitude stacking on the seismic data based on the azimuth information in the spiral gather, and calculating two-way travel time of each group of common-azimuth amplitude stacked data; comparing the size of the two-way travel time of each group of common-azimuth amplitude stacked data to determine a sensitive azimuth, the sensitive azimuth comprising one or more azimuth angles; determining near-offset amplitude stacked energy and far-offset amplitude stacked energy at the sensitive azimuth according to a preset offset range; calculating an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy to obtain a sensitive azimuth AVO attribute; and performing oil and gas detection based on the sensitive azimuth AVO attribute.

[0007] In one or more embodiments, the comparing the size of the two-way travel time of each group of common-azimuth amplitude stacked data to determine a sensitive azimuth comprises: comparing the size of the two-way travel time of each group of common-azimuth amplitude stacked data; and determining the azimuth corresponding to the minimum two-way travel time as the sensitive azimuth.

[0008] In one or more embodiments, the determining the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at the sensitive azimuth according to a preset offset range comprises: determining a near-offset range and a far-offset range according to the preset offset range; performing common-azimuth amplitude stacking on seismic data in the near-offset range to obtain near-offset amplitude stacked energy; and performing common-azimuth amplitude stacking on seismic data in the far-offset range to obtain far-offset amplitude stacked energy.

[0009] In one or more embodiments, the calculating an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy to obtain a sensitive azimuth AVO attribute comprises: calculating an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at the azimuth corresponding to the minimum two-way travel time to obtain a reservoir sensitive azimuth AVO attribute.

[0010] In one or more embodiments, the AVO attribute-based hydrocarbon detection method of the present application further comprises: determining near-offset amplitude stack energy and far-offset amplitude stack energy in each azimuth according to a preset offset range, and calculating energy difference between the near-offset amplitude stack energy and the far-offset amplitude stack energy in each azimuth; comparing the energy difference between the near-offset amplitude stack energy and the far-offset amplitude stack energy in all common azimuths, determining the maximum value in the energy difference as an azimuthal maximum AVO attribute, and determining the minimum value in the energy difference as an azimuthal minimum AVO attribute; and performing hydrocarbon detection based on the azimuthal maximum AVO attribute and / or the azimuthal minimum AVO attribute.

[0011] In one or more embodiments, the spiral gather comprises seismic data in 0°-360° directions from reflection point reflections at different depths on the same vertical line.

[0012] In one or more embodiments, the determining near-offset amplitude stack energy and far-offset amplitude stack energy in each azimuth according to a preset offset range, and calculating energy difference between the near-offset amplitude stack energy and the far-offset amplitude stack energy in each azimuth comprises: dividing a plurality of seismic data in a corresponding azimuth into near-offset seismic data and far-offset seismic data based on offset of each seismic data and the preset offset range; performing common-azimuth amplitude stack on the near-offset seismic data to obtain near-offset amplitude stack energy; and performing common-azimuth amplitude stack on the far-offset seismic data to obtain far-offset amplitude stack energy.

[0013] In one or more embodiments, the comparing the energy difference between the near-offset amplitude stack energy and the far-offset amplitude stack energy in all common azimuths, determining the maximum value in the energy difference as an azimuthal maximum AVO attribute, and determining the minimum value in the energy difference as an azimuthal minimum AVO attribute comprises: comparing the energy difference between the near-offset amplitude stack energy and the far-offset amplitude stack energy in 0°-360° directions; determining the maximum energy difference as the azimuthal maximum AVO attribute; and determining the minimum energy difference as the azimuthal minimum AVO attribute.

[0014] In one or more embodiments, the AVO attribute-based hydrocarbon detection method of the present application further comprises determining the offset range by: performing offset-azimuth domain data regularization on the spiral gather; and determining near-offset range and far-offset range according to the regularized offset distribution.

[0015] The AVO attribute-based oil and gas detection method of the present application further comprises that before the common-azimuth amplitude stacking of the seismic data based on the azimuth information in the spiral gather, the pre-stack data regularization is performed on the seismic data, and the pre-stack data regularization comprises bin equalization or amplitude normalization based on the number of covers.

[0016] The beneficial effects of the present application include that the present application analyzes the gathers in each azimuth of 0°-360° of each common reflection point in the spiral gather seismic data body, determines the AVO attribute in the sensitive azimuth by calculating the two-way travel time of the common-azimuth amplitude stacking data in each azimuth of 0°-360° first, and then determines the azimuth maximum AVO attribute and the azimuth minimum AVO attribute by comparing the extreme value of the energy difference between the near-offset amplitude stacking energy and the far-offset amplitude stacking energy of the common-azimuth amplitude stacking data in each azimuth of 0°-360°, and performs the seismic analysis by using the AVO attribute determined in the above manner, which can effectively avoid the problem that the AVO attribute of the partial azimuth gather will make the gather not conducive to the oil and gas detection to participate in the calculation, and make more gathers conducive to the oil and gas detection to participate in the calculation, so that the oil and gas detection result is more accurate. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other embodiments can be obtained without creative labor on the basis of these drawings.

[0018] Figure 1 The workflow diagram of an AVO attribute-based oil and gas detection method of an embodiment of the present application;

[0019] Figure 2 The comparative analysis diagram of the conventional AVO attribute, the reservoir sensitive azimuth AVO attribute, the maximum azimuth AVO attribute and the minimum azimuth AVO attribute acquisition method of the present application;

[0020] Figure 3 The detection imaging result of the C2b layer section of the known oil and gas field SM03 well by using the conventional AVO attribute of the embodiment of the present application;

[0021] Figure 4 The detection imaging result of the C2b layer section of the known oil and gas field SM03 well by using the fault sensitive azimuth of the embodiment of the present application;

[0022] Figure 5 The detection imaging result of the C2b layer section of the known oil and gas field SM03 well by using the reservoir sensitive azimuth AVO attribute of the embodiment of the present application;

[0023] Figure 6 Fig. 4 shows the detection imaging result of the C2b layer section of the SM03 well in the known oil and gas field by using the maximum azimuth AVO attribute of the embodiment of the present application;

[0024] Figure 7 Fig. 5 shows the detection imaging result of the C2b layer section of the SM03 well in the known oil and gas field by using the minimum azimuth AVO attribute of the embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the objects, technical solutions and advantages of the present application clearer, the embodiments of the present application are further described in detail below with reference to the accompanying drawings.

[0026] It should be noted that all the expressions of "first" and "second" in the embodiments of the present application are used to distinguish two same-named different entities or different parameters, and the "first" and "second" are only for the convenience of description and should not be understood as a limitation of the embodiments of the present application. The subsequent embodiments will not be described one by one.

[0027] In order to retain more sensitive information to the oil and gas reservoir, in some embodiments below, the present application proposes an oil and gas detection method based on AVO attribute, which calculates the common azimuth stack result in 0°-360° multiple azimuths based on common reflection point spiral gather, and determines multiple AVO attribute combinations in the most sensitive direction of the oil and gas reservoir from multiple common azimuth stack results in multiple ways to retain more sensitive information to the oil and gas reservoir. The technical solutions of the present application are described below in combination with the accompanying drawings.

[0028] Please refer to the accompanying drawings Figure 1 Fig. 1 shows the working process of an oil and gas detection method based on AVO attribute of an embodiment of the present application, which includes the following steps: step S1, collecting seismic data in a two-wide-one-high manner; step S2, performing OVT domain data processing on the seismic data, and extracting offset and azimuth information corresponding to the seismic data to obtain spiral gathers; step S3, performing common azimuth amplitude stacking on the seismic data based on the azimuth information in the spiral gathers, and calculating the two-way travel time of each group of common azimuth amplitude stacking data; step S4, comparing the size of the two-way travel time of each group of common azimuth amplitude stacking data to determine the sensitive azimuth, which includes one or more azimuth angles; step S5, determining the near-offset amplitude stacking energy and the far-offset amplitude stacking energy in the sensitive azimuth according to the preset offset range; step S6, calculating the energy difference of the near-offset amplitude stacking energy and the far-offset amplitude stacking energy to obtain the sensitive azimuth AVO attribute; and step S7, performing oil and gas detection based on the sensitive azimuth AVO attribute.

[0029] Specifically, the two-wide-one-high seismic record acquisition technique emphasizes accuracy and fidelity more than the conventional three-dimensional seismic record acquisition technique, and is no longer targeted at improving the quality of single-shot record data, but is mainly aimed at embodying full (wide) azimuth, full (wide) frequency band, high density, high coverage and full wave field characteristics. The full (wide) azimuth refers to acquiring seismic records by using a wide-azimuth observation system with an aspect ratio greater than 0.5, and when the aspect ratio is 1, it is a full-azimuth acquisition observation system, i.e. uniform acquisition in each azimuth. The full (wide) frequency band refers to widening the seismic high and low frequency bands, improving the effective frequency multiplication of the seismic system, focusing on the excitation and reception of high and low frequency end seismic information, and using single-point small explosive excitation and single-point digital geophone reception according to local conditions. High density refers to increasing the spatial sampling density in the field, reducing the surface element scale, increasing the effective coverage times of the target layer, achieving high coverage, ensuring the non-aliasing sampling of various wave fields, making the surface element properties uniform, combining with point acquisition technology, and ensuring the fidelity of seismic information through point excitation and point reception acquisition. For step S1, the common reflection point gather obtained by the two-wide-one-high method will contain seismic data propagating in various directions (0°-360° directions) with a certain reflection point as the center, which is also the basis for implementing the technical scheme of the present application.

[0030] For step S2, OVT domain extraction is a data division method, which is used for comprehensive consideration of the optimization results of azimuth and offset distance of the two-wide-one-high seismic data. OVT domain data division is carried out on the basis of cross-line gathers, and the acquired seismic records are extracted into single-coverage cross-line arranged gathers according to common lines and common geophones, then OVT slices are divided and numbered according to offset and geophone distance, and finally the same OVT slices in each cross-line gather are extracted into the same OVT subset, and then spiral gathers are obtained through OVT domain gather pre-stack processing and OVT domain gather pre-stack migration. Since the OVT subset is a collection of seismic traces controlled within a range of offset distance and azimuth, the spiral gather has the characteristic of uniform sampling in space, and adjacent traces have good coherence. More specifically, the spiral gather has the characteristic of uniform sampling in space, which specifically manifests that the spiral gather contains seismic data of different stratum depths in 0°-360° azimuths.

[0031] For step S3, different from the conventional technology, instead of taking the fracture direction at a certain depth point as the reference and only stacking the data of the formed gathers in a specific direction (such as the vertical fracture direction), the embodiment utilizes the feature that the spiral gathers contain anisotropic seismic data, and stacks the seismic data in each direction with the azimuth angle in the range of 360° to utilize the result of the stacking, i.e. the two-way travel time of each group of common-azimuth amplitude stacked data, to find the direction most sensitive to the oil and gas reservoir, so as to achieve the purpose of reserving more seismic data sensitive to the oil and gas reservoir. Specifically, the specific way of performing the common-azimuth amplitude stacking in step S3 can be to perform the common-azimuth amplitude stacking based on each azimuth angle, and when the seismic data in the azimuth angle is too little, the seismic data in the adjacent azimuth angle can be further considered to perform the common-azimuth amplitude stacking with the seismic data in the azimuth angle, so that the sensitive direction determined by the two-way travel time after the common-azimuth amplitude stacking can contain one azimuth angle or multiple azimuth angles.

[0032] In one embodiment, the specific process of step S4 of comparing the size of the two-way travel time of each group of common-azimuth amplitude stacked data to determine the sensitive direction includes: comparing the size of the two-way travel time of each group of common-azimuth amplitude stacked data; determining the direction corresponding to the minimum two-way travel time as the sensitive direction; the specific steps of step S5 of determining the near-offset amplitude stacked energy and the far-offset amplitude stacked energy in the sensitive direction according to the preset offset range include: determining the near-offset range and the far-offset range according to the preset offset range; performing the common-azimuth amplitude stacking on the seismic data in the near-offset range to obtain the near-offset amplitude stacked energy; performing the common-azimuth amplitude stacking on the seismic data in the far-offset range to obtain the far-offset amplitude stacked energy; the specific steps of step S6 of calculating the energy difference between the near-offset amplitude stacked energy and the far-offset amplitude stacked energy to obtain the sensitive direction AVO attribute include: calculating the energy difference between the near-offset amplitude stacked energy and the far-offset amplitude stacked energy in the direction corresponding to the minimum two-way travel time to obtain the reservoir sensitive direction AVO attribute. In the above process of determining the sensitive direction by step S4, the direction corresponding to the maximum two-way travel time can also be determined, which is the fault sensitive direction and can be used for fault detection. The offset range is determined by previously performing the offset-azimuth domain data regularization on the spiral gathers, and then determining the near-offset range and the far-offset range according to the offset distribution after the regularization.

[0033] In a further embodiment, in order to be able to utilize more seismic data sensitive to oil and gas, in addition to utilizing AVO attributes in sensitive azimuths, embodiments of the present application further propose determining azimuthal maximum AVO attributes and azimuthal minimum AVO attributes by comparing the extreme values of energy difference values of near-offset amplitude stack energy and far-offset amplitude stack energy of common-azimuth amplitude stack data in 0°-360° azimuths, and the specific steps are as follows: determining near-offset amplitude stack energy and far-offset amplitude stack energy in each azimuth according to a preset offset range, and calculating the energy difference value of near-offset amplitude stack energy and far-offset amplitude stack energy in each azimuth; comparing the energy difference values of near-offset amplitude stack energy and far-offset amplitude stack energy in all common azimuths, determining the maximum value in the energy difference values as the azimuthal maximum AVO attribute, and determining the minimum value in the energy difference values as the azimuthal minimum AVO attribute; and performing oil and gas detection based on the azimuthal maximum AVO attribute and / or the azimuthal minimum AVO attribute. In an optional embodiment, the present application can perform oil and gas detection by utilizing the sensitive azimuth AVO attribute, the azimuthal maximum AVO attribute and / or the azimuthal minimum AVO attribute.

[0034] In a further embodiment, the spiral gather contains seismic data in 0°-360° directions from reflection points at different depths on the same vertical line. Specifically, the azimuthal maximum AVO attribute and the azimuthal minimum AVO attribute determined by the method of the present embodiment are obtained by extreme value screening from the energy difference values in a plurality of azimuths, and represent the azimuth with the largest change in geological structure, such as a large fracture. Since the seismic data in the present embodiment is collected by geophones arranged at different depths, the present embodiment can realize detection of 360° different depths, can understand the interference of fractures at different depths on seismic wave data, and thus can realize targeted denoising of each seismic data.

[0035] In a further embodiment, determining near-offset amplitude stack energy and far-offset amplitude stack energy in each azimuth according to a preset offset range, and calculating the energy difference value of near-offset amplitude stack energy and far-offset amplitude stack energy in each azimuth, comprises: dividing a plurality of seismic data in the corresponding azimuth into near-offset seismic data and far-offset seismic data based on the offset of each seismic data and the preset offset range; performing common-azimuth amplitude stacking on the near-offset seismic data to obtain near-offset amplitude stack energy; and performing common-azimuth amplitude stacking on the far-offset seismic data to obtain far-offset amplitude stack energy.

[0036] In a further embodiment, the maximum value in the energy difference values is determined as the azimuthal maximum AVO attribute and the minimum value in the energy difference values is determined as the azimuthal minimum AVO attribute by comparing the energy difference values of the near-offset amplitude stack energy and the far-offset amplitude stack energy in all co-azimuths, including: comparing the energy difference values of the near-offset amplitude stack energy and the far-offset amplitude stack energy in 0°-360° directions; determining the maximum energy difference value as the azimuthal maximum AVO attribute; and determining the minimum energy difference value as the azimuthal minimum AVO attribute.

[0037] See Figure 2 , which shows a comparison of the conventional AVO attribute, the reservoir-sensitive azimuthal AVO attribute, the maximum azimuthal AVO attribute, and the minimum azimuthal AVO attribute acquisition method of the present application. As shown in Figure 2 , compared with the acquisition method of the azimuthal maximum / minimum AVO attribute of the present application, the conventional AVO attribute does not perform co-azimuth stacking of the near-offset and far-offset, respectively, and does not perform extreme value screening, thereby determining a set of azimuthal maximum / minimum AVO attributes with opposite attributes; compared with the reservoir-sensitive azimuthal AVO attribute of the present application, the conventional AVO attribute does not judge the sensitive azimuth; and the acquisition methods of the above three AVO attributes of the present application are different from the acquisition method of the conventional partial azimuthal gather AVO attribute, and the judgment of the sensitive azimuth of the present application is not limited to the direction of the fracture, but is more reasonable by actually comparing the two-way travel time of the amplitude stack energy in different azimuths.

[0038] In a further embodiment, the pre-stack data regularization is performed on the seismic data before the co-azimuth amplitude stacking of the seismic data based on each azimuth angle, and the pre-stack data regularization includes bin equalization or amplitude normalization based on the number of covers. The pre-stack regularization can effectively remove abnormal data in the seismic data, so that the co-azimuth stacking effect is better.

[0039] Application to the known oil and gas field SM03 well

[0040] In this embodiment, the detection effects of various AVO attributes are as follows: among them, the proven SM03 well is a gas-bearing layer in the C2b layer section, and the prediction results using the conventional AVO attribute and the partial azimuthal gather AVO attribute are not gas-bearing, and the prediction fails; and the minimum azimuthal AVO attribute, the maximum azimuthal AVO attribute, and the reservoir-sensitive azimuthal AVO attribute can all predict that the SM03 well is gas-bearing in the C2b layer section. For specific detection results, see Figures 3-7 , which respectively shows the detection imaging results of the C2b layer section using the conventional AVO attribute, the fault-sensitive azimuthal AVO attribute, the reservoir-sensitive azimuthal AVO attribute, the maximum azimuthal AVO attribute, and the minimum azimuthal AVO attribute in the embodiment of the present application. By comparing Figures 3-7It can be seen that the imaging results using the reservoir's sensitive azimuth AVO attribute— Figure 5 The imaging results obtained using fault-sensitive azimuth AVO attributes are significantly better than those obtained using other AVO attributes, demonstrating that reservoir-sensitive azimuth AVO attributes can effectively detect oil and gas in reservoirs; while the imaging results obtained using fault-sensitive azimuth AVO attributes— Figure 4 The experiment showed that the C2b layer did not contain gas, and the prediction failed. This experiment indirectly verified that fault-sensitive orientation data is not suitable for oil and gas detection.

[0041] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0042] It should be understood that, as used herein, the singular form “a” is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, “and / or” refers to any and all possible combinations of one or more of the associated listed items.

[0043] The embodiment numbers disclosed in the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0044] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method for hydrocarbon detection based on AVO attributes, characterized in that, The method comprises: acquiring seismic data in a two-wide-one-high manner; performing OVT domain data processing on the seismic data, and extracting offset and azimuth information of corresponding seismic data to obtain a spiral gather; performing common-azimuth amplitude stacking on the seismic data based on the azimuth information in the spiral gather, and calculating two-way travel time of each group of common-azimuth amplitude stacked data; comparing the two-way travel time of each group of common-azimuth amplitude stacked data to determine a sensitive azimuth, the sensitive azimuth comprising one or more azimuth angles; determining near-offset amplitude stacked energy and far-offset amplitude stacked energy at the sensitive azimuth according to a preset offset range; calculating an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy to obtain a sensitive azimuth AVO attribute; performing oil and gas detection based on the sensitive azimuth AVO attribute.

2. The method of claim 1, wherein, The comparison of the two-way travel time of each group of common-azimuth amplitude stacked data to determine a sensitive azimuth comprises: comparing the two-way travel time of each group of common-azimuth amplitude stacked data to determine a minimum two-way travel time corresponding azimuth as the sensitive azimuth.

3. The method of claim 2, wherein, The determination of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at the sensitive azimuth according to a preset offset range comprises: determining a near-offset range and a far-offset range according to the preset offset range; performing common-azimuth amplitude stacking on seismic data in the near-offset range to obtain near-offset amplitude stacked energy; performing common-azimuth amplitude stacking on seismic data in the far-offset range to obtain far-offset amplitude stacked energy.

4. The method of claim 3, wherein, The calculation of an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy to obtain a sensitive azimuth AVO attribute comprises: calculating an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at the minimum two-way travel time corresponding azimuth to obtain a reservoir sensitive azimuth AVO attribute.

5. The method of claim 1, wherein, The method further comprises: determining near-offset amplitude stacked energy and far-offset amplitude stacked energy at each azimuth according to a preset offset range, and calculating an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at each azimuth; comparing the energy difference values of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at all common azimuths to determine a maximum value in the energy difference values as an azimuth maximum AVO attribute, and to determine a minimum value in the energy difference values as an azimuth minimum AVO attribute; performing oil and gas detection based on the azimuth maximum AVO attribute and / or the azimuth minimum AVO attribute.

6. The method of claim 5, wherein, The spiral gather contains seismic data in 0°-360° directions from reflection points at different depths on the same vertical line.

7. The method of claim 5, wherein, The determination of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at each azimuth according to a preset offset range, and the calculation of an energy difference value of the near-offset amplitude stacked energy and the far-offset amplitude stacked energy at each azimuth, comprises: dividing multiple seismic data at a corresponding azimuth into near-offset seismic data and far-offset seismic data based on offset of each seismic data and a preset offset range; performing common-azimuth amplitude stack on the near-offset seismic data to obtain near-offset amplitude stack energy; performing common-azimuth amplitude stack on the far-offset seismic data to obtain far-offset amplitude stack energy.

8. The method of claim 7, wherein, The comparing of the energy difference between the near-offset amplitude stack energy and the far-offset amplitude stack energy in all common-azimuths, the determination of the maximum value in the energy difference as the azimuthal maximum AVO attribute, and the determination of the minimum value in the energy difference as the azimuthal minimum AVO attribute, comprise: comparing the energy difference between the near-offset amplitude stack energy and the far-offset amplitude stack energy in 0°-360° directions; determining the maximum energy difference as the azimuthal maximum AVO attribute; determining the minimum energy difference as the azimuthal minimum AVO attribute.

9. The method of claim 1, wherein, The method further comprises determining the offset range by the following steps: performing offset-azimuth domain data regularization on the spiral gather; determining the near-offset range and the far-offset range according to the regularized offset distribution.

10. The method of claim 1, wherein, The method further comprises, before performing common-azimuth amplitude stack on the seismic data based on the azimuth information in the spiral gather, performing pre-stack data regularization on the seismic data, the pre-stack data regularization comprising bin-averaging or amplitude normalization based on fold.

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