Pre-stack frequency domain fluid identification method and device, electronic equipment and medium

Abstract

The invention discloses a pre-stack frequency domain fluid identification method and device, electronic equipment and a medium. The method comprises the following steps: screening an effective angle range according to pre-stack angle gather data of a target interval of a typical well; in the effective angle range, acquiring a partially superposed data volume; extracting a high-frequency attenuation attribute and a low-frequency absorption attribute of the partially superposed data volume; according to the high-frequency attenuation attribute and the low-frequency absorption attribute, the frequency change attribute of the angle-divided superposition body is calculated; and acquiring a frequency change attribute gather according to the frequency change attribute, and further performing fluid identification. The calculation process of the obtained pre-stack frequency change attributes avoids an initial model, the calculation result is stable, and the fluid identification goodness of fit is high.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysical exploration, and more specifically, to a pre-stack frequency domain fluid identification method, apparatus, electronic device, and medium. Background Technology

[0002] Pre-stack data contains rich reservoir fluid information, and fluid identification based on pre-stack data has gradually become a research hotspot in reservoir fluid identification. Currently, there are two main methods for reservoir fluid identification based on seismic data:

[0003] (1) Fluid identification method based on pre-stack and post-stack seismic attributes. This method is limited by the fact that different work areas and different reservoirs have different fluid sensitivity and is only applicable to specific work areas.

[0004] (2) Fluid identification method based on pre-stack and post-stack inversion. This method is affected by the difficulty in obtaining low-frequency models and the strong multiple solutions of inversion, resulting in strong uncertainty in fluid prediction.

[0005] When seismic waves pass through fluid-containing media, high-frequency attenuation and low-frequency absorption occur. However, current research is limited to using either high-frequency attenuation or low-frequency absorption for fluid identification, and most of it is based on post-stack data, resulting in limited accuracy in fluid identification.

[0006] Therefore, it is necessary to develop a pre-stack frequency domain fluid identification method, device, electronic device, and medium.

[0007] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention

[0008] This invention proposes a pre-stack frequency domain fluid identification method, device, electronic device, and medium. The calculation process of the pre-stack frequency change attributes obtained by the invention avoids the initial model, and the calculation results are stable with high fluid identification accuracy.

[0009] In a first aspect, embodiments of this disclosure provide a pre-stack frequency domain fluid identification method, including:

[0010] Based on the pre-stack angle gather data of typical well targets, the effective angle range was selected;

[0011] Within the effective angle range, a portion of the superimposed data volume is acquired;

[0012] Extract the high-frequency attenuation and low-frequency absorption properties of the superimposed data volume;

[0013] Based on the high-frequency attenuation property and the low-frequency absorption property, calculate the frequency change property of the angular superposition body;

[0014] Based on the frequency change attributes, a frequency change attribute set is obtained, and then fluid identification is performed.

[0015] As one specific implementation of this disclosure, obtaining a portion of the overlay data body includes:

[0016] Within the effective angle range, the angles are divided to determine the superposition scheme, and the superposition is performed separately to obtain the superimposed data volume shown.

[0017] As a specific implementation of this disclosure, extracting the high-frequency attenuation properties and low-frequency absorption properties of the partially superimposed data volume includes:

[0018] For each of the aforementioned superimposed data volumes, the corresponding high-frequency attenuation attributes and low-frequency absorption attributes are extracted.

[0019] As a specific implementation of this disclosure, the frequency change attribute is:

[0020] A = f1(S1-S2)*f2(α*G1+β*G2)

[0021] Where: A represents the frequency variation attribute; f i Let i represent the normalization function, i = 1, 2; S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

[0022] As a specific implementation of this disclosure, obtaining the frequency change attribute set based on the frequency change attribute includes:

[0023] The frequency change attributes are rearranged according to the superposition center angle to obtain the frequency change attribute set.

[0024] As a specific implementation of this disclosure, obtaining a frequency change attribute trace set based on the frequency change attribute, and then performing fluid identification, includes:

[0025] Based on the frequency change attributes, calculate the pre-stack frequency change attributes, determine the threshold value through typical wells, and carry out fluid identification.

[0026] As a specific implementation of this disclosure, the pre-stack frequency change attribute is calculated using the following formula:

[0027] A = μ + AG * angle

[0028] Where A represents the frequency variation attribute; angle is the angle; and AG is the pre-stack frequency variation attribute.

[0029] Secondly, embodiments of this disclosure also provide a pre-stack frequency domain fluid identification device, comprising:

[0030] The filtering module filters the effective angle range based on the pre-stack angle gather data of typical well objectives.

[0031] The partial overlay module acquires partial overlay data within the effective angle range;

[0032] The extraction module extracts the high-frequency attenuation properties and low-frequency absorption properties of the superimposed data volume.

[0033] The calculation module calculates the frequency change attribute of the angular superposition body based on the high-frequency attenuation attribute and the low-frequency absorption attribute.

[0034] The identification module obtains a frequency change attribute set based on the frequency change attribute, and then performs fluid identification.

[0035] As one specific implementation of this disclosure, obtaining a portion of the overlay data body includes:

[0036] Within the effective angle range, the angles are divided to determine the superposition scheme, and the superposition is performed separately to obtain the superimposed data volume shown.

[0037] As a specific implementation of this disclosure, extracting the high-frequency attenuation properties and low-frequency absorption properties of the partially superimposed data volume includes:

[0038] For each of the aforementioned superimposed data volumes, the corresponding high-frequency attenuation attributes and low-frequency absorption attributes are extracted.

[0039] As a specific implementation of this disclosure, the frequency change attribute is:

[0040] A = f1(S1-S2)*f2(α*G1+β*G2)

[0041] Where: A represents the frequency variation attribute; f i Let i represent the normalization function, i = 1, 2; S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

[0042] As a specific implementation of this disclosure, obtaining the frequency change attribute set based on the frequency change attribute includes:

[0043] The frequency change attributes are rearranged according to the superposition center angle to obtain the frequency change attribute set.

[0044] As a specific implementation of this disclosure, obtaining a frequency change attribute trace set based on the frequency change attribute, and then performing fluid identification, includes:

[0045] Based on the frequency change attributes, calculate the pre-stack frequency change attributes, determine the threshold value through typical wells, and carry out fluid identification.

[0046] As a specific implementation of this disclosure, the pre-stack frequency change attribute is calculated using the following formula:

[0047] A = μ + AG * angle

[0048] Where A represents the frequency variation attribute; angle is the angle; and AG is the pre-stack frequency variation attribute.

[0049] Thirdly, embodiments of this disclosure also provide an electronic device, the electronic device comprising:

[0050] Memory, which stores executable instructions;

[0051] A processor that executes the executable instructions in the memory to implement the pre-stack frequency domain fluid identification method.

[0052] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the pre-stack frequency domain fluid identification method.

[0053] Its beneficial effects are as follows:

[0054] (1) This invention integrates high-frequency attenuation and low-frequency absorption phenomena, and proposes a new frequency variation property by normalizing and balancing the numerical difference between the two.

[0055] (2) This invention fully explores pre-stack seismic information and, based on the acquisition of post-stack frequency change attributes by angle, proposes a new frequency change attribute that varies with angle, namely the pre-stack frequency change attribute.

[0056] (3) This invention provides a technical process for fluid identification based on pre-stack frequency change attributes, which more intuitively demonstrates the differences in pre-stack frequency change attribute characteristics between fluid-containing and fluid-free cases, thereby improving the accuracy of fluid identification.

[0057] The methods and apparatus of the present invention have other features and advantages that will be apparent from or will be set forth in detail in the accompanying drawings and following detailed description, which together serve to explain the particular principles of the invention. Attached Figure Description

[0058] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same parts.

[0059] Figure 1 A flowchart illustrating the steps of a pre-stack frequency domain fluid identification method according to an embodiment of the present invention is shown.

[0060] Figure 2 A schematic diagram of the pre-stack gather of wellside track in study area B1 according to an embodiment of the present invention is shown.

[0061] Figure 3 A schematic diagram of a 1-12 degree partial superimposed data volume superposition profile is shown according to an embodiment of the present invention.

[0062] Figure 4 A schematic diagram illustrating the frequency variation property as a function of angle according to an embodiment of the present invention is shown.

[0063] Figure 5 A schematic diagram of a pre-stack frequency variation property profile according to an embodiment of the present invention is shown.

[0064] Figure 6 A block diagram of a pre-stack frequency domain fluid identification device according to an embodiment of the present invention is shown.

[0065] Explanation of reference numerals in the attached figures:

[0066] 201. Filtering module; 202. Partial overlay module; 203. Extraction module; 204. Calculation module; 205. Recognition module. Detailed Implementation

[0067] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0068] To facilitate understanding of the solutions and effects of the embodiments of the present invention, six specific application examples are given below. Those skilled in the art should understand that these examples are merely for the purpose of understanding the present invention, and any specific details therein are not intended to limit the present invention in any way.

[0069] Example 1

[0070] Figure 1 A flowchart illustrating the steps of a pre-stack frequency domain fluid identification method according to an embodiment of the present invention is shown.

[0071] like Figure 1 As shown, the pre-stack frequency domain fluid identification method includes:

[0072] Step 101: Based on the pre-stack angle gather data of typical well targets, filter the effective angle range;

[0073] Step 102: Within the effective angle range, acquire a portion of the superimposed data volume;

[0074] Step 103: Extract the high-frequency attenuation properties and low-frequency absorption properties of a portion of the superimposed data volume;

[0075] Step 104: Calculate the frequency variation properties of the angular superposition volume based on the high-frequency attenuation properties and the low-frequency absorption properties.

[0076] Step 105: Obtain frequency change attribute gathers based on frequency change attributes, and then perform fluid identification.

[0077] In one example, obtaining a portion of the overlay data volume includes:

[0078] Within the effective angle range, the angles are divided, the superposition scheme is determined, and the superposition is performed separately to obtain the superimposed data volume shown.

[0079] In one example, the high-frequency attenuation properties and low-frequency absorption properties of a portion of the superimposed data volume are extracted as follows:

[0080] For each part of the superimposed data volume, the corresponding high-frequency attenuation attribute and low-frequency absorption attribute are extracted.

[0081] In one example, the frequency change attribute is:

[0082] A = f1(S1-S2)*f2(α*G1+β*G2)

[0083] Where: A represents the frequency variation attribute; f i Let i represent the normalization function, i = 1, 2; S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

[0084] In one example, obtaining the frequency change attribute Tween based on the frequency change attribute includes:

[0085] The frequency change attributes are rearranged according to the size of the superposition center angle to obtain the frequency change attribute set.

[0086] In one example, obtaining a frequency change attribute gather based on the frequency change attribute, and then performing fluid identification, includes:

[0087] Pre-stack frequency change attributes are calculated based on frequency change attributes, threshold values ​​are determined through typical wells, and fluid identification is carried out.

[0088] In one example, the pre-stack frequency variation property is calculated using the following formula:

[0089] A = μ + AG * angle

[0090] Where A represents the frequency variation attribute; angle is the angle; and AG is the pre-stack frequency variation attribute.

[0091] Specifically, we analyzed pre-stack angle gather data for typical well targets to identify effective angle ranges. Based on these effective angle ranges, we divided the data into angle segments, determined the stacking scheme, and stacked the segments separately to obtain partial stacked data volumes. For each partial stacked data volume, we extracted the corresponding high-frequency attenuation and low-frequency absorption attributes.

[0092] Based on the high-frequency attenuation and low-frequency absorption properties of the partially superimposed data volume, the frequency variation properties of the angular superimposed volume are calculated:

[0093] A = f1(S1-S2)*f2(α*G1+β*G2)

[0094] Where: A represents the frequency variation attribute; f i S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

[0095] The frequency change attributes are rearranged according to the size of the superposition center angle to obtain the frequency change attribute set.

[0096] Based on the frequency change attributes of the rearranged angle-stacked data volume (i.e., frequency change attribute gather), the pre-stack frequency change attributes are calculated, and the threshold value is further determined through typical wells to carry out fluid identification.

[0097] Example 2

[0098] The present invention also provides a pre-stack frequency domain fluid identification device, comprising:

[0099] The filtering module filters the effective angle range based on the pre-stack angle gather data of typical well objectives.

[0100] The partial overlay module acquires partial overlay data within the effective angle range;

[0101] The extraction module extracts the high-frequency attenuation and low-frequency absorption properties of a portion of the superimposed data volume.

[0102] The calculation module calculates the frequency variation properties of the angular superposition volume based on the high-frequency attenuation properties and the low-frequency absorption properties.

[0103] The identification module obtains frequency change attribute gathers based on frequency change attributes, and then performs fluid identification.

[0104] In one example, obtaining a portion of the overlay data volume includes:

[0105] Within the effective angle range, the angles are divided, the superposition scheme is determined, and the superposition is performed separately to obtain the superimposed data volume shown.

[0106] In one example, the high-frequency attenuation properties and low-frequency absorption properties of a portion of the superimposed data volume are extracted as follows:

[0107] For each part of the superimposed data volume, the corresponding high-frequency attenuation attribute and low-frequency absorption attribute are extracted.

[0108] In one example, the frequency change attribute is:

[0109] A = f1(S1-S2)*f2(α*G1+β*G2)

[0110] Where: A represents the frequency variation attribute; f i Let i represent the normalization function, i = 1, 2; S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

[0111] In one example, obtaining the frequency change attribute Tween based on the frequency change attribute includes:

[0112] The frequency change attributes are rearranged according to the size of the superposition center angle to obtain the frequency change attribute set.

[0113] In one example, obtaining a frequency change attribute gather based on the frequency change attribute, and then performing fluid identification, includes:

[0114] Pre-stack frequency change attributes are calculated based on frequency change attributes, threshold values ​​are determined through typical wells, and fluid identification is carried out.

[0115] In one example, the pre-stack frequency variation property is calculated using the following formula:

[0116] A = μ + AG * angle

[0117] Where A represents the frequency variation attribute; angle is the angle; and AG is the pre-stack frequency variation attribute.

[0118] Specifically, we analyzed pre-stack angle gather data for typical well targets to identify effective angle ranges. Based on these effective angle ranges, we divided the data into angle segments, determined the stacking scheme, and stacked the segments separately to obtain partial stacked data volumes. For each partial stacked data volume, we extracted the corresponding high-frequency attenuation and low-frequency absorption attributes.

[0119] Based on the high-frequency attenuation and low-frequency absorption properties of the partially superimposed data volume, the frequency variation properties of the angular superimposed volume are calculated:

[0120] A = f1(S1-S2)*f2(α*G1+β*G2)

[0121] Where: A represents the frequency variation attribute; f i S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

[0122] The frequency change attributes are rearranged according to the size of the superposition center angle to obtain the frequency change attribute set.

[0123] Based on the frequency change attributes of the rearranged angle-stacked data volume (i.e., frequency change attribute gather), the pre-stack frequency change attributes are calculated, and the threshold value is further determined through typical wells to carry out fluid identification.

[0124] Example 3

[0125] Taking data from a real work area in China as an example, we conducted fluid identification research based on the pre-stack frequency variation attributes.

[0126] Figure 2 A schematic diagram of the pre-stack gather of wellside track in study area B1 according to an embodiment of the present invention is shown.

[0127] Analyze the pre-stack angle gather data of typical well targets to screen out the effective angle range. Figure 2 For the pre-stacked set of the wellside track in the B1 well of the study area, the effective angle is 1-34 degrees, as determined by analysis.

[0128] Figure 3 A schematic diagram of a 1-12 degree partial superimposed data volume superposition profile is shown according to an embodiment of the present invention.

[0129] Based on the effective angle range of 1-34 degrees, the angles are divided; a stacking scheme is determined, and stacking is performed separately for 1-12 degrees, 12-23 degrees, and 23-34 degrees, respectively, to obtain partial stacked data volumes. Figure 3 The superimposed profile of the data volume at degrees 1-12 is shown.

[0130] For some of the superimposed data volumes, high-frequency attenuation and low-frequency absorption properties are extracted separately, and then the frequency variation properties of the superimposed volume at different angles are calculated:

[0131] A=f1(S1-S2)*f2(α*G1+β*G2).

[0132] Figure 4 A schematic diagram illustrating the frequency variation property as a function of angle according to an embodiment of the present invention is shown.

[0133] The obtained frequency variation attributes are rearranged according to the magnitude of the stacking center angle, where the layer frequency variation attributes of typical well targets change with the angle as follows: Figure 4 As shown, it can be seen that the frequency change properties with angle change are significantly different before and after the presence of gas.

[0134] Figure 5 A schematic diagram of a pre-stack frequency variation property profile according to an embodiment of the present invention is shown.

[0135] Based on the rearranged frequency variation attribute gather, the pre-stack frequency variation attribute is calculated, and the pre-stack frequency variation attribute profile is as follows: Figure 5 As shown. The threshold value for the pre-stack frequency variation attribute is determined to be (>800) through the expression of typical well hydrocarbon conditions.

[0136] Based on the established threshold value, fluid identification was performed on the target layer to predict the fluid distribution in the study area. According to the actual drilling conditions (B1 is a high-yield gas well, and B2 is a water-producing well), the pre-stack frequency variation attribute profile matches the actual drilling conditions, proving that the pre-stack frequency variation attribute fluid identification has high accuracy.

[0137] Example 4

[0138] Figure 6 A block diagram of a pre-stack frequency domain fluid identification device according to an embodiment of the present invention is shown.

[0139] like Figure 6 As shown, the pre-stack frequency domain fluid identification device includes:

[0140] The filtering module 201 filters the effective angle range based on the pre-stack angle gather data of typical well targets.

[0141] Partial overlay module 202 acquires partial overlay data volume within the effective angle range;

[0142] Extraction module 203 extracts the high-frequency attenuation properties and low-frequency absorption properties of a portion of the superimposed data volume;

[0143] Calculation module 204 calculates the frequency change properties of the angular superposition body based on the high-frequency attenuation properties and the low-frequency absorption properties.

[0144] The identification module 205 obtains a frequency change attribute set based on the frequency change attribute, and then performs fluid identification.

[0145] In one example, obtaining a portion of the overlay data volume includes:

[0146] Within the effective angle range, the angles are divided, the superposition scheme is determined, and the superposition is performed separately to obtain the superimposed data volume shown.

[0147] In one example, the high-frequency attenuation properties and low-frequency absorption properties of a portion of the superimposed data volume are extracted as follows:

[0148] For each part of the superimposed data volume, the corresponding high-frequency attenuation attribute and low-frequency absorption attribute are extracted.

[0149] In one example, the frequency change attribute is:

[0150] A = f1(S1-S2)*f2(α*G1+β*G2)

[0151] Where: A represents the frequency variation attribute; f i Let i represent the normalization function, i = 1, 2; S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

[0152] In one example, obtaining the frequency change attribute Tween based on the frequency change attribute includes:

[0153] The frequency change attributes are rearranged according to the size of the superposition center angle to obtain the frequency change attribute set.

[0154] In one example, obtaining a frequency change attribute gather based on the frequency change attribute, and then performing fluid identification, includes:

[0155] Pre-stack frequency change attributes are calculated based on frequency change attributes, threshold values ​​are determined through typical wells, and fluid identification is carried out.

[0156] In one example, the pre-stack frequency variation property is calculated using the following formula:

[0157] A = μ + AG * angle

[0158] Where A represents the frequency variation attribute; angle is the angle; and AG is the pre-stack frequency variation attribute.

[0159] Example 5

[0160] This disclosure provides an electronic device, comprising: a memory storing executable instructions; and a processor executing the executable instructions in the memory to implement the aforementioned pre-stack frequency domain fluid identification method.

[0161] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0162] This memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0163] The processor may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of this disclosure, the processor is used to execute computer-readable instructions stored in the memory.

[0164] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0165] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0166] Example 6

[0167] This disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the pre-stack frequency domain fluid identification method.

[0168] A computer-readable storage medium according to embodiments of the present disclosure stores non-transitory computer-readable instructions. When these non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods described in the foregoing embodiments of the present disclosure are performed.

[0169] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0170] Those skilled in the art should understand that the above description of the embodiments of the present invention is only intended to illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any of the examples given.

[0171] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A pre-stack frequency domain fluid identification method, characterized in that, include: Based on the pre-stack angle gather data of typical well targets, the effective angle range was selected; Within the effective angle range, a portion of the superimposed data volume is acquired; Extract the high-frequency attenuation and low-frequency absorption properties of the superimposed data volume; Based on the high-frequency attenuation property and the low-frequency absorption property, calculate the frequency change property of the angular superposition body; Based on the frequency change attributes, a frequency change attribute set is obtained, and then fluid identification is performed.

2. The pre-stack frequency domain fluid identification method according to claim 1, wherein, The acquired overlay data includes: Within the effective angle range, the angles are divided to determine the superposition scheme, and the superposition is performed separately to obtain the superimposed data volume shown.

3. The pre-stack frequency domain fluid identification method according to claim 1, wherein, Extracting the high-frequency attenuation and low-frequency absorption properties of the aforementioned superimposed data volume includes: For each of the aforementioned superimposed data volumes, the corresponding high-frequency attenuation attributes and low-frequency absorption attributes are extracted.

4. The pre-stack frequency domain fluid identification method according to claim 1, wherein, The frequency change attribute is: A = f1(S1-S2)*f2(α*G1+β*G2) Where: A represents the frequency variation attribute; f i Let i represent the normalization function, i = 1, 2; S1 and S2 represent the low-frequency energy and high-frequency energy, respectively; G1 and G2 represent the low-frequency gradient and high-frequency gradient, respectively; and α and β are energy weighting factors.

5. The pre-stack frequency domain fluid identification method according to claim 1, wherein, The frequency change attribute collection obtained based on the frequency change attribute includes: The frequency change attributes are rearranged according to the superposition center angle to obtain the frequency change attribute set.

6. The pre-stack frequency domain fluid identification method according to claim 1, wherein, Obtaining a frequency change attribute gather based on the frequency change attribute, and then performing fluid identification, includes: Based on the frequency change attributes, calculate the pre-stack frequency change attributes, determine the threshold value through typical wells, and carry out fluid identification.

7. The pre-stack frequency domain fluid identification method according to claim 6, wherein, The pre-stack frequency variation attribute is calculated using the following formula: A = μ + AG * angle Where A represents the frequency variation attribute; angle is the angle; and AG is the pre-stack frequency variation attribute.

8. A pre-stack frequency domain fluid identification device, characterized in that, include: The filtering module filters the effective angle range based on the pre-stack angle gather data of typical well objectives. The partial overlay module acquires partial overlay data within the effective angle range; The extraction module extracts the high-frequency attenuation properties and low-frequency absorption properties of the superimposed data volume. The calculation module calculates the frequency change attribute of the angular superposition body based on the high-frequency attenuation attribute and the low-frequency absorption attribute. The identification module obtains a frequency change attribute set based on the frequency change attribute, and then performs fluid identification.

9. An electronic device, characterized in that, The electronic device includes: Memory, which stores executable instructions; A processor that executes the executable instructions in the memory to implement the pre-stack frequency domain fluid identification method 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 that, when executed by a processor, implements the pre-stack frequency domain fluid identification method according to any one of claims 1-7.

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