Oil and gas detection method, device and electronic equipment based on wide-azimuth data

Abstract

This application provides an oil and gas detection method, apparatus, and electronic device based on wide-azimuth data. The method includes: acquiring wide-azimuth seismic data of a target reservoir; extracting fast-speed azimuth seismic data from the wide-azimuth seismic data; performing frequency-band bandpass filtering on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands; extracting first seismic data and second seismic data from the multiple frequency bands of fast-speed seismic data; extracting the instantaneous amplitude attributes of the first and second seismic data to obtain a first instantaneous amplitude attribute volume and a second instantaneous amplitude attribute volume, respectively; obtaining a target oil and gas detection data volume based on the first and second instantaneous amplitude attribute volumes; and obtaining the oil and gas distribution range of the target reservoir based on the target oil and gas detection data volume.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration, and in particular to a method, apparatus, and electronic equipment for detecting oil and gas based on wide-azimuth data. Background Technology

[0002] In related technologies, oil and gas detection techniques are mainly based on two geophysical phenomena: amplitude variation with source-receiver distance (AVO) and amplitude variation with frequency (AVF), which occur when seismic waves pass through oil and gas layers. Examples include low-frequency enhanced slope attribute methods, high-frequency attenuated slope attribute methods, and single-frequency volume attribute methods. However, these methods are all based on attributes extracted from narrow-azimuth seismic data and do not consider the amplitude variation with azimuth (AVZ) in the lower gas layer.

[0003] Significant anisotropy exists in fault-developed zones and fractured reservoirs. When seismic waves propagate through gas layers (especially fractured gas reservoirs), their amplitude varies with the azimuth of the seismic observation, thus affecting the accuracy of oil and gas detection. Currently, there is a lack of effective solutions to these problems.

[0004] Therefore, how to eliminate the influence of geological body orientation anisotropy on the accuracy of oil and gas detection and improve the accuracy of oil and gas detection is an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides an oil and gas detection method, apparatus, electronic device, and storage medium based on wide-azimuth data, which are used to eliminate the influence of geological body azimuth anisotropy on the accuracy of oil and gas detection and improve the accuracy of oil and gas detection.

[0006] One embodiment of this application provides an oil and gas detection method based on wide azimuth data. The method includes: acquiring wide azimuth seismic data of a target reservoir; extracting fast-speed azimuth seismic data from the wide azimuth seismic data; performing frequency band bandpass filtering on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands; selecting, from the fast-speed seismic data in the multiple frequency bands, the seismic data with the largest amplitude enhancement in the lower gas layer of the target reservoir and a frequency band lower than a preset frequency band threshold, based on the original seismic profile after calibration of the known well gas layer, as the first seismic data; and based on the known... After the well gas layer is calibrated, the original seismic profile is used to select the seismic data with the largest amplitude attenuation in the lower gas layer of the target reservoir and a frequency band higher than a preset frequency band threshold from the fast-speed seismic data of the multiple frequency bands. This data is then used as the second seismic data. The instantaneous amplitude attributes of the first and second seismic data are extracted to obtain the first and second instantaneous amplitude attribute volumes, respectively. Based on the first and second instantaneous amplitude attribute volumes, the target oil and gas detection data volume is obtained. Based on the target oil and gas detection data volume, the oil and gas distribution range of the target reservoir is obtained.

[0007] In some embodiments, performing frequency band bandpass filtering on the fast azimuth seismic data to obtain fast azimuth seismic data in multiple frequency bands includes: obtaining seismic data in a first frequency band from the wide azimuth seismic data through a first bandpass filtering operation; obtaining seismic data in a second frequency band from the wide azimuth seismic data through a second bandpass filtering operation; obtaining seismic data in a third frequency band from the wide azimuth seismic data through a third bandpass filtering operation; and obtaining seismic data in a fourth frequency band from the wide azimuth seismic data through a fourth bandpass filtering operation; wherein the first frequency band and the second frequency band are lower than the dominant frequency of the wide azimuth seismic data, and the third frequency band and the fourth frequency band are higher than the dominant frequency of the wide azimuth seismic data, with the first frequency band lower than the second frequency band and the fourth frequency band higher than the third frequency band.

[0008] In some embodiments, obtaining the target oil and gas detection data body based on the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body includes: obtaining the target oil and gas detection data body y using the following formula:

[0009] y = AB

[0010] Wherein, A is the first instantaneous amplitude attribute body, and B is the second instantaneous amplitude attribute body.

[0011] In some embodiments, obtaining the oil and gas distribution range of the target reservoir based on the target oil and gas detection data volume includes: extracting the amplitude attribute corresponding to each gas layer of the target reservoir from the target oil and gas detection data volume, and obtaining the oil and gas distribution range of the target reservoir based on the amplitude attribute corresponding to all gas layers of the target reservoir.

[0012] One embodiment of this application provides an oil and gas detection device based on wide azimuth data. The device includes: a first acquisition module for acquiring wide azimuth seismic data of a target reservoir; a second acquisition module for extracting fast-speed azimuth seismic data from the wide azimuth seismic data; a third acquisition module for performing frequency band bandpass filtering on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands; a fourth acquisition module for selecting, based on the original seismic profile after calibration of a known well gas layer, the seismic data with the largest amplitude enhancement in the lower gas layer of the target reservoir and a frequency band lower than a preset frequency band threshold from the fast-speed seismic data in the multiple frequency bands, as the first seismic data; and a fifth acquisition module. The first module is used to select, based on the original seismic profile after calibration of the known well gas layer, the seismic data with the largest amplitude attenuation in the lower gas layer of the target reservoir and a frequency band higher than a preset frequency band threshold from the fast-speed seismic data of the multiple frequency bands, as the second seismic data; the sixth acquisition module is used to extract the instantaneous amplitude attributes of the first seismic data and the second seismic data to obtain the first instantaneous amplitude attribute volume and the second instantaneous amplitude attribute volume, respectively; the seventh acquisition module is used to obtain the target oil and gas detection data volume based on the first instantaneous amplitude attribute volume and the second instantaneous amplitude attribute volume; the eighth acquisition module is used to obtain the oil and gas distribution range of the target reservoir based on the target oil and gas detection data volume.

[0013] This application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the method described above when running the program.

[0014] This application provides a storage medium for storing a computer-readable program, which, when run, performs the method described above.

[0015] Compared with the prior art, the technical solution provided in this application has at least the following advantages: In the embodiments provided in this application, frequency band bandpass filtering is performed on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands; first seismic data and second seismic data are extracted from the fast-speed seismic data in these multiple frequency bands; based on the instantaneous amplitude attributes of the first and second seismic data, a first instantaneous amplitude attribute volume and a second instantaneous amplitude attribute volume are obtained respectively; based on the first instantaneous amplitude attribute volume and the second instantaneous amplitude attribute volume, the target oil and gas detection data volume is obtained; based on the target oil and gas detection data volume, the oil and gas distribution range of the target reservoir is obtained. This eliminates the influence of geological body azimuth anisotropy on the accuracy of oil and gas detection, improving the accuracy of oil and gas detection. Attached Figure Description

[0016] This application will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0017] Figure 1 This is an exemplary flowchart of an oil and gas detection method based on wide-azimuth data, according to some embodiments of this application;

[0018] Figure 2 This is an exemplary schematic diagram of a wide-azimuth original seismic profile according to some embodiments of this application;

[0019] Figure 3 This is an exemplary schematic diagram of a high-speed azimuth seismic profile according to some embodiments of this application;

[0020] Figure 4 This is an exemplary schematic diagram of a slow-velocity azimuth seismic profile according to some embodiments of this application;

[0021] Figure 5 This is an exemplary schematic diagram of a high-speed azimuth seismic profile in the 10-25 Hz frequency band, as shown in some embodiments of this application.

[0022] Figure 6 This is an exemplary schematic diagram of a high-velocity azimuth seismic profile in the 25-40 Hz frequency band, as shown in some embodiments of this application.

[0023] Figure 7 This is an exemplary schematic diagram of a high-speed azimuth instantaneous amplitude profile in the 10-25 Hz frequency band, as shown in some embodiments of this application.

[0024] Figure 8 This is an exemplary schematic diagram of a high-speed azimuth instantaneous amplitude profile in the 25-40 Hz frequency band according to some embodiments of this application;

[0025] Figure 9 This is an exemplary schematic diagram of an oil and gas detection profile calculated according to the methods shown in some embodiments of this application;

[0026] Figure 10 This is an exemplary schematic diagram of an oil and gas detection plane calculated according to the methods shown in some embodiments of this application;

[0027] Figure 11 This is an exemplary schematic diagram of an oil and gas detection plane calculated using other methods in related technologies;

[0028] Figure 12 These are exemplary schematic diagrams of an oil and gas detection device based on wide-angle data, according to some embodiments of this application;

[0029] Figure 13 This is an exemplary structural diagram of an electronic device according to some embodiments of this application. Detailed Implementation

[0030] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0031] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other words can achieve the same purpose, they may be replaced by other expressions.

[0032] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0033] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0034] Figure 1 This is a schematic diagram illustrating an application scenario of an oil and gas detection method based on wide-azimuth data, according to some embodiments of this application. For example... Figure 1 As shown, the method includes the following steps:

[0035] In step S110, wide-azimuth seismic data of the target reservoir are acquired.

[0036] Wide-azimuth exploration has a high ability to identify faults. Through wide-azimuth seismic data, the existence of faults and fractured reservoirs can be clearly reflected.

[0037] In step S120, fast azimuth seismic data is extracted from the wide azimuth seismic data.

[0038] As an example only, one can see from such Figure 2 Extracting from the wide-azimuth seismic data shown... Figure 3 The fast azimuth seismic data shown, and as follows Figure 4 The slow-velocity azimuth seismic data shown.

[0039] The phenomenon that the propagation velocity and particle polarization direction of seismic waves vary with the direction of wave propagation when the waves propagate in an anisotropic medium is called seismic anisotropy. Seismic anisotropy typically manifests in the following three aspects:

[0040] 1. The propagation speed of seismic waves varies with the direction of propagation.

[0041] 2. The propagation speed of seismic waves changes depending on the polarization direction of the wave particles. When an S-wave (seismic transverse wave) is incident on a regularly arranged fracture (anisotropic) region, it will split into a fast wave SH polarized along the fracture direction and a slow wave SV polarized perpendicular to the fracture direction.

[0042] 3. Abnormal polarization of wave particles will occur, that is, in anisotropic media, the wave polarization plane is usually neither parallel to nor perpendicular to the wave propagation direction.

[0043] Fast waves (SH) are polarized parallel to the fracture direction and can reflect the hydrocarbon reservoir information of the target reservoir; slow waves (SV) are polarized perpendicular to the fracture direction and can reflect the fracture information of the target reservoir. Therefore, by extracting fast-speed azimuth seismic data from wide-azimuth seismic data, the hydrocarbon reservoir information of the target reservoir can be accurately determined subsequently.

[0044] Anisotropy typically exists in fractured zones, especially in fractured reservoirs. Parallel to the fracture direction, seismic waves are only affected by reservoir thickness and fluids; perpendicular to the fracture direction, seismic waves are affected by the combined effects of reservoir thickness, fluids, and fractures. Therefore, conventional narrow-azimuth seismic data cannot accurately reflect the distribution of oil and gas when used for oil and gas detection.

[0045] The method provided in this application extracts seismic vector slices (i.e., fast azimuth seismic data) parallel to the direction of the fracture, thereby reducing the weakening effect of the fracture on the seismic waves and reflecting the distribution of oil and gas in a true and effective manner.

[0046] In step S130, the fast-speed azimuth seismic data is subjected to frequency band bandpass filtering to obtain fast-speed seismic data in multiple frequency bands.

[0047] In the specific implementation process, high-speed seismic data in multiple frequency bands can be obtained in the following ways: First band-pass filtering is used to obtain seismic data in the first frequency band from the wide-azimuth seismic data; second band-pass filtering is used to obtain seismic data in the second frequency band from the wide-azimuth seismic data; third band-pass filtering is used to obtain seismic data in the third frequency band from the wide-azimuth seismic data; and fourth band-pass filtering is used to obtain seismic data in the fourth frequency band from the wide-azimuth seismic data. Specifically, the first and second frequency bands are lower than the dominant frequency of the wide-azimuth seismic data, while the third and fourth frequency bands are higher than the dominant frequency of the wide-azimuth seismic data. The first frequency band is lower than the second frequency band, and the fourth frequency band is higher than the third frequency band.

[0048] In practice, the first frequency band and the second frequency band can be frequency bands that are adjacent to the main frequency and lower than the main frequency, or they can be frequency bands that are not adjacent to the main frequency and lower than the main frequency, and are not limited by the description in this specification.

[0049] In practice, the third and fourth frequency bands can be frequency bands that are adjacent to and higher than the main frequency, or they can be frequency bands that are not adjacent to the main frequency but are higher than the main frequency, and are not limited by the description in this specification.

[0050] As an example only, the dominant frequency of the wide-azimuth seismic data acquired in step S110 is 25 Hz, which can be obtained using frequency division bandpass filtering. Figure 3 The following frequency bands of seismic data were obtained from the fast azimuth seismic data shown: the first band of 5-10 Hz, the second band of 10-25 Hz, the third band of 25-40 Hz, and the fourth band of 40-60 Hz.

[0051] In step S140, based on the original seismic profile after the known well gas layer calibration, the seismic data with the largest amplitude enhancement in the lower gas layer of the target reservoir and a frequency band lower than the preset frequency band threshold is selected from the fast seismic data of multiple frequency bands as the first seismic data.

[0052] When seismic waves propagate in anisotropic media, different frequencies of shear waves exhibit different responses due to variations in rock scale and orientation. In the presence of fracture groups of different scales, microfractures are oriented under constraints such as historical stress fields and sedimentary processes. The polarization direction determined using low-frequency information can be considered the dominant fracture direction, resulting in increased amplitude in low-frequency seismic data below the gas layer of the target reservoir. Conversely, the polarization direction determined using high-frequency information can be considered the direction of the microfractures, leading to decreased amplitude in high-frequency seismic data below the gas layer of the target reservoir.

[0053] In order to obtain oil and gas detection data that can clearly reflect the information of the target reservoir, the seismic data with the largest amplitude enhancement in the lower gas layer of the target reservoir is selected from the two sets of low-frequency data obtained in step S130 and used as the first seismic data.

[0054] As an example only, from the seismic data of the first and second frequency bands in the example of step S130, the seismic data of the second frequency band with the largest amplitude enhancement in the lower gas layer of the target reservoir can be selected (e.g., Figure 5 (As shown), as the first earthquake data.

[0055] In step S150, based on the original seismic profile after the known well gas layer calibration, the seismic data with the largest amplitude attenuation in the lower gas layer of the target reservoir and a frequency band higher than the preset frequency band threshold is selected from the fast seismic data of multiple frequency bands as the second seismic data.

[0056] In order to obtain oil and gas detection data that can clearly reflect the oil and gas reservoir information of the target reservoir, the seismic data with the largest amplitude attenuation in the lower gas layer of the target reservoir is selected from the two sets of high-frequency data obtained in step S130 and used as the first seismic data.

[0057] As an example only, from the seismic data of the third frequency band and the seismic data of the fourth frequency band in the example of step S130, the seismic data of the third frequency band with the largest amplitude attenuation in the lower gas layer of the target reservoir can be selected (e.g., Figure 6 (As shown), as the second earthquake data.

[0058] In step S160, the instantaneous amplitude attributes of the first earthquake data and the second earthquake data are extracted to obtain the first instantaneous amplitude attribute volume and the second instantaneous amplitude attribute volume, respectively.

[0059] In the specific implementation process, common methods can be used to extract the instantaneous amplitude attributes of the first and second earthquake data. For the first instantaneous amplitude attribute data, please refer to [link to relevant documentation]. Figure 7 For the second instantaneous amplitude attribute, see [link / reference]. Figure 8 .

[0060] In step S170, the target oil and gas detection data volume is obtained based on the first instantaneous amplitude attribute volume and the second instantaneous amplitude attribute volume.

[0061] In the specific implementation process, the target oil and gas detection data volume y can be obtained using the following formula:

[0062] y = AB (1)

[0063] Where A is the first instantaneous amplitude attribute body and B is the second instantaneous amplitude attribute body.

[0064] In the embodiments provided in this application, based on the difference between the instantaneous amplitude attributes of the first seismic data (amplitude enhancement in the lower part of the gas layer) and the second seismic data (amplitude decay in the lower part of the gas layer), an oil and gas detection data volume that can clearly reflect the oil and gas reservoir information of the target reservoir can be obtained.

[0065] In step S180, the oil and gas distribution range of the target reservoir is obtained based on the target oil and gas detection data.

[0066] In the specific implementation process, the amplitude attributes corresponding to each gas layer of the target reservoir can be extracted from the target oil and gas detection data volume. Based on the amplitude attributes corresponding to all gas layers of the target reservoir, the following can be obtained: Figure 9 The target reservoir's oil and gas distribution range is shown.

[0067] In related technologies, methods for detecting oil and gas using low-frequency or high-frequency slopes (including single-frequency volumes) are theoretically based on selecting any two points on a smooth spectral curve for calculation, resulting in identical results. However, actual seismic data spectral curves are not smooth curves; the amplitude fluctuations in the spectrum are abrupt, and the linear relationships between multiple points differ. The calculation results exhibit randomness depending on the selected points.

[0068] In the embodiments provided in this application, the difference in amplitude between high and low frequency seismic data is directly calculated, covering most of the seismic data spectrum. There is no slope calculation of the line connecting two points or calculation of two single-frequency bodies. Therefore, a more accurate oil and gas distribution range of the target reservoir can be obtained.

[0069] contrast Figure 10 and Figure 11 As can be seen, the oil and gas detection data obtained according to the embodiments of this application has a much higher vertical resolution than the oil and gas detection data obtained by the methods provided by related technologies. It also effectively eliminates the influence of non-reservoir sections on the oil and gas detection results and reduces the ambiguity of conventional oil and gas detection results. Furthermore, by comparing with drilled wells, the oil and gas detection data obtained through the embodiments of this application are completely consistent with the drilled wells, which greatly improves the accuracy of the oil and gas detection results.

[0070] Figure 12 This is an exemplary schematic diagram of an oil and gas detection device based on wide-angle data, according to some embodiments of this application.

[0071] like Figure 12 As shown, the oil and gas detection device based on wide-azimuth data includes: a first acquisition module 1210, a second acquisition module 1220, a third acquisition module 1230, a fourth acquisition module 1240, a fifth acquisition module 1250, a sixth acquisition module 1260, a seventh acquisition module 1270, and an eighth acquisition module 1280.

[0072] The first acquisition module 1210 is used to acquire wide-azimuth seismic data of the target reservoir.

[0073] The second acquisition module 1220 is used to extract fast azimuth seismic data from the wide azimuth seismic data.

[0074] The third acquisition module 1230 is used to perform frequency band bandpass filtering on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands.

[0075] The fourth acquisition module 1240 is used to select, from the fast seismic data of the multiple frequency bands, the seismic data with the largest amplitude enhancement in the lower part of the gas layer of the target reservoir and the frequency band lower than the preset frequency band threshold, based on the original seismic profile after the known well gas layer calibration, as the first seismic data.

[0076] The fifth acquisition module 1250 is used to select, from the fast seismic data of the multiple frequency bands, the seismic data with the largest amplitude attenuation in the lower part of the gas layer of the target reservoir and the frequency band higher than the preset frequency band threshold, based on the original seismic profile after the known well gas layer calibration, as the second seismic data.

[0077] The sixth acquisition module 1260 is used to extract the instantaneous amplitude attributes of the first earthquake data and the second earthquake data, and obtain the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body respectively.

[0078] The seventh acquisition module 1270 is used to obtain the target oil and gas detection data body based on the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body.

[0079] The eighth acquisition module 1280 is used to obtain the oil and gas distribution range of the target reservoir based on the target oil and gas detection data.

[0080] In some embodiments, performing frequency band bandpass filtering on the fast azimuth seismic data to obtain fast azimuth seismic data in multiple frequency bands includes: obtaining seismic data in a first frequency band from the wide azimuth seismic data through a first bandpass filtering operation; obtaining seismic data in a second frequency band from the wide azimuth seismic data through a second bandpass filtering operation; obtaining seismic data in a third frequency band from the wide azimuth seismic data through a third bandpass filtering operation; and obtaining seismic data in a fourth frequency band from the wide azimuth seismic data through a fourth bandpass filtering operation; wherein the first frequency band and the second frequency band are lower than the dominant frequency of the wide azimuth seismic data, and the third frequency band and the fourth frequency band are higher than the dominant frequency of the wide azimuth seismic data, with the first frequency band lower than the second frequency band and the fourth frequency band higher than the third frequency band.

[0081] In some embodiments, obtaining the target oil and gas detection data body based on the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body includes: obtaining the target oil and gas detection data body y using the following formula:

[0082] y = AB

[0083] Wherein, A is the first instantaneous amplitude attribute body, and B is the second instantaneous amplitude attribute body.

[0084] In some embodiments, obtaining the oil and gas distribution range of the target reservoir based on the target oil and gas detection data volume includes: extracting the amplitude attribute corresponding to each gas layer of the target reservoir from the target oil and gas detection data volume, and obtaining the oil and gas distribution range of the target reservoir based on the amplitude attribute corresponding to all gas layers of the target reservoir.

[0085] In the above embodiments of the oil and gas detection device based on wide-angle data, the specific processing of each module and its resulting technical effects can be referred to the relevant descriptions in the corresponding method embodiments, and will not be repeated here.

[0086] Figure 13 This is an exemplary structural diagram of an electronic device according to some embodiments of this application. For example... Figure 13 As shown, the electronic device includes: at least one processor 1301, at least one communication interface 1302, at least one memory 1303, and at least one communication bus 1304. Optionally, the communication interface 1302 can be an interface for a communication module, such as an interface for a GSM module. The processor 1301 may be a CPU, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The memory 1303 may include high-speed RAM and may also include non-volatile memory, such as at least one disk storage device. The memory 1303 stores a program, and the processor 1301 calls the program stored in the memory 1303 to execute some or all of the above-described method embodiments.

[0087] This application relates to a storage medium for storing a computer-readable program, which, when run, performs some or all of the above-described method embodiments.

[0088] Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0089] Based on the same inventive concept, this application also provides a computer program product, including a computer program that, when executed by a processor, implements some or all of the above-described method embodiments.

[0090] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.

[0091] Furthermore, this application uses specific terms to describe its embodiments. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of this application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this application do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application can be appropriately combined.

[0092] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this application are not intended to limit the order of the processes and methods of this application. Although the foregoing disclosure has discussed some currently considered useful embodiments of the invention through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the substance and scope of the embodiments of this application. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely through software solutions, such as installing the described system on existing servers or mobile devices.

[0093] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, this disclosure method does not imply that the subject matter of the application requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of the single embodiments disclosed above.

[0094] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of scope in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0095] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, and documents referenced in this application, the entire contents of that patent are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this application, as well as documents that limit the broadest scope of the claims in this application (currently or subsequently appended to this application). It should be noted that if there are any inconsistencies or conflicts between the descriptions, definitions, and / or terminology used in the supplementary materials of this application and the content of this application, the descriptions, definitions, and / or terminology used in this application shall prevail.

[0096] Finally, it should be understood that the embodiments described in this application are merely illustrative of the principles of the embodiments of this application. Other modifications may also fall within the scope of this application. Therefore, alternative configurations of the embodiments of this application are considered as examples and not limitations, and are regarded as consistent with the teachings of this application. Accordingly, the embodiments of this application are not limited to the embodiments explicitly described and illustrated in this application.

Claims

1. A method for detecting oil and gas based on wide-azimuth data, characterized in that, The method includes: Acquire wide-azimuth seismic data of the target reservoir; Extract fast azimuth seismic data from the wide azimuth seismic data; The fast-rate azimuth seismic data is subjected to frequency band bandpass filtering to obtain fast-rate seismic data in multiple frequency bands; Based on the original seismic profile after the known well gas layer calibration, the seismic data with the largest amplitude enhancement in the lower gas layer of the target reservoir and a frequency band lower than the preset frequency band threshold is selected from the fast seismic data of the multiple frequency bands as the first seismic data; Based on the original seismic profile after the known well gas layer calibration, from the fast seismic data of the multiple frequency bands, the seismic data with the largest amplitude attenuation in the lower gas layer of the target reservoir and a frequency band higher than the preset frequency band threshold is selected as the second seismic data; Extract the instantaneous amplitude attributes of the first earthquake data and the second earthquake data to obtain the first instantaneous amplitude attribute volume and the second instantaneous amplitude attribute volume, respectively; Based on the first instantaneous amplitude attribute volume and the second instantaneous amplitude attribute volume, the target oil and gas detection data volume is obtained; Based on the target oil and gas detection data, the oil and gas distribution range of the target reservoir is obtained.

2. The method according to claim 1, characterized in that, The step of performing frequency-band bandpass filtering on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands includes: Seismic data in the first frequency band is obtained from the wide-azimuth seismic data through a first bandpass filtering operation; Seismic data in the second frequency band is obtained from the wide-azimuth seismic data through a second bandpass filtering operation; Seismic data in the third frequency band is obtained from the wide-azimuth seismic data through a third bandpass filtering operation; Seismic data in the fourth frequency band is obtained from the wide-azimuth seismic data through a fourth bandpass filtering operation; Wherein, the first frequency band and the second frequency band are lower than the dominant frequency of the wide-azimuth seismic data, and the third frequency band and the fourth frequency band are higher than the dominant frequency of the wide-azimuth seismic data, with the first frequency band being lower than the second frequency band and the fourth frequency band being higher than the third frequency band.

3. The method according to claim 1, characterized in that, The step of obtaining the target oil and gas detection data body based on the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body includes: The target oil and gas detection data volume y is obtained using the following formula: y = AB Wherein, A is the first instantaneous amplitude attribute body, and B is the second instantaneous amplitude attribute body.

4. The method according to claim 1, characterized in that, The step of obtaining the oil and gas distribution range of the target reservoir based on the target oil and gas detection data includes: The amplitude attributes corresponding to each gas layer of the target reservoir are extracted from the target oil and gas detection data volume, and the oil and gas distribution range of the target reservoir is obtained based on the amplitude attributes corresponding to all gas layers of the target reservoir.

5. An oil and gas detection device based on wide-azimuth data, characterized in that, The device includes: The first acquisition module is used to acquire wide-azimuth seismic data of the target reservoir; The second acquisition module is used to extract fast azimuth seismic data from the wide azimuth seismic data; The third acquisition module is used to perform frequency band bandpass filtering on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands. The fourth acquisition module is used to select, from the fast seismic data of the multiple frequency bands, the seismic data with the largest amplitude enhancement in the lower gas layer of the target reservoir and a frequency band lower than a preset frequency band threshold, based on the original seismic profile after the known well gas layer calibration, as the first seismic data; The fifth acquisition module is used to select, from the fast seismic data of the multiple frequency bands, the seismic data with the largest amplitude attenuation in the lower part of the gas layer of the target reservoir and the frequency band higher than the preset frequency band threshold, based on the original seismic profile after the known well gas layer calibration, as the second seismic data; The sixth acquisition module is used to extract the instantaneous amplitude attributes of the first seismic data and the second seismic data, and obtain the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body respectively; The seventh acquisition module is used to obtain the target oil and gas detection data body based on the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body; The eighth acquisition module is used to obtain the oil and gas distribution range of the target reservoir based on the target oil and gas detection data.

6. The apparatus according to claim 5, characterized in that, The step of performing frequency-band bandpass filtering on the fast-speed azimuth seismic data to obtain fast-speed seismic data in multiple frequency bands includes: Seismic data in the first frequency band is obtained from the wide-azimuth seismic data through a first bandpass filtering operation; Seismic data in the second frequency band is obtained from the wide-azimuth seismic data through a second bandpass filtering operation; Seismic data in the third frequency band is obtained from the wide-azimuth seismic data through a third bandpass filtering operation; Seismic data in the fourth frequency band is obtained from the wide-azimuth seismic data through a fourth bandpass filtering operation; Wherein, the first frequency band and the second frequency band are lower than the dominant frequency of the wide-azimuth seismic data, and the third frequency band and the fourth frequency band are higher than the dominant frequency of the wide-azimuth seismic data, with the first frequency band being lower than the second frequency band and the fourth frequency band being higher than the third frequency band.

7. The apparatus according to claim 5, characterized in that, The step of obtaining the target oil and gas detection data body based on the first instantaneous amplitude attribute body and the second instantaneous amplitude attribute body includes: The target oil and gas detection data volume y is obtained using the following formula: y = AB Wherein, A is the first instantaneous amplitude attribute body, and B is the second instantaneous amplitude attribute body.

8. The apparatus according to claim 5, characterized in that, The step of obtaining the oil and gas distribution range of the target reservoir based on the target oil and gas detection data includes: The amplitude attributes corresponding to each gas layer of the target reservoir are extracted from the target oil and gas detection data volume, and the oil and gas distribution range of the target reservoir is obtained based on the amplitude attributes corresponding to all gas layers of the target reservoir.

9. An electronic device comprising a memory and a processor, the memory storing a computer program, the processor executing the method as described in any one of claims 1 to 4 when running the program.

10. A storage medium for storing a computer-readable program, which, when executed, performs the method as described in any one of claims 1 to 4.

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