A method and device for identifying heterogeneous reservoirs based on seismic dominant frequency

Abstract

The embodiment of the present invention provides a method and device for identifying heterogeneous reservoirs based on seismic dominant frequency, which is mainly aimed at carbonate heterogeneous reservoirs. Based on well seismic calibration, spectrum analysis is carried out to obtain the seismic spectrum characteristics of the target formation; based on the understanding of the seismic response characteristics of the seismic reservoir, tuned frequency analysis is carried out by means of frequency division to obtain the seismic dominant frequency of the reservoir; the original seismic pure wave data is filtered according to the dominant frequency band of the reservoir to obtain the seismic pure wave data within the dominant frequency band; by establishing a porosity data body label, seismic intelligent interpretation is carried out within the seismic dominant frequency band to obtain the porosity data corresponding to the heterogeneous reservoir, and the identification of the heterogeneous reservoir is completed.

Description

Technical Field

[0001] The present invention relates to the field of seismic exploration technology, and in particular to a method and device for identifying heterogeneous reservoirs based on seismic dominant frequency. Background Art

[0002] Currently, the prediction of heterogeneous reservoirs, such as carbonate reservoirs, relies primarily on seismic attributes, primarily amplitude attributes (such as root mean square amplitude). However, due to the strong heterogeneity of heterogeneous reservoirs, the strength of reservoir development is directly proportional to the seismic response. Many high-quality reservoirs are obscured by the background of seismic data. Therefore, it is crucial to identify reservoirs obscured by the seismic background. Summary of the Invention

[0003] In response to the problems in the prior art, embodiments of the present invention provide a method and apparatus for identifying heterogeneous reservoirs based on seismic dominant frequency, which can at least partially solve the problems in the prior art.

[0004] In one aspect, a method for identifying heterogeneous reservoirs based on seismic dominant frequencies comprises:

[0005] Perform spectrum analysis on the original seismic pure wave data to obtain the spectrum characteristic data of the seismic reservoir segment;

[0006] identifying a dominant frequency band in the seismic reservoir segment according to the frequency spectrum characteristic data;

[0007] Performing filtering processing on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band;

[0008] Seismic interpretation is performed on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir.

[0009] In a preferred embodiment, the spectrum analysis of the original seismic pure wave data to obtain the spectrum characteristic data of the seismic reservoir segment includes:

[0010] Performing reservoir seismic response characteristic analysis on the original seismic pure wave data in combination with reservoir calibration to obtain reservoir seismic response data;

[0011] Spectral analysis of reservoir seismic response data is performed to obtain spectral characteristic data of the seismic reservoir segment.

[0012] In a preferred embodiment, the original seismic pure wave data is post-stack seismic data.

[0013] In a preferred embodiment, the identifying a dominant frequency band in the seismic reservoir segment based on the frequency spectrum characteristic data includes:

[0014] According to the frequency spectrum characteristic data, a seismic single-frequency data volume is obtained by using a frequency division method;

[0015] The seismic single-frequency data volume is subjected to tuned frequency analysis in combination with reservoir calibration to obtain a dominant frequency band of the reservoir.

[0016] In a preferred embodiment, the filtering process includes: band-pass filtering process, wherein the filtering process includes filtering the original seismic pure wave data according to the dominant frequency band, including:

[0017] The original seismic pure wave data is subjected to bandpass filtering according to the dominant frequency band to obtain the seismic pure wave data corresponding to the dominant frequency band.

[0018] In a preferred embodiment, performing bandpass filtering on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band includes:

[0019] Setting the filtering frequency band corresponding to the dominant frequency band;

[0020] Performing bandpass filtering on the original seismic pure wave data using the filter frequency band corresponding to the dominant frequency band;

[0021] The original seismic pure wave data and its corresponding frequency spectrum characteristic data are compared with the seismic pure wave data after bandpass filtering and its corresponding frequency spectrum characteristic data to obtain the seismic pure wave data corresponding to the dominant frequency band.

[0022] In a preferred embodiment, performing seismic interpretation and reservoir simulation on seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir includes:

[0023] By establishing lithologic data volume labels, we conduct seismic intelligent interpretation and reservoir simulation within the dominant seismic frequency band to obtain lithologic data corresponding to heterogeneous reservoirs.

[0024] Identify heterogeneous reservoirs based on their corresponding lithologic data.

[0025] In a preferred embodiment, performing seismic interpretation on seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir includes:

[0026] By establishing porosity data volume labels and conducting seismic intelligent interpretation within the dominant seismic frequency band, we can obtain porosity data corresponding to heterogeneous reservoirs.

[0027] Identify heterogeneous reservoirs based on their corresponding porosity data.

[0028] In a preferred embodiment, performing seismic interpretation on seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir includes:

[0029] By establishing permeability data volume labels, we conduct seismic intelligent interpretation and reservoir simulation within the dominant seismic frequency band to obtain permeability data corresponding to heterogeneous reservoirs.

[0030] Identify heterogeneous reservoirs based on their corresponding permeability data.

[0031] In another aspect, a device for identifying heterogeneous reservoirs based on seismic dominant frequencies comprises:

[0032] The spectrum analysis module performs spectrum analysis on the original seismic pure wave data to obtain the spectrum characteristic data of the seismic reservoir segment;

[0033] A dominant frequency band identification module, which identifies a dominant frequency band in the seismic reservoir segment according to the frequency spectrum characteristic data;

[0034] a filtering module, performing filtering processing on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band;

[0035] The heterogeneous reservoir identification module performs seismic interpretation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir.

[0036] In a preferred embodiment, the spectrum analysis module includes:

[0037] A characteristic analysis unit, which performs reservoir seismic response characteristic analysis on the original seismic pure wave data in combination with reservoir calibration to obtain reservoir seismic response data;

[0038] The spectrum analysis unit performs spectrum analysis on the reservoir seismic response data to obtain spectrum characteristic data of the seismic reservoir segment.

[0039] In a preferred embodiment, the original seismic pure wave data is post-stack seismic data.

[0040] In a preferred embodiment, the dominant frequency band identification module includes:

[0041] A single-frequency data volume generating unit is configured to obtain a seismic single-frequency data volume using a frequency dividing device according to the frequency spectrum characteristic data;

[0042] The dominant frequency band acquisition unit performs tuned frequency analysis on the seismic single-frequency data volume in combination with reservoir calibration to obtain the dominant frequency band of the reservoir.

[0043] In a preferred embodiment, the filtering process includes: band-pass filtering process, and the filtering module specifically performs band-pass filtering process on the original seismic pure wave data according to the dominant frequency band to obtain the seismic pure wave data corresponding to the dominant frequency band.

[0044] In a preferred embodiment, the filtering module specifically includes:

[0045] A setting unit, configured to set a filtering frequency band corresponding to the dominant frequency band;

[0046] a processing unit, performing bandpass filtering on the original seismic pure wave data using the filter frequency band corresponding to the dominant frequency band;

[0047] The comparison unit compares the original seismic pure wave data and its corresponding frequency spectrum characteristic data with the seismic pure wave data after bandpass filtering and its corresponding frequency spectrum characteristic data to obtain the seismic pure wave data corresponding to the dominant frequency band.

[0048] In a preferred embodiment, the heterogeneous reservoir identification module includes:

[0049] The lithologic data generation unit establishes lithologic data volume labels, conducts seismic intelligent interpretation and reservoir simulation within the dominant seismic frequency band, and obtains lithologic data corresponding to heterogeneous reservoirs.

[0050] The lithologic data identification unit identifies the heterogeneous reservoir according to the lithologic data corresponding to the heterogeneous reservoir.

[0051] In a preferred embodiment, the heterogeneous reservoir identification module includes:

[0052] The porosity data generation unit establishes porosity data volume labels, conducts seismic intelligent interpretation and reservoir simulation within the seismic dominant frequency band, and obtains porosity data corresponding to heterogeneous reservoirs;

[0053] The porosity data identification unit identifies the heterogeneous reservoir according to the porosity data corresponding to the heterogeneous reservoir.

[0054] In a preferred embodiment, the heterogeneous reservoir identification module includes:

[0055] The permeability data generation unit establishes permeability data volume labels, conducts seismic intelligent interpretation and reservoir simulation within the seismic dominant frequency band, and obtains permeability data corresponding to heterogeneous reservoirs;

[0056] The permeability data identification unit identifies the heterogeneous reservoir according to the permeability data corresponding to the heterogeneous reservoir.

[0057] On the other hand, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the heterogeneous reservoir identification method based on seismic dominant frequency described in any of the above embodiments are implemented.

[0058] In another aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the heterogeneous reservoir identification method based on seismic dominant frequency described in any of the above embodiments.

[0059] The embodiment of the present invention provides a method and device for identifying heterogeneous reservoirs based on seismic dominant frequency, which is mainly aimed at carbonate heterogeneous reservoirs. Based on the understanding of the seismic response characteristics of seismic reservoirs, the seismic spectrum characteristics of the seismic reservoirs are summarized in combination with spectrum analysis; based on the frequency division effect, interpretation is carried out within the seismic dominant frequency band, which is more conducive to the identification of intra-platform shoal heterogeneous reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0061] Figure 1 It is a flow chart of a method for identifying heterogeneous reservoirs based on seismic dominant frequency provided by an embodiment of the present invention.

[0062] Figure 2 Schematic diagram of data relationships of a carbonate reservoir identification method based on seismic dominant frequency according to an embodiment of the present invention.

[0063] Figure 3 This is a distribution diagram of reservoir dominant frequency bands according to a specific embodiment of the present invention.

[0064] Figure 4 Schematic diagram of original seismic pure wave data, seismic pure wave data after bandpass filtering and their spectrum characteristics according to a specific embodiment of the present invention.

[0065] Figure 5 3 is a schematic structural diagram of a heterogeneous reservoir identification device based on seismic dominant frequency provided by an embodiment of the present invention.

[0066] Figure 6 It is a schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of this application can be combined with each other in any manner.

[0068] Figure 1 This is a flow chart of a carbonate reservoir identification method based on seismic dominant frequency according to an embodiment of the present invention. Figure 2 Schematic diagram of data relationships of a carbonate reservoir identification method based on seismic dominant frequency according to an embodiment of the present invention. Figure 1 and Figure 2 As shown, the heterogeneous reservoir identification method based on seismic dominant frequency provided by the embodiment of the present invention includes:

[0069] S101, performing spectrum analysis on the original seismic pure wave data to obtain spectrum characteristic data of the seismic reservoir segment;

[0070] Specifically, it can be understood that the original seismic pure wave data can be post-stack seismic data. The present invention is mainly used for post-stack interpretation. Among them, the execution body of the heterogeneous reservoir identification method based on seismic dominant frequency provided by the embodiment of the present invention includes but is not limited to a server, or a host computer, etc.

[0071] S102, identifying a dominant frequency band in the seismic reservoir segment according to the frequency spectrum characteristic data;

[0072] Specifically, according to the spectrum characteristics, the frequency division method is used to obtain the seismic single-frequency data body, and the tuning frequency analysis is performed based on the single-frequency data body combined with reservoir calibration to obtain the dominant frequency band of the reservoir; among them, the frequency division method can be specifically preferred.

[0073] S103 , filtering the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band.

[0074] Specifically, a filter frequency band corresponding to the dominant frequency band can be set and used to perform bandpass filtering on the original seismic pure wave data to obtain the seismic pure wave data corresponding to the dominant frequency band. In addition, after the bandpass filtering, the original seismic pure wave data and its spectrum can be compared with the seismic pure wave data and its spectrum after the bandpass filtering to obtain the seismic pure wave data corresponding to the dominant frequency band.

[0075] S104: Perform seismic interpretation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir.

[0076] The heterogeneous reservoir identification method based on seismic dominant frequency provided in an embodiment of the present invention is mainly aimed at carbonate heterogeneous reservoirs. Based on the understanding of the seismic response characteristics of the seismic reservoir, the seismic spectrum characteristics of the seismic reservoir are summarized in combination with spectrum analysis; based on the frequency division effect, interpretation is carried out within the seismic dominant frequency band, which is more conducive to the identification of intra-platform shoal heterogeneous reservoirs.

[0077] On the basis of the above embodiments, step S101 further specifically includes:

[0078] S1011: performing reservoir seismic response characteristic analysis on the original seismic pure wave data in combination with reservoir calibration to obtain reservoir seismic response data;

[0079] S1012: Perform spectrum analysis on the reservoir seismic response data to obtain spectrum characteristic data of the seismic reservoir segment.

[0080] For example, by analyzing and summarizing the seismic profile characteristics of the intra-platform shoal reservoir encountered during drilling, the seismic response of the intra-platform shoal reservoir is divided into two categories: beaded strong reflection and chaotic-weak reflection; among them,

[0081] Reservoirs with bead-like strong reflection characteristics are mainly pore-vuggy reservoirs or fracture-pore-vuggy reservoirs. Their formation mechanism is mainly due to the obvious velocity difference between the reservoir and the surrounding rock.

[0082] The reservoir types showing chaotic-weak reflection characteristics are mainly fracture-type reservoirs or fracture-pore-type reservoirs. The formation mechanism is mainly due to the fact that the wave impedance difference between this type of reservoir and the surrounding rock is not obvious, making it difficult to form beaded strong reflection characteristics.

[0083] In some embodiments, step S102 specifically includes:

[0084] S1021: Obtaining a seismic single-frequency data volume using a frequency division method according to the frequency spectrum characteristic data;

[0085] S1022: Performing tuned frequency analysis on the seismic single-frequency data volume in combination with reservoir calibration to obtain a dominant frequency band of the reservoir.

[0086] Specifically, the frequency division method is applied to calculate the single-frequency tuning body of post-stack seismic pure wave data. The tuning body (20 Hz) retains the strength-weak relationship characteristics of the original strong and weak reflection signals while improving the resolution.

[0087] Based on the above embodiments, it can be understood that the filtering process includes bandpass filtering, and step S103 specifically includes: performing bandpass filtering on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band.

[0088] Furthermore, in some embodiments, more specifically, the step includes:

[0089] S1031: Setting the filtering frequency band corresponding to the dominant frequency band;

[0090] S1032: performing bandpass filtering on the original seismic pure wave data using the filter frequency band corresponding to the dominant frequency band;

[0091] S1033: Compare the original seismic pure wave data and its corresponding frequency spectrum characteristic data with the seismic pure wave data after bandpass filtering and its corresponding frequency spectrum characteristic data to obtain seismic pure wave data corresponding to the dominant frequency band.

[0092] For example, Figure 3 This is a distribution diagram of reservoir dominant frequency bands according to a specific embodiment of the present invention, as shown in FIG. Figure 3 As shown in the figure, based on the analysis of the seismic spectrum characteristics of the above-mentioned intra-platform shoal reservoir section, and considering the tuning frequency distribution characteristics of the reservoir, it is concluded that the dominant frequency distribution range of the beaded reflection reservoir section is 5 Hz-35 Hz, while the dominant frequency distribution range of the non-beaded weak reflection reservoir section is 15-25 Hz.

[0093] In conjunction with step 103 , a 10 Hz-15 Hz-25 Hz-30 Hz bandpass filter is designed to perform filtering on the original post-stack pure wave data.

[0094] Figure 4 Schematic diagram of original seismic pure wave data and seismic pure wave data after bandpass filtering and their spectrum characteristics according to a specific embodiment of the present invention. Figure 4 As shown in the figure, by comparing the pure wave data and their spectral characteristics before and after filtering, it is found that after filtering, the information in the dominant frequency band is more focused, the amplitude energy of the reservoir section is stronger, and it is more conducive to reservoir identification.

[0095] At the same time, the root mean square amplitude attributes are extracted from the filtered pure wave data. By comparison, it is found that the above three amplitude attributes can all be identified for beaded strong amplitude reservoirs; for non-beaded weak amplitude reservoirs, the original root mean square amplitude cannot be identified; the generalized S transform 20hz frequency division root mean square amplitude has a certain response; and the root mean square amplitude extracted from the filtered data has the strongest ability to characterize weak amplitude reservoirs.

[0096] Based on the above embodiment, step S104 further specifically includes:

[0097] S1041-1: By establishing lithologic data volume labels, intelligent seismic interpretation and reservoir simulation are performed within the dominant seismic frequency band to obtain lithologic data corresponding to heterogeneous reservoirs.

[0098] S1042-1: Identify heterogeneous reservoirs based on the lithologic data corresponding to the heterogeneous reservoirs.

[0099] For example, by applying the above-mentioned filtered seismic pure wave data to carry out predictions, the lithologic data volume labels corresponding to the heterogeneous reservoirs are obtained, thus realizing the prediction of the heterogeneous reservoirs in the intra-platform beach.

[0100] In other embodiments, reservoir identification may also be performed using porosity data volumes. Specifically, step S104 includes:

[0101] S1041-2: By establishing porosity data volume labels, seismic intelligent interpretation is carried out within the dominant seismic frequency band to obtain porosity data corresponding to heterogeneous reservoirs;

[0102] S1042-2: Identify heterogeneous reservoirs based on their corresponding porosity data.

[0103] In other embodiments, reservoir identification may also be performed using permeability data volumes. Specifically, step S104 includes:

[0104] S1041-3: By establishing permeability data volume labels, intelligent seismic interpretation and reservoir simulation are carried out within the dominant seismic frequency band to obtain permeability data corresponding to heterogeneous reservoirs;

[0105] S1042-3: Identify heterogeneous reservoirs based on the permeability data corresponding to the heterogeneous reservoirs.

[0106] In addition, the original prediction results had poor resolution between reservoirs and non-reservoirs. However, the prediction results using the new data better characterized non-beaded weak reflection reservoirs such as those in wells T45 and T451 while retaining the reservoir information corresponding to beaded strong reflections such as those in wells Z17, Z16, and Z162, achieving better prediction results.

[0107] It can be understood that the heterogeneous reservoir identification method based on seismic dominant frequency provided in the embodiment of the present invention is mainly aimed at carbonate heterogeneous reservoirs. Based on the understanding of the seismic response characteristics of the seismic reservoir, the seismic spectrum characteristics of the seismic reservoir are summarized in combination with spectrum analysis; based on the frequency division effect, interpretation is carried out within the seismic dominant frequency band, which is more conducive to the identification of intra-platform shoal heterogeneous reservoirs.

[0108] Figure 5 FIG. 1 is a schematic diagram of a structure of a heterogeneous reservoir identification device based on seismic dominant frequency according to an embodiment of the present invention. Figure 5 As shown, the heterogeneous reservoir identification device based on seismic dominant frequency provided by the embodiment of the present invention includes:

[0109] Spectrum analysis module 1 performs spectrum analysis on the original seismic pure wave data to obtain spectrum characteristic data of the seismic reservoir segment;

[0110] A dominant frequency band identification module 2 is configured to identify a dominant frequency band in the seismic reservoir segment according to the frequency spectrum characteristic data;

[0111] A filtering module 3 performs filtering processing on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band;

[0112] The heterogeneous reservoir identification module 4 performs seismic interpretation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir.

[0113] The heterogeneous reservoir identification device based on seismic dominant frequency provided in an embodiment of the present invention is mainly aimed at carbonate heterogeneous reservoirs. Based on the understanding of the seismic response characteristics of the seismic reservoir, the seismic spectrum characteristics of the seismic reservoir are summarized in combination with spectrum analysis; based on the frequency division effect, interpretation is carried out within the seismic dominant frequency band, which is more conducive to the identification of intra-platform shoal heterogeneous reservoirs.

[0114] Based on the same inventive concept, in a preferred embodiment, the spectrum analysis module includes:

[0115] A characteristic analysis unit, which performs reservoir seismic response characteristic analysis on the original seismic pure wave data in combination with reservoir calibration to obtain reservoir seismic response data;

[0116] The spectrum analysis unit performs spectrum analysis on the reservoir seismic response data to obtain spectrum characteristic data of the seismic reservoir segment.

[0117] Based on the same inventive concept, in a preferred embodiment, the original seismic pure wave data is post-stack seismic data.

[0118] Based on the same inventive concept, in a preferred embodiment, the dominant frequency band identification module includes:

[0119] A single-frequency data volume generating unit is configured to obtain a seismic single-frequency data volume using a frequency dividing device according to the frequency spectrum characteristic data;

[0120] The dominant frequency band acquisition unit performs tuned frequency analysis on the seismic single-frequency data volume in combination with reservoir calibration to obtain the dominant frequency band of the reservoir.

[0121] Based on the same inventive concept, in a preferred embodiment, the filtering process includes: bandpass filtering process, and the filtering module specifically performs bandpass filtering process on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band.

[0122] Based on the same inventive concept, in a preferred embodiment, the filtering module specifically includes:

[0123] A setting unit, configured to set a filtering frequency band corresponding to the dominant frequency band;

[0124] a processing unit, performing bandpass filtering on the original seismic pure wave data using the filter frequency band corresponding to the dominant frequency band;

[0125] The comparison unit compares the original seismic pure wave data and its corresponding frequency spectrum characteristic data with the seismic pure wave data after bandpass filtering and its corresponding frequency spectrum characteristic data to obtain the seismic pure wave data corresponding to the dominant frequency band.

[0126] Based on the same inventive concept, in a preferred embodiment, the heterogeneous reservoir identification module includes:

[0127] The lithologic data generation unit establishes lithologic data volume labels, conducts seismic intelligent interpretation and reservoir simulation within the dominant seismic frequency band, and obtains lithologic data corresponding to heterogeneous reservoirs.

[0128] The lithologic data identification unit identifies the heterogeneous reservoir according to the lithologic data corresponding to the heterogeneous reservoir.

[0129] Based on the same inventive concept, in a preferred embodiment, the heterogeneous reservoir identification module includes:

[0130] The porosity data generation unit establishes porosity data volume labels, conducts seismic intelligent interpretation and reservoir simulation within the seismic dominant frequency band, and obtains porosity data corresponding to heterogeneous reservoirs;

[0131] The porosity data identification unit identifies the heterogeneous reservoir according to the porosity data corresponding to the heterogeneous reservoir.

[0132] Based on the same inventive concept, in a preferred embodiment, the heterogeneous reservoir identification module includes:

[0133] The permeability data generation unit establishes permeability data volume labels, conducts seismic intelligent interpretation and reservoir simulation within the seismic dominant frequency band, and obtains permeability data corresponding to heterogeneous reservoirs;

[0134] The permeability data identification unit identifies the heterogeneous reservoir according to the permeability data corresponding to the heterogeneous reservoir.

[0135] The embodiments of the apparatus provided in the embodiments of the present invention can be specifically used to execute the processing flow of the above-mentioned method embodiments. Its functions are not described in detail here, and reference can be made to the detailed description of the above-mentioned method embodiments.

[0136] Figure 6 FIG. 1 is a schematic diagram of the physical structure of an electronic device provided in the twelfth embodiment of the present invention. Figure 6As shown, the electronic device may include: a processor 1201, a communications interface 1202, a memory 1203, and a communications bus 1204, wherein the processor 1201, the communications interface 1202, and the memory 1203 communicate with each other via the communications bus 1204. The processor 1201 may call logic instructions in the memory 1203 to execute the following method: performing spectral analysis on raw seismic pure wave data to obtain spectral characteristic data of a seismic reservoir segment; identifying a dominant frequency band in the seismic reservoir segment based on the spectral characteristic data; filtering the raw seismic pure wave data based on the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band; and performing seismic interpretation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir.

[0137] In addition, the logic instructions in the above-mentioned memory 1203 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0138] This embodiment discloses a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided by the above-mentioned method embodiments, for example, including: performing spectral analysis on original seismic pure wave data to obtain spectral characteristic data of the seismic reservoir segment; identifying a dominant frequency band in the seismic reservoir segment based on the spectral characteristic data; filtering the original seismic pure wave data based on the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band; performing seismic interpretation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir.

[0139] This embodiment provides a computer-readable storage medium, which stores a computer program. The computer program enables the computer to execute the methods provided by the above-mentioned method embodiments, for example, including: performing spectral analysis on original seismic pure wave data to obtain spectral characteristic data of the seismic reservoir segment; identifying a dominant frequency band in the seismic reservoir segment based on the spectral characteristic data; filtering the original seismic pure wave data based on the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band; performing seismic interpretation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir.

[0140] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0141] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0142] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0143] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0144] Throughout this specification, reference to terms such as "one embodiment," "a specific embodiment," "some embodiments," "for example," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0145] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for identifying heterogeneous reservoirs based on seismic dominant frequency, characterized in that: include: Perform spectrum analysis on the original seismic pure wave data to obtain the spectrum characteristic data of the seismic reservoir segment; identifying a dominant frequency band in the seismic reservoir segment according to the frequency spectrum characteristic data; Performing filtering processing on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band; Performing seismic interpretation and reservoir simulation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir; Performing seismic interpretation and reservoir simulation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir includes: By establishing lithologic data volume labels, we conduct seismic intelligent interpretation and reservoir simulation within the dominant seismic frequency band to obtain lithologic data corresponding to heterogeneous reservoirs. Identify heterogeneous reservoirs based on their corresponding lithologic data; Alternatively, by establishing porosity data volume labels, seismic intelligent interpretation and reservoir simulation can be performed within the dominant seismic frequency band to obtain porosity data corresponding to heterogeneous reservoirs. Identify heterogeneous reservoirs based on their corresponding porosity data; Alternatively, by establishing permeability data volume labels, intelligent seismic interpretation and reservoir simulation can be performed within the dominant seismic frequency band to obtain permeability data corresponding to heterogeneous reservoirs. Identify heterogeneous reservoirs based on their corresponding permeability data.

2. The method for identifying heterogeneous reservoirs according to claim 1, characterized in that: The spectrum analysis of the original seismic pure wave data to obtain the spectrum characteristic data of the seismic reservoir segment includes: Performing reservoir seismic response characteristic analysis on the original seismic pure wave data in combination with reservoir calibration to obtain reservoir seismic response data; Spectral analysis of reservoir seismic response data is performed to obtain spectral characteristic data of the seismic reservoir segment.

3. The method for identifying heterogeneous reservoirs according to claim 1, characterized in that: The original seismic pure wave data is post-stack seismic data.

4. The method for identifying heterogeneous reservoirs according to claim 1, characterized in that: The identifying a dominant frequency band in the seismic reservoir segment according to the frequency spectrum characteristic data includes: According to the frequency spectrum characteristic data, a seismic single-frequency data volume is obtained by using a frequency division method; The seismic single-frequency data volume is subjected to tuned frequency analysis in combination with reservoir calibration to obtain a dominant frequency band of the reservoir.

5. The method for identifying heterogeneous reservoirs according to claim 1, characterized in that: The filtering process includes: band-pass filtering process, wherein the filtering process includes filtering the original seismic pure wave data according to the dominant frequency band, including: The original seismic pure wave data is subjected to bandpass filtering according to the dominant frequency band to obtain the seismic pure wave data corresponding to the dominant frequency band.

6. The method for identifying heterogeneous reservoirs according to claim 5, characterized in that: The bandpass filtering process is performed on the original seismic pure wave data according to the dominant frequency band to obtain the seismic pure wave data corresponding to the dominant frequency band, including: Setting the filtering frequency band corresponding to the dominant frequency band; Performing bandpass filtering on the original seismic pure wave data using the filter frequency band corresponding to the dominant frequency band; The original seismic pure wave data and its corresponding frequency spectrum characteristic data are compared with the seismic pure wave data after bandpass filtering and its corresponding frequency spectrum characteristic data to obtain the seismic pure wave data corresponding to the dominant frequency band.

7. A device for identifying heterogeneous reservoirs based on seismic dominant frequency, characterized in that: include: The spectrum analysis module performs spectrum analysis on the original seismic pure wave data to obtain the spectrum characteristic data of the seismic reservoir segment; A dominant frequency band identification module, which identifies a dominant frequency band in the seismic reservoir segment according to the frequency spectrum characteristic data; a filtering module, performing filtering processing on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band; A heterogeneous reservoir identification module performs seismic interpretation on the seismic pure wave data corresponding to the dominant frequency band to identify the heterogeneous reservoir; The heterogeneous reservoir identification module includes: The lithologic data generation unit establishes lithologic data volume labels, conducts seismic intelligent interpretation and reservoir simulation within the dominant seismic frequency band, and obtains lithologic data corresponding to heterogeneous reservoirs. A lithologic data identification unit, which identifies a heterogeneous reservoir according to lithologic data corresponding to the heterogeneous reservoir; Alternatively, the porosity data generation unit establishes porosity data volume labels, performs seismic intelligent interpretation and reservoir simulation within the seismic dominant frequency band, and obtains porosity data corresponding to the heterogeneous reservoir; a porosity data identification unit, for identifying a heterogeneous reservoir according to porosity data corresponding to the heterogeneous reservoir; Alternatively, the permeability data generation unit establishes permeability data volume labels, performs seismic intelligent interpretation and reservoir simulation within the seismic dominant frequency band, and obtains permeability data corresponding to the heterogeneous reservoir; The permeability data identification unit identifies the heterogeneous reservoir according to the permeability data corresponding to the heterogeneous reservoir.

8. The heterogeneous reservoir identification device according to claim 7, characterized in that: The spectrum analysis module includes: A characteristic analysis unit, which performs reservoir seismic response characteristic analysis on the original seismic pure wave data in combination with reservoir calibration to obtain reservoir seismic response data; The spectrum analysis unit performs spectrum analysis on the reservoir seismic response data to obtain spectrum characteristic data of the seismic reservoir segment.

9. The heterogeneous reservoir identification device according to claim 7, characterized in that: The original seismic pure wave data is post-stack seismic data.

10. The heterogeneous reservoir identification device according to claim 7, characterized in that: The dominant frequency band identification module includes: A single-frequency data volume generating unit is configured to obtain a seismic single-frequency data volume using a frequency dividing device according to the frequency spectrum characteristic data; The dominant frequency band acquisition unit performs tuned frequency analysis on the seismic single-frequency data volume in combination with reservoir calibration to obtain the dominant frequency band of the reservoir.

11. The heterogeneous reservoir identification device according to claim 7, characterized in that: The filtering process includes: band-pass filtering process, wherein the filtering module performs band-pass filtering process on the original seismic pure wave data according to the dominant frequency band to obtain seismic pure wave data corresponding to the dominant frequency band.

12. The heterogeneous reservoir identification device according to claim 11, characterized in that: The filtering module specifically includes: A setting unit, configured to set a filtering frequency band corresponding to the dominant frequency band; a processing unit, performing bandpass filtering on the original seismic pure wave data using the filter frequency band corresponding to the dominant frequency band; The comparison unit compares the original seismic pure wave data and its corresponding frequency spectrum characteristic data with the seismic pure wave data after bandpass filtering and its corresponding frequency spectrum characteristic data to obtain the seismic pure wave data corresponding to the dominant frequency band.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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