Method and device for identifying volcanic channels of volcanic rocks

Abstract

The invention belongs to the field of oil and gas geophysics, and particularly discloses a volcanic rock volcanic channel identification method and device, and the method comprises the steps: obtaining a texture feature attribute and a tensor attribute based on a volcanic rock original time domain seismic data body; and fusing the texture feature attribute and the tensor attribute, and depicting the volcanic channel development position of the volcanic rock. According to the volcanic rock volcanic channel identification method, texture feature value attributes and tensor attributes are fused, the volcanic channel development position under the volcanic mechanism background can be completely described, and finally a complete and effective technical method and process are provided for volcanic rock volcanic channel phase identification.

Description

Technical Field

[0001] The invention belongs to the field of oil and gas geophysics, and in particular relates to a method and device for identifying volcanic channels in volcanic rocks. Background Art

[0002] Volcanic rock oil and gas reservoirs are one of the important areas of oil and gas exploration. Industrial oil and gas flows and large-scale reserves have been obtained from volcanic rocks in 40 basins in 13 countries around the world. High-yield oil and gas reservoirs have also been found in volcanic rocks in many basins in China. For example, a major breakthrough was made in volcanic rocks in the Songliao Basin this year. Volcanic rock reservoirs are controlled by many factors such as the distribution of volcanic bodies and the lithology and lithofacies of volcanic rocks. Accurate identification and characterization are particularly critical. Volcanic channel phases often show low-continuous weak-amplitude seismic reflection characteristics. The usual method is to characterize the boundaries and distribution range of volcanic channels based on variance attributes. Considering that the seismic data in the target area are affected by the strong amplitude of the overlying volcanic overflow phase, the seismic data quality is general and the accuracy of traditional variance bodies is not high, which brings certain difficulties to the fine identification of the boundaries of volcanic channels.

[0003] The existing volcanic reservoir identification and characterization methods are mainly aimed at acidic volcanic rocks with obvious paleo-uplift structures, which can be directly identified with the help of seismic attributes such as dip, azimuth and waveform classification. Compared with acidic volcanic rocks, intermediate-basic volcanic rocks have the characteristics of low magma viscosity, multiple eruption periods, and rapid vertical phase change. They are mostly produced in thin (inter) layers in drilling, and the rock mass is mostly low-lying volcanic rock uplifts. The center of the volcanic structure is not obvious, so it is often difficult to directly identify intermediate-basic volcanic structures. In addition, most of the oil and gas basins in China are currently in the mid-exploration stage, and the exploration direction is gradually transitioning to the fine exploration stage. The existing volcanic reservoir characterization methods can no longer meet the current fine exploration needs. The research results of the Songliao Basin show that the physical properties and oil and gas content of acidic volcanic reservoirs are controlled by volcanic lithofacies, while the relationship between intermediate-basic volcanic reservoir formation and lithofacies is not clear, which restricts the volcanic exploration process in this area.

[0004] Based on this technical background, the present invention studies a method and device for identifying volcanic rock volcanic channels. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a method and device for identifying volcanic channels in volcanic rocks. The method integrates texture eigenvalue attributes with tensor attributes, which can fully characterize the development position of volcanic channels under the background of volcanic structure, and finally provides a complete and effective technical method and process for the identification of volcanic channel phases in volcanic rocks.

[0006] In order to achieve the above object, a first aspect of the present invention provides a method for identifying a volcanic channel in a volcanic rock, comprising:

[0007] The texture feature attributes and tensor attributes are obtained based on the original time-domain seismic data volume of volcanic rocks;

[0008] The texture feature attributes are integrated with the tensor attributes to characterize the development location of the volcanic channel in the volcanic rock.

[0009] A second aspect of the present invention provides a volcanic rock volcanic channel identification device, comprising:

[0010] An attribute generation module is used to obtain texture feature attributes and tensor attributes based on the original time-domain seismic data volume of volcanic rocks;

[0011] The fusion characterization module is used to fuse the texture feature attributes with the tensor attributes to characterize the development position of the volcanic channel of the volcanic rock.

[0012] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0013] A memory storing executable instructions;

[0014] A processor, wherein the processor runs the executable instructions in the memory to implement the method for identifying a volcanic channel in a volcanic rock according to the first aspect.

[0015] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for identifying a volcanic channel in a volcanic rock as described in the first aspect.

[0016] The beneficial effects of the present invention include:

[0017] (1) The method for identifying volcanic channels in volcanic rocks provided by the present invention integrates texture eigenvalue attributes with tensor attributes, which can fully characterize the development location of volcanic channels under the background of volcanic structure, and finally provides a complete and effective technical method and process for the identification of volcanic channel phases in volcanic rocks.

[0018] (2) In the volcanic channel identification method of volcanic rocks provided by the present invention, the texture feature values ​​are mainly arranged and combined in terms of frequency, amplitude, and continuity. Combined with the seismic response characteristics of the volcanic rock envelope or the seismic response characteristics of the volcanic channel phase, the outline of the chaotic reflection volcanic body can be accurately depicted.

[0019] (3) The volcanic channel identification method of volcanic rocks provided by the present invention integrates the texture feature attributes with the tensor attributes, combines the gradient attributes of the original time domain seismic data volume, and the continuity or mutation of the horizontal and vertical distribution of the seismic strata, and can reflect a clearer target boundary.

[0020] (4) The volcanic channel identification method of volcanic rocks provided by the present invention calculates coherence attributes based on the original time-domain seismic data volume, and obtains texture feature attributes through coherence attribute calculation. Then, the original time-domain seismic data volume and the texture feature attributes are compared and fused, which can accurately reflect the envelope characteristics and channel characteristics of the volcanic rocks.

[0021] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings.

[0023] Figure 1 This is a flow chart of the volcanic channel identification method for volcanic rocks proposed by the present invention.

[0024] Figure 2 This is a rendering of texture feature attributes extracted by the volcanic rock volcanic channel identification method in Example 1 of the present invention.

[0025] Figure 3 This is a tensor attribute rendering of the volcanic channel identification method of volcanic rocks in Example 1 of the present invention. DETAILED DESCRIPTION

[0026] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0027] The present invention proposes a method for identifying volcanic rock volcanic channels, such as Figure 1 As shown, including:

[0028] The texture feature attributes and tensor attributes are obtained based on the original time-domain seismic data volume of volcanic rocks;

[0029] The texture feature attributes are integrated with the tensor attributes to characterize the location of volcanic channel development in volcanic rocks.

[0030] The method of the present invention integrates texture eigenvalue attributes with tensor attributes, which can fully characterize the development location of volcanic channels in the context of volcanic structures, and ultimately provides a complete and effective technical method and process for the identification of volcanic channel phases of volcanic rocks.

[0031] According to the present invention, texture feature attributes and tensor attributes are obtained based on the original time domain seismic data volume of volcanic rocks, including:

[0032] Coherent attributes are calculated based on the original time-domain seismic data volume;

[0033] Calculating texture feature attributes based on coherent attributes;

[0034] The original time-domain seismic data volume is compared and fused with the texture feature attributes to obtain the response feature type;

[0035] Computes a tensor attribute based on the response feature type.

[0036] According to the present invention, the coherent attributes calculated based on the original time domain seismic data volume include:

[0037] The volcanic rock time domain seismic data volume is filtered and the coherence value is calculated in turn to obtain the coherence attribute; the texture feature attributes calculated based on the coherence attribute include:

[0038] The texture feature value is calculated based on the coherent attribute to obtain the texture feature attribute.

[0039] The texture feature values ​​in the present invention mainly arrange and combine frequency, amplitude, and continuity, and can accurately depict the outline of a chaotic reflecting volcano body by combining the seismic response characteristics of the volcanic rock envelope or the seismic response characteristics of the volcanic channel phase.

[0040] In the present invention, coherence attributes are calculated based on the original time-domain seismic data volume, and texture feature attributes are calculated through coherence attributes. Then, the original time-domain seismic data volume and the texture feature attributes are compared and fused, which can accurately reflect the envelope characteristics and channel characteristics of volcanic rocks.

[0041] Preferably, the texture feature value includes at least one of frequency, amplitude and continuity.

[0042] Preferably, the response feature types include volcanic rock envelope seismic response features and volcanic channel phase seismic response features.

[0043] According to the present invention, calculating the tensor attribute based on the response feature type further includes:

[0044] Based on tensor attributes, high-frequency cluttered strong reflections are determined to distinguish volcanic channels from surrounding anomalies.

[0045] According to the present invention, the texture feature attributes are integrated with the tensor attributes to describe the location of the volcanic channel development in volcanic rocks, including:

[0046] The texture feature attributes are fused with the tensor attributes, combined with the gradient attributes of the original time-domain seismic data volume and the continuity or mutation of the horizontal and vertical distribution of the seismic strata, to characterize the development location of volcanic channels in the flood area.

[0047] In the present invention, the texture feature attributes are fused with the tensor attributes, combined with the gradient attributes of the original time-domain seismic data volume, and the continuity or mutation of the horizontal and vertical distribution of the seismic strata, which can reflect a clearer target boundary.

[0048] The present invention will be described in more detail below by way of examples.

[0049] The embodiment of the present invention takes the Chaganhua Huoshiling in Songliao Basin as the research object. The Chaganhua Huoshiling Group is composed of multiple volcanic structures. From the distribution characteristics of the volcanic structures, it has the characteristics of a central eruption. With the crater as the center, multiple volcanic structures are distributed in overlapping pieces to form a composite volcanic structure group. The volcanic rock body has a fast lateral change in stratum thickness, and the reservoir is extremely heterogeneous. The volcanic rock phase is mainly composed of the eruption phase and the overflow phase. The volcanic sedimentary phase and the normal sedimentary phase are developed in the low part of the structure. The internal structure of the volcano is complex, and the volcanic seismic response is little different from the surrounding area.

[0050] Embodiment 1:

[0051] This embodiment takes the data of Yaoyingtai area of ​​Chagan Huahuoshiling as an example, and carries out the work of depicting the development location of volcanic rock volcanic channels based on the volcanic rock volcanic channel identification method.

[0052] The volcanic channel identification method based on volcanic rocks in this embodiment specifically includes the following steps: Figure 1 For the Yaoyingtai area, the original body is processed, filtered, and coherent. On this basis, the texture features in different directions are calculated, and then the texture feature value attributes are compared and fused with the original seismic profile. It can be seen that the seismic texture attribute has significantly improved the recognition effect of the volcanic rock body with chaotic reflection. The seismic texture attribute can be used to depict the outline of the chaotic reflection volcanic body. Then, the gradient attribute is used, such as Figure 2 As shown, the continuity or mutation of the horizontal and vertical distribution of seismic strata is comprehensively applied to calculate attributes to reflect clearer target boundaries, such as the flood area reflecting the development location of volcanic channels.

[0053] Embodiment 2:

[0054] This embodiment provides a method for identifying a volcanic channel in a volcanic rock. Figure 1 As shown, including:

[0055] The texture feature attributes and tensor attributes are obtained based on the original time-domain seismic data volume of volcanic rocks;

[0056] The texture feature attributes are integrated with the tensor attributes to characterize the location of volcanic channel development in volcanic rocks;

[0057] The texture feature attributes and tensor attributes obtained based on the original time domain seismic data volume of volcanic rocks include:

[0058] Coherent attributes are calculated based on the original time-domain seismic data volume;

[0059] Calculating texture feature attributes based on coherent attributes;

[0060] The original time-domain seismic data volume is compared and fused with the texture feature attributes to obtain the response feature type;

[0061] Calculate tensor attributes based on the response feature type;

[0062] The coherent attributes calculated based on the original time domain seismic data volume include:

[0063] The volcanic rock time domain seismic data volume is filtered and the coherence value is calculated in turn to obtain the coherence attribute; the texture feature attributes calculated based on the coherence attribute include:

[0064] Calculating texture feature values ​​based on coherent attributes to obtain texture feature attributes;

[0065] The texture feature value includes at least one of frequency, amplitude, and continuity;

[0066] The response characteristics types include the seismic response characteristics of the volcanic rock envelope and the seismic response characteristics of the volcanic channel phase;

[0067] The tensor attributes calculated based on the response feature type also include:

[0068] Based on tensor attributes, high-frequency cluttered strong reflections are determined to distinguish volcanic channels from surrounding anomalies;

[0069] The texture feature attributes are integrated with the tensor attributes to describe the location of the volcanic channel development in volcanic rocks, including:

[0070] The texture feature attributes are fused with the tensor attributes, combined with the gradient attributes of the original time-domain seismic data volume and the continuity or mutation of the horizontal and vertical distribution of the seismic strata, to characterize the development location of volcanic channels in the flood area.

[0071] Embodiment three:

[0072] This embodiment provides a volcanic rock volcanic channel identification device, such as Figure 1 As shown, including:

[0073] An attribute generation module is used to obtain texture feature attributes and tensor attributes based on the original time-domain seismic data volume of volcanic rocks;

[0074] The fusion characterization module is used to fuse texture feature attributes with tensor attributes to characterize the location of volcanic channel development in volcanic rocks;

[0075] The texture feature attributes and tensor attributes obtained based on the original time domain seismic data volume of volcanic rocks include:

[0076] Coherent attributes are calculated based on the original time-domain seismic data volume;

[0077] Calculating texture feature attributes based on coherent attributes;

[0078] The original time-domain seismic data volume is compared and fused with the texture feature attributes to obtain the response feature type;

[0079] Calculate tensor attributes based on the response feature type;

[0080] The coherent attributes calculated based on the original time domain seismic data volume include:

[0081] The volcanic rock time domain seismic data volume is filtered and the coherence value is calculated in turn to obtain the coherence attribute; the texture feature attributes calculated based on the coherence attribute include:

[0082] Calculating texture feature values ​​based on coherent attributes to obtain texture feature attributes;

[0083] The texture feature value includes at least one of frequency, amplitude, and continuity;

[0084] The response characteristics types include the seismic response characteristics of the volcanic rock envelope and the seismic response characteristics of the volcanic channel phase;

[0085] The tensor attributes calculated based on the response feature type also include:

[0086] Based on tensor attributes, high-frequency cluttered strong reflections are determined to distinguish volcanic channels from surrounding anomalies;

[0087] The texture feature attributes are integrated with the tensor attributes to describe the location of the volcanic channel development in volcanic rocks, including:

[0088] The texture feature attributes are fused with the tensor attributes, combined with the gradient attributes of the original time-domain seismic data volume and the continuity or mutation of the horizontal and vertical distribution of the seismic strata, to characterize the development location of volcanic channels in the flood area.

[0089] Embodiment 4:

[0090] An embodiment of the present invention provides an electronic device including a memory and a processor.

[0091] A memory storing executable instructions;

[0092] The processor runs the executable instructions in the memory to implement the volcanic channel identification method of volcanic rocks.

[0093] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0094] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0095] Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present invention.

[0096] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0097] Embodiment five:

[0098] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a method for identifying a volcanic rock volcanic channel is implemented.

[0099] The computer-readable storage medium according to the embodiment of the present invention stores non-transitory computer-readable instructions, and when the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of the embodiments of the present invention are executed.

[0100] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0101] The volcanic channel identification method of volcanic rocks provided by the embodiment of the present invention integrates texture eigenvalue attributes with tensor attributes, which can fully characterize the development position of volcanic channels under the background of volcanic structure, and finally provide a complete and effective technical method and process for the identification of volcanic channel phases of volcanic rocks.

[0102] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for identifying volcanic channels in volcanic rocks, characterized in that: include: The texture feature attributes and tensor attributes are obtained based on the original time-domain seismic data volume of volcanic rocks; The texture feature attributes are integrated with the tensor attributes to characterize the development location of the volcanic channel in the volcanic rock.

2. The prediction method according to claim 1, characterized in that: The texture feature attributes and tensor attributes obtained based on the original time domain seismic data volume of volcanic rock include: Coherent attributes are calculated based on the original time-domain seismic data volume; Calculating texture feature attributes based on the coherent attributes; Comparing and fusing the original time-domain seismic data volume with the texture feature attributes to obtain a response feature type; A tensor attribute is calculated based on the response feature type.

3. The prediction method according to claim 1, characterized in that: The coherent attributes calculated based on the original time domain seismic data volume include: The volcanic rock time domain seismic data volume is filtered in sequence and the coherence value is calculated to obtain the coherence attribute; the texture feature attributes calculated based on the coherence attribute include: The texture feature value is calculated based on the coherent attribute to obtain the texture feature attribute.

4. The prediction method according to claim 3, characterized in that: The texture feature value includes at least one of frequency, amplitude, and continuity.

5. The prediction method according to claim 4, characterized in that: The response feature types include volcanic rock envelope seismic response features and volcanic channel phase seismic response features.

6. The prediction method according to claim 1, characterized in that: The tensor attributes calculated based on the response feature type also include: Based on the tensor attributes, high-frequency cluttered strong reflections are determined to distinguish the volcanic channel from surrounding anomalies.

7. The prediction method according to claim 1, characterized in that: The texture feature attributes are integrated with the tensor attributes to describe the location of the volcanic channel development in volcanic rocks, including: The texture feature attributes are fused with the tensor attributes, combined with the gradient attributes of the original time-domain seismic data volume, and the continuity or mutation of the horizontal and vertical distribution of the seismic strata, to characterize the development location of the volcanic channel in the flood area.

8. A volcanic rock volcanic channel identification device, characterized in that: include: An attribute generation module is used to obtain texture feature attributes and tensor attributes based on the original time-domain seismic data volume of volcanic rocks; The fusion characterization module is used to fuse the texture feature attributes with the tensor attributes to characterize the development position of the volcanic channel of the volcanic rock.

9. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the volcanic rock volcanic channel identification method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the volcanic rock volcanic channel identification method according to any one of claims 1 to 7 is implemented.

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