A carbonate rock bead-shaped reflection position identification method and computer equipment

Abstract

This invention relates to the technical field of seismic data interpretation, and discloses a method and computer equipment for identifying the locations of beaded reflections in carbonate rocks. The identification method includes: S1, obtaining a two-dimensional seismic migration profile; S2, extracting typical beaded reflections, determining their dimensions, statistically analyzing their structural morphology, and constructing adaptive hit-and-miss structural element pairs; S3, using a hit-and-miss transformation to identify locations that match the adaptive hit-and-miss structural element pairs. This invention's identification method extracts multiple typical beaded reflections, constructs adaptive hit-and-miss structural element pairs, and only identifies locations that match these pairs. Based on a hit-and-miss transformation algorithm, this algorithm has low hardware requirements, high computational efficiency, and high accuracy.

Description

Technical Field

[0001] This invention relates to the technical field of seismic data interpretation, and in particular to a method and computer equipment for identifying the location of beaded reflections in carbonate rocks. Background Technology

[0002] The Tarim Oilfield is a fracture-vuggy oil and gas reservoir in the northern Tarim Basin, a large Ordovician carbonate reservoir buried at a depth greater than 5300m, and an ultra-deep, complex reservoir. The reservoir space mainly consists of pores, cavities, and fractures, and their development is primarily influenced by the degree of dissolution fractures and cavities, i.e., the degree of later tectonic and karst alteration. This type of reservoir exhibits extremely strong heterogeneity both vertically and horizontally, with the most typical reflection characteristic in seismic data being beaded reflections. However, current identification of beaded reflections mainly relies on manual identification and deep learning-based target detection algorithms. Manual identification is currently the primary method, relying mainly on extracting attribute data time slices or layer slices vertically, and on visual identification on seismic migration profiles or referring to seismic inversion results horizontally. This method is influenced by the experience of interpreters and is relatively inefficient. Deep learning-based target detection algorithms, on the other hand, have strict requirements for label creation, the accuracy of the detection results is greatly affected by the label data, and they also have high hardware requirements. Summary of the Invention

[0003] To address the technical problems of low computational efficiency in manual identification and high hardware requirements in deep learning detection algorithms, this invention provides a method and computer device for identifying the location of beaded reflections in carbonate rocks. Based on the hit-and-miss transformation algorithm, it extracts typical beaded reflections and uses adaptive structuring element pairs to identify only the locations that match the adaptive structuring element pairs. This algorithm has low hardware requirements and high computational efficiency.

[0004] The objective of this invention is to provide a method for identifying the location of beaded reflections in carbonate rocks, comprising:

[0005] S1. Obtain a two-dimensional seismic migration profile;

[0006] S2. Extract typical beaded reflections, determine the size, statistically analyze the structural morphology of the beaded reflections, and construct adaptive hit-miss-hit structural element pairs.

[0007] S3. Use the hit-and-miss transformation to identify the positions of the adaptive hit-and-miss structure element pairs.

[0008] According to a preferred embodiment of the present invention, in step S2, the adaptive hit-miss structure element pair is constructed based on the relative amplitude percentage of the central extreme point of the structure element pair.

[0009] According to a preferred embodiment of the present invention, in step S2, the method for constructing the adaptive hit / miss pair of structural elements includes: assuming there are n target data p(x,y) in the two-dimensional data, defining the maximum value of each target data as the center of the structural element, determining the size of the structural element based on this center, calculating the percentage of the amplitude value of non-center points relative to the center point, defining the hit structural element as the minimum percentage of the amplitude value of the n target data, and defining the miss structural element as the maximum percentage of the amplitude value of the n target data; the selection of the adaptive hit / miss pair of structural elements is as follows:

[0010]

[0011] in, To adaptively hit the structuring element, For adaptive missing structural elements; f(i,j) is the seismic migration profile amplitude value; i is the seismic migration profile trace number, j is the seismic migration profile time;

[0012] min(p n (x, y) / p n max The minimum percentage of amplitude values ​​for n target data; max(p n (x, y) / p n max p represents the maximum percentage of amplitude values ​​among n target data points. n (x, y) represents the nth target data p(x, y); x is the dimension in the channel direction, and y is the dimension in the time direction; p n max This represents the maximum value of the nth target data.

[0013] According to a preferred embodiment of the present invention, in step S3, the formula for converting between hit and miss is as follows:

[0014]

[0015] Where f is the input seismic migration profile, For adaptive structural element pairs; i is the seismic migration trace number, j is the seismic migration time; p n (x, y) represents the nth target data p(x, y); x is the dimension in the channel direction, and y is the dimension in the time direction; p n max The maximum value of the nth target data; the meanings of the other symbols are as shown in equation (5).

[0016] The recognition result is shown in the following formula:

[0017]

[0018] in, For the recognition results, where For adaptive structuring element pairs; the result of hit-or-miss transformation. A value of 0 indicates that the hit-miss transformation is met; a value other than 0 indicates that the hit-miss transformation is not met.

[0019] According to a preferred embodiment of the present invention, in step S1, the two-dimensional seismic migration profile is a grayscale image. The two-dimensional seismic migration profile is a typical beaded reflection development seismic profile of this work area.

[0020] According to a preferred embodiment of the present invention, in step S2, the selection method of the typical beaded reflection is to manually select 10 to 20 clearly imaged beaded reflections within the seismic profile of the typical beaded reflection development in the work area.

[0021] The second objective of this invention is to provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described.

[0022] The third objective of this invention is to provide a computer storage medium storing a computer program thereon, characterized in that the computer program, when executed by a processor, implements the steps of the method described.

[0023] The fourth objective of this invention is to provide a computer program, characterized in that, when the computer program is executed by a processor, it implements the steps of the method described.

[0024] The beneficial effects of the present invention are: (1) The present invention extracts multiple typical beaded reflections and uses adaptive structural element pairs to identify only the positions that conform to the adaptive structural element pairs.

[0025] (2) A mathematical morphology-based adaptive hit-and-miss transformation algorithm is proposed. This algorithm has low hardware requirements, high computational efficiency, and high accuracy. Attached Figure Description

[0026] Appendix Figure 1 For adaptive structuring element pairs; (a) adaptive hit structuring element; (b) adaptive miss structuring element;

[0027] Appendix Figure 2 An adaptive structural element pair recognition diagram for any beaded position of a cross section in a certain work area of ​​the Tahe Oilfield; (a) Any cross section in a certain work area of ​​the Tahe Oilfield; (b) Adaptive hit / miss result;

[0028] Appendix Figure 3 For the appendix Figure 2 A partial view. Detailed Implementation

[0029] The present invention will be further described below with reference to specific embodiments, but this does not constitute any limitation on the present invention.

[0030] The hit-or-miss transformation result of 2D grayscale is a distance measure of the degree of correspondence between the spatial form of 2D data and the structure element pair. The higher the degree of correspondence between the spatial form of 2D data and the structure element pair, the smaller the relative movement distance between the structure element pairs, and the smaller the value of the hit-or-miss transformation result. When the spatial form of the target data in the 2D signal is uniquely determined, its corresponding position can be detected in the 2D signal by constructing a pair of structure elements with the same form as the target data as the structure element pair of the 2D grayscale hit-or-miss transformation. In actual 2D data recognition, the focus is on a class of target data with similar forms, where there are differences in the amplitude of the target data. Therefore, the structure element pair needs to be similar in form to the target data. Assuming there are n target data p(x,y) in the 2D signal to be analyzed, the hit structure element can be defined as the minimum value of the n target data, and the miss structure element can be defined as the maximum value of the n target data.

[0031]

[0032] Let the two-dimensional signal be f = f(x,y), and the structuring element be g = g(i,j). The two-dimensional grayscale hit-or-miss transform is defined as follows:

[0033] f! g=min{f(x+i,y+j)-g(i,j)} (2)

[0034]

[0035] The amplitude values ​​of beaded reflections vary greatly due to differences in depth, infill material properties, and surrounding rock velocity. Therefore, the distance (amplitude difference) between structural element pairs constructed by conventionally selecting target data and calculating maximum and minimum values ​​is already large, reaching 3000-8000. Meanwhile, the absolute amplitude values ​​of processed seismic data are generally within the range of 0-5000. Thus, the hit-and-miss transformation results of structural element pairs constructed using conventional methods cannot intuitively indicate whether beaded reflections have been identified.

[0036] Based on the specific "conical" shape of beaded reflections in three-dimensional space, this invention proposes an adaptive method for hitting and missing structural elements. Assuming there are n target data points p(x,y) in the two-dimensional data, the maximum value of each target data point is defined as the center of the structural element. The size of the structural element is determined using this center. For non-center points, the percentage of the amplitude value relative to the center point is calculated. Hitting the structural element can be defined as the minimum percentage of the amplitude values ​​of the n target data points, and missing the structural element can be defined as the maximum percentage of the amplitude values ​​of the n target data points.

[0037]

[0038] in, To adaptively hit the structuring element, For adaptive missing structural elements; f(i,j) is the seismic migration profile amplitude value; i is the seismic migration profile trace number, j is the seismic migration profile time;

[0039] min(p n (x, y) / p n max The minimum percentage of amplitude values ​​for n target data; max(p n (x, y) / p n max p represents the maximum percentage of amplitude values ​​among n target data points. n (x, y) represents the nth target data p(x, y); x is the dimension in the channel direction, and y is the dimension in the time direction; p n max The maximum value of the nth target data. f is the input seismic migration profile. For adaptive structuring element pairs.

[0040] The distance (difference in amplitude at the center point) between adaptive hit / miss structural elements is 0. For target data that conforms to its structural form, the result of the adaptive hit / miss transformation is 0; a non-zero value indicates that the target does not conform to the hit / miss transformation structural form. Therefore, this paper defines an intuitive adaptive hit / miss transformation that includes only two states: 1 (completely hit) and 0 (not hit), as follows:

[0041]

[0042] in, For the recognition results, where For adaptive structuring elements; the result of hit-or-miss transformation. A value of 0 indicates that the hit-miss transformation is met; a value other than 0 indicates that the hit-miss transformation is not met.

[0043]

Example

[0044] The Tahe Oilfield is located in Luntai County and Kuqa County, Xinjiang Uygur Autonomous Region. Structurally, it lies in the southern part of the Luntai Fault Zone of the Shaya Uplift in the Tarim Basin. The reservoir type is marine carbonate rock, with the main oil-producing layers being the Ordovician Yingshan Formation and Yijianfang Formation. The Tahe Oilfield is a fracture-vuggy oil and gas reservoir in the northern Tarim Basin, a large Ordovician carbonate rock reservoir with an ultra-deep and complex oil and gas reservoir buried at a depth greater than 5300m. The reservoir space is mainly composed of pores, cavities, and fractures, and the degree of development is mainly affected by the development of dissolution fractures and cavities, i.e., the degree of later tectonic and karst alteration. This type of reservoir has extremely strong heterogeneity in both vertical and horizontal directions, and the most typical reflection feature in seismic data is beaded reflection.

[0045] A profile was selected from a work area in the Tarim Oilfield. Using clear imaging and beaded reflections, an adaptive hit / miss structure element pair with a size of 11*13 was constructed. Figure 1 As shown (Note: the structural elements at this point are only amplitude percentages; multiplying by the corresponding value during calculation yields the adaptive hit / miss structural elements for each point). Then, arbitrarily select a cross-section from this work area, and the algorithm identifies the results as follows... Figure 2 As shown, Figure 3 It magnifies local details and can basically identify the positions of strong beaded reflections in offset imaging (solid box), and can also basically identify the positions of weak beaded reflections (difficult to identify by the human eye) in offset imaging (dashed box).

[0046] The Tahe Oilfield in the Tarim Basin is an unconventional oil and gas field in marine carbonate rocks, with the reservoir type mainly being fractured-vuggy, exhibiting a "beaded" reflection characteristic on seismic time-migration profiles. Based on actual data from nearly 1000 wells in the Tahe Oilfield, the encounter rate with drilled reservoirs reaches 95%. Therefore, rapid identification of beaded reflections is beneficial for reservoir identification and guiding well location deployment.

[0047] It should be noted that the embodiments described above are only for explaining the present invention and do not constitute any limitation on the present invention. The present invention has been described with reference to typical embodiments, but it should be understood that the words used therein are descriptive and explanatory terms, not limiting terms. Modifications can be made to the present invention within the scope of the claims, and revisions can be made to the present invention without departing from the scope and spirit of the present invention. Although the present invention described herein relates to specific methods, materials, and embodiments, it does not mean that the present invention is limited to the specific examples disclosed herein; on the contrary, the present invention can be extended to all other methods and applications with the same function.

Claims

1. A method for identifying the location of beaded reflections in carbonate rocks, characterized in that, include: S1. Obtain a two-dimensional seismic migration profile; S2. Extract typical beaded reflections, determine the size, statistically analyze the structural morphology of the beaded reflections, and construct adaptive hit-miss-hit structural element pairs. S3. Use the hit-and-miss transformation to identify the positions of the adaptive hit-and-miss structure element pairs.

2. The method for identifying the location of beaded reflections in carbonate rocks according to claim 1, characterized in that, In step S2, the adaptive hit / miss structure element pair is constructed based on the relative amplitude percentage of the central extreme point of the structure element pair.

3. The method for identifying the location of beaded reflections in carbonate rocks according to claim 2, characterized in that, In step S2, the method for constructing the adaptive hit / miss pair of structural elements includes: assuming there are n target data p(x, y) in the two-dimensional data, defining the maximum value of each target data as the center of the structural element, determining the size of the structural element based on this center, calculating the percentage of the amplitude value of non-center points relative to the center point, defining the hit structural element as the minimum percentage of the amplitude value of the n target data, and defining the miss structural element as the maximum percentage of the amplitude value of the n target data; the selection of the adaptive hit / miss pair of structural elements is as follows: in, To adaptively hit the structuring element, For adaptive non-hitting structural elements; f(i,j) is the seismic migration profile amplitude value; i is the seismic migration profile trace number, j is the seismic migration profile time; min(p n (x, y) / p n max The minimum percentage of amplitude values ​​for n target data; max(p n (x, y) / p n max p represents the maximum percentage of amplitude values ​​among n target data points. n (x, y) represents the nth target data p(x, y); x is the dimension in the channel direction, and y is the dimension in the time direction; p n max This represents the maximum value of the nth target data.

4. The method for identifying the location of beaded reflections in carbonate rocks according to claim 3, characterized in that, In step S3, the formula for converting between hit and miss is as follows: Where f is the input seismic migration profile, For adaptive structural element pairs; i is the seismic migration profile trace number, j is the seismic migration profile time; P n (x, y) represents the nth target data p(x, y); x is the dimension in the channel direction, and y is the dimension in the time direction; P m max The maximum value of the nth target data; The recognition result is shown in the following formula: in, For the recognition results, where For adaptive structuring elements; the result of hit-or-miss transformation. A value of 0 indicates that the hit-miss transformation is met; a value other than 0 indicates that the hit-miss transformation is not met.

5. The method for identifying the location of beaded reflections in carbonate rocks according to any one of claims 1-4, characterized in that, In step S1, the two-dimensional seismic migration profile is a grayscale image.

6. The method for identifying the location of beaded reflections in carbonate rocks according to any one of claims 1-4, characterized in that, In step S2, the selection method for the typical beaded reflection is to manually select 10 to 20 clear beaded reflections within the seismic profile of typical beaded reflection development in this work area.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-6.

8. A computer storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.

9. A computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.

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