Method, device, electronic equipment and medium for automatic division of sedimentation cycles

Abstract

The present invention proposes a method, device, electronic device and medium for automatic division of sedimentary cycles. The method for automatic division of sedimentary cycles comprises: selecting a logging curve that is sensitive to lithology according to the reservoir type; extracting a difference curve from the logging curve; and dividing sedimentary cycles according to the change trend of the difference curve. The present invention improves the spectrum resolution by calculating the autocorrelation function; and automatically divides the sedimentary cycles by extracting the difference curve, which greatly reduces the workload and human interference, and makes the results more accurate.

Description

Technical Field

[0001] The present invention belongs to the technical field of geophysical exploration, and in particular relates to a method, a device, an electronic device and a storage medium for automatically dividing sedimentary cycles. Background Art

[0002] Sedimentary cycle refers to the law of successive deposition of rock layers in the order of large to small particles and large to small specific gravity. On the stratigraphic section, it is shown as the order from old to new, and the rock layers are coarse sandstone-medium sandstone-fine sandstone-siltstone-mudstone in order of grain size from coarse to fine. Sedimentary cycle focuses on lithological sedimentary cycle. Sedimentary cycle refers to a sequence composed of repeated deposition of sedimentary action and sedimentary conditions in the same order. Sedimentary cycle is the regular periodic repetition of similar lithology and lithofacies in the vertical direction of the stratum, such as the color / grain size of the rock. Sedimentary cycles in reservoirs are generally small in scale.

[0003] In the process of oil and gas exploration, when dividing the sedimentary cycle of the target bottom layer, it is usually necessary to analyze the sedimentary cycle first. The conventional sedimentary cycle division method is guided by sequence stratigraphy or high-resolution sequence stratigraphy, and the sedimentary cycle interface and properties are determined based on drilling data and seismic data in the study area. However, this method has a huge workload and too much human interference, and there are multiple solutions.

[0004] In addition, since changes in sediment particle size will cause changes in the spectral energy of the seismic profile, the spectral energy of the seismic signal can also be analyzed through wavelet transform, and the sedimentary cycle can also be analyzed and determined. However, seismic data often lack high-frequency components and have low resolution, so there is still some difficulty in determining small-scale reservoir sedimentary cycles.

[0005] Therefore, the art needs to provide a new method for automatic division of sedimentary cycles to reduce workload and human interference and improve division accuracy. Summary of the invention

[0006] In view of the huge workload, much human interference, multiple solutions and low resolution of the existing methods for dividing sedimentary cycles, this paper proposes an automatic division method for sedimentary cycles. This method is mainly guided by high-resolution sequence stratigraphy. By optimizing logging curves, spectral analysis of the optimized curves and extracting difference curves, it can realize automatic tracking of multi-well cycles under dense well network conditions in the development stage, batch generate stratification results for each well, improve work efficiency and accuracy, and reduce human intervention and adjustment.

[0007] According to one aspect of the present invention, there is provided a method for automatically dividing a sedimentation cycle, comprising:

[0008] Select well logging curves that are sensitive to lithology according to reservoir type;

[0009] Extracting a difference curve from the logging curve;

[0010] Sedimentary cycles are divided according to the changing trend of the difference curve.

[0011] Furthermore, the method also includes preprocessing the selected logging curve, including removing singular values, correcting, filtering and standardizing.

[0012] Furthermore, the difference curve is obtained by calculating the autocorrelation function of the logging curve values.

[0013] Furthermore, the autocorrelation function of the logging curve value is:

[0014] R N (r1,r2,r3,...,r N )

[0015] Extrapolate the function to get the N+1th value of the function (r N+1 ),

[0016]

[0017] The difference curve X is obtained by calculating the difference between each value of the autocorrelation function and the measured data. n .

[0018] Furthermore, the difference of the logging data at each depth point can be obtained by comparing the measured logging data value with the calculated autocorrelation function value. n The sedimentary cycles are divided according to the trend of the sedimentary rocks.

[0019] Furthermore, the method includes mapping the resulting deposition cycles.

[0020] According to another aspect of the present invention, there is provided a device for automatically dividing a sedimentation cycle, comprising:

[0021] Selection module, select the logging curve sensitive to lithology according to the reservoir type;

[0022] A difference module extracts a difference curve from the logging curve;

[0023] A division module is used to divide the sedimentary cycles according to the change trend of the difference curve.

[0024] Specifically, the difference module calculates the autocorrelation function for the logging curve value, and obtains the difference curve by calculating the difference between each value of the autocorrelation function and the measured data;

[0025] The autocorrelation function of the logging curve value is:

[0026] R N(r1,r2,r3,...,r N )

[0027] Extrapolate the function to get the N+1th value of the function (r N+1 ),

[0028]

[0029] The difference curve X is obtained by calculating the difference between each value of the autocorrelation function and the measured data. n .

[0030] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0031] A memory storing executable instructions;

[0032] A processor runs the executable instructions in the memory to implement the automatic division method of sedimentation cycles.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for automatically dividing sedimentation cycles is implemented.

[0034] Compared with the existing technology, the present invention has the following innovative features:

[0035] By calculating the autocorrelation function, the spectrum resolution is improved; by extracting the difference curve, the sedimentary cycle is automatically divided, which greatly reduces the workload and human interference, making the results more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components in the exemplary embodiments of the present disclosure.

[0037] Figure 1 The figure is a flow chart of the method for automatic division of sedimentation cycles according to the present invention.

[0038] Figure 2 The original logging curve according to the embodiment of the present invention and the calculated difference curve.

[0039] Figure 3 This is an artificial division of sedimentation cycles according to an embodiment of the present invention.

[0040] Figure 4 Schematic diagram of an automatic division of deposition cycles according to an embodiment of the present invention.

[0041] Figure 5It is a technical flow chart according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0043] Conventional cycle analysis determines the interface and properties of sedimentary cycles based on drilling data and seismic data in the study area, but this method is labor-intensive and has too much human interference and multiple solutions. In addition, the spectrum energy of seismic signals can be analyzed and determined through wavelet transform, but seismic data often lack high-frequency components and have low resolution.

[0044] The present invention proposes a method for automatic division of sedimentary cycles. The method is mainly guided by high-resolution sequence stratigraphy. By optimizing logging curves, performing spectrum analysis on the optimized curves and extracting difference curves, automatic tracking of multi-well cycles under dense well network conditions in the development stage is achieved, and stratification results of each well are generated in batches, thereby improving work efficiency and accuracy and reducing manual intervention and adjustment.

[0045] like Figure 1 As shown, the present invention proposes a method for automatically dividing sedimentary cycles, comprising:

[0046] Select well logging curves that are sensitive to lithology according to reservoir type;

[0047] Extracting a difference curve from the logging curve;

[0048] Sedimentary cycles are divided according to the changing trend of the difference curve.

[0049] Specifically, the present invention creates a method for performing spectrum analysis on logging curves based on high-resolution sequence stratigraphy, and extracting difference curves from the curves to automatically divide sedimentary cycles. The details are as follows:

[0050] First, select the logging curve that is sensitive to lithology.

[0051] Preferably, the original logging curves may also be preprocessed, mainly including removal of singular values, correction, filtering and standardization.

[0052] Next, the spectrum of the logging curve value is estimated. The autocorrelation function R is calculated for the original logging curve value. N (r1,r2,r3,...,r N), extrapolate the function to get the N+1th value of the function (r N+1 ), which meets the following conditions:

[0053]

[0054] in

[0055]

[0056]

[0057] make The gradient matrix D(r) can be obtained

[0058]

[0059] Find the solution of the gradient matrix, that is

[0060]

[0061] in is the last row of the gradient matrix, that is

[0062]

[0063]

[0064] In this way, we can obtain r N+1 , solve them one by one, and obtain the difference curve X by calculating the difference between each value of the autocorrelation function and the measured data n .

[0065] (3) According to the obtained difference curve X n The sedimentary cycles are divided into two categories: a positive cycle is thick at the top and a thin at the bottom, and a reverse cycle is thin at the top and a thick at the bottom.

[0066] (4) Mapping the resulting sedimentary cycles.

[0067] To facilitate understanding of the solutions and effects of the embodiments of the present invention, a specific application example is given below. Those skilled in the art should understand that the example is only for facilitating understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.

[0068] Example 1

[0069] Reference Figure 2-Figure 5 , describing a specific application embodiment of the present invention.

[0070] First, select the sensitivity curve according to the reservoir type; perform curve preprocessing on the selected sensitivity curve; next, generate the corresponding difference curve for the sensitivity curve; finally, divide the sedimentary cycle according to the change trend of the difference curve.

[0071] Next, this embodiment compares the results of manually dividing the sedimentary cycles and automatically dividing the sedimentary cycles according to the difference curve to illustrate:

[0072] From the cyclic characteristics and sand formation development characteristics of Chuanxiao 603 Well (ref. Figure 3 ), during the deposition of the Shaximiao Formation, the JS2 period had the shallowest depositional water body and the most developed sandstone, and the next period was the period of the Lower Shaximiao Formation, where the sandstone formation was relatively developed. During the JS1 depositional period, the water body was the deepest, the depositional energy was the weakest, and mud deposits were the main type. During the depositional period of the Penglaizhen Formation, during the JP1 and JP2 periods, the northeastern and northwest source areas of the work area were located at the delta front, and sandstone dominated by underwater distributary channel microfacies was developed, and sandstone was the most developed. During the JP3 depositional period, the water body was the deepest, and the front delta-shore shallow lake was mainly developed, the depositional energy was the weakest, and mud deposits were the main type.

[0073] According to the GR curve of Well CX603, the medium-term, long-term and short-term sedimentary cycles were artificially divided. The specific results are as follows: Figure 3 As shown, the GR curve is analyzed by spectrum, and the difference curve of the GR curve is extracted. According to the trend shape and turning point of the difference curve (refer to Figure 2 ) to automatically track and thus determine the cycle interface and realize the automatic division of sedimentary cycles (refer to Figure 4 ).

[0074] Comparing the results of Peng 3, Peng 2 and Peng 1, the automatic division results of medium- and long-term cycles are more consistent with the manual division results, and the short-term cycles are more refined.

[0075] Example 2

[0076] This embodiment provides a device for automatically dividing a sedimentation cycle, comprising:

[0077] Selection module, select the logging curve sensitive to lithology according to the reservoir type;

[0078] A difference module extracts a difference curve from the logging curve;

[0079] A division module is used to divide the sedimentary cycles according to the change trend of the difference curve.

[0080] The selection module, the difference module, and the division module are sequentially connected in communication. The selection module sends the selected sensitive logging curve to the difference module, the difference module extracts the difference curve from the sensitive logging curve, and sends the extraction result to the division module, and the division module divides the sedimentary cycle according to the change trend of the difference curve.

[0081] Example 3

[0082] This embodiment provides an electronic device, which includes: a memory storing executable instructions; and a processor, which runs the executable instructions in the memory to implement the above-mentioned method for automatic division of deposition cycles.

[0083] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0084] 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.

[0085] The processor may be a central processing unit (CPU) or other forms of processing units having 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 disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0086] Those skilled in the art should be able to 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 disclosure.

[0087] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0088] Example 4

[0089] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for automatically dividing sedimentation cycles is implemented.

[0090] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of each embodiment of the present disclosure are executed.

[0091] 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).

[0092] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.

[0093] 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 automatically dividing sedimentary cycles, characterized in that: include: Select well logging curves that are sensitive to lithology according to reservoir type; Extracting a difference curve from the logging curve; Dividing the sedimentary cycles according to the changing trend of the difference curve; Among them, the difference curve is obtained by calculating the autocorrelation function of the logging curve value; Among them, the autocorrelation function of the logging curve value is: R N (r1,r2,r3,...,r N ) Extrapolate the function to get the N+1th value of the function (r N+1 ), The difference curve X is obtained by calculating the difference between each value of the autocorrelation function and the measured data. n .

2. The method for automatic division of sedimentary cycles according to claim 1, characterized in that: The method further includes preprocessing the selected logging curve, including removing singular values, correcting, filtering and standardizing.

3. The method for automatic division of sedimentary cycles according to claim 1, characterized in that: The difference between the measured data value and the calculated autocorrelation function value is used to obtain the difference curve X n The sedimentary cycles are divided according to the trend of the sedimentary rocks.

4. The method for automatic division of sedimentation cycles according to claim 1, characterized in that: Further comprising mapping the resulting sedimentary cycles.

5. A device for automatically dividing sedimentation cycles, characterized in that: include: Selection module, select the logging curve sensitive to lithology according to the reservoir type; A difference module extracts a difference curve from the logging curve; A division module, dividing the sedimentary cycles according to the change trend of the difference curve; Among them, the difference curve is obtained by calculating the autocorrelation function of the logging curve value; Among them, the autocorrelation function of the logging curve value is: R N (r1,r2,r3,...,r N ) Extrapolate the function to get the N+1th value of the function (r N+1 ), The difference curve X is obtained by calculating the difference between each value of the autocorrelation function and the measured data. n .

6. 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 method for automatic division of sedimentation cycles according to any one of claims 1 to 4.

7. 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 method for automatically dividing sedimentation cycles according to any one of claims 1 to 4 is implemented.

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