CN116296946A - Shale stratum development degree characterization method and device based on fractal-fluctuation theory - Google Patents

Shale stratum development degree characterization method and device based on fractal-fluctuation theory Download PDF

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CN116296946A
CN116296946A CN202310203793.6A CN202310203793A CN116296946A CN 116296946 A CN116296946 A CN 116296946A CN 202310203793 A CN202310203793 A CN 202310203793A CN 116296946 A CN116296946 A CN 116296946A
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杨柳
刘朝阳
刘合
李明峻
韩振川
余哲涵
申子航
左建平
吴旭
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China University of Mining and Technology Beijing CUMTB
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Abstract

The invention discloses a shale tattoo development degree characterization method and device based on a fractal-fluctuation theory. The method comprises the following steps: acquiring shale scratch test data; drawing a scribing distance-depth curve and a scribing depth-distance curve respectively by using scratch test data; dividing the scribing distance-depth curve by adopting different scales and establishing scratch complexity; dividing the drawn depth-distance curve by adopting different threshold values and establishing a scratch fluctuation step length; and calculating a layer development index according to the fluctuation step length and the scratch complexity, and defining a layer development classification index to represent the layer development degree. The invention solves the problem that the scratch test in the prior art lacks a shale grain development degree characterization method. In addition, the method provided by the invention has the advantages of simple required test equipment, clear test principle and easiness in implementation.

Description

Shale stratum development degree characterization method and device based on fractal-fluctuation theory
Technical Field
The invention relates to the technical field of oil and gas exploration and material analysis, in particular to a shale tattoo development degree characterization method and device based on fractal-fluctuation theory.
Background
Shale oil gas is an important component of natural gas resources in China, and a large amount of shale oil gas is generated in Sichuan basin, erdos basin, songliao basin and Songyang basin of China. With the continuous deep exploration and development of shale oil and gas, students find that shale oil and gas reservoirs have strong heterogeneity mainly caused by layering stack formed by the change of paleo-deposition environment and the like. The shale stratum can reflect microstructure characteristics and reservoir performance of the shale reservoir, and can reveal the expansion rule and fracturing effect of the pressure fracture network in the shale reservoir reconstruction process. The layers widely develop in the shale layer rich in organic matters, and the quality of the shale oil and gas reservoir layer generated from the self-storage is seriously influenced, so that shale layer research becomes a focus in shale oil and gas exploration and development basic research work.
At present, the stratum characterization method mostly adopts single triaxial rock mechanics experiments with different angles, which are all scatter measurement, and mineral resource exploitation gradually develops to the deep part, so that the geological structure environment is complex, and the coring operation becomes very difficult. And the sample is in a centimeter scale and cannot be characterized for millimeter-scale layers. The continuous section mechanical property can be obtained by adopting a scratch means, the prepared sample size is small, the maximum information about the heterogeneous behavior of the rock can be obtained from a small amount of core analysis, and the advantage is obvious. However, the scratch means can only obtain the parameters such as hardness, fracture toughness and the like, and a shale grain development degree characterization method is lacked.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides the following technical scheme.
The invention provides a shale stratum development degree characterization method based on a fractal-fluctuation theory, which comprises the following steps:
acquiring shale scratch test data;
drawing a scribing distance-depth curve and a scribing depth-distance curve respectively by using scratch test data;
dividing the scribing distance-depth curve by adopting different scales and establishing scratch complexity;
dividing the drawn depth-distance curve by adopting different threshold values and establishing a scratch fluctuation step length;
and calculating a layer development index according to the fluctuation step length and the scratch complexity, and defining a layer development classification index to represent the layer development degree.
Preferably, the shale scratch test data are obtained through a scratch test, wherein the scratch test comprises three stages of pre-scanning, engraving scanning and post-scanning; in the pre-scanning stage, scanning the surface of the sample with constant contact force, and recording the change of the scribing depth along with the scribing distance; in the stage of scribing scanning, linearly loading a scribing sample, and recording the change of loading force, friction force and scribing depth along with the scribing distance; in the post-scanning stage, the scratch morphology is scanned with constant contact force, and the change of the scratch depth along with the scratch distance is recorded.
Preferably, said dividing said scribe distance-depth curve and establishing a scribe complexity using different scales comprises:
dividing the vertical coordinate of the dividing distance-depth curve into depths by using different scales, and generating a plurality of sections corresponding to each scale;
within each section, the corresponding number of boxes is calculated according to the following formula
Figure SMS_1
：
Figure SMS_2
If->
Figure SMS_3
Is an integer;
Figure SMS_4
if->
Figure SMS_5
Is a non-integer;
in the method, in the process of the invention,
Figure SMS_6
for the number of boxes->
Figure SMS_7
For the scale->
Figure SMS_8
Is an integer part of the maximum value of the signal data within the interval, < >>
Figure SMS_9
An integer part of a minimum value of the signal data in the section;
adding the box numbers of all intervals corresponding to each scale to obtain the total box number;
establishing a double logarithmic relation curve between each scale and the corresponding total box number;
calculating the slope of a straight line segment in a double-logarithmic relation curve corresponding to each scale as the complexity of a corresponding scribing distance-depth curve;
the mean of the complexities is calculated as the scratch complexity of the rock.
Preferably, the equally dividing the scribing depth-distance curve by using different threshold values and establishing a scratch fluctuation step length includes:
performing equivalence division on the ordinate scratch distances of the scratch depth-distance curve by using different threshold values to generate domains with different numbers;
and calculating the number of the resident points of the scribing depth-distance curve contained in each domain, and defining the corresponding threshold value as the scratch fluctuation step length when the duty ratio of the number of the resident points of 1 reaches the maximum value.
Preferably, the method further comprises, before performing the equivalence division on the ordinate-type distance of the depth-distance curve by using different threshold values:
and amplifying the length of the scribing distance on the ordinate of the scribing depth-distance curve according to a preset proportion, and generating a corrected scribing depth-distance curve while keeping the value of the ordinate unchanged.
Preferably, the calculating the layer development index according to the fluctuation step length and the scratch complexity comprises:
Figure SMS_10
，
wherein,,
Figure SMS_11
is the index of development of the schlieren>
Figure SMS_12
Takes the value of 100 for the correction coefficient>
Figure SMS_13
For fluctuation step size +.>
Figure SMS_14
Is scratch complexity.
Preferably, the defining the index of the grade of the development of the tattoos to characterize the degree of development of the tattoos includes:
when (when)
Figure SMS_15
The degree of development is defined as the first level of development; when->
Figure SMS_16
The degree of development is defined as the secondary level of development; when->
Figure SMS_17
The degree of development is defined as the tertiary level of development.
The second aspect of the invention provides a shale grain development degree characterization device based on fractal-fluctuation theory, which comprises:
the data acquisition module is used for acquiring shale scratch test data;
the curve drawing module is used for drawing a drawing distance-depth curve and a drawing depth-distance curve respectively by using scratch test data;
the scratch complexity establishing module is used for dividing the scribing distance-depth curve by adopting different scales and establishing scratch complexity;
the fluctuation step length establishing module is used for equally dividing the dividing depth-distance curve by adopting different threshold values and establishing a scratch fluctuation step length;
the layer development degree characterization module is used for calculating a layer development index according to the fluctuation step length and the scratch complexity, and defining a layer development grading index to characterize the layer development degree.
A third aspect of the invention provides a memory storing a plurality of instructions for implementing the method as described in the first aspect.
A fourth aspect of the invention provides an electronic device comprising a processor and a memory coupled to the processor, the memory storing a plurality of instructions loadable and executable by the processor to enable the processor to perform the method of the first aspect.
The beneficial effects of the invention are as follows: the invention provides a shale tattoo development degree characterization method and device based on a fractal-fluctuation theory. The method is researched by means of shale scratch test, data processing, image analysis and the like, and scratch fluctuation step length is established based on fluctuation theory
Figure SMS_18
The method is used for quantitatively expressing the fluctuation frequency of the scratch curve of the lamellar shale; establishing a stratum corneum shale development complexity index based on fractal theory>
Figure SMS_19
The method is used for quantitatively expressing the complexity of the scratch curve of the lamellar shale; finally combining fractal-fluctuation theory and introducing the stratum corneum development index +.>
Figure SMS_20
Defining a layer development grading index to comprehensively characterize the layer development degree. The invention solves the problem that the scratch test in the prior art lacks a shale grain development degree characterization method. In addition, the method provided by the invention has the advantages of simple required test equipment, clear test principle and easiness in implementation.
Drawings
FIG. 1 is a flow chart of a shale tattoo development degree characterization method based on fractal-fluctuation theory;
FIG. 2 is a schematic illustration of a scratch test;
figures 3a-3d are graphs of scribe distance versus depth, respectively, for different sample scratches;
FIGS. 4a-4d are plot of the scoring distance versus depth for pyrite divided by scales 50, 100, 150 and 200, respectively;
FIG. 5 is a schematic view of a display
Figure SMS_21
A double logarithmic relationship curve;
FIG. 6a is a scribe depth-distance curve, and FIG. 6b is a modified scribe depth-distance curve;
FIGS. 7a-7d are plot depth-to-distance curves of pyrite divided by threshold values 10, 15, 20, 30, respectively;
FIG. 8 is a diagram illustrating the standing-point duty ratios corresponding to different threshold values;
FIG. 9 is a schematic diagram of a functional module of a shale tattoo development degree characterization device based on fractal-wave theory;
in fig. 2, the meaning of each symbol is:
1. scratch test sample, 2, scratch indenter, FN, vertical load, FT, horizontal load.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
Aiming at the problems existing in the prior art, the invention is based on the fractal theory and the fluctuation theory, introduces the fractal complexity of the fractal theory and the fluctuation step length of the fluctuation theory, quantitatively describes the characteristics of the scratch curve, and introduces the growth index of the stratum corneum
Figure SMS_22
And defining a grade index of the development of the tattoos to comprehensively characterize the development degree of the tattoos.
Example 1
As shown in fig. 1, the embodiment of the invention provides a shale grain development degree characterization method based on fractal-fluctuation theory, which comprises the following steps: s101, shale scratch test data are obtained; s102, drawing a scribing distance-depth curve and a scribing depth-distance curve respectively by using scratch test data; s103, dividing the scribing distance-depth curve by adopting different scales and establishing scratch complexity; s104, equally dividing the drawn depth-distance curve by adopting different threshold values and establishing a scratch fluctuation step length; s105, calculating a layer development index according to the fluctuation step length and the scratch complexity, and defining a layer development grading index to represent the layer development degree.
Wherein, prior to executing step S101, the shale scratch test may be performed first to obtain relevant data and store the relevant data for subsequent use.
In the actual operation process, sample preparation can be firstly carried out before scratch test is carried out, and the specific preparation method can be as follows: in situ shale sampling, the sample is initially polished parallel to its bedding surface with silicon carbide paper, and then the sample surface is further polished with an argon ion suspension to ensure that the shale sample surface is smooth. After the sample preparation is completed, a scratch test can be performed, and specifically, the following method can be adopted: scratch tests were performed in shale grain page planes. In the test, a rocweil C diamond probe with a half apex angle of 60 degrees was used, with a tip radius r=200 mm. For each test, the load was constant at 50 mN while the scratch speed remained constant, at 30 um/s on a 0.5mm scratch path. A schematic of the scratch test can be shown in fig. 2. Scratch testing is generally divided into three stages: pre-scanning, engraving scanning and post-scanning stages. Wherein, in the pre-scan stage: the sample surface was scanned with a constant contact force of 20uN and the variation of the sample surface relief (i.e., the scribe depth) with scribe distance was recorded. Etching and scanning: the scribing sample is linearly loaded, and the change of loading force, friction force and scribing depth along with the scribing distance is recorded. Post-scanning stage: the scratch morphology was scanned with a constant contact force of 20uN and the variation of the surface relief (i.e. the scratch depth) of the sample with the scratch distance was recorded.
Step S102 is executed, each scratch test generates a group of data, wherein the group of data comprises data of three stages of pre-scanning, engraving scanning and post-scanning, and effective data comes from the engraving scanning stage. Processing the generated data, wherein the drawing depth is set as an abscissa, the drawing distance is set as an ordinate, and a drawing depth-distance curve is generated; the scribing distance is set as the abscissa, and the scribing depth is set as the ordinate, and a scribing distance-depth curve is generated. Different samples produced different scratch penetration depth-distance curves and penetration distance-depth curves. As an example, the scribing distance-depth curve of pyrite sample scratches, sandy sample scratches, carbon dust sample scratches, and scale sample scratches are shown in fig. 3a-3d, respectively. Fig. 6a is a plot of depth of scratch versus distance for a pyrite sample.
Step S103 is performed to divide the scribe distance-depth curves and establish the scratch complexity using different scales, which can be implemented specifically as follows: dividing the ordinate of the dividing distance-depth curve into a plurality of intervals corresponding to each scale. In this step, different scales are selected based on fractal theory
Figure SMS_23
I.e. grid width->
Figure SMS_24
Dividing the drawn distance-depth plane image to form a plurality of equidistant square grids, wherein the length of the ordinate interval of each square grid is +.>
Figure SMS_25
。
Calculating the corresponding number of boxes in each section
Figure SMS_26
. If the integer part of the maximum value of the signal data in the square is divided by the scale +.>
Figure SMS_27
When the result of (a) is an integer, subtracting the integer part of the maximum value and the integer part of the minimum value of the signal data in the square, and comparing the result of the subtracting with the scale +.>
Figure SMS_28
As the number of boxes; if the integer part of the maximum value of the signal data in the square is divided by the scale +.>
Figure SMS_29
When the result of (2) is not an integer, subtracting the integer part of the maximum value and the integer part of the minimum value of the signal data in the square, and comparing the result of the subtracting with the scale +.>
Figure SMS_30
The ratio of (2) plus one is used as the number of boxes.
The method can be specifically expressed by the following formula:
Figure SMS_31
if->
Figure SMS_32
Is an integer;
Figure SMS_33
if->
Figure SMS_34
Is a non-integer;
in the method, in the process of the invention,
Figure SMS_35
for the number of boxes->
Figure SMS_36
For the scale->
Figure SMS_37
Is an integer part of the maximum value of the signal data within the interval, < >>
Figure SMS_38
Is the integer part of the minimum value of the signal data within the interval.
Adding the box numbers of all intervals corresponding to each scale to obtain the total box number; establishing a double logarithmic relation curve between each scale and the corresponding total box number; calculating the slope of a straight line segment in a double-logarithmic relation curve corresponding to each scale as the complexity of a corresponding scribing distance-depth curve; the mean of the complexities is calculated as the scratch complexity of the rock.
In one embodiment, taking pyrite-based layered shale as an example, different scales are selected based on fractal theory
Figure SMS_39
I.e. grid width->
Figure SMS_40
(50, 100, 150, 200) dividing the distance-depth-binned planar image into a plurality of equally spaced bins as shown in fig. 4a-4 d. The total length of the ordinate-drawn depth can be denoted as M if +.>
Figure SMS_41
Is an integer, the planar image of the scratch distance-depth is divided into +.>
Figure SMS_42
The equal spaceThe intervals of each interval are as follows:
Figure SMS_43
Figure SMS_44
；
if it is
Figure SMS_45
Not an integer, then get->
Figure SMS_46
The integer part of (2) is denoted as M 1 The sections divided on the ordinate are:
Figure SMS_47
Figure SMS_48
；
Figure SMS_49
the last space grid;
as an example such as when m=5.5,
Figure SMS_50
when it is the case, it can be divided into two equally spaced intervals of 2 and one non-equally spaced interval.
In any interval on the ordinate axis, e.g. in
Figure SMS_53
In the interval, the integer part of the maximum value of the signal data is marked as +.>
Figure SMS_57
And the integer part of the minimum is denoted +.>
Figure SMS_60
. Will->
Figure SMS_54
And->
Figure SMS_56
Calculate and scale after subtraction>
Figure SMS_59
Ratio of (1), if->
Figure SMS_62
Divide by the scale->
Figure SMS_51
Is an integer, the ratio is taken as the box number +.>
Figure SMS_55
If->
Figure SMS_58
Divide by the scale->
Figure SMS_61
If not, the result of adding one to the ratio is taken as the box number +.>
Figure SMS_52
。
The method can be specifically expressed by the following formula:
when (when)
Figure SMS_63
When the number is an integer: />
Figure SMS_64
When (when)
Figure SMS_65
When not an integer: />
Figure SMS_66
。
For example, when the maximum value of signal data in the interval is 5.5, the minimum value is 1.1, the scale
Figure SMS_67
When (I)>
Figure SMS_68
，/>
Figure SMS_69
The number of boxes is +.>
Figure SMS_70
。
Number of boxes of all sections corresponding to the scale
Figure SMS_71
Adding to obtain the total box number of the scale-corresponding scratch-in distance-depth plane image +.>
Figure SMS_72
The method can be specifically expressed by the following formula:
Figure SMS_73
superscript in the summation equation above if M is not an integer
Figure SMS_74
Is an integer part of (c).
Taking different scales
Figure SMS_75
Repeating the above steps to obtain corresponding +.>
Figure SMS_76
Finally get->
Figure SMS_77
A double logarithmic relationship is shown in fig. 5. />
Figure SMS_78
The shape of the log-log relationship, associated with different shale materials, contains a large amount of information about the rock. If a straight line (or an approximate straight line) exists in the curve, the scale range of the straight line is +.>
Figure SMS_79
In this regard, the slope of this line is considered to be the complexity D of the waveform image:
Figure SMS_80
FIG. 5 shows the corresponding score distance-depth curve according to four scratches (the score corresponding data sets are text1, text2, text3, text4, respectively), and the score distance-depth curve is drawn according to the score corresponding data set
Figure SMS_81
、/>
Figure SMS_82
Data-rendered +.>
Figure SMS_83
Taking straight line segments or approximate straight line segments in the curves respectively, calculating the slope of the straight line segments or approximate straight line segments to obtain the complexity D of the curve (signal waveform) of the distance-depth, and finally calculating the mean value ∈of D>
Figure SMS_84
Scratch complexity as the rock>
Figure SMS_85
The expression can be expressed as follows:
Figure SMS_86
wherein,,
Figure SMS_87
for the complexity of the scribing distance-depth curve (signal waveform) corresponding to the ith scratch, i=1, 2,3 … … n, n being the number of scratches.
Step S104 is executed, and the scribing depth-distance curve is divided by using different threshold values and the scratch fluctuation step length is established, which can be implemented in the following manner: performing equivalence division on the ordinate scratch distances of the scratch depth-distance curve by using different threshold values to generate domains with different numbers; and calculating the number of the resident points of the scribing depth-distance curve contained in each domain, and defining the corresponding threshold value as the scratch fluctuation step length when the duty ratio of the number of the resident points of 1 reaches the maximum value.
Further, before the performing the equivalence division on the ordinate of the drawn depth-distance curve by using different threshold values, the method may further include: and amplifying the length of the scribing distance on the ordinate of the scribing depth-distance curve according to a preset proportion, and generating a corrected scribing depth-distance curve while keeping the value of the ordinate unchanged.
In one embodiment, taking pyrite-based layered shale as an example, the scribing depth is set as an abscissa x, the scribing distance is defined as an ordinate y based on the wave theory, and the scribing depth-distance curve is drawn. The ordinate length is scaled up in proportion but the ordinate value remains unchanged, resulting in a modified scribe depth-distance curve as shown in fig. 6 b. The ordinate scribe distance of the modified scribe depth-distance curve is equally divided by different threshold values U (u=10, 15, 20, 30) in which y/U fields will be generated as shown in fig. 7a-7 d. And calculating the number S of standing points of the waveform image contained in each domain, and when the duty ratio of the number S of the standing points is 1 and reaches the maximum value, obtaining the corresponding domain value as the fluctuation step lambda of the scratch. Taking pyrite lamellar shale as an example, when the threshold value u=10, the duty ratio of the number of standing points at this time is 1 is maximum, as shown in fig. 8, and therefore, the fluctuation step λ=10 of pyrite lamellar shale.
Step 105 is executed to calculate the growth index of the layer according to the fluctuation step length and the scratch complexity, and specifically, the following formula can be adopted for calculation:
Figure SMS_88
wherein,,
Figure SMS_89
is a patternLayer development index, ->
Figure SMS_90
Takes the value of 100 for the correction coefficient>
Figure SMS_91
For fluctuation step size +.>
Figure SMS_92
Is scratch complexity.
Then, the index of the grade of the development of the tattoo can be defined according to the index of the development of the tattoo to represent the degree of the development of the tattoo, which can comprise: when (when)
Figure SMS_93
The degree of development is defined as the first level of development; when->
Figure SMS_94
The degree of development is defined as the secondary level of development; when->
Figure SMS_95
The degree of development is defined as the tertiary level of development.
In one embodiment, the variation of the surface relief (i.e., the scratch depth) of the sample with the scratch distance as the scratch test is performed, the scratch depth-distance curve and the scratch distance-depth curve are deeply analyzed based on the fractal theory and the wave theory, and the internal cause of the variation of the curve is considered to be due to the strong heterogeneity of the lamellar shale. The fractal complexity of the fractal theory and the fluctuation step length of the fluctuation theory are introduced, and the scratch curve characteristic is quantitatively described, so that the development degree of the tattoo shale is evaluated to a certain extent.
Analysis according to fluctuation theory can be carried out to reduce the development degree of the schlieren when the fluctuation step length is larger, and pyrite is adopted
Figure SMS_96
Scale insect->
Figure SMS_97
Sandy lamellar shale->
Figure SMS_98
For example, by the above method operation, the following results can be obtained:
Figure SMS_99
the development degree of the three shale layers is sequentially from high to low, namely a pyrite layer, a sandy layer and a scale insect layer.
Analysis according to the fractal theory can be carried out when the complexity is higher, and the development degree of the tattoo layer is higher, and by taking pyrite Dim 1, scale insect Dim 2 and sandy tattoo shale Dim 3 as examples, the following results can be obtained through the operation of the method:
Figure SMS_100
the development degree of the three shale layers is sequentially from high to low, namely a pyrite layer, a sandy layer and a scale insect layer.
Finally, combining fractal theory and fluctuation theory, and introducing a stratum corneum development index
Figure SMS_101
And according to the index of the growth of the lamina->
Figure SMS_102
And defining a grade index of the development of the tattoos to comprehensively characterize the development degree of the tattoos. I.e. the product of the fluctuation step and the complexity is defined as the stratum corneum development index +.>
Figure SMS_103
：
Figure SMS_104
Where α is a correction factor, and is typically 100. When (when)
Figure SMS_105
The degree of development is defined as the first level of hairLevel of fertility, when->
Figure SMS_106
The degree of development is defined as the level of secondary development when +.>
Figure SMS_107
The degree of development is defined as the tertiary level of development. The greater the BI value, the greater the degree of grain development. For example, pyrite lamellar shale bi=17, the degree of development is tertiary development level; the scale shale bi=6, the degree of development is the first level of development.
Example two
As shown in fig. 9, an embodiment of the present invention provides a shale tattoo development degree characterization device based on fractal-fluctuation theory, including: the data acquisition module 201 is used for acquiring shale scratch test data; the curve drawing module 202 is configured to draw a scribing distance-depth curve and a scribing depth-distance curve respectively using scratch test data; a scratch complexity establishing module 203, configured to divide the scribing distance-depth curves with different scales and establish scratch complexity; the fluctuation step length establishing module 204 is configured to equally divide the scribing depth-distance curve by using different threshold values and establish a scratch fluctuation step length; the layer development degree characterization module 205 is configured to calculate a layer development index according to the fluctuation step size and the scratch complexity, and define a layer development classification index to characterize the layer development degree.
The apparatus may be implemented by the method described in the first embodiment, which is not described herein.
The embodiment of the invention also provides a memory, which stores a plurality of instructions for implementing the method according to the embodiment one.
The embodiment of the invention also provides an electronic device, which comprises a processor and a memory connected with the processor, wherein the memory stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the method in the embodiment.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention. It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims (9)

1. The shale stratum development degree characterization method based on the fractal-fluctuation theory is characterized by comprising the following steps of:
acquiring shale scratch test data;
drawing a scribing distance-depth curve and a scribing depth-distance curve respectively by using scratch test data;
dividing the scribing distance-depth curve by adopting different scales and establishing scratch complexity;
dividing the drawn depth-distance curve by adopting different threshold values and establishing a scratch fluctuation step length;
calculating a layer development index according to the fluctuation step length and the scratch complexity, and defining a layer development classification index to represent the layer development degree;
wherein said dividing said scribe-in distance-depth curve and creating a scribe complexity using different scales comprises:
dividing the ordinate of the dividing distance-depth curve into depths by using different scales, and generating a plurality of intervals corresponding to each scale; within each section, the corresponding number of boxes is calculated according to the following formula
Figure QLYQS_1
：
Figure QLYQS_2
If->
Figure QLYQS_3
Is an integer;
Figure QLYQS_4
if->
Figure QLYQS_5
Is a non-integer;
in the method, in the process of the invention,
Figure QLYQS_6
for the number of boxes->
Figure QLYQS_7
For the scale->
Figure QLYQS_8
Is an integer part of the maximum value of the signal data within the interval,
Figure QLYQS_9
an integer part of a minimum value of the signal data in the section; adding the box numbers of all intervals corresponding to each scale to obtain the total box number; establishing a double logarithmic relation curve between each scale and the corresponding total box number; calculating the slope of a straight line segment in a double-logarithmic relation curve corresponding to each scale as the complexity of a corresponding scribing distance-depth curve; the mean of the complexities is calculated as the scratch complexity of the rock.
2. The shale tattoo development degree characterization method based on the fractal-fluctuation theory as recited in claim 1, wherein the shale scratch test data is obtained through a scratch test, and the scratch test comprises three stages of pre-scanning, engraving scanning and post-scanning; in the pre-scanning stage, scanning the surface of the sample with constant contact force, and recording the change of the scribing depth along with the scribing distance; in the stage of scribing scanning, linearly loading a scribing sample, and recording the change of loading force, friction force and scribing depth along with the scribing distance; in the post-scanning stage, the scratch morphology is scanned with constant contact force, and the change of the scratch depth along with the scratch distance is recorded.
3. The shale tattoo development level characterization method based on fractal-wave theory as recited in claim 1, wherein the equally dividing the scoring depth-distance curve with different threshold values and establishing a scratch fluctuation step size comprises:
performing equivalence division on the ordinate scratch distances of the scratch depth-distance curve by using different threshold values to generate domains with different numbers;
and calculating the number of the resident points of the scribing depth-distance curve contained in each domain, and defining the corresponding threshold value as the scratch fluctuation step length when the duty ratio of the number of the resident points of 1 reaches the maximum value.
4. The shale tattoo development characterization method based on fractal-wave theory as recited in claim 3, further comprising, prior to the performing the equivalence division on the ordinate-type penetration distance of the penetration depth-distance curve with different threshold values:
and amplifying the length of the scribing distance on the ordinate of the scribing depth-distance curve according to a preset proportion, and generating a corrected scribing depth-distance curve while keeping the value of the ordinate unchanged.
5. The shale tattoo development level characterization method based on fractal-wave theory as recited in claim 1, wherein calculating the tattoo development index from the wave step size and the scratch complexity comprises:
Figure QLYQS_10
，
wherein,,
Figure QLYQS_11
is the index of development of the schlieren>
Figure QLYQS_12
Takes the value of 100 for the correction coefficient>
Figure QLYQS_13
For fluctuation step size +.>
Figure QLYQS_14
Is scratch complexity.
6. The method for characterizing the development degree of shale tattoos based on fractal-wave theory as recited in claim 5, wherein defining the development grading index of tattoos to characterize the development degree of tattoos comprises:
when (when)
Figure QLYQS_15
The degree of development is defined as the first level of development; when->
Figure QLYQS_16
The degree of development is defined as the secondary level of development; when->
Figure QLYQS_17
The degree of development is defined as the tertiary level of development.
7. A shale tattoo development level characterization apparatus based on fractal-wave theory for implementing the method as recited in any one of claims 1-6, comprising:
the data acquisition module is used for acquiring shale scratch test data;
the curve drawing module is used for drawing a drawing distance-depth curve and a drawing depth-distance curve respectively by using scratch test data;
the scratch complexity establishing module is used for dividing the scribing distance-depth curve by adopting different scales and establishing scratch complexity;
the fluctuation step length establishing module is used for equally dividing the dividing depth-distance curve by adopting different threshold values and establishing a scratch fluctuation step length;
the layer development degree characterization module is used for calculating a layer development index according to the fluctuation step length and the scratch complexity, and defining a layer development grading index to characterize the layer development degree.
8. A memory, characterized in that a plurality of instructions for implementing the method according to any of claims 1-6 are stored.
9. An electronic device comprising a processor and a memory coupled to the processor, the memory storing a plurality of instructions that are loadable and executable by the processor to enable the processor to perform the method of any one of claims 1-6.
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