Method and apparatus for identifying dense crack zones

Abstract

This invention discloses a method and apparatus for identifying densely populated crack zones. The method includes: acquiring crack-related features of the area to be identified; classifying the cracks into groups; and for each group of cracks, performing the following steps: correcting the acquired crack development intensity data to obtain corrected data; using the corrected data to plot a distance-cumulative frequency map; calculating the average crack spacing, the standard deviation of crack spacing, and standardized local crack intensity data; plotting a local crack intensity distribution map; calculating the crack spacing variation coefficient; determining the sum of the absolute values ​​of the maximum deviations above and below the uniformly distributed cumulative frequency curve of the actual cumulative frequency distribution curve from the crack uniform distribution curve based on the distance-cumulative frequency map; and when the crack spacing variation coefficient is greater than 1 and the sum of the absolute values ​​is greater than 0, determining the densely populated crack zone in this group of cracks using the local crack intensity distribution map and standardized local crack intensity data. This invention can accurately identify densely populated crack zones in each crack group.

Description

Technical Field

[0001] This invention relates to the field of quantitative characterization and comprehensive evaluation of fracture distribution patterns in fractured reservoirs, and particularly to a method and apparatus for identifying densely fractured zones. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] In many energy extraction processes, including oil and gas exploration and development, as well as geothermal energy extraction, fluid flow within rocks is a fundamental process. In most unconventional oil and gas fields or self-generated and self-storing reservoirs, the permeability of the rock matrix is ​​very low. Natural fractures in these tight reservoirs serve as important storage spaces and main seepage conduits, and the degree of fracture development determines the quality of the reservoir. Therefore, characterizing fracture development intensity is crucial for evaluating the physical properties of tight rocks.

[0004] Fracture development intensity is usually characterized by the average fracture spacing or the average linear density of fractures. However, in most rocks, fractures are not uniformly distributed; rather, there are often densely fractured zones. In fact, these zones are the main channels for fluid flow within the rock, and they have been proven to be pathways for hydrocarbon migration, caprock failure, and reservoir permeability. Therefore, describing and understanding the distribution characteristics of fractures within densely fractured zones is of great significance.

[0005] Although densely fractured zones are widely recognized, little has been done on their characterization and identification. To study the distribution patterns of fractures, previous researchers proposed using frequency histograms to describe their distribution. However, this method involves statistical analysis at fixed intervals, which ignores information about individual fractures, reducing the quality of the raw data. Furthermore, the randomness in choosing the fixed interval and statistical step size can cause the statistical results to deviate from reality. Previous researchers have also proposed methods for identifying densely fractured zones, but these merely indicate areas where fracture intensity is greater than the average intensity, lacking statistical and seepage significance. Summary of the Invention

[0006] This invention provides a method for identifying densely fractured zones, used to accurately identify densely fractured zones in various fracture systems. The method includes:

[0007] Acquire crack-related features of the region to be identified, including crack surface morphology features, crack filling features, crack intersection relationships, crack orientation, and crack dip angle;

[0008] The cracks are grouped according to their related characteristics. For each crack group, the following method is performed:

[0009] Acquire crack development intensity data, correct the crack development intensity data, and obtain corrected data;

[0010] Using the corrected data, a distance-cumulative frequency plot was drawn, and the mean crack spacing and standard deviation of crack spacing were calculated.

[0011] Standardized local crack strength data are calculated using the calibration data, and a local crack strength distribution map is drawn based on the standardized local crack strength data.

[0012] The coefficient of variation of crack spacing is calculated based on the standard deviation of crack spacing and the average crack spacing.

[0013] The sum of the absolute values ​​of the maximum deviations of the actual cumulative frequency distribution curve from the crack uniform distribution cumulative frequency curve above and below is determined based on the distance-cumulative frequency diagram. The sum of these absolute values ​​is the crack spacing heterogeneity coefficient.

[0014] When the coefficient of variation of crack spacing is greater than 1 and the coefficient of heterogeneity of crack spacing is greater than 0, the crack-dense zone in the crack group is determined by using the local crack intensity distribution map and standardized local crack intensity data.

[0015] This invention also provides a device for identifying densely packed fracture zones, used to accurately identify densely packed fracture zones in various fracture systems. The device includes:

[0016] The acquisition module is used to acquire crack-related features of the area to be identified. The crack-related features include crack surface morphology features, crack filling features, crack intersection relationships, crack orientation, and crack dip angle.

[0017] The crack grouping module is used to classify cracks into groups based on crack-related characteristics. For each crack group, the module executes the following method:

[0018] Acquire crack development intensity data, correct the crack development intensity data, and obtain corrected data;

[0019] Using the corrected data, a distance-cumulative frequency plot was drawn, and the mean crack spacing and standard deviation of crack spacing were calculated.

[0020] Standardized local crack strength data are calculated using the calibration data, and a local crack strength distribution map is drawn based on the standardized local crack strength data.

[0021] The coefficient of variation of crack spacing is calculated based on the standard deviation of crack spacing and the average crack spacing.

[0022] The sum of the absolute values ​​of the maximum deviations of the actual cumulative frequency distribution curve from the crack uniform distribution cumulative frequency curve above and below is determined based on the distance-cumulative frequency diagram. The sum of these absolute values ​​is the crack spacing heterogeneity coefficient.

[0023] When the coefficient of variation of crack spacing is greater than 1 and the coefficient of heterogeneity of crack spacing is greater than 0, the crack-dense zone in the crack group is determined by using the local crack intensity distribution map and standardized local crack intensity data.

[0024] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for identifying dense crack zones.

[0025] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for identifying dense crack zones.

[0026] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for identifying dense crack zones.

[0027] In this embodiment of the invention, cracks are grouped by collecting relevant features of the cracks in the area to be identified, and crack density zones are identified for each group. During the identification process, crack development intensity data is acquired and corrected to obtain corrected data. Then, a distance-cumulative frequency map is plotted using the corrected data, the average crack spacing and the standard deviation of crack spacing (i.e., standardized local crack intensity data) are calculated, and a standardized local crack intensity distribution map is further plotted. The crack spacing variation coefficient and crack spacing heterogeneity coefficient are calculated. The relationship between the crack spacing variation coefficient and crack spacing heterogeneity coefficient and 1 and 0, respectively, is used to determine whether crack density zones exist in the group. Furthermore, the width and length of the crack density zones are determined using the local crack intensity distribution map and standardized local crack intensity data. Through the above method, crack density zones in each crack group can be quantitatively and accurately identified. Furthermore, the method in this embodiment of the invention has been applied and verified in the description of crack distribution patterns in outcrop areas and the determination of crack density zones, proving that the method is feasible and effective. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0029] Figure 1This is a flowchart illustrating a method for identifying densely cracked zones in an embodiment of the present invention.

[0030] Figure 2 This is a schematic diagram illustrating the measurement of crack development intensity data in an embodiment of the present invention;

[0031] Figure 3 This is a schematic diagram of a distance-cumulative frequency plot in an embodiment of the present invention;

[0032] Figure 4 This is a schematic diagram of a crack distribution bar graph in an embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram of the local crack intensity distribution map drawn in an embodiment of the present invention;

[0034] Figure 6 This is a superimposed display of the crack distribution bar chart, distance-cumulative frequency chart, and local crack intensity distribution chart in an embodiment of the present invention;

[0035] Figure 7 This is a schematic diagram of the process for quantitatively characterizing the crack distribution pattern in an embodiment of the present invention.

[0036] Figure 8 This is a schematic diagram showing the results of identifying densely cracked zones in an embodiment of the present invention;

[0037] Figure 9 This is a schematic diagram of the structure of a dense crack zone identification device according to an embodiment of the present invention;

[0038] Figure 10 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0040] To address the problems of existing technologies such as coarsening raw data, ignoring some crack information, and failing to accurately identify densely cracked zones, embodiments of the present invention provide a method for identifying densely cracked zones, such as... Figure 1 As shown, the method includes steps 101 to 108:

[0041] Step 101: Obtain crack-related features of the area to be identified.

[0042] Among them, crack-related features include crack surface morphology, crack filling characteristics, crack intersection relationship, crack orientation, and crack dip angle.

[0043] In this embodiment of the invention, a one-dimensional survey line method is used to collect crack-related features. Specifically, a one-dimensional survey line is arranged according to the crack exposure characteristics, ensuring that the survey line is as orthogonal as possible to the crack, and the relevant features of each crack intersecting the survey line are measured and recorded.

[0044] The advantages of this sampling method are: 1) Outcrops and core samples in the field are generally distributed in a near-linear manner, and the one-dimensional survey line method can obtain more fracture information; 2) The one-dimensional survey line method is convenient and efficient, especially the angle between the survey line and the fracture.

[0045] Step 102: Divide the cracks into groups based on their related characteristics. For each group of cracks, proceed with steps 103 to 108 as follows.

[0046] Specifically, existing methods can be used to classify the crack groups; the classification process will not be elaborated here.

[0047] Step 103: Obtain crack development intensity data, correct the crack development intensity data, and obtain corrected data.

[0048] Crack development intensity data includes the angle between the crack and the survey line (θ), the apparent distance between cracks (S′), and the apparent distance from the crack to the starting point of the survey line (d). i The apparent distance from the first to the Nth crack to the starting point of the survey line is d1′ to d′. N ′), total number of cracks intersecting the survey line (N), and apparent length of the survey line (L″).

[0049] Among them, see Figure 2 As shown, the angle (θ) between the crack and the survey line is measured using a geological compass or protractor; the apparent distance between cracks (S′) is the distance between two adjacent cracks along the survey line direction, i.e., the distance between the two intersection points of the two adjacent cracks and the survey line; the apparent distance (d) from the crack to the starting point of the survey line... i ′) is the distance from the intersection of the crack and the survey line to the starting point of the survey line; the apparent length of the survey line (L″) is the distance between the end point and the starting point of the survey line.

[0050] In this embodiment of the invention, the angular relationship between the root distance measuring line and the crack is used to correct the measured crack development intensity data. The apparent crack spacing, apparent measuring line length, and apparent distance from the crack to the starting point of the measuring line are corrected using the included angle of the measuring line, respectively, to obtain the crack spacing, measuring line length, and distance from the crack to the starting point of the measuring line; the crack spacing, measuring line length, distance from the crack to the starting point of the measuring line, included angle of the measuring line, and the total number of cracks intersecting with the measuring line are used as correction data.

[0051] Specifically, the distance between cracks, referred to as crack spacing (S), is the vertical distance between two adjacent cracks, equal to the product of the apparent crack spacing and the sine of the angle between the measuring line and the crack, i.e., S = S′sinθ; the true length of the measuring line, referred to as measuring line length (L′), is the length of the measuring line perpendicular to the crack direction, equal to the product of the apparent length of the measuring line and the sine of the angle between the measuring line and the crack, i.e., L′ = L″sinθ; the distance from the crack to the starting point of the measuring line (d) i The distance from the crack to the starting point of the survey line is equal to the product of the sine of the angle between the crack and the survey line, i.e., d. i =d i ′sinθ.

[0052] Step 104: Use the calibration data to plot the distance-cumulative frequency plot and calculate the average crack spacing and the standard deviation of crack spacing.

[0053] Compared to traditional bar charts, distance-cumulative frequency charts are more accurate and intuitive because they retain precise information about each crack and can reflect the contribution of each crack to the crack development intensity and distribution pattern.

[0054] The horizontal axis of the distance-cumulative frequency plot represents the standardized distance (distance from the crack to the starting point of the survey line (d)). i After standardization, the distance-cumulative frequency plot is obtained, with the ordinate representing the standardized cumulative frequency (obtained after standardizing the cumulative crack count). To eliminate the influence of crack spacing not being measured at the end of the survey line, the distance-cumulative frequency plot starts from the first crack intersecting the survey line, but this crack is not counted, i.e., the coordinates of this point are (0,0). Then, the counting starts from the second crack intersecting the survey line, so its coordinates are ((d2-d1),1). The count of the i-th crack intersecting the survey line is i-1, with coordinates ((d2-d1),1). i -d1),(i-1)), where d i This is the distance from the starting point of the survey line to the i-th crack, ending at the last crack intersecting the survey line, with coordinates ((d N -d1),(N-1)). In the distance-cumulative frequency map, the crack development intensity is equal to the slope of the cumulative frequency curve. To facilitate the comparison of crack distribution patterns between survey lines of different regions and lengths, the distance-cumulative frequency map needs to be standardized. After standardization, the coordinates of the i-th crack intersecting with the survey line are ((d1),(N-1)). i -d1) / (d N -d1),(i-1) / (N-1)).

[0055] For example, Figure 3 A schematic diagram of the distance-cumulative frequency plot is given.

[0056] In addition to distance-cumulative frequency plots, bar charts of crack distribution can also be drawn; see [link to relevant documentation]. Figure 4The image shown is a schematic diagram of the crack distribution in bar graphs. Figure 4 Each bar in the diagram represents a crack, visually illustrating where cracks are abundant and scarce. Using a bar graph to display the distribution characteristics of crack development intensity provides a visually intuitive understanding of crack distribution patterns.

[0057] The average development intensity of cracks can be expressed as the average crack spacing ( <s>It can be expressed as the average linear density of cracks (I). The average linear density of cracks is inversely related to the average crack spacing, I = 1 / <s>The average crack spacing refers to the average of all crack spacings or the ratio of the measuring line length to the total number of cracks; the average crack linear density refers to the ratio of the total number of cracks to the measuring line length. To eliminate the influence of missing crack spacing at the end of the measuring line, the measuring line length is corrected to the distance between the first crack and the Nth crack (L = d). N -d1), the total number of cracks is corrected to the original total number of cracks minus 1 (i.e., N-1), and then the average crack spacing <S> is calculated using the following formula:

[0058]

[0059] The average linear density of cracks, I, is:

[0060]

[0061] After calculating the average crack spacing, the standard deviation σ of the crack spacing can also be calculated using the following formula. S :

[0062]

[0063] Among them, S i Let d be the crack spacing of the i-th crack. N d1 is the distance of the Nth crack from the starting point of the survey line, d1 is the distance of the 1st crack from the starting point of the survey line, and N is the total number of cracks.

[0064] Step 105: Calculate standardized local crack strength data using the correction data, and draw a local crack strength distribution map based on the standardized local crack strength data.

[0065] Local crack strength (I) i The local crack strength refers to the crack development intensity at a given crack location, obtained through the distance between the crack and two adjacent cracks. In other words, the local crack strength is equal to half the sum of the distances between the crack and the preceding and following cracks.

[0066]

[0067] In the formula, I i Let ΔS be the local crack strength at the i-th crack. i d represents the average spacing occupied by the i-th crack. i+1 Let d be the distance from the (i+1)th crack to the starting point of the survey line. i-1 This represents the distance of the (i-1)th crack from the starting point of the survey line.

[0068] To facilitate comparison of crack distribution patterns across different regions and survey lines of varying lengths, the local crack strength can be standardized. The standardized local crack strength is as follows:

[0069]

[0070] In the formula, %I i Let d be the normalized local crack strength of the i-th crack. N d1 is the distance of the Nth crack from the starting point of the survey line, d1 is the distance of the 1st crack from the starting point of the survey line, and N is the total number of cracks.

[0071] For example, if N = 100, then %I1, %I2, %I3, ..., %I can be calculated. 100 .

[0072] In this embodiment of the invention, a local crack intensity distribution map is plotted using standardized local crack intensity as the ordinate and standardized distance as the abscissa, based on the standardized local crack intensity data of cracks 1 to N. For example, the plotted local crack intensity distribution map is as follows: Figure 5 As shown. Among them, Figure 5 The standardized crack strength indicated by the vertical axis is the standardized local crack strength.

[0073] Step 106: Calculate the coefficient of variation of crack spacing based on the standard deviation of crack spacing and the average crack spacing.

[0074] In this embodiment of the invention, the crack spacing variation coefficient (C) is utilized. V The crack spacing distribution characteristics are characterized by the coefficient of variation of crack spacing (σ). S The ratio of the crack spacing to the average crack distance (<S>):

[0075]

[0076] Among them, C V =0 indicates that the crack spacing is uniform; 0 < C V <1 indicates that the crack spacing is relatively uniform; C V ≈1 indicates that the crack spacing follows a negative exponential function distribution; C V >1 indicates that the crack spacing is irregularly distributed, with a dense distribution of cracks; C V >>1 indicates that a small number of cracks have abnormally large spacing, and the crack spacing follows a power-law distribution.

[0077] Step 107: Determine the sum of the absolute values ​​of the maximum deviations of the actual cumulative frequency distribution curve from the crack uniform distribution cumulative frequency curve above and below the distance-cumulative frequency diagram. The sum of absolute values ​​is the crack spacing heterogeneity coefficient.

[0078] See Figure 6 As shown, the dashed line connecting the coordinate points (0,0) and (100%, 100%) represents the cumulative frequency curve of the uniform crack distribution, while the thick line connecting (0,0) and (100%, 100%) represents the actual cumulative frequency distribution curve. Figure 6 As can be seen, the actual cumulative frequency distribution curve does not coincide with the cumulative frequency curve of the uniform distribution of cracks. D+ represents the maximum deviation of the actual cumulative frequency distribution curve from the cumulative frequency curve of the uniform distribution of cracks above, and D- represents the maximum deviation of the actual cumulative frequency distribution curve from the cumulative frequency curve of the uniform distribution of cracks below.

[0079] The crack spacing heterogeneity coefficient (V) is equal to the sum of the absolute values ​​of the maximum deviations of the cumulative frequency distribution curve from the cumulative frequency curve of a uniform crack distribution above and below:

[0080] V = |D+|+|D-|

[0081] Where |D+| and |D-| represent the absolute values ​​of the maximum deviations of the actual cumulative frequency distribution curve from the cumulative frequency curve of the uniform distribution of cracks, respectively.

[0082] The larger the crack spacing heterogeneity coefficient V, the stronger the heterogeneity of the crack spacing distribution. V=0 represents a uniform crack spacing distribution, while V=1 represents a highly non-uniform crack spacing distribution.

[0083] The data and maps obtained in the above steps can be used to quantitatively characterize the crack distribution pattern. For details, please refer to [link / reference needed]. Figure 7 As shown. First, see Figure 6 As shown, the crack distribution pattern can be visually understood from the crack distribution bar chart, distance-cumulative frequency chart, and local crack intensity distribution chart. Then, the crack distribution pattern is quantitatively determined based on the crack spacing variation coefficient and crack spacing heterogeneity coefficient. When C... V → When C = 0 and V ≈ 0, the crack spacing is uniformly distributed; when C V ≈1, when V→0, the crack spacing is randomly distributed; when C V >1. When V>0, the crack spacing is unevenly distributed, and there are densely cracked zones; when C V >>1. When V→1, the crack spacing distribution is extremely uneven and follows a power-law distribution.

[0084] Step 108: When the crack spacing variation coefficient is greater than 1 and the crack spacing heterogeneity coefficient is greater than 0, the crack density zone in this group of cracks is determined by using the local crack intensity distribution map and standardized local crack intensity data.

[0085] A zone of dense cracks is defined as a localized crack intensity greater than twice the normalized average crack development intensity, and its duration exceeding 5% of the survey line length. The normalized average crack development intensity is calculated based on the normalized local crack intensity data.

[0086]

[0087] Plot a line on the local crack intensity distribution map whose vertical axis is equal to twice the normalized average crack development intensity. Horizontal line, see Figure 8 As shown. Figure 8 The horizontal line marked with twice the average crack strength represents twice the normalized average crack development strength. The horizontal line. On the local crack strength curve, find data points from left to right where the local crack strength is greater than twice the normalized average crack development strength, and record the coordinate value (%L) of these points. i ,%I i Continue searching to the right for data points where the local crack strength is less than twice the average development strength of the standardized cracks, and record the coordinates of these points (%L). j-1 ,%I j-1 If %L j-1 -%L i If the crack width is ≥5%, then the area between the i-th crack and the (j-1)-th crack is a dense crack zone, and the width of the dense crack zone is L × (%L) j-1 -%L i If %L j-1 -%L i If the fracture density is less than 5%, then there is no densely populated fracture zone. Using this method, we can identify potentially densely populated fracture zones sequentially to the right until the survey line ends.

[0088] In this embodiment of the invention, cracks are grouped by collecting relevant features of the cracks in the area to be identified, and crack density zones are identified for each group. During the identification process, crack development intensity data is acquired and corrected to obtain corrected data. Then, a distance-cumulative frequency map is plotted using the corrected data, the average crack spacing and the standard deviation of crack spacing (i.e., standardized local crack intensity data) are calculated, and a standardized local crack intensity distribution map is further plotted. The crack spacing variation coefficient and crack spacing heterogeneity coefficient are calculated. The relationship between the crack spacing variation coefficient and crack spacing heterogeneity coefficient and 1 and 0, respectively, is used to determine whether crack density zones exist in the group. Furthermore, the width and length of the crack density zones are determined using the local crack intensity distribution map and standardized local crack intensity data. Through the above method, crack density zones in each crack group can be quantitatively and accurately identified. Furthermore, the method in this embodiment of the invention has been applied and verified in the description of crack distribution patterns in outcrop areas and the determination of crack density zones, proving that the method is feasible and effective.

[0089] To more clearly illustrate the implementation process of this invention, the following will use the "Ahe Formation tight sandstone reservoir in the Kuqa foreland basin" as a case study to identify fracture-dense zones. The outcrop in this case is located in the Tugerming section in the eastern part of the Kuqa foreland basin, exposing a medium-thick Ahe Formation sandstone stratum. This stratum is uncovered by vegetation and has excellent exposure. Due to its tight lithology and intense tectonic activity, fractures are highly developed, providing excellent material for quantitative characterization of fracture distribution patterns and research on fracture-dense zones.

[0090] Implementation process:

[0091] (1) Collection of information related to cracks

[0092] One-dimensional survey line method was used to collect crack-related information. The survey line was made as orthogonal as possible to the crack. The relevant information of each crack intersecting with the survey line was measured and recorded, including crack surface morphology, crack filling characteristics, crack intersection relationship, crack direction, and crack dip angle.

[0093] (2) Classification of crack orientation and grouping

[0094] Based on the crack surface morphology, crack filling characteristics, crack intersection relationship, crack direction and crack dip angle, the crack system was divided into crack groups. Two crack groups were developed in the study area, namely NNE-SSW and NW-SE, with NNE-SSW cracks being the main type. This case mainly analyzed the distribution pattern and crack density zone of this crack group.

[0095] (3) Measurement of crack development strength data

[0096] Based on the measurements of the outcrop area, the apparent length of the measuring line is 32.5m, the azimuth of the measuring line is 100°, the average direction of the crack is 20°, the angle between the crack and the measuring line is 80°, and a total of 112 cracks intersecting the measuring line were measured. At the same time, the apparent spacing between cracks was measured at 111 points, and the apparent distance between cracks and the starting point of the measuring line was measured at 112 points.

[0097] (4) Correction of crack development strength data

[0098] Based on the angular relationship between the survey line and the cracks, the measured data related to crack development intensity were corrected. After correction, the survey line length was 32.01m, and the corrected crack spacing was 111, with a crack distance of 112 from the starting point of the survey line.

[0099] (5) Calculation of average crack development strength

[0100] The average crack development intensity is calculated using the correction data obtained in step (4). The average crack development intensity is expressed as the average crack spacing ( <s>The crack length is expressed as the average linear density of cracks (I). To eliminate the influence of missing crack spacing at the end of the measuring line, the measuring line length is corrected to the distance between the first crack and the Nth crack (L = d). N -d1), the total number of cracks is corrected to the original total number of cracks minus 1 (N-1), and then the average crack development intensity is calculated. The calculation results are as follows:

[0101] <s>=0.29m

[0102] I=1 / <s>= (N-1) / (d) N -d1) = 3.47 lines / m

[0103] (6) Quantitative characterization of crack development intensity and distribution pattern: Using calibration data, the crack development intensity and distribution pattern are quantitatively characterized. The relevant maps, calculation data, and main steps required are as follows:

[0104] 1) Draw a bar chart of crack distribution: A bar chart is used to display the distribution characteristics of crack development intensity, providing a visually intuitive understanding of the crack distribution pattern (see the bar chart example). Figure 4 (As shown).

[0105] 2) Plotting the distance-cumulative frequency map: Plot the distance-cumulative frequency map using the corrected crack correlation data (see [link to distance-cumulative frequency map]). Figure 3 (As shown).

[0106] 3) Calculation and standardization of local crack strength: Local crack strength (I i The local crack strength refers to the crack development intensity at a given crack location, obtained through the distance between the crack and two adjacent cracks. In other words, the local crack strength is equal to half the sum of the distances between the crack and the preceding and following cracks.

[0107]

[0108] To facilitate comparison of crack distribution patterns across different regions and survey lines of varying lengths, the local crack strength can be standardized. The standardized local crack strength is as follows:

[0109]

[0110] The standardized local crack strength was calculated at a total of 110 crack locations.

[0111] 4) Draw a local crack intensity distribution map: Use the calculated standardized local crack intensity to draw a local crack intensity distribution map. The horizontal axis represents the standardized distance, and the vertical axis represents the standardized local crack intensity (see [link to local crack intensity distribution map]). Figure 5 (As shown).

[0112] 5) Crack Spacing Distribution Characteristics Analysis: Crack spacing distribution analysis was performed using crack spacing data. The coefficient of variation (CV) of crack spacing was used to characterize the crack spacing distribution characteristics. The CV is the ratio of the standard deviation of crack spacing to the average crack spacing, and was calculated to be 1.65.

[0113] 6) Calculation of crack spacing heterogeneity coefficient: The crack spacing heterogeneity coefficient (V) is calculated based on the distance-cumulative frequency plot. It is equal to the sum of the absolute values ​​of the maximum deviations of the cumulative frequency distribution curve from the cumulative frequency curve of the uniform crack distribution above and below (see...). Figure 6 V = |D+|+|D-| = 0.45.

[0114] 7) Quantitative characterization of crack distribution patterns: First, the crack distribution patterns are visually understood through crack distribution bar charts, distance-cumulative frequency charts, and local crack intensity distribution maps (see...). Figure 8 Then, the crack spacing variation coefficient and crack spacing heterogeneity coefficient were used to quantitatively determine the crack distribution pattern (see...). Figure 7 (Flowchart), where C V =1.65>1, V=0.45>0, indicating that the crack spacing is uneven and there is a dense crack zone.

[0115] (7) Determination of the location and width of the dense crack zone

[0116] A zone of dense cracks is defined as a localized crack intensity greater than twice the normalized average crack development intensity, and its duration exceeding 5% of the survey line length. A horizontal line with a vertical axis equal to twice the normalized average crack development intensity is plotted on the localized crack intensity distribution map (see [reference]). Figure 8 On the local crack strength curve, data points with local crack strength greater than twice the normalized average crack development strength are found from left to right, and their coordinates (18%, 2.1) are recorded. Continuing to the right, data points with local crack strength less than twice the normalized average crack development strength are found, and their coordinates (31%, 1.9) are recorded. 31% - 18% = 13% > 5%, therefore this interval is a crack-dense zone, and the width of the crack-dense zone is equal to 32.01 * 13% = 4.16 m. Using this method, possible crack-dense zones are identified sequentially to the right until the survey line ends. One crack-dense zone was identified along this survey line.

[0117] As can be seen from the above implementation process, the method in the embodiments of the present invention has been applied and verified in the description of the distribution law of cracks in the outcrop area and the identification of the crack dense zone. The application results show that the method can not only visually reflect the distribution law of cracks, but also quantitatively characterize the aggregation and dispersion of cracks, and accurately determine the range of the crack dense zone. The results prove that the method is feasible and effective.

[0118] This invention also provides a device for identifying densely cracked zones, as described in the following embodiments. Since the principle behind this device is similar to that of the method for identifying densely cracked zones, its implementation can be found in the implementation of the method for identifying densely cracked zones; repeated details will not be elaborated further.

[0119] like Figure 9 As shown, the device 900 includes an acquisition module 901, a group division module 902, and a determination module 903.

[0120] The acquisition module 901 is used to acquire crack-related features of the area to be identified. The crack-related features include crack surface morphology features, crack filling features, crack intersection relationships, crack orientation, and crack dip angle.

[0121] The crack grouping module 902 is used to group cracks according to their related characteristics. For each crack group, the determination module 903 performs the following method:

[0122] Acquire crack development intensity data, correct the crack development intensity data, and obtain corrected data;

[0123] Using the corrected data, a distance-cumulative frequency plot was drawn, and the mean crack spacing and standard deviation of crack spacing were calculated.

[0124] Standardized local crack strength data are calculated using the calibration data, and a local crack strength distribution map is drawn based on the standardized local crack strength data.

[0125] The coefficient of variation of crack spacing is calculated based on the standard deviation of crack spacing and the average crack spacing.

[0126] The sum of the absolute values ​​of the maximum deviations of the actual cumulative frequency distribution curve from the crack uniform distribution cumulative frequency curve above and below is determined based on the distance-cumulative frequency diagram. The sum of the absolute values ​​is the crack spacing heterogeneity coefficient.

[0127] When the coefficient of variation of crack spacing is greater than 1 and the coefficient of heterogeneity of crack spacing is greater than 0, the crack-dense zone in the crack group is determined by using the local crack intensity distribution map and standardized local crack intensity data.

[0128] In one implementation of this invention, the determining module 903 is used for:

[0129] Obtain the angle between the crack and the survey line, the apparent spacing between cracks, the apparent distance of the crack from the starting point of the survey line, the total number of cracks intersecting with the survey line, and the apparent length of the survey line;

[0130] The crack spacing, the apparent length of the measuring line, and the apparent distance from the crack to the starting point of the measuring line are corrected by using the included angle of the measuring line, and the crack spacing, the measuring line length, and the distance from the crack to the starting point of the measuring line are obtained respectively.

[0131] The crack spacing, survey line length, distance of cracks from the starting point of the survey line, angle of the survey line, and total number of cracks intersecting with the survey line are used as correction data.

[0132] In one implementation of this invention, the determining module 903 is used for:

[0133] The product of the apparent crack spacing and the sine of the angle between the survey line and the crack spacing is determined as the crack spacing.

[0134] The product of the apparent length of the survey line and the sine of the angle between the survey lines is determined as the length of the survey line.

[0135] The distance from the crack to the starting point of the survey line is determined by multiplying the apparent distance of the crack from the starting point of the survey line by the sine of the angle between the crack and the survey line.

[0136] In one implementation of this invention, the determining module 903 is used for:

[0137] according to Calculate the average crack spacing <S>;

[0138] Calculate the standard deviation of crack spacing based on crack spacing and average crack spacing;

[0139] Where, d N d1 is the distance of the Nth crack from the starting point of the survey line, d1 is the distance of the 1st crack from the starting point of the survey line, and N is the total number of cracks.

[0140] In one implementation of this invention, the determining module 903 is used for:

[0141] Calculate the average linear density of cracks based on the average crack spacing;

[0142] Calculate the local crack strength at the i-th crack based on the distances of the (i+1)-th crack from the starting point of the measuring line and the distances of the (i-1)-th crack from the starting point of the measuring line.

[0143] Based on the local crack strength and average linear density of the crack at the i-th crack, the standardized local crack strength of the i-th crack is calculated, and the standardized local crack strength data of the 1st to Nth cracks are obtained.

[0144] Using standardized local crack intensity as the ordinate and standardized distance as the abscissa, a local crack intensity distribution map is drawn using the standardized local crack intensity data of cracks 1 to N.

[0145] In one implementation of this invention, the determining module 903 is further configured to:

[0146] according to Calculate the average linear density I of the cracks;

[0147] according to Calculate the local crack strength I at the i-th crack. i ;

[0148] According to %I i =I i / I Calculate the normalized local crack strength % of the i-th crack. i ;

[0149] Where, ΔS i d represents the average spacing occupied by the i-th crack. i+1 Let d be the distance from the (i+1)th crack to the starting point of the survey line. i-1 This represents the distance of the (i-1)th crack from the starting point of the survey line.

[0150] In one implementation of this invention, the determining module 903 is used for:

[0151] The average development intensity of standardized cracks is calculated based on standardized local crack intensity data.

[0152] On the local crack intensity distribution map, draw a horizontal line with a vertical coordinate equal to twice the average development intensity of the standardized cracks. Read the points with the vertical coordinate on the horizontal line. If the vertical coordinate is on the horizontal line and the difference in the horizontal coordinate between the first and last consecutive points is greater than or equal to 5%, then the area where the consecutive points are located is determined as the crack-dense zone.

[0153] In this embodiment of the invention, cracks are grouped by collecting relevant features of the cracks in the area to be identified, and crack density zones are identified for each group. During the identification process, crack development intensity data is acquired and corrected to obtain corrected data. Then, a distance-cumulative frequency map is plotted using the corrected data, the average crack spacing and the standard deviation of crack spacing (i.e., standardized local crack intensity data) are calculated, and a standardized local crack intensity distribution map is further plotted. The crack spacing variation coefficient and crack spacing heterogeneity coefficient are calculated. The relationship between the crack spacing variation coefficient and crack spacing heterogeneity coefficient and 1 and 0, respectively, is used to determine whether crack density zones exist in the group. Furthermore, the width and length of the crack density zones are determined using the local crack intensity distribution map and standardized local crack intensity data. Through the above method, crack density zones in each crack group can be quantitatively and accurately identified. Furthermore, the method in this embodiment of the invention has been applied and verified in the description of crack distribution patterns in outcrop areas and the determination of crack density zones, proving that the method is feasible and effective.

[0154] This invention also provides a computer device. Figure 10 This is a schematic diagram of a computer device in an embodiment of the present invention. This computer device is capable of implementing all steps in the dense crack zone identification method described in the above embodiments. Specifically, the computer device includes the following components:

[0155] Processor 1001, memory 1002, communications interface 1003, and communication bus 1004;

[0156] The processor 1001, memory 1002, and communication interface 1003 communicate with each other through the communication bus 1004; the communication interface 1003 is used to realize information transmission between related devices.

[0157] The processor 1001 is used to call the computer program in the memory 1002, and when the processor executes the computer program, it implements the crack dense zone identification method in the above embodiment.

[0158] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for identifying dense crack zones.

[0159] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for identifying dense crack zones.

[0160] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0161] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0162] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0163] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0164] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.< / s> < / s> < / s> < / s> < / s>

Claims

1. A method for identifying densely cracked zones, characterized in that, The method comprises: Obtaining crack-related features of a region to be identified, the crack-related features including crack surface morphology features, crack filling features, crack intersection relationships, crack trends and crack dip angles; According to the crack-related features, the cracks are classified into groups, and for each group of cracks, the following method is performed: Obtaining crack development intensity data, correcting the crack development intensity data to obtain corrected data; Using the corrected data to draw a distance-cumulative frequency graph and calculate the average crack spacing and crack spacing standard deviation; Using the corrected data to calculate normalized local crack intensity data and draw a local crack intensity distribution map according to the normalized local crack intensity data; According to the crack spacing standard deviation and the average crack spacing, the crack spacing variation coefficient is calculated; According to the distance-cumulative frequency graph, the sum of the absolute values of the maximum deviations of the actual cumulative frequency distribution curve from the crack uniform distribution cumulative frequency curve is determined, and the sum of the absolute values is the crack spacing heterogeneity coefficient; When the crack spacing variation coefficient is greater than 1 and the crack spacing heterogeneity coefficient is greater than 0, the local crack intensity distribution map and the normalized local crack intensity data are used to determine the crack dense zone in the group of cracks.

2. The method of claim 1, wherein, Obtaining crack development intensity data, correcting the crack development intensity data to obtain corrected data, comprising: Obtaining the line angle between the cracks and the survey line, the apparent crack spacing, the apparent distance from the crack to the survey line starting point, the total number of cracks intersecting the survey line, and the apparent length of the survey line; Using the line angle to correct the apparent crack spacing, the apparent length of the survey line and the apparent distance from the crack to the survey line starting point to obtain the crack spacing, the length of the survey line and the distance from the crack to the survey line starting point, respectively; The crack spacing, the length of the survey line, the distance from the crack to the survey line starting point, the line angle and the total number of cracks intersecting the survey line are used as the corrected data.

3. The method of claim 2, wherein, Using the line angle to correct the apparent crack spacing, the apparent length of the survey line and the apparent distance from the crack to the survey line starting point to obtain the crack spacing, the length of the survey line and the distance from the crack to the survey line starting point, respectively, comprising: The product of the apparent crack spacing and the sine value of the line angle is determined as the crack spacing; The product of the apparent length of the survey line and the sine value of the line angle is determined as the length of the survey line; The product of the apparent distance from the crack to the survey line starting point and the sine value of the line angle is determined as the distance from the crack to the survey line starting point.

4. The method according to claim 2 or 3, characterized in that, Using the corrected data to calculate the average crack spacing and the crack spacing standard deviation, comprising: According to The average distance between cracks <S> is calculated; According to the crack spacing and the average crack spacing, the crack spacing standard deviation is calculated; wherein d N is the distance of the Nth crack from the start of the line, d1 is the distance of the 1st crack from the start of the line, and N is the total number of cracks.

5. The method of claim 4, wherein, Using the corrected data to calculate the normalized local crack intensity data and drawing a local crack intensity distribution map according to the normalized local crack intensity data, comprising: According to the average crack spacing, the average line density of the cracks is calculated; According to the distance from the i-th crack to the survey line starting point and the distance from the i-1-th crack to the survey line starting point, the local crack intensity at the i-th crack is calculated; According to the local crack intensity at the i-th crack and the average line density of the cracks, the normalized local crack intensity of the i-th crack is calculated, and the normalized local crack intensity data of the first to N-th cracks is obtained; Using the normalized local crack intensity data of the first to N-th cracks, a local crack intensity distribution map is drawn with the normalized local crack intensity as the vertical coordinate and the normalized distance as the horizontal coordinate.

6. The method of claim 5, wherein, The method further comprises: According to the average line density of the cracks I is calculated; According to The local crack intensity I at the i-th crack is calculated i ; According to %I i = I i / I calculates the normalized local crack intensity %I of the ith crack i ; where ΔS i is the average spacing of the i-th fracture, d i+1 is the distance of the i+1-th fracture from the start of the survey line, d i-1 is the distance of the i-1-th fracture from the start of the survey line.

7. The method of claim 1, wherein, determining a fracture dense zone in the group of fractures by using the local fracture intensity distribution map and the normalized local fracture intensity data, comprising: calculating a normalized fracture average development intensity according to the normalized local fracture intensity data; drawing a horizontal line with a vertical coordinate equal to 2 times the normalized fracture average development intensity on the local fracture intensity distribution map, reading the points with the vertical coordinate on the horizontal line, and determining the region of the continuous points as the fracture dense zone if the vertical coordinate is on the horizontal line and the horizontal coordinate difference between the first and last points is greater than or equal to 5%.

8. A fracture intensity zone identification apparatus, characterized by, The device comprises: an acquisition module configured to acquire fracture-related features of a region to be identified, the fracture-related features comprising fracture surface morphology features, fracture filling features, fracture intersection relationships, fracture strikes, and fracture dips; a group division module configured to divide fractures into groups according to the fracture-related features, and for each group of fractures, the determining module performs the following method: acquiring fracture development intensity data, correcting the fracture development intensity data to obtain corrected data; drawing a distance-cumulative frequency graph by using the corrected data, and calculating a fracture average spacing and a fracture spacing standard deviation; calculating normalized local fracture intensity data by using the corrected data, and drawing a local fracture intensity distribution map according to the normalized local fracture intensity data; calculating a fracture spacing variation coefficient according to the fracture spacing standard deviation and the fracture average spacing; determining the sum of absolute values of the maximum deviation of the actual cumulative frequency distribution curve from the fracture uniform distribution cumulative frequency curve according to the distance-cumulative frequency graph, and the sum of absolute values is a fracture spacing heterogeneity coefficient; when the fracture spacing variation coefficient is greater than 1 and the fracture spacing heterogeneity coefficient is greater than 0, determining a fracture dense zone in the group of fractures by using the local fracture intensity distribution map and the normalized local fracture intensity data.

9. The apparatus of claim 8, wherein, The determining module is configured to: acquire a survey line included angle between a fracture and a survey line, a fracture apparent spacing, a fracture distance from a survey line starting point, a total number of fractures intersecting the survey line, and a survey line apparent length; correct the fracture apparent spacing, the survey line apparent length, and the fracture distance from the survey line starting point by using the survey line included angle to obtain a fracture spacing, a survey line length, and a fracture distance from the survey line starting point, respectively; use the fracture spacing, the survey line length, the fracture distance from the survey line starting point, the survey line included angle, and the total number of fractures intersecting the survey line as corrected data.

10. The apparatus of claim 9, wherein, The determining module is configured to: determine the product of the fracture apparent spacing and the sine value of the survey line included angle as the fracture spacing; determine the product of the survey line apparent length and the sine value of the survey line included angle as the survey line length; determine the product of the fracture distance from the survey line starting point and the sine value of the survey line included angle as the fracture distance from the survey line starting point.

11. The apparatus of claim 9 or 10, wherein, The determining module is configured to: According to The average distance between cracks <S> is calculated; calculate a fracture spacing standard deviation according to the fracture spacing and the fracture average spacing; wherein d N is the distance of the Nth fracture from the start of the line, d1 is the distance of the 1st fracture from the start of the line, and N is the total number of fractures.

12. The apparatus of claim 11, wherein, The determining module is configured to: calculate a fracture average line density according to the fracture average spacing; calculate a local fracture intensity at the i-th fracture according to the fracture distance from the survey line starting point of the i+1-th fracture and the distance from the survey line starting point of the i-1-th fracture; calculate a normalized local fracture intensity of the i-th fracture according to the local fracture intensity at the i-th fracture and the fracture average line density, to obtain normalized local fracture intensity data of the first to N-th fractures; A local fracture intensity distribution graph is drawn using the normalized local fracture intensity data of the first to N fractures, with the normalized local fracture intensity as the ordinate and the normalized distance as the abscissa.

13. The apparatus of claim 12, wherein, The determining module is further configured to: According to the average line density of the cracks I is calculated; According to The local crack intensity I at the i-th crack is calculated i ; According to %I i = I i / I calculates the normalized local crack intensity %I of the ith crack i ; where ΔS i is the average spacing of the ith fracture, d i+1 is the distance of the ith+1 fracture from the start of the survey line, d i-1 is the distance of the ith-1 fracture from the start of the survey line.

14. The apparatus of claim 8, wherein, The determining module is configured to: The normalized average fracture development intensity is calculated according to the normalized local fracture intensity data. A horizontal line with an ordinate equal to 2 times the normalized average fracture development intensity is drawn on the local fracture intensity distribution graph, and points with the ordinate on the horizontal line are read; if the ordinate is on the horizontal line and the difference between the abscissa of the first point and the last point is greater than or equal to 5%, a region in which the points are located is determined as a fracture dense zone.

15. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the method in any of claims 1 to 7 when executing the computer program.

16. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method in any of claims 1 to 7.

17. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to implement the method in any of claims 1 to 7.

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