CN104866856B - Imaging logging image solution cavity information pickup method based on connected domain equivalence to processing - Google Patents
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Abstract
The invention discloses a kind of pick-up method of solution cavity information in imaging logging image based on of equal value pair of connected domain, belong to the pickup field of solution cavity information in imaging logging image, including following methods：A. the imaging logging image corrosion hole connected domain quantitative mark based on equivalence to processing, the parameter information of each connected domain, including the length of connected domain and width, connected domain circumradius, inscribed circle radius, circularity and sorting coefficient are picked up；B. the corrosion hole development degree based on the reflection of Areal porosity curve is layered to imaging logging image.Beneficial effects of the present invention are as follows：Had based on equivalence to the image connectivity field mark algorithm of processing it is quick, not repeating label the advantages of, utilize the algorithm, corrosion hole connected domain can be accurately marked from bianry image, and then target information pickup is carried out to each connected domain, including bore hole size, sorting coefficient, connected domain area (Areal porosity), circularity etc..
Description
Technical field
The invention belongs to the pickup field of solution cavity information in imaging logging image, and in particular to one kind is of equal value based on connected domain
To the imaging logging image solution cavity information pickup method of processing.
Background technology
1. abbreviation and Key Term definition
1.1 connected domain：Refer to the set being made up of several pixels, the pixel in the set has following characteristic：It is all
The grey level of pixel is respectively less than or equal to connected domain rank；Pixel in same connected domain communicates two-by-two, i.e., any two
A path being made up of completely the element of this set between individual pixel be present.
1.2 is of equal value right：Due to the influence of solution cavity form and scanning sequency, cause to start to be considered two disconnected areas
Domain, with going deep into for mark scan process, it is found that they actually belong to same connected region, this phenomenon can be claimed
It is equivalence to phenomenon.
As can be seen that when being scanned mark to figure, it is of equal value right that boxed area can produce, as shown in Figure 1.It is white in figure
Actual region is same connected region, but because the influence of scanning sequency and labeling algorithm, this region are marked as ' 8 '
' 14 ' two connected domains, as shown in Fig. 2 here it is equivalence to phenomenon.
1.3 Areal porosity：Solution cavity area accounts for the percentage of whole image area in image.
2. relevant knowledge introduction：
2.1 stratum micro-resisitivity images (FMI) are using multiple rows of button shape small electrode on multi-electrode to the borehole wall
Stratum emission current, due to the difference of the rock composition of electrode contact, structure and contained fluid, thus cause the change of electric current,
The change of electric current reflects the change of the rock resistivity of the borehole wall everywhere, can show the borehole wall imaging of resistivity accordingly.Image
From white (high resistance) to yellow, then to black (low resistance), the deeper resistivity of color is lower (as shown in Figure 4), four in figure
White ribbon is the white space that instrument is not covered with, and black curve is borehole wall crack, and black splotch is corrosion hole.
The connected domain of 2.2 images, it is exactly the reachability problem between pixel in fact.Target pixel points are assumed in two dimensional image
Its pixel value of the pixel adjacent with surrounding is identical, then claims the two pixels to connect.Needed first when studying connective
Determine neighborhood connection rule for the connection of 4 neighborhoods or the connection of 8 neighborhoods.4 neighborhoods connection be concerned with target pixel points it is upper and lower,
Left and right 4 location points (Fig. 5).Object pixel adjacent picture all in 3*3 matrixes in two-dimensional space is then chosen in the connection of 8 neighborhoods
Vegetarian refreshments, i.e., in addition to the point of upper and lower, left and right, in addition to upper left, upper right, lower-left, the location point (Fig. 6) of bottom right 4, calculation of the invention
Method is using 8 neighborhoods connection rule.
3. prior art introduction：
Crack information intelligent pick-up method (Yan Jianping 2009) in 3.1 imaging logging images
Imaging logging data can obtain the high-resolution image of the full borehole wall after processing, and the intersection of fracture surface and pit shaft exists
Morphological feature on image is rendered as monocyclic sine curve, using the point of hough transform --- in line duality captured image
The information such as crack angle, can obtain preferable result, can preferably be picked up for information such as the angle in crack, initial phases
Take, as shown in Figure 8.
Although this method can be very good to have picked up crack information, solution cavity information have ignored.And sent out in solution cavity
Educate and very not applicable in the less stratum in crack.
The 3.2 solution cavity automatic testing methods (field inscription on ancient bronze objects 1999) based on bottom hole path image
This method carries out solution cavity rim detection using Roberts operators, and side is carried out with the method based on directivity curve
Edge tracks and refinement, so as to realize automatically extracting and quantitatively calculating for solution cavity.This method is by extracting characteristic point, tracking obtains spy
Sign point direction sequence simultaneously carries out solution cavity differentiation using its corresponding directivity curve.Its algorithm amount of calculation is less, and judgement speed is fast,
With good real-time treatability and adaptability, as shown in Figure 10.
Although this method can preferably identify solution cavity, the detection identification to solution cavity is also only limitted to, for solution cavity
Relevant information can not extract, so as to can not further to solution cavity develop stratum evaluating reservoir provide data support.
The content of the invention
In view of the deficiencies of the prior art, the present invention provides a kind of imaging logging image based on connected domain equivalence to processing
Solution cavity information pickup method, although can effectively solve because of nonrecognition solution cavity information or can identify that not extracting solution cavity believes
Breath and caused by can not to solution cavity develop stratum evaluating reservoir provide data support the problem of.
To solve problem above, the technical solution adopted by the present invention is as follows：It is a kind of based on connected domain equivalence to processing into
Picture log comprises the following steps as solution cavity information pickup method：
A. the imaging logging image corrosion hole connected domain quantitative mark based on equivalence to processing, picks up each connected domain
Parameter information, including the length of connected domain and width, connected domain circumradius, inscribed circle radius, circularity and sorting coefficient；
B. the corrosion hole development degree based on the reflection of Areal porosity curve is layered to imaging logging image, then to every
Number, the distribution of connected domain sorting coefficient, circularity distribution, inscribed circle and the circumradius of one layer of statistics connected domain are distributed non-equal
Matter information.
Preferably, A specifically includes following steps：
1.1 image preprocessing：Gray processing processing is carried out to original image first, obtains gray level image；After gray processing processing,
Median filter process is carried out to image；Then row threshold division is entered to filtered image, obtains binary image；
1.2 connected component labelings, information pickup：First with the image connectivity field mark algorithm based on of equal value pair to binary map
As carry out connected component labeling processing, image after mark, at the same to mark image in each connected domain pick up its length and width,
The parameter information of inscribed circle radius, circumradius and circularity；Then connected component labeling image is picked up by Depth Domain pixel again
Its Areal porosity, Areal porosity histogram.
Preferably, B specifically includes following steps：
2.1 define connected domain length and width, inscribed circle radius, circumradius：I. connected domain is grown, and refers to that connected domain is most left
Side pixel is to the number of pixels between rightmost pixel, including left right pixels；II. field width is connected, refers to that connected domain is most pushed up
End pixel is to the number of pixels between lowermost end pixel, including top bottom pixel；III. connected domain inscribed circle radius, connected domain is most
The right and left pixel and most top low side pixel can be depicted as a rectangle, and inscribed circle radius has two values, and one refers to this
The half pixel of rectangle short side, i.e. RInterior S, another refers to the half pixel of this rectangle long side, i.e. RInterior L；IV.
Connected domain circumradius, most connected domain most the right and left pixel and top low side pixel can be depicted as a rectangle, circumscribed circle half
Footpath refers to the cornerwise half pixel of this rectangle, i.e. ROutside；Thus define, by each in programming output image
These parameters of connected domain, while count connected domain length and wide distribution, inscribed circle radius distribution, circumradius in one section of image
Distribution, connected domain circularity distributed intelligence；
2.2 define connected domain circularity：
By the rectangle that connected domain most the right and left pixel and most top bottom pixel form and circular degree of closeness, it is defined as
" connected domain circularity ", is specifically calculated by following formula：
Connected domain circularity
In formula, RInterior S- short inscribed circle radius, ROutside- circumradius；Denominator meaning：In the square inscribed circle radius with
The ratio of circumradius isA standard can be regarded as；
2.3 define connected domain sorting coefficient：
Connected domain sorting coefficient SCO=PC25/PC75
In formula, PC25/CP75Represent the cumulative frequency 25% on connected domain inscribed circle radius, circumradius accumulation curve
The ratio between corresponding radius value and 75% corresponding radius value of cumulative frequency；With reference to the concept of deposit sorting coefficient, according to SC0's
Size can also divide the sorting grade of hole connected domain：SC0=1~2.5, good sorting；SC0=2.5~4.0, sorting is medium；
SC0＞ 4.0, sorting are poor.
Preferably, the specific method that 1.1 pairs of filtered images enter row threshold division is as follows：Demarcated and be imaged by rock core
Log picture, make the figure reflection core corrosion hole after selected threshold segmentation, the information in crack.
Preferably, Areal porosity histogram of the 1.2 Areal porosity histogram for 10 to 30 pixels in interval.
Preferably, Areal porosity histogram of the 1.2 Areal porosity histogram for 20 pixels in interval.
Beneficial effects of the present invention are as follows：
1. had based on equivalence to the image connectivity field mark method of processing it is quick, not repeating label the advantages of, utilize this
Method, corrosion hole connected domain can be accurately marked from bianry image, and then target information pickup, bag are carried out to each connected domain
Include bore hole size, sorting coefficient (variance), connected domain area (Areal porosity), circularity etc..
2. being layered using the Areal porosity curve for reflecting corrosion hole development degree to image, can pick up on this basis
The heterogeneous information such as the Areal porosity value of each interval corrosion hole, bore hole size, circularity, sorting coefficient (variance) distribution, can be with
Preferably quantitative response goes out FMI picture depths domain corrosion hole development degree and anisotropism, helps more accurately to evaluate well
Cylinder geologic feature, benefiting our pursuits for pit shaft rock hole information is quantitatively picked up also with FMI images.
Brief description of the drawings
Fig. 1 bianry images；
Fig. 2 equivalences are to before processing image；
Fig. 3 equivalences are to image after processing；
Fig. 4 FMI images；
Fig. 54 connects schematic diagram；
Fig. 68 connects schematic diagram；
Crack (Yan Jianping 2009) is picked up in Fig. 7 man-machine interactions；
Fig. 8 improved Hough transforms pick up crack (Yan Jianping 2009)；
Fig. 9 original images (field inscription on ancient bronze objects 1999)；
Figure 10 solution cavities pickup result images (field inscription on ancient bronze objects 1999)；
Figure 11 FMI bianry image connected component labeling algorithm flows；
Figure 12 bianry image arrays diverse location identifies；
Neighborhood point is paid close attention to when Figure 13 " 2 " location point connected domain detects；
Neighborhood point is paid close attention to when Figure 14 " 3 " location point connected domain detects；
Neighborhood point is paid close attention to when Figure 15 " 4 " location point connected domain detects；
Neighborhood point is paid close attention to when Figure 16 " 5 " location point connected domain detects；
Figure 17 Electrical imaging artworks；
Figure 18 gray level images；
Figure 19 medium filtering images；
Figure 20 bianry images；
The processing of Figure 21 connected component labelings；
Figure 22 connected component labelings amplify；
Figure 23 Areal porosity curves；
Figure 24 20pixel Areal porosities are distributed；
Figure 25 connected domains inscribed circle radius is distributed；
Figure 26 connected domains circumradius is distributed；
Figure 27 connected domains circularity is distributed；
Figure 28 example Electrical imaging artworks；
Figure 29 example gray-scale maps；
Figure 30 example medium filterings；
Figure 31 example binary pictures；
Figure 32 example Areal porosity curves (layering)；
Figure 33 example 20pixel Areal porosities are distributed；
Figure 34 connected component labelings are simultaneously layered.
Embodiment
For the objects, technical solutions and advantages of the present invention are more clearly understood, develop simultaneously embodiment referring to the drawings, right
The present invention is described in further details.
Connected component labeling Method And Principle and thinking based on equivalence to processing
As shown in figure 11, a kind of imaging logging image solution cavity information pickup method based on connected domain equivalence to processing, i.e.,
The method for being handled imaging logging image using the connected domain labeling method based on of equal value pair and extracting related solution cavity information.
The input of the inventive method is FMI through gray scale, filtering, binaryzation and image of the inverted (Er) array Count []
[], wherein pixel value non-zero i.e. 1, the array represents black (background color) and white (target face when image is shown respectively
Color) two kinds of colors, i.e. white portion represents solution cavity.Output is that the new construction after connected component labeling has been done according to Count [] []
Array NCount [] [] and the image restored by NCount [] [], different values represents to belong to different in the result array
Connected domain.
When it is determined that after 8 neighborhoods connection rule, being scanned to the two-value numerical value of image, sequentially for from left to right, from upper
Under.Processing when, each target pixel points need to only judge the pixel and surrounding have determined that connectedness pixel between
Relation just can determine that the connectedness of oneself.But the field point of concern needed for different location points is different, Figure 12-16 is respectively
All possible location point and when each determining connective required concern neighborhood point.
But due to the influence of solution cavity form and scanning sequency, it is disconnected two regions to cause to be initially considered that, with
Mark scan process is goed deep into, it is found that they actually belong to same connected region, as Figure 14-16 three types are likely to
It is of equal value right to produce.Must parity price is to handling in a program, otherwise this will have a strong impact on mark effect.
Fig. 1 can be seen that when being scanned mark to Fig. 1, and it is of equal value right that boxed area can produce, as shown in Fig. 2 in figure
Actual white portion is same connected region, but because the influence of scanning sequency and labeling algorithm, this region are labeled
For ' 8 ' and ' 14 ' two connected domains, this result not only influences solution cavity, the accurate statistics of dissolution pore number, also influences corrosion hole
The accurate extraction of characterization information.So in image markup process, need timely to handle it when occurring of equal value pair,
In order to avoid encountered problems in information pickup work afterwards.
Here, illustrate of equal value pair of processing procedure by taking Figure 15 as an example.The mark value of four pixels of mark will have been completed
It is placed in new array B [], it is assumed that there are two non-zero and unequal values in B [], then they are exactly a parity price pair.This
When, Schilling NCount [x] [y] (the pixel mark value of No. 4 opening positions) is equal to first non-zero value in B [], then finds
All mark values are equal to the point of second non-zero value in B [] and record their position in NCount [] [], finally by NCount
The value of [x] [y] is assigned to them one by one.So far, this equivalence is to having been processed into.It is more than the feelings of two as non-zero value in B []
Condition, it can be handled according to the method.
Fig. 3 is shown red boxes region and has carried out the result of equal value to processing, and the region is designated generally as ' 7 ',
Eliminate of equal value pair of influence.
Corrosion hole marks, information pickup：
1. mark, pickup information Step
1.1 image preprocessing：Gray processing processing is carried out to original image (Figure 17) first, obtains gray level image (Figure 18)；
After gray processing processing, median filter process (Figure 19) is carried out to image；Then enter row threshold division to filtered image (to pass through
Rock core demarcates imaging logging image, enable selected threshold split after image relatively accurately reflect core corrosion hole, crack
Information), binary image (Figure 20) is obtained, is laid a good foundation for hole connected component labeling, information parameter pickup.
1.2 connected component labelings, information pickup：First with the above-mentioned image connectivity field mark algorithm based on equivalence pair to two
Value image (Figure 20) progress connected component labeling processing, image (Figure 21) after being marked, while to each company in mark image
Pick up the parameter informations such as its length and width, inscribed circle radius, circumradius, circularity in logical domain (its detailed definition description sees below)；
Connected component labeling image is actually still bianry image, but unlike continued labelling has been carried out to connected domain, program can be passed through
Enter the pickup of row information quantification to each connected domain, image is Figure 22 after it amplifies, and is clearly visible connected component labeling situation；Connect
And its Areal porosity (Figure 23), 20, interval are picked up by Depth Domain pixel to connected component labeling image (or binary image Figure 20) again
The Areal porosity histogram (Figure 24) of pixel (20pixel), it is to understand corrosion hole development degree and actual treatment mistake in Depth Domain
Layered shaping is carried out in journey to image to lay a good foundation.
2. mark, pickup information parameter
2.1 connected domain length and widths, inscribed circle radius, circumradius：I. connected domain is grown, and refers to connected domain Far Left picture
The number of pixels (including left right pixels) that element is arrived between rightmost pixel；II. field width is connected, refers to connected domain top picture
The number of pixels (including top bottom pixel) that element is arrived between lowermost end pixel；III. connected domain inscribed circle radius, connected domain are most left
Right both sides pixel and most top low side pixel can be depicted as a rectangle, and inscribed circle radius has two values, and one refers to this square
Half pixel (the R of shape short sideInterior S), another refers to the half pixel (R of this rectangle long sideInterior L)；IV. connect
Domain circumradius, connected domain most the right and left pixel and most top low side pixel can be depicted as a rectangle, and circumradius refers to
Be the cornerwise half pixel (R of this rectangleOutside).Thus define, can be by programming output image (Figure 21)
These parameters of each connected domain, while connected domain length and wide distribution, inscribed circle radius distribution (figure in one section of image can be counted
25), information, the distribution of these parameters such as circumradius distribution (Figure 26), connected domain circularity distribution (Figure 27) can reflect well
Cylinder stratum hole development degree.
2.2 connected domain circularity：Circularity was the original corner angle of rock debris particle described in sedimentary petrography originally by rounding
Degree, it is the important feature feature of detrital grain.It is unrelated with the shape of particle, simply the function of corner angle acuity.
Edge of the circularity in particle maximum projection plane image is geometrically reflected.Theresa Weld (1932) proposes following roundness calculation
Formula：
Circularity RO=(∑ r/n)/R (1)
In formula, the inscribed circle radius of r- corners, n- corner numbers, the maximum inscribed circle radius of R- particles.
In imaging logging FMI connected domain identification images, we want to describe degree of closeness of the corrosion hole connected domain with circle,
In be intended to use for reference roundness of clastic particles definition and formula, but actually this definition and think description connected domain circularity conceptually
It is different, and the parameter such as corner for being related to of the formula is also not easy to the design of image processing process Program, therefore, we will connect
The rectangle of logical domain most the right and left pixel and most top bottom pixel composition and circular degree of closeness, are defined as " connected domain circle
Degree ", is specifically calculated by following formula：
Connected domain circularity
In formula, RInterior S- short inscribed circle radius, ROutside- circumradius.Denominator meaning：In the square inscribed circle radius with
The ratio of circumradius isA standard can be regarded as.Obtaining all connected domain rectangle inscribed circles and outer
After connecing the ratio between radius of circle, it is made comparisons with standard value can more intuitively find out connected domain shape and the degree of closeness of circle.
2.3 connected domain sorting coefficients：Sorting coefficient is originally the parameter for representing deposit degree of sorting, and it reflects that particle is big
Small uniformity coefficient, or perhaps the deviation that deposit surrounds central tendency is showed, the sorting coefficient formula provided is：
S0=P25/P75 (3)
P in formula25And P75It is straight that particle corresponding to the place of particulate accumulation content 25% and 75% on accumulation curve is represented respectively
Footpath.We want that using for reference the formula carrys out the sorting of corrosion hole connected domain yardstick in phenogram picture, therefore above-mentioned formula is changed
For：
Connected domain sorting coefficient SCO=PC25/PC75 (4)
In formula, PC25/CP75Represent the cumulative frequency 25% on connected domain inscribed circle radius, circumradius accumulation curve
The ratio between corresponding radius value and 75% corresponding radius value of cumulative frequency.Wherein by calculating, inscribed circle radius in Figure 21 images
(RInterior S) sorting coefficient be 2.25, circumradius sorting coefficient be 2.6.Possibility can't in certain real image processing procedure
There is PC25Or PC75, usable probability statistical parameter " variance " is come to characterize sorting be also feasible to a certain extent.With reference to deposition
The concept of thing sorting coefficient, according to SC0Size can also divide the sorting grade of hole connected domain：SC0=1~2.5, sorting
It is good；SC0=2.5~4.0, sorting is medium；SC0＞ 4.0, sorting are poor.
Specific embodiment：
Figure 28-34 is the example handled according to the method described above, carry out after handled it is image layered with connect domain information and pick up
Take：The corrosion hole development degree that Figure 33 reflections are combined first with picture depth domain Areal porosity curve (Figure 32) is carried out to image
It is layered (Figure 34)；Its length and width, inscribed circle radius, circumradius, circularity are picked up to each connected domain in mark image simultaneously
Deng parameter information；Then again to connected component labeling image (Figure 34) by Depth Domain layering result, count obtain in each layer respectively
The parameter information (table 1) of the distribution of connected domain inscribed circle radius distribution circumradius, circularity distribution and correlation, from Figure 25-27 and
The quantitative parameter information of corrosion hole connected domain in table 1, preferably it can go out FMI picture depths domain corrosion hole hair by quantitative response
Degree and anisotropism are educated, helps more accurately to evaluate pit shaft geologic feature.
The image layered middle connected domain parameter information picks up data of table 1
One of ordinary skill in the art will be appreciated that embodiment described here is to aid in reader and understands this hair
Bright implementation, it should be understood that protection scope of the present invention is not limited to such especially statement and embodiment.Ability
The those of ordinary skill in domain can be made according to these technical inspirations disclosed by the invention it is various do not depart from essence of the invention its
Its various specific deformations and combination, these deformations and combination are still within the scope of the present invention.
Claims (5)
- A kind of 1. pick-up method of solution cavity information in imaging logging image based on connected domain equivalence pair, it is characterised in that including Following steps：A. the imaging logging image corrosion hole connected domain quantitative mark based on equivalence to processing, the ginseng of each connected domain is picked up Number information, including the length of connected domain and width, connected domain circumradius, inscribed circle radius, circularity and sorting coefficient；B. the corrosion hole development degree based on the reflection of Areal porosity curve is layered to imaging logging image, then to each layer Count number, the distribution of connected domain sorting coefficient, circularity distribution, inscribed circle and the heterogeneous letter of circumradius distribution of connected domain Breath；B specifically includes following steps：2.1 define connected domain length and width, inscribed circle radius, circumradius：I, connected domains are grown, and refer to connected domain Far Left picture The number of pixels that element is arrived between rightmost pixel, including left right pixels；II, connects field width, refers to connected domain top picture The number of pixels that element is arrived between lowermost end pixel, including top bottom pixel；III, connected domain inscribed circle radius, connected domain most left and right Both sides pixel and most top bottom pixel can be depicted as a rectangle, and inscribed circle radius has two values, and one refers to this rectangle The half pixel of short side, i.e. RInterior S, another refers to the half pixel of this rectangle long side, i.e. RInterior L；IV, is connected Domain circumradius, connected domain most the right and left pixel and most top bottom pixel can be depicted as a rectangle, and circumradius refers to Be the cornerwise half pixel of this rectangle, i.e. ROutside；Thus define, by each being connected in programming output image These parameters in domain, while count connected domain length and wide distribution, inscribed circle radius distribution, circumradius point in one section of image Cloth, connected domain circularity distributed intelligence；2.2 define connected domain circularity：By the rectangle that connected domain most the right and left pixel and most top bottom pixel form and circular degree of closeness, it is defined as " even Logical domain circularity ", is specifically calculated by following formula：In formula, RInterior S- short inscribed circle radius, ROutside- circumradius；Denominator meaning：In the square inscribed circle radius with it is external The ratio of radius of circle isA standard can be regarded as；2.3 define connected domain sorting coefficient：Connected domain sorting coefficient SCO=PC25/PC75In formula, PC25/PC75Represent on connected domain inscribed circle radius, circumradius accumulation curve corresponding to cumulative frequency 25% The ratio between radius value and 75% corresponding radius value of cumulative frequency；With reference to the concept of deposit sorting coefficient, according to SCOSize The sorting grade of hole connected domain can be divided：SCO=1~2.5, good sorting；4.0≥SCO>2.5, sorting is medium；SCO>4.0 Sorting is poor.
- 2. according to the method for claim 1, it is characterised in that A specifically includes following steps：1.1 image preprocessing：Gray processing processing is carried out to original image first, obtains gray level image；After gray processing processing, to figure As carrying out median filter process；Then row threshold division is entered to filtered image, obtains binary image；1.2 connected component labelings, information pickup：Bianry image is entered first with the image connectivity field mark algorithm based on of equal value pair The processing of row connected component labeling, image after being marked, while its length and width, inscribe are picked up to each connected domain in mark image The parameter information of radius of circle, circumradius and circularity；Then its face is picked up by Depth Domain pixel to connected component labeling image again Porosity, Areal porosity histogram.
- 3. according to the method for claim 2, it is characterised in that 1.1 pairs of filtered images enter the specific of row threshold division Method is as follows：Imaging logging image is demarcated by rock core, make selected threshold split after figure reflection core corrosion hole, crack Information.
- 4. according to the method for claim 2, it is characterised in that 1.2 Areal porosity histogram is 10 to 30 pixels in interval Areal porosity histogram.
- 5. according to the method for claim 4, it is characterised in that 1.2 Areal porosity histogram is the face of 20 pixels in interval Porosity histogram.
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| CN113393400B (en) * | 2021-06-22 | 2022-08-30 | 中海油田服务股份有限公司 | Processing method and device for eliminating noise characteristics of electric imaging image |
| CN113808190B (en) * | 2021-09-23 | 2023-07-28 | 西南石油大学 | Shale layer information quantitative extraction method based on electric imaging logging image |
| CN114565137A (en) * | 2022-01-29 | 2022-05-31 | 河南中烟工业有限责任公司 | Tobacco shred forming result prediction method based on two-dimensional morphological characteristics of tobacco flakes |
| CN115829990B (en) * | 2022-12-15 | 2023-10-10 | 吉林大学 | Natural crack identification method based on imaging logging image processing |
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