CN104866856A - Imaging log image solution cave information picking method based on connected domain equivalence pair processing - Google Patents
Imaging log image solution cave information picking method based on connected domain equivalence pair processing Download PDFInfo
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Abstract
The invention discloses an imaging log image solution cave information picking method based on connected domain equivalence pair processing, and belongs to the field of imaging log image solution cave information picking. The method comprises following steps: A. quantitatively marking connected domains of imaging log image solution caves based on equivalence pair processing, and picking parameter information of each connected domain, wherein the parameter information includes the length, the width, the circumscribed circle radius, the inscribed circle radius, the circularity and sorting coefficients of the connected domain; and B. layering an imaging log image based on solution cave development degrees reflected by surface porosity curves. The beneficial effects of the method are that an image connected domain marking algorithm based on equivalence pair processing is advantaged by rapid speed and non-repeated marking, and the solution cave connected domains can be accurately marked in a binary image by the use of the algorithm, so that object information of each connected domain can be picked, wherein the object information includes the cave size, the sorting coefficients, connected domain areas (surface porosities), the circularity and the like.
Description
Technical field
The invention belongs to the pickup field of solution cavity information in imaging logging image, be specifically related to a kind of based on the connected domain imaging logging image solution cavity information pickup method to process of equal value.
Background technology
1. abbreviation and Key Term definition
1.1 connected domains: refer to the set be made up of several pixels, the pixel in this set has following characteristic: the grey level of all pixels is all less than or equal to connected domain rank; Pixel in same connected domain communicates between two, namely between any two pixels, there is a path be made up of the element of this set completely.
1.2 of equal value on: due to the impact of solution cavity form and scanning sequency, cause starting to think two disconnected regions, along with going deep into of mark scannng process, find that in fact they belong to same connected region, this phenomenon can be referred to as of equal value to phenomenon.
Can find out, when carrying out passing marker to figure, boxed area can produce of equal value right, as shown in Figure 1.In figure, white portion is actual is same connected region, but due to the impact of scanning sequency and labeling algorithm, this region is marked as ' 8 ' and ' 14 ' two connected domains, and as shown in Figure 2, it is of equal value to phenomenon that Here it is.
1.3 Areal porosity: in image, solution cavity area accounts for the number percent of whole image area.
2. relevant knowledge introduction:
2.1 stratum micro-resisitivity image (FMI) utilize many rows button shape small electrode on multi-electrode to borehole wall stratum transmitter current, due to the difference of the rock composition of electrode contact, structure and contained fluid, cause the change of electric current thus, the change of electric current reflects the change of borehole wall rock resistivity everywhere, can show the borehole wall imaging of resistivity accordingly.Image is from white (high resistance) to yellow, arrive black (low resistance) again, the darker resistivity of color lower (as shown in Figure 4), in figure, four white ribbons are white spaces that instrument does not cover, black curve is borehole wall crack, and black splotch is corrosion hole.
The connected domain of 2.2 images is exactly the reachability problem between pixel in fact.In two dimensional image hypothetical target pixel with around certain its pixel value of adjacent pixel identical, then claim this two pixels to be communicated with.Needing when studying connective first to determine that neighborhood is communicated with rule is that 4 neighborhoods are communicated with or 8 neighborhoods are communicated with.It is 4, the upper and lower, left and right location point (Fig. 5) of target pixel points that 4 neighborhoods are communicated with what pay close attention to.8 neighborhoods are communicated with then chooses object pixel neighbor pixel all in 3*3 matrix in two-dimensional space, namely except the point of upper and lower, left and right, also comprise upper left, upper right, lower-left, 4, bottom right location point (Fig. 6), algorithm of the present invention adopts 8 neighborhoods to be communicated with 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 treatment, and the morphological feature of the intersection of fracture plane and pit shaft on image is rendered as monocyclic sinusoidal curve, point---the information such as the crack angle in line duality captured image of application hough transform, good result can be obtained, for the angle in crack, the information such as initial phase can be picked up preferably, as shown in Figure 8.
Although this method can well pick up crack information, have ignored solution cavity information.And it is not very applicable in the stratum that crack is less in solution cavity growth.
3.2 based on the solution cavity automatic testing method (field inscription on ancient bronze objects 1999) of bottom hole path image
The method comprises and utilizes Roberts operator to carry out solution cavity rim detection, carries out Edge track and refinement by the method based on directivity curve, thus realizes the automatic extraction of solution cavity and quantitatively calculate.The method is obtained unique point direction sequence by extract minutiae, tracking and is utilized the directivity curve of its correspondence to carry out solution cavity differentiation.Its algorithm calculated amount is less, and judgement speed is fast, has good real-time treatability and adaptability, as shown in Figure 10.
Although this method can identify solution cavity preferably, be also only limitted to the detection identification to solution cavity, the relevant information for solution cavity cannot be extracted, thus cannot provide Data support to the evaluating reservoir on solution cavity growth stratum further.
Summary of the invention
The present invention is directed to the deficiencies in the prior art, provide a kind of based on the connected domain imaging logging image solution cavity information pickup method to process of equal value, although effectively can solve because of nonrecognition solution cavity information or can identify and do not extract solution cavity information and the evaluating reservoir cannot growing stratum to solution cavity that causes provides the problem of Data support.
For overcoming the above problems, the technical solution used in the present invention is as follows: a kind of based on the connected domain imaging logging image solution cavity information pickup method to process of equal value, comprises the following steps:
A. based on the imaging logging image corrosion hole connected domain quantitative mark of equivalence to process, pick up the parameter information of each connected domain, comprise the length of connected domain and wide, connected domain circumradius, inscribed circle radius, circularity and sorting coefficient;
B. the corrosion hole development degree based on the reflection of Areal porosity curve carries out layering to imaging logging image, then to the heterogeneous body information of the number of every one deck statistics connected domain, the distribution of connected domain sorting coefficient, circularity distribution, incircle and circumradius distribution.
As preferably, A specifically comprises the following steps:
1.1 Image semantic classification: first gray processing process is carried out to original image, obtain gray level image; After gray processing process, medium filtering process is carried out to image; Then Threshold segmentation is carried out to filtered image, obtain binary image;
1.2 connected component labelings, information pickup: first utilize the image connectivity field mark algorithm based on equivalence is right to carry out connected component labeling process to bianry image, obtain marking rear image, each connected domain in marking image is picked up to the parameter information of its length and width, inscribed circle radius, circumradius and circularity simultaneously; Then again by Depth Domain pixel, its Areal porosity, Areal porosity histogram are picked up to connected component labeling image.
As preferably, B specifically comprises the following steps:
2.1 definition connected domain length and widths, inscribed circle radius, circumradius: I. connected domain is long, refers to the number of pixels between connected domain Far Left pixel to rightmost pixel, comprises left right pixels; II. be communicated with field width, refer to the number of pixels between connected domain top pixel to lowermost end pixel, comprise top bottom pixel; III. connected domain inscribed circle radius, the most the right and left pixel of connected domain and push up low end pixel most and can be depicted as a rectangle, inscribed circle radius has two values, 1/2nd pixels referring to this rectangle minor face, i.e. R
interior S, another refers to 1/2nd pixels on the long limit of this rectangle, i.e. R
interior L; IV. connected domain circumradius, the most the right and left pixel of connected domain and push up low end pixel most and can be depicted as a rectangle, circumradius refers to cornerwise 1/2nd pixels of this rectangle, i.e. R
outward; Define thus, by these parameters of connected domain each in program design output image, in statistics one section of image, connected domain length and wide distribution, inscribed circle radius distribute simultaneously, circumradius distributes, the distributed intelligence of connected domain circularity;
2.2 definition connected domain circularity:
By the rectangle of most for connected domain the right and left pixel and most top bottom pixel composition and circular degree of closeness, be defined as " connected domain circularity ", specifically calculated by following formula:
Connected domain circularity
In formula, R
interior S-short inscribed circle radius, R
outward-circumradius; Denominator meaning: the ratio of inscribed circle radius and circumradius is in the square
a standard can be regarded as;
2.3 definition connected domain sorting coefficients:
Connected domain sorting coefficient S
cO=PC
25/ PC
75
In formula, PC
25/ CP
75represent the ratio of the radius value that the radius value of cumulative frequency 25% correspondence is corresponding with cumulative frequency 75% on connected domain inscribed circle radius, circumradius summation curve; In conjunction with the concept of sediment sorting coefficient, according to S
c0size also can divide the sorting grade of hole connected domain: S
c0=1 ~ 2.5, good sorting; S
c0=2.5 ~ 4.0, sorting is medium; S
c0> 4.0, sorting is poor.
As preferably, 1.1 to carry out the concrete grammar of Threshold segmentation to filtered image as follows: demarcate imaging logging image by rock core, the figure after selected threshold is split reflects the information in core corrosion hole, crack.
As preferably, the Areal porosity histogram of 1.2 is the Areal porosity histogram of 10 to 30 pixels in interval.
As preferably, the Areal porosity histogram of 1.2 is the Areal porosity histogram of 20 pixels in interval.
Beneficial effect of the present invention is as follows:
1. have fast based on the image connectivity field mark method of equivalence to process, the advantage of not repeating label, utilize the method, accurately can mark corrosion hole connected domain from bianry image, and then target information pickup is carried out to each connected domain, comprise bore hole size, sorting coefficient (variance), connected domain area (Areal porosity), circularity etc.
2. utilize the Areal porosity curve of reflection corrosion hole development degree to carry out layering to image, the heterogeneous body information such as the Areal porosity value of each interval corrosion hole, bore hole size, circularity, sorting coefficient (variance) distribution can be picked up on this basis, FMI picture depth territory corrosion hole development degree and nonuniformity can be gone out by quantitative response preferably, contributing to evaluating pit shaft geologic feature more accurately, is also utilize FMI image quantitatively to pick up benefiting our pursuits of pit shaft rock hole information.
Accompanying drawing explanation
Fig. 1 bianry image;
Fig. 2 is of equal value to image before process;
Fig. 3 is of equal value to image after process;
Fig. 4 FMI image;
Fig. 54 is communicated with schematic diagram;
Fig. 68 is communicated with schematic diagram;
Fig. 7 man-machine interaction pickup crack (Yan Jianping 2009);
Fig. 8 improved Hough transform pickup crack (Yan Jianping 2009);
Fig. 9 original image (field inscription on ancient bronze objects 1999);
Figure 10 solution cavity pickup result images (field inscription on ancient bronze objects 1999);
Figure 11 FMI bianry image connected component labeling algorithm flow;
Figure 12 bianry image array 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;
The former figure of Figure 17 Electrical imaging;
Figure 18 gray level image;
Figure 19 medium filtering image;
Figure 20 bianry image;
The process of Figure 21 connected component labeling;
Figure 22 connected component labeling amplifies;
Figure 23 Areal porosity curve;
Figure 24 20pixel Areal porosity distributes;
Figure 25 connected domain inscribed circle radius distributes;
Figure 26 connected domain circumradius distributes;
Figure 27 connected domain circularity distributes;
The former figure of Figure 28 example Electrical imaging;
Figure 29 example gray-scale map;
Figure 30 example medium filtering;
Figure 31 example binary picture;
Figure 32 example Areal porosity curve (layering);
Figure 33 example 20pixel Areal porosity distributes;
Figure 34 connected component labeling layering.
Embodiment
For making object of the present invention, technical scheme and advantage clearly understand, to develop simultaneously embodiment referring to accompanying drawing, the present invention is described in further details.
Based on equivalence to the connected component labeling Method And Principle of process and thinking
As shown in figure 11, a kind of based on the connected domain imaging logging image solution cavity information pickup method to process of equal value, namely utilize and based on equivalence right connected domain labeling method imaging logging image to be processed and to extract the method for solution cavity information of being correlated with.
The inventive method be input as FMI through gray scale, filtering, binaryzation image (Er) array Count [] [] after negate, wherein pixel value is non-zero is 1, this array represents black (background color) and white (color of object) two kinds of colors respectively when image shows, namely white portion represents solution cavity.The image being new construction array NCount [] [] after having done connected component labeling according to Count [] [] and being restored by NCount [] [] exported, in this result array, different values represents and belongs to different connected domains.
After determining that 8 neighborhoods are communicated with rule, scan the two-value numerical value of image, order is from left to right, from top to bottom.When processing, the relation that each target pixel points only need judge this pixel and around determine between connective pixel just can determine oneself connectedness.But the required field point paid close attention to of different location points is different, the neighborhood point of required concern when Figure 12-16 is respectively all possible location point and determines connectedness separately.
But due to the impact of solution cavity form and scanning sequency, cause thinking disconnected two regions at first, along with going deep into of mark scannng process, find that in fact they belong to same connected region, as Figure 14-16 three types all likely produce of equal value right.Must parity price be to processing in a program, otherwise this will have a strong impact on mark effect.
Fig. 1 can find out, when carrying out passing marker to Fig. 1, boxed area can produce of equal value right, as shown in Figure 2, in figure, white portion is actual is same connected region, but due to the impact of scanning sequency and labeling algorithm, this region is marked as ' 8 ' and ' 14 ' two connected domains, this result not only affects the accurate statistics of solution cavity, dissolution pore number, also affects the accurate extraction of corrosion hole characterization information.So in image markup process, need to process timely it, in order to avoid encounter problems in information pickup work afterwards when occurring of equal value pair.
At this, for Figure 15, of equal value right processing procedure is described.The mark value of four pixels completing mark be placed in new array B [], suppose to have in B [] two non-zero and unequal values, so they are exactly a parity price pair.Now, Schilling NCount [x] [y] (pixel mark value of No. 4 positions) equal first non-zero value in B [], then find all mark value in NCount [] [] equal the point of second non-zero value in B [] and record their position, finally the value of NCount [x] [y] is assigned to them one by one.So far, this equivalence is to being processed.As for the situation that non-zero value in B [] is greater than two, all can process according to the method.
Fig. 3 display be that the result to process of equal value has been carried out in red boxes region, this region is labeled as ' 7 ' by unified, eliminate of equal value on impact.
Corrosion hole marks, information pickup:
1. mark, pick up information Step
1.1 Image semantic classification: first carry out gray processing process to original image (Figure 17), obtain gray level image (Figure 18); After gray processing process, medium filtering process (Figure 19) is carried out to image; Then Threshold segmentation is carried out to filtered image and (demarcate imaging logging image by rock core, image after selected threshold is split more accurately reflects the information in core corrosion hole, crack), obtain binary image (Figure 20), for hole connected component labeling, information parameter pickup are laid a good foundation.
1.2 connected component labelings, information pickup: first utilize the above-mentioned image connectivity field mark algorithm right based on equivalence to carry out connected component labeling process to bianry image (Figure 20), obtain marking rear image (Figure 21), the parameter informations such as its length and width, inscribed circle radius, circumradius, circularity (its detailed definition describes and sees below) are picked up to each connected domain in marking image simultaneously; In fact connected component labeling image is still bianry image, but has carried out continued labelling unlike to connected domain, carries out the pickup of information quantification by program to each connected domain, and it amplifies rear image and Figure 22, can know and see connected component labeling situation; Then again connected component labeling image (or binary image Figure 20) being picked up to the Areal porosity histogram (Figure 24) of its Areal porosity (Figure 23), 20 pixels (20pixel) in interval by Depth Domain pixel, laying a good foundation for carrying out layered shaping to image in Depth Domain understanding corrosion hole development degree and actual process.
2. mark, pick up information parameter
2.1 connected domain length and widths, inscribed circle radius, circumradius: I. connected domain is long, refer to the number of pixels (comprising left right pixels) between connected domain Far Left pixel to rightmost pixel; II. be communicated with field width, refer to the number of pixels (comprising top bottom pixel) between connected domain top pixel to lowermost end pixel; III. connected domain inscribed circle radius, the most the right and left pixel of connected domain and push up low end pixel most and can be depicted as a rectangle, inscribed circle radius has two values, 1/2nd pixel (R referring to this rectangle minor face
interior S), another refers to 1/2nd pixel (R on the long limit of this rectangle
interior L); IV. connected domain circumradius, the most the right and left pixel of connected domain and push up low end pixel most and can be depicted as a rectangle, circumradius refers to cornerwise 1/2nd pixel (R of this rectangle
outward).Define thus, by these parameters of each connected domain in program design output image (Figure 21), can add up the information such as connected domain in one section of image is long and wide distribution, inscribed circle radius distribution (Figure 25), circumradius distribute (Figure 26), connected domain circularity distribution (Figure 27), the distribution of these parameters can reflect wellbore formation hole development degree simultaneously.
2.2 connected domain circularity: circularity be originally rock debris particle is described in sedimentary petrography original corner angle by the degree of rounding, it is the important feature feature of detrital grain.The shape of it and particle has nothing to do, just the function of corner angle acuity.Circularity is geometrically reflecting the edge in particle maximum projection plane image.Theresa Weld (1932) proposes following roundness calculation formula:
Circularity R
o=(∑ r/n)/R (1)
In formula, the inscribed circle radius of r-corner, n-corner number, the maximum inscribed circle radius of R-particle.
In imaging logging FMI connected domain identification image, we want to describe corrosion hole connected domain with circular degree of closeness, so want definition and the formula of using for reference roundness of clastic particles, but in fact this definition and want describe connected domain circularity be conceptually different, and the parameters such as the corner that relates to of this formula are also not easy to the design of image processing process Program, therefore, we are by the rectangle of most for connected domain the right and left pixel and most top bottom pixel composition and circular degree of closeness, be defined as " connected domain circularity ", specifically calculated by following formula:
Connected domain circularity
In formula, R
interior S-short inscribed circle radius, R
outward-circumradius.Denominator meaning: the ratio of inscribed circle radius and circumradius is in the square
a standard can be regarded as.After the ratio obtaining all connected domain rectangle incircles and circumradius, itself and standard value are made comparisons and can find out connected domain shape and round degree of closeness more intuitively.
2.3 connected domain sorting coefficients: sorting coefficient is the parameter representing sediment degree of sorting originally, the degree of uniformity of its reflection grain size, or perhaps performance sediment is around the deviation of central tendency, the sorting coefficient formula provided is:
S
0＝P
25/P
75(3)
P in formula
25and P
75represent the particle diameter that on summation curve, particulate accumulation content 25% and 75% place is corresponding respectively.We want to use for reference the sorting that this formula carrys out corrosion hole connected domain yardstick in token image, are therefore revised as by above-mentioned formula:
Connected domain sorting coefficient S
cO=PC
25/ PC
75(4)
In formula, PC
25/ CP
75represent the ratio of the radius value that the radius value of cumulative frequency 25% correspondence is corresponding with cumulative frequency 75% on connected domain inscribed circle radius, circumradius summation curve.Wherein by calculating, inscribed circle radius (R in Figure 21 image
interior S) sorting coefficient is 2.25, circumradius sorting coefficient is 2.6.PC may can't be there is in certain real image processing procedure
25or PC
75, usable probability statistical parameter " variance " characterizes sorting to a certain extent is also feasible.In conjunction with the concept of sediment sorting coefficient, according to S
c0size also can divide the sorting grade of hole connected domain: S
c0=1 ~ 2.5, good sorting; S
c0=2.5 ~ 4.0, sorting is medium; S
c0> 4.0, sorting is poor.
Specific embodiment:
Figure 28-34 is the examples processed according to the method described above, carries out image layered and connected domain information pickup: first utilize the corrosion hole development degree that picture depth territory Areal porosity curve (Figure 32) is reflected in conjunction with Figure 33 to carry out layering (Figure 34) to image after processing; The parameter informations such as its length and width, inscribed circle radius, circumradius, circularity are picked up to each connected domain in marking image simultaneously; Then again to connected component labeling image (Figure 34) by Depth Domain layering result, statistics obtains the distribution of connected domain inscribed circle radius distribution circumradius, circularity distribution and relevant parameter information (table 1) in every one deck respectively, the quantitative parameter information of corrosion hole connected domain from Figure 25-27 and table 1, FMI picture depth territory corrosion hole development degree and nonuniformity can be gone out by quantitative response preferably, contribute to evaluating pit shaft geologic feature more accurately.
The image layered middle connected domain parameter information picks up data of table 1
Those of ordinary skill in the art will appreciate that, embodiment described here is to help reader understanding's implementation method of the present invention, should be understood to that protection scope of the present invention is not limited to so special statement and embodiment.Those of ordinary skill in the art can make various other various concrete distortion and combination of not departing from essence of the present invention according to these technology enlightenment disclosed by the invention, and these distortion and combination are still in protection scope of the present invention.
Claims (6)
1., based on a pick-up method for solution cavity information in connected domain right imaging logging image of equal value, it is characterized in that, comprise the following steps:
A. based on the imaging logging image corrosion hole connected domain quantitative mark of equivalence to process, pick up the parameter information of each connected domain, comprise the length of connected domain and wide, connected domain circumradius, inscribed circle radius, circularity and sorting coefficient;
B. the corrosion hole development degree based on the reflection of Areal porosity curve carries out layering to imaging logging image, then to the heterogeneous body information of the number of every one deck statistics connected domain, the distribution of connected domain sorting coefficient, circularity distribution, incircle and circumradius distribution.
2. method according to claim 1, is characterized in that, A specifically comprises the following steps:
1.1 Image semantic classification: first gray processing process is carried out to original image, obtain gray level image; After gray processing process, medium filtering process is carried out to image; Then Threshold segmentation is carried out to filtered image, obtain binary image;
1.2 connected component labelings, information pickup: first utilize the image connectivity field mark algorithm based on equivalence is right to carry out connected component labeling process to bianry image, obtain marking rear image, each connected domain in marking image is picked up to the parameter information of its length and width, inscribed circle radius, circumradius and circularity simultaneously; Then again by Depth Domain pixel, its Areal porosity, Areal porosity histogram are picked up to connected component labeling image.
3. method according to claim 1 and 2, is characterized in that, B specifically comprises the following steps:
2.1 definition connected domain length and widths, inscribed circle radius, circumradius: I. connected domain is long, refers to the number of pixels between connected domain Far Left pixel to rightmost pixel, comprises left right pixels; II. be communicated with field width, refer to the number of pixels between connected domain top pixel to lowermost end pixel, comprise top bottom pixel; III. connected domain inscribed circle radius, the most the right and left pixel of connected domain and push up low end pixel most and can be depicted as a rectangle, inscribed circle radius has two values, 1/2nd pixels referring to this rectangle minor face, i.e. R
interior S, another refers to 1/2nd pixels on the long limit of this rectangle, i.e. R
interior L; IV. connected domain circumradius, the most the right and left pixel of connected domain and push up low end pixel most and can be depicted as a rectangle, circumradius refers to cornerwise 1/2nd pixels of this rectangle, i.e. R
outward; Define thus, by these parameters of connected domain each in program design output image, in statistics one section of image, connected domain length and wide distribution, inscribed circle radius distribute simultaneously, circumradius distributes, the distributed intelligence of connected domain circularity;
2.2 definition connected domain circularity:
By the rectangle of most for connected domain the right and left pixel and most top bottom pixel composition and circular degree of closeness, be defined as " connected domain circularity ", specifically calculated by following formula:
Connected domain circularity
In formula, R
interior S-short inscribed circle radius, R
outward-circumradius; Denominator meaning: the ratio of inscribed circle radius and circumradius is in the square
a standard can be regarded as;
2.3 definition connected domain sorting coefficients:
Connected domain sorting coefficient S
c0=PC
25/ PC
75
In formula, PC
25/ CP
75represent the ratio of the radius value that the radius value of cumulative frequency 25% correspondence is corresponding with cumulative frequency 75% on connected domain inscribed circle radius, circumradius summation curve; In conjunction with the concept of sediment sorting coefficient, according to S
c0size also can divide the sorting grade of hole connected domain: S
c0=1 ~ 2.5, good sorting; S
c0=2.5 ~ 4.0, sorting is medium; S
c0> 4.0, sorting is poor.
4. method according to claim 2, is characterized in that, 1.1 to carry out the concrete grammar of Threshold segmentation to filtered image as follows: demarcate imaging logging image by rock core, the figure after selected threshold is split reflects the information in core corrosion hole, crack.
5. method according to claim 2, is characterized in that, the Areal porosity histogram of 1.2 is the Areal porosity histogram of 10 to 30 pixels in interval.
6. method according to claim 5, is characterized in that, the Areal porosity histogram of 1.2 is the Areal porosity histogram of 20 pixels in interval.
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