CN115078362A - Drillability characterization method based on rock mesoscopic structure - Google Patents
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- 239000011435 rock Substances 0.000 title claims abstract description 103
- 238000012512 characterization method Methods 0.000 title claims abstract description 6
- 239000002245 particle Substances 0.000 claims abstract description 61
- 229910052500 inorganic mineral Inorganic materials 0.000 claims abstract description 36
- 239000011707 mineral Substances 0.000 claims abstract description 36
- 238000000034 method Methods 0.000 claims abstract description 26
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- 238000005266 casting Methods 0.000 claims abstract description 5
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- 239000004568 cement Substances 0.000 claims description 3
- 239000003822 epoxy resin Substances 0.000 claims description 3
- 239000012634 fragment Substances 0.000 claims description 3
- 229920000647 polyepoxide Polymers 0.000 claims description 3
- 238000005406 washing Methods 0.000 claims description 2
- 238000007619 statistical method Methods 0.000 abstract 1
- 238000005553 drilling Methods 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 5
- 238000000926 separation method Methods 0.000 description 4
- 238000007373 indentation Methods 0.000 description 2
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Abstract
The invention discloses a drillability characterization method based on a rock mesoscopic structure, which comprises the following steps of: 1) selecting a plurality of rock samples as research objects, and 2) manufacturing a casting body slice; 3) shooting a microscopic image; 4) dividing the mineral particle contour: firstly, a mineral particle contour dividing principle is formulated, preliminary division is carried out, and then fine division is carried out by matching with the formulated mineral particle dividing principle; 5) calculating geometric parameters of the mineral particles; 6) calculating a microscopic structure quantization index; 7) performing a rock drillability test; 8) carrying out statistical analysis on the correlation between each mesoscopic structure quantitative index of the rock and the drillability, and screening out the mesoscopic structure quantitative index with the best correlation with the drillability of the rock; and establishing a model for predicting drillability by the rock mesoscopic structure quantitative index according to the optimal mesoscopic structure quantitative index. The method can realize the accurate division of the rock mineral particle outline, obtain the microscopic structure quantization index and reveal the rock breaking mechanism of the drill bit from the viewpoint of microscopic mechanics.
Description
Technical Field
The invention relates to the technical field of petroleum drilling, in particular to a drillability characterization method based on a rock mesoscopic structure.
Background
Rock drillability has been a parameter of major concern in oil and gas drilling projects. At present, the method for acquiring the drillability of the rock mainly comprises a micro-drilling method, a sound wave method and a rock mechanical property method. The micro-drilling method is the most commonly used method, but the problems of difficult underground coring, high drilling cost and the like exist, and the drillability of the rock in the whole well section cannot be obtained. Many models for predicting rock drillability by using the acoustic wave method are available, but the prediction models are not popularized and cannot be popularized to other blocks and strata. The effect of predicting the drillability of the rock by a rock mechanical property method is generally poor.
In patent CN107180302B, a method for evaluating the drillability of rock by using the content of rock debris elements is proposed, which evaluates the drillability of rock by the content of rock debris elements, but does not consider the influence of the structure of mineral particles inside the rock on the drillability. In patent CN114091290B, a rock drillability evaluation method based on rock chip nano indentation is proposed, which obtains micro hardness by performing nano indentation test on rock chip, and further characterizes rock drillability by the correlation between macro hardness and rock drillability, and this method is firstly limited by the correlation between macro hardness and rock drillability, and secondly does not consider the influence of the structure of mineral particles inside rock on drillability.
In summary, a method for representing drillability based on a rock microscopic structure is needed at present, so that the drillability of rock can be accurately predicted through underground rock debris, and finally the possibility of obtaining the drillability of the rock in the whole well section through the minimum cost is realized.
Disclosure of Invention
The invention aims to provide a method for representing drillability based on a rock mesostructure, which aims to predict the drillability of rocks by using underground rock debris by researching the internal relation between the rock mesostructure parameters and the drillability.
The invention provides a drillability characterization method based on a rock mesostructure, which comprises the following steps:
s1, selecting a plurality of rock samples as research objects, and respectively carrying out the following steps S2-S8.
S2, manufacturing a casting sheet: firstly, washing oil on the rock, then infusing epoxy resin into the rock in vacuum, and grinding into thin slices with the thickness not more than 0.03 mm.
S3, shooting microscopic images of the casting slice: the magnification of the microscope was adjusted to ensure that there were no less than 200 mineral particles in the photograph.
S4, dividing the mineral particle profile: firstly, a mineral particle contour dividing principle is formulated, a cellpool module in Python is used for preliminary division, and then ImageJ software is used for matching with the formulated mineral particle dividing principle for fine division. The mineral particle outline dividing principle is as follows: (1) calculation of preferential large particles, (2) treatment of particle fragments as one particle, (3) treatment of particles as two particles after the particles are separated by the fracture, (4) treatment of cement as one particle, (5) separation of particles with two wide ends and narrow middle ends into two particles, and (6) separation of different mineral particles into two particles.
And S5, calculating geometric parameters of the mineral particles, wherein the geometric parameters comprise the perimeter, the area and the Feret diameter of the contour of the mineral particles.
S6, calculating a mesoscopic structure quantization index, wherein the index comprises a mesoscopic structure coefficient TC, a minimum length-width ratio AR, a roundness SF, a square Rnd of a ratio of an object equivalent diameter to a length, a logarithm of a ratio of a square of an object perimeter to an object area Eds, a ratio of a square of an object perimeter to an object area CPa, an evaluation variance ratio t of a grain size and a grain linkage coefficient g; and (5) calculating each mesostructure quantization index by using matlab programming.
S7, performing rock drillability test: performing a rock drillability test using a rock drillability tester; the rock drillability level value is then calculated according to the calculation method in the standard (SY/T5426-2016). The rock drillability tester adopts a test device for testing the rock drillability disclosed in the patent CN 201922350632.1.
S8, statistically analyzing the correlation between each microscopic structure quantitative index of the rock and the drillability, and screening out the microscopic structure quantitative index with the best correlation with the drillability of the rock; and establishing a model for predicting drillability by the rock mesoscopic structure quantitative index according to the screened optimal mesoscopic structure quantitative index.
The specific method comprises the following steps: drawing by taking the quantitative index of each microscopic structure as an abscissa and the drillability level value of each rock sample as an ordinate to obtain a fitting curve and R of the fitting curve 2 Value, maximum R 2 The abscissa of the graph corresponding to the value is the mesoscopic structure quantitative index with the best relevance to the rock drillability; and further obtaining a functional relation between the optimal mesoscopic structure quantization index and the drillability level value, namely obtaining a model for predicting the drillability of the rock mesoscopic structure quantization index.
Compared with the prior art, the invention has the advantages that:
(1) the accurate division of the rock mineral particle outline is realized, the difficult problem that the mineral particles in the rock are difficult to divide is solved, and a theoretical basis is provided for artificially and intelligently extracting the rock microscopic structure.
(2) The distribution rule of the rock microscopic structure parameters can be obtained, the microscopic structure characteristics can be quantized, and the problem that the microscopic structure is difficult to quantize is solved.
(3) The method not only obtains the relationship between the rock mesoscopic structure quantitative index and the drillability, but also establishes a model for predicting the drillability by the mesoscopic structure quantitative index, and provides possibility for predicting the underground rock drillability in a large scale and accurately at low cost.
(4) The geometric characteristics and coordinate information of the mineral particles are obtained, and scientific basis can be provided for establishing a real rock sample for numerical simulation.
(5) The invention can research the relationship between the microscopic structure quantization index and the rock breaking of the drill bit and disclose the rock breaking mechanism of the drill bit through microscopic mechanics.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
FIG. 1 is a flow chart of a method of characterizing drillability based on a rock mesostructure of the present invention.
Fig. 2 shows the flow and results of the image processing stage.
Fig. 3 is a profile of a divided mineral particle.
FIG. 4 is a graph relating drillability to CPa.
FIG. 5 is a graph of drillability versus L.
FIG. 6 is a graph relating drillability to TC.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in FIGS. 1-6, the method for characterizing drillability based on rock mesostructure provided by the invention comprises the following steps:
s1, selecting a plurality of rock samples as research objects, and respectively carrying out the following steps S2-S8; in this example, 18 kinds of sandstone samples were selected as the study subjects.
S2, preparing a cast sheet (see fig. 2): the rock is first oil washed and then cut (201), epoxy resin is then vacuum impregnated into the rock (202), pressed (203), and ground into a cast sheet (204) of 0.03mm thickness.
S3, taking a microscopic image: pictures were taken using a professional polarizing microscope (205) and the magnification of the microscope was adjusted to ensure that no less than 200 mineral particles were in the picture.
S4, dividing the mineral grain profile (see fig. 3): firstly, a mineral particle contour dividing principle is formulated (301); then, the shot single-polarization and orthogonal polarization images are firstly subjected to primary division (302) of the mineral grain outline by using a celldump module in Python, and finally fine division (303) of the mineral grain outline is performed by using ImageJ software. The mineral particle contour dividing principle is as follows: (1) calculation of preferential large particles, (2) treatment of particle fragments as one particle, (3) treatment of particles as two particles after the particles are separated by the fracture, (4) treatment of cement as one particle, (5) separation of particles with two wide ends and narrow middle ends into two particles, and (6) separation of different mineral particles into two particles.
And S5, firstly, carrying out preliminary geometric parameter calculation on the divided mineral particle outline, wherein the geometric parameters comprise the perimeter, the area and the Feret diameter of the mineral particle outline.
S6, further calculating by using matlab programming according to the formula of the mesoscopic structure quantization index to obtain the final mesoscopic structure quantization index shown in Table 1. Table 1 shows the mesostructure quantitative indicators of 18 kinds of rocks.
TABLE 1, 18 kinds of rock microscopic structure quantitative indexes
Note: l-diameter; a-area; p-perimeter; AR-minimum aspect ratio; SF-roundness; rnd-the square of the ratio of the equivalent diameter to the length of the body; eds-the logarithm of the square of the perimeter of the object to the logarithm of the area of the object; CPa-ratio of the square of the object perimeter to the object area; t-evaluation variance ratio of grain size; g-grain linkage coefficient; TC-microscopic Structure coefficient.
S7, performing rock drillability test: firstly, preparing a standard rock sample, and performing rock drillability test by using a rock drillability tester; and setting parameters of bit pressure and rotation speed according to a drillability test standard, and finally calculating the effective drilling time obtained by the test to obtain the drillability of the rock. And calculating the rock drillability grade value according to the calculation method in the standard (SY/T5426-2016).
S8, statistically analyzing the correlation between each microscopic structure quantitative index of the rock and the drillability, and screening out the microscopic structure quantitative index with the best correlation with the drillability of the rock. And then establishing a model for predicting drillability by the rock mesoscopic structure quantitative index according to the screened optimal mesoscopic structure quantitative index.
The specific method comprises the following steps: drawing by taking the quantitative index of each microscopic structure as an abscissa and the drillability level value of each rock sample as an ordinate to obtain a fitting curve and R of the fitting curve 2 Value, maximum R 2 The abscissa of the graph corresponding to the value is the mesoscopic structure quantitative index with the best relevance to the rock drillability. As shown in FIGS. 4, 5 and 6, FIG. 4 is a graph of correlation between drillability and CPa, and R can be obtained by fitting a curve 2 0.64. FIG. 5 is a graph of the correlation between drillability and L, and by fitting a curve, R can be obtained 2 0.06. FIG. 6 is a graph relating drillability to TC. By fitting a curve, R can be obtained 2 0.73. The total number of the microscopic structure quantization indexes is 11, the total number of the obtained related relation graphs of each microscopic structure quantization index and drillability is 11, and the graphs are more and are not listed one by one. By comparing R of 11 graphs 2 Value, find the maximum R 2 The figure corresponding to the value, the microscopic structure quantization index corresponding to the abscissa of the figure is the index with the best correlation with drillability. In this embodiment, R of FIG. 6 2 The largest value, TC of fig. 6, correlates best with drillability.
From figure 6 a functional relationship of TC with drillability level value is derived,
the model is a model for predicting drillability of the rock mesoscopic structure quantization index TC.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (7)
1. A drillability characterization method based on a rock mesostructure is characterized by comprising the following steps:
s1, selecting a plurality of rock samples as research objects, and respectively carrying out the following steps S2-S8;
s2, manufacturing a casting sheet;
s3, shooting microscopic images of the casting slice;
s4, dividing the contour of the mineral particles: firstly, a mineral particle contour dividing principle is formulated, a celldose module in Python is used for preliminary division, and then ImageJ software is used for matching with the formulated mineral particle dividing principle for fine division;
s5, calculating geometric parameters of the mineral particles, wherein the geometric parameters comprise the perimeter, the area and the Feret diameter of the contour of the mineral particles;
s6, calculating a mesoscopic structure quantization index, wherein the index comprises a mesoscopic structure coefficient TC, a minimum length-width ratio AR, a roundness SF, a square Rnd of a ratio of an object equivalent diameter to a length, a logarithm of a ratio of a square of an object perimeter to an object area Eds, a ratio of a square of an object perimeter to an object area CPa, an evaluation variance ratio t of a grain size and a grain linkage coefficient g;
s7, performing rock drillability test;
s8, statistically analyzing the correlation between each microscopic structure quantitative index of the rock and the drillability, and screening out the microscopic structure quantitative index with the best correlation with the drillability of the rock; and establishing a model for predicting drillability by the rock mesoscopic structure quantitative index according to the screened optimal mesoscopic structure quantitative index.
2. The method for characterizing drillability based on a rock microstructure according to claim 1, wherein in step S4, the mineral particle profile classification rule is: (1) the method comprises the following steps of (1) preferentially dividing large particles with obvious boundaries, (2) treating particle fragments as one particle, (3) treating the particles as two particles after the particles are separated by cracks, (4) treating cement separated by minerals as one particle, and (5) dividing the particles with two wide ends and narrow middle into two particles.
3. The method for characterizing drillability based on rock mesostructure as claimed in claim 1, wherein in step S6, the program is written to calculate each mesostructure quantitative index.
4. The method for characterizing drillability based on a rock microstructure according to claim 1, wherein said step S7 includes performing a rock drillability test using a rock drillability tester and calculating a rock drillability level value according to the test result.
5. The method for characterizing drillability based on rock mesostructures according to claim 4, wherein in step S8, the value of drillability of each rock sample is plotted on the abscissa as the quantitative index of each mesostructure, and the value of drillability of each rock sample is plotted on the ordinate, so as to obtain the fitted curve, and R of the fitted curve 2 Value, maximum R 2 The abscissa of the graph corresponding to the value is the mesoscopic structure quantitative index with the best relevance to the rock drillability; and further obtaining a functional relation between the optimal mesoscopic structure quantitative index and the drillability level value, namely a model for predicting the drillability of the rock mesoscopic structure quantitative index.
6. The method for characterizing drillability based on a rock microstructure according to claim 1, wherein said step S2 is specifically: firstly, washing oil on the rock, then infusing epoxy resin into the rock in vacuum, and grinding into thin slices with the thickness not more than 0.03 mm.
7. The method for characterizing drillability based on rock mesostructure according to claim 1, wherein said method for taking microscopic images in step S3 is: the magnification of the microscope was adjusted to ensure that there were no less than 200 mineral particles in the photograph.
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| CN115407046B (en) * | 2022-08-05 | 2024-04-16 | 西南石油大学 | Comprehensive abrasiveness characterization method based on rock microstructure and equivalent quartz content |
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