CN115407046B - Comprehensive abrasiveness characterization method based on rock microstructure and equivalent quartz content - Google Patents
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Abstract
The invention discloses a comprehensive abrasiveness characterization method based on a rock microstructure and equivalent quartz content, which comprises the following steps of firstly selecting a plurality of rock samples as research objects, and then sequentially carrying out the following steps: XRD rock sample mineral composition test, equivalent quartz content calculation, cast body slice manufacturing, microscopic image shooting, mineral particle contour dividing, mineral particle geometric parameter calculating, fine structure quantization index and structural maturity grading, irregular rock sample regular manufacturing, rock grindability test, correlation analysis of rock fine structure quantization index and equivalent quartz content and grindability, and establishment of a model for jointly predicting grindability of the rock fine structure quantization index and the equivalent quartz content. The method of the invention realizes the purpose of predicting the abrasiveness of the rock by utilizing the underground irregular cuttings by considering the mesoscopic structural parameters of the rock and the internal relation between the equivalent quartz content and the abrasiveness of the rock.
Description
Technical Field
The invention relates to the technical field of petroleum and natural gas drilling engineering, in particular to a method for jointly representing abrasiveness through a rock microstructure and equivalent quartz content.
Background
Rock abrasiveness has been a parameter of great concern in oil and gas drilling engineering. The existing method for acquiring the rock abrasiveness mainly comprises a CERCHAR grinding method, a bond ball milling method, a well logging parameter calculation method and a rock mechanical property method, wherein the CERCHAR grinding method is most commonly used, but the problems that underground coring is difficult, the drilling cost is high, effective experiments are difficult to perform due to the fact that most rock scraps are irregular in shape, and the like exist, and the rock abrasiveness of a whole well section cannot be acquired. The model for predicting the rock abrasiveness by using the logging parameter calculation method is many, but the prediction model has no generalization and cannot be generalized to other blocks and strata. The rock mechanical property method is not good in predicting the general effect of rock abrasiveness.
Patent CN113009592B proposes a method for calculating the abrasiveness parameters of a rock sample by using the well logging data of the rock sample, and directly evaluating the rock abrasiveness parameters of the conglomerate stratum by using the density well logging data, the resistivity well logging data, the neutron porosity well logging data, the acoustic well logging data and the natural gamma well logging data, but does not consider the influence of the structure of mineral particles in the rock on the abrasiveness.
Patent CN103306672B proposes to determine the internal friction angle of the on-site shale in different drilling directions, i.e. the abrasiveness of the direction, based on a model of the relationship between the internal friction angle and the acoustic time difference, drilling angle in the vertical layer surface direction. This method is limited firstly by the association of macroscopic rock physical properties and rock abrasiveness and secondly by the fact that the structure of the mineral particles within the rock has no consideration for the abrasiveness.
In view of the foregoing, there is a need for a method for characterizing abrasiveness based on an irregular rock microstructure and an equivalent quartz content, so as to accurately predict the abrasiveness of rock through underground irregular rock fragments, and finally achieve the possibility of obtaining the abrasiveness of rock in the whole well section at the minimum cost.
Disclosure of Invention
The invention aims to provide a novel method for jointly representing the abrasiveness of rock based on an irregular rock microstructure and equivalent quartz content.
The invention provides a comprehensive abrasiveness characterization method based on a rock microstructure and equivalent quartz content, which comprises the following steps:
s1, selecting a plurality of rock samples as research objects; the mineral composition of the rock samples was first analyzed by XRD and the equivalent quartz content EQC of each rock sample was calculated.
S2, respectively manufacturing casting body slices by adopting each rock sample, and then shooting microscopic images. The method for manufacturing the cast sheet comprises the following steps: the rock sample was washed with oil, then epoxy resin was vacuum poured into the rock and polished to a thickness of 0.03mm. When a microscopic image is shot, the magnification of the microscope is adjusted, so that not less than 300 mineral particles in the photo are ensured, a single polarized light image is shot, the angles of the polarizer and the analyzer are adjusted, and a compensator with optical path difference lambda is inserted for optical path difference compensation so as to reduce chromatic dispersion and then an orthogonal polarized light image is shot.
S3, dividing the outline of the mineral particles according to the microscopic image: firstly, a mineral particle contour division principle is established, a cellpost module in Python is used for preliminary division, and then imageJ software is used for fine division in cooperation with the established mineral particle contour division principle.
The principle of mineral particle profile division is as follows:
(1) Preferentially dividing large particles with obvious boundaries; (2) Both the particulate crumb and cement are treated as a single particle; (3) Dividing the particles according to the dividing condition after the particles are divided by the cracks, and dividing the particles into one particle when the cracks are less than 1/3 of the particle diameter, or dividing the particles into two particles; (4) The incomplete particles at the image edge are directly regarded as a new particle for division; (5) When two particles overlap a part, the uppermost particle is preferentially divided, and when the lower particle is divided, the overlapped part is ignored, and the upper particle is directly divided into new particles according to the upper particle boundary; (6) clay and biohybrid are not classified as particles.
S4, after fine division, calculating geometrical parameters of the mineral particles, including calculating the perimeter P, the area A, the roundness Rnd, the aspect ratio AR and the Feret diameter L of the outline of the mineral particles;
s5, calculating a quantitative index of the microstructure, wherein the quantitative index comprises a microstructure parameter TC, a ratio SF of the area of the object to the area of the circle with the same circumference, an interlocking factor g and a ratio CP of the square of the circumference of the object to the area of the object A The logarithm of the square of the object perimeter to the logarithm of the object area Eds, the square Rnd of the ratio of the object equivalent diameter to the length, the average variance ratio t of the mineral particle sizes;
s6, classifying the structural maturity of all rock samples into 3 grades of immature, sub-mature and mature;
s7, preparing irregular rock samples into regularized samples, then carrying out rock abrasiveness test on all the rock samples, and calculating an abrasiveness grade value CAI of each rock sample. A method of making irregular rock samples into regularized rock samples: firstly, selecting one surface for grinding, then placing the surface into a rock standard sample manufacturing mould, and casting epoxy resin into the mould to obtain a standard sample with regular epoxy resin and irregular rock composition.
S8, statistically analyzing the correlation between the microscopic structure quantization index and the abrasiveness of the rock sample with the same maturity level, and finding out the microscopic structure quantization index with the best correlation with the abrasiveness of the rock. Specifically, for rock samples within the same maturity level, each microscopic structure quantization index is respectively used as an abscissa, and the abrasiveness level value CAI of each rock sample is used as an ordinate to draw a fitting straight line, and R of the fitting straight line is obtained 2 Value, maximum R 2 The abscissa of the graph corresponding to the value is the fine structure quantization index with the best relativity with the rock abrasiveness.
And statistically analyzing the correlation relationship between the equivalent quartz content and the abrasiveness of the rock samples with the same maturity grade. Specifically, for rock samples within the same maturity level, the equivalent quartz content EQC is plotted as an abscissa, and the abrasiveness level value CAI of the rock samples is plotted as an ordinate, so as to obtain a fitting straight line, namely, a relational expression between the abrasiveness level value CAI and the equivalent quartz content.
And S9, fitting a functional relation between the microscopic structure quantization index and the equivalent quartz content, which are optimal in correlation of the rock abrasiveness and the rock abrasiveness, so as to obtain a prediction model for predicting the rock abrasiveness together by the microscopic structure quantization index and the equivalent quartz content. Finally, a prediction model for predicting the rock abrasiveness under the conditions of three different structural maturity by jointly using the quantitative index of the microstructure and the equivalent quartz content is obtained.
Compared with the prior art, the invention has the following advantages:
(1) The method provided by the invention can obtain the distribution rule of the rock mesostructure parameters, can quantify the mesostructure characteristics, and solves the difficult problem that the mesostructure is difficult to quantify.
(2) The method provided by the invention can realize accurate division of the outlines of rock mineral particles, solves the problem that the mineral particles in the rock are difficult to divide, and provides a theoretical basis for artificial intelligent extraction of the microstructure of the rock.
(3) The method provided by the invention can obtain the geometric characteristics and coordinate information of mineral particles, and provides more accurate data support for classifying the maturity of the microstructure of the rock; and a scientific basis is provided for establishing a real rock sample for numerical simulation.
(4) The method provided by the invention can be used for regularly manufacturing the irregular rock, can be used for manufacturing a standard sample for the on-site underground irregular rock scraps, and provides feasibility for carrying out related tests.
(5) The method provided by the invention can obtain the relationship between the quantitative index of the microstructure of the rock and the equivalent quartz content and the abrasiveness, establishes a model for jointly predicting the abrasiveness by the quantitative index of the microstructure and the equivalent quartz content, further realizes accurate prediction of the abrasiveness of the rock through underground irregular rock scraps, can accurately predict the abrasiveness of the underground irregular rock in a large-scale and low-cost manner, and finally realizes the possibility of obtaining the abrasiveness of the rock of the whole well section through the minimum cost.
(6) The method provided by the invention can be used for researching the relationships between a plurality of quantitative indexes of the microstructure and equivalent quartz content and drill bit abrasion, and revealing the integral geometrical characteristics of mineral particles and the mechanism of the abrasion drill bit of particle types through micromechanics.
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 schematic flow chart of the abrasive synthetic characterization method based on the rock microstructure and equivalent quartz content of the present invention.
FIG. 2 is a diagram of a cast sheet prepared.
Fig. 3 is a view of the resulting single polarization and orthogonal polarization images taken under a professional polarization microscope.
Fig. 4 is a schematic diagram of the principle of mineral particle profiling.
Fig. 5 is a graph of the results of preliminary partitioning using a cellpost module in Python.
Fig. 6 is a graph of the results of fine classification using ImageJ software in conjunction with established mineral particle profile classification rules.
FIG. 7 is a phase of analysis of correlation of the quantitative index of the microstructure with the equivalent quartz content and grindability.
FIG. 8 is a model of the predicted abrasiveness of the microstructure quantification index (TC) and Equivalent Quartz Content (EQC).
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
As shown in FIG. 1, the method for comprehensively characterizing the abrasiveness based on the microstructure and the equivalent quartz content of the rock comprises the following steps in sequence: XRD mineral composition test (101), calculation of equivalent quartz content (102), casting body slice (103), shooting of microscopic image (104), division of mineral particle outline (105), calculation of mineral particle geometric parameters (106), calculation of microstructure quantification index and structure maturity grading (107), irregular rock sample regularization manufacture (108), rock abrasiveness test (109), analysis of microstructure quantification index and equivalent quartz content and abrasiveness correlation (110), and establishment of a model (111) for jointly predicting abrasiveness by the microstructure quantification index and the equivalent quartz content.
The XRD mineral composition test (101) and the calculation of the equivalent quartz content (102) are rock mineral composition analysis stages. And preparing the cast sheet (103) and taking a microscopic image (104) as a preparation stage of the image. The mineral particle contours (105) are divided into image processing phases. The calculation of the geometric parameters (106) of mineral particles, the calculation of the quantitative index of the microstructure and the classification of the structural maturity (107) are taken as parameter calculation stages.
In this example 18 rock samples were used as subjects.
The method for manufacturing the cast sheet comprises the following steps: the rock sample was washed with oil, cut, epoxy resin was then vacuum poured into the rock, pressurized and polished to a 0.03mm thick slice. The resulting cast sheet is shown in FIG. 2.
When a microscopic image is shot, the magnification of the microscope is adjusted, so that not less than 300 mineral particles in the photo are ensured, a single polarized light image is shot, the angles of the polarizer and the analyzer are adjusted, and a compensator with optical path difference lambda is inserted for optical path difference compensation so as to reduce chromatic dispersion and then an orthogonal polarized light image is shot. Fig. 3 is a view of the resulting single polarization and orthogonal polarization images taken under a professional polarization microscope.
The mineral particle contours are divided according to microscopic images, and the specific method comprises the following steps:
firstly, a mineral particle contour division principle is established, as shown in fig. 4, wherein the mineral particle contour division principle is as follows:
(1) Preferentially dividing large particles with obvious boundaries; (2) Both the particulate crumb and cement are treated as a single particle; (3) Dividing the particles according to the dividing condition after the particles are divided by the cracks, and dividing the particles into one particle when the cracks are less than 1/3 of the particle diameter, or dividing the particles into two particles; (4) The incomplete particles at the image edge are directly regarded as a new particle for division; (5) When two particles overlap a part, the uppermost particle is preferentially divided, and when the lower particle is divided, the overlapped part is ignored, and the upper particle is directly divided into new particles according to the upper particle boundary; (6) clay and biohybrid are not classified as particles. Preliminary division is carried out by using a cellpost module in Python, and then fine division is carried out by using imageJ software in cooperation with a formulated mineral particle profile division principle.
Then, preliminary division was performed using a cellpost module in Python, and the result is shown in fig. 5. The image J software is used for fine division according to the established mineral particle profile division principle, and the result is shown in figure 6.
Preliminary geometric parameter calculation is firstly carried out on the divided mineral particle contours, then further calculation is carried out by comparing with a formula of the quantitative index of the microstructure, and the final quantitative index of the microstructure is obtained as shown in table 1.
Table 1, microstructure quantitative index of 18 rock samples
According to the microscopic structure of the rock, the maturity classification is carried out according to the granularity, sorting, rounding degree and hetero-base content of the particles of the rock, and all rock samples are subjected to structural maturity classification and are classified into 3 classes of immature, sub-mature and mature. The specific classification criteria are as follows:
immature-clay impurity content in rock sample exceeds 5%, and the particles are generally classified into poor and angular shapes.
Sub-maturation-clay hetero-base content in rock samples is below 5%, but particle sorting is poor and rounding is not good.
Mature-rock samples contain little or no clay heteroatoms, and the particles are well sorted but not well rounded.
A method of making irregular rock samples into regularized rock samples: firstly, selecting one surface for grinding, then placing the surface into a rock standard sample manufacturing mould, and casting epoxy resin into the mould to obtain a standard sample with regular epoxy resin and irregular rock composition.
Rock abrasiveness testing was then performed on all rock samples. In this example, the test method is as in this document: ISRM Suggested Method for Determining the Abrasivity of Rock by the CERCHAR Abrasivity Test. The testing instrument adopts a rock abrasiveness parameter and metal abrasion resistance parameter testing device disclosed in patent CN 201610325278.5. And finally, calculating the abrasiveness grade value CAI of each rock sample.
As shown in fig. 7, correlation analysis is performed on numerous microscopic structure quantification indexes extracted from the rock with the immature, sub-mature and mature structures and three different structural maturity degrees one by one, and equivalent quartz content and grindability are analyzed, so that the combination of the microscopic structure quantification index with the largest grindability correlation in the rock with the same structural maturity degree and the equivalent quartz content is obtained.
Firstly, the correlation between the microstructure quantification index and the abrasiveness of rock samples with the same maturity level is statistically analyzed, and the microstructure quantification index with the best correlation with the abrasiveness of the rock is found. Specifically, for rock samples within the same maturity level, each microscopic structure quantization index is respectively used as an abscissa, and the abrasiveness level value CAI of each rock sample is used as an ordinate to draw a fitting straight line, and R of the fitting straight line is obtained 2 Value, maximum R 2 The abscissa of the graph corresponding to the value is the fine structure quantization index with the best relativity with the rock abrasiveness. In this embodiment, the microstructure quantification index TC is an index that has the best correlation with the rock abrasiveness. The grindability of sandstones of different maturity versus TC is shown in fig. 8 (b).
Then, the correlation between the equivalent quartz content and the abrasiveness of the rock samples of the same maturity grade was statistically analyzed. Specifically, for rock samples within the same maturity level, the equivalent quartz content EQC is plotted as an abscissa, and the abrasiveness level value CAI of the rock samples is plotted as an ordinate, so as to obtain a fitting straight line, namely, a relational expression between the abrasiveness level value CAI and the equivalent quartz content. FIG. 8 (a) is a graph of the abrasiveness of sandstones of different maturity versus EQC equivalent quartz content.
Under three different structural maturity, fitting the functional relation of the fine structural quantization index TC and the equivalent quartz content EQC with the best correlation between the rock abrasiveness and the rock abrasiveness respectively, wherein the specific functional relation is shown in figure 8. And obtaining a prediction model for predicting the rock abrasiveness under the conditions of three different structural maturity by jointly using the quantitative index of the microstructure and the equivalent quartz content.
The present invention is not limited to the above-mentioned embodiments, but is intended to be limited to the following embodiments, and any modifications, equivalents and modifications can be made to the above-mentioned embodiments without departing from the scope of the invention.
Claims (7)
1. The comprehensive abrasiveness characterization method based on the rock microstructure and the equivalent quartz content is characterized by comprising the following steps:
s1, selecting a plurality of rock samples as research objects; firstly, testing and analyzing mineral components of each rock sample, and calculating equivalent quartz content EQC of each rock sample;
s2, respectively adopting each rock sample to manufacture a casting body slice, and then shooting microscopic images to ensure that not less than 300 mineral particles are in the images;
s3, dividing the outline of the mineral particles according to the microscopic image: firstly, a mineral particle contour division principle is established, a cellpost module in Python is used for preliminary division, and then imageJ software is used for fine division in cooperation with the established mineral particle contour division principle;
s4, after fine division, calculating geometrical parameters of the mineral particles, including all parameters including the perimeter P, the area A, the roundness Rnd, the aspect ratio AR and the Feret diameter L of the outline of the mineral particles;
s5, calculating a quantitative index of the microstructure, wherein the quantitative index comprises a microstructure parameter TC, a ratio SF of the area of the object to the area of the circle with the same circumference, an interlocking factor g and a ratio CP of the square of the circumference of the object to the area of the object A Logarithm of square of object perimeter to logarithm of object area EdsAll parameters including mean variance ratio t of particle size;
s6, classifying the structural maturity of all rock samples into 3 grades of immature, sub-mature and mature;
s7, preparing irregular rock samples into regular rock samples, then carrying out rock abrasiveness test on all the rock samples, and calculating an abrasiveness grade value CAI of each rock sample;
s8, statistically analyzing the correlation between the microscopic structure quantization index and the abrasiveness of the rock sample with the same maturity level, and finding out the microscopic structure quantization index with the best correlation with the abrasiveness of the rock; analyzing the correlation relation between the equivalent quartz content and the abrasiveness of rock samples with the same maturity grade;
s9, fitting the mesoscopic structure quantization index with the best rock grindability relevance and the equivalent quartz content in a functional relation to obtain a functional relation formula of the rock grindability, the mesoscopic structure quantization index with the best rock grindability relevance and the equivalent quartz content, and obtaining a prediction model for jointly predicting the rock grindability by the mesoscopic structure quantization index and the equivalent quartz content; finally, a prediction model for predicting the rock abrasiveness under the conditions of three different structural maturity by jointly using the quantitative index of the microstructure and the equivalent quartz content is obtained.
2. The method for the comprehensive characterization of the abrasiveness based on the microstructure and the equivalent quartz content of the rock according to claim 1, wherein the principle of the profile division of the mineral particles is as follows:
(1) Preferentially dividing large particles with obvious boundaries; (2) Both the particulate crumb and cement are treated as a single particle; (3) Dividing the particles according to the dividing condition after the particles are divided by the cracks, and dividing the particles into one particle when the cracks are less than 1/3 of the particle diameter, or dividing the particles into two particles; (4) The incomplete particles at the image edge are directly regarded as a new particle for division; (5) When two particles overlap a part, the uppermost particle is preferentially divided, and when the lower particle is divided, the overlapped part is ignored, and the upper particle is directly divided into new particles according to the upper particle boundary; (6) clay and biohybrid are not classified as particles.
3. The method for the integrated characterization of abrasiveness based on the microstructure and equivalent quartz content of claim 1, wherein in step S1, the mineral composition of the rock sample is analyzed by XRD.
4. The method for the comprehensive characterization of abrasiveness based on a microscopic structure and equivalent quartz content according to claim 1, wherein in step S2, the method for manufacturing the cast sheet is: the rock sample was washed with oil, then epoxy resin was vacuum poured into the rock and polished to a thickness of 0.03mm.
5. The method for the comprehensive characterization of the abrasiveness based on the microscopic structure and the equivalent quartz content according to claim 4, wherein in the step S2, when the microscopic image is taken, the magnification of the microscope is adjusted, not less than 300 mineral particles in the image are ensured, the single polarized image is taken, the angles of the polarizer and the analyzer are adjusted, and a compensator with an optical path difference lambda is inserted for optical path difference compensation to reduce chromatic dispersion and then the orthogonal polarized image is taken.
6. The method for the comprehensive characterization of abrasiveness based on the microstructure and equivalent quartz content according to claim 1, wherein in step S7, the method for preparing irregular rock samples into regularized rock samples comprises: firstly, selecting one surface for grinding, then placing the surface into a rock standard sample manufacturing mould, and casting epoxy resin into the mould to obtain a standard sample with regular epoxy resin and irregular rock composition.
7. The method for the integrated characterization of abrasiveness based on a microscopic structure and equivalent quartz content according to claim 1, wherein step S8 comprises the following two steps:
s81, aiming at rock samples in the same maturity level, respectively plotting with each microscopic structure quantization index as an abscissa and the abrasiveness level value CAI of each rock sample as an ordinate to obtain a fitting straightLine and R of fitted straight line 2 Value, maximum R 2 The abscissa of the graph corresponding to the value is the fine structure quantization index with the best relativity with the rock abrasiveness;
s82, aiming at the rock samples in the same maturity level, plotting by taking the equivalent quartz content EQC as an abscissa and taking the abrasiveness level value CAI of the rock samples as an ordinate to obtain a fitting straight line, namely, a relation between the abrasiveness level value CAI and the equivalent quartz content.
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| US1931921A (en) * | 1932-12-01 | 1933-10-24 | Valley Forge Cement Company | Manufacture of cement |
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