CN112485401A - Quantitative experiment method for shale physical property response under influence of multi-factor coupling - Google Patents
Quantitative experiment method for shale physical property response under influence of multi-factor coupling Download PDFInfo
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Abstract
The invention provides a quantitative experimental method for shale physical property response under the influence of multi-factor coupling, which comprises the following steps: s1: determining the physical properties of the shale to be researched and determining induction factors and quantity; s2: determining the number of the specific gravity changes of each induction factor according to the number of the induction factors and the coupling relation between the induction factors; s3: introducing an orthogonal test design method in the mathematical statistics category, selecting a corresponding orthogonal table, determining specific proportion and combination of each induction factor under each level according to the orthogonal table, and determining the proportion of shale modeling components and modeling conditions; s4: constructing a controllable artificial shale sample to be tested by adopting an artificial shale modeling technology based on a hot pressing method; s5: physical properties of the series of rock samples are tested through a rock experiment, and quantitative influence relations of different influence factors on the physical properties are decoupled through a mathematical statistics method. The method can effectively solve the problem of quantitative research on physical property response under the influence of multi-factor coupling of rocks, which is ubiquitous in the field of geophysical.
Description
Technical Field
The invention relates to the fields of geological and geophysical research technology and laboratory test, in particular to a quantitative experimental method for shale physical property response under the influence of multi-factor coupling.
Background
The shale is in a large geological and geophysical environment, the properties of the shale are influenced by a plurality of geological factors such as buried depth, pressure, organic matter content and the like, and finally, the properties are shown and comprehensively reflected by a plurality of influence conditions. However, in practical research and application, it is more desirable to separate the combined effect of multiple factors from the large background so as to obtain the specific effect of a single factor on the result.
If the effect of each single factor affecting the shale properties on the target property can be separated, the overall situation of a specific study area can be estimated according to the degree of each factor in the area. This requires that each influencing factor of the target index can be controlled and varied independently. For example, the brittleness of shale is affected by a variety of factors, such as brittle minerals (quartz, carbonate), clay minerals, diagenetic pressure, organic content, and the like. The influence of various components, diagenesis conditions, particle sizes and the like on physical properties such as brittleness, anisotropy, mechanical properties and the like of shale is researched by a core testing method, a sample series needs to be prepared, and certain factor in the series can be ensured to be continuously changed according to experimental design. Meanwhile, all other factor conditions need to be kept consistent, namely, the single influence factor of the test sample needs to be completely controllable, and although the single influence factor cannot be achieved under the condition of natural shale, the artificial shale sample sequence with controllable factors can be manufactured to achieve the experimental purpose.
Difficulties still exist in the process of utilizing the artificial shale sample to carry out experiments. If the situation of interactive change of various factors is considered, as many sample test blocks as possible need to be manufactured for testing so as to ensure the stability and reliability of the test result. However, as the number of samples required increases, the number of samples required increases geometrically, and if the samples are made in their entirety, considerable time and labor costs are required.
Therefore, the invention provides a quantitative experimental method for the response of physical properties of shale under the influence of multi-factor coupling.
Disclosure of Invention
In order to solve the above problems, the present invention aims to provide a quantitative experimental method for shale physical property response under the influence of multi-factor coupling, which reduces the investment while reflecting the real influence of each factor on the target property as much as possible, shortens the production molding period, and avoids the phenomena of labor and time consumption, etc.
In order to achieve the above purpose, the present invention provides the following technical solutions.
A quantitative experiment method for shale physical property response under the influence of multi-factor coupling comprises the following steps:
s1: establishing physical properties of the shale to be researched, and determining induction factors and quantity influencing the physical properties of the shale aiming at the physical properties;
s2: determining the number of the specific gravity changes of each induction factor, namely the fixed level number, according to the number of the induction factors and the coupling relation among the induction factors;
s3: introducing an orthogonal test design method in the mathematical statistics category, selecting a corresponding orthogonal table according to the quantity and the horizontal quantity of the determined induction factors, determining the specific proportion and combination of each induction factor under each level according to the orthogonal table, and determining the proportion of shale modeling components and modeling conditions;
s4: taking geological conditions and physical properties of natural shale as geological constraints, and constructing a series of controllable artificial shale samples to be tested with components and condition ratios determined by orthogonal test design by adopting an artificial shale modeling technology based on a hot pressing method;
s5: and testing the physical properties of the established rock sample through a rock experiment, and decoupling the quantitative influence relation of different influence factors on the physical properties by adopting a mathematical statistics method based on the tested experimental data.
Preferably, the physical properties include elastic, electrical and mechanical properties; the elastic properties include anisotropy, brittleness, modulus, impedance, and speed; the electrical properties include resistivity and polarizability; the mechanical properties include Young's modulus, Poisson's ratio, and compressive strength.
Preferably, the inducing factors influencing the physical properties of the shale comprise geological diagenetic environment, clay minerals, clastic minerals, authigenic minerals and organic matter; the diagenetic environment comprises diagenetic pressure, diagenetic temperature and diagenetic time; the clay minerals include kaolinite, illite, montmorillonite, hydromica, and beidellite; the clastic minerals comprise quartz, feldspar, mica and calcite; the authigenic minerals include oxides and hydroxides of iron, aluminum, and manganese; the organic matter includes bitumen and kerogen.
Preferably, the specific gravity of the induction factors comprises the content percentages of different components, the sizes of different diagenesis pressures and the heights of different diagenesis temperatures.
Preferably, the selection principle of the orthogonal table is as follows: on the premise that test factors and interaction can be arranged, a smaller orthogonal table is selected, the situation of a full test is known through partial test analysis, and then an optimal horizontal combination is found.
Preferably, the number of levels of the test factor in S3 should be equal to the number of levels in the orthogonal table; the number of columns c of the orthogonal table is more than or equal to the number of columns occupied by the factors, the number of columns occupied by the interaction and the empty columns; the total freedom (a-1) of the orthogonal table is more than or equal to the factor freedom + the interaction freedom + the error freedom; if the sum of the factors and the degrees of freedom of interaction is equal to the total degree of freedom of the selected orthogonal table, the repeated orthogonal test is adopted to estimate the test error.
Preferably, the artificial shale sample in S4 is constructed according to the following principle: physical parameters, mechanical characteristics, seismic characteristics, microstructures and diagenetic conditions of various rocks are similar to those of natural shale.
Preferably, the rock experiment test in S5 includes a petrophysical test and a rock mechanical test; the rock physical test comprises an ultrasonic test, a differential resonance spectrum test, a low-frequency rock physical test and a resistivity test under a stratum environment; the rock mechanics test comprises a uniaxial compression experiment and a triaxial compression experiment under the uniaxial stratum environment.
Preferably, the mathematical statistical method comprises range analysis and analysis of variance.
The invention provides a quantitative experiment method for shale physical property response under the influence of multi-factor coupling, and the quantitative experiment method has the characteristics of balanced dispersion, orderliness and comparability and the like according to an experiment design scheme obtained by the orthogonality, the representativeness and the comprehensive comparability of an orthogonal table. Orthogonality is shown in two ways, one being that in either column, each level occurs equally many times. Second, all possible combinations of various levels between any two columns occur, and the number of occurrences is equal. The representativeness is that orthogonal experiments can be uniformly sampled, and better represents the basis of all samples. The representative main expression is in the following three aspects: (1) all possible combinations of different levels between any two columns occur and the number of pairs occurs equally. (2) All horizontal combinations of any two columns occur, making the combination of tests between any two factors a full test. (3) Because of the orthogonality of the orthogonal table, the test points of the orthogonal test are necessarily evenly distributed in the overall test points, and have extremely strong representativeness. The trend of the optimal conditions found by partial experiments and the optimal conditions found by full experiments should be consistent. Comprehensive comparability is expressed in that the occurrence times of each level in any column are equal; the occurrence times of all horizontal combinations between any two columns are equal, so that the test conditions of each level of any one factor are the same. This ensures that interference from other factors is maximally excluded in the effect of each level of factors in each column. Therefore, the influence of different levels of the factor on the test indexes can be comprehensively compared.
The invention is further described with reference to the following figures and examples.
Drawings
FIG. 1 is a flow chart of a quantitative experimental method for shale physical property response under the influence of multi-factor coupling according to an embodiment of the invention;
FIG. 2 is a schematic diagram of an orthogonal experiment point selection of a quantitative experiment method for shale physical property response under the influence of multi-factor coupling according to an embodiment of the invention;
FIG. 3 is a cross-sectional view of the longitudinal and transverse wave anisotropy parameter, the anisotropy Young's modulus parameter, the brittleness parameter and the clay content of a quantitative test method of shale physical property response under the influence of multi-factor coupling according to an embodiment of the present invention;
FIG. 4 is a cross-sectional view of the longitudinal and transverse wave anisotropy parameter, the anisotropy Young's modulus parameter, the brittleness parameter and the organic matter content of a quantitative test method of shale physical property response under the influence of multi-factor coupling according to an embodiment of the present invention;
fig. 5 is a cross-sectional view of the longitudinal and transverse wave anisotropy parameter, the anisotropy young's modulus parameter, the brittleness parameter and the pressure of the quantitative experiment method for shale physical property response under the influence of multi-factor coupling according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Examples
A quantitative experiment method for shale physical property response under the influence of multi-factor coupling is disclosed, the specific flow is shown in figure 1, and the method comprises the following steps:
s1: establishing the physical property of the shale to be researched, and determining the induction factors and the quantity (fixed factors) influencing the physical property of the shale aiming at the physical property;
the elastic property of the shale is selected as a research target, physical parameters which can characterize the physical properties are further determined after the research target is established, and the longitudinal and transverse wave anisotropy parameter, the Young modulus anisotropy parameter and the brittleness parameter are selected as indexes for measuring the experimental results in the example.
The calculation formula of each elastic parameter is as follows:
longitudinal wave anisotropy parameters:
transverse wave anisotropy parameters:
in the above formula: vP(90°)VP(90°)，VP(0°)VP(0 °) represents the longitudinal wave velocities in the parallel and perpendicular bedding directions, VSH(90°)VSH(90°)，VSH(0°)VSH(0°)VSH(0°)VSH(0 degree) respectively represents the fast transverse wave speeds in the parallel bedding direction and the vertical bedding direction, and can be obtained through ultrasonic rock physical experiment tests;
young's modulus anisotropy parameter:
wherein E11E11And E33E33The Young modulus in the parallel bedding direction and the Young modulus in the vertical bedding direction can be calculated through the longitudinal and transverse wave velocity and the shale density in the vertical bedding direction and the vertical bedding direction;
brittleness parameter:
wherein the content of the first and second substances,
respectively, normalized Young's modulus and Poisson's ratio, EmaxEmax，EminEmin，σmaxσmax，σminσminRespectively representing the maximum value and the minimum value of the Young modulus and the Poisson ratio of the shale in the research area, which can be obtained by statistical cross-over, the Young modulus and the Poisson ratioThe Poisson's ratio can be calculated by testing the longitudinal and transverse wave velocity and density of the shale experimentally.
According to the existing research and knowledge aiming at the elastic property of the shale, a main control factor influencing the elastic property of the shale is selected from a plurality of induction factors (geological diagenetic environment, clay minerals, clastic minerals, authigenic minerals and organic matters), or whether the induction factors influencing the elastic property are not clarified in the existing research is determined, the number of the selected induction factors is determined, and the requirement of subsequently selecting orthogonal determining factors is met.
S2: determining the number of the specific gravity changes of each induction factor, namely the fixed level number, according to the number of the induction factors and the coupling relation among the induction factors;
and determining the number of specific gravity changes of the induction factors based on the category and the number of the determined induction factors and the coupling relation among the factors and combining the principle of selecting a smaller orthogonal table as far as possible required by orthogonal experimental design, wherein the change numbers of the induction factors are the same. In the embodiment, the inducing factors are clay, organic matters and diagenetic pressure respectively, the change quantity of the clay content, the organic matter content and the diagenetic pressure is determined to be 4 according to the principle, the 4 is the horizontal quantity, 4 groups of ratios can be formed for subsequent modeling, and the specific gravity of each inducing factor on each level is determined in the next step.
S3: an orthogonal test design method in the mathematical statistics category is introduced, a corresponding orthogonal table is selected according to the number and the horizontal number of the determined induction factors, the specific proportion and the combination of each induction factor under each level are determined according to the orthogonal table, the proportion of shale modeling components and modeling conditions is determined, and a proper orthogonal table is selected according to the number of the induction factors and the number of the horizontal factors, namely 3 factors and 4 levels. Common orthogonal tables are: l is4(23)、L8(27)、L12(211)、L9(34)、L16(45)、L25(56) And the like. Selection principle of orthogonal table: on the premise of arranging test factors and interaction, a smaller orthogonal table is selected as much as possible to reduce the test times. The number of levels of the test factor should be equal to the number of levels in the orthogonal table; the number of columns c of the orthogonal table is more than or equal to the number of columns occupied by the factors, the number of columns occupied by the interaction and the empty columns; the total freedom (a-1) of the orthogonal table is more than or equal to the factor freedom + the interaction freedom + the error freedom; if the sum of the factors and the degrees of freedom of interaction is equal to the total degree of freedom of the selected orthogonal table, then the trial error can be estimated using a repeated orthogonal trial. L isa(bc): a is the total number of trials (number of rows); b is a factor level number; c is the factor number (column number).
And respectively arranging the inducing factors influencing the physical properties of the shale and the observed interaction at the top of each column of the orthogonal table to form the orthogonal table with a table head. If the interaction is not considered, all factors can be randomly arranged in all the rows to form a header; if the interaction is being examined, the factors and interactions should be arranged in the interaction list of the selected orthogonal table to prevent "cluttering" of the design.
Compiling a test scheme: the inducing factors are arranged in the columns of the factors in the orthogonal table (not including the interaction column to be examined) corresponding to different level values, and each level number in the orthogonal table is converted into the actual level value of the inducing factor. An orthogonal table L16 (4) was selected in this example5) Experimental design was performed to determine the specific gravity of each induction factor at each level based on the orthogonal table, and the horizontal factor table of table 1 was established for clay minerals (15%, 30%, 45%, 60%), organic matter content (14%, 12%, 10%, 8%), formation pressure (50MPa, 150MPa, 250MPa, 350 MPa).
Table 13 factor 4 horizontal shale properties orthogonal experimental design horizontal factor table
In the experimental design, the proportion of the artificial shale sample is matched according to an orthogonal table. The fixed mass of each sample is 500g, wherein the content of calcite is fixed to be 60g, and the mass accounts for 12%. A fixed amount of 25g of binder was added to each sample, 5% by mass. According to the mixture ratio in the design table, the content of the kerogen is divided into 4 levels, 40g, 50g, 60g and 70 g. Similarly, the clay content is divided into 4 levels, which are 75g, 150g, 225g and 300g respectively.
It should be noted that, in order to ensure the overall quality of the sample to be constant, the quality of the quartz is changed along with the kaolin and kerogen, so as to ensure the overall quality of the sample to be 500 g. Since the cross section of the mold is 7cm × 7cm square, the actual manufacturing pressures are approximately 25t, 75t, 125t, and 175t, respectively, by conversion from design pressures of 50MPa, 150MPa, 250MPa, and 350 MPa. On the basis, the specific proportion and combination of each induction factor under each level are determined according to an orthogonal table, and shale modeling components and modeling condition ratios are obtained (table 2).
Table 2 artificial shale 3 factor 4 horizontal orthogonal experiment
S4: taking geological conditions and physical characteristics of natural shale as geological constraints, and constructing a series of controllable artificial shale samples to be tested with component distribution ratios determined by orthogonal test design by adopting an artificial shale modeling technology based on a hot pressing method; according to the diagenetic condition, diagenetic action and physical characteristics of actual natural shale, in combination with modeling components and modeling condition ratios (table 2) determined by an orthogonal experimental design table, an artificial shale modeling technology based on a hot pressing method is adopted to construct artificial organic shale with corresponding ratios, wherein the key steps of the artificial modeling technology based on the hot pressing method are as follows:
(1) determining the mineral and diagenetic condition proportion; (2) and (3) mixing and ball milling, namely uniformly mixing the modeling minerals with different proportions by using a ball mill, wherein the ball milling adopts ball milling beads with large, medium and small sizes, and the number ratio of the ball milling beads to the modeling minerals is (10-20) to (20-25) to (80-100). The diameter range of the large ball grinding beads is 15-20 mm, the diameter range of the medium ball grinding beads is 10-15 mm, and the diameter of the small ball grinding beads is 5-10 mm. The rotating speed of the used ball mill is 350-450R/min, and the ball milling time is 36-48 h; (3) cementing, namely uniformly mixing the mixed mineral components with a binder, wherein the mixed powder and the binder are mixed in a manual grinding and sieving mode, and after uniform mixing, a mixed material is obtained, so that more than 99% of the mixed material can pass through a 300-mesh sieve; (4) filling the mixture into a mold, laying the mixture layer by layer into a hot-pressing mold, and performing pre-compaction treatment after laying each layer of the mixture for 4-6 times to obtain the mold filled with the mixture, wherein the mold is cleaned and/or wiped clean and coated with thin vaseline and/or silicone oil; (5) pre-compacting and hot-press molding, namely flatly paving the mixed material in a mold, then placing a pressure head, knocking the top surface of the pressure head for hundreds of times (capable of using a rubber hammer to knock with great force), bearing the pressure of 5-20 MPa on the mixed material, and maintaining the pressure for 0.4-1 h; and then heating and pressurizing, and carrying out heat preservation and pressure maintaining treatment, wherein the heat preservation and pressure maintaining time is 3600-5760 min.
According to the artificial organic shale modeling process based on the hot pressing method, 16 artificial shale samples to be tested are manufactured in combination with the determined orthogonal experimental design table (table 2).
S5: and testing the physical properties of the established rock sample through a rock experiment, and decoupling the quantitative influence relation of different influence factors on the physical properties by adopting a mathematical statistics method based on the tested experimental data.
Based on a series of constructed artificial shale samples with known induction factor specific gravity, the characteristics of physical properties of a research target and a corresponding theoretical derivation equation are combined, a targeted rock experimental test is performed, the research target of the example is shale elastic properties, including longitudinal and transverse wave anisotropy parameters, Young modulus anisotropy parameters and brittleness parameters, the density of the corresponding shale and the longitudinal and transverse wave speeds in the vertical and parallel bedding directions are required to be obtained by combining the transverse isotropy characteristics of the shale and a corresponding parameter calculation formula, and the ultrasonic pulse transmission method experimental acquisition can be performed, wherein an ultrasonic pulse transmission method test system comprises an oscilloscope, a signal generator, a signal amplifier, an ultrasonic transducer and a computer, and the main frequency of the ultrasonic transducer is megahertz. The corresponding elastic parameters of the series of samples were obtained by ultrasonic testing and the calculation formula described above (table 3).
TABLE 3 results of the experiment
Analyzing the influence of a certain induction factor on the physical properties of the shale at different levels. Taking three-factor three-level as an example, the schematic diagram of the orthogonal experiment point selection is shown in fig. 2, and the influence of each level of the factor a in table 1 on the test index is analyzed: it can be seen that the effect of a1 is reflected in trials nos. 1, 2 and 3, the effect of a2 is reflected in trials nos. 4, 5 and 6, and the effect of A3 is reflected in trials nos. 7, 8 and 9. The sum of the test indexes corresponding to the level 1 of the factor A is as follows:
the sum of the test indexes corresponding to the 2 levels of the factor A is:
the sum of the test indexes corresponding to the 3 levels of the factor A is:
different level indicators for the remaining factors were also calculated using the same method. (since the levels of factor A included B, C at 3 levels in the 9 level combinations, although the collocation was different, B, C was equally positioned, when comparing the levels of factor A, the effects of the levels of factor B cancelled each other, and the effects of the levels of factor C cancelled each other. therefore, there was overall comparability between 3 levels of factor A. similarly, there was overall comparability between 3 levels of factor B, C.)
In the examples, the influence of each of the three factors on the test index was analyzed based on the calculated results of the longitudinal and transverse wave anisotropy, young's modulus, and brittleness factor, and the influence of clay content level 1 (15%) was reflected in tests E1, E2, E3, and E4, the influence of clay content level 2 (30%) was reflected in tests E5, E6, E7, and E8, and the influence of clay content level 3 (45%) was reflected in tests E9, E10, E11, and E12. The effect of clay content level 4 (60%) is reflected in trials No. E11, E12, E13, E14; the sum of the test indexes corresponding to a level of 1 of the clay content is:
the sum of the test indexes corresponding to 2 levels of clay content is:
the sum of the test indexes corresponding to 3 levels of clay content is:
the sum of the test indexes corresponding to 4 levels of clay content is:
the different level indicators for the remaining factors were also calculated using the same method to obtain single factor impact values, given by table 5:
TABLE 5 statistical table of single factor influence values
Effect analysis of the present embodiment:
the four samples E1, E2, E3 and E4 reflect the influence of the clay content of 15%, and the differences between the clay content of 15% and the epsilon, gamma and Bmax of the 4 samples are averaged to obtain the range of the clay content of 15%, which is considered to represent the influence of the clay content of 15% on the epsilon, gamma, the anisotropic young modulus parameter and the Bmax value. Similarly, according to the above logic, we can calculate the influence of 3 factors on each value of epsilon, gamma and Bmax under 4 levels.
Shale has four properties: the longitudinal wave anisotropy, the transverse wave anisotropy, the anisotropic Young modulus parameter and the brittleness value are respectively matched with 3 factors in the experimental design: the clay content, kerogen and pressure level were crossed to obtain 12 sets of experimental panels, as shown in fig. 3-5.
In comparison of clay mineral characteristics, it is found that the anisotropy degree of longitudinal wave and transverse wave decreases slowly with the increase of clay mineral. This conclusion is somewhat different from the previous knowledge. From the standpoint of rock physics, it is believed that rocks are composed primarily of particles and pores, without regard to pore fillers. Thus, the type, proportion, and interaction of the particles and pores determine the primary properties of the rock. The experimental process of artificial shale production is essentially that particles and pores are controlled by a geophysical method according to a diagenesis process in geology so as to achieve the purpose of simulating a natural sample. From this point of view, the selection and matching of particles is more important, because the final state of the particles directly affects the size and properties of the pores during the physical simulation. The degree of anisotropy is determined by the orientation of the particles in combination with the orientation of the pores. The clay powder particles are much smaller than the quartz particles with respect to the quartz crystals and more often exist as a filler of pores, so that the directionally arranged pores are blocked with the increase of the clay powder, resulting in a decrease in the degree of the overall anisotropy.
Meanwhile, due to the argillaceous property of clay minerals, the elastic modulus is small, and the Young modulus and brittleness are affected along with the increase of the content. Therefore, the clay mineral is considered as an unstable factor in shale reservoir modification, and especially when the content of the water-sensitive clay mineral is high, the dissolution of the clay mineral is easy to promote the blockage of a fracture channel for gas production of shale, thereby influencing the production of shale gas. Therefore, the higher the clay content is, the more adverse to the modification of the reservoir. In addition, the well drilling process is easy to cause the occurrence of borehole wall collapse accidents due to the existence of clay minerals, and the clay minerals are dissolved in water and cause the borehole wall collapse to be a main problem in shale reservoir well completion.
Kerogen is a dispersed organic matter in sedimentary rock that is insoluble in alkalis, non-oxidizing acids, and non-polar organic solvents. In the intersection of kerogen with the velocity of longitudinal waves and transverse waves, the anisotropy degree of the longitudinal waves and the transverse waves of the shale is effectively improved along with the increase of the content of the kerogen. For analysis reasons, on one hand, micropores and microcracks are widely distributed on the surface of the organic carbon and are main gathering spaces for adsorbing gas, and meanwhile, the directional arrangement of the pores and the fissures can effectively increase the anisotropy degree of the shale.
During the experimental preparation process, the selected kerogen with higher maturity is gradually converted into a state similar to asphaltene and between a solid state and a fluid state under the conditions of mixing, stirring and long-term pressurization. Therefore, in this state, the increase in the kerogen amount significantly lowers the elastic modulus, and the young's modulus and brittleness may be significantly reduced.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A quantitative experiment method for shale physical property response under the influence of multi-factor coupling is characterized by comprising the following steps:
s1: establishing physical properties of the shale to be researched, and determining induction factors and quantity influencing the physical properties of the shale aiming at the physical properties;
s2: determining the number of the specific gravity changes of each induction factor, namely the fixed level number, according to the number of the induction factors and the coupling relation among the induction factors;
s3: introducing an orthogonal test design method in the mathematical statistics category, selecting a corresponding orthogonal table according to the quantity and the horizontal quantity of the determined induction factors, determining the specific proportion and combination of each induction factor under each level according to the orthogonal table, and determining the proportion of shale modeling components and modeling conditions;
s4: taking geological conditions and physical properties of natural shale as geological constraints, and constructing a series of controllable artificial shale samples to be tested with components and condition ratios determined by orthogonal test design by adopting an artificial shale modeling technology based on a hot pressing method;
s5: and testing the physical properties of the established rock sample through a rock experiment, and decoupling the quantitative influence relation of different influence factors on the physical properties by adopting a mathematical statistics method based on the tested experimental data.
2. The quantitative experimental method of multifactor coupling influence of shale physical property response as claimed in claim 1, wherein the physical properties comprise elastic properties, electrical properties and mechanical properties; the elastic properties include anisotropy, brittleness, modulus, impedance, and speed; the electrical properties include resistivity and polarizability; the mechanical properties include Young's modulus, Poisson's ratio, and compressive strength.
3. The quantitative experimental method for multi-factor coupling influence on physical property response of shale as claimed in claim 1, wherein the inducing factors influencing the physical property of shale comprise geological diagenetic environment, clay minerals, clastic minerals, authigenic minerals and organic matters; the diagenetic environment comprises diagenetic pressure, diagenetic temperature and diagenetic time; the clay minerals include kaolinite, illite, montmorillonite, hydromica, and beidellite; the clastic minerals comprise quartz, feldspar, mica and calcite; the authigenic minerals include oxides and hydroxides of iron, aluminum, and manganese; the organic matter includes bitumen and kerogen.
4. The quantitative experimental method for shale physical property response under multi-factor coupling influence according to claim 3, wherein the specific gravity of the induction factors comprises content percentages of different components, different diagenesis pressures and different diagenesis temperatures.
5. The quantitative experimental method for shale physical property response under multi-factor coupling influence according to claim 1, wherein the selection principle of the orthogonal table is as follows: on the premise that test factors and interaction can be arranged, a smaller orthogonal table is selected, the situation of a full test is known through partial test analysis, and then an optimal horizontal combination is found.
6. The method for quantitative experiment of shale physical property response under multi-factor coupling influence of claim 1, wherein the number of levels of test factors in S3 is equal to the number of levels in an orthogonal table; the number of columns c of the orthogonal table is more than or equal to the number of columns occupied by the factors, the number of columns occupied by the interaction and the empty columns; the total freedom (a-1) of the orthogonal table is more than or equal to the factor freedom + the interaction freedom + the error freedom; if the sum of the factors and the degrees of freedom of interaction is equal to the total degree of freedom of the selected orthogonal table, the repeated orthogonal test is adopted to estimate the test error.
7. The quantitative experimental method for influence of multifactor coupling on physical property response of shale as claimed in claim 1, wherein the artificial shale sample in S4 is constructed according to the following principle: physical parameters, mechanical characteristics, seismic characteristics, microstructures and diagenetic conditions of various rocks are similar to those of natural shale.
8. The quantitative experimental method of multifactor coupling influence on shale physical property response as claimed in claim 1, wherein the rock experimental test in S5 comprises rock physical test and rock mechanics test; the rock physical test comprises an ultrasonic test, a differential resonance spectrum test, a low-frequency rock physical test and a resistivity test under a stratum environment; the rock mechanics test comprises a uniaxial compression experiment and a triaxial compression experiment under the uniaxial stratum environment.
9. The quantitative experimental method for shale physical property response under multi-factor coupling influence according to claim 1, wherein the mathematical statistics method comprises range analysis and variance analysis.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104198243A (en) * | 2014-08-29 | 2014-12-10 | 中国石油天然气股份有限公司 | Preparation method of artificial rock core for simulating permafrost region hydrate stratum skeleton |
| CN104569344A (en) * | 2014-12-31 | 2015-04-29 | 长江大学 | Shale reservoir brittle mineral earthquake quantitative characterization method |
| CN104832166A (en) * | 2015-03-20 | 2015-08-12 | 中国石油化工股份有限公司江汉油田分公司勘探开发研究院 | Initial productivity prediction method of shale gas horizontal well |
| CN105601169A (en) * | 2015-12-16 | 2016-05-25 | 中国石油大学(北京) | Production method of hot-pressing-based kerogen-containing shale physical model and shale model |
| US20170067836A1 (en) * | 2015-09-03 | 2017-03-09 | Saudi Arabian Oil Company | Nano-level evaluation of kerogen-rich reservoir rock |
| CN107153096A (en) * | 2017-06-23 | 2017-09-12 | 中国石油大学(北京) | Shale reservoir into seam aptitude tests method and device |
| CN107167481A (en) * | 2017-06-05 | 2017-09-15 | 中国地质调查局油气资源调查中心 | The analysis method that a kind of impact shock influences on shale physical parameter |
| US20180030815A1 (en) * | 2015-03-31 | 2018-02-01 | Halliburton Energy Services, Inc. | Simplified geomechanical model of stresses on an orthorhombic media |
| CN109669424A (en) * | 2019-01-10 | 2019-04-23 | 清华大学 | A kind of complex condition material properties of rock experiment control system and method |
| CN109916754A (en) * | 2019-02-26 | 2019-06-21 | 成都理工大学 | A kind of reservoir brittleness evaluation method based on landwaste microscopic feature and drilling parameter |
| CN110244023A (en) * | 2019-07-02 | 2019-09-17 | 西南石油大学 | The measuring method that the physical analogy of seam full-hole core is combined with numerical simulation |
| CN110909486A (en) * | 2019-12-06 | 2020-03-24 | 西南石油大学 | Method for establishing orthotropic shale rock physical model |
| CN111239817A (en) * | 2020-02-05 | 2020-06-05 | 成都理工大学 | Method for improving fault likelihood attribute analysis precision |
-
2020
- 2020-11-10 CN CN202011257217.2A patent/CN112485401A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104198243A (en) * | 2014-08-29 | 2014-12-10 | 中国石油天然气股份有限公司 | Preparation method of artificial rock core for simulating permafrost region hydrate stratum skeleton |
| CN104569344A (en) * | 2014-12-31 | 2015-04-29 | 长江大学 | Shale reservoir brittle mineral earthquake quantitative characterization method |
| CN104832166A (en) * | 2015-03-20 | 2015-08-12 | 中国石油化工股份有限公司江汉油田分公司勘探开发研究院 | Initial productivity prediction method of shale gas horizontal well |
| US20180030815A1 (en) * | 2015-03-31 | 2018-02-01 | Halliburton Energy Services, Inc. | Simplified geomechanical model of stresses on an orthorhombic media |
| US20170067836A1 (en) * | 2015-09-03 | 2017-03-09 | Saudi Arabian Oil Company | Nano-level evaluation of kerogen-rich reservoir rock |
| CN105601169A (en) * | 2015-12-16 | 2016-05-25 | 中国石油大学(北京) | Production method of hot-pressing-based kerogen-containing shale physical model and shale model |
| CN107167481A (en) * | 2017-06-05 | 2017-09-15 | 中国地质调查局油气资源调查中心 | The analysis method that a kind of impact shock influences on shale physical parameter |
| CN107153096A (en) * | 2017-06-23 | 2017-09-12 | 中国石油大学(北京) | Shale reservoir into seam aptitude tests method and device |
| CN109669424A (en) * | 2019-01-10 | 2019-04-23 | 清华大学 | A kind of complex condition material properties of rock experiment control system and method |
| CN109916754A (en) * | 2019-02-26 | 2019-06-21 | 成都理工大学 | A kind of reservoir brittleness evaluation method based on landwaste microscopic feature and drilling parameter |
| CN110244023A (en) * | 2019-07-02 | 2019-09-17 | 西南石油大学 | The measuring method that the physical analogy of seam full-hole core is combined with numerical simulation |
| CN110909486A (en) * | 2019-12-06 | 2020-03-24 | 西南石油大学 | Method for establishing orthotropic shale rock physical model |
| CN111239817A (en) * | 2020-02-05 | 2020-06-05 | 成都理工大学 | Method for improving fault likelihood attribute analysis precision |
Non-Patent Citations (11)
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