Deep coal seam coal facies type classification method considering industrial component content

Abstract

The application discloses a deep coal seam coal facies type division method considering industrial component content, and relates to the technical field of unconventional reservoir exploration and development. The method comprises the following steps: obtaining a target coal sample in a research area, respectively performing industrial component testing and submicroscopic component identification and determination on the target coal sample, and calculating coal facies parameters according to actual submicroscopic component content; then performing correlation analysis on the coal facies parameters, and discussing the repeatability of coal facies characteristics under different coal facies parameters; screening out key coal facies parameters through the correlation between the coal facies parameters, and dividing coal facies basic types by using a coal facies parameter crossplot; and finally considering the content differences of ash content, moisture content, volatile content and fixed carbon in the industrial components in the coal facies and the influence on micropores, further refining the coal facies types, which is beneficial to subsequent construction of the deep coal seam coal facies type division method, and provides a good data basis and type division idea.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unconventional reservoir exploration and development, and particularly relates to a deep coal seam coal facies type classification method considering industrial component content. BACKGROUND

[0002] Deep coalbed methane has the advantages of large coal seam thickness, low to medium metamorphic degree, high free gas content, and simple coal structure. These characteristics make the gas production of deep coalbed methane exceed 10 4 m 3 , marking a major breakthrough in the exploration and development of deep coalbed methane in China. Therefore, deep coalbed methane has become the most important unconventional energy in China. The early high production of deep coalbed methane is affected by the free gas content. However, the key to realizing stable high-yield gas production in the later stage depends on the adsorbed gas content. Studies have shown that there are significant differences in pore structure at different depths in relatively thick coal seams, mainly affected by coal facies. This pore structure heterogeneity leads to significant differences in adsorbed gas and free gas content in the same coal seam. Therefore, studying the influence of coal facies on the adsorption process and adsorption capacity of deep coalbed methane is the key to realizing sustained high production of deep coalbed methane.

[0003] The current coal facies is generally classified based on the intersection of coal facies parameters. However, based on the conventional coal facies type classification method, there are still significant differences in pore structure in the same coal facies of deep coal seams. Therefore, the conventional coal facies type classification is not conducive to optimizing deep favorable coal facies and finding sweet spot areas.

[0004] In summary, the existing technology has established a coal facies type classification method. However, there are still the following problems: (1) related studies have proposed various coal facies parameters, and the applicability of different coal facies parameters to different coal facies characteristics needs further study. (2) Related results show that there is a relationship between industrial components and micropores, and micropores restrict the adsorptivity of deep coalbed methane and the sustained high production of deep coalbed methane. Therefore, a deep coal seam coal facies type classification method considering industrial component content needs to be studied.

[0005] Therefore, the prior art still needs to be further improved. SUMMARY

[0006] The purpose of the present application is to provide a deep coal seam coal facies type classification method considering industrial component content, which verifies the rationality and necessity of the deep coal seam coal facies type classification method considering industrial component content.

[0007] In order to achieve the above purpose, the following technical scheme is adopted in the present application:

[0008] A deep coal seam coal facies type classification method considering industrial component content, comprising the following steps in sequence:

[0009] S1, obtaining a target coal sample in a study area, respectively performing industrial component testing and submicroscopic component identification and determination on the target coal sample, calculating coal facies parameters according to actual submicroscopic component content, the coal facies parameters mainly including a tissue structure preservation index TPI, a vegetation index VI, a gelation index GI, a mirror-inert ratio V / I, a groundwater flow influence index GWI and a bone base ratio F / M;

[0010] S2, performing correlation analysis on the coal facies parameters selected in S1, and discussing the repeatability of the coal facies characteristics under different coal facies parameters.

[0011] S3, removing the characteristic parameters with repeated coal facies characteristics, respectively discussing the correlation between the tissue structure preservation index TPI, the gelation index GI and the groundwater flow influence index GWI and other coal facies parameters, and through the correlation analysis, it is determined that the three parameters of TPI, GI and GWI are standard parameters for coal facies division; the formulae used are (1), (2) and (3):

[0012]

[0013] In formulae (1), (2) and (3), Te is the homogeneous vitrinite content; T is the structural vitrinite content; F is the fusinite content; Sf is the semifusinite content; De is the matrix vitrinite content; Ma is the coarse grain content; Id is the inertodetrinite content; V is the vitrinite group content; G is the gelinite content; Co is the clumpy vitrinite content; CM is the mineral content; and Vd is the vitrodetrinite content.

[0014] S4, discussing the content difference of ash, moisture, volatile matter and fixed carbon in the coal facies and the influence on the micropore through the industrial component test results obtained in S1.

[0015] S5, increasing the ash content index according to the fact that the ash content is the most different in the same coal facies and has the strongest influence on the micropore, and further refining the coal facies type division.

[0016] The above-mentioned deep coal seam coal facies type division method considering the industrial component content, in S1, the coal facies parameters are based on three coal facies division indexes of vegetation type, water covering degree and swamp evolution degree, wherein the tissue structure preservation index TPI and the vegetation index VI are used to divide the vegetation type, the gelation index GI and the mirror-inert ratio V / I are used to distinguish the water covering degree, and the groundwater flow influence index GWI and the bone base ratio F / M are used to distinguish the swamp oxidation degree.

[0017] The above-mentioned deep coal seam coal facies type division method considering the industrial component content, in S1, the submicroscopic components of the target coal sample include structural vitrinite, homogeneous vitrinite, matrix vitrinite, clumpy vitrinite, gelinite, fusinite, semifusinite, coarse grain and inertodetrinite.

[0018] The deep coal seam coal facies type classification method considering the content of industrial components divides the vegetation type into herb and forest, divides the water covering degree into dry, wet and water covering, and divides the swamp evolution degree into low and high, wherein, when F / M>1, it represents a stagnant environment with weak water flow activity; and when F / M≤1, it represents a live water environment with strong water flow activity.

[0019] The deep coal seam coal facies type classification method considering the content of industrial components is V / I=Vitrinite Group / Inertinite Group, wherein, when V / I>4, it represents strong water covering; when 1

[0020] The deep coal seam coal facies type classification method considering the content of industrial components is S5, wherein, by discussing the difference of industrial components in the coal facies and the influence of the same on the micropore, the ash content is screened, the identification chart of TPI-GI and the ash-GWI is established, and the deep coal seam coal facies type classification is further refined.

[0021] Compared with the prior art, the present application has the following beneficial technical effects:

[0022] (1) The present application provides a deep coal seam coal facies type classification method considering the content of industrial components, which is based on the content of industrial components and submicroscopic components of a typical deep coal seam coal sample, utilizes coal facies parameter formula to calculate a plurality of different coal facies parameters, reverses the parameters of the vegetation type, water covering degree and swamp evolution degree of the coal, maximally utilizes the coal facies parameters representing the characteristics of the coal facies, avoids the repetition and tediousness of the coal facies parameters in the process of classifying the coal facies type, optimizes the coal correlation key parameters by performing correlation analysis on a plurality of coal facies parameters, and simplifies the coal facies type classification method.

[0023] (2) The present application performs correlation analysis by considering the influence of the content of industrial components on the micropore volume, and the analysis shows that the ash seriously restricts the adsorption of the micropore. By the micropore characteristics and adsorption characteristics under the restriction of different ash contents, the coal facies type classification method is further refined, a deep coal seam coal facies type classification method considering the content of industrial components is formed, and the rationality and necessity of the deep coal seam coal facies type classification method considering the content of industrial components are further verified by the difference analysis of the micropore volume of the wet herb swamp facies based on the ash content. BRIEF DESCRIPTION OF DRAWINGS

[0024] The present application will be further described below in combination with the drawings:

[0025] Figure 1 It is a submicroscopic component type identification chart for the target coal sample of the embodiment of the present application.

[0026] Figures 2 to 6 Figure for correlation of coal facies parameters for the embodiment of the present application. Figure 2 a shows the correlation of TPI-GI-VI, b shows the correlation of TPI-V / I-F / M, c shows the correlation of GI-VI-GWI, d shows the correlation of GI-V / I-F / M, and e shows the correlation of GWI-V / I-F / M.

[0027] Figure 7 TPI-GI coal facies parameter cross plot for the embodiment of the present application.

[0028] Figures 8 to 11 Correlation figure of industrial component content and micropore volume for the embodiment of the present application.

[0029] Figure 12 Division chart of deep coal seam high position herbaceous swamp facies considering ash content for the embodiment of the present application.

[0030] Figure 13 、 Figure 14 Micropore volume difference figure of high position humid herbaceous swamp considering ash content for the embodiment of the present application.

[0031] Figure 15 Flow chart of the method of the present application. DETAILED DESCRIPTION

[0032] The present application discloses a deep coal seam coal facies type division method considering industrial component content.

[0033] The present application discloses a deep coal seam coal facies type division method considering industrial component content. Figure 15 The method specifically comprises the following steps:

[0034] S1, identify and determine the content of submicroscopic component types by submicroscopic optical metering, including structural vitrinite, homogeneous vitrinite, matrix vitrinite, clumpy vitrinite, colloid vitrinite, fusinite, semifusinite, coarse grain, and clastic inertinite; and calculate coal facies parameters according to actual submicroscopic component content.

[0035] S2, select six coal facies parameters, respectively, the organization structure preservation index TPI, vegetation index VI, gelation index GI, mirror inertia ratio V / I, groundwater flow influence index GWI, bone base ratio F / M six coal facies parameters, analyze, the analysis mainly includes the division of vegetation type (herb and forest), water covering degree (dry, wet and water covering) and marsh evolution degree (low and high); TPI is low, indicating that the degradation intensity is high, and the structure preservation is poor; TPI is higher, indicating that the degradation intensity is low, and the plant cell is well preserved. High VI indicates forest swamp of woody plants, and low VI indicates lake environment dominated by herbaceous plants. If the peat is formed in a relatively dry environment, the GI value is lower. V / I>4 represents strong water covering; 1

[0036] S3, based on the above coal facies parameters, the correlation analysis of TPI (organization structure preservation index), GI (gelation index) and GWI (groundwater flow influence index) and other coal facies parameters is carried out respectively, and the key factors for dividing the basic type of coal facies are determined through correlation analysis, so as to provide data basis for subsequent fine division of coal facies;

[0037] The formulae used are (1), (2) and (3):

[0038]

[0039] In formulae (1), (2) and (3), Te is the content of homogeneous vitrinite; T is the content of structural vitrinite; F is the content of fusinite; Sf is the content of semifusinite; De is the content of matrix vitrinite; Ma is the content of coarse grain; Id is the content of inertinite; V is the content of vitrinite group; G is the content of gel vitrinite; Co is the content of clump vitrinite; CM is the content of mineral; and Vd is the content of vitrodetrinite.

[0040] S4, considering the influence of industrial components on the division of coal facies, the content difference of ash, moisture, volatile matter and fixed carbon in coal facies and the influence on micropore are discussed.

[0041] S5, according to the fact that the ash content is the most different in the same coal facies and has the strongest influence on micropore, the ash content index is added, and the fine division of coal facies type is further improved.

[0042] The application will be further described below in combination with specific examples.

[0043] Example 1:

[0044] Taking eight wells of Nalinhe-Suide block deep coal bed gas, namely, Tai11H, Qi32, Mi172, Jin32, Jin26, Qi85, Qi35 and Bu15 as examples.

[0045] The method comprises the following steps:

[0046] Step one: the identification of the submicroscopic component type and the determination of the content are carried out through the submicroscopic optical meter, including the structural vitrinite, the homogeneous vitrinite, the matrix vitrinite, the lump vitrinite, the gel vitrinite, the fusinite, the semifusinite, the coarse grain and the detrital inertinite. Figure 1 As shown in the formula (1), the formula (2) and the formula (3), Figure 1 is the identification diagram of the submicroscopic component type of the target coal sample.

[0047] Step two: the six coal facies parameters of the target coal sample in the research area, including the organization structure preservation index TPI, the vegetation index VI, the gelation index GI, the vitrinite-inertinite ratio V / I, the groundwater flow influence index GWI and the bone base ratio F / M are analyzed.When TPI>1 or VI>1, it represents the forest swamp of the woody plants; when TPI<1 or VI<1, it represents the lake environment mainly with the herbaceous plants. When V / I>4, it represents the strong water covering; when 1<V / I≤4, it represents the extremely wet-water covering; when 0.25<V / I≤1, it represents the wet-weak water covering; when GWI<1, it represents the high-position peat bog. When F / M>1, it represents the stagnant environment with weak water flow activity; when F / M≤1, it represents the live water environment with strong water flow activity, as shown in Table 1.

[0048] Table 1

[0049]

[0050]

[0051] Step three: the correlation analysis is carried out based on the above coal facies parameters, and the correlation analysis of the organization structure preservation index TPI, the gelation index GI and the groundwater flow influence index GWI with other coal facies parameters is carried out. As shown in the formula (1), the formula (2) and the formula (3), the key factors of the division of the basic types of the coal facies are determined through the correlation analysis, and the data basis for the subsequent fine division of the coal facies is provided. Figures 2 to 6 The formula (1), the formula (2) and the formula (3) are used.

[0052]

[0053]

[0054] In formula (1), (2), (3): Te is the homogeneous vitrinite content; T is the structural vitrinite content; F is the fusinite content; Sf is the semifusinite content; De is the degradative vitrinite content; Ma is the macroinite content; Id is the inertodetrinite content; V is the vitrinite group content; G is the gelinite content; Co is the collinite content; CM is the mineral content; Vd is the vitrodetrinite content;

[0055] The target deep coal samples in the research area have a GWI of less than 1, indicating that the high-position peat bog is generally developed in the research area; therefore, the key coal facies parameters of the research area are TPI-GI, as shown in Figure 7

[0056] Step four, considering the influence of industrial components on the division of coal facies, the content differences of ash, moisture, volatile matter, fixed carbon in the coal facies and the influence on micropores are discussed, as shown in Figures 8 to 11

[0057] Step five, according to the fact that the ash content is the most different in the same kind of coal facies and has the strongest influence on micropores, the ash content index is added to form the ash-TPI-GI coal facies type division method, which further refines the coal facies type division, and provides a data basis and idea for the perfection of the deep coal seam coal facies type division method considering the content of industrial components. Finally, the micropore pore volume difference of the humid herbaceous bog facies based on the ash content is large, which further verifies the necessity and rationality of the coal facies division type, as shown in Table 2, Figures 12 to 14

[0058] Table 2

[0059]

[0060] The parts not mentioned in the present application can be realized by referring to the prior art.

[0061] Those skilled in the art should recognize that the above embodiments are only used to illustrate the present application, and are not used as a limitation on the present application, and as long as the above embodiments are appropriately changed and changed within the scope of the spirit of the present application, the above embodiments should fall within the scope of the claims of the present application.​​​

Claims

1. A method for dividing coal facies types of deep coal seams considering industrial component content, characterized in that, Comprise the following steps in sequence: S1, obtaining a target coal sample in a study area, performing industrial component testing on the target coal sample, identifying and determining submicroscopic components, calculating coal facies parameters according to actual submicroscopic component content, the coal facies parameters including tissue structure preservation index TPI, vegetation index VI, gelation index GI, mirror-inert ratio V / I, groundwater flow influence index GWI and bone base ratio F / M; S2, performing correlation analysis on the coal facies parameters selected in S1, and discussing the repeatability of the coal facies characteristics under different coal facies parameters; S3, eliminating the characteristic parameters with repeated coal facies characteristics, respectively discussing the correlation of tissue structure preservation index TPI, gelation index GI and groundwater flow influence index GWI with other coal facies parameters, and through correlation analysis, it is clear that TPI~GI~GWI three parameters are used as standard parameters for coal facies division; the formulas used are (1), (2) and (3): (1)； (2)； (3)； In formulas (1), (2) and (3), Te is the content of homogeneous vitrinite; T is the content of structural vitrinite; F is the content of fusinite; Sf is the content of semifusinite; De is the content of matrix vitrinite; Ma is the content of coarse grain; Id is the content of inertodetrinite; V is the content of vitrinite group; G is the content of gel vitrinite; Co is the content of clumpy vitrinite; CM is the content of mineral; and Vd is the content of mirror-inert; S4, discussing the content difference of ash, moisture, volatile matter and fixed carbon in coal facies and the influence on micropores through the industrial component test results obtained in S1; S5, increasing the ash content index according to the largest difference of ash in the same coal facies and the strongest influence on micropores, to further refine the coal facies type division.

2. The method for dividing the coal facies type of deep coal seam considering the content of industrial components according to claim 1, characterized in that: In S1, the coal facies parameters are based on three coal facies division indexes of vegetation type, water covering degree and swamp evolution degree, wherein the tissue structure preservation index TPI and the vegetation index VI are used to divide the vegetation type, the gelation index GI and the mirror-inert ratio V / I are used to distinguish the water covering degree, and the groundwater flow influence index GWI and the bone base ratio F / M are used to distinguish the swamp oxidation degree.

3. The method for dividing the coal facies type of deep coal seam considering the content of industrial components according to claim 1, characterized in that: In S1, the submicroscopic components of the target coal sample include structural vitrinite, homogeneous vitrinite, matrix vitrinite, clumpy vitrinite, gel vitrinite, fusinite, semifusinite, coarse grain and inertodetrinite.

4. The method for dividing the coal facies type of deep coal seam considering the content of industrial components according to claim 2, characterized in that: The vegetation type is divided into herb and forest, the water covering degree is divided into dry, wet and water covering, and the swamp evolution degree is divided into low and high, when F / M>1, it represents a stagnant environment with weak water flow activity; when F / M≤1, it represents a live water environment with strong water flow activity.

5. The method for dividing the coal facies type of deep coal seam considering the content of industrial components according to claim 4, characterized in that: V / I=vitrinite group / inertinite group, when V / I>4, it represents strong water covering; when 1 6. The method for dividing the coal facies type of deep coal seam considering the content of industrial components according to claim 1, characterized in that: In S5, by discussing the difference of industrial components in coal facies and its influence on micropores, the ash content is selected, and the identification chart of TPI~GI and ash~GWI is established to further refine the coal facies type division of deep coal seams.

Images