Deep coal seam coal phase type division method considering industrial component content

Abstract

The invention discloses a deep coal seam coal phase type division method considering industrial component contents, 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 carrying out industrial component testing and submicroscopic component identification and determination on the target coal sample, and calculating coal phase parameters according to the actual submicroscopic component content; performing correlation analysis on the coal phase parameters, and discussing the repeatability of representing the coal phase characteristics under different coal phase parameters; key coal phase parameters are screened out through correlation among the coal phase parameters, and coal phase basic types are divided out through a coal phase parameter cross plot; finally, the content difference of ash, moisture, volatile components and fixed carbon in industrial components in the coal phase and the influence on micropores are considered, the type of the coal phase is further refined, subsequent construction of a deep coal seam coal phase type division method is facilitated, and a good data basis and a type division thought are provided for the deep coal seam coal phase type division method.

Description

Technical Field

[0001] The present invention relates to the technical field of unconventional reservoir exploration and development, and in particular to a method for classifying coal phase types in deep coal seams taking into account the content of industrial components. Background Art

[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 China's most important unconventional energy. The early high production of deep coalbed methane is affected by the free gas content. However, the key to achieving stable high-yield gas production in the later period depends on the adsorbed gas content. Studies have shown that in thicker coal seams, there are significant differences in pore structure at different depths, which are mainly affected by the coal phase. This heterogeneity of pore structure leads to significant differences in the content of adsorbed gas and free gas in the same coal seam. Therefore, studying the influence of coal phase on the adsorption process and adsorption capacity of deep coalbed methane is the key to achieving sustained high production of deep coalbed methane.

[0003] At present, coal phases are generally divided based on coal phase parameter cross plots. However, based on the conventional coal phase type classification method, the same coal phase in deep coal seams still has large differences in pore structure. Therefore, conventional coal phase type classification is not conducive to optimizing deep favorable coal phases and finding sweet spots.

[0004] In summary, the existing technology has established a method for classifying coal phase types. However, the following problems still exist: (1) Related studies have proposed various coal phase parameters, and the applicability of different coal phase parameters to different coal phase characteristics needs further study. (2) Related results show that there is a relationship between industrial components and micropores. Micropores restrict the adsorption of deep coalbed methane and restrict the continuous high production of deep coalbed methane. Therefore, the method for classifying deep coal phase types considering the content of industrial components needs to be studied.

[0005] This shows that the prior art needs to be further improved. Summary of the invention

[0006] The purpose of the present invention is to provide a method for classifying coal phase types of deep coal seams taking into account the content of industrial components, which verifies the rationality and necessity of the method for classifying coal phase types of deep coal seams taking into account the content of industrial components.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A method for classifying coal phase types of deep coal seams taking into account the content of industrial components comprises the following steps in sequence:

[0009] S1. Obtain target coal samples in the study area, conduct industrial component tests and submicroscopic component identification and determination on the target coal samples, and calculate coal phase parameters according to the actual submicroscopic component content. The coal phase parameters mainly include tissue structure preservation index TPI, vegetation index VI, gelation index GI, mirror inertia ratio V / I, groundwater flow influence index GWI and bone-to-base ratio F / M;

[0010] S2. Conduct correlation analysis on the coal phase parameters selected in S1 to explore the repeatability of coal phase characteristics under different coal phase parameters;

[0011] S3. Eliminate the repeated characteristic parameters of coal phase characteristics, and explore the correlation between the structure preservation index TPI, gelation index GI, groundwater flow influence index GWI and other coal phase parameters. Through correlation analysis, it can be seen that the three parameters TPI~GI~GWI are clearly defined as the standard parameters for coal phase division; the formulas used are (1), (2), (3):

[0012]

[0013] 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 silkenite; Sf is the content of semi-silky body; De is the content of matrix vitrinite; Ma is the content of coarse grains; Id is the content of inert scaffolds; V is the content of vitrinite; G is the content of colloidal vitrinite; Co is the content of agglomerated vitrinite; CM is the mineral content; Vd is the content of vitrinite;

[0014] S4. Based on the industrial component test results obtained in S1, explore the differences in the contents of ash, moisture, volatile matter, and fixed carbon in the coal phase and their effects on micropores;

[0015] S5. Based on the fact that ash content has the greatest difference in the same coal phase and has the strongest impact on micropores, the ash content index is added to further refine the classification of coal phase types.

[0016] In the above-mentioned method for classifying coal phase types of deep coal seams taking into account the content of industrial components, in S1, the coal phase parameters are based on three coal phase classification indicators: vegetation type, degree of water coverage, and degree of swamp evolution. Among them, the tissue structure preservation index TPI and the vegetation index VI are used to classify vegetation types, the gelation index GI and the mirror inertia ratio V / I are used to distinguish the degree of water coverage, and the groundwater flow influence index GWI and the bone-base ratio F / M are used to distinguish the degree of swamp oxidation.

[0017] In the above-mentioned method for classifying coal phase types of deep coal seams taking into account the content of industrial components, in S1, the submicroscopic components of the target coal sample include structural vitrinite, homogeneous vitrinite, matrix vitrinite, agglomerated vitrinite, colloidal vitrinite, silkenite, semi-silkyenite, coarse-grained body and clastic inertinite.

[0018] The above method for classifying deep coal seam lithotypes considering industrial component content classifies vegetation types into herbs and forests, water-covering degrees into dry, moist, and water-covered, and swamp evolution degrees into low-level and high-level. When F / M > 1, it represents a stagnant environment with weak water flow activity; when F / M ≤ 1, it represents an active water environment with strong water flow activity.

[0019] The above method for classifying deep coal seam lithotypes considering industrial component content, V / I = vitrinite / inertinite. When V / I > 4, it represents strong water-covering; when 1 < V / I ≤ 4, it represents extremely moist - water-covered; when 0.25 < V / I ≤ 1, it represents moist - weak water-covering.

[0020] The above method for classifying deep coal seam lithotypes considering industrial component content, in S5, by exploring the differences of industrial components in lithotypes and their effects on micropores, the ash content is screened out, and the discrimination charts of TPI ~ GI and ash ~ GWI are established to further refine the classification of deep coal seam lithotypes.

[0021] Compared with the prior art, the present invention brings the following beneficial technical effects:

[0022] (1) The present invention proposes a method for classifying deep coal seam lithotypes considering industrial component content. Based on the industrial components and submicroscopic component contents of typical deep coal seam coal samples, using the lithotype parameter formula, a variety of different lithotype parameters are calculated, truly inversing the parameters of coal vegetation type, water-covering degree, and swamp evolution degree, maximizing the use of lithotype parameters representing lithotype characteristics, avoiding the repetition and cumbersome of lithotype parameters in the process of classifying lithotype types, and by conducting correlation analysis of various lithotype parameters, optimizing the key lithotype parameters and simplifying the lithotype classification method.

[0023] (2) The present invention conducts correlation analysis by considering the influence of industrial component content on micropore volume. The analysis shows that ash severely restricts the adsorption of micropores. Through the micropore pore characteristics and adsorption characteristics under the restriction of different ash contents, the lithotype classification method is further refined, forming a method for classifying deep coal seam lithotypes considering industrial component content, and through the analysis of the difference in micropore volume of the moist herbaceous swamp facies based on ash content, the rationality and necessity of the method for classifying deep coal seam lithotypes considering industrial component content are further verified. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The following further describes the present invention with reference to the drawings:

[0025] Figure 1 It is an identification diagram of submicroscopic component types of the target coal sample in the embodiment of the present invention.

[0026] Figure 2 to Figure 6 This is a correlation diagram of target coal phase parameters in an embodiment of the present invention; Figure 2 In the figure, a shows the correlation between TPI-GI-VI, b shows the correlation between TPI-V / IF / M; c shows the correlation between GI-VI-GWI; d shows the correlation between GI-V / IF / M; and e shows the correlation between GWI-V / IF / M.

[0027] Figure 7 It is a cross-plot of TPI-GI coal phase parameters according to an embodiment of the present invention.

[0028] Figure 8 to Figure 11 Graph showing the correlation between the content of industrial components and the micropore volume of the embodiment of the present invention.

[0029] Fig.12 This is a division diagram of the high-lying herbaceous swamp phase of a deep coal seam taking into account the ash content according to an embodiment of the present invention.

[0030] Fig.13 , Fig.14 This is a graph showing the micropore volume differences of a high-lying moist herbaceous swamp taking into account the ash content according to an embodiment of the present invention.

[0031] Fig.15 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0032] The present invention discloses a method for classifying coal phase types in deep coal seams taking into account the content of industrial components. In order to make the advantages and technical solutions of the present invention clearer and more specific, the present invention is further described below in conjunction with specific embodiments.

[0033] The present invention provides a method for classifying coal phase types in deep coal seams taking into account the content of industrial components, such as Fig.15 As shown, the specific steps include:

[0034] S1. Use a submicroscopic optical meter to identify the types of submicroscopic components and determine their contents, including structural vitrinite, homogeneous vitrinite, matrix vitrinite, agglomerated vitrinite, colloidal vitrinite, silkenite, semi-silky body, coarse grain, clastic inertinite, etc. Calculate coal phase parameters based on the actual content of submicroscopic components.

[0035] S2. Select six coal facies parameters, namely the tissue structure preservation index TPI, vegetation index VI, gelification index GI, vitrinertinite ratio V / I, groundwater flow influence index GWI, and fibro-matrix ratio F / M. Analyze them. The analysis mainly includes the classification of vegetation types (herbaceous and forest), water covering degree (dry, moist, and water-covered), and swamp evolution degree (low-lying and high-lying). A low TPI indicates a high degree of degradation and poor structure preservation; a relatively high TPI indicates a low degree of degradation and well-preserved plant cells. A high VI represents a woody forest swamp, and a low VI represents a herbaceous-dominated lake environment. If the peat formation environment is moist, the GI value is relatively high; if the peat is formed in a relatively dry environment, the GI value is relatively low. V / I > 4 represents strong water covering; 1 < V / I ≤ 4 represents extremely moist - water-covered; 0.25 < V / I ≤ 1 represents moist - weakly water-covered; GWI represents the water level during the formation of the peat swamp. A high GWI usually represents stronger degradation of coal macerals and mineral input. When F / M > 1, it represents a stagnant environment with weak water flow activity; when F / M ≤ 1, it represents an active water environment with strong water flow activity.

[0036] S3. Conduct a correlation analysis based on the above coal facies parameters. Discuss the correlation analysis of TPI (tissue structure preservation index), GI (gelification index), and GWI (groundwater flow influence index) with other coal facies parameters respectively. Through the correlation analysis, clarify the key factors for classifying the basic types of coal facies, and provide a data basis for the subsequent refined classification of coal facies.

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

[0038]

[0039] In formulas (1), (2), and (3): Te is the content of homogeneous vitrinite; T is the content of structured 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 macrinite; Id is the content of inertodetrinite; V is the content of vitrinite; G is the content of gelatinous vitrinite; Co is the content of massive vitrinite; CM is the content of minerals; Vd is the content of vitrinodetrinite.

[0040] S4. Consider the influence of industrial components on the classification of coal facies, and discuss the content differences of ash, moisture, volatile matter, and fixed carbon in coal facies and their influence on micropores.

[0041] S5. Since the ash shows the largest difference in the same coal facies and has the strongest influence on micropores, add the ash content index to further refine the classification of coal facies types.

[0042] The following further illustrates the present invention with specific embodiments.

[0043] Example 1:

[0044] Taking eight wells, namely, Tai 11H, Qi 32, Mi 172, Jin 32, Jin 26, Qi 85, Qi 35, and Bu 15 in the deep coalbed methane in the Narin River-Suide Block as examples.

[0045] Using the method of the present invention, the specific steps are as follows:

[0046] Step 1: Identify the types of sub-microscopic components and determine their contents through a sub-microscopic optical meter, including sub-microscopic components such as structured vitrinite, homogeneous vitrinite, matrix vitrinite, massive vitrinite, gelatinous vitrinite, fusinite, semifusinite, macrinite, and detrital inertinite. Calculate the coal facies parameters according to the actual contents of the sub-microscopic components. As Figure 1 shown, Figure 1 is the identification map of the types of sub-microscopic components of the target coal sample.

[0047] Step 2: Analyze six coal facies parameters of the target coal sample in the study area, namely, the tissue structure preservation index TPI, vegetation index VI, gelification index GI, vitrinite-inertinite ratio V / I, groundwater flow influence index GWI, and framework matrix ratio F / M. TPI > 1 or VI > 1 indicates a woody forest swamp, and TPI < 1 or VI < 1 indicates a herb-dominated lake environment. V / I > 4 represents strong waterlogging; 1 < V / I ≤ 4 represents extremely humid - waterlogging; 0.25 < V / I ≤ 1 represents humid - weak waterlogging; GWI < 1 indicates a high-position peat swamp. When F / M > 1, it represents a stagnant environment with weak water flow activity; F / M ≤ 1 represents an active water environment with strong water flow activity, as shown in Table 1.

[0048] Table 1

[0049]

[0050]

[0051] Step 3: Conduct a correlation analysis based on the above coal facies parameters, and respectively explore the correlation analysis between the tissue structure preservation index TPI, gelification index GI, and groundwater flow influence index GWI and other coal facies parameters, as combined with Figure 2 to Figure 6 shown. Clearly define the key factors for dividing the basic types of coal facies through the correlation analysis, and provide a data basis for the refined division of coal facies in the follow-up;

[0052] The formulas used are (1), (2), and (3):

[0053]

[0054] 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 silkenite; Sf is the content of semi-silky body; De is the content of matrix vitrinite; Ma is the content of coarse grains; Id is the content of inert scaffolds; V is the content of vitrinite; G is the content of colloidal vitrinite; Co is the content of agglomerated vitrinite; CM is the mineral content; Vd is the content of vitrinite;

[0055] The GWI of deep coal samples in the study area is all less than 1, indicating that high-level peat swamps are generally developed in the study area; therefore, the key coal phase parameters of the study area are further clarified as TPI~GI, such as Figure 7 shown.

[0056] Step 4: Consider the influence of industrial components on coal phase division, explore the differences in the contents of ash, moisture, volatile matter, and fixed carbon in coal phase and their influence on micropores, such as Figure 8 to Figure 11 shown.

[0057] Step 5: Based on the fact that ash content has the greatest difference in the same coal phase and has the strongest impact on micropores, the ash content index is added to form the ash-TPI-GI coal phase type classification method, which further refines the coal phase type classification and provides a data basis and ideas for the subsequent improvement of the deep coal seam coal phase type classification method considering the content of industrial components. Finally, the micropore volume of the wet herbaceous swamp phase based on ash content is quite different, which further verifies the necessity and rationality of this coal phase classification type. Combined with Table 2, Figure 12 to Figure 14 shown.

[0058] Table 2

[0059]

[0060] Parts not described in the present invention can be implemented by referring to the existing technology.

[0061] Those skilled in the art should recognize that the above embodiments are only used to illustrate the present application and are not intended to be limiting of the present application. As long as they are within the spirit of the present application, appropriate changes and modifications to the above embodiments should fall within the scope of protection of the claims of the present application.

Claims

1. A method for classifying coal phase types in deep coal seams taking into account the content of industrial components, characterized in that: It successively includes the following steps: S1. Obtain the target coal samples in the study area, conduct industrial component tests and sub-microscopic component identification and determination on the target coal samples, calculate the coal facies parameters according to the actual sub-microscopic component content. The coal facies parameters mainly include the tissue structure preservation index TPI, vegetation index VI, gelification index GI, vitrinert ratio V / I, groundwater flow influence index GWI, and framework / matrix ratio F / M; S2. Conduct a correlation analysis on the coal facies parameters selected in S1 to explore the repeatability of the representation of coal facies characteristics under different coal facies parameters; S3. Eliminate the characteristic parameters with repeated coal facies characteristics, and respectively explore the correlations between the tissue structure preservation index TPI, gelification index GI, and groundwater flow influence index GWI and other coal facies parameters. Through the correlation analysis, it is clarified that the three parameters of TPI~GI~GWI are used as the standard parameters for coal facies division. The formulas used are (1), (2), and (3): In formulas (1), (2), and (3): Te is the content of homogeneous vitrinite; T is the content of structured vitrinite; F is the content of fusinite; Sf is the content of semi-fusinite; De is the content of matrix vitrinite; Ma is the content of macrinite; Id is the content of inertodetrinite; V is the content of vitrinite; G is the content of gelatinous vitrinite; Co is the content of massive vitrinite; CM is the content of minerals; Vd is the content of vitrinodetrinite; S4. Through the industrial component test results obtained in S1, explore the content differences of ash, moisture, volatile matter, and fixed carbon in the coal facies and their effects on micropores; S5. Since the ash content has the largest difference and the strongest influence on micropores in the same coal facies, add the ash content index to further refine the division of coal facies types.

2. A method for classifying coal phase types of deep coal seams taking into account 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 indicators: vegetation type, water-covering degree, and swamp evolution degree. Among them, the tissue structure preservation index TPI and vegetation index VI are used to divide the vegetation type, the gelification index GI and vitrinert ratio V / I are used to distinguish the water-covering degree, and the groundwater flow influence index GWI and framework / matrix ratio F / M are used to distinguish the swamp oxidation degree.

3. A method for classifying coal phase types of deep coal seams taking into account the content of industrial components according to claim 1, characterized in that: In S1, the sub-microscopic components of the target coal samples include structured vitrinite, homogeneous vitrinite, matrix vitrinite, massive vitrinite, gelatinous vitrinite, fusinite, semi-fusinite, macrinite, and detrital inertinite.

4. A method for classifying coal phase types of deep coal seams taking into account the content of industrial components according to claim 2, characterized in that: The vegetation type is divided into herbaceous and forest, the water-covering degree is divided into dry, moist, and water-covered, and the swamp evolution degree is divided into low-level and high-level. When F / M > 1, it represents a stagnant environment with weak water flow activity; when F / M ≤ 1, it represents an active water environment with strong water flow activity.

5. A method for classifying coal phase types of deep coal seams taking into account the content of industrial components according to claim 4, characterized in that: V / I = vitrinite / inertinite. When V / I > 4, it represents strong water-covering; when 1 < V / I ≤ 4, it represents extremely moist - water-covered; when 0.25 < V / I ≤ 1, it represents moist - weak water-covering.

6. The method for classifying coal phase types of deep coal seams taking into account the content of industrial components according to claim 1, characterized in that: In S5, by exploring the differences in industrial components in the coal facies and their effects on micropores, the ash content is screened out, and the discrimination charts of TPI~GI and ash~GWI are established to further refine the division of coal facies types of deep coal seams.

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