A method of coal petrology reservoir petrophysical modeling

Abstract

The present application belongs to the field of oil and gas exploration and development, unconventional and new energy technology, and discloses a method for coal rock reservoir petrophysical modeling. First, the density logging curve of the coal seam section and the coal seam interval transit time curve are corrected, and the coal seam skeleton mineral composition, coal seam porosity and coal seam water saturation are calculated. Then, the coal seam skeleton mineral equivalent model is determined through the Reuss limit model, the pore equivalent model is determined through the DEM model, and the fluid mixture equivalent model is determined through the Brie model. Finally, the coal seam petrophysical model is established. The present application is suitable for establishing the coal rock reservoir petrophysical model. After the coal seam skeleton equivalent model, the pore equivalent model and the fluid mixture equivalent model are determined, the coal rock reservoir petrophysical model is established in combination with the Gassman equation, the accurate elastic parameters and the shear wave velocity can be calculated, the petrophysical quantity version is established, the favorable reservoir type is divided, and the foundation is laid for the coal rock reservoir gas bearing property prediction.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of oil and gas exploration and development, unconventional and new energy, and particularly relates to a method for rock physics modeling of coal rock reservoirs. BACKGROUND

[0002] Coalbed methane as a new type of energy, its exploration is attracting more and more attention of many countries. Coal seam is not only the source rock of coalbed methane, but also the reservoir of coalbed methane. Finding coal seam does not necessarily mean finding effective coalbed methane reservoir, and further searching for a place conducive to the accumulation of coalbed methane is also needed. With the deepening of exploration work in recent years, the accurate identification and prediction of the gas content of coal rock reservoirs have become a very important work in the exploration of coalbed methane. At present, due to the lack of prediction technology for the gas content of coal rock reservoirs, the poor economic benefits of coalbed methane exploration and development have become the main problem restricting the exploration and development of coalbed methane in China. Although the comprehensive logging data can effectively evaluate the coal rock reservoir in the vertical direction, in the actual exploration and production, the lateral distribution and gas content characteristics of the coal rock reservoir still need to be studied.

[0003] The key to effectively identifying the gas content of coal rock reservoirs is to study the rock physics modeling method of coal rock reservoirs, reasonably and effectively estimate the S-wave velocity and elastic parameters of coal rock reservoirs, analyze the sensitive elastic parameters of gas-bearing reservoirs, establish an accurate rock physics analysis volume, and ultimately form a set of rock physics modeling method suitable for the coal rock reservoirs in the study area, providing a comprehensive and effective logging calibration basis for coal measures strata. Through the pre-stack inversion technology of seismic data, the gas content and plane distribution range of the main coal seam can be predicted, which provides a strong basis for the exploration, reserve calculation and well site deployment of the coalbed methane in the basin. Therefore, it is of great significance to study the rock physics modeling method of coal rock reservoirs. SUMMARY

[0004] The purpose of the present application is to provide a rock physics modeling method for coal rock reservoirs, which can calculate accurate elastic parameters and S-wave velocity by determining the coal seam skeleton equivalent model, pore equivalent model and fluid mixture equivalent model, and establishing a rock physics model for coal rock reservoirs based on the Gassman equation, and can divide the favorable reservoir type by establishing a rock physics volume, thereby laying a foundation for the prediction of the gas content of coal rock reservoirs.

[0005] In order to achieve the above purpose, the technical solution adopted by the present application is as follows:

[0006] A rock physics modeling method for coal rock reservoirs, comprising the following steps:

[0007] S1, logging curve correction of coal seam section

[0008] S11, density logging curve correction of coal seam section

[0009] Through the response characteristics of coal reservoir density logging, the influence of density logging by the expansion is analyzed, and the correction model of the influence of density logging curve by the expansion is established according to the relationship between the expansion and the density logging;

[0010] S12, coal seam interval acoustic travel time curve correction

[0011] According to the emission cycle of acoustic logging, the amount of acoustic travel time caused by the expansion is determined, and the correction model of the influence of acoustic travel time curve by the expansion is established;

[0012] S2, coal seam skeleton mineral component calculation

[0013] An equivalent volume model is used to equivalent the coal seam skeleton mineral component into a ternary volume model composed of carbon content, ash content and water content, and the volume of carbon content, ash content and water content in the coal seam skeleton mineral component is calculated;

[0014] The sum of the volume of carbon content, ash content and water content is 1, and the water content is the sum of matrix porosity and fracture porosity;

[0015] S3, coal seam porosity calculation

[0016] The coal seam porosity is divided into matrix porosity and fracture porosity, the fracture porosity is obtained by the resistivity curve obtained by resistivity logging, and then the matrix porosity is obtained by subtracting the fracture porosity from the volume of water content obtained in step S2 coal seam skeleton mineral component calculation;

[0017] S4, coal seam water saturation calculation

[0018] The coal seam water saturation is calculated by the Simandoux equation, and the formula of the Simandoux equation is:

[0019]

[0020] Wherein, S w is the water saturation, the value range is 0-1; R sh is the completely water-containing shale resistivity (Ω·m); R w is the formation water resistivity; V sh is the shale mass fraction, the value range is 0-1; R t is the formation resistivity (Ω·m); Фe is the effective porosity, the value range is 0-1; c, d, n are rock-electricity parameters;

[0021] S5, coal seam equivalent model determination

[0022] The coal seam skeleton mineral equivalent model is determined by the Reuss limit model and the volume of carbon content, ash content and water content in the coal seam skeleton mineral component obtained in step S2;

[0023] Determine the pore equivalent model through the DEM model and the matrix porosity and fracture porosity obtained in step S3;

[0024] Determine the fluid mixture equivalent model through the Brie model and the water saturation of the coal seam obtained in step S4;

[0025] S6, coal rock physical modeling and volume analysis

[0026] On the basis of the coal skeleton mineral equivalent model, the pore equivalent model and the fluid mixture equivalent model, a coal rock reservoir petrophysical model is established in combination with the Gassman equation;

[0027] Elastic parameters and P-wave and S-wave velocity ratio are calculated through the coal rock reservoir petrophysical model, crossplot analysis is performed on the elastic parameters, coal gas sensitive parameters are selected, a coal rock reservoir petrophysical analysis volume is established, and the coal rock reservoir type is classified.

[0028] As a limitation, in step S11, the correction model of the density logging curve affected by the hole enlargement is:

[0029] N c = N + a (D cal -D bits ) / D bits + b

[0030] Wherein, N is the value of the density logging curve before correction, N c is the value of the density logging curve after correction, D cal is the hole diameter, D bits is the drill bit diameter, and a and b are correction coefficients.

[0031] As a second limitation, in step S12, the correction model of the acoustic travel time curve affected by the hole enlargement is:

[0032] Δtc = Δt - Δ

[0033]

[0034] Wherein, Δtc is the corrected acoustic travel time, μs / m; Δt is the uncorrected acoustic travel time, μs / m; Δ is the acoustic travel time correction amount, μs / m; and ds is the difference between the measured hole diameter and the drill bit diameter, cm.

[0035] As a third limitation, the specific steps of step S2 are:

[0036] An equivalent volume model is used to equivalently form a ternary volume model composed of carbon, ash and water from the coal skeleton mineral components;

[0037] The neutron curve, the coal bed density logging curve and the coal bed acoustic wave time difference curve corrected in step S1 are used to analyze the neutron-density crossplot and the acoustic wave-density crossplot, the density value, the acoustic wave value and the neutron value of the carbon content in the skeleton mineral component of the coal bed, the density value, the acoustic wave value and the neutron value of the ash content, and the density value, the acoustic wave value and the neutron value of the moisture content are determined through the value range of the carbon content and the ash content in the area where the coal bed is located; the values are taken as the independent variables and input into the optimal logging interpretation module of the Rocklab software, the optimal logging linear equation set is solved, and the volume of the carbon content, the ash content and the moisture content in the skeleton mineral component of the coal bed is calculated.

[0038] As the fourth limitation, in step S3, the formula for calculating the fracture porosity by obtaining the resistivity curve through resistivity logging is:

[0039]

[0040] wherein, PHIF is the fracture porosity; R d is the deep lateral resistivity, Ω·m; R s is the shallow lateral resistivity, Ω·m; R w is the formation water resistivity, Ω·m; R wf is the formation free water resistivity, Ω·m; m is the cementation factor; R mf is the mud filtrate resistivity, Ω·m.

[0041] As the fifth limitation, in step S6, when the ratio of the compressional wave velocity to the shear wave velocity is greater than or equal to 1.8 and less than 2.05, the coal bed gas belongs to the Ⅰ type reservoir; when the ratio is greater than or equal to 2.05 and less than 2.25, the coal bed gas belongs to the Ⅱ type reservoir; and when the ratio is greater than or equal to 2.25, the coal bed gas belongs to the Ⅲ type reservoir.

[0042] Compared with the prior art, the technical progress achieved by the present application lies in that:

[0043] (1) The present application establishes the petrophysical model of the coal rock reservoir by determining the coal bed skeleton equivalent model, the pore equivalent model and the fluid mixture equivalent model and combining the Gassman equation, accurate elastic parameters and shear wave velocity can be calculated, the favorable reservoir type can be divided by establishing the petrophysical quantity version, and the foundation for the coal rock reservoir gas content prediction is laid;

[0044] (2) The present application selects the coal bed gas sensitive parameters by the crossplot analysis of the elastic parameters, establishes the petrophysical analysis quantity version of the research area coal bed gas, provides reliable elastic parameters for the pre-stack forward modeling and pre-stack inversion, is favorable for the analysis of the seismic response characteristics of the coal rock reservoir, and thus guides the reservoir prediction work;

[0045] (3) The present application predicts the main coal seam favorable area through pre-stack simultaneous inversion, improves the identification precision of reservoir gas content, and the coincidence degree of the inversion result and the known well is 86.7% on average, which provides a reliable basis for the next well site deployment;

[0046] (4) The present application provides a basis and reference for subsequent coal rock reservoir exploration, reserve calculation, trap identification and evaluation, target optimization and the like, and improves the drilling success rate.

[0047] The present application belongs to the field of oil and gas exploration and development, unconventional and new energy technology, and is suitable for establishing a coal rock reservoir rock physics model. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 The method flowchart of the embodiment of the present application is shown in the figure;

[0049] Figure 2 The relationship curve between the coal seam density change amount and the expansion rate in the embodiment of the present application is shown in the figure;

[0050] Figure 3 The comparison chart before and after the correction of the acoustic travel time curve and the density logging curve in the embodiment of the present application is shown in the figure;

[0051] Figure 4 The neutron-density crossplot in the embodiment of the present application is shown in the figure;

[0052] Figure 5 The acoustic-density crossplot in the embodiment of the present application is shown in the figure;

[0053] Figure 6 The comparison chart between the curve obtained by rock physics modeling and the original curve in the embodiment of the present application is shown in the figure;

[0054] Figure 7 The measured and coal rock reservoir rock physics model predicted P-S wave velocity ratio and P-wave impedance crossplot in the embodiment of the present application is shown in the figure;

[0055] Figure 8 The coal seam gas content rock physics analysis version in the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0056] The present application will be further described below in combination with the embodiments, but those skilled in the art should understand that the present application is not limited to the following embodiments, and any improvement and change made on the basis of the specific embodiments of the present application is within the scope of protection of the claims of the present application.

[0057] Embodiment A method for coal rock reservoir rock physics modeling

[0058] The coal seam section with serious diameter expansion in the embodiment is taken as a research area for illustration, wherein the maximum expansion rate of the research area reaches 61%, the coal seam in the research area has a shallow depth and a low porosity between 4% and 10%, and the pore structure is complex and includes matrix pores and fracture pores.

[0059] As shown in Figure 1 , the embodiment includes the following steps:

[0060] S1, coal seam section logging curve correction

[0061] S11, coal seam section density logging curve correction

[0062] The influence of the diameter expansion on the density logging is analyzed through the response characteristics of the coal rock reservoir density logging, and a correction model of the influence of the diameter expansion on the density logging curve is established according to the relationship between the diameter expansion and the density logging.

[0063] The correction model of the influence of the diameter expansion on the density logging curve is as follows:

[0064] N c =N+a(D cal -D bits ) / D bits +b

[0065] Wherein, N is the value of the density logging curve before correction, N c is the value of the density logging curve after correction, D cal is the well diameter, D bits is the drill bit diameter, and a and b are correction coefficients.

[0066] In this step, when the values of a and b are obtained, the density variation Δρ is obtained through the measured apparent relative density and the logging density of the coal rock diameter expansion section in the logging laboratory, and the least square method is used to obtain the relationship between the coal seam density variation and the expansion rate in the research area, and the coefficients of the relationship are the values of a and b to be obtained. As shown in Figure 2 , the relationship curve between the coal seam density variation and the expansion rate is obtained, that is, a = 2.7404 and b = -0.6293, and the corrected coal seam density logging curve is finally obtained. As shown in Figure 3 , after the correction of the coal seam density logging curve, the density value after correction is larger than the density value before correction in the diameter expansion section, which is very close to the apparent relative density value analyzed in the laboratory, indicating that the influence of the diameter expansion is eliminated to a certain extent in this step.

[0067] S12, coal seam section acoustic travel time curve correction

[0068] The amount of the increased acoustic travel time caused by the diameter expansion is determined according to the emission period of the acoustic logging, and a correction model of the influence of the diameter expansion on the acoustic travel time curve is established.

[0069] In this step, the frequency method is used for acoustic travel time curve correction, and the frequency method is based on the basic principle of acoustic logging instrument; in the normal case of wellbore, the acoustic travel time logging measures the first arrival travel time; if the coal seam is expanded, the first arrival wave is greatly attenuated, and the receiver receives the first arrival wave, therefore, the time difference between the two receivers will increase; in the actual logging, the emission frequency of the acoustic logging is generally 20 kHz, therefore, the period of the acoustic wave is T = 1 / 20 = 50 μs; according to the principle, the amount of acoustic travel time increase caused by the expansion effect should be a multiple of 50 μs, that is, the correction amount is 50 μs, and according to the principle, the correction model of the acoustic travel time curve affected by the expansion effect is given;

[0070] The correction model of the acoustic travel time curve affected by the expansion effect is:

[0071] Δtc = Δt - Δ

[0072]

[0073] Wherein, Δtc is the corrected acoustic travel time, μs / m; Δt is the acoustic travel time before correction, μs / m; Δ is the acoustic travel time correction amount, μs / m; ds is the difference between the measured hole diameter and the drill bit diameter, cm;

[0074] As shown in Figure 3 After the acoustic travel time curve is corrected, the correction result is lower than the measured value, and is close to the laboratory analysis value, which indicates that the amount of acoustic travel time increase caused by the expansion effect is determined according to the emission period of the acoustic logging, which can effectively improve the correction accuracy of the acoustic travel time logging expansion effect;

[0075] S2, coal seam matrix mineral component calculation

[0076] The equivalent volume model is used to equivalent the coal seam matrix mineral component into a ternary volume model composed of carbon content, ash content and water content, and the volume of the carbon content, ash content and water content in the coal seam matrix mineral component is calculated;

[0077] The sum of the carbon content, ash content and water content is 1, and the water content is the sum of the matrix porosity and the fracture porosity;

[0078] The specific process of this step is:

[0079] The equivalent volume model is used to equivalent the coal seam matrix mineral component into a ternary volume model composed of carbon content, ash content and water content;

[0080] The coal seam in the study area is analyzed by using the neutron curve and the corrected coal seam density logging curve and the coal seam acoustic travel time curve in step S1, and the neutron-density crossplot and the acoustic wave-density crossplot are analyzed, as shown in Figure 4 and Figure 5As shown, by taking the value range of carbon content and ash content in the area where the coal seam is located, the neutron value and density value of carbon point, ash point and water point are determined in the neutron-density crossplot, and the acoustic value and density value of carbon point, ash point and water point are determined in the acoustic-density crossplot;

[0081] The density value, acoustic value and neutron value of the carbon content, the density value, acoustic value and neutron value of the ash content, and the density value, acoustic value and neutron value of the water content in the determined coal seam matrix mineral component are input into the optimal well logging interpretation module of the Rocklab software as independent variables, and the optimal well logging linear equation set is solved to calculate the volume of the carbon content, ash content and water content in the coal seam matrix mineral component;

[0082] S3, coal porosity calculation

[0083] In this step, the coal porosity is divided into matrix porosity and fracture porosity. First, the fracture porosity is obtained by obtaining the resistivity curve through resistivity logging; then the matrix porosity is obtained by subtracting the fracture porosity from the volume of water content obtained in step S2 coal seam matrix mineral component calculation;

[0084] The formula for obtaining the fracture porosity by obtaining the resistivity curve through resistivity logging is:

[0085]

[0086] Wherein, PHIF is the fracture porosity; R d is the deep lateral resistivity, Ω·m; R s is the shallow lateral resistivity, Ω·m; R w is the formation water resistivity, Ω·m; R wf is the formation free water resistivity, Ω·m; m is the cementation factor; R mf is the mud filtrate resistivity, Ω·m;

[0087] S4, coal water saturation calculation

[0088] The general coal seam has high water mineralization degree, and the coal bed gas is more enriched, so in this step, the coal water saturation is calculated by the Simandoux equation, which is suitable for coal and rock reservoirs with high formation water mineralization degree;

[0089] The formula of the Simandoux equation is:

[0090]

[0091] Wherein, S w is the water saturation, the value range is 0-1; R sh is the completely water-containing shale resistivity (Ω·m); R w is the formation water resistivity; V sh is the shale mass fraction, the value range is 0-1; Rt R is the formation resistivity (Ω·m); Фe is the effective porosity, the value range is 0-1; c, d, n are rock-electricity parameters; through the Pickett diagram analysis of the intersection of resistivity and porosity in Rocklab software, the rock-electricity parameters of the coal seam in the study area are selected as c=1, d=1.6, n=2, and Rw=1.43;

[0092] S5, coal seam equivalent model determination

[0093] The coal seam skeleton mineral equivalent model is determined through the Reuss limit model and the volume of carbon, ash and water in the coal seam skeleton mineral components obtained in step S2.

[0094] The pore equivalent model is determined through the DEM model and the matrix porosity and fracture porosity obtained in step S3.

[0095] The fluid mixing equivalent model is determined through the Brie model and the water saturation of the coal seam obtained in step S4.

[0096] S6, coal rock physical modeling and analysis

[0097] On the basis of the coal seam skeleton mineral equivalent model, the pore equivalent model and the fluid mixing equivalent model, the coal rock reservoir rock physical model is established in combination with the Gassman equation.

[0098] The elastic parameters and the ratio of P-wave and S-wave velocity are calculated through the coal rock reservoir rock physical model, the coal gas sensitive parameters are selected through the crossplot analysis of the elastic parameters, the coal rock reservoir rock physical analysis template is established, and the gas-bearing reservoir type is classified.

[0099] As shown in Figure 6 , the prediction curve generated by the coal rock reservoir rock physical model in this step is basically consistent with the corrected measured curve; as shown in Figure 7 , the comparison between the measured P-wave and S-wave velocity ratio crossplot and the P-wave and S-wave velocity ratio crossplot predicted by the coal rock reservoir rock physical model shows that the coal seam P-wave and S-wave velocity ratio predicted by the coal rock reservoir rock physical model obviously reflects the gas-bearing property of the reservoir, which indicates that the coal rock reservoir rock physical model in this step can lay a foundation for the prediction of the gas-bearing property of the coal rock reservoir.

[0100] In this step, the coal rock reservoir type can be divided on the coal rock reservoir petrophysical analysis chart through the intersection of the ratio of the P-wave velocity to the S-wave velocity and the P-wave impedance, and the gas-bearing property of the coal rock reservoir is further quantitatively characterized by combining the coal seam porosity and gas saturation parameters, that is, the ratio of the P-wave velocity to the S-wave velocity of the type I reservoir is greater than or equal to 1.8 and less than 2.05, the porosity is greater than 10%, and the gas saturation is greater than 50%; the ratio of the P-wave velocity to the S-wave velocity of the type II reservoir is greater than or equal to 2.05 and less than 2.25, the porosity is 5%-10%, and the gas saturation is 20%-50%; the ratio of the P-wave velocity to the S-wave velocity of the type III reservoir is greater than or equal to 2.25, the porosity is less than 5%, and the gas saturation is less than 20%, as shown in FIG. 6. Figure 8

[0101] It should be noted that the above only describes the preferred embodiments of the present application and is not intended to limit the present application. Although the present application is described in detail with reference to the above embodiments, those skilled in the art can modify the technical solutions described in the above embodiments or equivalently replace some technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.​

Claims

1. A method of petrophysical modeling of coal rock reservoirs, characterized in that, The method comprises the following steps: S1, coal seam section logging curve correction S11, coal seam section density logging curve correction By analyzing the influence of density logging on the expansion, a correction model of the density logging curve affected by the expansion is established according to the relationship between the expansion and the density logging; S12, coal seam section acoustic travel time curve correction According to the emission period of the acoustic logging, the amount of increase of the acoustic travel time caused by the expansion is determined, and a correction model of the acoustic travel time curve affected by the expansion is established; S2, coal seam skeleton mineral component calculation An equivalent volume model is used to equivalently form a ternary volume model composed of carbon content, ash content and water content by equivalently converting the coal seam skeleton mineral component into the ternary volume model, so as to calculate the volume of the carbon content, ash content and water content in the coal seam skeleton mineral component; The sum of the volumes of the carbon content, ash content and water content is 1, and the water content is the sum of the matrix porosity and the fracture porosity; S3, coal seam porosity calculation The coal seam porosity is divided into matrix porosity and fracture porosity, the fracture porosity is obtained by obtaining the resistivity curve through resistivity logging, and then the matrix porosity is obtained by subtracting the fracture porosity from the volume of the water content obtained in the coal seam skeleton mineral component calculation in step S2; S4, coal seam water saturation calculation The coal seam water saturation is calculated by using the Simandu equation, and the formula of the Simandu equation is: wherein S w is the water saturation, with a value ranging from 0 to 1; R sh is the total water-bearing formation resistivity, Ω.m; R w is the formation water resistivity; V sh is the shale mass fraction, with a value ranging from 0 to 1; R t is the formation resistivity, Ω.m; Φe is the effective porosity, with a value ranging from 0 to 1; c, d, n are litho-electric parameters; S5, coal seam equivalent model determination The coal seam skeleton mineral equivalent model is determined by using the Reuss limit model and the volumes of the carbon content, ash content and water content obtained in step S2; The pore equivalent model is determined by using the DEM model and the matrix porosity and fracture porosity obtained in step S3; The fluid mixture equivalent model is determined by using the Brie model and the coal seam water saturation obtained in step S4; S6, coal seam rock physics modeling and volume analysis On the basis of the coal seam skeleton mineral equivalent model, the pore equivalent model and the fluid mixture equivalent model, a coal rock reservoir rock physics model is established by combining the Gassman equation; The elastic parameters and the ratio of the longitudinal wave velocity to the transverse wave velocity are calculated by using the coal rock reservoir rock physics model, the coal gas sensitive parameters are selected by crossplot analysis of the elastic parameters, a coal rock reservoir rock physics analysis volume is established, and the coal rock reservoir type is divided.

2. The method of petrophysical modeling of coal rock reservoirs according to claim 1, characterized in that, In step S11, the correction model of the density logging curve affected by the expansion is: N c = N + a(D cal - D bits ) / D bits + b Wherein, N is the value of the density logging curve before correction, N c is the value of the density logging curve after correction, D cal is the well diameter, D bits is the drill bit diameter, and a and b are correction coefficients.

3. The method of petrophysical modeling of coal rock reservoirs according to claim 1, characterized in that, In step S12, the correction model of the acoustic travel time curve affected by the expansion is: Δtc = Δt - Δ Wherein, Δtc is the corrected acoustic travel time, μs / m; Δt is the uncorrected acoustic travel time, μs / m; Δ is the acoustic travel time correction amount, μs / m; and ds is the difference between the measured well diameter and the drill bit diameter, cm.

4. The method of petrophysical modeling of coal rock reservoirs according to claim 1, characterized in that, The specific steps of step S2 are: An equivalent volume model is used to equivalently form a ternary volume model composed of carbon content, ash content and water content by equivalently converting the coal seam skeleton mineral component into the ternary volume model; The neutron curve, the coal bed density logging curve and the coal bed acoustic wave time difference curve corrected in step S1 are used to analyze the neutron-density crossplot and the acoustic wave-density crossplot, and through the value range of the carbon content and the ash content of the coal bed region, the density value, the acoustic wave value and the neutron value of the carbon content in the coal bed skeleton mineral component, the density value, the acoustic wave value and the neutron value of the ash content, and the density value, the acoustic wave value and the neutron value of the moisture content are determined; and they are taken as the independent variables to input the optimal logging interpretation module of the Rocklab software, the optimal logging linear equation set is solved, and the volume of the carbon content, the ash content and the moisture content in the coal bed skeleton mineral component is calculated.

5. The method of petrophysical modeling of coal rock reservoirs according to claim 1, characterized in that, In step S3, the formula for calculating the fracture porosity is obtained by obtaining the resistivity curve through the resistivity logging. where PHIF is fracture porosity; R d is deep lateral resistivity, Ω-m; R s is shallow lateral resistivity, Ω-m; R w is formation water resistivity, Ω-m; R wf is formation free water resistivity, Ω-m; m is cementation factor; R mf is mud filtrate resistivity, Ω-m.

6. The method of petrophysical modeling of coal rock reservoirs of claim 1, wherein, In step S6, when the ratio of the P-wave velocity to the S-wave velocity is greater than or equal to 1.8 and less than 2.05, the coal bed gas reservoir is classified as the Ⅰ type reservoir; when the ratio is greater than or equal to 2.05 and less than 2.25, the coal bed gas reservoir is classified as the Ⅱ type reservoir; and when the ratio is greater than or equal to 2.25, the coal bed gas reservoir is classified as the Ⅲ type reservoir.

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