Deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation

Abstract

The present invention belongs to the field of oil and gas field development, and specifically relates to a deep coalbed methane reservoir damage evaluation method based on nuclear magnetic resonance and intelligent evaluation, comprising: conducting a helium pulse method experiment and a nuclear magnetic resonance experiment before and after liquid phase invasion, respectively, to obtain the gas permeability and the permeability of the nuclear magnetic resonance method before and after liquid phase invasion; obtaining the permeability damage rate of the two methods and comparing them, and correcting the deviation obtained by the comparison by performing intelligent analysis and evaluation according to the hierarchical analysis method to obtain the correct permeability damage rate deviation value; using the permeability damage rate value obtained by the nuclear magnetic resonance method to evaluate the deep coalbed methane reservoir damage. The deep coalbed methane reservoir damage (liquid phase invasion) evaluation method based on nuclear magnetic resonance and intelligent evaluation proposed by the present invention can perform non-destructive and rapid detection of coal samples, can reduce time consumption, save costs, and accurately and quickly evaluate the degree of coalbed methane reservoir damage (liquid phase invasion).

Description

Technical Field

[0001] The present invention belongs to the field of oil and gas field development, and specifically designs a deep coalbed methane reservoir damage (liquid phase invasion) evaluation method based on nuclear magnetic resonance and intelligent evaluation. Background Art

[0002] Coalbed methane refers to hydrocarbon gas that exists in coal seams and is mainly composed of methane. It is mainly adsorbed on the surface of coal matrix particles, and some of it is free in coal pores or dissolved in coalbed water. As a semi-mineral resource of coal, it is an unconventional natural gas and an unconventional energy source.

[0003] Deep coalbed methane (CBM) refers to gas found in formations deeper than 1,500 meters. my country boasts abundant CBM resources, with deep CBM accounting for 70% of the nation's total. However, drilling and production of deep CBM remains challenging, primarily due to significant damage to the reservoirs during drilling (due to severe liquid intrusion).

[0004] Compared to conventional reservoir rocks, deep coal rocks are more brittle and prone to collapse, have low permeability, poor cementation, and well-developed microcracks. This results in a strong capillary effect, a Jamin effect, and high pressure sensitivity. Therefore, during drilling, drilling fluids easily invade and remain in the microcracks of deep coal rocks, causing reservoir damage. This damage not only reduces the return rate of drilling fluids and increases drilling costs, but also blocks the migration pathways of deep coalbed methane, affecting its production. This, in turn, results in high drilling and production costs, large production capacity differences, rapid production declines, poor production stability, and low recovery rates, severely hindering the development of deep coalbed methane.

[0005] Currently, reservoir damage caused by liquid invasion is primarily assessed by measuring the permeability damage rate before and after liquid invasion. Deep coalbed methane reservoirs, for example, have dense coal rock with extremely low permeability, making them susceptible to fragmentation and shedding under pressure. Furthermore, reservoir environmental factors such as pressure, temperature, pH, clay content in the coal seam, degree of liquid invasion, water salinity in the coal seam, contact angle of the coal rock with water, and coal maturity all influence the assessment of the extent of reservoir damage (liquid invasion) in deep coalbed methane. Consequently, conventional permeability testing methods for assessing reservoir damage (liquid invasion) in deep coalbed methane not only fail to effectively guarantee the integrity of deep coal cores, resulting in waste of valuable core samples and inaccurate permeability test data, but also present a cumbersome process that prevents a rapid and effective assessment of the extent of reservoir damage (liquid invasion). This severely restricts the timeliness and cost-effectiveness of reservoir damage (liquid invasion) assessments, negatively impacting reservoir protection and development. Summary of the Invention

[0006] In view of the above problems, the present invention is proposed to provide a method for evaluating the degree of damage (liquid phase invasion) of deep coalbed methane reservoirs based on nuclear magnetic resonance, which can overcome the above problems.

[0007] The technical solutions of the present invention are as follows:

[0008] The deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation includes the following steps:

[0009] Step 1: Select a deep coal sample and cut a deep coal core with smooth ends and no cracks on the surface, with a diameter of 25 mm and a length of 60 mm.

[0010] Step 2: Perform a helium pulse permeability test on a deep coal rock core dry sample, and fit the pressure difference data that changes with time to obtain the gas permeability of the sample as K Q1 ;

[0011] Step 3: Perform nuclear magnetic resonance experiments on deep coal core dry samples, obtain and analyze the T2 spectrum, and obtain the permeability of the sample by the nuclear magnetic resonance method as K H1 ;

[0012] Step 4: Conduct a self-imbibition experiment on a dry core sample of deep coal rock. Place the core vertically, immerse the lower end in a 6% mass fraction potassium chloride solution, and expose the upper end to air. Use the core self-imbibition method to saturate from bottom to top. After a period of self-imbibition, remove the core.

[0013] Step 5: Perform a nuclear magnetic resonance experiment on the core after self-imbibition to obtain the liquid phase invasion degree spectrum and T2 spectrum of the sample, and analyze and process the T2 spectrum to obtain the permeability of the sample by the nuclear magnetic resonance method, K H2 ;

[0014] Step 6: After drying the core after self-absorption, a helium pulse method permeability test is performed, and the pressure difference data that changes with time is fitted to obtain the gas permeability of the sample as K Q2 ;

[0015] Preferably, when the helium pulse method is used to measure the permeability in step 2 and step 6, a certain axial pressure and confining pressure are applied to the core, and the core environment is the same as that of the formation.

[0016] Step 7: According to the K Q1 , K Q2 and K H1 , K H2 , respectively calculate the permeability damage rate D measured by the helium pulse method Qk and the permeability damage rate D obtained by the nuclear magnetic resonance experimental method HkWhen measuring permeability using the helium pulse method, a certain amount of axial pressure and confining pressure will be applied to the core. The core environment is similar to that of the formation. Qk The actual permeability damage rate D k , so as to compare the permeability damage rate D obtained by NMR experimental method Hk Make a comparison.

[0017] Actual penetration damage rate D k :

[0018]

[0019] Permeability damage rate D obtained by NMR method Hk :

[0020]

[0021] In this step, the actual permeability damage rate D k The permeability damage rate D obtained by NMR method Hk The difference between them is the deviation E;

[0022] Calculation of deviation E:

[0023] E=|D k -D Hk | (3)

[0024] Correct the deviation E.

[0025] Furthermore, the factors affecting the permeability damage rate of deep coalbed methane reservoirs are graded. The first-level influencing factors include: the physical properties of deep coal rocks, the chemical properties of deep coal rocks, the content of each mineral component in deep coal rocks, and the formation water properties of deep coalbed methane reservoirs.

[0026] Specifically:

[0027] The physical properties of deep coal rock include the following secondary influencing factors: permeability, relative permeability, porosity, pore volume, surface area, wettability, density, compressive strength, tensile strength, shear strength, hardness, looseness, cementation type, particle sorting, resistivity, and liquid invasion time;

[0028] The chemical properties of deep coal rock include the following secondary influencing factors: organic matter content, inorganic matter content, elemental composition, and coalification degree;

[0029] The second-level influencing factors of the content of each mineral component in deep coal rock are: quartz content, potassium feldspar content, plagioclase content, calcite content, dolomite content, pyrite content, total clay content, siderite content, smectite content, illite content, kaolinite content, and chlorite content;

[0030] The secondary influencing factors of the formation water properties of deep coalbed methane reservoirs include: formation water salinity, formation water pH value, formation water density, and formation water hardness.

[0031] In order to make a faster and more effective evaluation of the degree of deep coalbed methane reservoir damage (liquid invasion) under reservoir conditions, one or more of the following secondary influencing factors are selected from the numerous factors that affect the permeability damage rate of deep coalbed methane reservoirs: permeability, relative permeability, porosity, pore volume, surface area, wettability, density, compressive strength, tensile strength, shear strength, hardness, looseness, cementation type, particle sorting, resistivity, liquid invasion time, organic matter content, inorganic matter content, elemental composition, coalification degree, quartz content, potassium feldspar content, plagioclase content, calcite content, dolomite content, pyrite content, total clay content, siderite content, smectite content, illite content, kaolinite content, chlorite content, formation water salinity, formation water pH value, formation water density, and formation water hardness;

[0032] The hierarchical analysis method is used to assign importance weights to the factors affecting the permeability of deep coal seams and construct a judgment matrix.

[0033] Table 1 Impact Factor Importance Evaluation Questionnaire

[0034]

[0035]

[0036] Establish an impact factor importance evaluation questionnaire, as shown in Table 1, where element x ij Indicates the importance of impact factor i to impact factor j; importance is expressed on a scale of 0 to 1, where 0 means both are equally important and 1 means i is extremely important to j, i, j ≤ m;

[0037] According to the impact factor importance evaluation questionnaire, the judgment matrix X is established:

[0038]

[0039] For the judgment matrix X, its weight vector needs to be calculated and consistency checked. The weight vector represents the relative importance of each element in its hierarchy.

[0040] Find the maximum eigenvalue λ of the judgment matrix X max And its corresponding weight vector α:

[0041] Xα=λ max α (5)

[0042] Find the weight of each impact factor:

[0043]

[0044] Consistency index CI:

[0045]

[0046] Where m is the order of the judgment matrix, that is, the number of elements; when m = 1, 2, no consistency check is required;

[0047] Random consistency index RI:

[0048] RI=0.1×(m-2),m≥3 (8)

[0049] Table 2 Random Consistency Index RI Values ​​when m = 12

[0050] m 1 2 3 4 5 6 7 8 9 10 11 12 RI 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

[0051] Consistency ratio CR:

[0052]

[0053] When the consistency ratio CR is less than 0.1, the consistency degree of the judgment matrix X is within the allowable range, which can well meet the consistency requirements and pass the consistency test. When the consistency ratio CR is greater than or equal to 0.1, it fails the consistency test and needs to adjust the values ​​of each element in the judgment matrix X, divide the weights again, and recalculate the consistency ratio CR until it passes the consistency test.

[0054] Furthermore, the importance of the influencing factors of deep coal seam permeability obtained through consistency detection is used to determine the matrix X, and the weighted average value is calculated to obtain the weighted average value And use this to calculate the actual penetration damage rate D k The permeability damage rate D obtained by NMR method Hk The deviation E between them is corrected, and the corrected value is recorded as S;

[0055] Weighted average Calculation:

[0056]

[0057] Where w i For the same importance x ij Number of occurrences, n≤m;

[0058] The correction process of S:

[0059]

[0060] Furthermore, in this application, when the actual permeability damage rate D k The permeability damage rate D obtained by NMR method Hk When the deviation E between them is corrected to a value S≤1%, it is within the allowable range, indicating that the permeability damage rate obtained by the nuclear magnetic resonance method is relatively accurate, and the deep coalbed methane reservoir damage (liquid invasion) evaluation method based on nuclear magnetic resonance and intelligent evaluation is feasible; if S>1%, the importance of each element of the judgment matrix is ​​adjusted, and the judgment process of the hierarchical analysis method is re-performed until the corrected value S≤1%.

[0061] If the calculated S value is within the allowable range, then further, the permeability damage rate D obtained by the nuclear magnetic resonance method described in this application is Hk , according to the following table, an effective evaluation of the degree of deep coalbed methane reservoir damage (liquid intrusion) can be carried out.

[0062] Table 3 Evaluation of the degree of deep coalbed methane reservoir damage (liquid invasion) by nuclear magnetic resonance method

[0063]

[0064]

[0065] The beneficial effects of the present invention are:

[0066] The method for evaluating the degree of damage (liquid phase invasion) to deep coalbed methane reservoirs provided by the present invention fully takes into account the fragility of rock samples and the difficulty in drilling cores. It can perform non-destructive and rapid testing of coal samples, reduce time consumption, save costs, and accurately and quickly evaluate the degree of damage (liquid phase invasion) to coalbed methane reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 This is a flow chart of the deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation of the present invention;

[0068] Figure 2 Flowchart of the analytic hierarchy process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] The present invention will be further described below with reference to embodiments and accompanying drawings, but is not limited thereto.

[0070] like Figure 1-2 shown.

[0071] Example 1:

[0072] The deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation includes the following steps:

[0073] Step 1: Select deep coal samples and cut three cores of deep coal rock. Each core should be smooth at both ends, without cracks, with a diameter of 25 mm and a length of 60 mm.

[0074] Step 2: Perform a helium pulse permeability test on a deep coal rock core dry sample, and fit the pressure difference data that changes with time to obtain the gas permeability of the sample as K Q1 ; A certain axial pressure and confining pressure are applied to the core, and the core environment is the same as that of the formation;

[0075] Step 3: Perform nuclear magnetic resonance experiments on deep coal core dry samples, obtain and analyze the T2 spectrum, and obtain the permeability of the sample by the nuclear magnetic resonance method as K H1 ;

[0076] Step 4: Conduct a self-imbibition experiment on the deep coal rock core dry sample. Place the core vertically, immerse the lower end in 6% potassium chloride solution, and expose the upper end to air. Use the core self-imbibition method to saturate from bottom to top. After a period of self-imbibition, take out the core.

[0077] Step 5: Perform a nuclear magnetic resonance experiment on the core after self-imbibition to obtain the liquid phase invasion degree spectrum and T2 spectrum of the sample, and analyze and process the T2 spectrum to obtain the permeability of the sample by the nuclear magnetic resonance method, K H2 ;

[0078] Step 6: After drying the core after self-absorption, a helium pulse method permeability test is performed, and the pressure difference data that changes with time is fitted to obtain the gas permeability of the sample as K Q2 ; A certain axial pressure and confining pressure are applied to the core, and the core environment is the same as that of the formation;

[0079] Step 7: Based on the obtained K Q1 , K Q2 and K H1 , K H2 , calculate the permeability damage rate D of the three cores measured by the helium pulse method Qk (ie, actual permeability damage rate D k ) and the permeability damage rate D obtained by nuclear magnetic resonance experimental method Hk .

[0080] In this embodiment, the core self-imbibition water experiments were conducted on the three cores for 1 hour, 5 hours, and 10 hours respectively to simulate the damage suffered by the cores.

[0081] Table 4 Permeability before and after self-absorption measured by helium pulse method

[0082] <![CDATA[Before self-priming K Q1 (mD)]]> <![CDATA[After self-priming K Q2 (mD)]]> 1. Self-priming for 1 hour 0.062 0.030 2. Self-priming for 5 hours 0.069 0.028 3. Self-priming for 10 hours 0.060 0.019

[0083] Table 5 Permeability before and after self-imbibition obtained by NMR experimental method

[0084] <![CDATA[Before self-priming K H1 (mD)]]> <![CDATA[After self-priming K H2 (mD)]]> 1. Self-priming for 1 hour 0.061 0.029 2. Self-priming for 5 hours 0.067 0.026 3. Self-priming for 10 hours 0.058 0.018

[0085] Actual penetration damage rate D k :

[0086]

[0087] Permeability damage rate D obtained by NMR method Hk :

[0088]

[0089] In this step, the actual permeability damage rate D k The permeability damage rate D obtained by NMR method Hk The difference between them is the deviation E.

[0090] Calculation of deviation E:

[0091] E=|D k -D Hk | (3)

[0092] Correct the deviation E.

[0093] Table 6 Actual permeability damage rate D k The permeability damage rate D obtained by NMR method Hk Deviation Table

[0094]

[0095]

[0096] In order to make a faster and more effective evaluation of the degree of deep coalbed methane reservoir damage (liquid invasion) under reservoir conditions, one or more of the following secondary influencing factors are summarized and screened out from the many factors affecting the permeability damage rate of deep coalbed methane reservoirs: permeability, relative permeability, porosity, pore volume, surface area, wettability, density, compressive strength, tensile strength, shear strength, hardness, looseness, cementation type, particle sorting, resistivity, liquid invasion time, organic matter content, inorganic matter content, elemental composition, coalification degree, quartz content, potassium feldspar content, plagioclase content, calcite content, dolomite content, pyrite content, total clay, siderite content, smectite content, illite content, kaolinite content, chlorite content, formation water mineralization, formation water pH value, formation water density, and formation water hardness.

[0097] The hierarchical analysis method is used to assign importance weights to the factors affecting the permeability of deep coal seams and construct a judgment matrix.

[0098] Table 1 Impact Factor Importance Evaluation Questionnaire

[0099]

[0100] Establish an impact factor importance evaluation questionnaire, as shown in Table 1, where element x ij Indicates the importance of impact factor i to impact factor j. Importance is expressed on a scale of 0 to 1, where 0 means both are equally important and 1 means i is extremely important to j, i, j ≤ m.

[0101] According to the impact factor importance evaluation questionnaire, the judgment matrix X is established:

[0102]

[0103] For the judgment matrix X, its weight vector needs to be calculated and consistency checked. The weight vector represents the relative importance of each element in its hierarchy.

[0104] Find the maximum eigenvalue λ of the judgment matrix X max And its corresponding weight vector α:

[0105] Xα=λ max α (5)

[0106] Find the weight of each impact factor:

[0107]

[0108] Consistency index CI:

[0109]

[0110] Where m is the order of the judgment matrix (ie, the number of elements). When m = 1 or 2, no consistency check is required.

[0111] Random consistency index RI, RI=0.1×(m-2),m≥3 (8)

[0112] Obtain the value according to the following table:

[0113] Table 2 Random Consistency Index RI Values ​​when m = 12

[0114] m 1 2 3 4 5 6 7 8 9 10 11 12 RI 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

[0115] Consistency ratio CR:

[0116]

[0117] After calculation, the calculation result of consistency ratio CR is obtained:

[0118] Table 7 Consistency ratio CR results

[0119] Consistency ratio CR 1. Self-priming for 1 hour 0.056 2. Self-priming for 5 hours 0.058 3. Self-priming for 10 hours 0.061

[0120] It can be seen that the consistency ratios CR of the importance of the influencing factors of the permeability of the three deep coal seams in this embodiment are all less than 0.1, which meets the passing requirement of the consistency ratio. The importance of the influencing factors of the permeability of the deep coal seams is accurately judged, and a weighted average can be performed. Calculation:

[0121]

[0122] Where w i For the same importance x ij Number of occurrences, n≤m.

[0123] Table 8 Weighted average

[0124]

[0125] The results are calculated based on the weighted average Damage rate to actual permeability D k The permeability damage rate D obtained by NMR method Hk The deviation E between them is corrected to obtain the correction value S:

[0126]

[0127] Table 9 Correction value S

[0128] Correction value S 1. Self-priming for 1 hour 0.5185％ 2. Self-priming for 5 hours 0.9735％ 3. Self-priming for 10 hours 0.4032％

[0129] It can be seen that the actual permeability damage rate D of the three deep coal cores in this embodiment is k The permeability damage rate D obtained by NMR method Hk The deviation E between them is corrected to obtain a value S of ≤1%, which is within the allowable range, indicating that the permeability damage rate obtained by the nuclear magnetic resonance method is relatively accurate, and the deep coalbed methane reservoir damage (liquid invasion) evaluation method based on nuclear magnetic resonance and intelligent evaluation is feasible.

[0130] Finally, the permeability damage rate D obtained by the nuclear magnetic resonance method described in this application is Hk According to Table 3, the degree of deep coalbed methane reservoir damage (liquid invasion) was evaluated and the following results were obtained.

[0131] Table 10 Nuclear magnetic resonance evaluation of deep coalbed methane reservoir damage (liquid invasion)

[0132] <![CDATA[Nuclear magnetic D Hk > Extent of damage 1. Self-priming for 1 hour 52.46％ medium 2. Self-priming for 5 hours 61.19％ medium 3. Self-priming for 10 hours 68.97％ medium

[0133] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation, characterized in that: The steps include: Step 1: Select deep samples and cut deep coal rock cores with smooth ends and no cracks on the surface, with a diameter of 25 mm and a length of 60 mm; Step 2: Perform a helium pulse permeability test on a deep coal rock core dry sample, and fit the pressure difference data that changes with time to obtain the gas permeability of the sample as K Q1 ; Step 3: Perform nuclear magnetic resonance experiments on deep coal core dry samples, obtain and analyze the T2 spectrum, and obtain the permeability of the sample by the nuclear magnetic resonance method as K H1 ; Step 4: Conduct a self-imbibition experiment on a dry core sample of deep coal rock. Place the core vertically, immerse the lower end in a 6% mass fraction potassium chloride solution, and expose the upper end to air. Use the core self-imbibition method to saturate from bottom to top. After a period of self-imbibition, remove the core. Step 5: Perform a nuclear magnetic resonance experiment on the core after self-imbibition to obtain the liquid phase invasion degree spectrum and T2 spectrum of the sample, and analyze and process the T2 spectrum to obtain the permeability of the sample by the nuclear magnetic resonance method, K H2 ; Step 6: After drying the core after self-absorption, a helium pulse method permeability test is performed, and the pressure difference data that changes with time is fitted to obtain the gas permeability of the sample as K Q2 ; Step 7: According to the K Q1 , K Q2 and K H1 , K H2 , respectively calculate the permeability damage rate D measured by the helium pulse method Qk and the permeability damage rate D obtained by the nuclear magnetic resonance experimental method Hk ; D Qk The actual permeability damage rate D k ; Actual penetration damage rate D k : （1） Permeability damage rate D obtained by NMR method Hk : （2） In this step, the actual permeability damage rate D k The permeability damage rate D obtained by NMR method Hk The difference between them is the deviation E; Calculation of deviation E: （3） Correct the deviation E; If the corrected value is within the allowable range, the permeability damage rate D obtained by the NMR method is Hk Conduct effective evaluation of the damage degree of deep coalbed methane reservoirs.

2. The deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation according to claim 1 is characterized in that: When the helium pulse method is used to measure the permeability in step 2 and step 6, a certain axial pressure and confining pressure are applied to the core, and the core environment is the same as that of the formation.

3. The deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation according to claim 1 is characterized in that: In step seven, the influencing factors are classified into primary and secondary influencing factors. The primary influencing factors include: physical properties of deep coal rocks, chemical properties of deep coal rocks, content of various mineral components in deep coal rocks, and formation water properties of deep coalbed methane reservoirs; Select one or more influencing factors, use the analytic hierarchy process to assign importance weights to the factors affecting the permeability of deep coal seams and construct a judgment matrix; Establish an impact factor importance evaluation questionnaire, where element x ij Indicates the importance of impact factor i to impact factor j; importance is expressed on a scale of 0 to 1, where 0 means both are equally important and 1 means i is extremely important to j, i, j ≤ m; According to the impact factor importance evaluation questionnaire, the judgment matrix X is established: （4） For the judgment matrix X, its weight vector needs to be calculated and consistency checked. The weight vector represents the relative importance of each element in its hierarchy. Find the maximum eigenvalue of the judgment matrix X And its corresponding weight vector α: （5） Find the weight of each impact factor: （6） Consistency index CI: （7） Where m is the order of the judgment matrix, that is, the number of elements; when m=1, 2, no consistency check is required; The random consistency index RI is taken as follows: RI=0.1×(m-2), m≥3 (8) Consistency ratio CR: （9） When the consistency ratio CR is less than 0.1, the consistency degree of the judgment matrix X is within the allowable range, can meet the consistency requirements, and passes the consistency test; when the consistency ratio CR is greater than or equal to 0.1, it fails the consistency test and needs to adjust the values ​​of each element in the judgment matrix X, re-divide the weights, and recalculate the consistency ratio CR until it passes the consistency test; According to the importance judgment matrix X of the influencing factors of deep coal seam permeability obtained through consistency detection, the weighted average value is calculated to obtain the weighted average value. , and use this to calculate the actual permeability damage rate D k The permeability damage rate D obtained by NMR method Hk The deviation E between them is corrected, and the corrected value is recorded as S; Weighted average Calculation: （10） Where, w i For the same importance x ij Number of occurrences, n≤m; The correction process of S: （11）。 4. The deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation according to claim 3 is characterized in that: When the actual penetration damage rate D k The permeability damage rate D obtained by NMR method Hk When the deviation E between them is corrected to a value S≤1%, it is within the allowable range, indicating that the permeability damage rate obtained by the nuclear magnetic resonance method is accurate, and the deep coalbed methane reservoir damage evaluation method based on nuclear magnetic resonance and intelligent evaluation is feasible; if S>1%, the importance of each element in the judgment matrix is ​​adjusted, and the judgment process of the hierarchical analysis method is repeated until the corrected value S≤1%.

5. The deep coalbed methane reservoir damage assessment method based on nuclear magnetic resonance and intelligent evaluation according to claim 3 is characterized in that: The physical properties of deep coal rock include the following secondary influencing factors: permeability, relative permeability, porosity, pore volume, surface area, wettability, density, compressive strength, tensile strength, shear strength, hardness, looseness, cementation type, particle sorting, resistivity, and liquid invasion time; The chemical properties of deep coal rock include the following secondary influencing factors: organic matter content, inorganic matter content, elemental composition, and coalification degree; The second-level influencing factors of the content of each mineral component in deep coal rock are: quartz content, potassium feldspar content, plagioclase content, calcite content, dolomite content, pyrite content, total clay content, siderite content, smectite content, illite content, kaolinite content, and chlorite content; The secondary influencing factors of the formation water properties of deep coalbed methane reservoirs include: formation water salinity, formation water pH value, formation water density, and formation water hardness.

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