A method, device, equipment, medium and product for predicting the amount of coal bed methane adsorption under water-containing conditions

Abstract

The application provides a method, device, equipment, medium and product for predicting the adsorption amount of coal bed methane under water-containing conditions, and relates to the technical field of oil and gas field development. The method comprises the following steps: determining the actual water saturation of each pore diameter in a target coal sample based on the pore structure characteristic data of the target coal sample and the nuclear magnetic signal amplitudes of the target coal sample under multiple different water-containing conditions; determining the length of methane occupying in the pores corresponding to each pore diameter in the target coal sample based on the actual water saturation of each pore diameter in the target coal sample; calculating the total volume of methane adsorption and the total surface area of methane adsorption; and determining the total adsorption amount of methane of the target coal sample under the actual water saturation based on the total volume of methane adsorption and the total surface area of methane adsorption. The method of the application fully considers the influence of the water saturation in the coal bed on the adsorption amount of methane, and combines different adsorption modes of methane in the pores, so that the predicted adsorption amount of methane is more accurate.

Description

Technical Field

[0001] This application relates to the field of oil and gas field development technology, and in particular to a method, apparatus, equipment, medium and product for predicting the amount of methane adsorption in coal seams considering water-bearing conditions. Background Technology

[0002] Coalbed methane (CBM), an abundant unconventional natural gas resource, primarily consists of methane. CBM is mainly found in adsorbed form (80%-95%), and adsorption capacity is a core indicator for measuring the gas storage capacity of a coal seam. Only by clearly defining the adsorption capacity of coal seams in different regions and at different depths can the "recoverable resources" be accurately calculated. For example, if a coal seam has a low adsorption capacity (e.g., <10m³),... 3 Even with large reserves, coal seams with low single-well production and insufficient development revenue may lose their mining value; conversely, high-adsorption coal seams (such as > 20 m) may be worth mining. 3 / t) has higher development potential. Without the prediction of absorption volume, it may lead to misjudgment of resources: either over-investing in the development of low-potential blocks, resulting in wasted costs; or missing high-value blocks, missing the opportunity to utilize resources.

[0003] Among the related technologies is the publication CN119147571A, "A Method for Determining the Molar Mass of Methane by Converting Nuclear Magnetic Resonance Signals," which utilizes low-field nuclear magnetic resonance technology. By measuring the relaxation signal of methane in the pores of coal / shale, a linear correlation model between the intensity of the nuclear magnetic resonance signal and the amount of methane is established. Combined with the conversion of the molar mass of methane to the amount of adsorption, the adsorption amount can be directly correlated with the number of micro-particles, avoiding the systematic errors of the traditional weighing method. The paper "A Correction Method for Coalbed Methane Adsorption Based on Langmuir Model" (publication number CN115656789A) uses isothermal adsorption experiments on coal samples with different moisture contents (5%~20%) to fit a correction coefficient of water saturation-adsorption constant (a value). The corrected a value is then substituted into the Langmuir equation to calculate the adsorption amount under water conditions. This method is applicable to coal seam scenarios with medium to low moisture contents (<20%). However, the correction coefficient is only obtained through experiments on a single coal type and does not consider the influence of coal sample pore structure on water adsorption, resulting in insufficient universality. The publication CN118234567A, titled "Method for Determining the Adsorption Capacity of Methane in Water-Bearing Coal Samples under High Pressure Conditions," employs a high-pressure adsorption instrument. It separates free water and methane in coal samples using a gas-water separation device, measures the adsorption capacity under different pressures (0~15MPa) and moisture contents, and establishes a three-dimensional correlation model of pressure-moisture content-adsorption capacity to achieve quantitative calculation of adsorption capacity. The experiment can be carried out under simulated high-pressure conditions, and the calculation results are closer to actual mining conditions. However, the experimental equipment is expensive, and the operation process is complex, making it difficult to meet the needs of large-scale resource assessment.

[0004] In summary, current technologies either completely ignore the influence of water saturation or only consider water-bearing conditions from a single dimension (such as correction coefficients or high-pressure experiments). These approaches generally suffer from poor universality, insufficient accuracy, and complex operation, failing to meet the demand for precise calculation of methane adsorption in water-bearing coal seams. Therefore, developing a method for calculating methane adsorption that couples multiple variables such as pore structure and water saturation is crucial for current research on coalbed methane development. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, medium, and product for predicting the methane adsorption capacity of coal seams considering water-bearing conditions, in order to solve the problem that the current method cannot meet the demand for accurate calculation of methane adsorption capacity in water-bearing coal seams.

[0006] In a first aspect, this application provides a method for predicting the methane adsorption capacity of coal seams considering water-bearing conditions, comprising:

[0007] The pore structure characteristics of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-bearing conditions are obtained. The multiple different water-bearing conditions include the actual water saturation of the coal seam where the target coal sample is located.

[0008] Based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water content conditions, the actual water saturation corresponding to each pore size in the target coal sample is determined by a preset water saturation calculation model.

[0009] A pre-defined capillary length calculation model is used to determine the length of methane occupied in the pores corresponding to each pore size of the target coal sample under the actual water saturation, based on the actual water saturation of each pore size in the target coal sample.

[0010] The total volume and total surface area of ​​methane adsorption are calculated based on the length occupied by methane in each pore size of the target coal sample.

[0011] Based on the total methane adsorption volume and the total methane adsorption surface area, a preset methane adsorption capacity determination model is used to determine the total methane adsorption capacity of the target coal sample at the actual water saturation level. Based on the total methane adsorption capacity of the target coal sample, the total methane adsorption capacity of the coal seam where the target coal sample is located at the actual water saturation level is predicted.

[0012] In one possible design, based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water content conditions, a preset water saturation calculation model is used to determine the actual water saturation corresponding to each pore size in the target coal sample, including:

[0013] Based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-saturation conditions, the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water-saturation conditions is determined.

[0014] Based on the NMR signal amplitudes of each pore size in the target coal sample under multiple different water content conditions, a preset water saturation calculation model is used to determine the actual water saturation corresponding to each pore size in the target coal sample.

[0015] In one possible design, the use of a preset capillary length calculation model, based on the actual water saturation corresponding to each pore size in the target coal sample, determines the length of methane occupied in the pores corresponding to each pore size of the target coal sample at the actual water saturation level, including:

[0016] The pore length corresponding to each pore diameter in the target coal sample is calculated based on the pore structure characteristic data of the target coal sample.

[0017] A pre-defined capillary length calculation model is used to determine the length of methane occupied in the pores corresponding to each pore size in the target coal sample at the actual water saturation and the pore length corresponding to each pore size in the target coal sample, based on the actual water saturation.

[0018] In one possible design, the calculation of the total methane adsorption volume and total methane adsorption surface area based on the methane capillary length corresponding to each pore size in the target coal sample includes:

[0019] Determine the critical pore size corresponding to methane in the coal seam;

[0020] Calculate the methane storage volume in each pore of the target coal sample whose pore size is less than or equal to the critical pore size, and determine the sum of the volumes as the total methane adsorption volume;

[0021] Calculate the methane storage area in each pore of the target coal sample whose pore size is larger than the critical pore size, and determine the sum of the areas as the total methane adsorption surface area.

[0022] In one possible design, the calculation of the total methane adsorption volume and total methane adsorption surface area based on the methane capillary length corresponding to each pore size in the target coal sample includes:

[0023] The average tortuosity of the target coal sample is calculated based on the pore structure characteristic data of the target coal sample;

[0024] Based on the length of methane occupied in the pores corresponding to each pore size in the target coal sample, the average tortuosity of the target coal sample, and the critical pore size, the total volume of methane adsorption and the total surface area of ​​methane adsorption are calculated.

[0025] In one possible design, the formula corresponding to the preset methane adsorption capacity determination model is: Where, n is the total methane adsorption amount of the target coal sample; V1 is the total methane adsorption volume; R is the methane gas constant; T is the actual temperature of the coal seam; p0 is the saturated vapor pressure; p is the actual pressure of the coal seam; E is the adsorption characteristic parameter; k is the non-uniformity coefficient of the coal surface; S2 is the total surface area of ​​methane adsorption; a m,g N is the cross-sectional area of ​​a methane molecule. A ρ is Avogadro's constant; gT p is the density of methane under standard conditions. L Where is the Langmuir pressure; M is the amount of methane.

[0026] Secondly, this application provides a device for predicting the methane adsorption capacity of coal seams considering water-bearing conditions, comprising:

[0027] The acquisition module is used to acquire pore structure feature data of the target coal sample and the nuclear magnetic resonance signal amplitude of the target coal sample under multiple different water-bearing conditions, wherein the multiple different water-bearing conditions include: the actual water saturation of the coal seam where the target coal sample is located;

[0028] The determination module is used to determine the actual water saturation corresponding to each pore size in the target coal sample based on the pore structure feature data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water content conditions, using a preset water saturation calculation model.

[0029] The determining module is also used to determine the length of methane occupied in the pores corresponding to each pore size in the target coal sample at the actual water saturation level by using a preset capillary length calculation model.

[0030] The calculation module is used to calculate the total methane adsorption volume and the total methane adsorption surface area based on the length occupied by methane in the pores corresponding to each pore size in the target coal sample.

[0031] The determining module is further configured to determine the total methane adsorption amount of the target coal sample at the actual water saturation level by using a preset methane adsorption amount determination model based on the total methane adsorption volume and the total methane adsorption surface area.

[0032] The prediction module is used to predict the total methane adsorption of the coal seam where the target coal sample is located at the actual water saturation level, based on the total methane adsorption of the target coal sample.

[0033] Thirdly, this application provides a predictive device for the amount of methane adsorption in a coal seam considering water content conditions, comprising: a processor, and a memory communicatively connected to the processor;

[0034] The memory stores the instructions that the computer executes;

[0035] The processor executes computer-executable instructions stored in memory to implement the method as described in any of the first aspects.

[0036] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any of the first aspects.

[0037] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method as described in the first aspect.

[0038] This application provides a method, apparatus, equipment, medium, and product for predicting methane adsorption in coal seams considering moisture conditions. It acquires pore structure characteristic data of a target coal sample and the NMR signal amplitude of the target coal sample under multiple different moisture conditions. These multiple different moisture conditions include: the actual moisture saturation of the coal seam where the target coal sample is located; based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different moisture conditions, it uses a preset moisture saturation calculation model to determine the actual moisture saturation corresponding to each pore size in the target coal sample; and it uses a preset capillary length calculation model based on the target coal... The actual water saturation corresponding to each pore size in the sample is used to determine the length occupied by methane in the pores corresponding to each pore size in the target coal sample at the actual water saturation. Based on the length occupied by methane in the pores corresponding to each pore size in the target coal sample, the total methane adsorption volume and the total methane adsorption surface area are calculated. According to the total methane adsorption volume and the total methane adsorption surface area, a preset methane adsorption amount determination model is used to determine the total methane adsorption amount of the target coal sample at the actual water saturation. Based on the total methane adsorption amount of the target coal sample, the total methane adsorption amount of the coal seam where the target coal sample is located is predicted at the actual water saturation.

[0039] The pore structure of coal plays a crucial role in methane adsorption; different pore sizes, shapes, and connectivity affect the adsorption capacity and amount of methane. Obtaining pore structure characteristic data of target coal samples provides important basic information for accurately predicting methane adsorption, enabling a more precise understanding of the methane adsorption characteristics of coal seams. By acquiring NMR signal amplitudes under multiple different moisture conditions, the existence state and distribution of methane in the coal seam can be comprehensively understood when moisture content changes, making the prediction results closer to reality. Based on pore structure characteristic data and NMR signal amplitudes under different moisture conditions, the actual water saturation corresponding to each pore size in the target coal sample is determined. Determining water saturation from the microscopic pore level, combined with actual measurement data, more accurately reflects the actual moisture content of different pore sizes in the coal seam than traditional methods, reducing calculation errors caused by differences in coal types (such as the different pore structures of lignite and anthracite). Based on the actual water saturation corresponding to each pore size, the length occupied by methane in the pores corresponding to each pore size at the actual water saturation level is determined. This study considers the relationship between water saturation and methane occupancy length, providing a more reasonable physical description of methane distribution in the pores of water-bearing coal seams, which helps to more accurately calculate methane adsorption-related parameters. In water-bearing coal seams, different pore structures affect the methane adsorption mode. By calculating the total methane adsorption volume and total methane adsorption surface area, and then using a pre-defined methane adsorption capacity determination model combined with these factors, the total methane adsorption capacity of the target coal sample is determined. Furthermore, the total methane adsorption capacity of the coal seam is predicted, resulting in highly accurate and reliable predictions. Attached Figure Description

[0040] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0041] Figure 1 This is an application scenario diagram of the method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions, provided in one embodiment of this application.

[0042] Figure 2 A flowchart of a method for predicting the amount of methane adsorption in a coal seam considering water-bearing conditions, provided as an embodiment of this application;

[0043] Figure 3 A flowchart of a method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions, provided for another embodiment of this application;

[0044] Figure 4 A pore structure characteristic data diagram of a target coal sample with a water saturation of 17% provided in an embodiment of this application;

[0045] Figure 5NMR signal amplitude diagrams of target coal samples under different moisture content conditions provided in an embodiment of this application;

[0046] Figure 6 A graph showing the isothermal adsorption test results of a target coal sample with a water saturation of 17% provided in an embodiment of this application;

[0047] Figure 7 The figure shows the fitting result of the adsorption amount of a target coal sample with a water saturation of 17% provided in an embodiment of this application;

[0048] Figure 8 A schematic diagram of a predictive device for coal seam methane adsorption considering water content conditions, provided in an embodiment of this application;

[0049] Figure 9 This is a schematic diagram of a device for predicting the amount of methane adsorption in a coal seam, taking into account water content, provided in an embodiment of this application.

[0050] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0051] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0052] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.

[0053] Among current techniques for calculating coalbed methane adsorption, some methods utilize low-field nuclear magnetic resonance (NMR) technology. By measuring the relaxation signal of methane in the pores of coal or shale, a linear correlation model between NMR signal intensity and methane content is established. Combined with the conversion of methane molar mass to adsorption capacity, this directly correlates with the number of microparticles and avoids the systematic errors of traditional gravimetric methods. Other techniques, based on the traditional Langmuir model, use isothermal adsorption experiments on coal samples with different moisture contents (5%~20%) to fit a correction coefficient between water saturation and adsorption constant (a value). The corrected a value is then substituted into the Langmuir equation to calculate the adsorption capacity under water content conditions. This method is applicable to coal seams with medium to low moisture contents (<20%). However, the correction coefficient is only derived from experiments on a single coal type and does not consider the influence of coal sample pore structure on water adsorption, resulting in poor universality. Another method uses a high-pressure adsorption instrument to separate free water and methane in coal samples through a gas-water separation device. The adsorption capacity is measured under different pressures (0-15 MPa) and moisture contents, and a three-dimensional correlation model of pressure-moisture content-adsorption capacity is constructed for quantitative calculation. This can simulate the high-pressure environment in the field, and the results are more consistent with actual mining conditions. However, the experimental equipment is expensive and the operation process is complex, making it difficult to meet the needs of large-scale resource assessment. In summary, existing technologies either completely ignore the influence of water saturation or only consider water conditions from a single dimension. They generally suffer from poor universality, insufficient accuracy, and complex operation, failing to meet the need for accurate calculation of methane adsorption capacity in coal seams considering water conditions. Therefore, researching a method for calculating methane adsorption capacity that couples multiple variables such as pore structure and water saturation is crucial for current coalbed methane development research.

[0054] Therefore, when facing technical problems in existing technologies, in order to accurately determine the total methane adsorption capacity of coal seams under actual water-bearing conditions, the coupling influence of coal reservoir pore structure and water saturation on methane adsorption was fully considered. Multiple NMR signal amplitudes under different water-bearing conditions were obtained, including the actual water saturation of the coal seam where the target coal sample is located, as well as the pore characteristic data of the target coal sample, such as pore size distribution and total pore volume. Since the inhibitory effect of water content distribution with different pore sizes on methane adsorption varies significantly, based on pore characteristic data and NMR signal amplitudes, a pre-set water saturation calculation model was used to decompose the actual water saturation corresponding to each pore size. This avoids the ambiguity of traditional total water saturation calculations and lays the foundation for subsequent accurate calculations. To establish the physical relationship between water-bearing conditions and methane adsorption space, and to get rid of dependence on empirical coefficients, a pre-set capillary length calculation model was adopted, based on the actual water saturation of each pore size. Determining the length occupied by methane in the pores allows for the visualization of the influence of water on adsorption as quantitative data on the usable space for methane, improving the physical rationality of the calculation. Due to differences in pore structure, the adsorption mode of methane varies; some adsorbs throughout the pore volume as micropores, while others adsorb as adsorption layers on the pore surface. Therefore, calculating the total volume and surface area of ​​methane adsorption based on the length occupied by methane enables an effective connection from microscopic pore space to macroscopic adsorption parameters, further improving calculation accuracy. To address the compatibility issue between laboratory data and field coal seams, a pre-defined methane adsorption capacity determination model is used. This model, combined with the total volume and surface area, calculates the total methane adsorption capacity of the target coal sample and extends it to the corresponding coal seam. This approach not only eliminates the need for expensive high-pressure experimental equipment, saving costs and time, but also ensures that the results closely match the actual water content conditions in the field, meeting the needs of large-scale resource assessment and development scheme optimization.

[0055] Figure 1 This is an application scenario diagram of the method for predicting coal seam methane adsorption considering water-bearing conditions provided in one embodiment of this application, such as... Figure 1 As shown in the embodiments of this application, the application scenarios corresponding to the method for predicting the amount of methane adsorption in coal seams considering moisture conditions include: a terminal device 101, a server 102, and a server database 103. The server database 103 pre-stores pore structure characteristic data of multiple coal samples and the NMR signal amplitude of each coal sample under multiple different moisture conditions. This data was obtained through helium porosity testing, low-temperature CO2 adsorption experiments, N2 adsorption experiments, high-pressure mercury intrusion porosimetry experiments, and NMR experiments. The data is stored in the server database 103 according to the correspondence between different coal samples, pore characteristic data, and NMR signal amplitudes under multiple different moisture conditions. When a user sends a prediction request for the amount of methane adsorption in coal seams considering moisture conditions to the server 102 through the terminal device 101, the type of coal sample can be included in the request.

[0056] Specifically, the user sends a prediction request for the amount of methane adsorbed in the coal seam considering moisture conditions to the server 102 via the terminal device 101. When the server 102 receives the prediction request, it retrieves the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different moisture conditions from the server database 103 according to the type of coal sample in the request. Then, based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different moisture conditions, the server 102 uses a preset moisture saturation calculation model to determine the actual moisture saturation corresponding to each pore size in the target coal sample. Finally, it uses a preset capillary length calculation model based on the moisture saturation of the target coal sample... The actual water saturation corresponding to each pore size is used to determine the length of methane occupied in the pores of the target coal sample at the actual water saturation. Based on the length of methane occupied in the pores of each pore size in the target coal sample, the total methane adsorption volume and the total methane adsorption surface area are calculated. Finally, the server 102 uses a preset methane adsorption capacity determination model to determine the total methane adsorption capacity of the target coal sample at the actual water saturation based on the total methane adsorption capacity of the target coal sample. Based on the total methane adsorption capacity of the target coal sample, the server 102 predicts the total methane adsorption capacity of the coal seam where the target coal sample is located at the actual water saturation and sends the prediction result to the terminal device 101 so that the user can obtain the total methane adsorption capacity of the coal seam where the target coal sample is located.

[0057] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0058] Figure 2 A flowchart illustrating a method for predicting the amount of methane adsorption in coal seams considering moisture conditions, as provided in an embodiment of this application, is shown below. Figure 2 As shown, the execution subject of this embodiment is a predictive device for the amount of methane adsorption in coal seams considering moisture conditions. This predictive device can be implemented through a computer program, or through a medium storing the relevant computer program, such as a USB flash drive and / or optical disc; alternatively, it can be implemented through a physical device integrating or installing the relevant computer program, such as a chip, a predictive device for the amount of methane adsorption in coal seams considering moisture conditions, etc. The predictive method for the amount of methane adsorption in coal seams considering moisture conditions provided in this embodiment includes the following steps:

[0059] Step 201: Obtain the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-bearing conditions. The multiple different water-bearing conditions include the actual water saturation of the coal seam where the target coal sample is located.

[0060] The target coal sample refers to a coal sample mined from a water-bearing coal seam that needs to be predicted.

[0061] The different moisture conditions include: 100% moisture saturation, the actual moisture saturation of the coal seam where the target coal sample is located, and 0% moisture saturation.

[0062] The pore structure characteristics data of the target coal sample include pore volume, pore size, porosity, etc., which are obtained by helium porosimetry, low-temperature CO2 adsorption experiment, N2 adsorption experiment and high-pressure mercury intrusion experiment.

[0063] It is understandable that the above experiment was conducted using a dry target coal sample, i.e., a water saturation of 0%.

[0064] Among them, the nuclear magnetic resonance signal amplitude of the target coal sample under multiple different moisture conditions refers to the nuclear magnetic resonance signal amplitude obtained by performing nuclear magnetic resonance experiments on the target coal sample after saturating it with different amounts of water.

[0065] Understandably, after obtaining relevant data from the above-mentioned experiments, the extracted target coal samples are stored in advance in a prediction device for the amount of methane adsorption in coal seams that takes into account water content. Furthermore, multiple coal samples can be tested in advance to obtain data, and the relevant data can be stored in accordance with the coal sample number, as well as the relevant data of the coal seam where the target coal sample is located, such as pressure and temperature.

[0066] For example, a user initiates a prediction request for the amount of methane adsorbed in a coal seam considering water-bearing conditions. After receiving the request, the prediction device for the amount of methane adsorbed in a coal seam considering water-bearing conditions obtains the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-bearing conditions from the pre-stored data based on the request.

[0067] Step 202: Based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water content conditions, the actual water saturation corresponding to each pore size in the target coal sample is determined by using a preset water saturation calculation model.

[0068] The preset water saturation calculation model is pre-configured in the prediction device for coal seam methane adsorption considering water conditions. It is used to calculate the actual water saturation corresponding to each pore size in the target coal sample. The formula corresponding to the preset water saturation calculation model is shown in Equation (1):

[0069] (1)

[0070] In the formula: For aperture d iThe corresponding actual water saturation, dimensionless; i is the number of different pore sizes, such as 1, 2, 3; , , The pore size d of the target coal sample is defined as follows: actual water saturation, water saturation of 100%, and water saturation of 0% in the coal seam where the target coal sample is located. i The corresponding NMR signal amplitude, au.

[0071] For example, i=1, d1=2nm, i=2, d2=5nm, etc.

[0072] It is understandable that the target coal sample has different pore sizes (d) under the conditions of actual water saturation, water saturation of 100%, and water saturation of 0% in the coal seam where the target coal sample is located. i The corresponding NMR signal amplitude is determined based on the pore structure characteristics data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different moisture conditions.

[0073] Specifically, after obtaining the relevant data of the target coal sample, the NMR signal amplitude corresponding to each pore size in the target coal sample under different water conditions is first determined based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water conditions. Then, the NMR signal amplitude corresponding to each pore size under different water conditions is sequentially input into the preset water saturation calculation model to determine the actual water saturation corresponding to each pore size in the target coal sample.

[0074] Step 203: Using a preset capillary length calculation model, based on the actual water saturation corresponding to each pore size in the target coal sample, determine the length occupied by methane in each pore size in the target coal sample under the actual water saturation.

[0075] The pre-configured capillary length calculation model is pre-configured in the prediction device for methane adsorption in coal seams considering water content conditions. It is used to calculate the length of methane occupied in the pores corresponding to each pore size in the target coal sample. The formula corresponding to the pre-configured capillary length calculation model is shown in Equation (2):

[0076] (2)

[0077] In the formula: For the pore size d at actual water saturation i The corresponding length occupied by methane in the pore, in meters; For aperture d i The corresponding hole length, in meters (m); For aperture d i The corresponding actual water saturation is dimensionless.

[0078] in, V i For aperture d i The corresponding orifice volume, m 3 / kg.

[0079] Specifically, after obtaining the actual water saturation corresponding to each pore size in the target coal sample, the values ​​are sequentially input into the preset capillary length calculation model to determine the length of methane occupied in each pore size in the target coal sample under the actual water saturation.

[0080] The length occupied by methane refers to the actual length of the space occupied by methane in the entire pore space, excluding the space occupied by water.

[0081] Step 204: Calculate the total methane adsorption volume and total methane adsorption surface area based on the length occupied by methane in the pores corresponding to each pore size in the target coal sample.

[0082] Understandably, due to capillary condensation, methane adsorption occurs differently in different pore structures. Some methane is adsorbed within the pore volume as micropores, while some is adsorbed on the pore surface as a monolayer. Therefore, the total volume of methane adsorbed refers to the total volume of methane adsorbed through micropore filling, while the total surface area of ​​methane adsorbed refers to the total surface area of ​​methane adsorbed through monolayer adsorption.

[0083] Therefore, based on the length occupied by methane in the pores corresponding to each pore size in the target coal sample, the total volume and total surface area of ​​methane adsorption are calculated using the cylinder volume calculation formula and the cylinder surface area calculation formula, respectively.

[0084] For example, the aperture is d i The length occupied by methane is The total volume of methane adsorbed is The total surface area for methane adsorption is .

[0085] Step 205: Based on the total methane adsorption volume and total methane adsorption surface area, the total methane adsorption amount of the target coal sample under the actual water saturation is determined using a preset methane adsorption amount determination model, and the total methane adsorption amount of the coal seam where the target coal sample is located is predicted based on the total methane adsorption amount of the target coal sample under the actual water saturation.

[0086] Among them, the preset methane adsorption capacity determination model is pre-configured in the prediction device for methane adsorption capacity of coal seams that takes into account water content, and is used to determine the total methane adsorption capacity of the target coal sample under the actual water saturation.

[0087] Specifically, after calculating the total volume and surface area of ​​methane adsorption, these are input into a preset methane adsorption capacity determination model. The model determines the total methane adsorption capacity of the target coal sample under the actual water saturation based on preset logic. Then, using the total methane adsorption capacity of the target coal sample as a benchmark, the total methane adsorption capacity of the coal seam where the target coal sample is located is predicted. For example, data such as the total volume, actual pressure, and actual temperature of the coal seam are obtained to predict the total amount of methane adsorbed by the coal seam.

[0088] This application provides a method for predicting the methane adsorption capacity of coal seams considering moisture conditions. It acquires pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different moisture conditions. These multiple moisture conditions include the actual moisture saturation of the coal seam where the target coal sample is located. Based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different moisture conditions, a preset moisture saturation calculation model is used to determine the actual moisture saturation corresponding to each pore size in the target coal sample. A preset capillary length calculation model is used based on the actual moisture saturation of the target coal sample at each pore size. The actual water saturation corresponding to each pore size is used to determine the length occupied by methane in the pores of the target coal sample at the actual water saturation. Based on the length occupied by methane in the pores of each pore size in the target coal sample, the total methane adsorption volume and the total methane adsorption surface area are calculated. According to the total methane adsorption volume and the total methane adsorption surface area, a preset methane adsorption capacity determination model is used to determine the total methane adsorption capacity of the target coal sample at the actual water saturation. Based on the total methane adsorption capacity of the target coal sample, the total methane adsorption capacity of the coal seam where the target coal sample is located is predicted at the actual water saturation.

[0089] The pore structure of coal plays a crucial role in methane adsorption; different pore sizes, shapes, and connectivity affect the adsorption capacity and amount of methane. Obtaining pore structure characteristic data of target coal samples provides important basic information for accurately predicting methane adsorption, enabling a more precise understanding of the methane adsorption characteristics of coal seams. By acquiring NMR signal amplitudes under multiple different moisture conditions, the existence state and distribution of methane in the coal seam can be comprehensively understood when moisture content changes, making the prediction results closer to reality. Based on pore structure characteristic data and NMR signal amplitudes under different moisture conditions, the actual water saturation corresponding to each pore size in the target coal sample is determined. Determining water saturation from the microscopic pore level, combined with actual measurement data, more accurately reflects the actual moisture content of different pore sizes in the coal seam than traditional methods, reducing calculation errors caused by differences in coal types (such as the different pore structures of lignite and anthracite). Based on the actual water saturation corresponding to each pore size, the length occupied by methane in the pores corresponding to each pore size at the actual water saturation level is determined. This study considers the relationship between water saturation and methane occupancy length, providing a more reasonable physical description of methane distribution in the pores of water-bearing coal seams, which helps to more accurately calculate methane adsorption-related parameters. In water-bearing coal seams, different pore structures affect the methane adsorption mode. By calculating the total methane adsorption volume and total methane adsorption surface area, and then using a pre-defined methane adsorption capacity determination model combined with these factors, the total methane adsorption capacity of the target coal sample is determined. Furthermore, the total methane adsorption capacity of the coal seam is predicted, resulting in highly accurate and reliable predictions.

[0090] As an optional implementation, based on the above embodiments, the actual water saturation corresponding to each pore size in the target coal sample is determined using a preset water saturation calculation model, based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water content conditions. This includes:

[0091] Based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water content conditions, the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water content conditions is determined.

[0092] Based on the NMR signal amplitudes of each pore size in the target coal sample under multiple different water content conditions, the actual water saturation corresponding to each pore size in the target coal sample is determined using a preset water saturation calculation model.

[0093] Specifically, the pore structure characteristic data of the target coal sample obtained includes the full pore size distribution characteristic data of the coal sample. The prediction device for the methane adsorption of coal seam considering the water-bearing conditions uses a pre-set logical rule to associate the full pore size distribution characteristic data of the target coal sample with the NMR signal amplitude of the target coal sample under multiple different water-bearing conditions, so as to obtain the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water-bearing conditions. Then, the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water-bearing conditions is input into the preset water saturation calculation model to calculate the actual water saturation corresponding to each pore size in turn.

[0094] The pre-set logic rules can adopt the aperture and relaxation time conversion method defined in GBT+42035-2022.

[0095] The method for predicting coal seam methane adsorption considering moisture conditions provided in this application determines the actual moisture saturation corresponding to each pore size in the target coal sample based on the pore structure characteristic data and the NMR signal amplitude of the target coal sample under multiple different moisture conditions. This includes: determining the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different moisture conditions based on the pore structure characteristic data and the NMR signal amplitude of the target coal sample under multiple different moisture conditions; and determining the actual moisture saturation corresponding to each pore size in the target coal sample based on the NMR signal amplitude corresponding to each pore size under multiple different moisture conditions using a pre-set moisture saturation calculation model. The pore structure characteristic data reflects key information such as the distribution, size, and shape of pores inside the coal sample, while the NMR signal amplitude is directly related to the moisture content in the coal. By comprehensively considering these two important factors, the actual moisture content of each pore size in the coal sample can be reflected more comprehensively and accurately, reducing the deviation caused by a single factor and thus improving the accuracy of moisture saturation measurement. By refining the water saturation to each pore size, more accurate data support is provided for subsequent determination of methane adsorption content, thereby improving the accuracy of prediction.

[0096] As an optional implementation, based on the above embodiments, a preset capillary length calculation model is used to determine the length of methane occupied in the pores corresponding to each pore size in the target coal sample at the actual water saturation level, based on the actual water saturation level of each pore size in the target coal sample. This includes:

[0097] The pore length corresponding to each pore size in the target coal sample is calculated based on the pore structure characteristic data of the target coal sample.

[0098] A pre-defined capillary length calculation model was used to determine the length of methane occupied in the pores of each pore size in the target coal sample under the actual water saturation, based on the actual water saturation and the pore length corresponding to each pore size in the target coal sample.

[0099] It is understandable that the pore structure characteristic data of the target coal sample includes the total pore size and the pore volume corresponding to each pore size. Based on the pore volume and pore size data, the pore length corresponding to each pore size can be calculated, such as by using the formula for calculating the volume of a cylinder.

[0100] Specifically, after calculating the pore length corresponding to each pore diameter in the target coal sample, the pore length corresponding to each pore diameter and the actual water saturation are sequentially input into the preset capillary length calculation model, as shown in Equation (2), so that the length occupied by methane in each pore corresponding to the current actual water saturation can be determined.

[0101] The method for predicting methane adsorption in coal seams considering moisture content provided in this application employs a pre-set capillary length calculation model based on the actual moisture saturation corresponding to each pore size in the target coal sample. This model determines the length of methane occupied in the pores corresponding to each pore size at the actual moisture saturation. The method includes: calculating the pore length corresponding to each pore size in the target coal sample based on the pore structure characteristic data; and using the pre-set capillary length calculation model based on the actual moisture saturation and pore length corresponding to each pore size in the target coal sample to determine the length of methane occupied in the pores corresponding to each pore size at the actual moisture saturation. Calculating the pore length corresponding to each pore size through pore structure characteristic data expands the geometric characteristics of coal sample pores from a simple description of pore size to a precise quantification of pore length, providing a more comprehensive and in-depth understanding of the three-dimensional structure of coal sample pores. The actual moisture saturation reflects the occupancy of water in the coal pores; combining this with the pore length corresponding to each pore size to determine the methane occupied length provides a clear view of the influence of moisture on the methane storage space. Determining the length occupied by methane in pores of different sizes at the actual water saturation level allows for a more accurate calculation of the amount of methane adsorbed in pores of different sizes in a coal sample.

[0102] As an optional implementation, based on the above embodiments, the total methane adsorption volume and total methane adsorption surface area are calculated based on the methane capillary length corresponding to each pore size in the target coal sample, including:

[0103] Determine the critical pore size corresponding to methane in coal seams;

[0104] Calculate the methane storage volume in each pore of the target coal sample whose pore size is less than or equal to the critical pore size, and determine the sum of the volumes as the total methane adsorption volume;

[0105] Calculate the methane storage area in each pore of the target coal sample with a pore size greater than the critical pore size, and determine the sum of the areas as the total methane adsorption surface area.

[0106] The critical pore size is the boundary pore size used to distinguish the adsorption state of methane. The formula for calculating the critical pore size is shown in equation (3).

[0107] (3)

[0108] In the formula: d c Where V is the critical aperture, in meters; L The molar volume of methane is 3.8 × 10⁻⁶. -5 m 3 / mol; γ is the surface tension of methane, 0.03 N / m; p is the current pressure of the coal seam, Pa; p0 is the saturated vapor pressure, Pa; θ is the contact angle of methane on the adsorbent, θ=0°; T is the actual temperature of the coal seam, K; R is the methane constant, 8.314 J / mol.

[0109] in, p c T represents the critical pressure of methane, in Pa; c ν is the critical temperature of methane, in K.

[0110] It should be noted that, due to the effect of capillary condensation, in pores with a pore size smaller than the critical pore size, methane forms a liquid under the action of capillary condensation, that is, it is adsorbed in the pores by filling the micropores; in pores with a pore size larger than the critical pore size, it is adsorbed on the pore surface by monolayer adsorption.

[0111] It is understandable that, due to the different temperatures of each coal seam and the varying pressures of the coal seam during mining, the critical aperture is affected by the temperature and pressure of the coal seam.

[0112] Optionally, the total volume of methane adsorption is given by the formula The calculated total surface area of ​​methane adsorption is given by the formula. Calculated.

[0113] Specifically, after obtaining the critical pore size of methane, the pore size data is divided into those less than or equal to the critical pore size and those greater than the critical pore size based on the pore characteristic data of the target coal sample. The pore size values ​​less than or equal to the critical pore size and the corresponding length of methane occupied in the pore are then substituted into the formula. In this process, the methane storage volume corresponding to each pore size is calculated, and the total methane adsorption volume is obtained by summing them up. The pore size values ​​larger than the critical pore size and the corresponding length of methane occupied in the pores are substituted into the formula. In this process, the methane storage area corresponding to each pore size is calculated, and the total methane adsorption surface area is obtained by summing them up.

[0114] The method for predicting methane adsorption in coal seams considering water content provided in this application calculates the total methane adsorption volume and total methane adsorption surface area based on the methane capillary length corresponding to each pore size in the target coal sample. This includes: determining the critical pore size corresponding to methane in the coal seam; calculating the methane storage volume in pores with pore sizes less than or equal to the critical pore size in the target coal sample, and summing these volumes to determine the total methane adsorption volume; and calculating the methane storage area in pores with pore sizes greater than the critical pore size in the target coal sample, and summing these areas to determine the total methane adsorption surface area. By using the critical pore size as a boundary, the method accurately distinguishes the forms of methane adsorption, calculates the volume and surface area separately according to different adsorption forms, and accurately calculates the volume of methane storage pores with pore sizes less than or equal to the critical pore size, and summing these volumes to determine the total methane adsorption volume, it avoids resource calculation errors caused by insufficient understanding of pore structure. Compared with traditional resource calculation methods based on overall porosity or simple pore size classification, this method can better reflect the actual occurrence of methane in coal seams, thus improving the accuracy and reliability of resource assessment.

[0115] As an optional implementation, based on the above embodiments, the total methane adsorption volume and total methane adsorption surface area are calculated based on the methane capillary length corresponding to each pore size in the target coal sample, including:

[0116] The average tortuosity of the target coal sample was calculated based on the pore structure characteristic data of the target coal sample.

[0117] Based on the length of methane occupied in the pores corresponding to each pore size in the target coal sample, the average tortuosity of the target coal sample, and the critical pore size, the total volume of methane adsorption and the total surface area of ​​methane adsorption are calculated.

[0118] The average tortuosity can be calculated using equation (4).

[0119] (4)

[0120] In the formula: The average tortuosity is dimensionless. Porosity, %.

[0121] The total volume of methane adsorption can be calculated using equation (5).

[0122] (5)

[0123] In the formula: V1 is the total volume of methane adsorption, m 3 / kg; For the pore size d at actual water saturation i The corresponding length occupied by methane in the pore, in meters; The average tortuosity is dimensionless.

[0124] The total surface area of ​​methane adsorption can be calculated using equation (6).

[0125] (6)

[0126] In the formula: S2 is the total surface area of ​​methane adsorption, m 2 / kg; For the pore size d at actual water saturation i The corresponding length occupied by methane in the pore, in meters; The average tortuosity is dimensionless.

[0127] Specifically, porosity is extracted from the pore structure characteristic data of the target coal sample and substituted into equation (6) to calculate the average tortuosity of the target coal sample. Then, the pore diameter values ​​less than or equal to the critical pore diameter and the corresponding length values ​​occupied by methane in the pores are substituted into equation (4) to calculate the total volume of methane adsorption. The pore diameter values ​​greater than the critical pore diameter and the corresponding length values ​​occupied by methane in the pores are substituted into equation (5) to calculate the total surface area of ​​methane adsorption.

[0128] The method for predicting methane adsorption in coal seams considering moisture conditions provided in this application calculates the total methane adsorption volume and total methane adsorption surface area based on the methane capillary length corresponding to each pore size in the target coal sample. This includes: calculating the average tortuosity of the target coal sample based on its pore structure characteristic data; and calculating the total methane adsorption volume and total methane adsorption surface area based on the length of methane occupied in each pore size, the average tortuosity of the target coal sample, and the critical pore size. By calculating the average tortuosity of the target coal sample based on pore structure characteristic data, the complexity of the coal sample pores can be quantified more accurately. Compared to considering only simple parameters such as pore size and pore volume, the average tortuosity can more comprehensively reflect the actual geometry of the pores, providing crucial information for a deeper understanding of the pore structure of the coal sample. By combining the average tortuosity with the length occupied by methane in pores of different sizes, a more comprehensive pore structure characterization system can be constructed. This system considers not only the size of the pores and the length of methane distribution within them, but also the tortuosity of the pore paths, thus more realistically reflecting the occurrence and migration environment of methane in coal samples. Introducing the average tortuosity makes the calculated total methane adsorption volume and total methane adsorption surface area closer to reality, providing more reliable data support for coalbed methane resource assessment.

[0129] As an optional implementation, based on the above embodiments, the formula corresponding to the preset methane adsorption amount determination model is: Where n is the total methane adsorption amount of the target coal sample, and m 3 / kg; V1 is the total volume of methane adsorption, m 3 / kg; R is the methane gas constant, kJ / mol; T is the actual temperature of the coal seam, K; p0 is the saturated vapor pressure, Pa; p is the current pressure of the coal seam, Pa; E is the adsorption characteristic parameter; k is the non-uniformity coefficient of the coal and rock surface; S2 is the total surface area for methane adsorption, m² 2 ;a m,g m is the cross-sectional area of ​​a methane molecule. 2 N A ρ is Avogadro's constant; gT The density of methane under standard conditions is kg / m³. 3 ;p L Where is the Langmuir pressure, Pa; M is the amount of methane, kg / mol.

[0130] Among them, R, E, k, a m,g N A ρ gT Both M and M are constant values ​​that can be pre-input into a prediction device for the methane adsorption of coal seams that takes into account water content, or the numerical correspondence can be directly filled into the formula corresponding to the model.

[0131] Where, p L The Langmuir pressure, measured by isothermal adsorption experiments on target coal samples, can be pre-input into a prediction device for the methane adsorption capacity of coal seams that takes into account moisture content. It is understood that different coal samples will have different corresponding pressures. L different.

[0132] Specifically, after calculating the total methane adsorption volume V1 and the total methane adsorption surface area S2, these values ​​are input into the formula corresponding to the preset methane adsorption amount determination model. Then, the current pressure and temperature of the coal seam are obtained and input into the formula to determine the total amount of methane adsorbed by the target coal sample under the actual water saturation.

[0133] It is understandable that as mining conditions change, coal seam pressure will change accordingly. Therefore, even if the actual water saturation remains unchanged, pressure changes will also cause changes in the amount of methane adsorbed.

[0134] The method for predicting methane adsorption in coal seams considering water-bearing conditions provided in this application presupposes the following formula for determining the methane adsorption amount: Where n is the total methane adsorption amount of the target coal sample, and m 3 / kg; V1 is the total volume of methane adsorption, m 3 / kg; R is the methane gas constant, kJ / mol; T is the actual temperature of the coal seam, K; p0 is the saturated vapor pressure, Pa; p is the current pressure of the coal seam, Pa; E is the adsorption characteristic parameter; k is the non-uniformity coefficient of the coal and rock surface; S2 is the total surface area for methane adsorption, m² 2 ;a m,gm is the cross-sectional area of ​​a methane molecule. 2 N A ρ is Avogadro's constant; gT The density of methane under standard conditions is kg / m³. 3 ;p L Where is the Langmuir pressure, Pa; M is the amount of methane, kg / mol. The formula corresponding to the preset methane adsorption capacity determination model can respond quickly and provide methane adsorption capacity determination results in a timely manner. This not only significantly reduces the number of field drilling, sampling, and testing operations, thereby saving a lot of manpower, material resources, and time costs, but also improves the accuracy of predicting methane adsorption capacity in coal seams that take into account water-bearing conditions.

[0135] Figure 3 A flowchart of a method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions, as provided in another embodiment of this application, is shown below. Figure 3 As shown, the method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions provided in this embodiment includes the specific processes of determining the actual water saturation corresponding to each pore size in the target coal sample, determining the length occupied by methane in each pore size in the target coal sample under the actual water saturation, and calculating the total volume and total surface area of ​​methane adsorption. Therefore, the method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions provided in this embodiment includes the following steps:

[0136] Step 301: Obtain the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-bearing conditions. The multiple different water-bearing conditions include the actual water saturation of the coal seam where the target coal sample is located.

[0137] Step 302: Based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water content conditions, determine the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water content conditions.

[0138] Step 303: Based on the NMR signal amplitudes corresponding to multiple different water content conditions for each pore size in the target coal sample, the actual water saturation corresponding to each pore size in the target coal sample is determined using a preset water saturation calculation model.

[0139] Step 304: Calculate the pore length corresponding to each pore diameter in the target coal sample based on the pore structure characteristic data of the target coal sample.

[0140] Step 305: Using a preset capillary length calculation model, based on the actual water saturation corresponding to each pore size in the target coal sample and the pore length corresponding to each pore size in the target coal sample, determine the length occupied by methane in the pores corresponding to each pore size in the target coal sample under the actual water saturation.

[0141] Step 306: Determine the critical pore size corresponding to methane in the coal seam.

[0142] Step 307: Calculate the average tortuosity of the target coal sample based on the pore structure characteristic data of the target coal sample.

[0143] Step 308: Based on the length occupied by methane in the pores corresponding to each pore size in the target coal sample, the critical pore size, and the average tortuosity of the target coal sample, calculate the methane storage volume in the pores with pore sizes less than or equal to the critical pore size in the target coal sample, and determine the sum of the volumes as the total methane adsorption volume.

[0144] Step 309: Based on the length of methane occupied in the pores corresponding to each pore size in the target coal sample, the critical pore size, and the average tortuosity of the target coal sample, calculate the methane storage area in the pores with pore sizes larger than the critical pore size in the target coal sample, and determine the sum of the areas as the total methane adsorption surface area.

[0145] Step 310: Based on the total methane adsorption volume and total methane adsorption surface area, the total methane adsorption amount of the target coal sample under the actual water saturation is determined using a preset methane adsorption amount determination model, and the total methane adsorption amount of the coal seam where the target coal sample is located is predicted based on the total methane adsorption amount of the target coal sample under the actual water saturation.

[0146] In this embodiment, the implementation method and technical effect of steps 301-310 are similar to those of the corresponding solutions in the above embodiments, and will not be repeated here.

[0147] For example, the steps for predicting the moisture content of a target coal sample with an actual moisture saturation of 17% are as follows:

[0148] Understandably, before starting the prediction, the target coal sample is first subjected to helium porosity testing, low-temperature CO2 adsorption experiments, N2 adsorption experiments, and high-pressure mercury intrusion porosimetry to obtain the pore structure characteristic data of the target coal sample, such as... Figure 4 As shown, the porosity is 4.74%. The target coal sample was then saturated with different amounts of water, and nuclear magnetic resonance (NMR) tests were performed to obtain the following results: Figure 5 The NMR signal amplitudes of the target coal sample are shown under multiple different moisture content conditions. Isothermal adsorption experiments were performed on the target coal sample to obtain p... L =1.12×10 6 Pa. The above data, along with the pressure and temperature of the coal seam where the target sample is located, are pre-stored in a prediction device for the methane adsorption capacity of the coal seam, taking into account the water content.

[0149] At the start of the prediction, the total methane adsorption amount of the target coal sample under different pressures is obtained through steps 301-310.

[0150] To further verify the accuracy of the method provided, isothermal adsorption experiments were conducted on the target coal sample to obtain the methane adsorption capacity of the target coal sample under different pressures at a water saturation of 17%. Figure 6 As shown.

[0151] The total methane adsorption amount of the target coal sample under different pressures predicted using the method of this application is compared with the total methane adsorption amount of the target coal sample under different pressures obtained by isothermal adsorption experiments. The results are shown below. Figure 7 The results are shown.

[0152] from Figure 7 As can be seen, the data predicted using the method of this application is very close to the data obtained from experiments, thus proving the reliability of the method of this application.

[0153] Figure 8 A schematic diagram of a predictive device for coal seam methane adsorption considering water content, provided in an embodiment of this application, is shown below. Figure 8 As shown, the prediction device for coal seam methane adsorption considering water-bearing conditions provided in this embodiment is located in the prediction equipment for coal seam methane adsorption considering water-bearing conditions. The prediction device 80 for coal seam methane adsorption considering water-bearing conditions provided in this embodiment includes: an acquisition module 81, a determination module 82, a calculation module 83, and a prediction module 84.

[0154] The acquisition module 81 is used to acquire pore structure characteristic data of the target coal sample and NMR signal amplitude of the target coal sample under multiple different water-saturation conditions, including the actual water saturation of the coal seam where the target coal sample is located. The determination module 82 is used to determine the actual water saturation corresponding to each pore size in the target coal sample based on the pore structure characteristic data and NMR signal amplitude of the target coal sample under multiple different water-saturation conditions using a preset water saturation calculation model. The determination module 82 is also used to calculate the actual water saturation corresponding to each pore size in the target coal sample using a preset capillary length calculation model. The system uses a combination of a calculation module 83 and a prediction module 84 to determine the length of methane adsorption in each pore size of the target coal sample at the actual water saturation level. The calculation module 83 calculates the total methane adsorption volume and total methane adsorption surface area based on the length of methane adsorption in each pore size of the target coal sample. The determination module 82 also determines the total methane adsorption amount of the target coal sample at the actual water saturation level using a preset methane adsorption amount determination model based on the total methane adsorption volume and total methane adsorption surface area.

[0155] The prediction device for coal seam methane adsorption considering water-bearing conditions provided in this embodiment can perform... Figure 2The implementation principles and technical effects of the methods shown are similar, and will not be repeated here.

[0156] Optionally, the determining module 82, when determining the actual water saturation corresponding to each pore size in the target coal sample based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-content conditions, specifically uses the following methods: determining the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water-content conditions based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-content conditions; and determining the actual water saturation corresponding to each pore size in the target coal sample based on the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water-content conditions using the preset water saturation calculation model.

[0157] Optionally, the determining module 82, when using a preset capillary length calculation model to determine the length of methane occupied in the pores corresponding to each pore size in the target coal sample at the actual water saturation level, specifically performs the following: calculating the pore length corresponding to each pore size in the target coal sample based on the pore structure characteristic data of the target coal sample; and using the preset capillary length calculation model to determine the length of methane occupied in the pores corresponding to each pore size in the target coal sample at the actual water saturation level and the pore length corresponding to each pore size in the target coal sample.

[0158] Optionally, the calculation module 83, when calculating the total methane adsorption volume and total methane adsorption surface area based on the methane capillary length corresponding to each pore size in the target coal sample, is specifically used for: determining the critical pore size corresponding to methane in the coal seam; calculating the methane storage volume in pores with pore sizes less than or equal to the critical pore size in the target coal sample, and determining the sum of the volumes as the total methane adsorption volume; calculating the methane storage area in pores with pore sizes greater than the critical pore size in the target coal sample, and determining the sum of the areas as the total methane adsorption surface area.

[0159] Optionally, the calculation module 83, when calculating the total methane adsorption volume and total methane adsorption surface area based on the methane capillary length corresponding to each pore size in the target coal sample, is specifically used for: calculating the average tortuosity of the target coal sample based on the pore structure characteristic data of the target coal sample; and calculating the total methane adsorption volume and total methane adsorption surface area based on the length of methane occupied in the pores corresponding to each pore size in the target coal sample, the average tortuosity of the target coal sample, and the critical pore size.

[0160] The formula corresponding to the model for determining the preset methane adsorption capacity is: Where, n is the total methane adsorption amount of the target coal sample; V1 is the total methane adsorption volume; R is the methane gas constant; T is the actual temperature of the coal seam; p0 is the saturated vapor pressure; p is the current pressure of the coal seam; E is the adsorption characteristic parameter; k is the non-uniformity coefficient of the coal surface; S2 is the total surface area of ​​methane adsorption; a m,g N is the cross-sectional area of ​​a methane molecule. A ρ is Avogadro's constant; gT p is the density of methane under standard conditions. L Where is the Langmuir pressure; M is the amount of methane.

[0161] Figure 9 A schematic diagram of a predictive device for coal seam methane adsorption considering moisture conditions, provided in an embodiment of this application, is shown below. Figure 9 As shown, the prediction device 90 for coal seam methane adsorption considering water content provided in this embodiment includes: a processor 91 and a memory 92 communicatively connected to the processor.

[0162] The memory 92 stores computer-executed instructions; the processor 91 executes the computer-executed instructions stored in the memory 92 to implement the method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions provided in any of the above embodiments. Related explanations can be understood by referring to the relevant descriptions and effects corresponding to the steps in the accompanying drawings, and will not be elaborated upon here.

[0163] The program may include program code, which includes computer-executable instructions. Memory 92 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0164] In this embodiment, the memory 92 and the processor 91 are connected via a bus. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 9 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0165] This application also provides a computer-readable storage medium storing computer-executable instructions. When executed by a processor, these instructions are used to implement the method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions provided in any of the above embodiments. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0166] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method for predicting the amount of methane adsorption in coal seams considering water-bearing conditions provided in any of the above embodiments.

[0167] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0168] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0169] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0170] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0171] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0172] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0173] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not described in detail in a particular embodiment can be referred to in the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as these combinations of technical features do not contradict each other, they should be considered within the scope of this specification. Those skilled in the art, upon considering the specification and practicing the invention disclosed herein, will readily conceive of other embodiments of this application. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary technical means in the art not disclosed in this application. The specification and embodiments are considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0174] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for predicting the amount of methane adsorption in coal seams considering water content, characterized in that, The method includes: The pore structure characteristics of the target coal sample and the nuclear magnetic resonance signal amplitude of the target coal sample under multiple different water-bearing conditions are obtained. The multiple different water-bearing conditions include the actual water saturation of the coal seam where the target coal sample is located. Based on the pore structure characteristics of the target coal sample and the NMR signal amplitudes of the target coal sample under multiple different moisture conditions, a preset moisture saturation calculation model is used to determine the actual moisture saturation corresponding to each pore size in the target coal sample. This includes: determining the NMR signal amplitudes corresponding to each pore size in the target coal sample under multiple different moisture conditions based on the pore structure characteristics of the target coal sample and the NMR signal amplitudes of the target coal sample under multiple different moisture conditions; and determining the actual moisture saturation corresponding to each pore size in the target coal sample based on the NMR signal amplitudes corresponding to each pore size under multiple different moisture conditions using a preset moisture saturation calculation model. The preset water saturation calculation model is pre-configured in the prediction device for coal seam methane adsorption considering water conditions, and is used to calculate the actual water saturation corresponding to each pore size in the target coal sample. The formula corresponding to the preset water saturation calculation model is shown in equation (1): （1） In the formula: For aperture d i The corresponding actual water saturation, dimensionless; i is the number of different pore sizes, such as 1, 2, 3; , , The pore size d of the target coal sample is defined as follows: actual water saturation, water saturation of 100%, and water saturation of 0% in the coal seam where the target coal sample is located. i The corresponding NMR signal amplitude, au; using a preset capillary length calculation model based on the actual water saturation corresponding to each pore size in the target coal sample, the length occupied by methane in each pore size corresponding to the actual water saturation is determined; The total volume and total surface area of ​​methane adsorption are calculated based on the length occupied by methane in each pore size of the target coal sample. Based on the total methane adsorption volume and the total methane adsorption surface area, a preset methane adsorption capacity determination model is used to determine the total methane adsorption capacity of the target coal sample at the actual water saturation level. Based on the total methane adsorption capacity of the target coal sample, the total methane adsorption capacity of the coal seam where the target coal sample is located is predicted at the actual water saturation level. The preset capillary length calculation model, based on the actual water saturation level corresponding to each pore size in the target coal sample, determines the length occupied by methane in the pores corresponding to each pore size in the target coal sample at the actual water saturation level, including: The pore length corresponding to each pore diameter in the target coal sample is calculated based on the pore structure characteristic data of the target coal sample. A pre-defined capillary length calculation model is used to determine the length of methane occupied in the pores corresponding to each pore size of the target coal sample at the actual water saturation and the pore length corresponding to each pore size of the target coal sample, based on the actual water saturation. The calculation of the total methane adsorption volume and total methane adsorption surface area based on the length occupied by methane in each pore corresponding to each pore size in the target coal sample includes: Determine the critical pore size corresponding to methane in the coal seam; Calculate the methane storage volume in each pore of the target coal sample whose pore size is less than or equal to the critical pore size, and determine the sum of the volumes as the total methane adsorption volume; Calculate the methane storage area in each pore of the target coal sample whose pore size is larger than the critical pore size, and determine the sum of the areas as the total methane adsorption surface area.

2. The method according to claim 1, characterized in that, The calculation of the total methane adsorption volume and total methane adsorption surface area based on the methane capillary length corresponding to each pore size in the target coal sample includes: The average tortuosity of the target coal sample is calculated based on the pore structure characteristic data of the target coal sample; Based on the length of methane occupied in the pores corresponding to each pore size in the target coal sample, the average tortuosity of the target coal sample, and the critical pore size, the total volume of methane adsorption and the total surface area of ​​methane adsorption are calculated.

3. The method according to claim 1, characterized in that, The formula corresponding to the preset methane adsorption capacity determination model is: Where, n is the total methane adsorption amount of the target coal sample; V1 is the total methane adsorption volume; R is the methane gas constant; T is the actual temperature of the coal seam; p0 is the saturated vapor pressure; p is the current pressure of the coal seam; E is the adsorption characteristic parameter; k is the non-uniformity coefficient of the coal surface; S2 is the total surface area of ​​methane adsorption; a m,g N is the cross-sectional area of ​​a methane molecule. A ρ is Avogadro's constant; gT p is the density of methane under standard conditions. L Where is the Langmuir pressure; M is the amount of methane.

4. An apparatus for predicting the amount of methane adsorption in a coal seam considering moisture conditions, used to execute the method for predicting the amount of methane adsorption in a coal seam considering moisture conditions as described in claim 1, characterized in that, include: The acquisition module is used to acquire pore structure feature data of the target coal sample and the nuclear magnetic resonance signal amplitude of the target coal sample under multiple different water-bearing conditions, wherein the multiple different water-bearing conditions include: the actual water saturation of the coal seam where the target coal sample is located; The determination module is used to determine the actual water saturation corresponding to each pore size in the target coal sample based on the pore structure characteristic data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-bearing conditions, using a preset water saturation calculation model; the preset water saturation calculation model is pre-configured in the prediction device for coal seam methane adsorption considering water-bearing conditions, and is used to calculate the actual water saturation corresponding to each pore size in the target coal sample. The formula corresponding to the preset water saturation calculation model is shown in equation (1): （1） In the formula: For aperture d i The corresponding actual water saturation, dimensionless; i is the number of different pore sizes, such as 1, 2, 3; , , The pore size d of the target coal sample is defined as follows: actual water saturation, water saturation of 100%, and water saturation of 0% in the coal seam where the target coal sample is located. i The corresponding NMR signal amplitude, au; The determining module is also used to determine the length of methane occupied in the pores corresponding to each pore size in the target coal sample at the actual water saturation level by using a preset capillary length calculation model. The calculation module is used to calculate the total methane adsorption volume and the total methane adsorption surface area based on the length occupied by methane in the pores corresponding to each pore size in the target coal sample. The determining module is further configured to determine the total methane adsorption amount of the target coal sample at the actual water saturation level by using a preset methane adsorption amount determination model based on the total methane adsorption volume and the total methane adsorption surface area. The prediction module is used to predict the total methane adsorption of the coal seam where the target coal sample is located at the actual water saturation level, based on the total methane adsorption of the target coal sample. The determining module is specifically used to determine the NMR signal amplitude corresponding to each pore size in the target coal sample under multiple different water-cut conditions based on the pore structure feature data of the target coal sample and the NMR signal amplitude of the target coal sample under multiple different water-cut conditions; and to determine the actual water saturation corresponding to each pore size in the target coal sample based on the NMR signal amplitude corresponding to each pore size under multiple different water-cut conditions using a preset water saturation calculation model. The determining module is specifically used to calculate the pore length corresponding to each pore diameter in the target coal sample based on the pore structure characteristic data of the target coal sample; and to determine the length occupied by methane in the pores corresponding to each pore diameter in the target coal sample at the actual water saturation and the pore length corresponding to each pore diameter in the target coal sample under the actual water saturation using a preset capillary length calculation model. The calculation module is specifically used to determine the critical pore size corresponding to methane in the coal seam; calculate the methane storage volume in each pore of the target coal sample whose pore size is less than or equal to the critical pore size, and determine the sum of the volumes as the total methane adsorption volume; calculate the methane storage area in each pore of the target coal sample whose pore size is greater than the critical pore size, and determine the sum of the areas as the total methane adsorption surface area.

5. A device for predicting the amount of methane adsorption in coal seams considering moisture content, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 3.

7. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1 to 3.

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