A method, apparatus, and equipment for determining the content of deep coalbed methane.

Abstract

This disclosure provides a method, apparatus, and device for determining the gas content of deep coal seams. The method includes: acquiring multiple sets of coal seam data from a target well in the area to be tested; processing the coal seam density, natural gamma value, resistivity value, and apparent resistivity value in the coal seam data to obtain the coal seam ash content and coal seam moisture content of each set of coal seam data; acquiring core samples corresponding to a second depth value in the target well, and analyzing and processing the core samples at the second depth value to obtain the coal seam volatiles data corresponding to the second depth value; and determining the gas content of the area to be tested at multiple first depth values ​​based on the coal seam ash content and coal seam moisture content corresponding to a first depth value and the coal seam volatiles data corresponding to the second depth value. The technical solution of this disclosure improves the accuracy of determining the gas content of deep coal seams at different depths by using multiple sets of coal seam data from a target well to determine the gas content of the area to be tested at multiple first depth values.

Description

Technical Field

[0001] This disclosure relates to the field of coal rock gas content technology, and in particular to a method, apparatus, and equipment for determining the content of deep coal rock gas. Background Technology

[0002] With the development of the coalbed methane industry and the continuous deepening of coalbed methane exploration and development, the research on methods for determining the content of deep coalbed methane has received increasing attention.

[0003] The current methods used to determine the content of deep coalbed methane mainly rely on the relationship between well logging volumetric density and ash content to estimate the content. However, such methods use very limited well logging data, resulting in a large cumulative error in the parameters. This leads to inaccuracies in determining the content of deep coalbed methane at different depths, thus affecting the determination of the true distribution of deep coalbed methane content. Summary of the Invention

[0004] This disclosure provides a method, apparatus, and equipment for determining the content of deep coal gas, thereby improving the accuracy of the content of deep coal gas at different depths.

[0005] In a first aspect, embodiments of this disclosure provide a method for determining the content of deep coalbed methane, the method comprising:

[0006] Multiple sets of coal and rock data of the target well in the area to be tested are acquired. The coal and rock data include the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value of the area to be tested at a first depth value. The first depth value is determined based on the depth value range of the area to be tested and a first preset depth adjustment step size.

[0007] By processing the coal density value, natural gamma value, resistivity value and apparent resistivity value in the multiple sets of coal and rock data, the coal ash content and coal moisture content corresponding to each set of coal and rock data are obtained.

[0008] Core samples corresponding to multiple second depth values ​​in the area to be tested are obtained from the target well, and the core samples at the multiple second depth values ​​are analyzed and processed to obtain the coal and rock volatiles data corresponding to the multiple second depth values; wherein, the second depth value is determined based on the depth value range and a second preset depth adjustment step size;

[0009] Based on the coal ash content and coal moisture content corresponding to multiple first depth values, and the coal volatiles data corresponding to multiple second depth values, the gas content of the area to be tested at multiple first depth values ​​is determined.

[0010] Secondly, embodiments of the present invention also provide an apparatus for determining the content of deep coalbed methane, the apparatus comprising:

[0011] The coal and rock data acquisition module is used to acquire multiple sets of coal and rock data of the target well in the area to be tested. The coal and rock data includes the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value of the area to be tested at a first depth value. The first depth value is determined based on the depth value range of the area to be tested and a first preset depth adjustment step.

[0012] The coal and rock ash and moisture content determination module is used to process the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value in the multiple sets of coal and rock data to obtain the coal and rock ash content and coal and rock moisture content corresponding to each set of coal and rock data.

[0013] The coal and rock volatiles data determination module is used to acquire core samples corresponding to multiple second depth values ​​in the area to be tested for the target well, and to analyze and process the core samples at the multiple second depth values ​​to obtain the coal and rock volatiles data corresponding to the multiple second depth values; wherein, the second depth value is determined based on the depth value range and a second preset depth adjustment step size;

[0014] The gas content determination module is used to determine the gas content of the area to be tested at multiple first depth values ​​based on the coal ash content and coal moisture content of coal rock data corresponding to multiple first depth values, and the coal volatile matter data corresponding to multiple second depth values.

[0015] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0016] One or more processors;

[0017] Storage device for storing one or more programs.

[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining the content of deep coal and rock gas as described in any embodiment of the present invention.

[0019] Fourthly, embodiments of the present invention also provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the method for determining the content of deep coalbed methane as described in any of the embodiments of the present invention.

[0020] Fifthly, embodiments of the present invention also provide a computer program product, including a computer program, characterized in that, when executed by a processor, the computer program implements the method for determining the content of deep coalbed methane as described in any embodiment of the present invention.

[0021] The technical solution of this disclosure first acquires multiple sets of coal and rock data of the target well in the area to be tested. These coal and rock data include the coal and rock density, natural gamma ray, resistivity, and apparent resistivity values ​​of the area to be tested at a first depth value. The first depth value is determined based on the depth range of the area to be tested and a first preset depth adjustment step. Then, by processing the coal and rock density, natural gamma ray, resistivity, and apparent resistivity values ​​in the multiple sets of coal and rock data, the coal and rock ash content and coal and rock moisture content corresponding to each set of data are obtained. Further, core samples corresponding to multiple second depth values ​​of the target well in the area to be tested are acquired, and the core samples at the multiple second depth values ​​are analyzed and processed to obtain coal and rock volatiles data corresponding to the multiple second depth values. The second depth values ​​are determined based on the depth range and a second preset depth adjustment step. Finally, based on the coal and rock ash content and coal and rock moisture content of the coal and rock data corresponding to the multiple first depth values, and the coal and rock volatiles data corresponding to the multiple second depth values, the gas content of the area to be tested at the multiple first depth values ​​is determined. This invention addresses the problem in existing technologies that estimate deep coalbed methane content by relating well volume density to ash content, where the cumulative error in the parameters is significant, leading to inaccuracies in determining the content at different depths. The present invention acquires multiple parameters, including coal density, natural gamma ray, resistivity, and apparent resistivity, for the tested area at all first depths, and also acquires coal volatiles data for the tested area at all second depths. After acquiring all parameter data, a relationship is established between the parameter data at the first and second depths, thereby determining the methane content of the tested area at all first depths. This significantly improves the accuracy of determining the methane content at different depths. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of exemplary embodiments of the present invention, the accompanying drawings used in describing the embodiments are briefly introduced below. Obviously, the accompanying drawings described are only a portion of the drawings of the embodiments to be described in this invention, and not all of the drawings. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort.

[0023] Figure 1 This is a schematic flowchart of a method for determining the content of deep coal rock gas provided in an embodiment of this disclosure;

[0024] Figure 2 This is a schematic diagram of the first depth value provided in an embodiment of the present invention;

[0025] Figure 3This is a schematic diagram of the coal ash content and coal moisture content at the first depth, and the coal volatile matter data alignment processing at multiple second depth values ​​provided in the embodiments of the present invention.

[0026] Figure 4 This is a flowchart illustrating another method for determining the content of deep coal rock gas provided in an embodiment of the present invention;

[0027] Figure 5 This is a schematic diagram of the structure of a device for determining the content of deep coal rock gas provided in an embodiment of the present invention;

[0028] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0029] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0030] Before introducing the technical solutions provided by the embodiments of this disclosure, the application scenarios can be illustrated first. The technical solutions provided by the embodiments of this disclosure can be applied to scenarios where the gas content at all depths of deep coal and rock is determined. For example, the gas content of a target well at multiple depths in the test area can be determined based on multiple sets of coal and rock data of the target well in the test area, so as to achieve rapid evaluation or screening of the enrichment degree of coalbed methane. It should be noted that the target well refers to the well selected in the process of coalbed methane exploration and development to determine key parameters such as gas content. The properties of coal seams change significantly at different depths, affecting key parameters such as gas content. Therefore, for a target well, it is necessary to evaluate the coal and rock gas content at these different depth ranges or multiple depth values ​​to determine the gas content, reserves, and development potential of the target well. The test area refers to the spatial depth area within the target well where further exploration of its gas content is planned. Among them, deep coal and rock are affected by pressure, and the gas is more in an adsorbed state, resulting in lower gas content, but the gas reserves may be larger. Based on the technical solution of this disclosure, the gas content of the test area at multiple first depth values ​​is determined based on multiple parameters of the test area at all first depth values, thereby more accurately determining the gas content of deep coal and rock at different depths.

[0031] Example 1

[0032] Figure 1This is a schematic flowchart of a method for determining the gas content of deep coal and rock provided in this embodiment. This embodiment is applicable to the situation where the gas content of deep coal and rock at all depths is determined based on multiple sets of coal and rock data of the target well in the area to be tested. This method can be executed by a device for determining the gas content of deep coal and rock. This device can be implemented in the form of software and / or hardware. The hardware can be a mobile electronic device. This electronic device can execute the method for determining the gas content of deep coal and rock provided in this technical solution.

[0033] like Figure 1 As shown, the method includes:

[0034] S110. Obtain multiple sets of coal and rock data of the target well in the area to be tested.

[0035] In this invention, a target well refers to a well whose key parameters, such as gas content, are determined. Determining the gas content of this well provides a basis for subsequent resource assessment, development plan design, and further drilling deployment. The area to be tested refers to the spatial depth region within the target well where further exploration of its gas content is planned. It should be noted that a target well may have one or multiple areas to be tested. In this embodiment, the area to be tested can be the deep coal and rock region of the target well. Because the total thickness and coal quality of the coal seams in deep coal and rock regions are relatively stable, the total reserves of coal gas may be large. Therefore, this embodiment acquires multiple sets of coal and rock data from deep coal and rock regions. Exploring and evaluating the gas content level within the deep coal and rock region can provide a basis for deciding whether and how to further develop it.

[0036] It should be noted that coal and rock data refers to information about coal and rock obtained through various exploration methods during coalbed methane exploration and development. For example, coal and rock data can include basic coal and rock parameters, well logging data, and laboratory analysis data. Based on different coal and rock data parameters, results such as gas content can be calculated and analyzed. Optionally, coal and rock data can be obtained using logging tools such as density logging, natural gamma logging, sonic logging, and resistivity logging. Within the area to be tested, different depths can contain a set of coal and rock data, so multiple sets of coal and rock data can exist within the depth range of the area to be tested. Because corresponding coal and rock data exist at a certain depth or within a certain depth range, the calculated in-well gas content at that depth or within a certain depth range is accurate.

[0037] The coal and rock data includes the coal and rock density, natural gamma value, resistivity value and apparent resistivity value of the area to be measured at the first depth value. The first depth value is determined based on the depth range of the area to be measured and the first preset depth adjustment step size.

[0038] It should be noted that, as Figure 2As shown, the depth range of the area to be measured refers to the vertical depth interval of the area. During exploration, it is necessary to sample, measure, or analyze coal seams within the depth range of the area to be measured to determine their gas content. Coal seams outside the depth range of the area to be measured can be ignored. In this embodiment, the area to be measured can be a deep coal and rock region, and the depth range of deep coal and rock regions is generally 1500 meters to 3000 meters. For example, the depth range of the area to be measured can be the range of 2000 meters to 2500 meters of the target underground area to be measured.

[0039] The first preset depth adjustment step size refers to the vertical depth increment used each time a measurement continues downward within the depth range of the area to be measured during exploration. It can also be understood as the vertical distance between each test. A smaller first preset depth adjustment step size results in denser measurement points, enabling the capture of subtle changes in the coal seam and improving the ability to distinguish details of coal and gas. Conversely, a larger first preset depth adjustment step size results in sparser measurement points, faster data acquisition, and lower costs, but may miss some crucial details. In actual data acquisition, the first preset depth adjustment step size can be flexibly adjusted according to the complexity of the area to be measured, the target, measurement accuracy, and operational economy, thereby obtaining sufficiently dense stratigraphic information more systematically and economically. For example, the first preset depth adjustment step size can be 1 meter or 10 meters.

[0040] It should be noted that, based on the depth range of the area to be measured, the starting point of the depth range can first be determined. Then, by adjusting the step size according to the first preset depth, a series of discrete measurement depth values, i.e., the first depth values, can be obtained. The starting point of the depth range can be the initial measurement depth of interest in the deep coal and rock layers. The ending point of the depth range can be the final measurement depth of interest in the deep coal and rock layers, which can be understood as the deepest section of the deep coal and rock layers planned to reach in the target well design. When the starting depth of the depth range of the area to be measured is 1000 meters, and the first preset depth adjustment step size is 10 meters, the next measurement depth will be 1010 meters, the next measurement depth will be 1020 meters, and so on. It should be noted that various measurement tools are usually used to obtain the first depth values, such as drilling sounders, acoustic sounding technology, magnetometers, etc., which can provide accurate depth data. It should also be noted that coal and rock data exist under each first depth value, thus there are multiple sets of coal and rock data.

[0041] In coal and rock data, the coal and rock density value refers to the ratio of the mass to the volume of coal and rock, used to describe the compactness and structural characteristics of the coal and rock material. The coal and rock density value in coal and rock data can be represented by DEN, with units of g / cm³. 3The natural gamma value in coal rock data refers to the intensity of gamma rays released during the decay of naturally occurring radioactive elements (such as uranium, potassium, and thorium) in coal rock. The natural gamma value in coal rock data can be represented by GR, and its unit is API. The resistivity value in coal rock data refers to the degree to which the rock, soil, or minerals in the coal rock impede the flow of electric current, indicating the difficulty of current flow within the coal rock. A higher resistivity value indicates that the coal rock is less conductive, and vice versa. The resistivity value in coal rock data can be represented by RT, and its unit is Ω·m. The apparent resistivity value in coal rock data refers to the resistivity of the coal rock obtained through geophysical measurements (such as surface resistivity methods, downhole resistivity logging, etc.). The apparent resistivity value in coal rock data reflects the overall resistivity of the coal rock, not just the resistivity of a single rock layer. The apparent resistivity value in coal rock data can be represented by ρ. s It is expressed as Ω·m. It should be noted that subsequent calculations of coal ash content and coal moisture content require support from parameters such as coal density, natural gamma, resistivity, and apparent resistivity.

[0042] Specifically, by adjusting the step size based on the depth range of the area to be measured and the first preset depth, all first depth values ​​can be determined. Then, multiple sets of coal and rock data for the target well at all first depth values ​​are acquired. The acquired coal and rock data include coal and rock density values, natural gamma values, resistivity values, and apparent resistivity values.

[0043] For example, if the target well's depth in the test area ranges from 500 to 800 meters, and the first preset depth adjustment step is 10 meters, then within this 300-meter range, sampling or measurement will be performed every 10 meters. Furthermore, the coal and rock data sampled or measured every 10 meters includes coal and rock density, natural gamma ray, resistivity, and apparent resistivity. All coal and rock data for the target well at all first depth values ​​in the test area are obtained.

[0044] In this embodiment, well logging data is retrieved, which includes coal and rock data corresponding to at least one detection well in multiple areas to be tested; the data to be used for the target well is retrieved from the well logging data, and multiple sets of coal and rock data associated with the areas to be tested are retrieved from the data to be used.

[0045] Well logging data is typically stored in databases or specialized geological software. It usually includes various logging curves from several wells, corresponding stratigraphic interval information, lithological interpretation, and coal and petrographic characteristics. Inspection wells are used to obtain geological information and coal and petrographic data from areas that are the same as or similar to the area being tested or the target well. Inspection well logging data can provide the geological background and coal and petrographic properties of the target well's area. By acquiring logging data from inspection wells (which may be neighboring or representative wells), the coal and petrographic data of the target well in the area being tested can be inferred. The coal and petrographic data corresponding to inspection wells in multiple areas being tested can include: coal and petrographic density values, natural gamma values, resistivity values, apparent resistivity values, and sonic values.

[0046] Optionally, identifying target wells is an important step in exploration work. Target well selection is typically based on coal and rock data from monitoring wells in multiple areas to be tested, thus selecting the well with the highest exploration value and development potential. Target well selection requires comprehensive consideration of multiple factors. In this embodiment, coal and rock data from monitoring wells in multiple areas to be tested can be retrieved, and the target well can be verified by comparing the monitoring well data.

[0047] The "data to be used" refers to the data selected from all logging data of the target well based on pre-defined requirements or filtering conditions (such as depth range, time period, etc.). Specifically, logging data is retrieved from databases or specialized geological software. A single well may contain coal and rock data in multiple depth ranges, each representing a different geological stratum or coal seam. Therefore, logging data can include coal and rock data from multiple wells in different areas to be tested. Based on the coal and rock data from multiple wells, the well with the greatest exploration value and development potential is compared and verified as the target well. After determining the target well, the "data to be used" for the target well is retrieved from the logging data according to time period and depth range constraints. Finally, the step size is adjusted according to the depth range of the area to be tested and a first preset depth, and multiple sets of coal and rock data associated with the area to be tested are retrieved from the "data to be used," thus obtaining multiple sets of coal and rock data for the target well in the area to be tested.

[0048] S120. By processing the coal density value, natural gamma value, resistivity value and apparent resistivity value in multiple sets of coal and rock data, the coal ash content and coal moisture content corresponding to each set of coal and rock data are obtained.

[0049] It should be noted that coal ash content and coal moisture content are important indicators in coalbed methane exploration, reflecting the mineral composition, hydrate content, and physicochemical properties of the coal seam. The coal ash content, as defined in the data, refers to the proportion of non-combustible minerals in the coal, usually expressed as a percentage. Ash is the residue left after coal combustion, including minerals such as silicon, aluminum, iron, calcium, and magnesium. Higher coal ash content affects coalbed methane storage capacity because the mineral portion typically lacks gas adsorption properties; coal seams with lower ash content generally have better gas storage and transport capabilities. The ash content of coal is usually closely related to its porosity, permeability, and other physical properties. Coal seams with lower ash content typically have higher porosity and better permeability, making them suitable for coalbed methane extraction.

[0050] The coal and rock moisture content in coal and rock data refers to the proportion of water contained in the coal and rock, usually expressed as a percentage. This water can be free water (such as water within the coal seam) or chemical water (such as water adsorbed on the surface of coal particles). Coal seams with high moisture content typically have lower gas adsorption capacity because the water occupies the pore space, reducing the effective porosity of the coal seam. Excessive moisture also affects the permeability and exploitability of coalbed methane. Furthermore, the ratio of surface water to water in the pores affects the adsorption characteristics of the coal; coal seams with higher surface water content have weaker adsorption performance, potentially impacting gas extraction efficiency.

[0051] It should also be noted that there is usually an inverse relationship between the ash content and moisture content of coal. Higher moisture content in coal typically corresponds to lower ash content, and vice versa. In coalbed methane extraction, coal seams with low moisture and low ash content generally possess better gas adsorption and permeability, and are therefore often considered high-quality gas reservoirs. Coal seams with high moisture and high ash content may require additional processing steps (such as dehydration and ash reduction) to improve their recoverability. The moisture and ash content of coal are crucial in coalbed methane development; through proper control of ash and moisture content, the extraction efficiency and economic benefits of coalbed methane can be optimized.

[0052] Specifically, after obtaining multiple sets of coal and rock data, the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value in each set of coal and rock data are processed to obtain the coal and rock ash content and coal and rock moisture content corresponding to each set of coal and rock data.

[0053] In this embodiment, a density normalization parameter is determined based on the coal density values ​​from multiple sets of coal and rock data; wherein the density normalization parameter includes the minimum and maximum density values; a gamma normalization parameter is determined based on the natural gamma values ​​from multiple sets of coal and rock data; wherein the gamma normalization parameter includes the maximum and minimum gamma values; a resistivity normalization parameter is determined based on the resistivity values ​​from multiple sets of coal and rock data; and an apparent resistivity normalization parameter is determined based on the apparent resistivity values ​​from multiple sets of coal and rock data; wherein the apparent resistivity normalization parameter includes the maximum and minimum apparent resistivity values; for multiple sets of coal and rock data, the coal and rock ash content and coal and rock moisture content are determined based on the coal and rock density values, natural gamma values, resistivity values, apparent resistivity values, density normalization parameter, gamma normalization parameter, resistivity normalization parameter, and apparent resistivity normalization parameter.

[0054] When normalizing coal density values, it is usually necessary to first determine the "range" of coal density values ​​across multiple sets of coal data. This involves defining the maximum and minimum density values. The maximum density value refers to the highest density value among multiple sets of coal data. From a geological or coal quality perspective, the maximum density value reflects the extreme case of the highest density in the coal, such as when the coal composition is compact and the content of minerals or metal elements is relatively high, resulting in a coal section with a high density. The minimum density value refers to the lowest density value among multiple sets of coal data. From a geological or coal quality perspective, the minimum density value reflects the extreme case of the lowest density in the coal, such as when high porosity, high volatile matter content, or other mineral content leads to a coal section with an overall low density. When subsequently mapping coal density values ​​to a fixed interval (e.g., [0,1]), these two extreme values ​​are used for interval scaling of the coal density values. It should be noted that density normalization parameters typically refer to a set of key values ​​or configuration parameters used when normalizing data. In this embodiment of the invention, the density normalization parameter refers to the minimum and maximum density values ​​of coal and rock density in multiple sets of coal and rock data. In specific operations, after determining the minimum and maximum density values ​​of coal and rock density, all coal and rock density values ​​can be mapped using the corresponding formula to ensure the consistency of data processing.

[0055] When normalizing natural gamma values, it is usually necessary to first determine the "range" of natural gamma values ​​across multiple sets of coal and rock data, namely the maximum and minimum gamma values. The maximum gamma value refers to the highest natural gamma value among the multiple sets of coal and rock data. It typically corresponds to the portion of the coal and rock sample rich in radioactive elements and serves as a benchmark parameter in the normalization process. The minimum gamma value refers to the lowest natural gamma value among the multiple sets of coal and rock data. It typically corresponds to a lower level of radioactivity or a lower content of elements such as uranium and thorium in the coal and rock sample and is another important benchmark value in the normalization process. When subsequently mapping natural gamma values ​​to a fixed interval (e.g., [0,1]), these two extreme values ​​are used for interval scaling of the natural gamma values. It should be noted that gamma normalization parameters typically refer to a set of key values ​​or configuration parameters used when normalizing data. In this embodiment of the invention, the gamma normalization parameter refers to the maximum and minimum gamma values ​​among multiple sets of coal and rock data. In specific operations, after determining the maximum and minimum gamma values, all natural gamma values ​​can be mapped using the corresponding formula to ensure the consistency of data processing.

[0056] When normalizing resistivity values, it is usually necessary to first determine the "range" of resistivity values ​​across multiple sets of coal and rock data. This includes the maximum and minimum resistivity values. The maximum resistivity value refers to the highest resistivity value among multiple sets of coal and rock data. From a geological or coal quality perspective, the maximum resistivity value typically occurs in coal and rock containing less conductive components, lower porosity, or is dry. The minimum resistivity value refers to the lowest resistivity value among multiple sets of coal and rock data. From a geological or coal quality perspective, the minimum resistivity value reflects conditions such as high fluid saturation, large porosity, or the presence of conductive minerals (e.g., high salt content) in the coal and rock, resulting in lower resistivity. When subsequently mapping resistivity values ​​to a fixed range (e.g., [0,1]), these two extreme values ​​are used for range scaling of the resistivity values. It should be noted that resistivity normalization parameters typically refer to a set of key values ​​or configuration parameters used when normalizing data. In this embodiment of the invention, the resistivity normalization parameters refer to the minimum and maximum resistivity values ​​among multiple sets of coal and rock data. In practice, once the minimum and maximum resistivity values ​​are determined, all resistivity values ​​can be mapped using the corresponding formulas to ensure consistency in data processing.

[0057] When normalizing apparent resistivity values, it is usually necessary to first determine the "range" of apparent resistivity values ​​across multiple sets of coal and petrographic data. This includes the maximum and minimum apparent resistivity values. The maximum apparent resistivity value refers to the highest value among multiple sets of coal and petrographic data. From a geological or coal quality perspective, the maximum apparent resistivity value represents the region in the coal and petrographic sample where current propagation is most difficult. These regions typically have low porosity, low water saturation, or contain fewer conductive minerals, resulting in higher apparent resistivity. The minimum apparent resistivity value refers to the lowest value among multiple sets of coal and petrographic data. From a geological or coal quality perspective, the minimum apparent resistivity value reflects the region in the coal and petrographic sample where current propagation is most easy. These regions typically have high porosity, high fluid saturation, or contain more conductive minerals, resulting in lower apparent resistivity. When subsequently mapping apparent resistivity values ​​to a fixed range (e.g., [0,1]), these two extreme values ​​are used for range scaling of the apparent resistivity values. It should be noted that apparent resistivity normalization parameters typically refer to a set of key values ​​or configuration parameters used when normalizing data. In this embodiment of the invention, the apparent resistivity normalization parameters refer to the minimum and maximum apparent resistivity values ​​among multiple sets of coal and rock data. In specific operations, after determining the minimum and maximum apparent resistivity values, all apparent resistivity values ​​can be mapped using corresponding formulas to ensure data processing consistency. Using these two extreme values ​​for range scaling of apparent resistivity values ​​can eliminate scale differences between different datasets and improve data comparability.

[0058] It should be noted that there is a certain correlation between the coal density, natural gamma value, resistivity, apparent resistivity, density normalization parameter, gamma normalization parameter, resistivity normalization parameter, and apparent resistivity normalization parameter in coal petrography data and the physicochemical properties of coal petrography (such as ash content and moisture content). Determining the ash content and moisture content of coal petrography data based on these parameters typically requires regression analysis or other statistical models.

[0059] In this embodiment, the density value to be used is determined based on the coal density value and density normalization parameter in the coal and rock data; the gamma value to be used is determined based on the natural gamma value and gamma normalization parameter in the coal and rock data; the resistivity value to be used is determined based on the resistivity value and resistivity normalization parameter in the coal and rock data; the apparent resistivity value to be used is determined based on the apparent resistivity value and apparent resistivity normalization parameter in the coal and rock data; the ash content of the coal and rock is obtained by processing the density value to be used, the gamma value to be used, and the resistivity value to be used based on the ash content of the coal and rock data using a function to determine the ash content of the coal and rock data; and the moisture content of the coal and rock is obtained by processing the density value to be used, the gamma value to be used, and the apparent resistivity value to be used based on a function to determine the moisture content of the coal and rock data.

[0060] Among them, the coal and rock density value refers to the raw coal and rock density data actually collected at each first depth value, reflecting the physical properties of coal and rock. The density value to be used refers to the coal and rock density value needed in actual application, which is usually obtained by normalizing the coal and rock density value. For example, the formula for determining the density value to be used is as follows:

[0061]

[0062] Where DEN' represents the density value to be used; DEN represents the coal and rock density value; DEN max Indicates the maximum density; DEN min This represents the minimum density.

[0063] The natural gamma value refers to the raw natural gamma value data actually collected at each first depth value. The gamma value to be used refers to the natural gamma value that needs to be used in actual application, and the gamma value to be used is usually obtained by normalizing the natural gamma value.

[0064] For example, let's take a formula as an example to illustrate how to determine the gamma value to be used:

[0065]

[0066] Where GR' represents the gamma value to be used; GR represents the natural gamma value; GR max Indicates the maximum gamma value; GR min This represents the minimum gamma value.

[0067] The resistivity values ​​are the raw resistivity data actually collected at each first depth, reflecting the physical properties of coal and rock. The resistivity values ​​to be used refer to the resistivity values ​​required for practical applications, which are usually obtained through normalized resistivity values.

[0068] For example, the formula for determining the resistivity value to be used is as follows:

[0069]

[0070] Where RT' represents the resistivity value to be used; RT represents the resistivity value; RT max Represents the maximum resistivity; RT min This represents the minimum resistivity.

[0071] The apparent resistivity value refers to the raw apparent resistivity data actually collected at each first depth value, reflecting the physical properties of coal and rock. The apparent resistivity value to be used refers to the apparent resistivity value needed in actual application, which is usually obtained by normalizing the apparent resistivity value.

[0072] For example, the formula for determining the apparent resistivity value to be used is as follows:

[0073]

[0074] Where, ρ s 'Indicates the apparent resistivity value to be used; ρ s Represents the apparent resistivity value; ρ smax Represents the maximum apparent resistivity; ρ smin This represents the minimum apparent resistivity.

[0075] It should be noted that to determine the ash content of coal by processing the density, gamma, and resistivity values ​​to be used, a regression model or function can be established. This function typically predicts the ash content of coal based on its physical parameters such as density, natural gamma, and resistivity. There is usually a certain correlation between the ash content of coal and its density, gamma, and resistivity.

[0076] For example, using a formula, the function for determining the ash content of coal is:

[0077] A d =7.388+8.3561*DEN'+6.2268*GR'+0.00076795*RT';

[0078] Among them, A dThis represents the ash content of coal. It's important to note that the parameters 7.388, 8.3561, 6.2268, and 0.00076795 in the coal ash content determination function are not solely based on historical experience, but are obtained from a large amount of existing measured data (laboratory analysis results, well logging data, etc.) and corresponding statistical or regression models. For example, ash content analysis can be performed on a certain number of coal samples in the laboratory (e.g., industrial analysis to determine ash content) to obtain accurate ash content data. Simultaneously, parameters such as density, gamma value, and resistivity of the corresponding coal samples are measured. These measured parameters and ash content are then correlated, and regression analysis (such as linear regression, multiple regression, neural networks, etc.) is used to calibrate or fit the coefficients. It should also be noted that for certain regions or specific coal seams, appropriate empirical corrections may be made to the general model, or specialized regional models may be established to ensure that the predicted results match reality.

[0079] It should be noted that to determine the moisture content of coal and rock based on the required density, gamma value, and apparent resistivity, a regression model or function can be established. This function typically predicts the moisture content of coal and rock based on physical parameters such as density, natural gamma value, and apparent resistivity. There is usually a certain correlation between the moisture content of coal and rock and their density, gamma value, and apparent resistivity.

[0080] For example, using a formula, the function for determining the moisture content of coal and rock is:

[0081] M a =1.4655-0.5827*DEN'-2.1115*GR'+0.2319*ρ s ';

[0082] Among them, M aThis represents the moisture content of coal. It should be noted that parameters such as 1.4655, 0.5827, 2.1115, and 0.2319 can be obtained based on a large amount of existing measured data (laboratory analysis results, well logging data, etc.) and corresponding statistical or regression models. For example, the moisture content of a certain number of coal samples can be analyzed in the laboratory (e.g., industrial analysis to determine ash content) to obtain accurate moisture content data. Simultaneously, parameters such as density, gamma value, and apparent resistivity of the corresponding coal samples can be measured. These measured parameters and moisture content of the coal samples can be correlated, and regression analysis (such as linear regression, multiple regression, neural networks, etc.) can be used to calibrate or fit the coefficients. It should also be noted that the moisture content of coal is closely related to factors such as region, coal type, and climate of the mining area. In some regions, based on long-term well logging data and accumulated experience, certain patterns or correction coefficients may have emerged. For example, for coal seams in certain areas, the relationship between moisture content and gamma value or resistivity may have been verified and exhibit strong regional specificity. Therefore, in some cases, the determination of coefficients not only depends on laboratory data and regression models, but may also be modified based on practical experience to make the model more in line with local conditions.

[0083] Specifically, after acquiring multiple sets of coal and rock data, the minimum and maximum density values ​​are obtained from the coal and rock density values; the maximum and minimum gamma values ​​are obtained from the natural gamma values; the maximum and minimum resistivity values ​​are obtained from the resistivity values; and the maximum and minimum apparent resistivity values ​​are obtained from the apparent resistivity values. Then, based on each coal density value, minimum density value, and maximum density value in the coal and rock data, all density values ​​to be used are determined; based on each natural gamma value, maximum gamma value, and minimum gamma value in the coal and rock data, all gamma values ​​to be used are determined; based on each resistivity value, maximum resistivity value, and minimum resistivity value in the coal and rock data, all resistivity values ​​to be used are determined; based on each apparent resistivity value, maximum apparent resistivity value, and minimum apparent resistivity value in the coal and rock data, all apparent resistivity values ​​to be used are determined; the density values, gamma values, and resistivity values ​​to be used are then substituted into the coal and rock ash content determination function to determine the coal and rock ash content; the density values, gamma values, and apparent resistivity values ​​to be used are then substituted into the coal and rock moisture content determination function to determine the coal and rock moisture content.

[0084] For example, taking a certain deep coal and rock formation as an example, after obtaining data from well logging, the coal and rock density value (DEN) for a certain set of coal and rock data is taken as 1.25 g / cm³. 3 Maximum density DEN max The value is 1.90 g / cm³. 3 minimum density DEN min The value is 1.06 g / cm³.3 Therefore, the density value DEN' to be used is:

[0085]

[0086] For a given set of coal and petrographic data, the natural gamma value GR is 106.9 API, and the maximum gamma value GR is... max The value is 348.89 API, and the minimum gamma value is GR. min If the value is 15.2API, then the gamma value GR' to be used is:

[0087]

[0088] For a given set of coal and rock data, the resistivity value RT is 135.5 Ω·m, and the maximum resistivity RT max The value is 10584.9 Ω·m, and the minimum resistivity is RT. min If the value is taken as 15.4 Ω·m, then the resistivity value RT' to be used is:

[0089]

[0090] For a given set of coal and rock data, the apparent resistivity value ρ s The value is 210.79 Ω·m, and the maximum apparent resistivity ρ smax The value is taken as 10615.68 Ω·m, and the minimum apparent resistivity ρ smin If the value is 16.26 Ω·m, then the apparent resistivity value ρ to be used is... s for:

[0091]

[0092] For this set of coal and petrographic data, the coal and petrographic ash content A d for:

[0093] A d =7.388 + 8.3561 * 0.226 + 6.2268 * 0.275 + 0.00076795 * 0.0114 = 10.99;

[0094] For this set of coal and petrography data, the coal and petrography moisture content M a for:

[0095] M a =1.4655 - 0.5827 * 0.226 - 2.1115 * 0.275 + 0.2319 * 0.0184 = 0.757;

[0096] For multiple sets of coal and rock data, the ash content and moisture content of each set of coal and rock data can be determined based on the coal and rock density value, natural gamma value, resistivity value, apparent resistivity value, density normalization parameter, gamma normalization parameter, resistivity normalization parameter, and apparent resistivity normalization parameter in the coal and rock data.

[0097] S130. Obtain core samples corresponding to multiple second depth values ​​in the target well area, and analyze and process the core samples at multiple second depth values ​​to obtain coal and rock volatiles data corresponding to multiple second depth values; wherein, the second depth value is determined based on the depth value range and the second preset depth adjustment step size.

[0098] The second preset depth adjustment step size refers to the vertical depth increment used each time drilling tools are used to continue sampling downwards within the depth range of the area to be measured during exploration. It can also be understood as the vertical distance between each sampling. The second preset depth adjustment step size can be measured by the distance from the wellhead to the target location. In some cases, the second depth value may also need to consider the relative positional relationships between different strata. For example, in an exploration project, the second depth value may represent the depth in a certain stratum, which may have specific geological characteristics or mineral resources. A smaller second preset depth adjustment step size results in denser sampling points, enabling the capture of subtle changes in the coal seam and improving the ability to distinguish geological details. A larger first preset depth adjustment step size results in sparser sampling points, faster sampling speed, and lower cost, but may miss some key details. In actual data acquisition, the second preset depth adjustment step size can be flexibly adjusted according to the complexity of the area to be measured, the target, measurement accuracy, and operational economy, thereby obtaining sufficiently dense stratigraphic information more systematically and economically. For example, the second preset depth adjustment step size could be 10 meters.

[0099] It should be noted that, based on the depth range of the area to be measured, the starting point of the depth range can first be determined. Then, by adjusting the step size according to the second preset depth, a series of discrete sampling depth values, i.e., the second depth values, can be obtained. For example, when the starting depth of the depth range of the area to be measured is 1000 meters, and the second preset depth adjustment step size is 20 meters, the next sampling depth will be 1020 meters, the next after that will be 1040 meters, and so on. It should also be noted that core samples corresponding to each second depth value of the target well in the area to be measured should be obtained. In coal and gas exploration, combining measurements at different depths with collected core samples can help exploration personnel comprehensively understand the underground geological conditions and provide a basis for subsequent mining or other engineering decisions.

[0100] Specifically, core samples are obtained at each second depth value. Core samples refer to a complete columnar sample of coal and rock obtained by cutting underground coal and rock strata through rotation or impact during core drilling and other techniques.

[0101] It should be noted that coal volatile matter data refers to the percentage of volatile components released during the heating process of coal. Volatile matter mainly consists of easily volatile gases (such as water vapor, carbon dioxide, and carbon monoxide) and organic matter (such as tar and bitumen components) in coal, which escape from the coal during heating. By processing core samples corresponding to multiple second-depth values, coal volatile matter data corresponding to each second-depth value can be obtained. This data is then used as a parameter to calculate coalbed methane content. Higher volatile matter data indicates higher coalbed methane content. This suggests that the coal contains more organic matter, which can release more coalbed methane (such as methane) under appropriate conditions. Therefore, by analyzing the volatile matter in coal, the coalbed methane content can be indirectly estimated, and the reserves and exploitation potential of coalbed methane can be assessed.

[0102] Specifically, the second depth value can be determined by adjusting the step size based on the depth range of the area to be measured and the second preset depth. Then, core samples corresponding to multiple second depth values ​​are acquired, and these samples are analyzed and processed separately to obtain the coal volatiles data corresponding to each second depth value. In coal gas exploration, the parameters provided by volatiles data are crucial. They not only help us understand the gas potential of coal but also provide important geological basis for coalbed methane development, reservoir model establishment, and gas reservoir production scheme design. Higher volatiles data values ​​in coal usually indicate a greater amount of organic matter that can be converted into gas; therefore, such coal often has a higher gas content. Especially under certain coalbed methane reservoir conditions, higher volatiles data values ​​indicate a greater gas release potential.

[0103] S140. Based on the coal ash content and coal moisture content corresponding to multiple first depth values, and the coal volatiles data corresponding to multiple second depth values, determine the gas content of the area to be tested at multiple first depth values.

[0104] In this embodiment, by aligning the coal ash content and moisture content at multiple first depths and the coal volatiles data at multiple second depths, the coal ash content, moisture content, and volatiles data corresponding to each first depth value are obtained. If the coal ash content is within a first numerical range, the moisture content is within a second numerical range, and the volatiles data is within a third numerical range, then the gas content of the area to be detected corresponding to the first depth value is at the first level. If the coal ash content is within a fourth numerical range, the moisture content is within a fifth numerical range, and the volatiles data is within a sixth numerical range, then the gas content of the area to be detected corresponding to the first depth value is at the second level. If the coal ash content is within a seventh numerical range, the moisture content is within an eighth numerical range, and the volatiles data is within a ninth numerical range, then the gas content of the area to be detected corresponding to the first depth value is at the third level.

[0105] The second preset depth adjustment step size can be larger than the first preset depth adjustment step size. Therefore, the number of coal ash content or coal moisture content values ​​at the first depth can be greater than the number of coal volatile matter data values ​​at the second depth. To obtain the coal volatile matter data corresponding to each first depth value, the coal volatile matter data can be determined according to the actual depth value. For example... Figure 3 As shown, the coal and rock volatilization data corresponding to each first depth value is determined by aligning the depth values. For example, when the depth range is 2500 meters to 3000 meters, the first preset depth adjustment step is 1.25 meters, and the second preset depth adjustment step is 5 meters, the coal and rock volatilization data corresponding to the first depth values ​​of 2501.25, 2502.5, 2503.75, and 2505 are all the same as the coal and rock volatilization data corresponding to the second depth value of 2505. This process is repeated to determine the coal and rock volatilization data corresponding to each first depth value.

[0106] It should be noted that the first numerical range refers to coal ash content below 10%; the second numerical range refers to coal moisture content above 0.8%; the third numerical range refers to coal volatile matter content above 20%; the first level refers to a relatively high gas content in the area to be tested corresponding to the first depth value; the fourth numerical range refers to coal ash content between 10% and 20%; the fifth numerical range refers to coal moisture content between 0.5% and 0.8%; the sixth numerical range refers to coal volatile matter content between 10% and 20%; the second level refers to a moderate gas content in the area to be tested corresponding to the first depth value; the seventh numerical range refers to coal ash content above 20%; the eighth numerical range refers to coal moisture content below 0.5%; the ninth numerical range refers to coal volatile matter content below 10%; and the third level refers to a relatively low gas content in the area to be tested corresponding to the first depth value.

[0107] Specifically, for coal and rock at the first depth, when determining its volatile matter data, the volatile matter data of coal and rock at the first depth belonging to the same second depth are all set as the volatile matter data of the second depth value. This yields the ash content, moisture content, and volatile matter data corresponding to each first depth value. Then, based on the numerical range of the ash content, moisture content, and volatile matter data, the gas content level of the area to be tested corresponding to the first depth value is determined. Based on the gas content at different depths of deep coal and rock, the exploitation potential of the area under multiple depth conditions can be assessed. For example, a higher gas content may indicate better gas resource development potential within a certain depth range. This allows for the determination of the optimal gas resource exploitation depth, improving exploitation efficiency and resource utilization. For example, if the calculated ash content of coal at a certain first depth is 10.99% (between 10-20%), the moisture content is 0.757% (between 0.5-0.8%), and the volatile matter content is 13.6% (between 10-20%), then the appropriate level corresponding to this first depth value should be analyzed and determined.

[0108] The technical solution of this disclosure first acquires multiple sets of coal and rock data of the target well in the area to be tested. These coal and rock data include the coal and rock density, natural gamma ray, resistivity, and apparent resistivity values ​​of the area to be tested at a first depth value. The first depth value is determined based on the depth range of the area to be tested and a first preset depth adjustment step. Then, by processing the coal and rock density, natural gamma ray, resistivity, and apparent resistivity values ​​in the multiple sets of coal and rock data, the coal and rock ash content and coal and rock moisture content corresponding to each set of data are obtained. Further, core samples corresponding to multiple second depth values ​​of the target well in the area to be tested are acquired, and the core samples at the multiple second depth values ​​are analyzed and processed to obtain coal and rock volatiles data corresponding to the multiple second depth values. The second depth values ​​are determined based on the depth range and a second preset depth adjustment step. Finally, based on the coal and rock ash content and coal and rock moisture content of the coal and rock data corresponding to the multiple first depth values, and the coal and rock volatiles data corresponding to the multiple second depth values, the gas content of the area to be tested at the multiple first depth values ​​is determined. This invention addresses the problem in existing technologies that estimate deep coalbed methane content by relating well volume density to ash content, where the cumulative error in the parameters is significant, leading to inaccuracies in determining the content at different depths. The present invention acquires multiple parameters, including coal density, natural gamma ray, resistivity, and apparent resistivity, for the tested area at all first depths, and also acquires coal volatiles data for the tested area at all second depths. After acquiring all parameter data, a relationship is established between the parameter data at the first and second depths, thereby determining the methane content of the tested area at all first depths. This significantly improves the accuracy of determining the methane content at different depths.

[0109] Example 2

[0110] Figure 4 This is a flowchart illustrating a method for determining the content of deep coal gas according to an embodiment of the present invention. Based on the aforementioned embodiments, it provides a more detailed explanation of determining the coal volatiles data corresponding to the second depth value. Specific implementation methods can be found in the technical solution of this embodiment. Technical terms that are the same as or corresponding to those in the above embodiments will not be repeated here.

[0111] like Figure 4 As shown, the method specifically includes the following steps:

[0112] S210. Obtain multiple sets of coal and rock data of the target well in the area to be tested.

[0113] S220. By processing the coal density value, natural gamma value, resistivity value and apparent resistivity value in multiple sets of coal and rock data, the coal ash content and coal moisture content corresponding to each set of coal and rock data are obtained.

[0114] S230. For core samples at multiple second depth values, the core samples are crushed and filtered to obtain samples to be used.

[0115] In this process, after crushing and filtering all core samples at the second depth, a portion of the mass of each core sample is selected as the usable sample. It should be noted that the purpose of crushing and filtering the core samples is primarily to ensure that the core samples better reflect their essential characteristics in subsequent analysis or experiments, while improving the accuracy of the test results. Specifically, a cone crusher or ultrasonic crushing equipment can be used to break larger core samples into smaller particles. Crushing the core samples increases their surface area, making subsequent processing (such as heating, dissolving, etc.) more uniform and effective, and preventing large particles from affecting the experimental results. Next, different particle sizes of sieves can be selected to filter the crushed core samples according to experimental needs. Filtration effectively removes large particles, impurities, or unwanted substances from the core samples, ensuring the purity of the final usable sample. During the crushing and filtering process, it is crucial to ensure the representativeness of the sample at each step, avoiding the influence of human factors on the experimental results. The advantage of crushing and filtering core samples is that the processed samples can better reflect their true physical and chemical properties in subsequent drying and heating steps, thereby improving the reliability of experimental results.

[0116] Specifically, the same operation is performed on core samples at each second depth value. Taking a core sample at a certain second depth value as an example, the selected core sample is crushed using a crusher, and then filtered through a 0.22mm sieve. Then, 5-10g of the sieved core sample is weighed to obtain the sample to be used.

[0117] S240. When the sample to be used is dried to a stable mass, obtain a first mass of target sample and heat-dry the target sample to obtain the measured moisture content of the target sample during the heating and drying process.

[0118] Here, the first mass refers to the mass of the sample obtained from the dried and quality-stable sample to be used. Optionally, drying the sample to be used until it reaches quality stability can be achieved by placing it in a temperature-controlled oven, typically set at 100-110°C, to ensure complete removal of moisture. Furthermore, the mass change of the sample needs to be checked periodically during the drying process. Alternatively, freeze-drying can be used, where the moisture in the sample is first frozen at a low temperature, and then the moisture is directly sublimated away through vacuum heating.

[0119] It should be noted that, in order to ensure that the sample is dried to a stable quality, it is necessary to take out the sample and weigh it after each drying period, and record the change in mass until the change in mass is no longer significant, indicating that the moisture has been completely removed. Furthermore, when the mass of the sample no longer changes and several consecutive weighing results are consistent, it indicates that the sample has been dried to a stable quality.

[0120] In this embodiment, two first-mass target samples can be weighed, one of which is used for subsequent heating and drying to obtain the measured moisture content of the target sample during the heating and drying process; the other is used for static treatment in a preset environment.

[0121] In this process, after the sample to be used has been initially dried and its quality stabilized, a first mass of the target sample is further dried at a higher temperature to determine the lost moisture content. Optionally, the temperature may be even higher when drying the first mass of the target sample, or staged drying (e.g., different temperature gradients such as 105℃, 200℃, 350℃, etc.) may be performed according to experimental requirements to distinguish different forms of moisture. It is important to note that after drying, the sample should be rapidly cooled in a desiccator and weighed to prevent it from reabsorbing moisture or oxidizing, which could affect the measurement results.

[0122] For example, the formula for determining the moisture content of the target sample during the heating and drying process is as follows:

[0123]

[0124] Where Mad represents the measured moisture content of the target sample during the heating and drying process. m1 represents the initial mass, and m2 represents the mass of the target sample after heating and drying.

[0125] Specifically, the sample to be used can be placed in a drying oven at 100-110℃ and dried until its quality is stable. For the sample that has been dried to a stable quality, a target sample with a mass of 1±0.01g can be selected, spread evenly in a weighing bottle, and further heated and dried. After the heating and drying is completed, the moisture content of the target sample can be obtained by comparing the mass change of the target sample before and after heating and drying.

[0126] For example, the sample to be used is placed in a drying oven at 100-110℃ and dried until its mass stabilizes. A first target sample with a mass of 1g is selected, spread evenly in a weighing bottle, and then heated and dried. After the heating and drying process is complete, the mass of the target sample after heating and drying is obtained as 0.764g. The moisture content (Mad) of the target sample during the entire heating and drying process is calculated to be 23.4%.

[0127] S250. The target sample after heating and drying is subjected to static treatment in a preset environment to obtain the second mass of the target sample.

[0128] Among them, for another target sample with the first mass, the remaining sample mass after the target sample has been subjected to static treatment in a preset environment is called the second mass.

[0129] In this embodiment, the target sample is placed in a muffle furnace preheated to the target temperature for a predetermined time. Optionally, a porcelain crucible containing the target sample can be placed in a muffle furnace preheated to 920°C, the furnace door closed, and the crucible heated inside for 7-10 minutes, with the furnace temperature maintained at 900±10°C during heating. After drying, the porcelain crucible is removed from the muffle furnace, cooled for 5-7 minutes, and the remaining mass is weighed to obtain the second mass of the target sample. It should be noted that the target sample may contain moisture, including water of crystallization, free water, and hygroscopic water. By placing the target sample in a muffle furnace and heating it at a specific temperature, this moisture can be removed, ensuring that only the solid portion remains in the sample, thus allowing for more accurate determination of other components. The muffle furnace provides a stable temperature environment and uniform heating, ensuring that the sample is processed at the specified temperature. This is crucial for sample drying and moisture determination, avoiding the influence of temperature fluctuations on experimental results. By heating to the target temperature in a muffle furnace and setting the time, the consistency and reproducibility of the experiment were ensured, thereby improving the accuracy and reliability of the results.

[0130] Specifically, another portion of the target sample with a first mass of 1 ± 0.01 g is weighed, and after being heated and dried in a preset environment, the target sample is allowed to stand still. The remaining mass is then weighed to obtain the second mass of the target sample. Finally, based on the first mass, the second mass, and the measured moisture content, the coal and petrographic volatiles data of the core sample corresponding to the second depth value are determined.

[0131] S260. Based on the first and second masses, determine the third mass.

[0132] The third mass is the difference between the first and second masses, representing the mass of the target sample that volatilizes after being heated in the muffle furnace.

[0133] For example, let's take a formula as an example to illustrate the determination of the third mass:

[0134] m3 = m1 - m2

[0135] Where m3 represents the third mass, m1 represents the first mass, and m2 represents the second mass.

[0136] Specifically, the first and second masses are obtained, and the third mass of the target sample is calculated.

[0137] S270. Determine the moisture loss value based on the ratio of the third mass to the first mass.

[0138] The moisture loss value refers to the ratio of the mass of moisture lost from the target sample after heating in a muffle furnace to the mass of the target sample.

[0139] For example, the formula for determining the water loss value is as follows:

[0140]

[0141] Where m3 represents the third mass, m1 represents the first mass, and S represents the moisture loss value.

[0142] Specifically, the first and third masses are obtained, and the moisture loss value is calculated.

[0143] S280. Based on the moisture loss value and the measured moisture content, determine the coal and rock volatiles data of the core sample.

[0144] Coal volatile matter data is a crucial basis for assessing the combustion characteristics, gas release potential, and coalbed methane exploration of coal samples. Coal volatile matter data can be obtained by measuring moisture loss and moisture content, combined with high-temperature volatile matter testing.

[0145] For example, the formula for determining the coal volatiles data of a core sample is as follows:

[0146]

[0147] Among them, V ad This represents the coal and rock volatiles data of the core sample.

[0148] Specifically, after obtaining the moisture loss value and measuring the moisture content, the coal and rock volatiles data of the core sample are calculated.

[0149] For example, another 1g target sample is weighed. The porcelain crucible containing the target sample is placed in a muffle furnace preheated to 920°C. The furnace door is closed, and the crucible is heated inside the muffle furnace for 8 minutes, maintaining a constant furnace temperature of 900°C during heating. After drying, the crucible is removed from the muffle furnace and cooled for 6 minutes. The remaining mass is then weighed, yielding a second mass of 0.63g for the target sample. Based on the first mass of 1g and the second mass of 0.63g, the third mass is determined to be 0.37g. (Coal volatile matter data V) ad for:

[0150]

[0151] S290. Based on the coal ash content and coal moisture content corresponding to multiple first depth values, and the coal volatiles data corresponding to multiple second depth values, determine the gas content of the area to be tested at multiple first depth values.

[0152] The technical solution of this disclosure involves obtaining the coal ash content and coal moisture content corresponding to each set of coal and rock data. For core samples at multiple second depth values, the core samples are crushed and filtered to obtain samples to be used. Then, when the samples to be used are dried to a stable mass, a first mass of target sample is obtained, and the target sample is heated and dried to obtain the measured moisture content of the target sample during the heating and drying process. Further, the heated and dried target sample is subjected to static treatment in a preset environment to obtain a second mass of the target sample. Based on the first and second masses, a third mass is determined. Based on the ratio of the third mass to the first mass, a moisture loss value is determined. Based on the moisture loss value and the measured moisture content, the coal volatile matter data of the core sample is determined. Finally, based on the coal ash content and coal moisture content of the coal and rock data corresponding to multiple first depth values, and the coal volatile matter data corresponding to multiple second depth values, the gas content of the area to be tested at multiple first depth values ​​is determined. By employing efficient and precise coal and rock analysis methods, the gas content is comprehensively assessed. Furthermore, through progressively refined sample processing steps, the accuracy of each step is ensured, thereby enhancing the stability and reliability of experimental data and improving the accuracy of gas content in deep coal and rock at different depths.

[0153] Example 3

[0154] Figure 5 This is a schematic diagram of a device for determining the gas content of deep coal and rock provided in an embodiment of this disclosure. As shown in the figure, the device includes: a coal and rock data acquisition module 310, a coal and rock ash moisture content determination module 320, a coal and rock volatile matter data determination module 330, and a gas content determination module 340.

[0155] A coal and rock data acquisition module is used to acquire multiple sets of coal and rock data of the target well in the test area. The coal and rock data includes the coal and rock density value, natural gamma value, resistivity value, and apparent resistivity value of the test area at a first depth value. The first depth value is determined based on the depth range of the test area and a first preset depth adjustment step. A coal and rock ash and moisture content determination module is used to process the coal and rock density value, natural gamma value, resistivity value, and apparent resistivity value in the multiple sets of coal and rock data to obtain the coal and rock ash content and coal and rock moisture content corresponding to each set of coal and rock data. A coal and rock volatile matter data determination module is also included. The system is used to acquire core samples corresponding to multiple second depth values ​​in the area to be tested from the target well, and to analyze and process the core samples at the multiple second depth values ​​to obtain coal volatiles data corresponding to the multiple second depth values; wherein, the second depth values ​​are determined based on the depth value range and a second preset depth adjustment step size; the gas content determination module is used to determine the gas content of the area to be tested at multiple first depth values ​​based on the coal ash content and coal moisture content of the coal data corresponding to multiple first depth values, and the coal volatiles data corresponding to multiple second depth values.

[0156] The technical solution of this disclosure first acquires multiple sets of coal and rock data of the target well in the area to be tested. These coal and rock data include the coal and rock density, natural gamma ray, resistivity, and apparent resistivity values ​​of the area to be tested at a first depth value. The first depth value is determined based on the depth range of the area to be tested and a first preset depth adjustment step. Then, by processing the coal and rock density, natural gamma ray, resistivity, and apparent resistivity values ​​in the multiple sets of coal and rock data, the coal and rock ash content and coal and rock moisture content corresponding to each set of data are obtained. Further, core samples corresponding to multiple second depth values ​​of the target well in the area to be tested are acquired, and the core samples at the multiple second depth values ​​are analyzed and processed to obtain coal and rock volatiles data corresponding to the multiple second depth values. The second depth values ​​are determined based on the depth range and a second preset depth adjustment step. Finally, based on the coal and rock ash content and coal and rock moisture content of the coal and rock data corresponding to the multiple first depth values, and the coal and rock volatiles data corresponding to the multiple second depth values, the gas content of the area to be tested at the multiple first depth values ​​is determined. This invention addresses the problem in existing technologies that estimate deep coalbed methane content by relating well volume density to ash content, where the cumulative error in the parameters is significant, leading to inaccuracies in determining the content at different depths. The present invention acquires multiple parameters, including coal density, natural gamma ray, resistivity, and apparent resistivity, for the tested area at all first depths, and also acquires coal volatiles data for the tested area at all second depths. After acquiring all parameter data, a relationship is established between the parameter data at the first and second depths, thereby determining the methane content of the tested area at all first depths. This significantly improves the accuracy of determining the methane content at different depths.

[0157] Based on the above technical solutions, the coal and rock data acquisition module 310 includes: retrieving well logging data, wherein the well logging data includes coal and rock data corresponding to at least one detection well in multiple areas to be tested; retrieving the data to be used from the well logging data of the target well, and retrieving multiple sets of coal and rock data associated with the areas to be tested from the data to be used.

[0158] Based on the above technical solutions, the coal and rock ash moisture content determination module 320 includes: a density normalization parameter determination submodule, a gamma normalization parameter determination submodule, a resistivity normalization parameter determination submodule, an apparent resistivity normalization parameter determination submodule, and a coal and rock ash moisture content determination submodule.

[0159] The density normalization parameter determination submodule is used to determine the density normalization parameter based on the coal density values ​​in the multiple sets of coal and rock data; wherein, the density normalization parameter includes a minimum density value and a maximum density value;

[0160] The gamma normalization parameter determination submodule is used to determine the gamma normalization parameter based on the natural gamma values ​​in the multiple sets of coal and rock data, wherein the gamma normalization parameter includes the maximum gamma value and the minimum gamma value;

[0161] The resistivity normalization parameter determination submodule is used to determine the resistivity normalization parameter based on the resistivity values ​​in the multiple sets of coal and rock data, wherein the resistivity normalization parameter includes the maximum resistivity value and the minimum resistivity value.

[0162] The apparent resistivity normalization parameter determination submodule is used to determine the apparent resistivity normalization parameter based on the apparent resistivity values ​​of the multiple sets of coal and rock data, wherein the apparent resistivity normalization parameter includes the maximum apparent resistivity value and the minimum apparent resistivity value.

[0163] The coal ash and moisture content determination submodule is used to determine the coal ash content and coal moisture content of the multiple sets of coal data based on the coal density value, natural gamma value, resistivity value, apparent resistivity value, density normalization parameter, gamma normalization parameter, resistivity normalization parameter, and apparent resistivity normalization parameter in the coal data.

[0164] Based on the above technical solutions, the coal and rock ash moisture content determination submodule includes: a unit for determining the density value to be used, a unit for determining the gamma value to be used, a unit for determining the resistivity value to be used, a unit for determining the apparent resistivity value to be used, and a unit for determining the coal and rock ash content.

[0165] The unit for determining the density value to be used is used to determine the density value to be used based on the coal and rock density value in the coal and rock data and the density normalization parameter.

[0166] The unit for determining the gamma value to be used is used to determine the gamma value to be used based on the natural gamma value in the coal and rock data and the gamma normalization parameter.

[0167] The resistivity value determination unit is used to determine the resistivity value to be used based on the resistivity value in the coal and rock data and the resistivity normalization parameter.

[0168] The apparent resistivity value determination unit is used to determine the apparent resistivity value to be used based on the apparent resistivity value in the coal and rock data and the apparent resistivity normalization parameter.

[0169] The coal ash content determination unit is used to process the density value to be used, the gamma value to be used, and the resistivity value to be used based on the coal ash content determination function to obtain the coal ash content.

[0170] The coal and rock moisture content determination unit is used to process the density value to be used, the gamma value to be used, and the apparent resistivity value to be used based on the coal and rock moisture content determination function to obtain the coal and rock moisture content.

[0171] Based on the above technical solutions, the coal and rock volatiles data determination module 330 includes: a sample determination submodule, a moisture content determination submodule, a second quality determination submodule, and a coal and rock volatiles data determination submodule.

[0172] The sample to be used determination submodule is used to crush the core samples at the multiple second depth values ​​and filter the crushed core samples to obtain the sample to be used.

[0173] The moisture content determination submodule is used to obtain a first mass of target sample when the sample to be used is dried to a stable mass, and to heat and dry the target sample to obtain the measured moisture content of the target sample during the heating and drying process.

[0174] The second mass determination submodule is used to statically process the heated and dried target sample in a preset environment to obtain the second mass of the target sample.

[0175] The coal volatiles data determination submodule is used to determine the coal volatiles data of the core sample corresponding to the second depth value based on the first mass, the second mass, and the measured moisture content.

[0176] Based on the above technical solutions, the moisture content determination submodule includes: placing the target sample in a muffle furnace preheated to the target temperature for a preset time.

[0177] Based on the above technical solutions, the coal volatiles data determination submodule includes: determining a third mass based on the first mass and the second mass; determining a moisture loss value based on the ratio of the third mass to the first mass; and determining the coal volatiles data of the core sample based on the moisture loss value and the measured moisture content.

[0178] Based on the above technical solutions, the gas content determination module 340 includes: aligning the coal ash content and moisture content at multiple first depths, and the coal volatiles data at multiple second depths, to obtain the coal ash content, moisture content, and volatiles data corresponding to each first depth value; if the coal ash content is within a first numerical range, the moisture content is within a second numerical range, and the volatiles data is within a third numerical range, then the gas content of the area to be detected corresponding to the first depth value is at a first level; if the coal ash content is within a fourth numerical range, the moisture content is within a fifth numerical range, and the volatiles data is within a sixth numerical range, then the gas content of the area to be detected corresponding to the first depth value is at a second level; if the coal ash content is within a seventh numerical range, the moisture content is within an eighth numerical range, and the volatiles data is within a ninth numerical range, then the gas content of the area to be detected corresponding to the first depth value is at a third level.

[0179] The apparatus for determining the content of deep coal and rock gas provided in this disclosure can execute the method for determining the content of deep coal and rock gas provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects for executing the method.

[0180] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of this disclosure.

[0181] Example 4

[0182] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Refer to the following... Figure 6 It illustrates an electronic device suitable for implementing embodiments of the present disclosure (e.g., Figure 6 The diagram below shows the structure of the terminal device or server 500. The terminal device in this embodiment may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and vehicle terminals (e.g., vehicle navigation terminals). Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0183] like Figure 6As shown, electronic device 500 may include a processing unit (e.g., central processing unit, graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. An edit / output (I / O) interface 505 is also connected to bus 504.

[0184] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0185] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of embodiments of this disclosure.

[0186] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0187] The electronic device provided in this embodiment and the method for determining the content of deep coal and rock gas provided in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0188] Example 5

[0189] This disclosure provides a computer storage medium storing a computer program that, when executed by a processor, implements the method for determining the content of deep coalbed methane provided in the above embodiments.

[0190] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0191] In some implementations, the server may communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and may interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed networks.

[0192] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0193] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to:

[0194] Multiple sets of coal and rock data of the target well in the area to be tested are acquired. The coal and rock data include the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value of the area to be tested at a first depth value. The first depth value is determined based on the depth value range of the area to be tested and a first preset depth adjustment step size.

[0195] By processing the coal density value, natural gamma value, resistivity value and apparent resistivity value in the multiple sets of coal and rock data, the coal ash content and coal moisture content corresponding to each set of coal and rock data are obtained.

[0196] Core samples corresponding to multiple second depth values ​​in the area to be tested are obtained from the target well, and the core samples at the multiple second depth values ​​are analyzed and processed to obtain the coal and rock volatiles data corresponding to the multiple second depth values; wherein, the second depth value is determined based on the depth value range and a second preset depth adjustment step size;

[0197] Based on the coal ash content and coal moisture content corresponding to multiple first depth values, and the coal volatiles data corresponding to multiple second depth values, the gas content of the area to be tested at multiple first depth values ​​is determined.

[0198] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0199] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0200] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0201] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0202] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0203] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0204] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0205] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for determining the content of deep coalbed methane, characterized in that, include: Multiple sets of coal and rock data of the target well in the area to be tested are acquired. The coal and rock data include the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value of the area to be tested at a first depth value. The first depth value is determined based on the depth value range of the area to be tested and a first preset depth adjustment step size. By processing the coal density value, natural gamma value, resistivity value and apparent resistivity value in the multiple sets of coal and rock data, the coal ash content and coal moisture content corresponding to each set of coal and rock data are obtained. Core samples corresponding to multiple second depth values ​​in the area to be tested are obtained from the target well, and the core samples at the multiple second depth values ​​are analyzed and processed to obtain the coal and rock volatiles data corresponding to the multiple second depth values; wherein, the second depth value is determined based on the depth value range and a second preset depth adjustment step size; Based on the coal ash content and coal moisture content corresponding to multiple first depth values, and the coal volatiles data corresponding to multiple second depth values, the gas content of the area to be tested at multiple first depth values ​​is determined.

2. The method according to claim 1, characterized in that, The acquisition of multiple sets of coal and rock data of the target well in the area to be tested includes: Retrieve well logging data, wherein the well logging data includes coal and rock data corresponding to at least one detection well in multiple test areas; The data to be used for the target well is retrieved from the well logging data, and multiple sets of coal and rock data associated with the area to be tested are retrieved from the data to be used.

3. The method according to claim 1 or 2, characterized in that, The process involves processing the coal density, natural gamma, resistivity, and apparent resistivity values ​​from the multiple sets of coal and rock data to obtain the coal ash content and moisture content corresponding to each set of coal and rock data, including: Based on the coal density values ​​in the multiple sets of coal and rock data, a density normalization parameter is determined; wherein, the density normalization parameter includes a minimum density value and a maximum density value; Based on the natural gamma values ​​in the multiple sets of coal and rock data, a gamma normalization parameter is determined, wherein the gamma normalization parameter includes the maximum gamma value and the minimum gamma value; Based on the resistivity values ​​in the multiple sets of coal and rock data, a resistivity normalization parameter is determined, wherein the resistivity normalization parameter includes the maximum resistivity value and the minimum resistivity value; Based on the apparent resistivity values ​​of the multiple sets of coal and rock data, an apparent resistivity normalization parameter is determined, wherein the apparent resistivity normalization parameter includes the maximum apparent resistivity value and the minimum apparent resistivity value. For the multiple sets of coal and rock data, the coal and rock ash content and coal and rock moisture content are determined based on the coal and rock density value, natural gamma value, resistivity value, apparent resistivity value, density normalization parameter, gamma normalization parameter, resistivity normalization parameter and apparent resistivity normalization parameter in the coal and rock data.

4. The method according to claim 3, characterized in that, The determination of coal ash content and coal moisture content based on the coal density value, natural gamma value, resistivity value, apparent resistivity value, density normalization parameter, gamma normalization parameter, resistivity normalization parameter, and apparent resistivity normalization parameter in the coal and rock data includes: Based on the coal and rock density values ​​in the coal and rock data and the density normalization parameter, the density value to be used is determined; Based on the natural gamma value in the coal and rock data and the gamma normalization parameter, determine the gamma value to be used; Based on the resistivity values ​​in the coal and rock data and the resistivity normalization parameters, determine the resistivity values ​​to be used. Based on the apparent resistivity value in the coal and rock data and the apparent resistivity normalization parameter, the apparent resistivity value to be used is determined. The coal ash content is obtained by processing the density value to be used, the gamma value to be used, and the resistivity value to be used based on the coal ash content determination function. The coal moisture content is obtained by processing the density value to be used, the gamma value to be used, and the apparent resistivity value to be used based on the coal moisture content determination function.

5. The method according to claim 1, characterized in that, The analysis and processing of core samples at the plurality of second depth values ​​to obtain coal and rock volatiles data corresponding to the plurality of second depth values ​​includes: For the core samples at the multiple second depth values, the core samples are crushed and filtered to obtain samples to be used. When the sample to be used is dried to a stable mass, a first mass of target sample is obtained, and the target sample is heated and dried to obtain the measured moisture content of the target sample during the heating and drying process; The target sample, after being heated and dried, is subjected to static treatment in a preset environment to obtain the second mass of the target sample; Based on the first mass, the second mass, and the measured moisture content, the coal and rock volatiles data of the core sample corresponding to the second depth value are determined.

6. The method according to claim 5, characterized in that, The heating and drying of the target sample includes: The target sample is placed in a muffle furnace preheated to the target temperature for a preset time.

7. The method according to claim 5, characterized in that, The determination of coal volatiles data of the core sample corresponding to the second depth value based on the first mass, the second mass, and the measured moisture content includes: Based on the first quality and the second quality, determine the third quality; The moisture loss value is determined based on the ratio of the third mass to the first mass; Based on the moisture loss value and the measured moisture content, the coal volatiles data of the core sample are determined.

8. The method according to claim 1, characterized in that, The step of determining the gas content of the area to be tested at multiple first depth values ​​based on the coal ash content and coal moisture content corresponding to multiple first depth values, and the coal volatile matter data corresponding to multiple second depth values, includes: By aligning the coal ash content and moisture content at the multiple first depths and the coal volatiles data at the multiple second depths, the coal ash content, moisture content and volatiles data corresponding to each first depth value are obtained. If the coal ash content is within a first numerical range, the moisture content is within a second numerical range, and the coal volatile matter data is within a third numerical range, then the gas content of the area to be detected corresponding to the first depth value is of the first level. If the coal ash content is within the fourth numerical range, the moisture content is within the fifth numerical range, and the coal volatile matter data is within the sixth numerical range, then the gas content of the area to be detected corresponding to the first depth value is at the second level. If the coal ash content is within the seventh numerical range, the moisture content is within the eighth numerical range, and the coal volatile matter content is within the ninth numerical range, then the gas content of the area to be detected corresponding to the first depth value is at the third level.

9. A device for determining the content of deep coalbed methane, characterized in that, include: The coal and rock data acquisition module is used to acquire multiple sets of coal and rock data of the target well in the area to be tested. The coal and rock data includes the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value of the area to be tested at a first depth value. The first depth value is determined based on the depth value range of the area to be tested and a first preset depth adjustment step. The coal and rock ash and moisture content determination module is used to process the coal and rock density value, natural gamma value, resistivity value and apparent resistivity value in the multiple sets of coal and rock data to obtain the coal and rock ash content and coal and rock moisture content corresponding to each set of coal and rock data. The coal and rock volatiles data determination module is used to acquire core samples corresponding to multiple second depth values ​​in the area to be tested for the target well, and to analyze and process the core samples at the multiple second depth values ​​to obtain the coal and rock volatiles data corresponding to the multiple second depth values; wherein, the second depth value is determined based on the depth value range and a second preset depth adjustment step size; The gas content determination module is used to determine the gas content of the area to be tested at multiple first depth values ​​based on the coal ash content and coal moisture content of coal rock data corresponding to multiple first depth values, and the coal volatile matter data corresponding to multiple second depth values.

10. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs. When one or more programs are executed by one or more processors, the one or more processors implement the method for determining the content of deep coalbed methane as described in any one of claims 1-8.

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