Method and device for identifying oil-rich coal seam, electronic equipment and storage medium

Abstract

The invention provides a method and a device for identifying an oil-rich coal seam, and belongs to the technical field of identification of the oil-rich coal seam. Typical logging response characteristics of the oil-rich coal seam are determined through tar yield data measured by a Gray dry distillation test in combination with logging information; according to tar yield measurement data, well logging parameters sensitive to oil-rich coal seam reflection are selected through multi-parameter rendezvous analysis; performing normalization processing on the selected sensitive parameters; the influence of a measurement environment and human factors on the quality of logging information is avoided; constructing an oil-rich coal seam indication factor Z according to the normalized sensitive parameters; calibration is carried out according to the tar yield measured through a known coal well test, the coal seam of an unknown coal well is evaluated through the indication factor Z, whether the coal seam is an oil-rich coal seam or not is judged, and therefore technical support is provided for improving the recognition efficiency of the oil-rich coal and defining the distribution rule of the oil-rich coal.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil-rich coal seam identification, and in particular relates to an oil-rich coal seam identification method, device, electronic equipment and storage medium. Background Art

[0002] At present, my country's energy structure presents the resource endowment characteristics of "lack of oil, little gas, and relatively rich in coal". As an important fossil energy, coal is the main energy consumption in my country. Coal is subject to factors such as my country's resource conditions, development stage, industrial structure, technological level, growth trend and energy security. The status of coal as the main energy source of the country will not change in the short term, and it will continue to play the role of energy ballast.

[0003] According to the definition in the Mineral Resources Industry Requirements Manual, oil-rich coal refers to coal with a tar yield of 7% to 12%, while coal with a tar yield of less than 7% is defined as oily coal, and coal with a tar yield of more than 12% is called high-oil coal. Now, coal with a tar yield of ≥7% is also collectively referred to as oil-rich coal.

[0004] As a coal resource that combines the properties of coal, oil and gas, oil-rich coal is currently mainly identified by the Geggin distillation test, that is, whether the tar yield measured by the Geggin distillation test is greater than 7%. If the tar yield is greater than 7%, it is oil-rich coal, otherwise it is oil-poor coal.

[0005] Well logging, as a technical means, is currently widely used in the field of oil and coalfield exploration. Well logging is a technical method to understand underground geological bodies by using the geophysical characteristics of underground rock formations, such as electrochemical properties, electrical conductivity, acoustic properties, and radioactivity. Since well logging data can continuously and indirectly reflect the geophysical properties of underground rock formations, if the response characteristics of well logging data to oil-rich coal can be discovered, it will provide important technical support for the identification of oil-rich coal seams.

[0006] At present, the identification of oil-rich coal seams mainly relies on test measurements, and there is still a lack of research on the rapid and accurate identification of oil-rich coal seams using well logging data. Although the Gekin distillation test measurement can accurately obtain the tar yield of coal rocks and then identify oil-rich coal seams, its shortcomings are also obvious.

[0007] It is mainly reflected in two aspects: 1. The test measurement relies on coring of coal seams. It is relatively simple to coring surface open-pit coal mines, but it is difficult to coring deep coal mines because of the high cost of coring.

[0008] 2. The data obtained from the experimental measurement are discrete and discontinuous, and it is difficult to extend and apply them to other research areas. Summary of the invention

[0009] In view of the above problems, the present invention proposes a method and device for identifying oil-rich coal seams, which can avoid the influence of measurement environment and human factors on the quality of logging data, improve the identification efficiency of oil-rich coal, and provide technical support for clarifying the distribution law of oil-rich coal.

[0010] An aspect of an embodiment of the present invention provides a method for identifying an oil-rich coal seam, comprising:

[0011] According to the coal rock gold distillation test measurement data of the coal well in the test measurement block, the tar yield data of the coal rock is obtained; wherein the coal rock measured in the test includes oil-bearing coal and oil-rich coal;

[0012] According to the coal rock tar yield data combined with the logging parameters at the corresponding depth points, a multi-parameter intersection analysis is performed on the coal wells in the test measurement block to screen the sensitive parameters in the logging that are sensitive to the oil-rich coal seams;

[0013] The sensitive parameters reflecting the sensitivity of the oil-rich coal seam are normalized to obtain the second sensitive parameter, and the second sensitive parameter is made within the interval of (0,1);

[0014] The second sensitive parameter is mathematically processed to obtain the oil-rich coal seam indicator factor Z;

[0015] The oil-rich coal seam is identified based on the tar yield data of the coal wells in the test measurement block combined with the oil-rich coal seam indicator factor Z.

[0016] Preferably, the coal wells in the test measurement block are subjected to intersection analysis based on the coal tar yield data in combination with the logging parameters at the corresponding depth points, and sensitive parameters in the logging that are sensitive to the oil-rich coal seams are screened, including:

[0017] Generating a first cross-plot according to the tar yield data and logging parameters; wherein the logging parameters include: deep resistivity, compensated density and natural gamma;

[0018] According to the correlation between the tar yield and the logging parameters reflected in the first cross-plot, sensitive parameters sensitive to the oil-rich coal are screened out.

[0019] Preferably, the normalization process of the well logging parameters sensitive to the oil-rich coal seam includes:

[0020] For the selected sensitive parameters of oil-rich coal, such as compensation density and deep resistivity, the numerical variation range of the compensation density of the coal seam and the numerical variation range of the deep resistivity are obtained, and normalization processing is performed according to the numerical variation range of the compensation density and the numerical variation range of the deep resistivity. Since the variation range of the deep resistivity value is large, the logarithm is taken before normalization;

[0021] The sensitive parameter is normalized to obtain a second sensitive parameter, where the second sensitive parameter includes: a normalized compensation density X and a normalized deep resistivity Y.

[0022] Preferably, the mathematical processing of the second sensitive parameter to obtain the oil-rich coal seam indicator factor Z comprises:

[0023] Constructing the oil-rich coal seam indicator factor Z according to the second sensitive parameter;

[0024] Among them, the oil-rich coal seam indicator factor Z is obtained by subtracting the normalized compensation density X from the normalized deep resistivity Y.

[0025] Preferably, the method of identifying the oil-rich coal seam based on the tar yield data of the coal well in the test measurement block in combination with the oil-rich coal seam indicator factor Z comprises:

[0026] Obtaining a tar yield value through a coal seam grouting test, generating a second cross-plot with the tar yield value and the oil-rich coal seam indicator factor Z, and determining a lower limit value Zmin of the indicator factor Z corresponding to the oil-rich coal seam according to the second cross-plot;

[0027] The oil-rich coal seam is determined based on the lower limit value Zmin of the indicator factor Z.

[0028] Preferably, the determining of the oil-rich coal seam according to the lower limit value Zmin of the indicator factor Z comprises:

[0029] The oil-rich coal seam indicator factor Z is greater than the lower limit value Zmin, and the coal seam corresponding to the oil-rich coal seam indicator factor is determined to be an oil-rich coal seam;

[0030] When the oil-rich coal seam indication factor Z is less than or equal to the lower limit value Zmin, the coal seam corresponding to the oil-rich coal seam indication factor is determined to be an oil-poor coal seam.

[0031] Preferably, it is characterized in that

[0032] The sensitive parameters that are sensitive to oil-rich coal layers in screening logging are obtained through the correlation between tar yield data and logging parameters;

[0033] Among them, if the tar yield is positively correlated with the deep resistivity, or the tar yield is negatively correlated with the compensation density, it is determined that the logging parameter is relatively sensitive to the tar yield of the coal rock.

[0034] Based on the same inventive concept, another aspect of the embodiment of the present invention provides a device for identifying an oil-rich coal seam, comprising:

[0035] A data acquisition unit is used to acquire tar yield data of coal rock according to the coal rock gold distillation test measurement data of the coal well in the test measurement block; wherein the coal rock measured in the test includes oil-bearing coal and oil-rich coal;

[0036] An intersection analysis unit is used to perform intersection analysis on the coal wells in the test measurement block according to the coal rock tar yield data combined with the logging parameters of the corresponding depth points, and screen the sensitive parameters in the logging that are sensitive to the oil-rich coal seams;

[0037] A data processing unit is used to perform normalization processing on the sensitive parameter reflecting the sensitivity of the oil-rich coal seam to obtain a second sensitive parameter, and make the second sensitive parameter within the interval of (0,1);

[0038] The second sensitive parameter is mathematically processed to obtain the oil-rich coal seam indicator factor Z;

[0039] The identification unit is used to identify the oil-rich coal seam based on the tar yield data of the coal wells in the test measurement block combined with the oil-rich coal seam indicator factor Z.

[0040] Based on the same inventive concept, another aspect of the embodiment of the present invention provides an electronic device for identifying an oil-rich coal seam, comprising:

[0041] A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0042] a memory storing a computer program;

[0043] The processor implements a method for quickly identifying oil-rich coal seams when executing the program stored in the memory.

[0044] Based on the same inventive concept, another aspect of an embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements a method for quickly identifying oil-rich coal seams when executed by a processor.

[0045] Beneficial effects of the present invention:

[0046] The present invention clarifies typical logging response characteristics of oil-rich coal seams by combining tar yield data measured by a Geggin distillation test with logging data; selects logging parameters sensitive to the oil-rich coal seams through intersection analysis according to the tar yield measurement data; performs normalization processing on the selected sensitive parameters; avoids the influence of measurement environment and human factors on the quality of logging data; constructs an oil-rich coal seam indicator factor Z according to the normalized sensitive parameters; calibrates according to the tar yield measured by a known coal well test, and uses the indicator factor Z to evaluate the coal seams of unknown coal wells to determine whether they are oil-rich coal seams, thereby providing technical support for improving the recognition efficiency of oil-rich coal and clarifying the distribution law of oil-rich coal.

[0047] Other features and advantages of the present invention will be described in the following description, and partly become obvious from the description, or be understood by implementing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 A flow chart of a method for identifying an oil-rich coal seam according to the present invention is shown;

[0050] Figure 2 A cross plot of coal seam tar yield and resistivity is shown;

[0051] Figure 3 A cross plot of coal seam tar yield and compensated density is shown;

[0052] Figure 4 A schematic diagram of constructing the oil-rich coal layer indicator factor Z using X1 logging parameters is shown;

[0053] Figure 5 It shows the schematic diagram of calculating the indicator factor of the coal seam section of X1 logging;

[0054] Figure 6 The schematic diagram of calculating the indicator factor of the coal seam section of X2 logging is shown;

[0055] Figure 7 The cross-plot of coal seam tar yield and indicator factor Z is shown;

[0056] Figure 8 The comparison diagram between the oil-rich coal layer indicator factor Z and the actual coal rock type of X3 logging is shown;

[0057] Fig. 9 A schematic diagram of a device for identifying an oil-rich coal seam according to the present invention is shown;

[0058] Fig.10 A schematic diagram of an electronic device for identifying oil-rich coal seams in the present invention is shown. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] It should be noted that the terms "first", "second" etc. in the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged in appropriate circumstances, so that the embodiments of the present application described here. In the present application, the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inside", "outside", "middle", "vertical", "horizontal", "lateral", "longitudinal" etc. are based on the orientation or positional relationship shown in the accompanying drawings.

[0061] The embodiment of the present invention provides a method for identifying an oil-rich coal seam. Figure 1 ,include:

[0062] S101: according to the coal rock gold distillation test measurement data of the coal well in the test measurement block, the tar yield data of the coal rock is obtained; wherein the coal rock measured in the test includes oil-bearing coal and oil-rich coal;

[0063] It should be noted that the research block mainly targeted by the present invention is a key coal well, which can also be referred to as a well logging in the present invention. The Gekin distillation test is to heat a certain number of coal samples or coal blends in a distillation tube according to certain requirements, collect tar, thermal decomposition water, ammonia and coal gas during the test, and compare the semi-coke with the standard Gekin coke type to judge the coking property of the coal from its bonding condition. The advantage of this method is that it can more comprehensively understand the situation of the thermal decomposition products of coal and can also indicate the coking property of coal at the same time.

[0064] S102: performing intersection analysis on the coal wells in the test measurement block according to the coal tar yield data combined with the logging parameters of the corresponding depth points, and screening the sensitive parameters in the logging that are sensitive to the oil-rich coal seams;

[0065] Specifically, for key coal wells, the coal tar yield data obtained by experimental measurement and the logging parameters (such as natural gamma, acoustic wave time difference, compensated density, deep resistivity, etc.) at the corresponding depth points are used for intersection analysis to screen out the logging parameters that are sensitive to the oil-rich coal layer. The logging parameters in the present invention mainly include: compensated density and deep resistivity.

[0066] S103: normalizing the sensitive parameter reflecting the sensitivity of the oil-rich coal seam to obtain a second sensitive parameter, and making the second sensitive parameter within the interval of (0, 1);

[0067] Specifically, the normalization process for sensitive parameters reflecting the sensitivity of the oil-rich coal seam includes:

[0068] Obtaining the numerical variation range of the coal seam compensation density and the numerical variation range of the deep resistivity, and performing normalization processing according to the numerical variation range of the compensation density and the numerical variation range of the deep resistivity, wherein since the variation range of the deep resistivity value is large, a logarithmic processing is performed on it before normalization;

[0069] The sensitive parameter is normalized to obtain a second sensitive parameter, where the second sensitive parameter includes: a normalized compensation density X and a normalized deep resistivity Y.

[0070] Among them, the oil-rich coal seam indicator factor Z is obtained by subtracting the normalized compensation density X from the normalized deep resistivity Y.

[0071] S104: mathematically process the second sensitive parameter to obtain an oil-rich coal seam indicator factor Z;

[0072] Specifically, mathematically processing the second sensitive parameter to obtain the oil-rich coal seam indication factor Z includes: constructing the oil-rich coal seam indication factor Z according to the second sensitive parameter; wherein the oil-rich coal seam indication factor Z is obtained by subtracting the normalized compensation density X from the normalized deep resistivity Y.

[0073] S105: Identify the oil-rich coal seam based on the tar yield data of the coal wells in the test measurement block combined with the oil-rich coal seam indicator factor Z.

[0074] In some optional embodiments, the coal wells in the test measurement block are subjected to intersection analysis based on the coal tar yield data combined with the logging parameters at the corresponding depth points, and sensitive parameters in the logging that are sensitive to the oil-rich coal seams are screened, including:

[0075] generating a first crossplot according to the tar yield data and the logging parameters;

[0076] Sensitive parameters are screened according to the correlation between the tar yield and the logging parameters reflected in the first cross-plot.

[0077] Combine the following Figure 2 and Figure 3 The embodiments of the present invention are described in detail.

[0078] See also Figure 2 and Figure 3The sensitive parameters that are sensitive to oil-rich coal layers in well logging are screened out through the correlation between tar yield data and deep resistivity and compensation density; among them, if the tar yield is significantly positively correlated with the deep resistivity, or the tar yield is significantly negatively correlated with the compensation density, it is determined that the well logging is relatively sensitive to the tar yield of coal rock.

[0079] Based on the key coal wells, on the basis of coal core depth correction, the tar yield data obtained from the Gekin distillation test and the logging parameters of the corresponding depth points were used for intersection analysis. Figure 2 and Figure 3 The cross-plot of tar yield measured in coal rock test and corresponding logging parameters (resistivity and compensated density) shows that tar yield is positively correlated with deep resistivity and negatively correlated with compensated density. The correlations between the two are 0.88 and 0.71, respectively, indicating that the two logging parameters, resistivity and compensated density, are relatively sensitive to the tar yield of coal rock. Therefore, these two parameters are selected as sensitive parameters for oil-rich coal.

[0080] It should be noted that, due to the large range of numerical variation of different logging parameters, if normalization is not performed, the numerical variation characteristics of different parameters will interfere with each other. At the same time, it is also to avoid the overall change of the logging curve caused by the measurement environment, human factors and other non-underground rock characteristics of the logging parameters. Under normal circumstances, such as the compensation density DEN, the numerical variation range of the coal seam is (1, 2), while the numerical variation range of the resistivity RT in the coal seam is (20, 200000). The numerical values ​​and variation ranges of the two are very different, so the selected sensitive parameters are all normalized. The specific operation method is as follows:

[0081]

[0082] Where DEN is the measured compensation density, g / cm 3 ; DENmin is the minimum value of coal seam compensation density, which is 1, g / cm 3 ; DENmax is the maximum value of coal seam compensation density, which is 2, g / cm 3 ; RT is the measured deep resistivity of well logging, Ω.m; LgRT is the logarithm of the deep resistivity. Since the resistivity value varies in a large range, the purpose of taking the logarithm is to be able to linearly scale it, Ω.m; LgRTmin is the logarithm of the minimum value of the deep resistivity of the coal seam, Ω.m; LgRTmin is the logarithm of the maximum value of the deep resistivity of the coal seam, Ω.m; X is the value after normalization of the compensation density, that is, the second compensation density, dimensionless; Y is the value after normalization of the logarithm of the deep resistivity, dimensionless.

[0083] Depend on Figure 2 and Figure 3It can be seen that both deep resistivity and compensation density have a good correlation with tar yield, and oil-rich coal seams are characterized by high resistivity values ​​and small compensation density values. Figure 4 In order to quickly indicate whether the oil-rich coal seam is developed, the present invention proposes to construct a new parameter - the oil-rich coal seam indication factor Z

[0084] The specific construction method is as follows:

[0085] Z=YX

[0086] It can be found that, in theory, when the coal tar yield is higher, the Z value is larger, and when the tar yield is lower, the Z value is smaller.

[0087] In some optional embodiments, the method of identifying the oil-rich coal seam according to the tar yield data of the coal well in the test measurement block combined with the oil-rich coal seam indicator factor Z includes:

[0088] Obtaining a tar yield value through a coal seam grouting test, generating a second cross-plot with the tar yield value and the oil-rich coal seam indicator factor Z, and determining a lower limit value Zmin of the indicator factor Z corresponding to the oil-rich coal seam according to the second cross-plot;

[0089] The oil-rich coal seam is determined based on the lower limit value Zmin of the indicator factor Z.

[0090] Specifically, determining the oil-rich coal seam according to the lower limit value Zmin of the indicator factor Z includes:

[0091] The oil-rich coal seam indicator factor Z is greater than the lower limit value Zmin, and the coal seam corresponding to the oil-rich coal seam indicator factor is determined to be an oil-rich coal seam;

[0092] When the oil-rich coal seam indication factor Z is less than or equal to the lower limit value Zmin, the coal seam corresponding to the oil-rich coal seam indication factor is determined to be an oil-poor coal seam.

[0093] Specifically, for key coal mines in the study area, see Figure 5 Combined with the tar yield value obtained by coal seam Gejin distillation test, cross-analysis is carried out to clarify the lower limit value Zmin of the indicator factor Z corresponding to the oil-rich coal seam (tar yield ≥ 7%).

[0094] See also Figure 5 and Figure 6According to the tar yield measured by the Ge Jin distillation test of the X1 well coal seam, the tar yield is distributed in the range of 3.5%-7.9%, with an average tar yield of 5.34%. This coal seam is mainly oil-poor coal. The tar yield of the X2 well coal seam is distributed in the range of 14.5%-16.1%, with an average tar yield of 15.4%. This coal seam is an oil-rich coal seam. From the calculated oil-rich coal seam indicator factor, it can be found that the Z value calculated for the X1 well is between -0.15 and 0.06, with an average value of -0.05; the Z value calculated for the X2 well is between 0.82 and 0.86, with an average value of 0.835.

[0095] For example, Figure 7 For example, the lower limit of the indicator factor of the oil-rich coal seam in the Tuha Santanghu Basin is 0.095, that is, when the calculated indicator factor Z is greater than or equal to 0.095, the coal seam is oil-rich coal, otherwise, it is oil-poor coal.

[0096] Figure 8 In order to study the actual application effect of a coal well in the block, the calculated oil-rich coal indicator factor Z is used to show that the actual calculated oil-rich coal seam indicator factor Z and the actual coal rock type comparison result show that the lower part of the coal seam is rich in oil, with a Z value greater than 0.095; the upper part is poor in oil, with a Z value less than 0.095. The Z value is consistent with the actual coal rock classification, and the method can quickly and accurately identify oil-rich coal seams, further confirming the effectiveness of the method.

[0097] It should be noted that, through the above method of the present invention, the oil-rich coal seams in other coal wells in the study area that have not been measured by the Ge Jin distillation test can be identified. The technical method is simple to operate, convenient for quickly and accurately identifying oil-rich coal seams, and can provide technical support for the study of the distribution characteristics of oil-rich coal seams. Even non-well logging professionals can quickly master the application. The method is not limited to the Tuha Santanghu Basin mentioned in the present invention, and the research method and ideas can also be extended and applied to other coal fields.

[0098] Based on the same inventive concept, the second aspect of the present invention also provides a device for identifying oil-rich coal seams, see Fig. 9 ,include:

[0099] The data acquisition unit 21 is used to acquire the tar yield data of the coal rock according to the coal rock gold distillation test measurement data of the coal well in the test measurement block; wherein the coal rock measured in the test includes oil-bearing coal and oil-rich coal;

[0100] An intersection analysis unit 22 is used to perform intersection analysis on the coal wells in the test measurement block according to the coal tar yield data combined with the logging parameters of the corresponding depth points, and screen the sensitive parameters in the logging that are sensitive to the oil-rich coal seams;

[0101] The data processing unit 23 is used to perform normalization processing on the sensitive parameter reflecting the sensitivity of the oil-rich coal seam to obtain a second sensitive parameter, and make the second sensitive parameter within the interval of (0, 1);

[0102] The second sensitive parameter is mathematically processed to obtain the oil-rich coal seam indicator factor Z;

[0103] The identification unit 24 is used to identify the oil-rich coal seam according to the tar yield data of the coal wells in the test measurement block combined with the oil-rich coal seam indicator factor Z.

[0104] Based on the same inventive concept, the third aspect of the present invention also provides an electronic device 161 for identifying an oil-rich coal seam, see Fig.10 , including a processor 164, a communication interface 165, a memory 162 and a communication bus, wherein the processor 164, the communication interface 165 and the memory 162 communicate with each other through the communication bus;

[0105] A memory 162 storing a computer program 163;

[0106] The processor 164 implements the method for quickly identifying oil-rich coal seams when executing the program stored in the memory 162.

[0107] The above communication bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus may be divided into an address bus, a data bus, a control bus, etc.

[0108] The communication interface 165 is used for communication between the electronic device 161 and other devices.

[0109] The memory 162 may include a random access memory 162 (RAM), or may include a non-volatile memory 162 (non-volatile memory), such as at least one disk memory 162. Optionally, the memory 162 may also be at least one storage device located away from the processor 164.

[0110] The above-mentioned processor 164 can be a general-purpose processor 164, including a central processing unit 164 (CPU), a network processor 164 (NP), etc.; it can also be a digital signal processor 164 (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0111] Based on the same inventive concept, the third aspect of the present invention further provides a computer-readable storage medium storing a computer program 163 , which implements the method for quickly identifying oil-rich coal seams when executed by a processor 164 .

[0112] The computer-readable storage medium may be included in the device / apparatus described in the above embodiment; or it may exist independently without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method for quickly identifying oil-rich coal seams according to the embodiment of the present disclosure is implemented.

[0113] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for identifying oil-rich coal seams, characterized in that: include: According to the coal rock gold distillation test measurement data of the coal well in the test measurement block, the tar yield data of the coal rock is obtained; wherein the coal rock measured in the test includes oil-bearing coal and oil-rich coal; According to the coal rock tar yield data combined with the logging parameters at the corresponding depth points, a multi-parameter intersection analysis is performed on the coal wells in the test measurement block to screen the sensitive parameters in the logging that are sensitive to the oil-rich coal seams; The sensitive parameters reflecting the sensitivity of the oil-rich coal seam are normalized to obtain the second sensitive parameter, and the second sensitive parameter is made within the interval of (0,1); The second sensitive parameter is mathematically processed to obtain the oil-rich coal seam indicator factor Z; The oil-rich coal seam is identified based on the tar yield data of the coal wells in the test measurement block combined with the oil-rich coal seam indicator factor Z.

2. The method according to claim 1, characterized in that The coal wells in the test measurement block are subjected to intersection analysis based on the coal tar yield data combined with the logging parameters at the corresponding depth points, and sensitive parameters in the logging that are sensitive to the oil-rich coal seams are screened, including: Generating a first cross-plot according to the tar yield data and logging parameters; wherein the logging parameters include: deep resistivity, compensated density and natural gamma; According to the correlation between the tar yield and the logging parameters reflected in the first cross-plot, sensitive parameters sensitive to the oil-rich coal are screened out.

3. The method according to claim 1, characterized in that The normalization process for the sensitive logging parameters reflected by the oil-rich coal seam includes: For the selected sensitive parameters of oil-rich coal, such as compensation density and deep resistivity, the numerical variation range of the compensation density of the coal seam and the numerical variation range of the deep resistivity are obtained, and normalization processing is performed according to the numerical variation range of the compensation density and the numerical variation range of the deep resistivity. Since the variation range of the deep resistivity value is large, the logarithm is taken before normalization; The sensitive parameter is normalized to obtain a second sensitive parameter, where the second sensitive parameter includes: a normalized compensation density X and a normalized deep resistivity Y.

4. The method according to claim 1, characterized in that: The second sensitive parameter is mathematically processed to obtain the oil-rich coal seam indicator factor Z, including: Constructing the oil-rich coal seam indicator factor Z according to the second sensitive parameter; Among them, the oil-rich coal seam indicator factor Z is obtained by subtracting the normalized compensation density X from the normalized deep resistivity Y.

5. The method according to claim 1, characterized in that The method of identifying the oil-rich coal seam according to the tar yield data of the coal well in the test measurement block combined with the oil-rich coal seam indicator factor Z comprises: Obtaining a tar yield value through a coal seam grouting test, generating a second cross-plot with the tar yield value and the oil-rich coal seam indicator factor Z, and determining a lower limit value Zmin of the indicator factor Z corresponding to the oil-rich coal seam according to the second cross-plot; The oil-rich coal seam is determined based on the lower limit value Zmin of the indicator factor Z.

6. The method according to claim 5, characterized in that The step of determining the oil-rich coal seam according to the lower limit value Zmin of the indicator factor Z comprises: The oil-rich coal seam indicator factor Z is greater than the lower limit value Zmin, and the coal seam corresponding to the oil-rich coal seam indicator factor is determined to be an oil-rich coal seam; When the oil-rich coal seam indication factor Z is less than or equal to the lower limit value Zmin, the coal seam corresponding to the oil-rich coal seam indication factor is determined to be an oil-poor coal seam.

7. The method according to claim 1 or 2, characterized in that: The sensitive parameters that are sensitive to oil-rich coal layers in screening logging are obtained through the correlation between tar yield data and logging parameters; Among them, if the tar yield is positively correlated with the deep resistivity, or the tar yield is negatively correlated with the compensation density, it is determined that the logging parameter is relatively sensitive to the tar yield of the coal rock.

8. A device for identifying oil-rich coal seams, characterized in that: include: A data acquisition unit is used to acquire tar yield data of coal rock according to the coal rock gold distillation test measurement data of the coal well in the test measurement block; wherein the coal rock measured in the test includes oil-bearing coal and oil-rich coal; An intersection analysis unit is used to perform intersection analysis on the coal wells in the test measurement block according to the coal rock tar yield data combined with the logging parameters of the corresponding depth points, and screen the sensitive parameters in the logging that are sensitive to the oil-rich coal seams; A data processing unit is used to perform normalization processing on the sensitive parameter reflecting the sensitivity of the oil-rich coal seam to obtain a second sensitive parameter, and make the second sensitive parameter within the interval of (0,1); The second sensitive parameter is mathematically processed to obtain the oil-rich coal seam indicator factor Z; The identification unit is used to identify the oil-rich coal seam based on the tar yield data of the coal wells in the test measurement block combined with the oil-rich coal seam indicator factor Z.

9. An electronic device for identifying oil-rich coal seams, characterized in that: include: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; a memory storing a computer program; The processor, when executing the program stored in the memory, implements the method for quickly identifying oil-rich coal seams as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, the method for quickly identifying oil-rich coal seams described in any one of claims 1 to 7 is implemented.

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