Lithology identification method, device and equipment for coal field logging and medium

Abstract

The invention relates to the technical field of oil field logging, in particular to a lithology identification method, device and equipment for coal field logging and a medium, and the method comprises the steps: obtaining exploring tube collection data, storing the data in a file, and establishing logging original data; forming a resistivity curve and a natural gamma curve based on the logging original data; layering the non-coal rock layer according to the change condition of the resistivity curve and the change condition of the natural gamma curve, and determining the resistivity statistical value and the natural gamma statistical value of each layer; performing normalization processing on the resistivity statistical value and the natural gamma statistical value of each layer to obtain a resistivity normalization result and a natural gamma normalization result of each layer; calculating a lithologic index result of each layer based on the resistivity normalization result and the natural gamma normalization result of each layer; and based on the lithological index result of each layer, determining the lithological interpretation of each layer, and further reducing the misjudgment condition of the lithological interpretation and improving the accuracy of the lithological interpretation through layered statistics and standardization of the lithological indexes.

Description

Technical Field

[0001] The present invention relates to the technical field of oilfield logging, and in particular to a lithology identification method, device, equipment and medium for coalfield logging. Background Art

[0002] Coal-bearing strata are all sedimentary rocks, and the lithology of the surrounding rocks is generally dominated by clastics, namely mudstone, sandy mudstone, muddy siltstone, siltstone, fine-grained sandstone, medium-grained sandstone, coarse-grained sandstone, conglomerate, etc. The comprehensive logging lithology interpretation of coalfields is mainly based on natural gamma curves and resistivity curves. The natural gamma curve reflects the mud content of the rock mass. The higher the mud content, the higher the natural gamma curve value; the resistivity curve is a comprehensive reflection of clastic rocks. The general rule is that the coarser the rock particles, the higher the resistivity. When interpreting lithology, on the logging curve diagram, lithology identification is performed based on the abnormal amplitude direction and relative size relationship of the natural gamma and resistivity curves.

[0003] However, since the lithology interpretation of coalfield comprehensive logging is qualitative interpretation, and requires the division and identification of the lithology of the entire well, in actual work, the interpreter needs to manually identify the lithology of each layer, and a borehole may be divided into hundreds of lithology layers. In the process of data interpretation, a lot of manpower and energy will be consumed, and there will be the following problems that affect the reliability of the interpretation:

[0004] (1) Different interpreters may identify the lithology of the same response as different lithology due to their different professional knowledge;

[0005] (2) The same interpreter may be affected by external factors or lack of concentration when working, which may also lead to misjudgment;

[0006] (3) When interpreting data from different boreholes in the same work area, there may be inconsistencies in the interpretation standards, resulting in inconsistent interpretation results for the same layer in different boreholes.

[0007] Therefore, how to reduce the misjudgment of lithology interpretation is a technical problem that needs to be solved urgently. Summary of the invention

[0008] In view of the above problems, the present invention provides a method, device, equipment and medium for lithology identification in coalfield logging that overcomes the above problems or at least partially solves the above problems.

[0009] In a first aspect, the present invention provides a lithology identification method for coalfield well logging, comprising:

[0010] Obtain the data collected by the probe tube, store it in a file, and establish the original logging data;

[0011] Based on the raw logging data, a resistivity curve and a natural gamma curve are formed;

[0012] For non-coal rock formations, stratify them according to the changes in the resistivity curve and the natural gamma curve, and determine the resistivity statistics and natural gamma statistics of each layer;

[0013] The resistivity statistics and natural gamma statistics of each layer are normalized respectively to obtain the resistivity normalization results and natural gamma normalization results of each layer;

[0014] Based on the resistivity normalization results and natural gamma normalization results of each layer, the lithology index results of each layer are calculated;

[0015] Based on the lithological index results of each layer, the lithological interpretation of each layer is determined.

[0016] Preferably, the data collected by the probe is data collected at each preset depth in the wellbore.

[0017] Preferably, for the non-coal rock formation, stratification is performed according to the change of the resistivity curve and the change of the natural gamma curve, and the resistivity statistics and natural gamma statistics of each layer are determined, including:

[0018] For non-coal rock formations, stratification is performed according to the changes in the resistivity curve and the natural gamma curve, so that the layers with the same change pattern are one layer, and the stratification results are obtained;

[0019] Based on the stratification results, the truncated average value of the resistivity of each layer is calculated to obtain the resistivity statistics of each layer, and the truncated average value of the natural gamma value of each layer is calculated to obtain the natural gamma statistics of each layer.

[0020] Preferably, based on the stratification results, the resistivity of each layer is calculated by a truncated average value to obtain the resistivity statistics of each layer, and the natural gamma value of each layer is calculated by a truncated average value to obtain the natural gamma statistics of each layer, including:

[0021] The stratification results are imported into EXCEL, and the truncated average value of the resistivity of each layer is calculated to obtain the resistivity statistics of each layer, and the truncated average value of the natural gamma value of each layer is calculated to obtain the natural gamma statistics of each layer.

[0022] Preferably, the resistivity statistics and natural gamma statistics of each layer are normalized respectively to obtain the resistivity normalized result and natural gamma normalized result of each layer, including:

[0023] The resistivity statistics of each layer are normalized to obtain the resistivity normalization results of each layer, which are specifically calculated according to the following formula:

[0024]

[0025] Among them, R 0,n is the normalized resistivity result of the current layer, R max is the maximum resistivity statistical value of the wellbore, R min is the minimum resistivity statistical value of the wellbore, R n is the resistivity statistic of the current layer;

[0026] The natural gamma statistics of each layer are normalized to obtain the natural gamma normalization results of each layer, which are specifically calculated according to the following formula:

[0027]

[0028] Among them, GR 0,n is the natural gamma normalization result of the current layer, GR max is the maximum natural gamma statistic value of the wellbore, GR min is the minimum natural gamma statistic value of the wellbore, GR n It is the natural gamma statistic of the current layer.

[0029] Preferably, the lithology index results of each layer are calculated based on the resistivity normalization results and natural gamma normalization results of each layer, specifically according to the following calculation formula:

[0030]

[0031] Among them, LITH n is the lithology index result of the current layer, R 0,n-1 is the resistivity normalized result of the top adjacent layer of the current layer, R 0,n+1 is the resistivity normalized result of the bottom adjacent layer of the current layer, GR 0,n-1 is the normalized result of the natural gamma value of the top adjacent layer of the current layer, GR 0,n+1 The natural gamma value normalization result of the bottom adjacent layer of the current layer.

[0032] Preferably, the lithology interpretation of each layer is determined based on the lithology index results of each layer, including:

[0033] Obtain the corresponding relationship table between lithology index results and lithology interpretation;

[0034] Based on the lithology index results of each layer and the corresponding relationship table, the lithology interpretation of each layer is determined.

[0035] In a second aspect, the present invention further provides a lithology identification device for coalfield well logging, comprising:

[0036] The acquisition module is used to acquire the data collected by the probe tube, store it in a file, and establish the original logging data;

[0037] A forming module, used for forming a resistivity curve and a natural gamma curve based on the raw logging data;

[0038] The first determination module is used to stratify the non-coal rock layer according to the change of the resistivity curve and the change of the natural gamma curve, and determine the resistivity statistical value and the natural gamma statistical value of each layer;

[0039] A module is obtained, which is used to normalize the resistivity statistics and natural gamma statistics of each layer, and obtain the resistivity normalization result and natural gamma normalization result of each layer;

[0040] A calculation module, used for calculating the lithology index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer;

[0041] The second determination module is used to determine the lithology interpretation of each layer based on the lithology index results of each layer.

[0042] In a third aspect, the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0043] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0044] One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:

[0045] The invention provides a lithology identification method for coalfield logging, comprising: acquiring probe acquisition data, storing the data in a file, and establishing original logging data; forming a resistivity curve and a natural gamma curve based on the original logging data; stratifying non-coal rock layers according to the change of the resistivity curve and the change of the natural gamma curve, and determining the resistivity statistics and the natural gamma statistics of each layer; normalizing the resistivity statistics and the natural gamma statistics of each layer, respectively, to obtain the resistivity normalization results and the natural gamma normalization results of each layer; calculating the lithology index results of each layer based on the resistivity normalization results and the natural gamma normalization results of each layer; determining the lithology interpretation of each layer based on the lithology index results of each layer, and then reducing the misjudgment of the lithology interpretation through stratified statistics and standardized lithology indexes, and improving the accuracy of the lithology interpretation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Also, throughout the accompanying drawings, the same reference figures are used to represent the same components. In the drawings:

[0047] Figure 1 A schematic diagram of the steps of the lithology identification method of coalfield logging in an embodiment of the present invention is shown;

[0048] Figure 2 A schematic diagram showing the import of probe collected data into EXCEL in an embodiment of the present invention is shown;

[0049] Figure 3 A schematic diagram of a natural gamma curve in an embodiment of the present invention is shown;

[0050] Figure 4 A schematic diagram showing the results presented after the hierarchical results are imported into EXCEL in an embodiment of the present invention;

[0051] Figure 5 A schematic diagram showing the calculation of truncated average value in EXCEL in an embodiment of the present invention is shown;

[0052] Figure 6 A schematic diagram showing the resistivity normalization result of each layer in an embodiment of the present invention;

[0053] Figure 7 A schematic diagram showing the natural gamma normalization results of each layer in an embodiment of the present invention is shown;

[0054] Figure 8 A schematic diagram of code for automatically generating a table according to the format of a result table based on the automatically identified lithology in an embodiment of the present invention is shown;

[0055] Fig. 9 A schematic diagram showing the lithology index results in an embodiment of the present invention is shown;

[0056] Fig.10 A schematic diagram showing that the stratification point data of the coal seam in the embodiment of the present invention is also input into the table;

[0057] Fig.11 A schematic diagram showing the automatic generation of a coal seam achievement table in an embodiment of the present invention is shown;

[0058] Fig.12 A schematic diagram of the structure of a lithology identification device for coalfield well logging in an embodiment of the present invention is shown;

[0059] Fig.13 The schematic diagram of the structure of the computer equipment for implementing the lithology identification method of coalfield logging in the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0060] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0061] Embodiment 1

[0062] The embodiment of the present invention provides a lithology identification method for coalfield logging, such as Figure 1 As shown, including:

[0063] S101, acquiring the data collected by the probe, storing it in a file, and establishing the original logging data;

[0064] S102, generating a resistivity curve and a natural gamma curve based on the original logging data;

[0065] S103, for the non-coal rock layer, stratify the layer according to the change of the resistivity curve and the change of the natural gamma curve, and determine the resistivity statistical value and the natural gamma statistical value of each layer;

[0066] S104, normalizing the resistivity statistics and natural gamma statistics of each layer respectively to obtain the resistivity normalization result and natural gamma normalization result of each layer;

[0067] S105, calculating the lithology index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer;

[0068] S106, determining the lithology interpretation of each layer based on the lithology index results of each layer.

[0069] First, in S101, the probe acquisition data is obtained, which may be data acquired by different probes. Then, the data is converted into decimal format and imported into EXCEL, and different labels are used to represent the different probe acquisition data, such as Figure 2 As shown in the figure, "05" indicates the electrode system probe, "18" indicates the combined density probe, "19" indicates the well temperature probe, and "27" indicates the data obtained by the well inclination probe. At the same time, important information such as well logging field records, drilling catalog results, and well logging notices can also be stored in the file to establish the original well logging data.

[0070] The probe data collected here is the data collected at every preset depth in the wellbore. The sampling interval is generally 0.05m.

[0071] Next, S102 is executed to form a resistivity curve and a natural gamma curve based on the original logging data. The resistivity curve is a curve showing the change of the resistivity value collected with the change of the wellbore depth; the natural gamma curve is also a curve showing the change of the natural gamma curve collected with the change of the wellbore depth. Figure 3 As shown, this is the natural gamma curve formed.

[0072] For coal seams (carbonaceous mudstone), there are also long source distance gamma curves and short source distance gamma curves.

[0073] Next, S103 is executed to stratify the non-coal rock layers according to the changes in the resistivity curve and the natural gamma curve.

[0074] Specifically, for non-coal rock formations, stratification is performed according to the changes in the resistivity curve and the natural gamma curve, so that the formations with the same change pattern are grouped as one layer, and the stratification results are obtained;

[0075] Based on the stratification results, the truncated average value of the resistivity of each layer is calculated to obtain the resistivity statistics of each layer, and the truncated average value of the natural gamma value of each layer is calculated to obtain the natural gamma statistics of each layer.

[0076] Specifically, the stratification results are imported into EXCEL, the resistivity of each layer is calculated by a truncated average value to obtain the resistivity statistics of each layer, and the natural gamma value of each layer is calculated by a truncated average value to obtain the natural gamma statistics of each layer.

[0077] After importing the stratified results into EXCEL, the results presented are as follows Figure 4 shown.

[0078] The truncated mean value specifically discards 10% of the data at both the high and low ends and calculates the average value of the remaining data. Figure 5 The calculation formula shown.

[0079] After obtaining the truncated mean value of the resistivity and the truncated mean value of the natural gamma value of each layer, execute S104 to normalize the resistivity statistics (truncated mean value of the resistivity) and the natural gamma statistics (truncated mean value of the natural gamma) of each layer, respectively, to obtain the normalized resistivity results and the normalized natural gamma results of each layer.

[0080] Specifically, the resistivity statistics of each layer are normalized to obtain the resistivity normalization results of each layer, which are specifically obtained according to the following calculation formula:

[0081]

[0082] Among them, R 0,nis the normalized resistivity result of the current layer, R max is the maximum resistivity statistical value of the wellbore, R min is the minimum resistivity statistical value of the wellbore, R n It is the resistivity statistics of the current layer.

[0083] like Figure 6 As shown in the figure, the column items pointed by arrows are the normalized results of resistivity of each layer.

[0084] The natural gamma statistics of each layer are normalized to obtain the natural gamma normalization results of each layer, which are specifically calculated according to the following formula:

[0085]

[0086] Among them, GR 0,n is the natural gamma normalization result of the current layer, GR max is the maximum natural gamma statistic value of the wellbore, GR min is the minimum natural gamma statistic value of the wellbore, GR n It is the natural gamma statistic of the current layer.

[0087] like Figure 7 As shown in the figure, the column items pointed by the arrows are the natural gamma normalization results of each layer.

[0088] After obtaining the resistivity normalization results and the natural gamma normalization results of each layer, S105 is executed to calculate the lithology index results of each layer based on the resistivity normalization results and the natural gamma normalization results of each layer. Specifically, the calculation is performed according to the following calculation formula:

[0089]

[0090] Among them, LITH n is the lithology index result of the current layer, R 0,n-1 is the resistivity normalized result of the top adjacent layer of the current layer, R 0,n+1 is the resistivity normalized result of the bottom adjacent layer of the current layer, GR 0,n-1 is the normalized result of the natural gamma value of the top adjacent layer of the current layer, GR 0,n+1 The natural gamma value normalization result of the bottom adjacent layer of the current layer.

[0091] After obtaining the lithology index results of each layer, S106 is executed to determine the lithology interpretation of each layer based on the lithology index results of each layer.

[0092] Specifically, a corresponding relationship table between lithological index results and lithological interpretations is obtained;

[0093] Based on the lithological index results and corresponding relationship table of each layer, the lithological interpretation of each layer is determined.

[0094] The corresponding relationship between the lithology index results and lithology interpretation is as follows:

[0095] Table 1: Correspondence between lithology index results and lithology interpretation

[0096]

[0097] According to the corresponding relationship table and the lithological index results of each layer, the lithological interpretation of each layer can be determined.

[0098] like Figure 8 As shown in the figure, the code is written using the Visual Basic editor of EXCEL to automatically generate a table of automatically identified lithologies in the format of the result table, thereby reducing the mistakes caused by manual filling in the table. The specific lithology index results generated are as follows Fig. 9 The arrows shown indicate the vertical columns.

[0099] For coal seam interpretation, the coal seam layer point data is also entered into the table, such as Fig.10 As shown, in the "C1-D" and "C2-D" columns in the "Coal" tab, the parameter identifier is entered at the corresponding position of the coal seam floor depth in column A, "Ω" represents the resistivity curve, "γ" represents the natural gamma curve, "L" represents the long source distance gamma curve, and "S" represents the short source distance gamma curve. The system automatically calculates the thickness of each layer, the maximum depth difference and thickness difference of the two curve interpretation results, automatically counts the density value of the coal seam section, and determines whether it is coal or carbonaceous mudstone based on the density value.

[0100] Then, use the Visual Basic editor of EXCEL to write code to automatically generate a coal seam results table, which is displayed in the "List" label and output as a coal seam interpretation results table, such as Fig.11 shown.

[0101] One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:

[0102] The invention provides a lithology identification method for coalfield logging, comprising: acquiring probe acquisition data, storing the data in a file, and establishing original logging data; forming a resistivity curve and a natural gamma curve based on the original logging data; stratifying non-coal rock layers according to the change of the resistivity curve and the change of the natural gamma curve, and determining the resistivity statistics and the natural gamma statistics of each layer; normalizing the resistivity statistics and the natural gamma statistics of each layer, respectively, to obtain the resistivity normalization results and the natural gamma normalization results of each layer; calculating the lithology index results of each layer based on the resistivity normalization results and the natural gamma normalization results of each layer; determining the lithology interpretation of each layer based on the lithology index results of each layer, and then reducing the misjudgment of the lithology interpretation through stratified statistics and standardized lithology indexes, and improving the accuracy of the lithology interpretation.

[0103] Embodiment 2

[0104] Based on the same inventive concept, the embodiment of the present invention also provides a lithology identification device for coalfield logging, such as Fig.12 As shown, including:

[0105] The acquisition module 1201 is used to acquire the data collected by the probe, store it in a file, and establish the original logging data;

[0106] A forming module 1202 is used to form a resistivity curve and a natural gamma curve based on the raw logging data;

[0107] The first determination module 1203 is used to stratify the non-coal rock layer according to the change of the resistivity curve and the change of the natural gamma curve, and determine the resistivity statistics and natural gamma statistics of each layer;

[0108] Obtaining module 1204, for normalizing the resistivity statistics and natural gamma statistics of each layer, respectively, to obtain resistivity normalization results and natural gamma normalization results of each layer;

[0109] The calculation module 1205 is used to calculate the lithology index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer;

[0110] The second determination module 1206 is used to determine the lithology interpretation of each layer based on the lithology index results of each layer.

[0111] In an optional embodiment, the data collected by the probe is the data collected at each preset depth in the wellbore.

[0112] In an optional implementation, the first determining module 1203 is configured to:

[0113] For non-coal rock formations, stratification is performed according to the changes in the resistivity curve and the natural gamma curve, so that the layers with the same change pattern are one layer, and the stratification results are obtained;

[0114] Based on the stratification results, a truncated average value is calculated for the resistivity of each layer to obtain the resistivity statistics of each layer, and a truncated average value is calculated for the natural gamma value of each layer to obtain the natural gamma statistics of each layer.

[0115] In an optional implementation, the first determining module 1203 is configured to:

[0116] The stratification results are imported into EXCEL, and the truncated average value of the resistivity of each layer is calculated to obtain the resistivity statistics of each layer, and the truncated average value of the natural gamma value of each layer is calculated to obtain the natural gamma statistics of each layer.

[0117] In an optional implementation, a module 1204 is obtained for:

[0118] The resistivity statistics of each layer are normalized to obtain the resistivity normalization results of each layer, which are specifically obtained according to the following calculation formula:

[0119]

[0120] Among them, R 0,n is the normalized resistivity result of the current layer, R max is the maximum resistivity statistical value of the wellbore, R min is the minimum resistivity statistical value of the wellbore, R n is the resistivity statistic of the current layer;

[0121] The natural gamma statistics of each layer are normalized to obtain the natural gamma normalization results of each layer, which are specifically calculated according to the following formula:

[0122]

[0123] Among them, GR 0,n is the natural gamma normalization result of the current layer, GR max is the maximum natural gamma statistic value of the wellbore, GR min is the minimum natural gamma statistic value of the wellbore, GR n It is the natural gamma statistic of the current layer.

[0124] In an optional implementation, the calculation module 1205 is used to:

[0125] The specific calculation is as follows:

[0126]

[0127] Among them, LITH n is the lithology index result of the current layer, R 0,n-1 is the resistivity normalized result of the top adjacent layer of the current layer, R 0,n+1 is the resistivity normalized result of the bottom adjacent layer of the current layer, GR 0,n-1 is the normalized result of the natural gamma value of the top adjacent layer of the current layer, GR 0,n+1 The natural gamma value normalization result of the bottom adjacent layer of the current layer.

[0128] In an optional implementation, the second determining module 1206 is configured to:

[0129] Obtain the corresponding relationship table between lithology index results and lithology interpretation;

[0130] Based on the lithology index results of each layer and the corresponding relationship table, the lithology interpretation of each layer is determined.

[0131] Embodiment 3

[0132] Based on the same inventive concept, an embodiment of the present invention provides a computer device, such as Fig.13 As shown, it includes a memory 1304, a processor 1302, and a computer program stored in the memory 1304 and executable on the processor 1302. When the processor 1302 executes the program, the steps of the above-mentioned coalfield logging lithology identification method are implemented.

[0133] Among them, Fig.13 In the embodiment of the present invention, a bus architecture (represented by bus 1300) is shown, and bus 1300 may include any number of interconnected buses and bridges, and bus 1300 links various circuits including one or more processors represented by processor 1302 and memory represented by memory 1304. Bus 1300 may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. Bus interface 1306 provides an interface between bus 1300 and receiver 1301 and transmitter 1303. Receiver 1301 and transmitter 1303 may be the same element, namely a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 1302 is responsible for managing bus 1300 and general processing, while memory 1304 may be used to store data used by processor 1302 when performing operations.

[0134] Embodiment 4

[0135] Based on the same inventive concept, an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the above-mentioned lithology identification method of coalfield logging are implemented.

[0136] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description of the above specific languages ​​is for disclosing the best mode of the present invention.

[0137] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0138] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the following intention: that the claimed invention requires more features than the features explicitly recorded in each embodiment. More specifically, as reflected in each embodiment, the inventive aspects lie in less than all the features of the single embodiment disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself serves as a separate embodiment of the present invention.

[0139] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0140] In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present invention and form different embodiments. For example, in a specific embodiment, any one of the claimed embodiments may be used in any combination.

[0141] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or a digital signal processor (DSP) can be used in practice to implement some or all functions of some or all components of a lithology identification device for coalfield logging and a computer device according to an embodiment of the present invention. The present invention can also be implemented as a device or device program (e.g., a computer program and a computer program product) for executing part or all of the methods described herein. Such a program for implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0142] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc., does not indicate any order. These words may be interpreted as names.

Claims

1. A lithology identification method for coalfield logging, characterized in that: include: Obtain the data collected by the probe tube, store it in a file, and establish the original logging data; Based on the raw logging data, a resistivity curve and a natural gamma curve are formed; For non-coal rock formations, stratify them according to the changes in the resistivity curve and the natural gamma curve, and determine the resistivity statistics and natural gamma statistics of each layer; The resistivity statistics and natural gamma statistics of each layer are normalized respectively to obtain the resistivity normalization results and natural gamma normalization results of each layer; Based on the resistivity normalization results and natural gamma normalization results of each layer, the lithology index results of each layer are calculated; Based on the lithological index results of each layer, the lithological interpretation of each layer is determined.

2. The method according to claim 1, characterized in that The data collected by the probe is the data collected at each preset depth in the wellbore.

3. The method according to claim 1, characterized in that For the non-coal rock layer, stratification is performed according to the change of the resistivity curve and the change of the natural gamma curve, and the resistivity statistical value and the natural gamma statistical value of each layer are determined, including: For non-coal rock formations, stratification is performed according to the changes in the resistivity curve and the natural gamma curve, so that the layers with the same change pattern are one layer, and the stratification results are obtained; Based on the stratification results, the truncated average value of the resistivity of each layer is calculated to obtain the resistivity statistics of each layer, and the truncated average value of the natural gamma of each layer is calculated to obtain the natural gamma statistics of each layer.

4. The method according to claim 3, characterized in that Based on the stratification results, the resistivity of each layer is calculated by the truncated average value to obtain the resistivity statistics of each layer, and the natural gamma of each layer is calculated by the truncated average value to obtain the natural gamma statistics of each layer, including: The stratification results are imported into EXCEL, and the truncated average value of the resistivity of each layer is calculated to obtain the resistivity statistics of each layer, and the truncated average value of the natural gamma value of each layer is calculated to obtain the natural gamma statistics of each layer.

5. The method according to claim 1, characterized in that The resistivity statistics and natural gamma statistics of each layer are normalized respectively to obtain the resistivity normalization results and natural gamma normalization results of each layer, including: The resistivity statistics of each layer are normalized to obtain the resistivity normalization results of each layer, which are specifically calculated according to the following formula: Among them, R 0,n is the normalized resistivity result of the current layer, R max is the maximum resistivity statistical value of the wellbore, R min is the minimum resistivity statistical value of the wellbore, R n is the resistivity statistic of the current layer; The natural gamma statistics of each layer are normalized to obtain the natural gamma normalization results of each layer, which are specifically calculated according to the following formula: Among them, GR 0,n is the natural gamma normalization result of the current layer, GR max is the maximum natural gamma statistic value of the wellbore, GR min is the minimum natural gamma statistic value of the wellbore, GR n It is the natural gamma statistic of the current layer.

6. The method according to claim 5, characterized in that The lithology index results of each layer are calculated based on the resistivity normalization results and natural gamma normalization results of each layer, and are specifically calculated according to the following calculation formula: Among them, LITH n is the lithology index result of the current layer, R 0,n-1 is the resistivity normalized result of the top adjacent layer of the current layer, R 0,n+1 is the resistivity normalized result of the bottom adjacent layer of the current layer, GR 0,n-1 is the normalized result of the natural gamma value of the top adjacent layer of the current layer, GR 0,n+1 The natural gamma value normalization result of the bottom adjacent layer of the current layer.

7. The method according to claim 1, characterized in that The lithology interpretation of each layer is determined based on the lithology index results of each layer, including: Obtain the corresponding relationship table between lithology index results and lithology interpretation; Based on the lithology index results of each layer and the corresponding relationship table, the lithology interpretation of each layer is determined.

8. A lithology identification device for coalfield logging, characterized in that: include: The acquisition module is used to acquire the data collected by the probe tube, store it in a file, and establish the original logging data; A forming module, used for forming a resistivity curve and a natural gamma curve based on the raw logging data; The first determination module is used to stratify the non-coal rock layer according to the change of the resistivity curve and the change of the natural gamma curve, and determine the resistivity statistical value and the natural gamma statistical value of each layer; A module is obtained, which is used to normalize the resistivity statistics and natural gamma statistics of each layer, and obtain the resistivity normalization result and natural gamma normalization result of each layer; A calculation module, used for calculating the lithology index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer; The second determination module is used to determine the lithology interpretation of each layer based on the lithology index results of each layer.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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