A lithology identification method, device, equipment and medium for coalfield logging

Abstract

The present invention relates to the technical field of oilfield well logging, and in particular to a lithology identification method, device, equipment and medium for coalfield well logging. The method comprises: obtaining probe acquisition data, storing the data in a file and establishing raw logging data; forming a resistivity curve and a natural gamma curve based on the raw logging data; stratifying non-coal rock layers according to changes in the resistivity curve and the natural gamma curve, and determining resistivity statistics and natural gamma statistics of each layer; normalizing the resistivity statistics and natural gamma statistics of each layer to obtain normalized resistivity results and normalized natural gamma results of each layer; calculating lithology index results of each layer based on the normalized resistivity results and natural gamma results of each layer; and determining lithology interpretations of each layer based on the lithology index results of each layer, thereby reducing misjudgment of lithology interpretations and improving the accuracy of lithology interpretations through stratified statistics and standardized lithology indicators.

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 surrounding rock is generally clastic, consisting of mudstone, sandy mudstone, argillaceous siltstone, siltstone, fine-grained sandstone, medium-grained sandstone, coarse-grained sandstone, and conglomerate. Lithologic interpretation in coalfield comprehensive logging is primarily based on gamma ray and resistivity curves. The gamma ray curve reflects the shale content of the rock mass, with higher gamma ray values ​​indicating higher shale content. The resistivity curve provides a comprehensive reflection of clastic rock, generally indicating that coarser rock grains have higher resistivity. Lithologic interpretation involves identifying lithologic features based on the direction and relative magnitude of anomalies in the gamma ray and resistivity curves on the well logging graph.

[0003] However, since coalfield comprehensive logging lithologic interpretation is qualitative and requires the division and identification of the lithologic properties of the entire well, in actual work, interpreters need to manually identify the lithologic properties of each layer. A single borehole may be divided into hundreds of lithologic layers, which consumes a lot of manpower and energy during the data interpretation process. In addition, there are the following issues that affect the reliability of the interpretation:

[0004] (1) Different interpreters may identify 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 during work, which may lead to misjudgment;

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

[0007] Therefore, how to reduce the misjudgment of lithologic 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 lithologic 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, store it in a file, and create the original logging data;

[0011] generating a resistivity curve and a natural gamma ray curve based on the raw logging data;

[0012] For non-coal rock layers, 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 normalized results and natural gamma normalized results of each layer;

[0014] Calculate the lithologic index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer;

[0015] Based on the lithologic index results of each layer, the lithologic 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 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:

[0018] For non-coal rock layers, 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 grouped as one layer to obtain the stratification results;

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

[0020] Preferably, the step of calculating the truncated average value of the resistivity of each layer based on the stratification result to obtain the resistivity statistics of each layer and calculating the truncated average value of the natural gamma value of each layer to obtain the natural gamma statistics of each layer includes:

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

[0022] Preferably, the resistivity statistics and natural gamma statistics of each layer are normalized respectively to obtain the resistivity normalized results and natural gamma normalized results 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 ray statistic value of the wellbore, GR min is the minimum natural gamma ray statistic value of the wellbore, GR n It is the natural gamma statistic of the current layer.

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

[0030]

[0031] Among them, LITH n is the lithologic 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 natural gamma value normalization result 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, determining the lithologic interpretation of each layer based on the lithologic index results of each layer includes:

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

[0034] Based on the lithologic index results of each layer and the corresponding relationship table, the lithologic 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 obtain the data collected by the probe, store it in a file, and establish the original logging data;

[0037] A forming module, configured to form a resistivity curve and a natural gamma ray 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] Obtaining a module for normalizing the resistivity statistics and natural gamma statistics of each layer to obtain the resistivity normalization results and natural gamma normalization results of each layer;

[0040] A calculation module is used to calculate the lithologic 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 lithologic interpretation of each layer based on the lithologic 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 implements the method described in the first aspect when the program is executed by a processor.

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

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

[0046] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. Throughout the drawings, the same reference figures denote the same components. In the drawings:

[0047] Figure 1 A schematic diagram showing the steps of a lithology identification method for coalfield well logging according to an embodiment of the present invention is shown;

[0048] Figure 2 A schematic diagram showing the import of probe-collected data into EXCEL according to 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 after the hierarchical results are imported into EXCEL in an embodiment of the present invention is shown;

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

[0052] Figure 6 A schematic diagram showing the resistivity normalization results 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 based on the automatically identified lithology in the format of a result table according to an embodiment of the present invention is shown;

[0055] Figure 9 A schematic diagram showing the lithology index results in an embodiment of the present invention;

[0056] Figure 10 A schematic diagram showing that the layer point data of the coal seam is also input into a table in an embodiment of the present invention;

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

[0058] Figure 12 A schematic structural diagram of a lithology identification device for coalfield well logging according to an embodiment of the present invention is shown;

[0059] Figure 13 The diagram shows the structure of a computer device for implementing the lithology identification method of coalfield well logging in an embodiment of the present invention. 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. Rather, these embodiments are provided 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] Example 1

[0062] The embodiment of the present invention provides a lithology identification method for coalfield logging, such as Figure 1 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 ray 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, performing normalization processing on the resistivity statistics and natural gamma statistics of each layer to obtain the resistivity normalization result and natural gamma normalization result of each layer;

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

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

[0069] First, in S101, the probe acquisition data is obtained, which may be data collected by different probes. Then, these data are converted into decimal format and imported into EXCEL, and different labels are used to represent different probe acquisition data, such as Figure 2 As shown in the figure, "05" represents the electrode system probe, "18" represents the combined density probe, "19" represents the well temperature probe, and "27" represents data obtained from the well deviation probe. Important information such as logging site records, drilling log results, and logging notices can also be stored in the file to create raw logging data.

[0070] The probe data collected here is collected at preset depths within the wellbore, with a sampling interval of 0.05m.

[0071] Next, S102 is executed to generate a resistivity curve and a natural gamma curve based on the original logging data. The resistivity curve is a curve showing the changes in the resistivity value collected as the wellbore depth changes; the natural gamma curve is also a curve showing the changes in the natural gamma curve collected as the wellbore depth changes. 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 layer according to the change of the resistivity curve and the change of the natural gamma curve.

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

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

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

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

[0078] The truncated mean specifically discards 10% of the data at both the high and low ends, and calculates the average 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 statistical values ​​of each layer are normalized to obtain the resistivity normalization results of each layer, which are specifically calculated according to the following 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 statistical value of the current layer.

[0083] like Figure 6 As shown in the figure, the column items pointed by the arrows are the normalized results of the 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 ray statistic value of the wellbore, GR min is the minimum natural gamma ray 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 natural gamma normalization results of each layer, S105 is executed to calculate the lithologic index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer. The calculation is specifically performed according to the following formula:

[0089]

[0090] Among them, LITH n is the lithologic 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 natural gamma value normalization result 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 lithologic index results of each layer, S106 is executed to determine the lithologic interpretation of each layer based on the lithologic index results of each layer.

[0092] Specifically, a correspondence table between lithologic index results and lithologic interpretations is obtained;

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

[0094] The corresponding relationship between the lithologic index results and lithologic interpretation is shown in the following table:

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

[0096]

[0097] According to the corresponding relationship table and the lithologic index results of each layer, the lithologic 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 Figure 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 Figure 10 As shown in the figure, in the "C1-D" and "C2-D" columns of the "Coal" tab, enter the parameter identifier corresponding to the coal seam floor depth in column A. "Ω" represents the resistivity curve, "γ" represents the natural gamma ray curve, "L" represents the long-source-distance gamma ray curve, and "S" represents the short-source-distance gamma ray curve. The system automatically calculates the thickness of each layer, the maximum depth and thickness difference between the two curve interpretations, and automatically calculates the density value of the coal seam section. Based on the density value, it can be used to determine whether it is coal or carbonaceous mudstone.

[0100] Then, use the Visual Basic editor of EXCEL to write code to automatically generate a coal seam result table, which is displayed in the "List" label and output as the coal seam interpretation result table, such as Figure 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 present invention provides a lithology identification method for coalfield well logging, comprising: acquiring probe acquisition data, storing the data in a file, and establishing raw well logging data; forming a resistivity curve and a natural gamma curve based on the raw well logging data; stratifying non-coal rock layers according to changes in the resistivity curve and the natural gamma curve, and determining resistivity statistics and natural gamma statistics of each layer; normalizing the resistivity statistics and natural gamma statistics of each layer to obtain resistivity normalization results and natural gamma normalization results of each layer; calculating lithology index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer; and determining lithology interpretations of each layer based on the lithology index results of each layer, thereby reducing misjudgment of lithology interpretations and improving the accuracy of lithology interpretations through stratified statistics and standardized lithology indicators.

[0103] Example 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 Figure 12 Shown, including:

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

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

[0107] The first determining module 1203 is configured 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;

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

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

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

[0111] In an optional embodiment, the data collected by the probe is 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 layers, 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 grouped as one layer to obtain the stratification results;

[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 were imported into EXCEL, and the truncated average value of the resistivity of each layer was calculated to obtain the resistivity statistical value of each layer. The truncated average value of the natural gamma value of each layer was calculated to obtain the natural gamma statistical value of each layer.

[0117] In an optional embodiment, 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 calculated according to the following 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 ray statistic value of the wellbore, GR min is the minimum natural gamma ray 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 configured to:

[0125] The calculation is specifically based on the following formula:

[0126]

[0127] Among them, LITH n is the lithologic 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 natural gamma value normalization result 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 lithologic index results and lithologic interpretation;

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

[0131] Example 3

[0132] Based on the same inventive concept, an embodiment of the present invention provides a computer device, such as Figure 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, Figure 13 In the embodiment of the present invention, a bus architecture (represented by bus 1300) is shown. 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 therefore will not be described further 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 component, namely a transceiver, which provides 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] Example 4

[0135] Based on the same inventive concept, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the above-mentioned coalfield logging lithology identification method 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 this type of system. In addition, the present invention is not directed to any specific programming language. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the above description of specific languages ​​is for the purpose of disclosing the best mode of the present invention.

[0137] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may 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, 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 an intention that the claimed invention requires more features than those explicitly recited in each embodiment. Rather, as reflected in each embodiment, inventive aspects lie in fewer than all the features of the individual embodiments previously disclosed. Accordingly, the claims that follow the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own 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 may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed herein may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, 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] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of the present invention and to 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. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components of the lithology identification device for coalfield logging and computer equipment 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 rather than limit the invention, 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 signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" 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 several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. 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 well logging, characterized in that: include: Obtain the data collected by the probe, store it in a file, and create the original logging data; generating a resistivity curve and a natural gamma ray curve based on the raw logging data; For non-coal rock layers, 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, 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 ray statistic value of the wellbore, GR min is the minimum natural gamma ray statistic value of the wellbore, GR n is the natural gamma statistic of the current layer; Based on the resistivity normalization results and natural gamma normalization results of each layer, the lithologic index results of each layer are calculated according to the following calculation formula: Among them, LITH n is the lithologic 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 natural gamma value normalization result 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; Based on the lithologic index results of each layer, the lithologic interpretation of each layer is determined.

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

3. The method according to claim 1, wherein 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 layers, 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 grouped as one layer to obtain the stratification results; Based on the stratification results, the truncated average value of the resistivity of each layer is calculated to obtain the resistivity statistical value of each layer, and the truncated average value of the natural gamma of each layer is calculated to obtain the natural gamma statistical value of each layer.

4. The method according to claim 3, wherein 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. The truncated average value of the natural gamma of each layer is calculated to obtain the natural gamma statistics of each layer, including: The stratification results were imported into EXCEL, and the truncated average value of the resistivity of each layer was calculated to obtain the resistivity statistical value of each layer. The truncated average value of the natural gamma value of each layer was calculated to obtain the natural gamma statistical value of each layer.

5. The method according to claim 1, wherein The lithologic interpretation of each layer is determined based on the lithologic index results of each layer, including: Obtain the corresponding relationship table between lithologic index results and lithologic interpretation; Based on the lithologic index results of each layer and the corresponding relationship table, the lithologic interpretation of each layer is determined.

6. A lithology identification device for coalfield logging, characterized in that: include: The acquisition module is used to obtain the data collected by the probe, store it in a file, and establish the original logging data; A forming module, configured to form a resistivity curve and a natural gamma ray 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; The obtaining module is used to normalize the resistivity statistics and natural gamma statistics of each layer respectively to obtain the resistivity normalization results and natural gamma normalization results of each layer. The obtaining module is used to: 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 ray statistic value of the wellbore, GR min is the minimum natural gamma ray statistic value of the wellbore, GR n is the natural gamma statistic of the current layer; The calculation module is used to calculate the lithologic index results of each layer based on the resistivity normalization results and natural gamma normalization results of each layer. The calculation module is specifically calculated according to the following calculation formula: Among them, LITH n is the lithologic 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 natural gamma value normalization result 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; The second determination module is used to determine the lithologic interpretation of each layer based on the lithologic index results of each layer.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

8. 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 5 is implemented.

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