Lithology identification method

Abstract

The embodiment of the application discloses a lithology identification method, comprising: drawing a first spider web diagram based on multiple logging curves; performing standardization and normalization processing on the multiple logging curves to obtain corrected logging curves; performing lithology category division based on lithology grain size, and obtaining a second spider web diagram corresponding to each lithology category based on logging data; determining a lithology division boundary based on the second spider web diagram; and performing lithology identification based on the first spider web diagram, the corrected logging curves and the lithology division boundary. The lithology identification method provided by the embodiment of the application can quickly determine lithology, has high coincidence rate, and solves the problem that it is difficult to achieve fine lithology identification standard by using conventional logging curves when only a small amount of core, slice and logging data are available.

Description

Technical Field

[0001] This application relates to the field of oil and gas exploration and development technology, and in particular to a lithology identification method. Background Technology

[0002] Lithological identification is fundamental to understanding strata and predicting reservoirs. Complex sedimentary rocks exhibit diverse rock types, including high-gamma mudstone, low-gamma mudstone, siltstone, fine sandstone, medium sandstone, and coarse sandstone. However, the logging responses of siltstone and low-gamma mudstone, as well as fine sandstone and medium / coarse sandstone, show little difference, resulting in low identification success rates and potential misjudgments of reservoir fluid properties. Lithological identification has become a key factor restricting effective reservoir exploration and development. Currently, commonly used lithological identification methods are mainly divided into three categories: ① plotting methods, represented by basic experiments; ② cross-plotting and spider web plot methods, represented by statistical classification; ③ mathematical and physical methods, including neural network methods, modular clustering, decision trees, support vector machines, principal component analysis, Fisher's discriminant analysis, and optimization methods.

[0003] The chart method is based on experimental data and establishes a theoretical chart according to the logging response relationship of rocks. This method generally selects 2 to 3 logging parameters, and the lithology identification is inaccurate.

[0004] Cross-plot analysis utilizes cross-plots of well logging curves to analyze the logging characteristics of different lithologies. Generally, a two-dimensional cross-plot method is used. This method is simple to operate, but for complex lithologies, it requires the gradual stripping and combination of multiple two-dimensional cross-plots to achieve identification. However, this is a qualitative identification method and heavily relies on the knowledge and experience of the interpreters. Spider web plot analysis is a method that uses multiple curves to identify lithologies, enabling comprehensive lithological judgment. However, relying solely on the similarity of the shape and angle parameters of the spider web plot for judgment is not ideal for complex lithologies and cannot fully utilize the advantages of the spider web plot.

[0005] Mathematical physics methods use a variety of information to make comprehensive judgments on lithology, especially for the division of thin interbedded and interlayered layers, which has a high resolution. However, the limitations of this method are that it is relatively complex to operate, requires a large number of rock physics experimental samples, the judgment criteria and process are not very intuitive, and it lacks geological understanding. Summary of the Invention

[0006] The present invention aims to solve at least one of the technical problems existing in the prior art or related art.

[0007] In view of this, embodiments of this application propose a lithology identification method, including:

[0008] Based on multiple well logging curves, a first spider web diagram was drawn;

[0009] The various logging curves are standardized and normalized to obtain calibrated logging curves;

[0010] Lithology categories are classified based on lithological grain size, and a second spider web diagram corresponding to each lithology category is obtained based on well logging data;

[0011] Based on the second spider web diagram, the lithological delineation boundary line is determined;

[0012] Lithology identification is performed based on the first spider web diagram, the corrected logging curve, and the lithology division boundary line.

[0013] In one feasible implementation, the step of drawing the first spider web diagram based on multiple well logging curves includes:

[0014] The first spider web diagram was plotted by selecting neutron porosity logging curves, density logging curves, sonic transit time logging curves, natural gamma logging curves, deep resistivity logging curves, and shallow resistivity logging curves.

[0015] In one feasible implementation, the step of standardizing and normalizing the various logging curves to obtain calibrated logging curves includes:

[0016] Select key wells within the identified area and define the standard layers of the key wells;

[0017] Based on the standard layer, all logging curves within the identified area are corrected using the peak method to obtain a benchmark corrected logging curve;

[0018] The benchmark calibration logging curve is normalized to obtain the calibration logging curve.

[0019] In one feasible implementation, the steps of classifying lithology based on lithological grain size and obtaining a second spider web diagram corresponding to each lithology based on well logging data include:

[0020] Based on lithological grain size, lithology is divided into mudstone, fine-grained sandstone, and medium-coarse sandstone;

[0021] Based on known well logging curves and core analysis data, second spider web diagrams were drawn to match the mudstone, fine-grained sandstone, and medium-coarse sandstone types, respectively.

[0022] In one feasible implementation, the step of determining the lithological boundary line based on the second spider web diagram includes:

[0023] Calculate the first area of ​​the geometric figure enclosed by the lines connecting the neutron porosity point, density point, acoustic transit time point and natural gamma point in the second spider web diagram;

[0024] Calculate the first angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep-detection resistivity point in the second spider web diagram;

[0025] Based on the first area, determine the area identification boundary line;

[0026] Based on the first included angle, the included angle identification boundary line is determined.

[0027] In one feasible implementation, the step of calculating the first area of ​​the geometric figure formed by the lines connecting the neutron porosity point, density point, acoustic transit time point, and natural gamma point in the second spider web diagram includes: calculating the first area using the following formula:

[0028]

[0029] Among them, S BCDE1 OC1 is the length of the neutron porosity curve after standardization and normalization, OB1 is the length of the density curve after standardization and normalization, OD1 is the length of the acoustic transit time curve after standardization and normalization, and OE1 is the length of the natural gamma curve after standardization and normalization.

[0030] In one feasible implementation, the step of calculating the first angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep-penetration resistivity point in the second spider web diagram includes:

[0031]

[0032] Where α1 is the first included angle, OA1 is the length of the shallow probe resistivity curve after standardization and normalization, OB1 is the length of the density curve after standardization and normalization, and OC1 is the length of the neutron porosity curve after standardization and normalization.

[0033] In one feasible implementation, the step of lithology identification based on the first spider web diagram, the corrected logging curve, and the lithology demarcation boundary line includes:

[0034] Based on the first spider web diagram and the corrected logging curve, the second area of ​​the geometric figure enclosed by the lines connecting the neutron porosity point, density point, sonic transit time point and natural gamma point in the first spider web diagram is obtained.

[0035] Based on the first spider web diagram and the corrected logging curve, obtain the second included angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep-penetration resistivity point in the first spider web diagram.

[0036] Based on the comparison results between the second area and the area identification boundary line, and the comparison results between the second included angle and the included angle identification boundary line, lithological information is determined.

[0037] In one feasible implementation, the lithology identification method further includes:

[0038] Collect core samples from unknown areas and determine the actual lithology based on the core samples;

[0039] The actual lithology is compared with the lithology identification results to determine the accuracy of the identification.

[0040] In one feasible implementation, if the identification accuracy is lower than a first threshold, a second spider web diagram is redrawn, and the lithological delineation boundary is re-acquired.

[0041] Compared with the prior art, the present invention has at least the following beneficial effects: The identification method provided in this application first draws a first spider web diagram based on multiple well logging curves, which enables more well logging curves to participate in lithology identification and reduces the probability of lithology misjudgment; then, the multiple well logging curves are standardized and normalized to obtain calibrated well logging curves, so that the standardization and normalization of well logging curves of different units and orders of magnitude are conducive to accurate lithology identification in the future; further, lithology categories are classified based on lithological grain size, and a second spider web diagram corresponding to each lithology category is obtained based on well logging data; based on the second spider web diagram, the lithology division boundary line is determined, that is, based on the known lithology information, the second spider web diagrams corresponding to different types of lithology categories are determined, and the lithology division boundary line is determined based on the second spider web diagram; finally, based on the first spider web diagram, the calibrated well logging curves, and the lithology division boundary line, lithology identification is performed, thus completing the accurate identification of lithology. The lithology identification method provided in this application can quickly determine lithology with a high accuracy rate, solving the problem that conventional logging curves are insufficient to achieve precise lithology identification when only a small amount of core, thin section, and logging data are available. Attached Figure Description

[0042] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0043] Figure 1 A schematic flowchart illustrating the steps of a lithology identification method according to an embodiment of this application;

[0044] Figure 2 A schematic diagram of the second spider web diagram for the first embodiment provided in this application;

[0045] Figure 3 A schematic diagram of the second spider web diagram provided in the second embodiment of this application;

[0046] Figure 4 A schematic diagram of the second spider web diagram for the third embodiment provided in this application;

[0047] Figure 5 A schematic diagram of the second spider web diagram for the fourth embodiment provided in this application;

[0048] Figure 6 A schematic diagram of the second spider web diagram for the fifth embodiment provided in this application;

[0049] Figure 7 A schematic diagram of the second spider web diagram for the sixth embodiment provided in this application;

[0050] Figure 8 A schematic diagram of a first spider web diagram provided in one embodiment of this application;

[0051] Figure 9 The image shows the identification effect of a lithology identification method according to an embodiment of this application. Detailed Implementation

[0052] To better understand the above technical solutions, the technical solutions of the embodiments of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this application, rather than limitations on the technical solutions of this application. In the absence of conflict, the embodiments of this application and the technical features in the embodiments can be combined with each other.

[0053] like Figure 1 As shown in the embodiments of this application, a lithology identification method is proposed, including:

[0054] Step 101: Draw the first spider web diagram based on multiple well logging curves. It is understood that drawing the first spider web diagram using multiple well logging curves allows for lithology assessment based on data from various curves, reducing the probability of misjudgment. It is understood that well logging curves with high sensitivity to lithology identification can be selected from among the multiple curves to draw the first spider web diagram, thereby improving the accuracy of lithology identification. It is understood that the first spider web diagram is an example diagram drawn based on well logging curves. By adjusting the position of the well logging curves on the spider web diagram, it is used to discover that the area and angle formed by fixed well logging curves and scales can reflect the grain size of sandstone.

[0055] Step 102: Standardize and normalize multiple logging curves to obtain calibrated logging curves. Standardizing and normalizing multiple logging curves allows logging curves of different units and orders of magnitude to be standardized and normalized, facilitating data comparison and processing.

[0056] Step 103: Classify lithology based on lithological grain size, and obtain the second spider web diagram corresponding to each lithology category based on well logging data. Classifying lithology categories according to lithological grain size enables the lithology identification method provided in this application embodiment to identify the grain size of lithology, facilitating the subsequent determination of reservoir fluid properties based on the lithology identification results, and providing data support for oil and gas development. Obtaining the second spider web diagram corresponding to each lithology category based on well logging data, i.e., drawing the second spider web diagram corresponding to each lithology category based on the explored core samples, facilitates subsequent lithology identification.

[0057] Step 104: Determine the lithological boundary lines based on the second spider web diagram. Each second spider web diagram determines the boundary lines between two adjacent lithological categories, facilitating subsequent lithological identification.

[0058] Step 105: Based on the first spider web diagram, the corrected logging curves, and the lithology demarcation line, lithology identification is performed. By comparing the corrected logging data and the first spider web diagram with the lithology demarcation line, the lithological grain size can be determined. This facilitates the subsequent determination of reservoir fluid properties based on the lithology identification results, providing data support for oil and gas development.

[0059] The identification method provided in this application first draws a first spider web diagram based on multiple well logging curves, enabling more well logging curves to participate in lithology identification and reducing the probability of lithology misjudgment. Then, the multiple well logging curves are standardized and normalized to obtain calibrated well logging curves, making the standardization and normalization of well logging curves of different units and orders of magnitude beneficial for subsequent accurate lithology identification. Further, lithology categories are classified based on lithological grain size, and a second spider web diagram corresponding to each lithology category is obtained based on well logging data. Based on the second spider web diagram, lithology division boundaries are determined; that is, based on known lithology information, the second spider web diagrams corresponding to different types of lithology are determined, and the lithology division boundaries are determined based on the second spider web diagrams. Finally, lithology identification is performed based on the first spider web diagram, the calibrated well logging curves, and the lithology division boundaries, thus completing accurate lithology identification. The lithology identification method provided in this application can quickly determine lithology with a high accuracy rate, solving the problem that it is difficult to achieve precise lithology identification standards using conventional well logging curves when only a small amount of core, thin section, and well logging data is available.

[0060] In some examples, the steps for plotting the first spider web diagram based on multiple well logging curves include:

[0061] The first spider web diagram was plotted by selecting neutron porosity logging curves, density logging curves, sonic transit time logging curves, natural gamma logging curves, deep resistivity logging curves, and shallow resistivity logging curves.

[0062] Subporosity logging curves (NPHI), density logging curves (RHOB), sonic transit time logging curves (DT), natural gamma logging curves (GR), deep resistivity logging curves (LLD), and shallow resistivity logging curves (LLS) are highly correlated with lithology identification. Therefore, drawing the first spider web diagram using the above logging curves can improve the accuracy of lithology identification.

[0063] Understandably, the correlation between logging curves and lithology identification can be determined based on well logging records, well logging data, and lithology descriptions from wellbore core samples. Furthermore, based on the correlation, the selection of sub-porosity logging curves, density logging curves, sonic transit time logging curves, natural gamma logging curves, deep resistivity logging curves, and shallow resistivity logging curves can be used to draw the first spider web diagram.

[0064] Understandably, the second spiderweb diagram represents the spiderweb patterns of six different grain sizes of sandstone at six different depths, based on core analysis. It serves as a typical example, primarily used for classification, grouping the six categories into three. Spiderweb diagrams for the same lithology category may show slight differences in angle and area, indicating that the lithology distribution represents a range. By calculating the spiderweb diagram angles and areas of wells with core analysis, and then statistically analyzing the frequency distribution range of the angle and area histograms for the core segments, the lithological decomposition line is ultimately determined.

[0065] In some examples, the steps for standardizing and normalizing multiple logging curves to obtain calibrated logging curves include: selecting key wells within the identified area and identifying the standard layers of the key wells; based on the standard layers, calibrating all logging curves within the identified area using the peak method to obtain benchmark calibrated logging curves; and normalizing the benchmark calibrated logging curves to obtain calibrated logging curves.

[0066] The selection requirements for key wells are: complete logging items and reliable logging data; core sampling and experimental analysis data of the target formation; and systematic production testing and complete oil (gas) and water analysis data.

[0067] The selection criteria for standard layers are as follows: they should be widely distributed and have stable sedimentation in the target area; they should have obvious lithological and electrical characteristics to facilitate tracking and comparison throughout the area; they should have sufficient stratigraphic thickness, generally 2-5m; mudstone or dense layers are generally selected.

[0068] In some examples, to better identify lithology, fixed values ​​are used for the inner and outer scale ranges of each logging curve, with the NPHI scale ranging from 0.45 to (-0.15), in meters. 3 / m 3 The RHOB scale is 1.85-2.85, and the unit is g / cm³. 3 The DT scale is 140-40, in µs / ft; the GR scale is 150-0, in API; and the LLD and LLS scales are 0.2-2000, in ohms.m. The center of the spider web pattern corresponds to the left scale of the logging curve, and the outer edge corresponds to the right scale. This scale design ensures that higher clay content results in a closer proximity to the center point of the spider web pattern, with smaller corresponding areas and angles.

[0069] In some examples, density logging curves, subporosity logging curves, sonic transit time logging curves, and natural gamma logging curves can be normalized using the following formula:

[0070]

[0071] Where I represents the normalized logging parameter value; I log I represents the response value of the well logging curve. 内 I represents the left scale value corresponding to the logging curve. 外 This represents the right-hand scale value corresponding to the logging curve.

[0072] In some examples, shallow resistivity logging curves can be normalized using the following formula:

[0073]

[0074] Where I represents the normalized logging parameter value; I log I represents the response value of the well logging curve. 内 I represents the left scale value corresponding to the logging curve. 外 This represents the right-hand scale value corresponding to the logging curve.

[0075] This setting facilitates rapid normalization of logging curves and improves the accuracy of normalization, making it easier to accurately identify lithology.

[0076] In some examples, the steps of classifying lithology based on lithological grain size and obtaining a second spider web diagram corresponding to each lithological category based on well logging data include: classifying lithology into mudstone, fine-grained sandstone, and medium-coarse sandstone based on lithological grain size; and drawing a second spider web diagram matching mudstone, fine-grained sandstone, and medium-coarse sandstone based on known well logging curves and core analysis data.

[0077] The lithology is classified into mudstone, fine-grained sandstone, and medium-coarse sandstone by grain size classification. This classification of lithology into three levels facilitates lithology classification and improves identification efficiency. Furthermore, by characterizing lithology with three grain sizes, reservoir fluid properties can be determined based on the lithology identification results, avoiding the impact of overly detailed lithology classification on identification efficiency.

[0078] like Figures 2 to 7 As shown, spiderweb patterns of high-gamma mudstone, low-gamma mudstone, siltstone, fine sandstone, medium sandstone, and coarse sandstone are displayed respectively. It can be seen that... Figure 2 and Figure 3 The areas of the spider web diagrams are quite similar. Figure 4 and Figure 5 The areas of the spider web diagrams are quite similar. Figure 6 and Figure 7 The spider web map areas are relatively similar, so the six total lithologies can be divided into three levels, and the reservoir fluid properties can be determined through these three levels.

[0079] In some examples, the steps for determining lithological demarcation boundaries based on the second spider web diagram include: calculating the first area of ​​the geometric figure enclosed by the lines connecting the neutron porosity point, density point, sonic transit time point, and natural gamma point in the second spider web diagram; calculating the first angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep resistivity point in the second spider web diagram; determining the area identification boundary based on the first area; and determining the angle identification boundary based on the first angle.

[0080] Using the first area and the first included angle as the lithological boundary line can quickly determine the lithology with a high accuracy rate. This solves the problem that conventional logging curves are difficult to use to accurately identify lithological standards when there is only a small amount of core, thin section and logging data.

[0081] In some examples, in addition to obtaining the area identification boundary based on the first area, core grain size analysis data can also be used to draw an area frequency histogram to determine the area identification boundary.

[0082] In some examples, when obtaining the angle identification boundary based on the first included angle, core grain size analysis data can also be used to draw an angle frequency histogram to determine the angle identification boundary.

[0083] In some examples, the step of calculating the first area of ​​the geometry enclosed by the lines connecting the neutron porosity point, density point, acoustic transit time point, and natural gamma point in the second spider web diagram includes: obtaining the first area by calculating the following formula:

[0084]

[0085] Among them, S BCDE1 OC1 is the length of the neutron porosity curve after standardization and normalization, OB1 is the length of the density curve after standardization and normalization, OD1 is the length of the acoustic transit time curve after standardization and normalization, and OE1 is the length of the natural gamma curve after standardization and normalization.

[0086] By selecting the above formula, the first area can be quickly calculated, which facilitates the determination of the area identification boundary line.

[0087] In some examples, the steps for calculating the first angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep-penetration resistivity point in the second spider web diagram include:

[0088]

[0089] Where α1 is the first included angle, OA1 is the length of the shallow probe resistivity curve after standardization and normalization, OB1 is the length of the density curve after standardization and normalization, and OC1 is the length of the neutron porosity curve after standardization and normalization.

[0090] By selecting the above formula, the second included angle can be quickly obtained, which facilitates the determination of the dividing line for angle identification.

[0091] like Figure 8 As shown, in some examples, the steps for lithology identification based on the first spider web diagram, the calibrated logging curve, and the lithology demarcation boundary line include: obtaining the second area of ​​the geometric figure enclosed by the lines connecting the neutron porosity point, density point, sonic transit time point, and natural gamma point in the first spider web diagram, based on the first spider web diagram and the calibrated logging curve; obtaining the second angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep resistivity point in the first spider web diagram, based on the first spider web diagram and the calibrated logging curve; and determining the lithology information based on the comparison results of the second area and the area identification boundary line, and the comparison results of the second angle and the angle identification boundary line.

[0092] Based on the corrected data, the second area and the second included angle of the first spider web diagram are obtained. Then, by comparing the second area and the second included angle with the area identification boundary line and the included angle identification boundary line respectively, the lithological information of the reservoir to be analyzed can be obtained, which can improve the efficiency of lithological identification.

[0093] Understandably, by calculating the area and angle curves of the entire well section point by point according to the depth sequence, the lithology can be identified based on the area and angle boundary lines of the three types of lithology.

[0094] In some examples, the step of obtaining the second area of ​​the geometric figure enclosed by the lines connecting the neutron porosity points, density points, sonic transit time points, and natural gamma points in the first spider web diagram, based on the first spider web diagram and the calibrated logging curve, includes:

[0095]

[0096] Among them, S BCDE2 The first and second areas are defined by the same formula. OC2 represents the length of the neutron porosity curve after standardization and normalization, OB2 represents the length of the density curve after standardization and normalization, OD2 represents the length of the sonic transit time curve after standardization and normalization, and OE2 represents the length of the natural gamma curve after standardization and normalization. Calculating the first and second areas using the same formula ensures the reliability of the angle obtained, facilitating accurate lithological determination.

[0097] In some examples, the steps of obtaining the second included angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep probe resistivity point in the first spider web diagram include:

[0098]

[0099] Where α2 is the second included angle, OA2 is the length of the shallow probe resistivity curve after standardization and normalization, OB2 is the length of the density curve after standardization and normalization, and OC2 is the length of the neutron porosity curve after standardization and normalization. Using the same formula to calculate the first and second included angles ensures the reliability of the angle acquisition and facilitates accurate lithology determination.

[0100] In one feasible implementation, the lithology identification method further includes: collecting core samples from an unknown area, determining the actual lithology based on the core samples, and comparing the actual lithology with the lithology identification results to determine the identification accuracy.

[0101] It is understandable that by collecting core samples to determine the actual lithology, and then comparing them with the lithology identification results identified by the lithology identification method provided in this application embodiment, the accuracy of the lithology identification method provided in this application embodiment can be determined, and the lithology identification method can be verified.

[0102] In some examples, if the identification accuracy is below the first threshold, a second spider web diagram is redrawn and the lithological delineation boundary is re-acquired.

[0103] If the identification accuracy is lower than the first threshold, it indicates that the accuracy of the lithology identification method is low. In this case, the second spider web diagram can be redrawn and the lithology division boundary line can be re-acquired to improve the detection accuracy.

[0104] In some examples, the lithology identification method provided in this application does not rely on the absolute value of logging curves to classify lithology, but rather uses the relative value of logging curves. It plots the sensitive curves in a spider web diagram according to a fixed scale and order, quantitatively calculates the angles and areas between the sensitive curves, and defines lithology identification standards. This solves the problems of complex logging responses and difficulty in identifying lithology in silty sandstone reservoirs. The optimized angles and areas are calculated point-by-point using the spider web diagram of sensitive logging curves, achieving quantitative lithology analysis of non-cored well sections. For example... Figure 9 As shown, where Figure 9 The fifth curve is the area curve; the sixth curve is the angle curve; the seventh curve, the Core_Lith curve, represents the lithology results from core grain size analysis, and the Pre_Lith curve represents the predicted lithology results. Through processing and analysis of six cored wells in a certain area, the lithology identification method provided in this application achieved an automatic lithology identification accuracy of 90.1%. This method is easy to operate, has high lithology identification accuracy, and meets the needs of reserve submission and oilfield exploration and development in the study area.

[0105] In this invention, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance; the term "multiple" refers to two or more unless otherwise explicitly defined. The terms "install," "connect," "link," and "fix" should be interpreted broadly. For example, "connect" can be a fixed connection, a detachable connection, or an integral connection; "link" can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0106] In the description of this invention, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or unit referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0107] In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0108] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A lithology identification method, characterized in that, include: Based on multiple well logging curves, a first spider web diagram was drawn; The various logging curves are standardized and normalized to obtain calibrated logging curves; Lithology categories are classified based on lithological grain size, and a second spider web diagram corresponding to each lithology category is obtained based on well logging data; Calculate the first area of ​​the geometric figure enclosed by the lines connecting the neutron porosity point, density point, acoustic transit time point and natural gamma point in the second spider web diagram; Calculate the first angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep-detection resistivity point in the second spider web diagram; Based on the first area, determine the area identification boundary line; Based on the first included angle, determine the included angle identification boundary line; Based on the first spider web diagram and the corrected logging curve, the second area of ​​the geometric figure enclosed by the lines connecting the neutron porosity point, density point, sonic transit time point and natural gamma point in the first spider web diagram is obtained. Based on the first spider web diagram and the corrected logging curve, obtain the second included angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep-penetration resistivity point in the first spider web diagram. Based on the comparison results between the second area and the area identification boundary line, and the comparison results between the second included angle and the included angle identification boundary line, lithological information is determined; The first area is obtained by calculating the following formula: Among them, S BCDE1 OC1 is the length of the neutron porosity curve after standardization and normalization, OB1 is the length of the density curve after standardization and normalization, OD1 is the length of the acoustic transit time curve after standardization and normalization, and OE1 is the length of the natural gamma curve after standardization and normalization. The step of calculating the first angle between the first line connecting the density point and the neutron porosity point and the second line connecting the density point and the deep-penetration resistivity point in the second spider web diagram includes: Where α1 is the first included angle, OA1 is the length of the shallow probe resistivity curve after standardization and normalization, OB1 is the length of the density curve after standardization and normalization, and OC1 is the length of the neutron porosity curve after standardization and normalization.

2. The lithology identification method according to claim 1, characterized in that, The steps for drawing the first spider web diagram based on multiple well logging curves include: The first spider web diagram was plotted by selecting neutron porosity logging curves, density logging curves, sonic transit time logging curves, natural gamma logging curves, deep resistivity logging curves, and shallow resistivity logging curves.

3. The lithology identification method according to claim 1, characterized in that, The step of standardizing and normalizing the various logging curves to obtain calibrated logging curves includes: Select key wells within the identified area and define the standard layers of the key wells; Based on the standard layer, all logging curves within the identified area are corrected using the peak method to obtain a benchmark corrected logging curve; The benchmark calibration logging curve is normalized to obtain the calibration logging curve.

4. The lithology identification method according to claim 2, characterized in that, The steps of classifying lithology based on lithological grain size and obtaining the second spider web diagram corresponding to each lithology based on well logging data include: Based on lithological grain size, lithology is divided into mudstone, fine-grained sandstone, and medium-coarse sandstone; Based on known well logging curves and core analysis data, second spider web diagrams were drawn to match the mudstone, fine-grained sandstone, and medium-coarse sandstone types, respectively.

5. The lithological identification method according to any one of claims 1 to 4, characterized in that, Also includes: Collect core samples from unknown areas and determine the actual lithology based on the core samples; The actual lithology is compared with the lithology identification results to determine the accuracy of the identification.

6. The lithology identification method according to claim 5, characterized in that, If the identification accuracy is lower than the first threshold, a second spider web diagram is redrawn, and the lithological boundary line is re-acquired.

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