Mutual cutting method-based logging layering interpretation conclusion accurate comparison method and related system

Abstract

The invention provides a logging layering interpretation conclusion accurate comparison method based on a mutual cutting method and a related system, and belongs to the technical field of logging data processing in oil exploration and development. The method comprises the following steps: for two versions of hierarchical interpretation conclusion sets of a well, mutually cutting according to top depth and bottom depth, splitting original interpretation layer sections into comparable layer sections, then enabling the comparable layer sections to form comparable layer section groups in a one-to-one correspondence manner, and judging whether the comparable layer section groups are equal or not through comparison of a depth domain and a conclusion domain; and counting and summarizing comparison conclusions of all the comparable layer section groups to form a complete difference comparison result of the well. Through automatic cutting and comparison processes, the method can be added into an existing processing and explaining process very easily, and the difference between explaining results of different versions can be obtained quickly, so that the multi-well comprehensive research period is shortened; especially for the conditions of a large number of wells, a large number of oil reservoirs and a large number of interpretation layer sections, the comparison work efficiency can be remarkably improved, and artificial introduction of extra errors is avoided.

Description

Technical Field

[0001] This invention belongs to the field of well logging data processing technology in petroleum exploration and development, specifically involving a method and related system for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method. Background Technology

[0002] Data collected by logging instruments along the wellbore, such as natural gamma ray, resistivity, sonic transit time, and rock density, must undergo processing and interpretation to generate parameters like porosity, saturation, and permeability, as well as conclusions regarding lithology, oil, gas, and water layers. Only then can these data be used for reserve calculations, reservoir modeling, and development planning. Layered interpretation conclusions are one of the main outcomes of well logging interpretation. Each well has multiple layers, each consisting of a top depth, a bottom depth, and interpretation conclusions. Interpretation conclusions can be of various types, such as lithology, reservoir classification, and oil-water conclusions.

[0003] Well logging data from different stages of exploration and development undergoes multiple rounds of processing and interpretation, resulting in different versions of interpretation results. Each version contains differences, manifesting in aspects such as depth, layer thickness, and interpretation conclusions. Accurately understanding the location and frequency of these differences, the total extent of the differences, and the causes are crucial for assessing the accuracy and reliability of the interpretation results and for understanding their impact on subsequent research.

[0004] Generally, two versions of interpretation conclusions cannot be directly compared because the backgrounds of well logging data processing and interpretation differ, including the level of understanding of the formation and reservoir, the richness of well logging, core, and oil testing data, and the accuracy of interpretation models and parameters. Therefore, although the interpretation conclusions are generally similar, there are significant differences in details. The main difference lies in the intersecting relationship between the depths of the layers, which are not completely equal. Although it can be roughly seen that some layers correspond, there are still differences between their top and bottom depths, making it impossible to perform a simple and direct quantitative comparison. A method needs to be invented to automatically complete the quantitative comparison.

[0005] The methods or technologies in existing publicly available patent materials mainly focus on the problem of automatic layer division, and pay less attention to the problem of automatic comparison of interpretation conclusions: (1) CN104793263A: Automatically stratify multiple logging curves based on their variation characteristics and boundary conditions; obtain representative values ​​of each curve layer by layer according to the curve shape; and automatically evaluate the formation properties based on the obtained values ​​and the discrimination criteria. (2) CN109670539A: Sandstone stratification is performed using deep belief neural network (DBN). Based on four types of logging data (natural gamma, density, sonic, and neutron) from a well, the mudstone and sandstone at the corresponding locations can be determined. The output of the output layer neurons can only be infinitely close to 1 and 0. The lithological label of the mudstone and sandstone stratification is a floating-point data in the range of [0,1]. The size indicates the degree of membership of the mudstone and sandstone layers, which can more accurately represent its lithological characteristics. (3) CN112784980A: Intelligent well logging layer division is realized by using a neural network layer division model. It can quickly and accurately perform intelligent layer division in the well logging processing and interpretation process, thereby improving the layering efficiency. (4) CN116975669A: By utilizing well logging curves to construct geological description invariant features to effectively mine inter-well multi-curve invariant correlation information, and then, with the support of invariant features, a hierarchical energy-constrained unsupervised integrated clustering region growth model is designed, so as to realize the automatic hierarchical layering of reservoir fine description for industrial application needs. (5) CN118191946A: An automated layering method for logging curves based on principal component self-organizing neural network method, which achieves the purpose of reducing sample dimension, improving operating efficiency and lithological interpretation accuracy; (6) CN118148629A: By automatically matching the relationship of logging response curves, the correspondence between the formation depth of this well and the depth of adjacent wells is obtained, and the reservoir division result of this well is generated based on the depth correspondence and the reservoir division result of adjacent wells, thereby reducing the dependence on human experience and quickly generating the reservoir division result of this well.

[0006] On the other hand, existing well logging data processing and interpretation software all provide layered data management and automatic layering functions: (1) The LEAD software (Yu Chunhao, 2005; Qi Xiaobo, 2006; Zhou Jun, 2010; Yu Chunhao, 2011) provides functions such as tabular data management and generating oil and gas conclusions; (2) CIFLog software (Zhang Liyan, 2011; Chen Chun, 2011; Li Ning, 2013; Li Ning, 2021) provides functions such as table record block group storage, table data management, and automatic layering; (3) Techlog software (https: / / www.slb.com / products-and-services / delivering-digital-at-scale / software / techlog-wellbore-software / techlog) provides functions such as hierarchical data management (Zone editor module) and automatic stratification (Summaries module); (4) Geolog (https: / / www.aspentech.com / en / products / sse / aspen-geolog) provides functions such as hierarchical data management (text module) and automatic stratification (Pay Summary module).

[0007] However, these software programs lack readily available tools or functions to support automated comparison of the differences between the interpretation conclusions of two versions. In practice, interpreters often use spreadsheet tools such as Excel to complete this task manually. Because the differences between layers involve complex relationships such as vertical displacement, intersection, and one-to-many inclusion, layer segmentation is required before comparison. When there are many wells, reservoirs, and interpretation layers, this work becomes very inefficient and prone to errors. What could have been a precise comparison degenerates into a semi-qualitative statistical task, and the results can often only serve as a general comparative reference, achieving only a "rough" level of accuracy. Summary of the Invention

[0008] The purpose of this invention is to overcome the problem that the interpretation conclusions of the two versions differ greatly due to the different backgrounds of well logging data processing and interpretation, making it impossible to conduct simple and direct quantitative comparison and automated comparison. This invention provides a method and related system for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for accurately comparing well logging layer interpretation conclusions based on the mutual cutting method, comprising the following steps: Obtain the hierarchical interpretation conclusion sets of two versions of well logging, using one hierarchical interpretation conclusion set as the left set and the other as the right set; The left set is cut based on the right set to form a comparable left set; The right set is cut using a comparable left set to form a comparable right set; Based on the comparable left set and the comparable right set, a comparable segment group is constructed to form a comparable layered interpretation conclusion set; Perform a comparison operation on each comparable segment group in the comparable stratified interpretation conclusion set to form a comparison conclusion; Based on the comparative conclusions, the number and thickness of the explanatory conclusions of the comparable left set and the comparable right set are summarized and statistically analyzed to form a complete comparison of the differences between the two versions of the hierarchical explanatory conclusion sets.

[0010] In the step of obtaining the hierarchical interpretation conclusion set of two versions of well logging, the hierarchical interpretation conclusion set includes several interpretation segment groups, and each interpretation segment includes two major categories of attribute data: depth domain and conclusion domain.

[0011] The depth domain includes three attributes: top depth, bottom depth, and thickness of the layer, with the bottom depth being greater than the top depth; the conclusion domain includes one or more of the following attributes: lithology, reservoir classification, and oil, gas, and water conclusion.

[0012] Two interpretation segments are constructed as a comparable segment group if and only if their depth domains are completely equal.

[0013] Two explanatory segments are considered equal if they are comparable segments and have the same conclusion domain; otherwise, they are considered unequal.

[0014] The specific steps for cutting the left set from the right set are as follows: for each interpretation segment in the left set, determine the positional relationship between the interpretation segment in the left set and the corresponding interpretation segment in the right set; cut the interpretation segment in the left set according to the interpretation segment in the right set; split out the comparable segments; the conclusion domain of the comparable segments is completely consistent with the interpretation segment in the right set; and construct the comparable left set from the comparable segments.

[0015] The positional relationships between the left set interpretation segment and the corresponding right set interpretation segment are: equal, intersecting at the top, intersecting at the bottom, not intersecting at the top, not intersecting at the bottom, contained or contained.

[0016] The specific steps for cutting the right set from the comparable left set are as follows: for each interpretation segment in the right set, determine the positional relationship between the right set interpretation segment and the corresponding interpretation segment in the comparable left set; cut the right set interpretation segment according to the comparable left set to separate the comparable segment; the conclusion domain of the comparable segment is completely consistent with the interpretation segment of the comparable left set; and construct the comparable right set from the comparable segment.

[0017] The specific steps for constructing a comparable segment group based on the comparable left set and the comparable right set are as follows: the top and bottom boundaries of the interpretation segments in the comparable left set and the comparable right set are completely aligned with each other. The comparable segments in the two sets are combined to construct a comparable segment group, forming a comparable hierarchical interpretation conclusion set.

[0018] The conclusion of the comparison is as follows: (1) Left increase / right decrease: There are comparable segments in the left concentration but not in the right concentration; (2) Right increase / left decrease: There are comparable segments in the right concentration but not in the left concentration; (3) Equal: The conclusion domains of the comparable segments of the left and right sets are completely equal; (4) Inequality: The conclusion domains of the comparable segments of the left set and the right set are not completely equal.

[0019] Secondly, the present invention provides a precise comparison system for well logging layer interpretation conclusions based on the mutual cutting method, comprising: The hierarchical interpretation conclusion loading module is used to obtain two versions of hierarchical interpretation conclusion sets from well logging, with one hierarchical interpretation conclusion set as the left set and the other as the right set; The first mutual cutting method application module is used to cut the left set with reference to the right set to obtain a comparable left set; The second mutual cutting method application module is used to cut the right set with reference to the comparable left set to obtain the comparable right set; The comparison and analysis module is used to construct a set of comparable segments based on the comparable left set and the comparable right set, and to obtain a set of comparable hierarchical interpretation conclusions. The summary module is used to summarize and statistically analyze the comparative stratified interpretation conclusion sets, forming a complete comparison of the differences between the two versions of the stratified interpretation conclusion sets.

[0020] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method.

[0021] Fourthly, the present invention provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method for accurately comparing well logging layer interpretation conclusions based on the mutual cutting method.

[0022] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a precise comparison method and system for well logging layered interpretation conclusions based on the mutual cutting method. The steps are as follows: S1: Define two versions of well logging layered interpretation conclusion sets as a left set and a right set, respectively; S2: Cut the left set with reference to the right set to form a comparable left set; S3: Cut the right set with the comparable left set to form a comparable right set; S4: Construct comparable segment groups based on the comparable left and right sets to form a comparable layered interpretation conclusion set; S5: Perform a comparison operation on each comparable segment group in the comparable layered interpretation conclusion set to form a comparison conclusion; S6: Summarize and statistically analyze the comparable left and right sets, counting the number of layers and thickness according to the comparison conclusion to form a complete difference comparison result between the two versions of the layered interpretation conclusion set. This invention, through automated cutting and comparison processes, can be easily integrated into existing processing and interpretation workflows, quickly obtaining differences between different versions of interpretation results, thereby shortening the multi-well comprehensive study cycle; especially for situations with a large number of wells, reservoir sets, and interpretation segments, it can significantly improve the efficiency of comparison work and avoid introducing additional errors by humans.

[0023] Furthermore, by accurately comparing the hierarchical interpretation conclusion sets, subtle differences between different versions of the interpretation results can be identified, increasing the transparency of well logging interpretation results. By analyzing the possible causes of these differences in data acquisition, data possession, geological understanding, and well logging processing and interpretation, we can guide further improvements in well logging interpretation work, reduce interpretation deviations caused by human factors, and thus enhance the accuracy and reliability of well logging interpretation results.

[0024] Furthermore, different versions of interpretation results may come from different stages, different professions, different teams, or different interpretation software. By accurately comparing the differences in interpretation results, we can effectively identify and correct differences and errors in the interpretation process, improve the consistency of interpretation results from different versions, and enable them to be understood and applied by experts in different fields. This will promote cooperation among professionals from different backgrounds to jointly solve complex geological and reservoir problems. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the process of the present invention.

[0027] Figure 2 This is a schematic diagram of the system structure of the present invention; Figure 3 This provides a hierarchical explanation of the conclusion set data structure and a graphical representation.

[0028] Figure 4 This diagram illustrates the positional relationships between the layers.

[0029] Figure 5 This diagram illustrates the changes in the left and right sets at different stages.

[0030] Figure 6 This is a schematic diagram of the data structure for a comparative, hierarchical interpretation of the conclusion set.

[0031] Figure 7 This is a statistical diagram illustrating the differences in the conclusion set for stratified interpretation.

[0032] Figure 8 This is the set of conclusions for comparative layered interpretation of well X-1.

[0033] Figure 9 A summary statistical table of the differences in the stratified interpretation conclusions of well X-1.

[0034] Figure 10This is a schematic diagram of the system in Example 5. Detailed Implementation

[0035] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0036] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0037] Example 1: like Figure 1 As shown, a method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method includes the following steps: S1: Define the two versions of well logging's hierarchical interpretation conclusion sets as the left set and the right set, respectively; S2: Cut the left set with reference to the right set (referred to as right-cut left) to form a comparable left set; S3: The left set can be compared to the right set to form a comparable right set; S4: Based on the comparable left set and the comparable right set, construct a comparable segment group to form a comparable hierarchical interpretation conclusion set; S5: Perform a comparison operation on each comparable segment group in the comparable stratified interpretation conclusion set to form a comparison conclusion; S6: Summarize and statistically analyze the comparable left set and the comparable right set, and statistically analyze the number of layers and thickness according to the comparison conclusions to form a complete difference comparison result of the two versions of the hierarchical interpretation conclusion set.

[0038] Specifically, S1 defines the result of well logging data after processing and interpretation as a layered interpretation conclusion set, which consists of multiple interpretation segments. Each interpretation segment comprises two main categories of attribute data: depth domain and conclusion domain. The depth domain includes three attributes: top depth, bottom depth, and thickness (the first two are referred to as top and bottom boundaries), with the bottom depth being greater than the top depth. The conclusion domain includes attributes such as lithology, reservoir classification, and oil, gas, and water conclusions. A conclusion domain can have a single attribute, such as an oil, gas, and water conclusion, or it can have multiple attributes simultaneously, such as reservoir classification and oil, gas, and water conclusions. Two interpretation segments can be compared if and only if their depth domains are completely equal, i.e., their top and bottom depths are completely equal. In this case, these two segments are called comparable segments. Two interpretation segments are equal if they are comparable segments and their conclusion domains are equal; otherwise, they are unequal.

[0039] Specifically, in S2, the left set is cut based on the right set (referred to as right-to-left cutting). The interpretive segments in the left set are split into comparable segments, and the resulting left set is called the comparable left set. For each interpretive segment in the left set, the following operations are performed: 2.1: Determine the positional relationship between the left set interpretation segment and the corresponding right set interpretation segment, including seven relationships: equal, top intersection, bottom intersection, top non-intersection, bottom non-intersection, contained, and contained. 2.2: The decision to cut is based on the positional relationship. For cases where there is intersection, such as top intersection, bottom intersection, or inclusion, the left set interpretation segment is cut using the top or bottom of the right set interpretation segment to separate comparable segments. The conclusion domain of the comparable segments is completely consistent with the original interpretation segment. For cases where there is no intersection, such as equality, top non-intersection, bottom non-intersection, or inclusion, no splitting is required, and the original left set interpretation segment is directly regarded as a comparable segment. 2.3: After all interpretation segments of the left set have been operated on, a comparable left set is constructed, in which each segment has been aligned with the top or bottom boundary of the corresponding segment of the right set, and there is no intersection relationship.

[0040] Specifically, S3, referring to the comparable left set constructed by S2, cuts the right set (referred to as left-to-right cut), splitting the interpretive segments in the right set into comparable segments. The resulting right set is called the comparable right set. For each interpretive segment in the comparable left set, the following operations are performed: 3.1: Determine the positional relationship between the right set's interpretation segment and the corresponding interpretation segment of the comparable left set, including seven relationships: equal, top intersection, bottom intersection, top non-intersection, bottom non-intersection, contained, and contained. 3.2: Determine whether to cut based on positional relationships. For cases where there is intersection, such as top intersection, bottom intersection, or inclusion, use the top or bottom of the comparable left set interpretation segment to cut the right set interpretation segment, splitting it into comparable segments. The conclusion domain of the comparable segments remains completely consistent with the original interpretation segment. For cases where there is no intersection, such as equality, top non-intersection, bottom non-intersection, or inclusion, no splitting is required, and the original right set interpretation segment is directly regarded as a comparable segment. 3.3: After all interpretation segments of the right set have been operated on, a comparable right set is constructed, in which each segment has been aligned with the top or bottom boundary of the corresponding segment of the comparable left set, and there is no intersection relationship.

[0041] Specifically, the top and bottom boundaries of the segments in the comparable left set and the comparable right set in S4 are completely aligned with each other. By combining the comparable segments in the two sets, a comparable segment group is constructed, and the resulting set is called the comparable layered interpretation conclusion set (or simply comparable set).

[0042] Specifically, in S5, a comparison operation is performed on each group of comparable layers in the comparable set. Since the depth domains are already completely equal, only the conclusion domains need to be compared, resulting in four possible comparison conclusions: (1) Left increase / right decrease: There are comparable segments in the left concentration but not in the right concentration; (2) Right increase / left decrease: There are comparable segments in the right concentration but not in the left concentration; (3) Equal: The conclusion domains of the comparable segments of the left and right sets are completely equal; (4) Inequality: The conclusion domains of the comparable segments of the left set and the right set are not completely equal.

[0043] Example 2: like Figure 2 As shown, a precise comparison system for well logging layer interpretation conclusions based on the mutual cutting method includes: The hierarchical interpretation conclusion loading module is used to obtain two versions of hierarchical interpretation conclusion sets from well logging, with one hierarchical interpretation conclusion set as the left set and the other as the right set; The first mutual cutting method application module is used to cut the left set with reference to the right set to obtain a comparable left set; The second mutual cutting method application module is used to cut the right set with reference to the comparable left set to obtain the comparable right set; The comparison and analysis module is used to construct a set of comparable segments based on the comparable left set and the comparable right set, and to obtain a set of comparable hierarchical interpretation conclusions. The summary module is used to summarize and statistically analyze the comparative stratified interpretation conclusion sets, generating a complete comparison of the differences between the two versions of the stratified interpretation conclusion sets. The report can include various formats such as charts, graphs, and statistical analysis results to meet different user needs.

[0044] Example 3: like Figure 3 As shown, a schematic diagram of a hierarchical interpretation conclusion set data is presented. It consists of three interpretation segments. Each interpretation segment includes well name, depth domain attributes, conclusion domain attributes, and other attributes. The depth domain attributes include the top depth, bottom depth, and thickness of the segment. The conclusion domain attributes include lithology, reservoir classification, oil, gas, and water conclusions, etc. Figure 3 The right side is a graphical representation of the set of interpretation conclusions for this layered interpretation. The three interpretation layers are displayed sequentially from top to bottom, according to the well depth from shallow to deep.

[0045] (2) When the left set is cut by reference to the right set, there are 7 possible positional relationships between the left set interpretation segment (referred to as the left segment) and the corresponding right set interpretation segment (right segment): equal, top intersection, bottom intersection, top non-intersection, bottom non-intersection, contained, and contained. See Figure 4 : ① Equal ( Figure 4a): The top and bottom boundaries of the left layer are completely equal to those of the right layer, meaning that the left layer can be directly regarded as a comparable layer. ② Intersection at the top ( Figure 4 b): The top boundary of the left segment is shallower than the top boundary of the right segment, and the bottom boundary of the left segment is located between the top and bottom boundaries of the right segment. In this case, the left segment needs to be divided into two comparable segments, and the division depth point is the top boundary of the right segment. ③ The bottoms intersect ( Figure 4 c): The top boundary of the left segment is located between the top and bottom boundaries of the right segment. The bottom boundary of the left segment is deeper than the bottom boundary of the right segment. In this case, the left segment needs to be divided into two comparable segments, and the division depth point is the bottom boundary of the right segment. ④ The tops do not intersect ( Figure 4 d): The bottom boundary of the left layer is shallower than the top boundary of the right layer, meaning that the left layer is entirely above the right layer and the two do not intersect. In this case, the left layer is directly regarded as a comparable layer. ⑤ The bottoms do not intersect ( Figure 4 e): The top boundary of the left layer is deeper than the bottom boundary of the right layer, meaning that the left layer is entirely below the right layer and the two do not intersect. In this case, the left layer is directly regarded as a comparable layer. ⑥ Contains ( Figure 4 f): The top boundary of the left layer is deeper than the top boundary of the right layer, and the bottom boundary of the left layer is shallower than the bottom boundary of the right layer. In other words, the left layer is completely surrounded by the right layer. This left layer does not need to be split and can be directly regarded as a comparable layer. ⑦ Includes ( Figure 4 g): The top boundary of the left segment is shallower than the top boundary of the right segment, and the bottom boundary of the left segment is deeper than the bottom boundary of the right segment. In other words, the left segment completely contains the right segment. This left segment needs to be divided into three comparable segments, with the division depth points being the top and bottom boundaries of the right segment, respectively.

[0046] (3) Changes in the left and right sets at different stages, such as Figure 5 As shown: Initial stage ( Figure 5 a): The left set consists of 7 interpretation segments, and the right set consists of 6 interpretation segments; Right cut left ( Figure 5 b): The left set is cut according to the original right set. After the left set is cut, it consists of 15 comparable segments. Among them, the initial interpretation segments 1, 2, and 5 do not need to be further split. The initial interpretation segment 3 is split into two comparable segments (comparable segments 3 and 4) according to the top intersection relationship. The initial interpretation segment 4 is split into three comparable segments (comparable segments 5, 6, and 7) according to the top intersection and bottom intersection relationships respectively. The initial interpretation segment 6 is split into two comparable segments (comparable segments 9 and 10) according to the bottom intersection relationship. The initial interpretation segment 7 is split into five comparable segments (comparable segments 11 to 15) according to two inclusion relationships respectively. After the cutting is completed, the left set is called the comparable left set. Cut left and right ( Figure 5 c): The right set is cut from the comparable left set. After the right set is cut, it consists of 12 comparable segments. The initial interpretation segments 1, 4, 5, and 6 do not need to be further split. The initial interpretation segment 2 is split into 3 comparable segments (comparable segments 2, 3, and 4) according to the bottom intersection and top intersection relationships respectively. The initial interpretation segment 3 is split into 5 comparable segments (comparable segments 5-9) according to the bottom intersection, inclusion, and top intersection relationships respectively. After the cutting is completed, the right set is called the comparable right set. Construct comparable sets ( Figure 5 d): The top and bottom boundaries of the segments in the comparable left and right sets are completely aligned. By combining the comparable segments from both sets, comparable segment groups are constructed. There are a total of 19 segment groups, and the resulting set is called the comparable layer interpretation conclusion set, or simply the comparable set. Considering only whether the depth domains of the comparable layers in the left and right sets are equal, the comparison conclusions of each segment group fall into three categories: equal / unequal (meaning that comparable segments exist in both the left and right sets, but the conclusion domains are not compared first), left-increase (the left set has comparable segments but the right set does not), and right-increase (the right set has comparable segments but the left set does not).

[0047] (4) Figure 6 The table presents an example of a comparable set, showing four comparable stratigraphic groups. The comparison is based on the oil, gas, and water conclusion domains. The first group shows an increase on the left / decrease on the right, with an oil layer only in the left set. The second group shows equality, with corresponding oil layers in both the left and right sets. The third group shows an increase on the right / decrease on the left, with an oil layer only in the right set. The fourth group shows inequality, with one layer in both the left and right sets, but the left set contains a water layer while the right set contains both oil and water; therefore, the comparison conclusion is inequality.

[0048] (5) Figure 7 This is an example of the statistical results of a comparable set. Based on the comparison conclusions, the number of layers and thickness are summarized for the comparable set, so that the differences between the two versions of the interpretation conclusions can be clearly understood.

[0049] Example 4: like Figure 8 As shown, taking well X-1 in a certain oilfield as an example, this paper presents a comparison of the two complete versions of the stratified interpretation conclusion set.

[0050] (1) There are 60 comparable segment groups in the comparison set, of which there are 40 initial interpretation layers in the left set and 45 initial interpretation layers in the right set. The layer number encoding rules for the comparable segments formed after the split are as follows: (a) If the original interpretation layer does not need to be split, the layer number remains unchanged; (b) If the original interpretation layer needs to be split, the layer number of the comparable segment after the split is [original interpretation layer number] - [comparable segment number after split]. For example, the layer number of the left set comparison segment corresponding to the 17th comparable segment is 13-1. This layer is the first comparable segment split from the 13th initial interpretation layer of the left set.

[0051] (2) For example Figure 9 As shown, the interpretation conclusions are divided into five types: oil layer, poor oil layer, oil-water co-containment layer, water layer, and dry layer. Furthermore, based on the interpretation conclusions and comparative conclusions, [the following is a list of categories / types of layers]. Figure 7 By summarizing and statistically analyzing the comparable sets, detailed statistical differences can be obtained. For the two versions of the stratified interpretation conclusion sets of well X-1, there are 33 equal layers, totaling 100.68 meters; 12 layers are unequal to the left set, totaling 10.08 meters; and 12 layers are unequal to the right set, totaling 10.08 meters. Compared to the right set, the left set adds 4 layers, totaling 2.64 meters; and the right set adds 11 layers, totaling 9.63 meters. Specifically: ① Among the equal stratigraphic intervals, there are 26 oil layers, totaling 77.44 meters (comparable interval groups 1, 3, 4, 5, 6, 7, 12, 13, 20, 22, 26, 27, 29, 33, 35, 36, 38, 39, 40, 42, 43, 45, 46, 48, 49, and 50), only 1 poor oil layer, totaling 1 meter (comparable interval group 9), only 1 oil-water co-existing layer, totaling 5.64 meters (comparable interval group 52), 3 water layers, totaling 15.8 meters (comparable interval groups 55, 59, and 60), and 2 dry layers, totaling 0.8 meters (comparable interval groups 57 and 58). ② In the segments that are not equal to the left set, there are 8 oil layers with a total length of 8.42 meters, 3 poor oil layers with a total length of 1.4 meters (the 10th, 11th and 18th comparable segments), and only 1 oil-water co-containment layer with a total length of 0.26 meters (the 53rd comparable segment). ③ Among the segments not equal to those in the right set, there are 3 oil layers totaling 1.4 meters (comparable segments 10, 11, and 18), 7 poor oil layers totaling 8.3 meters, only 1 oil-water co-containment layer totaling 0.12 meters (comparable segment 51), and only 1 water layer totaling 0.26 meters (comparable segment 53). Comparing the segments not equal to those in the left and right sets, it can be found that the poor oil layers in the 10th, 11th, and 18th comparable segments in the left set are interpreted as oil layers in the right set, and the oil-water co-containment layer in the 53rd comparable segment in the left set is interpreted as a water layer in the right set. ④ Among the newly added sections in Zuoji, there are 3 oil layers with a total length of 2.04 meters (the 25th, 32nd, and 41st comparable sections), and only 12 poor oil layers with a total length of 0.6 meters (the 17th comparable section). ⑤ Among the newly added sections in the right section, there are 8 oil layers with a total length of 7.84 meters (comparable sections 2, 14, 15, 16, 19, 21, 23, and 28), only 1 poor oil layer with a total length of 0.52 meters (comparable section 31), and 2 water layers with a total length of 1.27 meters (comparable sections 54 and 56).

[0052] By precisely comparing and analyzing the hierarchical interpretation conclusion sets, we can accurately identify the differences between different versions of interpretation results. This comparison is not limited to direct comparison at the result level, but delves into every key aspect of the interpretation process, including the accuracy of data acquisition, the comprehensiveness of data possession, the depth of geological understanding, and the rationality of well logging processing and interpretation methods. This guides us to further improve well logging interpretation work. This not only helps improve the accuracy and reliability of well logging interpretation results, but also promotes technological progress and development in the entire oil and gas exploration and development field. At the same time, this continuous improvement and optimization of well logging interpretation work will provide more solid technical support and guarantee for the sustainable development and utilization of oil and gas resources.

[0053] Example 5: like Figure 10 As shown, the present invention also provides an electronic device 100 for a precise comparison method of well logging layer interpretation conclusions based on the mutual cutting method; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0054] The memory 101 can be used to store the computer program 103. The processor 102 implements the steps of the precise comparison method for well logging layer interpretation conclusions based on the mutual cutting method described in Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0055] The at least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor. The processor 102 is the control center of the electronic device 100, connecting various parts of the electronic device 100 via various interfaces and lines.

[0056] The memory 101 in the electronic device 100 stores multiple instructions to implement a method for accurately comparing well logging layer interpretation conclusions using the mutual cutting method. The processor 102 can execute the multiple instructions to achieve the following: Obtain the hierarchical interpretation conclusion sets of two versions of well logging, using one hierarchical interpretation conclusion set as the left set and the other as the right set; The left set is cut based on the right set to form a comparable left set; The right set is cut using a comparable left set to form a comparable right set; Based on the comparable left set and the comparable right set, a comparable segment group is constructed to form a comparable layered interpretation conclusion set; Perform a comparison operation on each comparable segment group in the comparable stratified interpretation conclusion set to form a comparison conclusion; Based on the comparative conclusions, the number and thickness of the explanatory conclusions of the comparable left set and the comparable right set are summarized and statistically analyzed to form a complete comparison of the differences between the two versions of the hierarchical explanatory conclusion sets.

[0057] Example 6: If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0058] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0060] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] Finally, it should be noted that the above embodiments only describe the basic principles, main features, and advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects. The scope of the present invention is defined by the appended claims rather than the foregoing description, and therefore all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0062] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method, characterized in that, Includes the following steps: Obtain the hierarchical interpretation conclusion sets of two versions of well logging, using one hierarchical interpretation conclusion set as the left set and the other as the right set; The left set is cut based on the right set to form a comparable left set; The right set is cut using a comparable left set to form a comparable right set; Based on the comparable left set and the comparable right set, a comparable segment group is constructed to form a comparable layered interpretation conclusion set; Perform a comparison operation on each comparable segment group in the comparable stratified interpretation conclusion set to form a comparison conclusion; Based on the comparative conclusions, the number and thickness of the explanatory conclusions of the comparable left set and the comparable right set are summarized and statistically analyzed to form a complete comparison of the differences between the two versions of the hierarchical explanatory conclusion sets.

2. The method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 1, characterized in that, In the step of obtaining the hierarchical interpretation conclusion set of two versions of well logging, the hierarchical interpretation conclusion set includes several interpretation segment groups, and each interpretation segment includes two major categories of attribute data: depth domain and conclusion domain.

3. The method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 2, characterized in that, The depth domain includes three attributes: top depth, bottom depth, and thickness of the layer, with the bottom depth being greater than the top depth; the conclusion domain includes one or more of the following attributes: lithology, reservoir classification, and oil, gas, and water conclusion.

4. The method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 2, characterized in that, Two interpretation segments are constructed as a comparable segment group if and only if their depth domains are completely equal.

5. The method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 4, characterized in that, Two explanatory segments are considered equal if they are comparable segments and have the same conclusion domain; otherwise, they are considered unequal.

6. The method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 2, characterized in that, The specific steps for cutting the left set from the right set are as follows: for each interpretation segment in the left set, determine the positional relationship between the interpretation segment in the left set and the corresponding interpretation segment in the right set; cut the interpretation segment in the left set according to the interpretation segment in the right set; split out the comparable segments; the conclusion domain of the comparable segments is completely consistent with the interpretation segment in the right set; and construct the comparable left set from the comparable segments.

7. A method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 6, characterized in that, The positional relationships between the left set interpretation segment and the corresponding right set interpretation segment are: equal, intersecting at the top, intersecting at the bottom, not intersecting at the top, not intersecting at the bottom, contained or contained.

8. The method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 6, characterized in that, The specific steps for cutting the right set from the comparable left set are as follows: for each interpretation segment in the right set, determine the positional relationship between the right set interpretation segment and the corresponding interpretation segment in the comparable left set; cut the right set interpretation segment according to the comparable left set to separate the comparable segment; the conclusion domain of the comparable segment is completely consistent with the interpretation segment of the comparable left set; and construct the comparable right set from the comparable segment.

9. A method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 6 or 8, characterized in that, The specific steps for constructing a comparable segment group based on the comparable left set and the comparable right set are as follows: the top and bottom boundaries of the interpretation segments in the comparable left set and the comparable right set are completely aligned with each other. The comparable segments in the two sets are combined to construct a comparable segment group, forming a comparable hierarchical interpretation conclusion set.

10. A method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method according to claim 1, characterized in that, The conclusion of the comparison is as follows: (1) Left increase / right decrease: There are comparable segments in the left concentration but not in the right concentration; (2) Right increase / left decrease: There are comparable segments in the right concentration but not in the left concentration; (3) Equal: The conclusion domains of the comparable segments of the left and right sets are completely equal; (4) Inequality: The conclusion domains of the comparable segments of the left set and the right set are not completely equal.

11. A precise comparison system for well logging layered interpretation conclusions based on the mutual cutting method, characterized in that, include: The hierarchical interpretation conclusion loading module is used to obtain two versions of hierarchical interpretation conclusion sets from well logging, with one hierarchical interpretation conclusion set as the left set and the other as the right set; The first mutual cutting method application module is used to cut the left set with reference to the right set to obtain a comparable left set; The second mutual cutting method application module is used to cut the right set with reference to the comparable left set to obtain the comparable right set; The comparison and analysis module is used to construct a set of comparable segments based on the comparable left set and the comparable right set, and to obtain a set of comparable hierarchical interpretation conclusions. The summary module is used to summarize and statistically analyze the comparative stratified interpretation conclusion sets, forming a complete comparison of the differences between the two versions of the stratified interpretation conclusion sets.

12. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for accurate comparison of well logging layer interpretation conclusions based on the mutual cutting method as described in any one of claims 1 to 10.

13. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for accurately comparing the logging layer interpretation conclusions based on the mutual cutting method as described in any one of claims 1 to 10.

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