A method for quickly identifying formation position based on element logging

Abstract

The present application relates to oil and gas field shale gas exploration and development technical field, disclose a kind of formation position fast identification method based on element logging, comprising the following steps: step 1, collection adjacent well element analysis data;Step 2, calculate and generate adjacent well element characteristic curve;Step 3, based on the element characteristic curve identification feature point;Step 4, establish the corresponding relationship model of feature point and target formation;Step 5, real-time acquisition of positive drilling element analysis data and generate element characteristic curve;Step 6, through well section comparison positive drilling and adjacent well element characteristic curve form;According to feature point matching result determines the formation position where positive drilling bit is located.The present application can identify the formation position where drilling bit is located in real time and accurately, reduce the useless footage of drilling, avoid to wear bottom and over-target front distance and other problems, effectively assist well trajectory adjustment, improve box drilling rate.

Description

Technical Field

[0001] This invention relates to the field of shale gas exploration and development technology in oil and gas fields, specifically to a method for rapid identification of formation locations based on elemental logging. Background Technology

[0002] In shale gas horizontal well development, accurately identifying the real-time formation location of the drill bit is a prerequisite for achieving precise geological guidance and ensuring that the wellbore trajectory always lies within the optimal target layer (such as the high-quality shale section of the Longmaxi Formation). Precise guidance of the target layer directly affects single-well production, reservoir encounter rate, ultimate recovery rate, and overall development economic benefits.

[0003] However, due to the unique drilling environment of horizontal wells, where the drill bit is far from the vertical reference well, and given that the Longmaxi Formation is the main producing layer with strong lateral homogeneity in its shale mineral composition, traditional methods relying on surface geological models and physical logging curves such as gamma / resistivity during drilling for formation correlation suffer from significantly reduced resolution and reliability in areas where lateral lithological variations within the target layer are minimal. In actual operations, especially during the critical target entry (landing) and horizontal section drilling stages of horizontal wells, the inability to accurately identify landmark stratigraphic interfaces or specific strata in real time frequently leads to accidents such as "bottom penetration" (the drill bit prematurely penetrates the bottom of the target layer and enters a non-target formation) or "overshoot" (the drill bit fails to reach the predetermined target layer depth). Actual positioning errors generally exceed 20 meters, resulting in ineffective footage, project delays, and increased costs.

[0004] While current elemental logging technology, by analyzing the elemental content of rock cuttings, theoretically improves the accuracy of lithology identification compared to traditional logging techniques, it still has significant limitations in its application to marine organic-rich shale formations such as the Longmaxi Formation.

[0005] First, the Longmaxi Formation shale is generally homogeneous in its mineral composition, with very small gradients in the content of key minerals (such as quartz and clay) in the lateral direction (along the strike of the strata). This results in highly similar and weakened conventional drilling gamma and resistivity curves, lacking obvious "marker layer" characteristics. Correspondingly, the response curves of single elements lack obvious stratigraphic indicativeness (showing a highly homogenized trend in the vertical sequence of strata), and lack clear, stable, and cross-well comparable peak or abrupt change characteristics, making it difficult to serve as a reliable stratigraphic indicator.

[0006] Secondly, existing methods rely on engineers' experience to compare lithology with adjacent wells, resulting in insufficient real-time positioning capabilities. At the same time, the over-reliance on subjective experience leads to poor consistency and large errors in the judgment results, resulting in a persistently high target error rate in horizontal wells.

[0007] Third, traditional elemental logging interpretation often requires cross-well comparison analysis using complete logging data from adjacent wells. This analysis has a significant time lag and cannot provide timely and effective data support for real-time trajectory adjustments during horizontal well drilling. These limitations prevent current technologies from supporting rapid and accurate determination of formation location. Summary of the Invention

[0008] The present invention aims to provide a rapid formation location identification method based on elemental logging, which solves the technical problem that existing technologies cannot accurately determine the formation location of the drill bit for formations with small variations in lithological characteristics. It can identify the formation location of the drill bit in real time and accurately, and assist in on-site geological guidance construction.

[0009] The basic solution provided by this invention is: a method for rapid identification of formation location based on elemental logging, comprising the following steps:

[0010] Step 1: Collect elemental analysis data from adjacent wells;

[0011] Step 2: Calculate and generate elemental characteristic curves for adjacent wells;

[0012] Step 3: Identify feature points based on the element feature curves;

[0013] Step 4: Establish a correspondence model between feature points and target strata;

[0014] Step 5: Collect elemental analysis data of the drilling operation in real time and generate elemental characteristic curves;

[0015] Step 6: Compare the elemental characteristic curves of the drilling well and adjacent wells through the well profile; determine the formation location of the drilling bit based on the characteristic point matching results.

[0016] Furthermore, the elemental analysis data includes: calcium content data, silicon content data, aluminum content data, sulfur content data, titanium content data, manganese content data, and zirconium content data.

[0017] Furthermore, the elemental characteristic curves include:

[0018] Characteristic curve 1 = (A+D) / (B+C); Characteristic curve 2 = D / E / F; Characteristic curve 3 = G / C;

[0019] Where A represents the calcium content determined by elemental logging; B represents the silicon content determined by elemental logging; C represents the aluminum content determined by elemental logging; D represents the sulfur content determined by elemental logging; E represents the titanium content determined by elemental logging; F represents the manganese content determined by elemental logging; and G represents the zirconium content determined by elemental logging.

[0020] Furthermore, the feature points include:

[0021] Feature point 1: Feature curve 1 shows a sudden increase in high value and is significantly different from the upper and lower curve data;

[0022] Feature point 2: Feature curve 2 shows a region where mirrored curves intersect;

[0023] Feature point 3: Feature curve 3 shows a sudden increase in high value.

[0024] Furthermore, feature point 1 corresponds to the interface between Longmaxi Formation Long 2 and Long 1; feature point 2 corresponds to Longmaxi Formation ... The lower part of the subsegment; feature point 3 corresponds to the dragon. Lower part of the sub-segment.

[0025] Furthermore, the establishment of the correspondence model in step 4 includes: quantifying the distance between each feature point and the target area. The vertical thickness threshold of the top boundary of the sublayer was determined, and a database of thicknesses in adjacent wells was constructed.

[0026] Furthermore, the well profile comparison in step 6 includes: synchronously displaying the characteristic curves of the drilling well and at least two adjacent wells according to depth coordinates, and determining the formation location by the similarity of curve shape and the offset of characteristic points.

[0027] Furthermore, it also includes step 7, which predicts the vertical thickness of the drill bit from the target layer in real time based on the location of the feature points.

[0028] Furthermore, in steps 1 and 5, after the raw elemental analysis data is collected, it is standardized to eliminate acquisition errors.

[0029] The working principle and advantages of this invention are as follows:

[0030] This invention presents a rapid formation location identification method based on elemental logging, which can identify the formation location of the drill bit in real time and accurately, assisting in on-site geological guidance construction. The key points are:

[0031] First, this scheme effectively solves the real-time positioning problem of shale gas horizontal wells in the Longmaxi Formation by establishing three sets of specific element ratio curves and quantitative feature point identification rules. Firstly, this scheme adopts a multi-element collaborative analysis mode, selecting seven elements—calcium, silicon, aluminum, sulfur, titanium, manganese, and zirconium—to construct composite curves ((Ca+S) / (Si+Al), S / Ti / Mn, Zr / Al), overcoming the weakness of single-element response and significantly improving the ability to distinguish homogeneous lithological formations. Secondly, the three defined feature points have clear mathematical morphological criteria (e.g., sudden high values ​​must be clearly distinguishable from upper and lower curve data, and the area of ​​the intersection region of mirror curves must change from zero to present), forming transferable quantitative discrimination standards and reducing reliance on subjective experience. Finally, through dynamic comparison of well profiles and vertical thickness prediction, real-time calculation of drill bit position is achieved, controlling the formation identification error within 8m and providing minute-level response basis for drilling trajectory adjustment.

[0032] Second, this scheme overcomes the inherent limitations of existing elemental logging applications: Firstly, this scheme proposes for the first time a three-curve linkage identification mechanism. Characteristic curve 1 sensitively captures changes in mineral content to identify segment boundaries; characteristic curve 2 uses sulfur enrichment characteristics to indicate the reducing environmental marker layer; and characteristic curve 3 locates the marine flooding surface based on heavy mineral enrichment. These three can form a complementary discrimination system within the sub-segments of the Longmaxi Formation. Secondly, a dynamic mapping model between characteristic points and geological interfaces is established, linking characteristic point 1 (high-value abrupt change in curve 1) to the Longmaxi Formation 2-Longmaxi Formation interface, and characteristic point 2 (mirror intersection of curve 2) to the Longmaxi Formation 2-Longmaxi Formation interface. In the lower part of the sub-segment, feature point 3 (high value of curve 3) locks in the dragon. At the bottom of the sub-section, a functional leap is achieved from lithological identification to location positioning. Furthermore, the mirror intersection feature, by introducing the mathematical mirror principle into geological curve analysis and replacing single-point numerical judgments with area changes, can transform the subtle ratio fluctuations of characteristic curves into visual geometric figures, thereby enabling the dragon... The sedimentary environment transformation of the sub-section is presented as a binary criterion—the abrupt change in the intersection area from nothing to something can make features that were originally difficult to identify obvious, effectively improve the stratigraphic identification rate, and accurately control the vertical thickness error. Attached Figure Description

[0033] Figure 1 This is a schematic flowchart of an embodiment of a method for rapid identification of formation location based on element logging according to the present invention.

[0034] Figure 2 This is a schematic diagram of the elemental characteristic curves of adjacent wells, representing an application example of a method for rapid formation location identification based on elemental logging according to the present invention.

[0035] Figure 3This is a schematic diagram showing the comparison of the elemental characteristic curves of the drilling wells in an application example of an embodiment of the method for rapid formation location identification based on elemental logging of the present invention.

[0036] Figure 4 This is a schematic diagram of single-element analysis comparison of an embodiment of a rapid formation location identification method based on elemental logging according to the present invention;

[0037] Figure 5 This is a schematic diagram of the first well-to-well comparison of element combination features according to an embodiment of the rapid formation location identification method based on element logging of the present invention.

[0038] Figure 6 This is a schematic diagram of the second well-to-well comparison based on the element combination features of an embodiment of the rapid formation location identification method based on element logging of the present invention.

[0039] in, Figures 2 to 6 Color-coded illustrations are used to facilitate the differentiation of complex curves and lines. Detailed Implementation

[0040] The following detailed explanation illustrates the specific implementation methods:

[0041] The basic implementation examples are as follows: Figure 1 As shown: A method for rapid identification of formation location based on elemental logging, comprising the following steps:

[0042] Step 1: Collect elemental analysis data from adjacent wells; the elemental analysis data includes: calcium content data, silicon content data, aluminum content data, sulfur content data, titanium content data, manganese content data, and zirconium content data.

[0043] Optionally, after the raw elemental analysis data is collected, it is standardized to eliminate acquisition errors.

[0044] Specifically, the standardized processing formula used is as follows: ;

[0045] in, This is the standardized element content data. This is the original elemental content data; It is the average element content of the well section (i.e., the average value of the original data of the element within the same well and target well section). Standard deviation (i.e., the degree of dispersion of raw data within the same well section).

[0046] Step 2: Calculate and generate the elemental characteristic curves of adjacent wells.

[0047] The elemental characteristic curves include:

[0048] Characteristic curve 1 = (A+D) / (B+C); Characteristic curve 2 = D / E / F; Characteristic curve 3 = G / C.

[0049] Where A represents the calcium content determined by elemental logging; B represents the silicon content determined by elemental logging; C represents the aluminum content determined by elemental logging; D represents the sulfur content determined by elemental logging; E represents the titanium content determined by elemental logging; F represents the manganese content determined by elemental logging; and G represents the zirconium content determined by elemental logging. All units are equal.

[0050] Step 3: Identify feature points based on the element feature curve.

[0051] The feature points include:

[0052] Feature 1: Feature curve 1 shows a sudden increase in high value that is significantly different from the data of the upper and lower curves. For example, if the subsequent value of this sudden increase drops to less than 20% to 50% of the high value, it is considered a "significant difference". It should be noted that in practical applications, this criterion can be adjusted adaptively according to the overall fluctuation of feature curve 1.

[0053] Feature point 2: Feature curve 2 exhibits a mirror curve intersection region. Specifically, the mirror curve intersection region refers to the closed geometric region formed between the original curve and the mirror curve after mirroring the original element ratio curve (e.g., S / Ti / Mn) along a baseline (e.g., the Y-axis). Figure 2 As shown.

[0054] Feature point 3: Feature curve 3 shows a sudden increase in high value.

[0055] Step 4: Establish a correspondence model between feature points and target strata.

[0056] In this embodiment, the establishment of the correspondence model includes: quantizing the distance between each feature point. The vertical thickness threshold of the top boundary of the sublayer was determined, and a database of thicknesses in adjacent wells was constructed.

[0057] Step 5: Collect elemental analysis data of the drilling operation in real time and generate three sets of elemental characteristic curves.

[0058] Optionally, after collecting the raw elemental analysis data from the drilling operation, the data can be standardized to eliminate acquisition errors.

[0059] The standardization process is consistent with the standardization described in step 1, and the element characteristic curve is consistent with the form described in step 2.

[0060] Step 6: Compare the elemental characteristic curves of the drilling well and adjacent wells through the well profile; determine the formation location of the drilling bit based on the characteristic point matching results.

[0061] The well profile comparison includes: synchronously displaying the characteristic curves of the main drilling well and at least two adjacent wells according to depth coordinates, and determining the formation location by the similarity of curve shape and the offset of characteristic points.

[0062] For example, with dragon Using the top boundary of the sub-layer as the reference plane and feature point 1 as the alignment anchor point, the curves of adjacent wells are translated by depth. The morphological similarity of feature curve 2 is calculated, and the vertical offset of feature point 3 is calculated.

[0063] Feature point 1 corresponds to the interface between Longmaxi Formation Long 2 and Long 1; feature point 2 corresponds to Longmaxi Formation ... The lower part of the subsegment; feature point 3 corresponds to the dragon. Lower part of the sub-segment.

[0064] Step 7: Predict the vertical thickness of the drill bit from the target layer in real time based on the location of the feature points.

[0065] Specifically, this includes the following sub-steps: Calling feature points of the same type from the adjacent well database to Long... The vertical thickness distribution range of the top boundary of the small layer is used as the basic data; then the vertical thickness is adjusted according to the structural position relationship between the drilling well and adjacent wells; then, based on the adjusted vertical thickness value, the distance of the current feature point of the drilling well to the dragon is predicted. Vertical thickness of the top boundary of the sub-layer.

[0066] To facilitate understanding, an application example is introduced here to illustrate the practical steps of this method:

[0067] Step 1: Collect elemental analysis data from adjacent wells.

[0068] The target well was selected as the drilling well Z201H20-6, and the adjacent wells were selected as follows: Z201H16-1 (well section 4028.00~4500.00m); Z201H8-10 (well section 3924.00~4410.00m).

[0069] The elemental analysis data includes: calcium content data, silicon content data, aluminum content data, sulfur content data, titanium content data, manganese content data, and zirconium content data. The elemental content data was acquired using an X-ray fluorescence logging instrument.

[0070] Step 2: Calculate and generate the elemental characteristic curves of adjacent wells.

[0071] Step 3: Identify feature points based on the element feature curve.

[0072] Step 4: Establish a correspondence model between feature points and target strata.

[0073] like Figure 2As shown, the elemental characteristic curves of the target stratigraphic segments of wells Z201H16-1 (interval 4028.00~4500.00m) and Z201H8-10 (interval 3924.00~4410.00m), after calculation and processing, exhibit three overall characteristics from top to bottom:

[0074] Feature point 1 shows a high value on the (A+D) / (B+C) element characteristic curves of wells Z201H16-1 (well section 4324.00~4338.00m) and Z201H8-10 (well section 4246.00~4254.00m), with the value being greater than 0.35, and the lower data being less than half of the high value data.

[0075] Characteristic point 2 shows no self-mirror intersection of the D / E / F element characteristic curves above 4412.00m in well Z201H16-1 and above 4300.00m in well Z201H8-10, but self-mirror intersection occurs below.

[0076] Feature point 3 shows a high value in the G / C element characteristic curves of wells Z201H16-1 (well section 4430.00~4438.00m) and Z201H8-10 (well section 4330.00~4342.00m).

[0077] Feature point 1 is located between the second segment of the dragon and the dragon. At the sub-segment boundary, feature point 2 is located in the dragon. In the lower part of the subsegment, feature point 3 is located in the dragon. Lower part of the sub-segment.

[0078] The summary is shown in Table 1:

[0079] Table 1. Characteristic curves and characteristic points of adjacent wells

[0080]

[0081] Step 5: Collect elemental analysis data of the drilling operation in real time and generate three sets of elemental characteristic curves;

[0082] Step 6: Compare the elemental characteristic curves of the drilling well and adjacent wells through the well profile; determine the formation location of the drilling bit based on the characteristic point matching results.

[0083] Specifically, the elemental data of the Z201H20-6 well (section 4030.00~4400.00m) was collected through the above steps. After calculation and processing, a well-connected comparison profile was established with the elemental data of the adjacent wells Z201H16-1 (section 4028.00~4500.00m) and Z201H8-10 (section 3924.00~4410.00m).

[0084] like Figure 3 As shown, the comparison revealed that the (A+D) / (B+C) element characteristic curve of well Z201H20-6 showed a high value in the well section from 4204.00 to 4268.00 m; the D / E / F element characteristic curves did not show self-mirror intersection above 4362.00 m, but began to show self-mirror intersection below; the G / C element characteristic curve began to show a high value at 4390.00 m, and the high value has not yet ended.

[0085] Based on these three characteristics, we can analyze the current position of drilling bits in the well. Lower part of the sub-segment.

[0086] The summary is shown in Table 2:

[0087] Table 2 Characteristic curves and characteristic points of active drilling

[0088]

[0089] Step 7: Predict the vertical thickness of the drill bit from the target layer in real time based on the location of the feature points.

[0090] Through this step, we summarize and analyze the characteristic point 1 of the adjacent well Z201H16-1. The vertical thickness of the small roof is 47m, and the feature point 2 is located at the dragon. The vertical thickness of the small roof is 32m, and the characteristic point is 3 meters away from the dragon. The vertical thickness of the top layer is 4m; the characteristic point of well Z201H8-10 is 1 meter away from Long. The vertical thickness of the small roof is 62m, and the feature point 2 is located at the dragon. The vertical thickness of the small roof is 28m, and the characteristic point is 3 meters away from the dragon. The vertical thickness of the small roof is 21m.

[0091] Based on the above data, according to the distance of the third characteristic point of the adjacent well from Long The vertical thickness distribution of the top layer ranges from 26.68 to 31.43 m. Based on the structural location of this well, the distance from the third characteristic point of this well to Long is predicted. The vertical thickness of the small roof is 30.00m.

[0092] Actual measurements confirmed that the distance between the drill bit position and the wellhead, predicted based on feature points, was [missing information]. The difference between the thickness of the sublayer and the actual drilling is 3.78m.

[0093] Furthermore, the established element curve feature model was applied in field experiments on 8 wells, and the drill bit position distance was predicted based on the feature points. The difference between the thickness of the small layer top and the actual drilling is less than 8m, indicating that the element curve characteristic model is reliable.

[0094] This embodiment provides a rapid formation location identification method based on elemental logging, which can identify the formation location of the drill bit in real time and accurately, assisting in on-site geological guidance construction. In particular, this solution effectively solves the problem of real-time positioning of shale gas horizontal wells in the Longmaxi Formation by establishing three sets of specific element ratio curves and quantifying feature point identification rules.

[0095] Specifically, in the stratigraphic identification study of the Longmaxi Formation, this scheme systematically demonstrated the effects of elements from aspects such as reflecting the redox environment, paleoclimate, paleodeep water, and intensity of terrestrial input.

[0096] In the early stages of research and development, the research objective started with single elements, focusing on the Long 2-Long well section within the study area (the Zu 201-Zu 203 well area of ​​the Yuxi Block). (Analysis of elemental characteristics of sub-sections) A detailed analysis of the transformations of 36 elements in 84 wells was conducted (e.g.) Figure 4 As shown in the figure, and in conjunction with the sedimentary environment of the target layer, the sensitive elements Co, As, Pb, Ba, and P were studied in detail. The analysis results show that the curves of each single element are relatively stable overall, with no obvious changes. This proves that although the same element can be used as a sensitive element for multiple sedimentary environments, it still has obvious limitations in judging sedimentary environments and their characteristics based on single elements.

[0097] Furthermore, we conducted verification using multi-element and mineral assemblages, finding that traditional redox indices—such as the ratios of P / S, S / P, S / P / Fe, S / P / Fe / Mn, V / Cr, V / (V+Ni), Ni / Co, and Th / U—showed no significant changes in the target stratigraphic unit. This demonstrates that commonly used indices in existing technologies are ineffective in marine organic-rich shale formations like the Longmaxi Formation.

[0098] Based on this, we comprehensively considered various environmental factors, including redox environment, anoxic environment, reducing environment, paleosalinity, paleoclimate, paleoclimate, paleowater depth, provenance, self-precipitated minerals, paleoproductivity, clay minerals, brittle minerals, and clay-loving minerals, to design a new element combination. Through repeated verification using this multi-element combination, as shown in Table 3, we discovered for the first time that the S / Ti / Mn ratio in Longyan... The sub-section exhibits a universal anomaly (well area visibility of 83%-96.8%), while the Zr / Al ratio can indicate peak terrigenous input in specific well areas. This discovery overturns the traditional understanding of shale gas exploration relying on gamma / resistivity.

[0099] Table 3. Results of combined verification

[0100]

[0101] Furthermore, based on the above findings, this scheme creatively constructs three sets of characteristic curves:

[0102] Characteristic curve 1 = (Ca+S) / (Si+Al): By correlating the phase transitions of carbonate minerals and clay minerals, the lithological transition from Long 2 to Long 1 is accurately captured;

[0103] Characteristic curve 2 = S / Ti / Mn: Utilizing the synergistic effect of sulfur reducing properties and terrigenous transport indicators, a sensitive signal of sedimentary environment is established;

[0104] Characteristic curve 3 = Zr / Al: Using zircon enrichment as an isochronous marker to pinpoint the transgression event surface.

[0105] The three curves form a complementary discrimination system, which solves the industry problem of ambiguous response of single elements or traditional combinations in homogeneous shale.

[0106] Secondly, addressing the challenge of identifying subtle signal variations in characteristic curves (such as the original fluctuations of S / Ti / Mn being only ±0.05, which are difficult to identify), this solution proposes a self-mirror symmetry intersection filling method (corresponding to feature point 2). This method introduces the mathematical mirror principle into geological curve analysis, replacing single-point numerical judgments with area changes. Specifically, the original curve is mirrored along the baseline, and by filling the intersection area between positive and negative curves, subtle ratio fluctuations are transformed into visual geometric figures, thereby enabling the identification of subtle signal variations. The sedimentary environment transition of the sub-section is presented as a binary criterion—the abrupt change in the intersection area from nothing to something can make features that were originally difficult to identify obvious, effectively improving the stratigraphic identification rate and controlling vertical thickness error.

[0107] The above descriptions are merely embodiments of the present invention. Commonly known structures and characteristics of the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent.

Claims

1. A method for rapid formation location identification based on elemental logging, characterized in that, Includes the following steps: Step 1: Collect elemental analysis data from adjacent wells; the elemental analysis data includes: calcium content data, silicon content data, aluminum content data, sulfur content data, titanium content data, manganese content data, and zirconium content data; Step 2: Calculate and generate the elemental characteristic curves of adjacent wells; the elemental characteristic curves include: characteristic curve 1 = (A+D) / (B+C); characteristic curve 2 = D / E / F; characteristic curve 3 = G / C; Where A represents the calcium content determined by elemental logging; B represents the silicon content determined by elemental logging; C represents the aluminum content determined by elemental logging; D represents the sulfur content determined by elemental logging; E represents the titanium content determined by elemental logging; F represents the manganese content determined by elemental logging; and G represents the zirconium content determined by elemental logging. Step 3: Identify feature points based on the element feature curves; the feature points include: Feature point 1: Feature curve 1 shows a sudden increase in high value and is significantly different from the upper and lower curve data; Feature point 2: Feature curve 2 shows a mirror curve intersection region; the mirror curve intersection region specifically refers to: the closed geometric region formed between the original curve and the mirror curve after mirroring the original element ratio curve along the baseline; Feature point 3: Feature curve 3 shows a sudden increase in high value; Step 4: Establish a correspondence model between feature points and target strata; feature point 1 corresponds to the interface between Longmaxi Formation Long 2 and Long 1; feature point 2 corresponds to the middle and lower part of Long 12 sub-member; feature point 3 corresponds to the lower part of Long 12 sub-member. Step 5: Collect elemental analysis data of the drilling operation in real time and generate elemental characteristic curves; Step 6: Compare the elemental characteristic curves of the drilling well and adjacent wells through the well profile; determine the formation location of the drilling bit based on the characteristic point matching results. Step 7: Predict the vertical thickness of the drill bit from the target layer in real time based on the location of the feature points.

2. The method for rapid formation location identification based on elemental logging according to claim 1, characterized in that, The establishment of the correspondence model in step 4 includes: quantizing the distance between each feature point. The vertical thickness threshold of the top boundary of the sublayer was determined, and a database of thicknesses in adjacent wells was constructed.

3. The method for rapid formation location identification based on elemental logging according to claim 1, characterized in that, The well profile comparison in step 6 includes: synchronously displaying the characteristic curves of the drilling well and at least two adjacent wells according to depth coordinates, and determining the formation location by the similarity of curve shape and the offset of characteristic points.

4. The method for rapid formation location identification based on elemental logging according to claim 1, characterized in that, In steps 1 and 5, after the raw elemental analysis data is collected, it is standardized to eliminate acquisition errors.

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