A stratum dip angle intelligent rapid picking method based on natural gamma ray logging response in a horizontal well and related equipment

Abstract

The application discloses a stratum dip angle intelligent rapid picking method based on a natural gamma ray logging response in a horizontal well and related equipment, and the method comprises the following steps: establishing a natural gamma ray logging response curve by simulating logging response characteristics of a horizontal well track entering a stratum at different angles, analyzing the natural gamma ray logging response curve, and obtaining a first mathematical formula for estimating a first stratum interface angle; performing grouping average and sliding average processing on the natural gamma ray logging curve, and determining a stratum interface interval length corresponding to the natural gamma ray logging curve; calculating the first stratum interface angle according to the stratum interface interval length and a spherical detection radius by using the first mathematical formula, and calculating a stratum dip angle according to the first stratum interface angle and a well inclination angle. According to the application, the stratum dip angle can be rapidly calculated and picked up only by relying on the natural gamma ray logging data, and the calculation precision and the calculation efficiency are relatively high. The application can be widely applied to the technical field of stratum exploration or detection.

Description

Technical Field

[0001] This application relates to the field of geological exploration or detection technology, and in particular to a method and related equipment for intelligent and rapid acquisition of formation dip angle based on natural gamma logging response in horizontal wells. Background Technology

[0002] In modern oil and gas exploration, formation dip information, as a crucial parameter reflecting subsurface structures, is essential for improving the efficiency of geological interpretation and resource extraction. Previously, in obtaining formation dip information through gamma-ray logging, conventional gamma-ray logging was typically used as a foundation, employing multiple detectors to acquire azimuth gamma-ray data and inverting geological structures to obtain formation dip information. Combining drilling azimuth gamma-ray data with computer image processing technology could effectively improve the accuracy and efficiency of identifying and calculating formation dip. In recent years, in automated geological guidance systems, existing methods for obtaining formation dip typically include: combining drilling data, conventional inclinometers, and imaging logging to quickly predict and calibrate formation dip; incorporating imaging technology into azimuth logging to improve the efficiency and accuracy of dip acquisition; and using geometric methods to obtain formation dip.

[0003] However, the above methods for measuring formation dip often suffer from high cost and low cost-effectiveness. In practical well logging applications, due to factors such as high expenses, many wells do not undergo azimuth gamma logging or imaging logging, which limits the detailed analysis of the relationship between formation and well trajectory.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose an intelligent and rapid method and related equipment for picking up formation dip angles based on the natural gamma logging response in horizontal wells. By simulating the logging response under different angles and obtaining the mathematical formula for calculating the formation interface angle, and then combining the average processing of the natural gamma logging curve to determine the formation interface interval length, it is possible to achieve rapid calculation and picking of formation dip angles relying solely on natural gamma logging data.

[0006] To achieve the above objectives, one aspect of this application proposes a method for intelligent and rapid formation dip angle acquisition based on natural gamma logging response in horizontal wells, the method comprising:

[0007] The natural gamma logging curve of a horizontal well is obtained by using a natural gamma logging detector, and the well inclination angle corresponding to each logging point of the natural gamma logging curve and the spherical detection radius of the natural gamma logging detector are obtained. By simulating the logging response characteristics of well trajectories entering the formation at different angles, several natural gamma logging response curves are established. By analyzing each of the natural gamma logging response curves, a first mathematical formula is obtained to calculate the angle of the first formation interface based on the length of the formation interface interval and the spherical detection radius. The natural gamma logging curves are sequentially subjected to group averaging and moving average processing to determine the length of the formation interface interval corresponding to the natural gamma logging curves. The first formation interface angle is calculated using the first mathematical formula based on the formation interface interval length and the spherical detection radius, and the formation dip angle is calculated based on the first formation interface angle and the well inclination angle. Wherein, the first formation interface angle is the angle between the well trajectory and the formation interface.

[0008] In some embodiments, establishing several natural gamma logging response curves by simulating the logging response characteristics of well trajectories entering the formation at different angles includes: The simulated probe enters the formation along the simulated well trajectory and passes through the simulated formation interface; Based on the intersection relationship between the spherical detection range of the simulated detector and the simulated formation interface, the gamma ray intensity in different regions within the spherical detection range is calculated to obtain the natural gamma logging response curve.

[0009] In some embodiments, the step of analyzing each of the natural gamma logging response curves to obtain a first mathematical formula for calculating the angle of the first formation interface based on the formation interface interval length and the spherical detection radius includes: Obtain the first and second critical points where the spherical detection range of the simulated detector enters the simulated stratum interface region; The length of the simulated formation interface interval is determined based on the first critical point and the second critical point; Obtain the second formation angle between the simulated well trajectory and the simulated formation interface; The first mathematical formula is determined based on the correspondence between the spherical detection radius, the length of the simulated stratigraphic interface interval, and the second stratigraphic angle.

[0010] In some embodiments, the expression of the first mathematical formula is:

[0011] in, The angle between the first stratum interfaces is... The radius of the spherical detection is [missing information]. The length of the stratigraphic interface interval is given.

[0012] In some embodiments, the step of sequentially performing grouped averaging and moving average processing on the natural gamma logging curves to determine the formation interface interval length corresponding to the natural gamma logging curves includes: The natural gamma logging curves are grouped according to a preset first window number of points, the first arithmetic mean of each group is calculated, and the first arithmetic mean of two adjacent groups is compared. When the difference between the first arithmetic mean of two adjacent groups meets the preset first threshold condition, the first candidate interval is determined according to the corresponding logging point; The natural gamma logging curves are grouped into sliding windows according to a preset step size, and the second arithmetic mean of each sliding window is calculated. The second arithmetic mean of two adjacent sliding windows is then compared. When the difference between the second arithmetic mean of two adjacent sliding windows meets the preset second threshold condition, the second candidate interval is determined according to the corresponding logging point; The length of the formation interface interval is determined based on the first candidate interval and the second candidate interval.

[0013] In some embodiments, calculating the formation dip angle based on the included angle of the first formation interface and the well inclination angle includes: Obtain the geological profile corresponding to the natural gamma logging curve; Determine whether the inclination angle with the well is not greater than 90 degrees; When the well inclination angle is not greater than 90 degrees, the dip angle of the first candidate formation is calculated using the second mathematical formula based on the angle between the first formation interface and the well inclination angle, and it is determined whether the dip angle of the first candidate formation conforms to the geological conditions. When the dip angle of the first candidate stratum conforms to the geological profile, the dip angle of the first candidate stratum is taken as the dip angle of the stratum. When the dip angle of the first candidate formation does not conform to the geological conditions, the dip angle of the second candidate formation is calculated using a third mathematical formula based on the angle between the first formation interfaces and the well inclination angle, and the dip angle of the second candidate formation is taken as the formation dip angle. When the well inclination angle is greater than 90 degrees, the dip angle of the third candidate formation is calculated using the third mathematical formula based on the angle between the first formation interface and the well inclination angle, and it is determined whether the dip angle of the third candidate formation conforms to the geological conditions. When the dip angle of the third candidate stratum conforms to the geological profile, the dip angle of the third candidate stratum shall be taken as the dip angle of the stratum. If the dip angle of the third candidate formation does not conform to the geological conditions, the dip angle of the fourth candidate formation is calculated using a second mathematical formula based on the angle between the first formation interface and the well inclination angle, and the dip angle of the fourth candidate formation is taken as the formation dip angle.

[0014] In some embodiments, the expression of the second mathematical formula is:

[0015] The expression for the third mathematical formula is:

[0016] in, The dip angle of the strata is [insert angle here]. The angle between the first stratum interfaces is... The well inclination angle is denoted as .

[0017] To achieve the above objectives, another aspect of this application proposes an intelligent rapid formation dip acquisition device based on the natural gamma logging response in a horizontal well, the device comprising: The natural gamma logging curve acquisition module is used to acquire the natural gamma logging curve of a horizontal well through a natural gamma logging detector, and to acquire the well inclination angle corresponding to each logging point of the natural gamma logging curve and the spherical detection radius of the natural gamma logging detector. The formation interface angle analysis module is used to establish several natural gamma logging response curves by simulating the logging response characteristics of well trajectories entering the formation at different angles. The module analyzes each of the natural gamma logging response curves to obtain a first mathematical formula for calculating the first formation interface angle based on the formation interface interval length and the spherical detection radius. The formation interface interval length determination module is used to perform group averaging and moving average processing on the natural gamma logging curves in sequence to determine the formation interface interval length corresponding to the natural gamma logging curves. The formation dip angle calculation module is used to calculate the angle between the first formation interfaces based on the length of the formation interface interval and the spherical detection radius using the first mathematical formula, and to calculate the formation dip angle based on the angle between the first formation interfaces and the well inclination angle. Wherein, the first formation interface angle is the angle between the well trajectory and the formation interface.

[0018] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the methods described above.

[0019] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0020] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the methods described above.

[0021] The embodiments of this application include at least the following beneficial effects: This application provides a method and related equipment for intelligent and rapid acquisition of formation dip angle based on natural gamma logging response in horizontal wells. This scheme establishes natural gamma logging response curves by simulating the logging response characteristics of well trajectories entering the formation at different angles, and analyzes the response curves to obtain a mathematical formula for calculating the formation interface angle based on the formation interface interval length and the spherical detection radius. This provides a clear physical basis for determining the formation interface angle, which is beneficial for completing dip angle acquisition without increasing additional logging costs. By sequentially performing group averaging and moving average processing on the natural gamma logging curves to determine the formation interface interval length, the effective extraction of the interface change interval can still be achieved even when there are fluctuations in the logging curves, reducing the workload of manual interpretation, improving processing efficiency, and ensuring the timeliness and practicality of formation dip angle acquisition. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating the steps of a method for intelligent and rapid formation dip angle acquisition based on natural gamma logging response in a horizontal well, as provided in an embodiment of this application. Figure 2 A schematic diagram of the detector-stratum interface as provided in this application embodiment, relative to the lower hemisphere; Figure 3 A schematic diagram showing the intersection of the detector and the formation interface in the upper hemisphere, as provided in an embodiment of this application. Figure 4 The natural gamma logging response curves corresponding to different angles between the simulated well trajectory and the formation interface provided in the embodiments of this application; Figure 5 A schematic diagram of the formation model corresponding to the logging response when the angle between the simulated well trajectory and the formation interface is 10°, as provided in the embodiments of this application. Figure 6 A schematic diagram of the formation model corresponding to the logging response when the angle between the simulated well trajectory and the formation interface is 20°, as provided in the embodiments of this application. Figure 7 A schematic diagram of the formation model corresponding to the logging response when the angle between the simulated well trajectory and the formation interface is 30°, as provided in the embodiments of this application. Figure 8 A schematic diagram of the formation model corresponding to the logging response when the angle between the simulated well trajectory and the formation interface is 40°, as provided in the embodiments of this application. Figure 9 A schematic diagram of the formation model corresponding to the logging response when the angle between the simulated well trajectory and the formation interface is 50°, as provided in the embodiments of this application. Figure 10 A schematic diagram of the formation model corresponding to the logging response when the angle between the simulated well trajectory and the formation interface is 60°, as provided in the embodiments of this application. Figure 11 A schematic diagram of the formation model corresponding to an angle of α° between the well trajectory and the formation interface, provided in an embodiment of this application; Figure 12 A simplified schematic diagram of the formation model corresponding to an angle of α° between the well trajectory and the formation interface, provided in an embodiment of this application. Figure 13 A schematic diagram illustrating the principle of predicting the length of formation interface intervals using the grouped average and moving average methods provided in the embodiments of this application; Figure 14 A schematic diagram of 12 possible formation dip angle calculation models when the horizontal well trajectory and formation interface orientation have different relationships, as provided in the embodiments of this application. Figure 15 A comprehensive result diagram of gamma logging interpretation for a horizontal well in an oilfield, provided in an embodiment of this application; Figure 16 This is a schematic diagram of the structure of an intelligent rapid formation dip angle acquisition device based on the natural gamma logging response in a horizontal well, provided in an embodiment of this application. Figure 17 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0025] The concept of the present invention will now be explained in conjunction with the background art.

[0026] In modern oil and gas exploration, formation dip angle information, as a crucial parameter reflecting subsurface structure, is essential for improving the efficiency of geological interpretation and resource extraction. In the early explorations of the principles and applications of horizontal well formation dip angle determination, researchers established a series of functions between formation dip angle and other formation parameters through Monte Carlo simulation experiments to develop dip angle processing software compatible with various instruments. This laid the physical foundation for subsequent quantitative calculation of formation dip angle using well logging images. Previously, in the problem of obtaining formation dip angle through gamma logging, conventional gamma logging was typically used as a basis, employing multiple detectors to acquire azimuth gamma data and inverting geological structures to obtain formation dip angle information. Combining drilling azimuth gamma data with computer image processing technology can effectively improve the accuracy and efficiency of identifying and calculating formation dip angle. In recent years, research on calculating formation dip angle in automated geological guidance has mainly fallen into three categories: The first category combines logging-while-drilling data, conventional inclinometers, and imaging logging to quickly predict and calibrate formation dip angles. This involves improving and enhancing imaging logging technologies such as electrical imaging and acoustic imaging to increase the accuracy and reliability of formation dip angle calculations. For example, in electrical imaging logging, deep learning-based supervised machine learning models can be used to automatically detect non-sinusoidal bedding features in borehole images and extract formation dip angles from these images. Alternatively, algorithms can be optimized to construct unsupervised neural networks, thereby achieving efficient calculation of formation dip angles.

[0027] The second category involves using azimuth gamma logging technology to obtain dip information, as mentioned above. Imaging techniques can also be combined with azimuth logging to improve the efficiency and accuracy of data acquisition. For example, in azimuth density imaging logging, an electronically controlled X-ray source can replace the traditional Cs-137 source, transforming the thin-layer interface identification problem into a mathematical clustering problem to reduce the root square error of the relative dip angle.

[0028] The third category involves using geometric methods to pick up the dip angle of the strata, such as true thickness direction correction comparison and horizontal segment split comparison.

[0029] However, existing logging technologies that pick up formation dip angles, such as imaging logging, formation dip logging, and azimuth gamma logging, are costly in practical applications and can only be used in horizontal wells with complex formation variations. This limits the detailed analysis of the relationship between formations and well trajectories in many wells. In actual logging applications, due to factors such as high costs, many wells do not undergo azimuth gamma logging or imaging logging, which limits the detailed analysis of the relationship between formations and well trajectories.

[0030] Therefore, it is necessary to develop a natural gamma forward modeling algorithm capable of quickly and accurately picking up formation dip angles. This application provides an intelligent and rapid formation dip angle picking method and related equipment based on the natural gamma logging response in horizontal wells. This algorithm establishes a physical model reflecting the angle between the well trajectory and the formation by simulating the logging response characteristics of the well trajectory entering the formation at different angles. This provides a low-cost and efficient solution for predicting the formation interface interval and quickly picking up the formation dip angle for practical applications. This solution is suitable for logging formation modeling in thin interbedded layers and complex structural areas. It not only facilitates adjusting the drilling trajectory, improves the drilling success rate, and saves costs, but also provides a new approach for real-time prediction of formation dip angles, possessing significant practical value and broad market prospects.

[0031] This application provides an intelligent and rapid formation dip angle acquisition method based on the natural gamma logging response in horizontal wells, relating to the field of information technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the intelligent and rapid formation dip angle acquisition method based on the natural gamma logging response in horizontal wells, but is not limited to the above forms.

[0032] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0033] Figure 1 This is an optional flowchart of a method for intelligent and rapid formation dip angle acquisition based on natural gamma logging response in horizontal wells, provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S101 to S104.

[0034] S101. Obtain the natural gamma logging curve of the horizontal well through the natural gamma logging detector, and obtain the well inclination angle corresponding to each logging point of the natural gamma logging curve and the spherical detection radius of the natural gamma logging detector. S102. By simulating the logging response characteristics of well trajectories entering the formation at different angles, several natural gamma logging response curves are established. Each natural gamma logging response curve is analyzed to obtain the first mathematical formula for calculating the angle between the first formation interfaces based on the length of the formation interface interval and the spherical detection radius. In some embodiments, several natural gamma logging response curves are established by simulating the logging response characteristics of well trajectories entering the formation at different angles, including: S1021. The simulated probe enters the formation along the simulated well trajectory and passes through the simulated formation interface; S1022. Based on the intersection relationship between the spherical detection range of the simulated detector and the simulated formation interface, the gamma ray intensity in different areas within the spherical detection range is calculated to obtain the natural gamma logging response curve.

[0035] In some embodiments, the natural gamma logging response curves are analyzed to obtain a first mathematical formula for calculating the angle of the first formation interface based on the formation interface interval length and the spherical detection radius, including: S1023. Obtain the first and second critical points when the spherical detection range of the simulated detector enters the simulated stratum interface region. S1024. Determine the length of the simulated formation interface interval based on the first critical point and the second critical point; S1025. Obtain the second formation angle between the simulated well trajectory and the simulated formation interface; S1026. Determine the first mathematical formula based on the correspondence between the spherical detection radius, the length of the simulated stratigraphic interface interval, and the second stratigraphic angle.

[0036] In some embodiments, the expression of the first mathematical formula is:

[0037] in, The angle between the first stratigraphic interfaces. For spherical detection radius, This represents the length of the stratigraphic interface interval.

[0038] Specifically, in this embodiment, natural gamma logging curves for horizontal wells are obtained using a natural gamma logging detector. These natural gamma logging curves record the variation of the natural radioactivity intensity of the formation along the well depth, typically reflecting differences in the natural radioactivity levels of the formation surrounding the wellbore and can be used to characterize the variation characteristics of different formation segments. The spherical detection radius is used to characterize the effective detection range of the logging detector. When a horizontal well crosses the formation interface between different formations, the natural gamma logging curves often show changes in amplitude or shape at the corresponding locations.

[0039] Figure 2 and Figure 3 This demonstrates the detection range of a natural gamma-ray logging probe and two scenarios involving its intersection with the formation. When the gamma-ray probe intersects the formation along its well trajectory in the lower hemisphere of the spherical detection range, the gamma-ray intensity of mudstone (shale) within the fan-shaped and conical regions, and the gamma-ray intensity of sandstone (sandstone) within the arc-shaped region, are calculated through integration, corresponding to... Figure 2 The gamma ray intensity in regions A, B, and C can be calculated using the following formula: (1) (2)

[0040] (3) in, , and ( ) respectively represent Figure 2 The gamma ray intensity at point O of the probe in regions A, B, and C within the spherical detection range; the subscripts of parameters a, q, ρ, and μ are used to distinguish between mudstone (subscript 1) and sandstone (subscript 2); ( R( is the angle between the spherical coordinate axis and the detection range;) ) is the spherical detection radius; d( () represents the distance from the center of the spherical detection range to the stratigraphic interface; The formula for the guilloché function is as follows: (4) When the gamma-ray detector intersects the formation along the well trajectory in the upper hemisphere of the spherical detection range, the gamma-ray intensity of mudstone in the fan-shaped and conical regions and the gamma-ray intensity of sandstone in the arc-shaped region are calculated by integration, respectively corresponding to... Figure 3 The gamma ray intensity in regions A, B, and C can be calculated using the following formula: (5) (6) (7) Figure 4 To simulate the different angles between the well trajectory and the formation interface when the probe drills into the formation ( , , , , , The corresponding natural gamma logging response curve is shown on the horizontal axis, which represents the logging depth (cm) and the vertical axis represents the natural gamma (API unit). When the gamma detector enters the mudstone layer from top to bottom along the well trajectory at a certain well inclination angle β, the midpoint of the detector when it coincides with the formation interface is taken as the base point. When the midpoint of the detector on the well trajectory is above the interface, the distance d from the interface is negative and is calculated using equations (1), (2), and (3). When the midpoint of the detector is below the interface, the distance d from the interface is positive and is calculated using equations (5), (6), and (7).

[0041] based on Figure 4 Natural gamma logging response curves at different angles between the well trajectory and the formation interface were used to establish... Figures 5 to 10 The diagram shows a horizontally layered mudstone and sandstone formation model. The distance between points A and B in the formation model represents the distance the probe travels along the well trajectory from mudstone to sandstone, which is the length of the red logging response curve. Circles centered at points A and B, with the probe's travel distance as the radius, are tangent to the formation interface on the upper and lower sides, respectively. It can be seen that as the angle increases, the distance between points A and B gradually decreases. At that time, the two circles were tangent to the formation interface, but since the research object was a horizontal well, a large-angle formation model of the well trajectory and the formation interface was not established.

[0042] To facilitate the calculation of the angle α between the well trajectory and the formation, it is necessary to summarize the calculation formula for the angle α based on the formation model rules corresponding to different logging responses at different angles in step A. In actual measurements, the boundary between the well trajectory and the formation is mostly a curve. If the gamma curve response value changes significantly at a certain logging point, let the two critical points be M and N, the distance between points M and N from the formation interface be R, the distance between points M and N on the well trajectory be ΔS, and the intersection of the well trajectory and the formation interface be at point O. In this case, the angle α between the horizontal well trajectory and the formation interface can be expressed as | | Angle with the stratigraphic interface ( Figure 11Therefore, the formula for calculating the angle α between the horizontal well trajectory and the formation interface is obtained: (8) Where R is the detector's detection radius, and the straight line Let O be the tangent line between the well trajectory and the formation boundary. Considering that the detector's detection radius is much smaller than the well trajectory, assuming the well trajectory and the formation boundary as a straight line will not significantly affect the final calculated formation angle. In this case, the common tangent line of the circular detection ranges at the two critical points M and N is the formation tangent line at point O. Figure 12 Therefore, the optimized formula for calculating the angle α between the well trajectory and the formation interface is obtained as follows: (9) Where ΔS is the straight-line distance between the two critical points M and N; R is the detector radius; and α is the angle between the well trajectory and the formation interface.

[0043] S103. Perform group averaging and moving average processing on the natural gamma logging curves in sequence to determine the length of the formation interface interval corresponding to the natural gamma logging curves. In some embodiments, the natural gamma ray logging curves are sequentially subjected to group averaging and moving average processing to determine the formation interface interval length corresponding to the natural gamma ray logging curves, including: S1031. Group the natural gamma logging curves according to the preset number of first window points, calculate the first arithmetic mean of each group, and compare the first arithmetic mean of adjacent groups. S1032. When the difference between the first arithmetic mean of two adjacent groups meets the preset first threshold condition, the first candidate interval is determined according to the corresponding logging point. S1033. The natural gamma logging curves are grouped into sliding windows according to a preset step size, the second arithmetic mean of each sliding window is calculated, and the second arithmetic mean of two adjacent sliding windows is compared. S1034. When the difference between the second arithmetic mean of two adjacent sliding windows meets the preset second threshold condition, the second candidate interval is determined according to the corresponding logging point. S1035. Determine the length of the stratigraphic interface interval based on the first candidate interval and the second candidate interval.

[0044] Specifically, in S103, the angle between the well trajectory and the formation is predicted using conventional natural gamma. During the process, it is very important to be able to quickly determine the interval of the geological interface in which the detector enters and exits, i.e., ΔS in equation (9). Figure 13This paper presents a method for determining formation interface intervals by combining the grouped averaging method and the moving average method. The processing flow of this method is as follows: First, all gamma logging values ​​on the natural gamma logging curve are grouped into windows of 5 points each, and an arithmetic mean is calculated independently. Let the comparison coefficient of the grouped average of adjacent windows be W1, and the comparison coefficient of the moving average be W2. In this simulation, W1 is selected as 0.1%, and W2 is selected as 0.08%. For the convenience of simulation, Figure 13 The image only shows the path from point A ( ) to point B ( There are 16 groups in total. The green triangles represent the average value of each group. Points (green dots) where the ratio of the average value of the previous group to the average value of the next group is greater than W1 are selected as the initial screening range for the natural gamma detector's entry and exit from the stratigraphic interface. Figure 13 The interval of the x-coordinate from point C to point D [ , Next, for all gamma logging values ​​on the natural gamma logging curve, an arithmetic average is calculated by sliding the values ​​in increments of 9 points, with the interval between adjacent logging points as one step. Figure 13 The red circles represent the average value of each window. Points (red dots) where the ratio of the average value of the previous group to the average value of the next group is greater than W2 are selected as the range of the natural gamma detector entering and exiting the formation interface for secondary screening. Figure 13 The interval of the x-coordinate from point E to point F [ , The final selected interval is [min{ },max{ The length of}], i.e. Figure 13The distance between the x-coordinates of points E and D is the distance ΔS between the two critical points at the formation interface where the detector enters and exits. This simulation represents the process of the well trajectory moving from a high-radioactivity non-reservoir to a low-radioactivity reservoir. Conversely, when comparing the average values ​​of adjacent windows in groups, points with a ratio of the average value of the previous group to the average value of the next group less than (1-W1) should be selected. When comparing the moving average, points with a ratio of the average value of the previous group to the average value of the next group less than (1-W2) should be selected. Both methods can be used simultaneously in practical applications. It should be noted that when using the group averaging method and the moving average method to determine the length of ΔS, the natural gamma logging curve used in the simulation calculation of ΔS is relatively smooth. Although the gamma logging values ​​were verified by adding noise in the data testing section, the "sawtooth" characteristics of the actual logging curve are more obvious when using the group averaging method and the moving average method to determine the length of ΔS. Therefore, when applying this method in practice, it is necessary to increase the comparison coefficients W1 and W2 of the group averaging and moving average methods. It is worth noting that the selection of W1 and W2 can be adjusted from small to large using programming tools until a clear ΔS interval appears. This method can effectively determine the ΔS interval when predicting the dip angle of common horizontal well formations by combining group averaging and moving average. However, in the problem of dip angle prediction at faults, since the relationship between the logging spacing and the ΔS length is not much smaller than that, and even a group averaging window is larger than ΔS, only the moving average method is needed when predicting the dip angle of faults to reduce errors.

[0045] S104. Calculate the first formation interface angle using the first mathematical formula based on the formation interface interval length and the spherical detection radius, and calculate the formation dip angle based on the first formation interface angle and the well inclination angle; wherein, the first formation interface angle is the angle between the well trajectory and the formation interface; In some embodiments, calculating the formation dip angle based on the first formation interface angle and the well inclination angle includes: S1041. Obtain the geological overview corresponding to the natural gamma logging curve; S1042. Determine whether the inclination angle with the well is not greater than 90 degrees; S1043. When the well inclination angle is not greater than 90 degrees, the dip angle of the first candidate formation is calculated using the second mathematical formula based on the angle between the first formation interface and the well inclination angle, and it is determined whether the dip angle of the first candidate formation conforms to the geological conditions. S1044. When the dip angle of the first candidate stratum conforms to the geological profile, the dip angle of the first candidate stratum shall be taken as the stratum dip angle. S1045. When the dip angle of the first candidate formation does not conform to the geological conditions, the dip angle of the second candidate formation is calculated based on the interface angle of the first formation and the well inclination angle using the third mathematical formula, and the dip angle of the second candidate formation is taken as the formation dip angle. S1046. When the well inclination angle is greater than 90 degrees, the dip angle of the third candidate formation is calculated based on the angle between the first formation interface and the well inclination angle using the third mathematical formula, and it is determined whether the dip angle of the third candidate formation conforms to the geological conditions. S1047. When the dip angle of the third candidate stratum conforms to the geological profile, the dip angle of the third candidate stratum shall be taken as the stratum dip angle. S1048. When the dip angle of the third candidate stratum does not conform to the geological profile, the dip angle of the fourth candidate stratum is calculated using the second mathematical formula based on the angle between the first stratum interfaces and the well inclination angle, and the dip angle of the fourth candidate stratum is taken as the stratum dip angle.

[0046] In some embodiments, the expression of the second mathematical formula is:

[0047] The expression for the third mathematical formula is:

[0048] Where θ is the formation dip angle, α is the angle between the first formation interfaces, and β is the well inclination angle.

[0049] Specifically, in this embodiment, in S103, the interval ΔS where the formation interface is located has been determined. This interval can be substituted into Formula 9 to calculate the angle α between the well trajectory and the formation. Next, the formation dip angle θ needs to be calculated based on the well inclination angle β and the angle α between the well trajectory and the formation. When inputting the well inclination angle, if there is a local updip or structural uplift on the top surface of the reservoir, the well trajectory will change its original direction. Therefore, when calculating the formation dip angle, both cases with well inclination angles less than or equal to 90° and greater than 90° are considered. Figure 14 Based on the relationship between the horizontal well trajectory and the formation interface orientation, 12 formation models that may occur during actual gamma logging were established.

[0050] in, Figure 14 (a1)-(c2) is the well inclination angle less than or equal to Stratigraphic model at that time Figure 14 (d1)-(f2) represents the well inclination angle greater than The formation model at that time. The well trajectory and formation interface are divided into two strikes: downward and upward. Let the formation dip angle be θ. ), the well inclination angle is β( The well trajectory makes an angle α with the formation interface. ).exist Figure 14 In (a1) and (a2), the well trajectory is oblique to the formation interface and has the same direction (i.e., Same dip orientations), θ is less than ( The terrain inclination angle θ is calculated using equation (10); Figure 14In (b1) and (b2), the well trajectory intersects the formation interface obliquely and has different orientations (i.e., different dip orientations), θ is less than α, and the topographic dip angle θ is calculated using equation (11); Figure 14 In (c1) and (c2), the well trajectory is oblique to the formation and has the same strike, θ is greater than ( And θ is greater than α, the terrain dip angle θ is calculated using equation (12); Figure 14 In (d1) and (d2), the well trajectory is oblique to the formation interface and has the same strike, θ is less than ( The terrain inclination angle θ is calculated using equation (13); Figure 14 In (e1) and (e2), the well trajectory intersects the formation interface obliquely and has different orientations, θ is less than α, and the topographic dip angle θ is calculated using equation (12); Figure 14 In (f1) and (f2), the well trajectory is oblique to the formation and has the same strike, θ is greater than ( And θ is greater than α, the terrain inclination angle θ is calculated using formula (11).

[0051] (10) (11) (12) (13) Based on the calculation rules of the dip angle of the 12 formation models above, the formulas for calculating the topographic dip angle θ are summarized as Equation (14) and Equation (15), and the calculation process of the dip angle of the formation when the well trajectory intersects the formation interface is established: First, determine whether the well inclination angle is less than or equal to If the well inclination angle is less than or equal to θ is calculated using equation (14), and then it is confirmed whether it conforms to the geological conditions. If it does, θ can be output directly; otherwise, equation (15) needs to be used to calculate θ. If the well inclination angle is greater than θ is calculated using equation (15), and then it is confirmed whether it conforms to the geological conditions. If it does, θ can be output directly; otherwise, equation (14) needs to be used to calculate θ.

[0052] (14) (15) It should be noted that when using this method to pick up the formation dip angle θ, two angles can be calculated for the same logging point according to equations (14) and (15). One of these angles is obviously inconsistent with the actual geological conditions. It is also possible to combine the gamma logging interpretation results map to determine whether the geological conditions at the formation interface are consistent. Figure 7 Which model is used, and when the well inclination angle is less than or equal to When (a1)-(b2) are common types, it is more reasonable to use equation (14) to initially determine the formation dip angle; when the well inclination angle is greater than When (d1)-(e2) is the common type, it is more reasonable to use formula (15) to initially determine the dip angle of the strata.

[0053] The present invention will be further described below with reference to a specific embodiment: In this embodiment, the method is applied to Figure 15 In a gamma logging example of a horizontal well in an oilfield, good prediction results were achieved. Even when the well trajectory in area B in the figure changed direction when drilling into the formation interface, the formation dip angle could still be picked up quickly and accurately.

[0054] It can be recognized that this embodiment can predict the angle between the well trajectory and the formation based on the physical model of the angle between the well trajectory and the formation; predict the interval where the formation interface is located by the group averaging and moving average methods; predict the formation dip angle based on 12 possible formation models when the horizontal well trajectory intersects the formation interface obliquely; and verify through the application example of natural gamma logging in horizontal wells that this method has a certain degree of accuracy and reliability.

[0055] Furthermore, compared with other logging techniques for predicting formation dip angles, such as azimuth gamma logging, formation dip logging, and imaging logging, this embodiment offers more significant economic benefits and lower costs. Compared to other logging techniques for predicting formation dip angles, this embodiment demonstrates higher accuracy in picking up dip angles. Simultaneously, this embodiment is applicable to various thin interbedded and complex structural formations, possessing broad practical value. Moreover, the calculation process of the model in this embodiment is based on existing geological and logging data, making it easy to operate and implement.

[0056] Please see Figure 16 This application also provides an intelligent rapid formation dip acquisition device based on the natural gamma logging response in a horizontal well, which can implement the above-mentioned method. The device includes: The Natural Gamma Logging Curve Acquisition Module is used to acquire the natural gamma logging curve of a horizontal well through a natural gamma logging detector, and to acquire the well inclination angle corresponding to each logging point of the natural gamma logging curve and the spherical detection radius of the natural gamma logging detector. The formation interface angle analysis module is used to establish several natural gamma logging response curves by simulating the logging response characteristics of well trajectories entering the formation at different angles. By analyzing each natural gamma logging response curve, a first mathematical formula is obtained to calculate the first formation interface angle based on the formation interface interval length and the spherical detection radius. The formation interface interval length determination module is used to perform group averaging and moving average processing on the natural gamma logging curves in sequence to determine the formation interface interval length corresponding to the natural gamma logging curves. The formation dip angle calculation module is used to calculate the first formation interface angle based on the formation interface interval length and the spherical probe radius using a first mathematical formula, and to calculate the formation dip angle based on the first formation interface angle and the well inclination angle. The first formation interface angle is the angle between the well trajectory and the formation interface.

[0057] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0058] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0059] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0060] Please see Figure 17 , Figure 17 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the methods described in the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0061] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0062] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0063] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0064] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0065] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0066] This application provides an intelligent and rapid method and related equipment for obtaining formation dip angles based on the natural gamma logging response in horizontal wells. The method establishes natural gamma logging response curves by simulating the logging response characteristics of well trajectories entering the formation at different angles. Analysis of these curves yields a mathematical formula for calculating the formation interface angle based on the formation interface interval length and the spherical detection radius. This provides a clear physical basis for determining the formation interface angle, facilitating dip angle acquisition without increasing logging costs. Furthermore, by sequentially performing grouped averaging and moving average processing on the natural gamma logging curves, the formation interface interval length is determined. This allows for effective extraction of interface variation intervals even when logging curves fluctuate, reducing manual interpretation workload, improving processing efficiency, and ensuring the timeliness and practicality of formation dip angle acquisition.

[0067] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0068] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0069] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0070] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0071] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0072] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0073] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0074] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0075] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0076] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0077] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for intelligent and rapid formation dip angle acquisition based on natural gamma logging response in horizontal wells, characterized in that, include: The natural gamma logging curve of a horizontal well is obtained by using a natural gamma logging detector, and the well inclination angle corresponding to each logging point of the natural gamma logging curve and the spherical detection radius of the natural gamma logging detector are obtained. By simulating the logging response characteristics of well trajectories entering the formation at different angles, several natural gamma logging response curves are established. By analyzing each of the natural gamma logging response curves, a first mathematical formula is obtained to calculate the angle of the first formation interface based on the length of the formation interface interval and the spherical detection radius. The natural gamma logging curves are sequentially subjected to group averaging and moving average processing to determine the length of the formation interface interval corresponding to the natural gamma logging curves. The first formation interface angle is calculated using the first mathematical formula based on the formation interface interval length and the spherical detection radius, and the formation dip angle is calculated based on the first formation interface angle and the well inclination angle. Wherein, the first formation interface angle is the angle between the well trajectory and the formation interface; The calculation of the formation dip angle based on the included angle of the first formation interface and the well inclination angle includes: Obtain the geological profile corresponding to the natural gamma logging curve; Determine whether the inclination angle with the well is not greater than 90 degrees; When the well inclination angle is not greater than 90 degrees, the dip angle of the first candidate formation is calculated using the second mathematical formula based on the angle between the first formation interface and the well inclination angle, and it is determined whether the dip angle of the first candidate formation conforms to the geological conditions. When the dip angle of the first candidate stratum conforms to the geological profile, the dip angle of the first candidate stratum is taken as the dip angle of the stratum. When the dip angle of the first candidate formation does not conform to the geological conditions, the dip angle of the second candidate formation is calculated using a third mathematical formula based on the angle between the first formation interfaces and the well inclination angle, and the dip angle of the second candidate formation is taken as the formation dip angle. When the well inclination angle is greater than 90 degrees, the dip angle of the third candidate formation is calculated using the third mathematical formula based on the angle between the first formation interface and the well inclination angle, and it is determined whether the dip angle of the third candidate formation conforms to the geological conditions. If the dip angle of the third candidate stratum conforms to the geological profile, the dip angle of the third candidate stratum shall be taken as the dip angle of the stratum. When the dip angle of the third candidate formation does not conform to the geological conditions, the dip angle of the fourth candidate formation is calculated using the second mathematical formula based on the angle between the first formation interface and the well inclination angle, and the dip angle of the fourth candidate formation is taken as the formation dip angle; The expression for the first mathematical formula is: in, The angle between the first stratum interfaces is [angle]. The radius of the spherical detection is [missing information]. The length of the stratigraphic interface interval; The expression for the second mathematical formula is: The expression for the third mathematical formula is: in, The dip angle of the strata is [insert value here]. The angle between the first stratum interfaces is [angle]. The well inclination angle is denoted as .

2. The intelligent and rapid formation dip angle acquisition method based on natural gamma logging response in horizontal wells according to claim 1, characterized in that, The method establishes several natural gamma logging response curves by simulating the logging response characteristics of well trajectories entering the formation at different angles, including: The simulated probe enters the formation along the simulated well trajectory and passes through the simulated formation interface; Based on the intersection relationship between the spherical detection range of the simulated detector and the simulated formation interface, the gamma ray intensity in different regions within the spherical detection range is calculated to obtain the natural gamma logging response curve.

3. The method for intelligent and rapid formation dip angle acquisition based on natural gamma logging response in horizontal wells according to claim 2, characterized in that, The analysis of each of the natural gamma logging response curves yields a first mathematical formula for calculating the angle of the first formation interface based on the formation interface interval length and the spherical detection radius, including: Obtain the first and second critical points when the spherical detection range of the simulated detector enters the simulated stratum interface region; The length of the simulated formation interface interval is determined based on the first critical point and the second critical point; Obtain the second formation angle between the simulated well trajectory and the simulated formation interface; The first mathematical formula is determined based on the correspondence between the spherical detection radius, the length of the simulated stratigraphic interface interval, and the second stratigraphic angle.

4. The intelligent and rapid formation dip angle acquisition method based on natural gamma logging response in horizontal wells according to claim 1, characterized in that, The step of sequentially performing grouped averaging and moving average processing on the natural gamma logging curves to determine the formation interface interval length corresponding to the natural gamma logging curves includes: The natural gamma logging curves are grouped according to a preset first window number of points, the first arithmetic mean of each group is calculated, and the first arithmetic mean of two adjacent groups is compared. When the difference between the first arithmetic mean of two adjacent groups meets the preset first threshold condition, the first candidate interval is determined according to the corresponding logging point; The natural gamma logging curves are grouped into sliding windows according to a preset step size, and the second arithmetic mean of each sliding window is calculated. The second arithmetic mean of two adjacent sliding windows is then compared. When the difference between the second arithmetic mean of two adjacent sliding windows meets the preset second threshold condition, the second candidate interval is determined according to the corresponding logging point; The length of the formation interface interval is determined based on the first candidate interval and the second candidate interval.

5. A smart and rapid formation dip acquisition device based on natural gamma logging response in horizontal wells, characterized in that, The apparatus for performing the method according to any one of claims 1 to 4, the apparatus comprising: The natural gamma logging curve acquisition module is used to acquire the natural gamma logging curve of a horizontal well through a natural gamma logging detector, and to acquire the well inclination angle corresponding to each logging point of the natural gamma logging curve and the spherical detection radius of the natural gamma logging detector. The formation interface angle analysis module is used to establish several natural gamma logging response curves by simulating the logging response characteristics of well trajectories entering the formation at different angles. The module analyzes each of the natural gamma logging response curves to obtain a first mathematical formula for calculating the first formation interface angle based on the formation interface interval length and the spherical detection radius. The formation interface interval length determination module is used to perform group averaging and moving average processing on the natural gamma logging curves in sequence to determine the formation interface interval length corresponding to the natural gamma logging curves. The formation dip angle calculation module is used to calculate the angle between the first formation interfaces based on the length of the formation interface interval and the spherical detection radius using the first mathematical formula, and to calculate the formation dip angle based on the angle between the first formation interfaces and the well inclination angle. Wherein, the first formation interface angle is the angle between the well trajectory and the formation interface.

6. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 4.

7. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 4.

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