Adaptive simplified simulation method and device for borehole directional electromagnetic wave logging

Abstract

The embodiment of the application discloses a self-adaptive simplified simulation method and device for a while-drilling azimuthal electromagnetic wave logging. The focus of the scheme is that aiming at the fault model characteristics, through constructing a differentiation coefficient and a simplified termination coefficient, combined with a one-dimensional fast simulation algorithm, the self-adaptive simplified calculation of a complex fault model can be realized. The application combines the edge detection capability of the while-drilling azimuthal electromagnetic wave logging, proposes the division of the theoretical contribution area, and constructs the differentiation coefficient accordingly, so that the quantitative judgment of whether the model is simplified can be realized. Secondly, the application proposes a simplified method of continuously increasing the number of subdivision of the contribution area, and constructs a simplified termination coefficient, so that the adaptive control of the model simplification process can be realized. Thirdly, the method of the application only involves the generation of a simplified model, and does not need to perform high-dimensional numerical calculation, so the solving speed is fast.

Description

Technical Field

[0001] This application relates to the field of petroleum exploration technology, specifically to an adaptive simplified simulation method and apparatus for azimuth electromagnetic wave logging while drilling. Background Technology

[0002] With the continuous advancement of oil and gas exploration and development technologies, especially the rapid development of drilling technologies for highly deviated / horizontal wells, logging-while-drilling (LOW) technology is increasingly widely used in oil and gas field exploration and development. Azimuth electromagnetic logging (AWP) is a crucial component of LOW and a vital foundation for real-time formation boundary detection. It utilizes the propagation and reflection characteristics of electromagnetic waves in the formation to obtain the formation's electrical parameters. This technology boasts advantages such as high resolution, large detection depth, and minimal impact from the wellbore environment, exhibiting unique strengths in real-time geological steering of horizontal wells. It provides technical support for accurately locating oil and gas layers, optimizing wellbore trajectory design, and improving oil and gas recovery. The successful application of AWP relies heavily on numerical simulation technology. Rapid and accurate logging response calculations are essential for instrument parameter optimization, pre-drilling forward modeling, and post-drilling evaluation.

[0003] However, in practical applications, azimuth logging response simulation while drilling still faces many challenges. In particular, achieving rapid and accurate simulation of complex formation models has become one of the core difficulties in azimuth logging applications. Compared to ideal horizontally layered formations, complex formation models are characterized by discontinuous formation interfaces and rapid changes in formation properties. Taking faults, a common feature in oil and gas exploration and development, as an example, their characteristics are: far from the fault plane, the formation interfaces are relatively parallel and the structure is relatively simple, while near the fault plane, the formation undergoes displacement and the structure becomes complex. Currently, azimuth logging response simulation for complex fault models typically employs two methods: the first is a simplified simulation based on a simple one-dimensional formation model, which ensures simulation efficiency but sacrifices the accuracy of logging responses near the fault plane; the second is logging response simulation based on rigorous 2.5D and three-dimensional numerical simulation algorithms, which ensures simulation efficiency but has a slow computation speed, making it difficult to meet the real-time calculation needs of logging responses. Therefore, there is an urgent need to design an adaptive and simplified simulation scheme for complex geological models in order to effectively improve the speed and accuracy of the algorithm. Summary of the Invention

[0004] In view of the above problems, this application is made in order to provide an adaptive simplified simulation method, apparatus, computing device, computer storage medium and computer program product for azimuth logging while drilling that overcomes or at least partially solves the above problems.

[0005] According to one aspect of the embodiments of this application, an adaptive simplified simulation method for azimuth electromagnetic wave logging while drilling is provided, comprising:

[0006] S1, Construct a fault model based on fault modeling data parameters;

[0007] S2, based on the maximum edge distance of each coil pair in the azimuth logging instrument, the theoretical contribution area of ​​each coil pair is delineated in the fault model;

[0008] S3, for any coil pair, with the location of the drilling azimuth electromagnetic wave logging instrument as the center, the theoretical contribution area is divided into multiple first-grained contribution areas according to the contribution intensity.

[0009] S4, calculate the first azimuth signal of the simplified model corresponding to multiple first-grain size contribution regions during the drilling azimuth electromagnetic wave logging process;

[0010] S5: Calculate the differentiation coefficients based on multiple first-azimuth signals, and evaluate whether model simplification simulation is needed based on the differentiation coefficients. If so, proceed to S6.

[0011] S6, divide any first-grained contribution region into multiple second-grained contribution regions, and calculate the second azimuth signal of the simplified model corresponding to any second-grained contribution region during the drilling azimuth electromagnetic wave logging process;

[0012] S7, perform synthesis processing on multiple second azimuth signals corresponding to any first granularity contribution region to obtain the first equivalent azimuth signal corresponding to any first granularity contribution region;

[0013] S8: Calculate the simplified termination coefficient based on multiple first equivalent azimuth signals. Evaluate whether to terminate the simplified simulation of the model based on the simplified termination coefficient. If not, increase the value of the second granularity and jump to S6. If yes, jump to S9.

[0014] S9 synthesizes multiple first equivalent azimuth signals to obtain the target drilling azimuth signal and outputs it.

[0015] Furthermore, the calculation of the first azimuth signal of the simplified model corresponding to multiple first-grained contribution regions during the drilling azimuth electromagnetic wave logging process further includes:

[0016] For any first-grained contribution region, the location of the formation interface is compared with the first-grained contribution region;

[0017] If the formation interface is located above the first grain size contribution region, the simplified model's interface position is set to the upper boundary of the first grain size contribution region. If the interface is located below the first grain size contribution region, the interface position is set to the lower boundary of the first grain size contribution region. If the interface is located within the first grain size contribution region, the intersection of the formation interface and the left boundary of the first grain size contribution region is taken as the simplified model's interface depth point 1, and the right boundary of the formation interface and the first grain size contribution region is taken as the simplified model's interface depth point 2. Connecting depth point 1 and depth point 2 serves as the simplified model's boundary.

[0018] By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the first azimuth signal of the simplified model corresponding to the first grain size contribution area during the azimuth electromagnetic logging process is calculated.

[0019] Furthermore, the calculation of the differentiation coefficients based on multiple first-azimuth signals further includes:

[0020] The differentiation coefficient is calculated using the following formula:

[0021]

[0022] Where D is the differentiation coefficient, ε is a constant, and G H G M G L These are the first azimuth signals corresponding to multiple first-granularity contribution regions.

[0023] Furthermore, calculating the second azimuth signal of the simplified model corresponding to any second grain size contribution region during the drilling azimuth electromagnetic wave logging process further includes:

[0024] For the i-th second-grained contribution region, the intersection of the formation interface and the left boundary of the i-th second-grained contribution region is taken as the interface depth point i1 of the simplified model, and the right boundary of the formation interface and the i-th second-grained contribution region is taken as the interface depth point i2 of the simplified model. The depth point i1 and the depth point i2 are connected as the boundary of the simplified model. Here, the value of the second grain is set to N, 1≤i≤N.

[0025] By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the second azimuth signal of the simplified model corresponding to the i-th second grain size contribution region during the azimuth electromagnetic logging process is calculated.

[0026] Furthermore, the calculation of simplified termination coefficients based on multiple first equivalent azimuth signals further includes:

[0027] The second equivalent azimuth signal is calculated using the following formula:

[0028]

[0029] ; ;

[0030] in, G E This is the second equivalent azimuth signal. , and The first equivalent azimuth signal corresponding to multiple first-granularity contribution regions respectively; , , The second orientation signal represents multiple second-granularity contribution regions, where N is the value of the second granularity.

[0031] Using the current second equivalent azimuth signal The second equivalent azimuth signal of the previous iteration Calculate the simplified termination coefficient k:

[0032]

[0033] If j=1, let ;

[0034] Where k is the simplification termination coefficient, G E denoted by , where j represents the second equivalent azimuth signal and j is the iteration number.

[0035] Furthermore, the target drilling azimuth signal is obtained by synthesizing multiple first equivalent azimuth signals, which further includes:

[0036] The target azimuth signal is calculated using the following formula:

[0037]

[0038] Wherein, G represents the target azimuth signal during drilling. , and The first equivalent azimuth signal corresponding to each of the multiple first-granularity contribution regions.

[0039] Furthermore, based on the maximum probe distance of each coil pair in the azimuth logging instrument, the theoretical contribution region of each coil pair is further delineated in the fault model, including:

[0040] Based on the working frequency and coil distance of the coil pair in the azimuth logging instrument, the maximum probe distance of the coil pair is determined by creating a preset chart.

[0041] For any pair of coils, the theoretical contribution area of ​​the pair is determined by taking the location of the azimuth logging instrument while drilling as the center, with the height being twice the maximum probe distance in the vertical direction and the width being one times the maximum probe distance in the horizontal direction.

[0042] Furthermore, the multiple first-granularity contribution regions include: a first contribution region, a second contribution region, and a third contribution region;

[0043] For any coil pair, with the location of the azimuth logging instrument as the center, the theoretical contribution region is divided into multiple first-grained contribution regions based on the contribution intensity, further including:

[0044] Centered on the location of the azimuth electromagnetic logging instrument, a rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 0.25 times the maximum probe distance in the horizontal direction is defined as the first contribution area;

[0045] Centered on the location of the azimuth electromagnetic logging instrument, the area after deducting the first contribution area is defined as the second contribution area within a rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 0.5 times the maximum probe distance in the horizontal direction.

[0046] Centered on the location of the azimuth electromagnetic logging instrument, the area after deducting the second contribution region from the rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 1.0 times the maximum probe distance in the horizontal direction is defined as the third contribution region.

[0047] According to another aspect of the embodiments of this application, an adaptive simplified simulation device for azimuth logging while drilling is provided, comprising:

[0048] The building module is suitable for constructing fault models based on fault modeling data parameters;

[0049] The first partitioning module is suitable for defining the theoretical contribution area of ​​each coil pair in the fault model based on the maximum probe distance of each coil pair in the azimuth logging instrument during drilling.

[0050] The second division module is suitable for dividing the theoretical contribution area into multiple first-grained contribution areas based on the contribution intensity, with the location of the drilling azimuth electromagnetic wave logging instrument as the center, for any coil pair.

[0051] The first calculation module is adapted to calculate the first azimuth signal of the simplified model corresponding to multiple first-grain size contribution regions during the drilling azimuth electromagnetic wave logging process.

[0052] The first evaluation module is suitable for calculating the differentiation coefficient based on multiple first azimuth signals, and evaluating whether model simplification simulation is needed based on the differentiation coefficient. If so, the second calculation module is triggered to execute.

[0053] The second calculation module is adapted to divide any first-grained contribution region into multiple second-grained contribution regions, and to calculate the second azimuth signal of the simplified model corresponding to any second-grained contribution region during the drilling azimuth electromagnetic wave logging process.

[0054] The first synthesis module is adapted to synthesize multiple second azimuth signals corresponding to any first granularity contribution region to obtain a first equivalent azimuth signal corresponding to any first granularity contribution region.

[0055] The second evaluation module is adapted to calculate the simplified termination coefficient based on multiple first equivalent azimuth signals, evaluate whether to terminate the simplified simulation of the model based on the simplified termination coefficient, if not, increase the value of the second granularity and trigger the execution of the second calculation module, if yes, trigger the execution of the second synthesis module.

[0056] The second synthesis module is adapted to synthesize multiple first equivalent azimuth signals to obtain the target drilling azimuth signal and output it.

[0057] According to another aspect of the embodiments of this application, a computing device is provided, including: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus;

[0058] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-mentioned adaptive simplified simulation method for azimuth electromagnetic logging while drilling.

[0059] According to another aspect of the embodiments of this application, a computer storage medium is provided, wherein at least one executable instruction is stored in the storage medium, and the executable instruction causes a processor to perform the operation corresponding to the above-described adaptive simplified simulation method for azimuth electromagnetic logging while drilling.

[0060] According to another aspect of the embodiments of this application, a computer program product is provided, including at least one executable instruction, which causes a processor to perform operations corresponding to the above-described adaptive simplified simulation method for azimuth electromagnetic logging while drilling.

[0061] The adaptive simplified simulation method and apparatus for azimuth electromagnetic wave logging while drilling provided in this application focuses on the characteristics of fault models. By constructing differentiation coefficients and simplified termination coefficients, combined with a one-dimensional fast simulation algorithm, adaptive simplified calculation of complex fault models can be achieved. There are two main existing methods for calculating the azimuth electromagnetic wave logging response of fault models while drilling. One method directly simplifies the model to simple layered formations and then uses a one-dimensional fast simulation algorithm for calculation. This method has high computational efficiency but cannot truly reflect the response of complex fault structures, resulting in low simulation accuracy. The other method uses high-dimensional numerical algorithms, such as the finite difference method and the finite element method. This method can accurately characterize the fault structure and obtain a more accurate azimuth electromagnetic wave response while drilling, but the solution speed is slow and cannot meet the requirements of real-time solution. Compared with traditional methods, the key advantages of this application are as follows: First, this application, combining the edge-finding capability of azimuth electromagnetic wave logging while drilling, proposes three concepts of strong, medium, and weak contribution regions, and constructs differentiation coefficients accordingly, enabling quantitative judgment of whether the model has been simplified; second, this application proposes a simplification method that continuously increases the number of contribution region subdivisions and constructs a simplification termination coefficient, enabling adaptive control of the model simplification process; third, the method of this application only involves the generation of simplified models, without the need for high-dimensional numerical calculations, resulting in fast solution speed. The benefits of this application are: First, when the instrument is far from the fault plane, this method will automatically select a one-dimensional algorithm for calculation without further simplification, avoiding the cost of extensive simplified model calculations; second, when the instrument is near the fault plane, this method can also automatically terminate the simplification process, effectively balancing the speed and accuracy of the calculation.

[0062] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of the embodiments of this application are described below. Attached Figure Description

[0063] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0064] Figure 1 A flowchart illustrating an adaptive simplified simulation method for azimuth electromagnetic logging while drilling according to an embodiment of this application is shown.

[0065] Figure 2 This is a schematic diagram of a fault model in an embodiment of this application;

[0066] Figure 3 A comparison of the phase difference azimuth signal response of the fault model during drilling azimuth electromagnetic wave logging with the results of the traditional simplified method;

[0067] Figure 4 The drilling azimuth electromagnetic wave phase difference azimuth signal for the simplified model corresponding to different first-grained contribution regions in this application;

[0068] Figure 5 The diagram shows the variation of the model differentiation coefficient with horizontal distance, calculated according to one embodiment of this application.

[0069] Figure 6 This paper shows a simplified termination coefficient as a function of horizontal distance for different iteration numbers calculated according to an embodiment of this application;

[0070] Figure 7 A simplified termination coefficient at a horizontal distance of 4.7m according to one embodiment of this application is shown as a function of the number of iterations;

[0071] Figure 8 This is a comparison diagram of the phase difference azimuth signal response of the fault model during drilling azimuth electromagnetic wave logging and the results of the adaptive simplification method in this application;

[0072] Figure 9 A structural block diagram of an adaptive simplified simulation device for azimuth logging while drilling according to an embodiment of this application is shown.

[0073] Figure 10 A schematic diagram of the structure of a computing device according to an embodiment of this application is shown. Detailed Implementation

[0074] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0075] Compared to traditional electromagnetic resistivity logging while drilling (EMILDR), azimuth electromagnetic logging while drilling (ASW) offers greater depth detection. Furthermore, ASW utilizes the cross-components of magnetic fields to detect formation interfaces, making it exceptionally sensitive to formation structure. Therefore, for complex fault models, using traditional simplification methods can lead to low-precision simulation results, or even azimuth signals with completely opposite signs. Employing sophisticated high-dimensional numerical simulation algorithms cannot meet the needs of real-time field calculations. Therefore, establishing a simplified simulation algorithm for ASW response of fault models is essential.

[0076] Based on this, this application fully considers the nature of the fault and discloses an adaptive simplified simulation method for the azimuth electromagnetic wave logging response applicable to fault models. The method includes the following steps: S1, constructing a fault model based on fault modeling data parameters; S2, defining the theoretical contribution region of each coil pair in the fault model based on the maximum probe distance of each coil pair in the azimuth electromagnetic wave logging instrument; S3, for any coil pair, dividing the theoretical contribution region into multiple first-grained contribution regions centered on the location of the azimuth electromagnetic wave logging instrument, based on the contribution intensity; S4, calculating the first azimuth signal of the simplified model corresponding to each of the multiple first-grained contribution regions during the azimuth electromagnetic wave logging process; S5, calculating the differentiation coefficient based on the multiple first azimuth signals, and evaluating whether... If a model simplification simulation is required, proceed to step S6; S6: Divide any first-grained contribution region into multiple second-grained contribution regions, and calculate the second azimuth signal of the simplified model corresponding to each second-grained contribution region during the drilling azimuth electromagnetic wave logging process; S7: Synthesize the multiple second azimuth signals corresponding to any first-grained contribution region to obtain the first equivalent azimuth signal corresponding to any first-grained contribution region; S8: Calculate the simplification termination coefficient based on the multiple first equivalent azimuth signals, and evaluate whether to terminate the model simplification simulation based on the simplification termination coefficient. If not, increase the value of the second grained region and proceed to step S6; if yes, proceed to step S9; S9: Synthesize the multiple first equivalent azimuth signals to obtain the target drilling azimuth signal and output it. This application enables rapid simulation of the fault model's drilling azimuth electromagnetic wave logging response through quantitative evaluation of the differentiation coefficient and simplification termination coefficient.

[0077] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0078] Figure 1 A flowchart illustrating an adaptive simplified simulation method for azimuth logging while drilling according to an embodiment of this application is shown, as follows: Figure 1 As shown, the method includes the following steps:

[0079] Step S101: Construct a fault model based on the fault modeling data parameters.

[0080] Fault modeling data parameters are the parameters required to construct fault models. The fault modeling data parameters will vary depending on the different scenarios. For the study area scenario, the fault modeling data parameters mainly consist of the structural feature data of the study area, including vertical pilot well data, seismic imaging data, adjacent well data, and preset well trajectory data.

[0081] For scientific research scenarios, fault modeling data parameters mainly include stratigraphic interface depth, layer thickness, resistivity, fault location, and fault displacement.

[0082] The fault model constructed based on the tectonic feature data of the study area further includes:

[0083] Based on the data from vertical pilot wells, the formation thickness and resistivity of each formation are determined, and a layered formation model is established based on the formation interface depth, the thickness of each formation, and the resistivity.

[0084] Based on seismic imaging data and adjacent well data, the fault location, fault displacement and other parameters are determined, thereby establishing a complete fault model;

[0085] Set the horizontal position coordinates and vertical depth coordinates of the wellbore in the fault model based on the preset wellbore trajectory data.

[0086] The construction of fault models based on scientific research needs further includes:

[0087] Based on the needs of scientific research, parameters such as the depth of the stratigraphic interface, the thickness of each layer, resistivity, fault location, and fault displacement can be arbitrarily set to establish a fault model.

[0088] Fault models can be established according to scientific research needs without involving specific research blocks. Therefore, the following methods can be used to establish... Figure 2 The fault model shown:

[0089] First, assume there is a horizontal three-layered stratum, where the upper and lower strata are sufficiently thick relative to the instrument's probe edge, and the middle stratum is 3m thick;

[0090] Secondly, it is assumed that the middle stratum is a high-resistivity target layer with a resistivity of 20 Ω·m, and the upper and lower strata are low-resistivity surrounding rocks with a resistivity of 2 Ω·m.

[0091] Secondly, assuming that the strata fracture at a horizontal distance of 5m to form a fault plane, the strata on the left side of the fault plane are relatively uplifted, and the strata on the right side of the fault plane are relatively downlifted, forming a vertical fault model.

[0092] Finally, assuming a wellbore drills through a fault plane at a 45° inclination angle, the coordinates of the intersection point between the wellbore trajectory and the fault plane are (5m, 5m), and the coordinates of the intersection points between the wellbore trajectory and the upper and lower interfaces are (2.5m, 2.5m) and (7.5m, 7.5m).

[0093] Figure 3 The comparison between the simulated response and the actual response results of the traditional simplification method is shown. It can be seen that when the instrument is close to the fault plane, the results of the traditional simplification method deviate significantly from the actual response, and the orientation signal is reversed at the fault plane. This indicates that the traditional simplification method is not suitable for calculating complex fault models.

[0094] Step S102: Based on the maximum probe distance of each coil pair in the azimuth logging instrument, the theoretical contribution area of ​​each coil pair is delineated in the fault model.

[0095] Specifically, the theoretical contribution area refers to the formation region that contributes to the response of the azimuth logging-while-drilling (WAS) instrument. A coil pair refers to a coil system consisting of a transmitting coil and a receiving coil. The maximum detection distance refers to the farthest distance at which the coil pair can detect the formation boundary.

[0096] First, based on the operating frequency and coil distance of the coil pair in the azimuth logging (WVR) tool, the maximum detection distance is determined. Generally, lower frequency and longer coils result in a larger detection distance from the signal, while higher frequency and shorter coils result in a smaller detection distance. In this example, the most commonly used WVR coil pair configuration of 96in-100kHz is used, which provides the maximum WVR detection capability. By creating a well-known Picasso chart and using 0.1 degrees and 0.02 dB as thresholds for the phase difference and amplitude ratio signals, respectively, the maximum detection distance of the coil pair can be determined; the maximum detection distance for 96in-100kHz is approximately 7m. Similarly, the maximum detection distance can be obtained for other coil pair configurations using the same method.

[0097] Then, for any coil pair with a combination of working frequency and coil distance, the theoretical contribution area of ​​each coil pair is determined with the location of the drilling azimuth electromagnetic wave logging instrument as the center, the height being twice the maximum probe distance in the vertical direction and the width being one times the maximum probe distance in the horizontal direction. In this example, the theoretical contribution area has a height of 14m and a width of 7m.

[0098] Step S103: For any coil pair, with the location of the azimuth logging instrument during drilling as the center, the theoretical contribution area is divided into multiple first-grained contribution areas according to the contribution intensity.

[0099] Contribution intensity refers to the relative influence of different geological formations on the measurement signal of the coil pair. Based on the different contribution intensities, the theoretical contribution area of ​​the coil pair can be divided into multiple regions according to the first granularity, that is, multiple first-granularity contribution regions.

[0100] The first granularity can be 3. Therefore, the multiple first granularity contribution regions include: the first contribution region, the second contribution region, and the third contribution region.

[0101] Centered on the location of the azimuth electromagnetic logging instrument, a rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 0.25 times the maximum probe distance in the horizontal direction is defined as the first contribution area; in this embodiment, the height of the first contribution area is 14m and the width is 1.75m.

[0102] Centered on the location of the azimuth electromagnetic logging instrument, the area after deducting the first contribution region from a rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 0.5 times the maximum probe distance in the horizontal direction is defined as the second contribution region; in this embodiment, the height of the second contribution region is 14m and the width is 1.75m.

[0103] Centered on the location of the drilling azimuth electromagnetic logging instrument, the area within a rectangle with a height equal to twice the maximum probe distance in the vertical direction and a width equal to 1.0 times the maximum probe distance in the horizontal direction, minus the second contribution area, is defined as the third contribution area. In this embodiment, the height of the third contribution area is 14m and the width is 3.5m.

[0104] For example, the theoretical contribution regions of the coil pairs can be divided according to the strength of their contribution. Therefore, the first contribution region can also be called the strong contribution region, the second contribution region can also be called the medium contribution region, and the third contribution region can also be called the weak contribution region. The strong contribution region refers to the stratigraphic range closest to the instrument, which contributes the most to the instrument response; the medium contribution region refers to the stratigraphic range at a medium distance from the instrument, which contributes a moderate amount to the instrument response; and the weak contribution region refers to the stratigraphic range at a relatively far distance from the instrument, which contributes a weaker amount to the instrument response.

[0105] Step S104: Calculate the first azimuth signal of the simplified model corresponding to multiple first-grain size contribution regions during the drilling azimuth electromagnetic wave logging process.

[0106] Specifically, for any first-grained contribution region, the position of the stratigraphic interface is compared with the first-grained contribution region. If the stratigraphic interface is above the first-grained contribution region, the interface position of the simplified model is set as the upper boundary of the first-grained contribution region. If the interface is below the first-grained contribution region, the interface position is set as the lower boundary of the first-grained contribution region. If the interface is within the first-grained contribution region, the intersection of the stratigraphic interface and the left boundary of the first-grained contribution region is taken as the interface depth point 1 of the simplified model, and the right boundary of the stratigraphic interface and the first-grained contribution region is taken as the interface depth point 2 of the simplified model. The connection between depth point 1 and depth point 2 is taken as the boundary of the simplified model. After the boundary is determined, the simplified model can be determined. The above processing can realize the simplification of the fault model.

[0107] By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the first azimuth signal of the simplified model corresponding to the first grain size contribution area during the azimuth electromagnetic logging process is calculated.

[0108] The first azimuth signal can be either the phase difference azimuth signal GP or the amplitude ratio azimuth signal GA. The following formula defines GP and GA:

[0109]

[0110] Where Vzz and Vzx represent the coaxial component and cross component of the induced electromotive force, respectively.

[0111] Based on the above division of theoretical contribution regions, G H The first azimuth signal, denoted as the strong contribution region, will be G. M The first azimuth signal in the central contribution area is denoted as G. L The first azimuth signal is denoted as the weak contribution region.

[0112] Figure 4 The diagram shows the phase difference azimuth signals of the drilling azimuth electromagnetic waves corresponding to the simplified models of different first-grain size contribution regions in this application. The phase difference azimuth signal responses calculated based on the simplified models of strong contribution region, medium contribution region and weak contribution region are shown here. It can be seen that when the instrument is far away from the fault plane, the three responses almost overlap, while when it is close to the fault plane, the three curves are severely separated, indicating that the simplified models have large differences.

[0113] Step S105: Calculate the differentiation coefficients based on multiple first azimuth signals. Evaluate whether model simplification simulation is needed based on the differentiation coefficients. If yes, proceed to step S106; otherwise, proceed to step S110.

[0114] Specifically, the differentiation coefficient is calculated according to the following formula:

[0115]

[0116] Where D is the differentiation coefficient, whose value is between 0 and 1, with the value closer to 0 indicating greater differentiation. H G M G L The smaller the difference, the greater the difference; conversely, the larger the difference, the greater the difference. ε is a constant; for amplitude-to-azimuth signals, ε is 1, and for phase-to-azimuth signals, ε is 10. G H G M G L These are the first azimuth signals corresponding to multiple first-granularity contribution regions. The differentiation coefficient D is used as a quantitative evaluation criterion for whether the model is simplified. An adaptive determination is made as to whether the model needs simplification. Here, the differentiation coefficient is compared with a first threshold. Those skilled in the art can set the differentiation coefficient according to actual needs. It is recommended that the first threshold be set to 0.01, i.e., when D < 0.01, the model does not need simplification, and the process proceeds to step S110; when D > 0.01, the model needs simplification, and the process proceeds to step S106.

[0117] In this example, taking GP96L as an example, the calculated differentiation coefficient is as follows: Figure 5It can be seen that the differentiation coefficient is very small when far from the fault plane, but increases sharply when close to the fault plane. When the differentiation coefficient is less than the threshold of 0.01, the process jumps to step S110; when the differentiation coefficient is greater than the threshold of 0.01, the process jumps to step S106.

[0118] Step S106: Divide any first-grained contribution region into multiple second-grained contribution regions, and calculate the second azimuth signal of the simplified model corresponding to any second-grained contribution region during the drilling azimuth electromagnetic wave logging process.

[0119] Specifically, for each first-granularity contribution region, it can be divided into multiple regions according to the second granularity. Assuming the second granularity is represented by N, for any first-granularity contribution region, it is further subdivided into N regions. Let the width of any first-granularity contribution region be W, then the width of the i-th second-granularity contribution region is...

[0120] For the i-th second-grained contribution region, the intersection of the formation interface and the left boundary of the i-th second-grained contribution region is taken as the interface depth point i1 of the simplified model, and the right boundary of the formation interface and the i-th second-grained contribution region is taken as the interface depth point i2 of the simplified model. The depth point i1 and the depth point i2 are connected as the boundary of the simplified model, where 1≤i≤N.

[0121] By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the second azimuth signal of the simplified model corresponding to the i-th second grain size contribution region during the azimuth electromagnetic logging process is calculated.

[0122] For ease of subsequent description, we can use G. Hi The second orientation signal of the i-th second-granularity contribution region of the first contribution region is represented by G. Mi The second orientation signal of the i-th second-granularity contribution region of the second contribution region is represented by G. Li The second orientation signal represents the i-th second-granularity contribution region of the third contribution region.

[0123] Step S107: Perform synthesis processing on multiple second azimuth signals corresponding to any first granularity contribution region to obtain a first equivalent azimuth signal corresponding to any first granularity contribution region.

[0124] Specifically, the first equivalent azimuth signal can be calculated using the following formula:

[0125] ; ;

[0126] in, , and The first equivalent azimuth signal corresponding to multiple first-granularity contribution regions respectively; , , The second azimuth signal is the second azimuth signal of multiple second granularity contribution regions, where N is the value of the second granularity; the first equivalent azimuth signal is the equivalent azimuth signal corresponding to the first granularity contribution region.

[0127] Step S108: Calculate the simplified termination coefficient based on multiple first equivalent azimuth signals, evaluate whether to terminate the simplified simulation of the model based on the simplified termination coefficient. If not, increase the value of N and jump to step S106. If yes, jump to step S109.

[0128] Specifically, the second equivalent azimuth signal is calculated using the following formula:

[0129]

[0130] Among them, G E The second equivalent azimuth signal is the total equivalent azimuth signal corresponding to multiple first-granularity contribution regions.

[0131] Record the current second equivalent azimuth signal Using the current second equivalent azimuth signal The second equivalent azimuth signal of the previous iteration Calculate the simplified termination coefficient k:

[0132]

[0133] If j=1, let ;

[0134] Where k is the simplification termination coefficient, its value is between 0 and 1, the closer to 0, the smaller the difference between the current simplification result and the previous iteration result, and vice versa, G E This represents the second equivalent azimuth signal.

[0135] Using the simplification termination coefficient k as a quantitative evaluation criterion for whether the model needs further simplification, an adaptive determination is made to determine whether the model needs further simplification. A threshold of 0.1 is recommended; that is, when k < 0.1, the model terminates simplification and proceeds to step S109. When k > 0.1, the number of subdivisions of the contribution region is set to twice the number of subdivisions in the previous iteration. In other words, when the first-granularity contribution region is subdivided in the next iteration, the value of the second granularity will be twice that of the previous iteration. Let N represent the second granularity. Then proceed to step S106, where j is the iteration number of the first granularity contribution region being divided into multiple second granularity contribution regions.

[0136] Figure 6 The diagram shows the simplified termination coefficient versus horizontal distance for different iterations calculated according to an embodiment of this application. It can be seen that as the number of iterations increases, the number of points greater than the threshold decreases continuously. By the fifth iteration, there are no points greater than the threshold. Figure 7 Taking a horizontal distance of 4.7m as an example, the change of the termination coefficient during the iteration process is shown.

[0137] Step S109: Combine multiple first equivalent azimuth signals to obtain the target drilling azimuth signal and output it.

[0138] Specifically, the target azimuth signal is calculated using the following formula:

[0139]

[0140] Wherein, G is the target azimuth signal while drilling, which can represent the phase difference azimuth signal GP or the amplitude ratio azimuth signal GA. , and These are the first equivalent azimuth signals corresponding to multiple first-granularity contribution regions.

[0141] That is, , and These represent the first equivalent azimuth signals for the strong contribution region, medium contribution region, and weak contribution region, respectively.

[0142] Figure 8 The comparison between the fault response in this embodiment and the calculation results using the above-mentioned adaptive simplification method is shown. It can be seen that the calculation results using this method have a high degree of agreement with the actual results and are significantly better than the traditional simplification method.

[0143] Step S110: Combine multiple first azimuth signals to obtain the target drilling azimuth signal and output it.

[0144] The implementation process of this step is similar to that of step S109, and will not be repeated here.

[0145] The adaptive simplified simulation method for azimuth electromagnetic wave logging while drilling provided in this application focuses on the characteristics of the fault model. By constructing differentiation coefficients and simplified termination coefficients, combined with a one-dimensional fast simulation algorithm, it can achieve adaptive simplified calculation of complex fault models. There are two main existing methods for calculating the azimuth electromagnetic wave logging response of fault models while drilling. One method directly simplifies the model to simple layered formations and then uses a one-dimensional fast simulation algorithm for calculation. This method has high computational efficiency but cannot truly reflect the response of complex fault structures, resulting in low simulation accuracy. The other method uses high-dimensional numerical algorithms, such as the finite difference method and the finite element method. This method can accurately characterize the fault structure and obtain a more accurate azimuth electromagnetic wave response while drilling, but the solution speed is slow and cannot meet the requirements of real-time solution. Compared with traditional methods, the key advantages of this application are as follows: First, this application, combining the edge-finding capability of azimuth electromagnetic wave logging while drilling, proposes three concepts of strong, medium, and weak contribution regions, and constructs differentiation coefficients accordingly, enabling quantitative judgment of whether the model has been simplified; second, this application proposes a simplification method that continuously increases the number of contribution region subdivisions and constructs a simplification termination coefficient, enabling adaptive control of the model simplification process; third, the method of this application only involves the generation of simplified models, without the need for high-dimensional numerical calculations, resulting in fast solution speed. The benefits of this application are: First, when the instrument is far from the fault plane, this method will automatically select a one-dimensional algorithm for calculation without further simplification, avoiding the cost of extensive simplified model calculations; second, when the instrument is near the fault plane, this method can also automatically terminate the simplification process, effectively balancing the speed and accuracy of the calculation.

[0146] Figure 9 A structural block diagram of an adaptive simplified simulation device for azimuth logging while drilling according to an embodiment of this application is shown, as follows: Figure 9 As shown, the device includes:

[0147] Module 901 is suitable for constructing fault models based on fault modeling data parameters;

[0148] The first partitioning module 902 is adapted to delineate the theoretical contribution area of ​​each coil pair in the fault model based on the maximum probe distance of each coil pair in the drilling azimuth electromagnetic wave logging instrument.

[0149] The second division module 903 is suitable for dividing the theoretical contribution area into multiple first-grained contribution areas based on the contribution intensity, with the location of the drilling azimuth electromagnetic wave logging instrument as the center, for any coil pair.

[0150] The first calculation module 904 is adapted to calculate the first azimuth signal of the simplified model corresponding to multiple first grain size contribution regions during the drilling azimuth electromagnetic wave logging process.

[0151] The first evaluation module 905 is adapted to calculate the differentiation coefficient based on multiple first azimuth signals, and evaluate whether model simplification simulation is needed based on the differentiation coefficient. If so, the second calculation module is triggered to execute.

[0152] The second calculation module 906 is adapted to divide any first-grained contribution region into multiple second-grained contribution regions, and calculate the second azimuth signal of the simplified model corresponding to any second-grained contribution region during the drilling azimuth electromagnetic wave logging process.

[0153] The first synthesis module 907 is adapted to perform synthesis processing on multiple second azimuth signals corresponding to any first granularity contribution region to obtain a first equivalent azimuth signal corresponding to any first granularity contribution region.

[0154] The second evaluation module 908 is adapted to calculate the simplified termination coefficient based on multiple first equivalent azimuth signals, evaluate whether to terminate the simplified simulation of the model based on the simplified termination coefficient, if not, increase the value of the second granularity and trigger the execution of the second calculation module, if yes, trigger the execution of the second synthesis module.

[0155] The second synthesis module 909 is adapted to synthesize multiple first equivalent azimuth signals to obtain the target drilling azimuth signal and output it.

[0156] Optionally, the first calculation module is further adapted to: for any first grain size contribution region, compare the location of the formation interface with the first grain size contribution region;

[0157] If the formation interface is located above the first grain size contribution region, the simplified model's interface position is set to the upper boundary of the first grain size contribution region. If the interface is located below the first grain size contribution region, the interface position is set to the lower boundary of the first grain size contribution region. If the interface is located within the first grain size contribution region, the intersection of the formation interface and the left boundary of the first grain size contribution region is taken as the simplified model's interface depth point 1, and the right boundary of the formation interface and the first grain size contribution region is taken as the simplified model's interface depth point 2. Connecting depth point 1 and depth point 2 serves as the simplified model's boundary.

[0158] By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the first azimuth signal of the simplified model corresponding to the first grain size contribution area during the azimuth electromagnetic logging process is calculated.

[0159] Optionally, the first evaluation module is further adapted to calculate the differentiation coefficient using the following formula:

[0160]

[0161] Where D is the differentiation coefficient, ε is a constant, and G H G M GL These are the first azimuth signals corresponding to multiple first-granularity contribution regions.

[0162] Optionally, the second calculation module is further adapted to: for the i-th second-grained contribution region, take the intersection of the formation interface and the left boundary of the i-th second-grained contribution region as the interface depth point i1 of the simplified model, take the right boundary of the formation interface and the i-th second-grained contribution region as the interface depth point i2 of the simplified model, and connect depth point i1 and depth point i2 as the boundary of the simplified model, where the value of the second grain is N, 1≤i≤N;

[0163] By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the second azimuth signal of the simplified model corresponding to the i-th second grain size contribution region during the azimuth electromagnetic logging process is calculated.

[0164] Optionally, the second evaluation module is further adapted to:

[0165] The second equivalent azimuth signal is calculated using the following formula:

[0166]

[0167] ; ;

[0168] in, G E This is the second equivalent azimuth signal. , and The first equivalent azimuth signal corresponding to multiple first-granularity contribution regions respectively; , , The second orientation signal represents multiple second-granularity contribution regions, where N is the value of the second granularity.

[0169] Using the current second equivalent azimuth signal The second equivalent azimuth signal of the previous iteration Calculate the simplified termination coefficient k:

[0170]

[0171] If j=1, let ;

[0172] Where k is the simplification termination coefficient, G E denoted by , where j represents the second equivalent azimuth signal and j is the iteration number.

[0173] Optionally, the second synthesis module is further adapted to: calculate the target azimuth signal while drilling using the following formula:

[0174]

[0175] Wherein, G represents the target azimuth signal during drilling. , and The first equivalent azimuth signal corresponding to each of the multiple first-granularity contribution regions.

[0176] Optionally, the first division module is further adapted to: determine the maximum probe distance of the coil pair by creating a preset chart based on the working frequency and coil distance of the coil pair in the drilling azimuth electromagnetic wave logging instrument;

[0177] For any pair of coils, the theoretical contribution area of ​​the pair is determined by taking the location of the azimuth logging instrument while drilling as the center, with the height being twice the maximum probe distance in the vertical direction and the width being one times the maximum probe distance in the horizontal direction.

[0178] Optionally, the multiple first-granularity contribution regions include: a first contribution region, a second contribution region, and a third contribution region;

[0179] The second division module is further adapted to: taking the location of the drilling azimuth electromagnetic wave logging instrument as the center, delineating a rectangle with a height of 2 times the maximum probe edge distance in the vertical direction and a width of 0.25 times the maximum probe edge distance in the horizontal direction as the first contribution area;

[0180] Centered on the location of the azimuth electromagnetic logging instrument, the area after deducting the first contribution area is defined as the second contribution area within a rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 0.5 times the maximum probe distance in the horizontal direction.

[0181] Centered on the location of the azimuth electromagnetic logging instrument, the area after deducting the second contribution region from the rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 1.0 times the maximum probe distance in the horizontal direction is defined as the third contribution region.

[0182] The descriptions of the above modules refer to the corresponding descriptions in the method embodiments, and will not be repeated here.

[0183] The adaptive simplified simulation device for azimuth electromagnetic wave logging while drilling provided in this application focuses on the characteristics of the fault model. By constructing differentiation coefficients and simplified termination coefficients, combined with a one-dimensional fast simulation algorithm, it can achieve adaptive simplified calculation of complex fault models. There are two main existing methods for calculating the azimuth electromagnetic wave logging response of fault models while drilling. One method directly simplifies the model to simple layered formations and then uses a one-dimensional fast simulation algorithm for calculation. This method has high computational efficiency but cannot truly reflect the response of complex fault structures, resulting in low simulation accuracy. The other method uses high-dimensional numerical algorithms, such as the finite difference method and the finite element method. This method can accurately characterize the fault structure and obtain a more accurate azimuth electromagnetic wave response while drilling, but the solution speed is slow and cannot meet the requirements of real-time solution. Compared with traditional methods, the key advantages of this application are as follows: First, this application, combining the edge-finding capability of azimuth electromagnetic wave logging while drilling, proposes three concepts of strong, medium, and weak contribution regions, and constructs differentiation coefficients accordingly, enabling quantitative judgment of whether the model has been simplified; second, this application proposes a simplification method that continuously increases the number of contribution region subdivisions and constructs a simplification termination coefficient, enabling adaptive control of the model simplification process; third, the method of this application only involves the generation of simplified models, without the need for high-dimensional numerical calculations, resulting in fast solution speed. The benefits of this application are: First, when the instrument is far from the fault plane, this method will automatically select a one-dimensional algorithm for calculation without further simplification, avoiding the cost of extensive simplified model calculations; second, when the instrument is near the fault plane, this method can also automatically terminate the simplification process, effectively balancing the speed and accuracy of the calculation.

[0184] This application provides a non-volatile computer storage medium storing at least one executable instruction or computer program that enables a processor to perform the operation corresponding to the adaptive simplified simulation method for azimuth electromagnetic logging while drilling in any of the above method embodiments.

[0185] This application provides a computer program product, which includes at least one executable instruction or computer program that enables a processor to perform the operation corresponding to the adaptive simplified simulation method for azimuth electromagnetic logging while drilling in any of the above method embodiments.

[0186] Figure 10 The diagram shows a structural schematic of an embodiment of the computing device of this application. The specific embodiments of this application do not limit the specific implementation of the computing device.

[0187] like Figure 10As shown, the computing device may include: a processor 1002, a communications interface 1004, a memory 1006, and a communications bus 1008.

[0188] The processor 1002, communication interface 1004, and memory 1006 communicate with each other via communication bus 1008. Communication interface 1004 is used to communicate with other network elements, such as clients or other servers. Processor 1002 executes program 1010, specifically performing the relevant steps in the above-described embodiment of the adaptive simplified simulation method for drilling azimuth electromagnetic wave logging for computing equipment.

[0189] Specifically, program 1010 may include program code that includes computer operation instructions.

[0190] The processor 1002 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computing device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0191] Memory 1006 is used to store program 1010. Memory 1006 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0192] Specifically, program 1010 can be used to cause processor 1002 to execute the adaptive simplified simulation method for azimuth electromagnetic wave logging while drilling in any of the above method embodiments. The specific implementation of each step in program 1010 can be found in the corresponding descriptions of the steps and units in the above-described adaptive simplified simulation embodiments for azimuth electromagnetic wave logging while drilling, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described equipment and modules can be referred to the corresponding process descriptions in the foregoing method embodiments, and will not be repeated here.

[0193] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, the embodiments of this application are not directed to any particular programming language. It should be understood that the contents of the embodiments of this application described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best implementation of the embodiments of this application.

[0194] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0195] Similarly, it should be understood that, in order to simplify this disclosure and aid in understanding one or more of the various inventive aspects, in the foregoing description of exemplary embodiments of the present application, various features of the present application embodiments are sometimes grouped together into a single embodiment, figure, or description thereof. However, this approach to disclosure should not be construed as reflecting an intention that the claimed embodiments of the present application require more features than expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the present application.

[0196] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0197] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are meant to be within the scope of the embodiments of this application and form different embodiments. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

[0198] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components according to the embodiments of this application. The embodiments of this application can also be implemented as device or apparatus programs (e.g., computer programs and computer program products) for performing part or all of the methods described herein. Such programs implementing the embodiments of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0199] It should be noted that the above embodiments are illustrative of the embodiments of this application and not limiting of the embodiments of this application, and those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Embodiments of this application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

Claims

1. An adaptive simplified simulation method for azimuth electromagnetic wave logging while drilling, comprising: S1, Construct a fault model based on fault modeling data parameters; S2, based on the maximum probe distance of each coil pair in the azimuth logging instrument, the theoretical contribution area of ​​each coil pair is delineated in the fault model. S3, for any coil pair, with the location of the drilling azimuth electromagnetic wave logging instrument as the center, the theoretical contribution area is divided into multiple first-grained contribution areas according to the contribution intensity. S4, calculate the first azimuth signal of the simplified model corresponding to multiple first-grain size contribution regions during the drilling azimuth electromagnetic wave logging process; S5, calculate the differentiation coefficient based on multiple first azimuth signals, and evaluate whether model simplification simulation is needed based on the differentiation coefficient. If so, proceed to S6. S6, divide any first-grained contribution region into multiple second-grained contribution regions, and calculate the second azimuth signal of the simplified model corresponding to any second-grained contribution region during the drilling azimuth electromagnetic wave logging process; S7, perform synthesis processing on multiple second azimuth signals corresponding to any first granularity contribution region to obtain the first equivalent azimuth signal corresponding to any first granularity contribution region; S8: Calculate the simplified termination coefficient based on multiple first equivalent azimuth signals, evaluate whether to terminate the simplified simulation of the model based on the simplified termination coefficient, if not, increase the value of the second granularity and jump to S6; if yes, jump to S9. S9, synthesizes and processes multiple first equivalent azimuth signals to obtain the target drilling azimuth signal and outputs it; The calculation of the simplified termination coefficient based on multiple first equivalent azimuth signals further includes: The second equivalent azimuth signal is calculated using the following formula: ； ； in, G E This is the second equivalent azimuth signal. , and The first equivalent azimuth signal corresponding to multiple first-granularity contribution regions respectively; , , The second orientation signal represents multiple second-granularity contribution regions, where N is the value of the second granularity. Using the current second equivalent azimuth signal The second equivalent azimuth signal of the previous iteration Calculate the simplified termination coefficient k: If j=1, let ; Where k is the simplification termination coefficient, G E denoted by , where j represents the second equivalent azimuth signal and j is the iteration number.

2. The method according to claim 1, wherein, The step of calculating the first azimuth signal of the simplified model corresponding to multiple first-grained contribution regions during the drilling azimuth electromagnetic wave logging process further includes: For any first-grained contribution region, the location of the formation interface is compared with the first-grained contribution region; If the formation interface is located above the first grain size contribution region, the simplified model's interface position is set to the upper boundary of the first grain size contribution region. If the interface is located below the first grain size contribution region, the interface position is set to the lower boundary of the first grain size contribution region. If the interface is located within the first grain size contribution region, the intersection of the formation interface and the left boundary of the first grain size contribution region is taken as the simplified model's interface depth point 1, and the right boundary of the formation interface and the first grain size contribution region is taken as the simplified model's interface depth point 2. Connecting depth point 1 and depth point 2 serves as the simplified model's boundary. By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the first azimuth signal of the simplified model corresponding to the first grain size contribution area during the azimuth electromagnetic logging process is calculated.

3. The method according to claim 1 or 2, wherein, The calculation of the differentiation coefficient based on multiple first azimuth signals further includes: The differentiation coefficient is calculated using the following formula: Where D is the differentiation coefficient, ε is a constant, and G H G M G L These are the first azimuth signals corresponding to multiple first-granularity contribution regions.

4. The method according to claim 1 or 2, wherein, The step of calculating the second azimuth signal of the simplified model corresponding to any second grain size contribution region during the drilling azimuth electromagnetic wave logging process further includes: For the i-th second-grained contribution region, the intersection of the formation interface and the left boundary of the i-th second-grained contribution region is taken as the interface depth point i1 of the simplified model, and the right boundary of the formation interface and the i-th second-grained contribution region is taken as the interface depth point i2 of the simplified model. The depth point i1 and the depth point i2 are connected as the boundary of the simplified model. Here, the value of the second grain is set to N, 1≤i≤N. By combining the location of the azimuth electromagnetic logging instrument and the well inclination angle, the second azimuth signal of the simplified model corresponding to the i-th second grain size contribution region during the azimuth electromagnetic logging process is calculated.

5. The method according to claim 1 or 2, wherein, The step of synthesizing multiple first equivalent azimuth signals to obtain the target drilling azimuth signal further includes: The target azimuth signal is calculated using the following formula: Where G represents the target azimuth signal during drilling. , and The first equivalent azimuth signal corresponding to each of the multiple first-granularity contribution regions.

6. The method according to claim 1 or 2, wherein, The step of defining the theoretical contribution region of each coil pair in the fault model based on the maximum probe distance of each coil pair in the azimuth logging instrument further includes: Based on the operating frequency and coil distance of the coil pair in the azimuth logging instrument, the maximum probe distance of the coil pair is determined by creating a preset chart. For any pair of coils, the theoretical contribution area of ​​the pair is determined by taking the location of the azimuth logging instrument while drilling as the center, with a vertical height of twice the maximum probe distance and a horizontal width of one maximum probe distance.

7. The method according to claim 1 or 2, wherein, Multiple first-granularity contribution regions include: a first contribution region, a second contribution region, and a third contribution region; The step of dividing the theoretical contribution region into multiple first-grained contribution regions based on the contribution intensity, centered on the location of the drilling azimuth electromagnetic logging instrument, for any coil pair, further includes: Centered on the location of the azimuth electromagnetic logging instrument, a rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 0.25 times the maximum probe distance in the horizontal direction is defined as the first contribution area; Centered on the location of the azimuth electromagnetic logging instrument, the area after deducting the first contribution area is defined as the second contribution area within a rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 0.5 times the maximum probe distance in the horizontal direction. Centered on the location of the azimuth electromagnetic logging instrument, the area after deducting the second contribution region from the rectangle with a height of twice the maximum probe distance in the vertical direction and a width of 1.0 times the maximum probe distance in the horizontal direction is defined as the third contribution region.

8. A simplified adaptive simulation device for azimuth logging while drilling, comprising: The building module is suitable for constructing fault models based on fault modeling data parameters; The first partitioning module is adapted to delineate the theoretical contribution area of ​​each coil pair in the fault model based on the maximum probe distance of each coil pair in the azimuth logging instrument. The second division module is suitable for dividing the theoretical contribution area into multiple first-grained contribution areas based on the contribution intensity, with the location of the drilling azimuth electromagnetic wave logging instrument as the center, for any coil pair. The first calculation module is adapted to calculate the first azimuth signal of the simplified model corresponding to multiple first-grain size contribution regions during the drilling azimuth electromagnetic wave logging process. The first evaluation module is adapted to calculate the differentiation coefficient based on multiple first azimuth signals, and evaluate whether model simplification simulation is needed based on the differentiation coefficient. If so, the second calculation module is triggered to execute. The second calculation module is adapted to divide any first-grained contribution region into multiple second-grained contribution regions, and to calculate the second azimuth signal of the simplified model corresponding to any second-grained contribution region during the drilling azimuth electromagnetic wave logging process. The first synthesis module is adapted to synthesize multiple second azimuth signals corresponding to any first granularity contribution region to obtain a first equivalent azimuth signal corresponding to any first granularity contribution region. The second evaluation module is adapted to calculate a simplified termination coefficient based on multiple first equivalent azimuth signals, evaluate whether to terminate the simplified simulation of the model based on the simplified termination coefficient, and if not, increase the value of the second granularity to trigger the execution of the second calculation module; if yes, trigger the execution of the second synthesis module. The second synthesis module is adapted to synthesize multiple first equivalent azimuth signals to obtain the target drilling azimuth signal and output it. The second evaluation module is further adapted to calculate the second equivalent azimuth signal using the following formula: ； ； in, G E This is the second equivalent azimuth signal. , and The first equivalent azimuth signal corresponding to multiple first-granularity contribution regions respectively; , , The second orientation signal represents multiple second-granularity contribution regions, where N is the value of the second granularity. Using the current second equivalent azimuth signal The second equivalent azimuth signal of the previous iteration Calculate the simplified termination coefficient k: If j=1, let ; Where k is the simplification termination coefficient, G E denoted by , where j represents the second equivalent azimuth signal and j is the iteration number.

9. A computing device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the adaptive simplified simulation method for azimuth electromagnetic logging as described in any one of claims 1-7.

10. A computer storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the adaptive simplified simulation method for azimuth electromagnetic logging as described in any one of claims 1-7.

11. A computer program product comprising at least one executable instruction that causes a processor to perform an operation corresponding to the adaptive simplified simulation method for azimuth electromagnetic logging as described in any one of claims 1-7.

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