Method, device and system for identifying stratum type during rotary drilling and rotary drilling rig

Abstract

This invention relates to the field of rotary drilling control, and provides a method, apparatus, system, and rotary drilling rig for identifying formation types during rotary drilling. The method includes: identifying the operating condition of the rotary drilling rig based on first state data; when the operating condition of the rotary drilling rig is identified as drilling, acquiring second state data associated with the formation type in the rotary drilling rig, the second state data including vibration type data and non-vibration type data; extracting feature data characterizing the formation type based on the second state data; identifying the current formation type of the rotary drilling rig based on the feature data, and controlling the issuance of a prompt message indicating the current formation type. This allows for automatic identification of the formation type and display of the identification results during the rotary drilling process, enabling the operator to adjust the operating parameters of the rotary drilling rig or change the drilling tools according to the current formation type to improve construction efficiency.

Description

Technical Field

[0001] This invention relates to the field of rotary drilling control technology, and in particular to a method, device, system, and rotary drilling rig for identifying formation types during rotary drilling. Background Technology

[0002] Rotary drilling rigs are mainly used for hole-forming operations in building foundation engineering. They can be used in most geological formations, such as for hole-forming operations in highway bridges and high-rise building construction.

[0003] Currently, due to the unique nature of pile foundation operations, rotary drilling rigs cannot automatically identify and display geological formations in real time during drilling operations. The selection of construction methods and the determination of rotary drilling rig operating parameters mainly rely on prior geological survey results and the operator's experience and proficiency in operating the rotary drilling rig. This often results in low construction efficiency due to poor selection of rotary drilling rig operating parameters, unsuitable attachments, or inappropriate construction methods. Therefore, how to automatically identify geological formations and provide timely or real-time geological information during rotary drilling operations is a pressing technical problem that the industry needs to solve. Summary of the Invention

[0004] This invention provides a method, apparatus, system, and rotary drilling rig for identifying formation types during rotary drilling, in order to solve any of the aforementioned technical problems existing in the prior art.

[0005] This invention provides a method for identifying formation types during rotary drilling, comprising:

[0006] The operating condition of the rotary drilling rig is identified based on the first state data of the rotary drilling rig;

[0007] When the working condition of the rotary drilling rig is identified as drilling, the second state data associated with the formation type of the rotary drilling rig is obtained. The second state data includes vibration type data and non-vibration type data.

[0008] Based on the second state data, feature data characterizing the stratigraphic type are extracted;

[0009] Based on the feature data, the current formation type of the rotary drilling rig is identified, and a prompt message indicating the current formation type is issued.

[0010] According to the present invention, a method for identifying formation types during rotary drilling, wherein the step of extracting feature data characterizing formation types based on the second state data includes:

[0011] Obtain statistical data of the non-vibration type data within a preset unit time period;

[0012] Obtain statistical data of the vibration type data within the preset unit time period;

[0013] The statistical data of the non-vibration type data within the preset unit time period is fused with the statistical data of the vibration type data to obtain the feature data within the preset unit time period.

[0014] According to the present invention, a method for identifying formation type during rotary drilling is provided, wherein the vibration type data includes a power head vibration signal, and the power head vibration signal includes vibration components in three orthogonal directions;

[0015] The statistical data obtained from the vibration type data within the preset unit time period includes:

[0016] The vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period are statistically analyzed to obtain the time-domain statistical data of the power head vibration signal in each orthogonal direction within the preset unit time period.

[0017] The time-domain statistical data may include at least one of the following: skewness, kurtosis, peak value, root mean square, margin factor, and waveform factor;

[0018] The vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period are subjected to Fourier transform to obtain the power density spectrum of each orthogonal direction within the preset unit time period; the power density spectrum of each orthogonal direction within the preset unit time period is statistically analyzed to obtain the frequency domain statistical data of each orthogonal direction within the preset unit time period.

[0019] The frequency domain statistics may include at least one of the following: the power mean of the power density spectrum over the entire frequency range, the power variance of the power density spectrum over the entire frequency range, the power mean of each frequency sub-interval in the power density spectrum, and the power variance of each frequency sub-interval in the power density spectrum.

[0020] The time-domain statistical data and the frequency-domain statistical data for each orthogonal direction within the preset unit time period are used as the statistical data for the vibration type data within the preset unit time period.

[0021] According to a method for identifying formation type during rotary drilling provided by the present invention, the non-vibration type data includes power head rotation speed, power head torque, power head pressurization pressure, engine speed and average drilling speed.

[0022] The statistical data obtained within a preset unit time period for the non-vibration type data includes:

[0023] The average values ​​of the power head rotation speed, the power head torque, the power head pressurization pressure, the engine speed, and the average feed rate within the preset unit time period are used as statistical data for the non-vibration type data within the preset unit time period.

[0024] According to a method for identifying formation type during rotary drilling provided by the present invention, the step of identifying the current formation type drilled by the rotary drilling rig based on the feature data includes:

[0025] The feature data is input into the stratigraphic type identification model to obtain the current stratigraphic type output by the stratigraphic type identification model;

[0026] The stratigraphic type identification model is obtained by training a random forest model based on feature data samples and corresponding stratigraphic type samples.

[0027] According to a method for identifying formation type during rotary drilling provided by the present invention, the control issuing a prompt message about the current formation type includes:

[0028] The display screen in the rotary drilling rig displays a prompt message indicating the current formation type.

[0029] According to the present invention, a method for identifying formation type during rotary drilling is provided, wherein the first state data includes engine speed, engine torque, main pump pressure, auxiliary pump pressure, slewing angle, lowering depth, and hole depth.

[0030] The process of identifying the operating condition of the rotary drilling rig based on its first state data includes:

[0031] When the first state data meets the drilling conditions, the operating condition of the rotary drilling rig is determined to be drilling; wherein, the drilling conditions include:

[0032] The engine speed is greater than the preset speed;

[0033] The pressure of the main pump or the pressure of the auxiliary pump is greater than the preset pressure;

[0034] The rotation angle is within a preset angle range;

[0035] The engine torque is greater than the preset torque;

[0036] The lowering depth is greater than or equal to zero;

[0037] The change in the lowering depth is greater than zero;

[0038] The lowering depth is greater than or equal to the hole forming depth.

[0039] The present invention also provides a formation type identification device during rotary drilling, comprising:

[0040] The working condition identification module is used to identify the working condition of the rotary drilling rig based on the first state data of the rotary drilling rig.

[0041] The data acquisition module is used to acquire second state data associated with the formation type of the rotary drilling rig when the working condition of the rotary drilling rig is identified as drilling. The second state data includes vibration type data and non-vibration type data.

[0042] The feature extraction module is used to extract feature data characterizing the stratigraphic type based on the second state data;

[0043] The formation identification and prompting module is used to identify the current formation type being drilled by the rotary drilling rig based on the feature data, and to control the issuance of prompting information for the current formation type.

[0044] The present invention also provides a formation type identification system for rotary drilling, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the formation type identification method for rotary drilling as described above.

[0045] The present invention also provides a rotary drilling rig, including a formation type identification system for rotary drilling as described in any of the above embodiments.

[0046] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the formation type identification method for rotary drilling as described above.

[0047] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the formation type identification method during rotary drilling as described above.

[0048] The method for identifying formation types during rotary drilling provided by this invention can identify the working condition of the rotary drilling rig based on its first state data. When the working condition of the rotary drilling rig is identified as drilling, second state data associated with the formation type can be obtained. Characteristic data representing the formation type can be extracted from the vibration type data and non-vibration type data included in the second state data. Based on the characteristic data, the current formation type of the rotary drilling rig can be identified, and a prompt message for the current formation type can be issued. This achieves automatic identification and prompting of the formation type during the drilling process of the rotary drilling rig. In this way, the operator of the rotary drilling rig can understand the current formation type in real time while operating the rotary drilling rig. Furthermore, the operator can adjust the operating parameters of the rotary drilling rig or replace the appropriate drilling tools according to the current formation type to effectively improve construction efficiency. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating the method for identifying formation types during rotary drilling provided by the present invention.

[0051] Figure 2 This is a schematic diagram of the structure provided by the present invention for displaying prompt information about the current stratigraphic type on a display screen;

[0052] Figure 3 This is a schematic diagram of the formation type identification device during rotary drilling provided by the present invention;

[0053] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention.

[0054] Figure label:

[0055] 210: Display screen; 220: Formation type display area; 310: Working condition identification module; 320: Data acquisition module; 330: Feature extraction module; 340: Formation identification prompt module; 410: Processor; 420: Communication interface; 430: Memory; 440: Communication bus. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0057] This embodiment provides a method for identifying formation types during rotary drilling, which can be executed by the controller in the rotary drilling rig, such as... Figure 1 As shown, the method for identifying the formation type during rotary drilling may include:

[0058] Step 110: Identify the working condition of the rotary drilling rig based on the first state data of the rotary drilling rig.

[0059] A rotary drilling rig includes an upper slewing platform, on which are mounted a main pump, auxiliary pump, engine, main winch, and power head, etc. The engine drives the main and auxiliary pumps to supply oil to the main winch and power head and other actuators. The main winch controls the raising and lowering of the power head; the depth at which it is lowered is called the lowering depth.

[0060] The first state data of a rotary drilling rig is data associated with its operating conditions, used to identify these conditions. This data may include, for example, engine speed, engine torque, main pump pressure, auxiliary pump pressure, slewing angle, lowering depth, and hole depth. Hole depth is also known as borehole depth. The slewing angle refers to the slewing angle of the upper slewing platform.

[0061] The operating conditions of a rotary drilling rig can include no construction, idling, rotation, lowering, lifting, soil dumping, hole cleaning, drilling, and other operating conditions.

[0062] Step 120: When the working condition of the rotary drilling rig is identified as drilling, the second state data associated with the formation type of the rotary drilling rig is obtained. The second state data includes vibration type data and non-vibration type data.

[0063] Here, the second state data is used for stratigraphic type identification. Stratigraphic types can be classified according to hardness, for example including soil, soft rock (e.g., strongly weathered rock), medium-hard rock (e.g., sandstone), and very hard rock (e.g., granite).

[0064] When the rotary drilling rig is in drilling mode, the formation type can be identified. When the rotary drilling rig is not in drilling mode, the formation type identification is not required.

[0065] The vibration type data refers to the vibration data from the rotary drilling rig, including, for example, the vibration signal from the power head. When the power head of the rotary drilling rig reaches different formation types, the vibration patterns generated by the power head vary due to differences in hardness. Therefore, the current formation type can be identified by combining the power head vibration signal. In practice, a vibration sensor can be installed on the power head, and the vibration sensor can transmit the power head vibration signal via Ethernet User Datagram Protocol (UDP). The controller can receive the power head vibration signal collected by the vibration sensor.

[0066] Non-vibration type data refers to state data related to the formation type, excluding the vibration data of the rotary drilling rig. For example, the non-vibration type data includes the power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average feed rate. When the rotary drilling rig's power head reaches different formation types, due to differences in hardness, the power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average feed rate will also change accordingly. Therefore, the current formation type can be identified by combining the power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average feed rate.

[0067] In practice, the torque of the rotary drilling rig can be collected by the torque sensor on the power head, the rotational speed of the power head can be collected by the rotational speed sensor on the power head, the engine speed can be collected by the rotational speed sensor on the engine, the average drilling speed can be obtained based on the depth sensor on the main winch, and the pressure of the power head can be obtained by the pressure sensor. When the data of each sensor is transmitted to the controller, non-vibration type data can be transmitted through CAN.

[0068] If outliers or missing values ​​are found in the received non-vibration type data and vibration type data, the values ​​adjacent to the outliers will be used to replace them, or the values ​​adjacent to the missing values ​​will be used to supplement them, in order to avoid interruption of stratum identification and affect construction. Outliers include values ​​that exceed the preset range.

[0069] Step 130: Extract feature data representing the stratigraphic type based on the second state data.

[0070] Step 140: Identify the current formation type being drilled by the rotary drilling rig based on the feature data, and control the system to issue a prompt message indicating the current formation type.

[0071] In this embodiment, the operating condition of the rotary drilling rig can be identified based on its first state data. When the operating condition of the rotary drilling rig is identified as drilling, second state data associated with the formation type can be obtained. Characteristic data representing the formation type can be extracted from the vibration type data and non-vibration type data included in the second state data. Then, based on the characteristic data, the current formation type of the rotary drilling rig can be identified, and the rotary drilling rig can be controlled to issue a prompt message about the current formation type. This achieves automatic identification and prompting of the formation type during the drilling process of the rotary drilling rig. In this way, the operator of the rotary drilling rig can understand the current formation type in a timely and accurate manner during the drilling process. Furthermore, the operator can adjust the operating parameters of the rotary drilling rig, replace the drill bit and drilling tools that are more suitable for the current formation type, or change the construction method according to the current formation type, thereby effectively improving construction efficiency.

[0072] In an exemplary embodiment, the step of extracting feature data characterizing the formation type based on the second state data may specifically include:

[0073] Obtain statistical data of the non-vibration type data within a preset unit time period;

[0074] Obtain statistical data of the vibration type data within the preset unit time period;

[0075] The statistical data of the non-vibration type data within the preset unit time period is fused with the statistical data of the vibration type data to obtain the feature data within the preset unit time period.

[0076] For example, the preset unit of time can be seconds, minutes, etc. For instance, statistical data A and B of the non-vibration type data and statistical data C and D of the vibration type data can be obtained per second. The statistical data A and B of the non-vibration type data and the statistical data C and D of the vibration type data per second are concatenated to obtain A, B, C, and D, which serve as the feature data per second. If there are 80 seconds, 80 feature data points are obtained. Each feature data point is used to identify a corresponding geological formation type.

[0077] In practical applications, vibration data is collected at a higher frequency than non-vibration data, and the collection frequencies of non-vibration data are not entirely the same. To facilitate the fusion of the two types of data, in this embodiment, within each preset unit time period, statistics are obtained for non-vibration data and vibration data. Then, the statistics of non-vibration data and vibration data are spliced ​​together to fuse them and obtain a feature data for the preset unit time period. This method is not only simple to operate, but also accurately reflects the characteristics of the stratigraphic type, which is conducive to the rapid and accurate identification of stratigraphic types.

[0078] In an exemplary embodiment, when the vibration type data includes a power head vibration signal, the power head vibration signal includes vibration components in three orthogonal directions. Accordingly, obtaining the statistical data of the vibration type data within the preset unit time period may specifically include:

[0079] The first step is to statistically analyze the vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period to obtain the time-domain statistical data of the power head vibration signal in each orthogonal direction within the preset unit time period. The time-domain statistical data may include at least one of the following: skewness, kurtosis, peak value, root mean square, margin factor, and waveform factor.

[0080] For example, the vibration signal of the power head may include vibration components in three orthogonal directions: the x-axis, y-axis, and z-axis.

[0081] The vibration signal of the power head acquired by the vibration sensor is a vibration signal in the time domain. Skewness, kurtosis, peak value, root mean square (RMS), margin factor, and waveform factor are the time-domain characteristics of the vibration signal. When the power head of a rotary drilling rig reaches different types of strata, the vibration patterns generated by the power head vary due to differences in hardness. The time-domain characteristics of the power head vibration signal can reflect these different vibration patterns. Therefore, the vibration components of the power head vibration signal in the three orthogonal directions (x-axis, y-axis, and z-axis) within a preset unit time period can be statistically analyzed to obtain time-domain statistical data in the three orthogonal directions. For example, the skewness, kurtosis, peak value, RMS, margin factor, and waveform factor in the three orthogonal directions can be obtained by statistically analyzing the vibration components of the power head vibration signal in the three orthogonal directions (x-axis, y-axis, and z-axis) per second. Thus, the time-domain statistical data obtained per second includes 18 data items.

[0082] The second step involves performing a Fourier transform on the vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period to obtain the power density spectrum in each orthogonal direction within the preset unit time period; and then statistically analyzing the power density spectrum in each orthogonal direction within the preset unit time period to obtain frequency domain statistical data for each orthogonal direction within the preset unit time period. The frequency domain statistical data may include at least one of the following: the power mean of the power density spectrum over the entire frequency range, the power variance of the power density spectrum over the entire frequency range, the power mean corresponding to each frequency sub-interval in the power density spectrum, and the power variance corresponding to each frequency sub-interval in the power density spectrum.

[0083] After performing Fourier transforms on the vibration components of the power head vibration signal in the three orthogonal directions of x-axis, y-axis and z-axis within a preset unit time, the power density spectrum in the three orthogonal directions of x-axis, y-axis and z-axis within the preset unit time can be obtained. This power density spectrum characterizes the distribution of signal power at different frequencies.

[0084] In practice, the mean and variance of the power at each frequency within the entire frequency range of the power density spectrum can be calculated to obtain the power mean and power variance for the entire frequency range of the power density spectrum. Alternatively, the entire frequency range of the power density spectrum can be divided into multiple frequency sub-ranges, and the mean and variance of the power at each frequency within a single frequency sub-range can be calculated to obtain the corresponding power mean and power variance for that sub-range. This allows for the acquisition of frequency domain statistical data in three orthogonal directions: the x-axis, y-axis, and z-axis, thus revealing the frequency domain characteristics of the power head vibration signal. By dividing the entire frequency range of the power density spectrum into multiple frequency sub-ranges, local frequency domain characteristics can be preserved, resulting in more accurate feature data.

[0085] The number of frequency sub-intervals can be set according to the actual situation. For example, the number of frequency sub-intervals is within the preset range, such as 5 to 10, which can preserve the local frequency domain characteristics without affecting the efficiency of stratum identification.

[0086] When the power head of a rotary drilling rig reaches different types of strata, the vibration generated by the power head will vary due to the different hardness of the strata. The frequency domain characteristics of the vibration signal of the power head can also reflect the different vibration conditions.

[0087] For example, if the number of frequency sub-intervals is 10, the power density spectrum of the power head vibration signal in the three orthogonal directions (x-axis, y-axis, and z-axis) per second is statistically analyzed to obtain the following data in the three orthogonal directions: the power mean of the power density spectrum across the entire frequency interval, the power variance of the power density spectrum across the entire frequency interval, the power mean of each frequency sub-interval in the power density spectrum, and the power variance of each frequency sub-interval in the power density spectrum. Thus, the frequency domain statistical data obtained per second includes 66 data items.

[0088] The third step is to use the time-domain statistical data and the frequency-domain statistical data of each orthogonal direction within the preset unit time as the statistical data of the vibration type data within the preset unit time.

[0089] Specifically, the time-domain statistical data and the frequency-domain statistical data for each orthogonal direction within the preset unit time period are concatenated to obtain the statistical data of the vibration type data within the preset unit time period. For example, concatenating the 18 data items of the time-domain statistical data and the 66 data items of the frequency-domain statistical data mentioned above yields statistical data of vibration type data per second, including 84 data items.

[0090] In this embodiment, by statistically analyzing the vibration signal of the power head in the time and frequency domains, the statistical data of the vibration type data obtained is very rich, which can further improve the accuracy of formation type identification.

[0091] In an exemplary embodiment, when the non-vibration type data includes power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average feed rate, obtaining statistical data of the non-vibration type data within a preset unit time period may specifically include: calculating the average value of the power head rotation speed, the average value of the power head torque, the average value of the power head pressurization pressure, the average value of the engine speed, and the average value of the average feed rate within the preset unit time period as statistical data of the non-vibration type data within the preset unit time period.

[0092] For example, the average values ​​of the power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average advance rate per second can be statistically analyzed. This yields five data points for the non-vibration type data per second. Combined with the 84 data points for the vibration type data per second, the final characteristic data per second comprises 89 data points. Thus, combining these 89 multimodal data points for formation type identification results in more comprehensive data and more accurate identification.

[0093] In this embodiment, the average values ​​of the power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average feed rate within each preset unit time period are directly calculated. This integrates the power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average feed rate within a preset unit time period into a single data set, simplifying the calculation and improving processing efficiency.

[0094] Of course, the sum of the power head rotation speed, the sum of the power head torque, the sum of the power head pressurization pressure, the sum of the engine speed, and the sum of the average feed rate can also be calculated separately per second, and so on.

[0095] In an exemplary embodiment, identifying the current formation type drilled by the rotary drilling rig based on the feature data may specifically include:

[0096] The feature data is input into the stratigraphic type identification model to obtain the current stratigraphic type output by the stratigraphic type identification model;

[0097] The stratigraphic type identification model is obtained by training a random forest model based on feature data samples and corresponding stratigraphic type samples.

[0098] In practical applications, vibration type data samples and non-vibration type data samples can be pre-collected and pre-processed, including handling missing and outlier values. Then, based on the pre-processed vibration type data samples and non-vibration type data samples, feature data samples characterizing the stratigraphic type are extracted. The stratigraphic type samples corresponding to the feature data samples are labeled, and the feature data samples and labeled stratigraphic type samples are input into a random forest model for training, resulting in a stratigraphic type identification model. This stratigraphic type identification model is used to identify stratigraphic types based on the feature data.

[0099] In this embodiment, the implicit relationship between the feature data samples representing stratigraphic types and the corresponding stratigraphic type samples is learned through a random forest model, which can quickly identify stratigraphic types, is less prone to overfitting, has noise resistance, and has a higher accuracy in stratigraphic type identification.

[0100] Of course, other machine learning models can also be used to train a stratigraphic type identification model.

[0101] The above is merely an example of one way to identify the current formation type of the rotary drilling rig based on the feature data. Other methods can also be used, such as converting each data item in the feature data into a score corresponding to each data item according to a preset correspondence between the value and the score, weighting and summing the scores, and determining the current formation type of the rotary drilling rig based on the summation result, etc.

[0102] In an exemplary embodiment, the control issuing a prompt message about the current formation type may specifically include: controlling the display screen in the rotary drilling rig to display the prompt message about the current formation type.

[0103] The rotary drilling rig includes a display screen that shows information indicating the current formation type, making it more intuitive and convenient for the operator to view the formation type. This information can be text or an image representing the formation type, etc.

[0104] As a preferred embodiment, the display screen in the rotary drilling rig can be controlled to display the current formation type information in an image format. For example, a formation type display area 220 can be set in the display screen 210, and the current formation type can be displayed in real time in the formation type display area 220, as shown in the following example. Figure 2 As shown in the image, by using images, the operator can have a clear view of the situation below the hole. This allows the operator to control the working parameters in a timely and accurate manner, or to change the working tools or optimize the construction method as needed, thereby maximizing work efficiency.

[0105] In an exemplary embodiment, when the first state data includes engine speed, engine torque, main pump pressure, auxiliary pump pressure, slewing angle, lowering depth, and drilling depth, identifying the operating condition of the rotary drilling rig based on the first state data of the rotary drilling rig may specifically include:

[0106] When the first state data meets the drilling conditions, the operating condition of the rotary drilling rig is determined to be drilling; wherein, the drilling conditions include:

[0107] The engine speed is greater than the preset speed;

[0108] The pressure of the main pump or the pressure of the auxiliary pump is greater than the preset pressure;

[0109] The rotation angle is within a preset angle range;

[0110] The engine torque is greater than the preset torque;

[0111] The lowering depth is greater than or equal to zero;

[0112] The change in the lowering depth is greater than zero;

[0113] The lowering depth is greater than or equal to the hole forming depth.

[0114] In practical applications, various working conditions of rotary drilling rigs can be accurately identified by combining engine speed, engine torque, main pump pressure, auxiliary pump pressure, slewing angle, lowering depth, and drilling depth. For example:

[0115] 1. If the engine speed is less than or equal to the preset speed, the rotary drilling rig is in a non-operational condition.

[0116] 2. If the engine speed is greater than the preset speed and the pressure of the main pump or auxiliary pump is less than or equal to the preset pressure, the rotary drilling rig is in idle condition.

[0117] 3. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the slewing angle exceeds the preset angle range, and the lowering depth is less than 0, then the working condition of the rotary drilling rig is slewing.

[0118] IV. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the rotation angle exceeds the preset angle range, and the lowering depth is greater than or equal to 0, then the operating condition of the rotary drilling rig is other operating condition.

[0119] 5. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the slewing angle is within the preset angle range, the engine torque is greater than the preset torque, and the lowering depth is less than 0, then the working condition of the rotary drilling rig is soil dumping.

[0120] VI. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the slewing angle is within the preset angle range, the engine torque is greater than the preset torque, the lowering depth is greater than or equal to 0, and the change in lowering depth is less than or equal to 0, then the operating condition of the rotary drilling rig is "other operating condition". Here, the change in lowering depth refers to the change in lowering depth between two adjacent data acquisition times.

[0121] 7. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the rotation angle is within the preset angle range, the engine torque is greater than the preset torque, the lowering depth is greater than or equal to 0, the change in the lowering depth is greater than or equal to 0, and the lowering depth is less than the hole depth, then the working condition of the rotary drilling rig is hole cleaning.

[0122] 8. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the rotation angle is within the preset angle range, the engine torque is greater than the preset torque, the lowering depth is greater than or equal to 0, the change in the lowering depth is greater than or equal to the hole depth, then the working condition of the rotary drilling rig is drilling.

[0123] 9. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the rotation angle is within the preset angle range, 0 ≤ the engine torque ≤ the preset torque, and the change in the lowering depth is greater than 0, then the working condition of the rotary drilling rig is lowering.

[0124] 10. If the engine speed is greater than the preset speed, and the pressure of the main pump or auxiliary pump is greater than the preset pressure, the rotation angle is within the preset angle range, 0 ≤ the engine torque ≤ the preset torque, and the change in the lowering depth ≤ 0, then the working condition of the rotary drilling rig is lifting.

[0125] The following describes the formation type identification device for rotary drilling provided by the present invention. The formation type identification device for rotary drilling described below and the formation type identification method for rotary drilling described above can be referred to in correspondence.

[0126] This embodiment provides a formation type identification device for rotary drilling, such as... Figure 3 As shown, it includes:

[0127] The working condition identification module 310 is used to identify the working condition of the rotary drilling rig based on the first state data of the rotary drilling rig.

[0128] The data acquisition module 320 is used to acquire second state data associated with the formation type of the rotary drilling rig when the working condition of the rotary drilling rig is identified as drilling. The second state data includes vibration type data and non-vibration type data.

[0129] Feature extraction module 330 is used to extract feature data characterizing the stratigraphic type based on the second state data;

[0130] The formation identification prompt module 340 is used to identify the current formation type being drilled by the rotary drilling rig based on the feature data, and to control the issuance of prompt information for the current formation type.

[0131] In an exemplary embodiment, the feature extraction module 330 is specifically used for:

[0132] Obtain statistical data of the non-vibration type data within a preset unit time period;

[0133] Obtain statistical data of the vibration type data within the preset unit time period;

[0134] The statistical data of the non-vibration type data within the preset unit time period is fused with the statistical data of the vibration type data to obtain the feature data within the preset unit time period.

[0135] In an exemplary embodiment, the vibration type data includes a power head vibration signal, which includes vibration components in three orthogonal directions;

[0136] Feature extraction module 330 is specifically used for:

[0137] The vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period are statistically analyzed to obtain the time-domain statistical data of the power head vibration signal in each orthogonal direction within the preset unit time period. The time-domain statistical data may include at least one of the following: skewness, kurtosis, peak value, root mean square, margin factor, and waveform factor;

[0138] The vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period are subjected to Fourier transform to obtain the power density spectrum of each orthogonal direction within the preset unit time period; the power density spectrum of each orthogonal direction within the preset unit time period is statistically analyzed to obtain the frequency domain statistical data of each orthogonal direction within the preset unit time period. The frequency domain statistical data may include at least one of the following: the power mean of the power density spectrum over the entire frequency range, the power variance of the power density spectrum over the entire frequency range, the power mean corresponding to each frequency sub-interval in the power density spectrum, and the power variance corresponding to each frequency sub-interval in the power density spectrum;

[0139] The time-domain statistical data and the frequency-domain statistical data for each orthogonal direction within the preset unit time period are used as the statistical data for the vibration type data within the preset unit time period.

[0140] In an exemplary embodiment, the non-vibration type data includes power head rotation speed, power head torque, power head pressurization pressure, engine speed, and average feed rate;

[0141] Feature extraction module 330 is specifically used for:

[0142] The average values ​​of the power head rotation speed, the power head torque, the power head pressurization pressure, the engine speed, and the average feed rate are statistically analyzed within the preset unit time period.

[0143] In an exemplary embodiment, the formation identification prompting module 340 is specifically used for:

[0144] The feature data is input into the stratigraphic type identification model to obtain the current stratigraphic type output by the stratigraphic type identification model;

[0145] The stratigraphic type identification model is obtained by training a random forest model based on feature data samples and corresponding stratigraphic type samples.

[0146] In an exemplary embodiment, the formation identification prompting module 340 is specifically used for:

[0147] The display screen in the rotary drilling rig displays a prompt message indicating the current formation type.

[0148] In an exemplary embodiment, the first state data includes engine speed, engine torque, main pump pressure, auxiliary pump pressure, rotation angle, lowering depth, and drilling depth;

[0149] The operating condition identification module 310 is specifically used for:

[0150] When the first state data meets the drilling conditions, the operating condition of the rotary drilling rig is determined to be drilling; wherein, the drilling conditions include:

[0151] The engine speed is greater than the preset speed;

[0152] The pressure of the main pump or the pressure of the auxiliary pump is greater than the preset pressure;

[0153] The rotation angle is within a preset angle range;

[0154] The engine torque is greater than the preset torque;

[0155] The lowering depth is greater than or equal to zero;

[0156] The change in the lowering depth is greater than zero;

[0157] The lowering depth is greater than or equal to the hole forming depth.

[0158] This embodiment also provides a formation type identification system for rotary drilling, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the formation type identification method for rotary drilling as provided in any of the above embodiments. The processor may be the controller described above.

[0159] The memory could be the memory in the display screen of the rotary drilling rig, or a hard drive, etc.

[0160] In an exemplary embodiment, the formation type identification system during rotary drilling also includes a vibration sensor disposed on the power head, which is used to collect vibration signals from the power head.

[0161] In an exemplary embodiment, the formation type identification system during rotary drilling further includes:

[0162] The speed sensor on the power head is used to collect the speed of the power head;

[0163] The engine speed sensor is used to collect engine speed data;

[0164] The depth sounding sensor on the main winch is used to obtain the average feed rate;

[0165] A pressure sensor is used to obtain the pressure applied by the power head.

[0166] This embodiment also provides a rotary drilling rig, including a formation type identification system for rotary drilling as provided in any of the above embodiments.

[0167] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute a formation type identification method during rotary drilling, the method including:

[0168] The operating condition of the rotary drilling rig is identified based on the first state data of the rotary drilling rig;

[0169] When the working condition of the rotary drilling rig is identified as drilling, the second state data associated with the formation type of the rotary drilling rig is obtained. The second state data includes vibration type data and non-vibration type data.

[0170] Based on the second state data, feature data characterizing the stratigraphic type are extracted;

[0171] Based on the feature data, the current formation type of the rotary drilling rig is identified, and a prompt message indicating the current formation type is issued.

[0172] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a 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 several 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 described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0173] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the formation type identification method during rotary drilling provided by the above methods, the method comprising:

[0174] The operating condition of the rotary drilling rig is identified based on the first state data of the rotary drilling rig;

[0175] When the working condition of the rotary drilling rig is identified as drilling, the second state data associated with the formation type of the rotary drilling rig is obtained. The second state data includes vibration type data and non-vibration type data.

[0176] Based on the second state data, feature data characterizing the stratigraphic type are extracted;

[0177] Based on the feature data, the current formation type of the rotary drilling rig is identified, and a prompt message indicating the current formation type is issued.

[0178] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned methods for identifying formation types during rotary drilling, the method comprising:

[0179] The operating condition of the rotary drilling rig is identified based on the first state data of the rotary drilling rig;

[0180] When the working condition of the rotary drilling rig is identified as drilling, the second state data associated with the formation type of the rotary drilling rig is obtained. The second state data includes vibration type data and non-vibration type data.

[0181] Based on the second state data, feature data characterizing the stratigraphic type are extracted;

[0182] Based on the feature data, the current formation type of the rotary drilling rig is identified, and a prompt message indicating the current formation type is issued.

[0183] The device embodiments described above are merely illustrative. The units described 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 modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0184] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0185] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying a ground type during rotary drilling, characterized by, include: The operating condition of the rotary drilling rig is identified based on the first state data of the rotary drilling rig; When the working condition of the rotary drilling rig is identified as drilling, the second state data associated with the formation type of the rotary drilling rig is obtained. The second state data includes vibration type data and non-vibration type data. Based on the second state data, feature data characterizing the formation type is extracted; including: obtaining statistical data of the non-vibration type data within a preset unit time period; obtaining statistical data of the vibration type data within the preset unit time period; and fusing the statistical data of the non-vibration type data within the preset unit time period with the statistical data of the vibration type data to obtain the feature data within the preset unit time period; The vibration type data includes a power head vibration signal, which includes vibration components in three orthogonal directions. Obtaining statistical data of the vibration type data within the preset unit time period includes: statistically analyzing the vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period to obtain time-domain statistical data of the power head vibration signal in each orthogonal direction within the preset unit time period; performing Fourier transform on the vibration components of the power head vibration signal in each orthogonal direction within the preset unit time period to obtain the power density spectrum in each orthogonal direction within the preset unit time period; and statistically analyzing the power density spectrum in each orthogonal direction within the preset unit time period to obtain frequency-domain statistical data of each orthogonal direction within the preset unit time period. Based on the feature data, the current formation type of the rotary drilling rig is identified, and a prompt message indicating the current formation type is issued.

2. The method for identifying formation types during rotary drilling according to claim 1, characterized in that, The non-vibration type data includes power head speed, power head torque, power head pressurization pressure, engine speed, and average feed rate. The statistical data obtained within a preset unit time period for the non-vibration type data includes: The average values ​​of the power head rotation speed, the power head torque, the power head pressurization pressure, the engine speed, and the average feed rate are statistically analyzed within the preset unit time period.

3. The method for identifying formation types during rotary drilling according to claim 1, characterized in that, The step of identifying the current formation type drilled by the rotary drilling rig based on the feature data includes: The feature data is input into the stratigraphic type identification model to obtain the current stratigraphic type output by the stratigraphic type identification model; The stratigraphic type identification model is obtained by training a random forest model based on feature data samples and corresponding stratigraphic type samples.

4. The method for identifying formation types during rotary drilling according to claim 1, characterized in that, The control system issues a prompt message regarding the current formation type, including: The display screen in the rotary drilling rig displays a prompt message indicating the current formation type.

5. The method for identifying formation types during rotary drilling according to any one of claims 1 to 4, characterized in that, The first state data includes engine speed, engine torque, main pump pressure, auxiliary pump pressure, rotation angle, lowering depth, and drilling depth; The process of identifying the operating condition of the rotary drilling rig based on its first state data includes: When the first state data meets the drilling conditions, the operating condition of the rotary drilling rig is determined to be drilling; wherein, the drilling conditions include: The engine speed is greater than the preset speed; The pressure of the main pump or the pressure of the auxiliary pump is greater than the preset pressure; The rotation angle is within a preset angle range; The engine torque is greater than the preset torque; The lowering depth is greater than or equal to zero; The change in the lowering depth is greater than zero; The lowering depth is greater than or equal to the hole forming depth.

6. A formation type identification device for rotary drilling, characterized in that, include: The working condition identification module is used to identify the working condition of the rotary drilling rig based on the first state data of the rotary drilling rig. The data acquisition module is used to acquire second state data associated with the formation type of the rotary drilling rig when the working condition of the rotary drilling rig is identified as drilling. The second state data includes vibration type data and non-vibration type data. A feature extraction module is used to extract feature data characterizing the formation type based on the second state data; including: obtaining statistical data of the non-vibration type data within a preset unit time period; obtaining statistical data of the vibration type data within the preset unit time period; fusing the statistical data of the non-vibration type data and the statistical data of the vibration type data within the preset unit time period to obtain the feature data within the preset unit time period; the vibration type data includes a dynamic head vibration signal, and the dynamic head vibration signal includes vibration components in three orthogonal directions; obtaining the statistical data of the vibration type data within the preset unit time period includes: statistically analyzing the vibration components of the dynamic head vibration signal in each orthogonal direction within the preset unit time period to obtain time-domain statistical data of the dynamic head vibration signal in each orthogonal direction within the preset unit time period; performing Fourier transform on the vibration components of the dynamic head vibration signal in each orthogonal direction within the preset unit time period to obtain the power density spectrum in each orthogonal direction within the preset unit time period; and statistically analyzing the power density spectrum in each orthogonal direction within the preset unit time period to obtain frequency-domain statistical data of each orthogonal direction within the preset unit time period. The formation identification and prompting module is used to identify the current formation type being drilled by the rotary drilling rig based on the feature data, and to control the issuance of prompting information for the current formation type.

7. A formation type identification system for rotary drilling, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the formation type identification method for rotary drilling as described in any one of claims 1 to 5.

8. A rotary drilling rig, characterized in that, Includes the formation type identification system during rotary drilling as described in claim 7.

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