Well logging while drilling high-speed transmission system and method based on multi-mode combination

Abstract

The invention provides a logging-while-drilling high-speed transmission system and method based on multi-modal combination, and belongs to the technical field of oil exploration and logging-while-drilling, the logging-while-drilling high-speed transmission system comprises an underground acquisition unit, a transmission unit and a ground decoding unit, the underground acquisition unit continuously acquires multiple types of stratum parameters in the drilling process of a drilling tool and generates standardized data frames, and the transmission unit transmits the standardized data frames to the ground decoding unit; the transmission unit selects different transmission modes to transmit standardized data frames in real time, the ground decoding unit comprises an independent decoding layer, a redundancy check layer and a fusion layer, and the independent decoding layer performs wavelet transformation on the standardized data frames to separate modal signals corresponding to the transmission modes; the redundancy check layer marks conflict data with low consistency by calculating correlation among different modal signals and repairs the conflict data, the fusion layer constructs a probability fusion model based on a Bayesian network, and output data of the redundancy check layer is input into the probability fusion model to obtain decoded stratum parameters. According to the invention, efficient and reliable transmission of underground data can be effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of petroleum exploration and logging while drilling, and in particular relates to a high-speed transmission system and method for logging while drilling based on multi-modal combination. Background Art

[0002] Logging while drilling (LWD) is a key technology for acquiring real-time formation parameters during oil drilling. Its core lies in the efficient transmission of multimodal logging data, such as resistivity, acoustic waves, gamma, and pressure. Traditional LWD transmission systems primarily utilize a single transmission mode, such as mud pulses or cable transmission, which suffers from low transmission rates and weak anti-interference capabilities.

[0003] For example, a mud pulse signal denoising method, device, equipment and storage medium disclosed in Chinese patent application number 202411594200.4 constructs a linear mud pulse signal model and denoises the mud pulse signal based on a standard Kalman filter algorithm. However, since the mud pulse signal is subject to nonlinear interference, the linear model has a low fit, and the standard Kalman filter algorithm is difficult to adapt to a variable noise environment and has low filtering accuracy for nonlinear interference, resulting in poor denoising effect.

[0004] Another example is a method, system, terminal, and medium for processing mud pressure wave signals in logging while drilling (LWD), disclosed in Chinese patent application number 202311465807.8. The method first collects a signal as a noise sample and obtains its frequency domain characteristics when the mud pump is turned on. When the downhole instrument is operating, it collects the pressure fluctuation signal and calculates the spectral characteristics. The frequency domain characteristic points of the two are then compared to select a bandpass or bandstop filter to filter out the noise frequency. Finally, the mud pump is restarted, and the filtered pressure wave signal is decoded to complete the processing. If the filtering effect is not good or the operating parameters change, the above steps are repeated. However, in LWD pressure wave transmission technology, the mud pressure wave signal is affected by many factors, and the signal collected on the ground is interfered with by mud pump noise and other factors.

[0005] Furthermore, existing denoising techniques are typically based on preset filter / signal processing method parameters, with engineers adjusting these parameters based on experience. This results in low signal recognition success rates and poor adaptability across different operating areas. Summary of the Invention

[0006] The purpose of the present invention is to propose a high-speed transmission system and method for logging while drilling based on multi-modal combination, which can effectively improve the efficient and reliable transmission of downhole data.

[0007] The present invention is achieved through the following technical solutions: A high-speed transmission system for logging while drilling based on multi-modal combination includes a downhole acquisition unit, a transmission unit and a ground decoding unit. The downhole acquisition unit continuously collects multiple types of formation parameters and generates standardized data frames during the drilling process of the drill bit. The transmission unit selects different transmission modes according to the formation parameter category, well depth and mud viscosity to transmit the standardized data frames in real time. The ground decoding unit includes an independent decoding layer, a redundant check layer and a fusion layer. The independent decoding layer performs wavelet transform on the received standardized data frames to separate the modal signals corresponding to each transmission mode. The redundant check layer marks conflicting data with low consistency by calculating the correlation between different modal signals and repairs the conflicting data. The fusion layer constructs a probabilistic fusion model based on a Bayesian network. The output data of the redundant check layer is input into the probabilistic fusion model to obtain decoded formation parameters. The transmission modes include mud pulse mode, electromagnetic wave mode and optical fiber mode.

[0008] Furthermore, the downhole acquisition unit includes an ultrasonic imaging device, a resistivity imaging device and a conventional logging instrument installed in the drilling tool. The formation parameters acquired by the downhole acquisition unit include ultrasonic imaging data, resistivity imaging data and conventional logging data. The conventional logging instrument includes a natural gamma meter, a natural potential logging instrument, an acoustic logging instrument, a density logging instrument, a resistivity logging instrument and a caliper logging instrument. The conventional logging data includes natural gamma related to lithology, natural potential related to lithology and permeability, acoustic wave time difference related to porosity and permeability, formation density related to porosity, formation resistivity related to oil and water layers, and wellbore diameter related to well wall conditions.

[0009] Furthermore, the transmission unit selects different transmission modes to transmit the formation parameters in real time according to the formation parameter category, well depth and mud viscosity. Specifically, when the well depth is less than a set well depth threshold and the mud viscosity is less than a set viscosity threshold, the transmission unit selects the electromagnetic wave mode and the optical fiber mode for joint transmission; otherwise, the transmission unit selects the mud pulse mode and the optical fiber mode for joint transmission. When the electromagnetic wave mode and the optical fiber mode are selected for joint transmission, for the ultrasonic imaging data and the resistivity imaging data, at least 80% of the total data volume of the ultrasonic imaging data and 80% of the total data volume of the resistivity imaging data are transmitted using the optical fiber mode. 0%, and the remaining data is transmitted using the electromagnetic wave mode. For conventional logging parameters, at least 60% of the conventional logging data is transmitted using the optical fiber mode, and the remaining data is transmitted using the electromagnetic wave mode. When the mud pulse mode and the optical fiber mode are jointly transmitted, for ultrasonic imaging data and resistivity imaging data, at least 80% of the total ultrasonic imaging data and 80% of the total resistivity imaging data are transmitted using the optical fiber mode, and the remaining data is transmitted using the mud pulse mode. For conventional logging parameters, at least 60% of the conventional logging data is transmitted using the optical fiber mode, and the remaining data is transmitted using the mud pulse mode.

[0010] Furthermore, the downhole acquisition unit embeds different identification fields in the headers of standardized data frames corresponding to ultrasonic imaging data, resistivity imaging data and conventional logging data, and the transmission unit determines the category of the transmitted data according to the identification fields.

[0011] Furthermore, the transmission unit includes a mud pulse modulator, an electromagnetic wave coupler and an optical fiber slip ring. The mud pulse modulator is used to encode data into pressure waves and form a mud pulse mode with a low-frequency transmission channel of 0~10kHz. The electromagnetic wave coupler is used to encode data into electromagnetic waves and form an electromagnetic wave mode with a medium-frequency transmission channel of 10kHz~1MHz. The optical fiber slip ring is used to encode data into optical signals and form an optical fiber mode with a high-frequency optical fiber channel.

[0012] Furthermore, the independent decoding layer is based on the formula The received formation parameters x ( t ) to perform wavelet transform, a is the scale parameter, b is the translation parameter, is the mother wavelet function, when setting a When >100, the modal signal corresponding to the mud pulse mode is obtained , when setting 10< a When ≤100, the modal signal corresponding to the electromagnetic wave mode is obtained , when setting a When <10, the modal signal corresponding to the optical fiber mode is obtained .

[0013] Furthermore, the redundant check layer is based on the formula Calculating modal information S i With modal information S j If the mutual information between I ( S i , S j )<information threshold, then the modal information is determined S i With modal information S j For conflicting data, according to the formula Calculating modal information S i With modal information S j The correlation, if C ij < correlation threshold, the modal information S i With modal informationS j Conflicting data points are marked as having low consistency, otherwise they are not marked. i , j =1,2,3 and i ≠ j , To calculate information entropy, Modal information S i No. k Sample data, N Modal information S i The number of sample data, Indicates when Returns 1 if yes, otherwise returns 0, 1≤ k ≤ N .

[0014] Furthermore, the redundancy check layer also includes an adaptive equalizer, and the marked conflicting data points are used as input of the adaptive equalizer. The adaptive equalizer adopts the minimum mean square error algorithm, and dynamically adjusts the step size factor of the minimum mean square error algorithm according to the error between the output and input of the adaptive equalizer to repair the conflicting data, and uses the repaired data and the unmarked data together as the new modal information. .

[0015] Furthermore, the probability fusion model of the fusion layer is expressed as ,in, is the decoded formation parameter, is the likelihood function, is the prior probability of the known formation parameters, The modal information when the formation parameter is D The conditional probability of The weighted coefficient is the reliability weight of each known modal information.

[0016] The present invention is also achieved through the following technical solutions: The transmission method of the high-speed transmission system for logging while drilling based on multi-modal combination as described above comprises the following steps: Step S1: continuously collecting multiple types of formation parameters during the drilling process of the drilling tool; Step S2: selecting different transmission modes according to formation parameter type, well depth, and mud viscosity to transmit formation parameters to the surface in real time; Step S3: First, the ground performs a wavelet transform on the received formation parameters to separate the modal signals corresponding to each transmission mode. Then, by calculating the correlation between different modal signals, conflicting data with low consistency is marked and the conflicting data is repaired. Finally, a probabilistic fusion model is constructed based on the Bayesian network. The repaired data and the unmarked data are input into the probabilistic fusion model to obtain the decoded formation parameters, where the transmission modes include mud pulse mode, electromagnetic wave mode and optical fiber mode.

[0017] The present invention has the following beneficial effects: 1. The downhole acquisition unit of the present invention continuously collects multiple types of formation parameters and generates standardized data frames during the drilling process of the drill bit. The transmission unit selects different transmission modes according to the formation parameter category, well depth and mud viscosity to transmit the standardized data frames in real time, which can achieve efficient coordination of multi-modal transmission and effectively improve transmission efficiency. The ground decoding unit includes an independent decoding layer, a redundant check layer and a fusion layer. The independent decoding layer performs wavelet transform on the received standardized data frame to separate the modal signals corresponding to each transmission mode. The redundant check layer calculates the correlation between different modal signals, marks conflicting data with low consistency, and repairs the conflicting data. The fusion layer constructs a probabilistic fusion model based on the Bayesian network. The output data of the redundant check layer is input into the probabilistic fusion model to obtain the decoded formation parameters. It can significantly reduce the impact of the complex downhole environment on the transmission signal. The bit error rate can be reduced by 2 to 3 orders of magnitude compared with the traditional system. It also supports multiple scenario applications such as high-definition imaging and real-time logging, improving the intelligence level of logging while drilling. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described in detail below with reference to the accompanying drawings.

[0019] Figure 1 Schematic diagram of the structure of the system of the present invention.

[0020] Figure 2 Flowchart of the method of the present invention.

[0021] Among them, 1. Resistivity imaging equipment; 2. Ultrasonic imaging equipment; 3. Conventional logging instruments; 4. Conditioning circuit; 5. Mode switching controller; 6. Mud pulse modulator; 7. Electromagnetic wave coupler; 8. Fiber optic slip ring; 9. Ground decoding unit; 10. Main control computer; 11. Drill string; 12. Drilling fluid circulation system. DETAILED DESCRIPTION

[0022] like Figure 1As shown, a multimodal combined logging while drilling (LWD) high-speed transmission system includes a downhole acquisition unit, a transmission unit, a surface decoding unit 9, and a display unit. The surface decoding unit 9 is implemented in a main control computer 10, and the output data of the surface decoding unit 9 is displayed and stored by the main control computer 10. The downhole acquisition unit continuously collects multiple types of formation parameters and generates standardized data frames while the drill bit is running. The transmission unit selects different transmission modes based on the formation parameter type, well depth, and mud viscosity to transmit the standardized data frames in real time. The surface decoding unit 9 includes an independent decoding layer, a redundant check layer, and a fusion layer. The independent decoding layer performs a wavelet transform on the received standardized data frames to separate the modal signals corresponding to each transmission mode. The redundant check layer calculates the correlation between different modal signals, marks conflicting data with low consistency, and repairs the conflicting data. The fusion layer constructs a probabilistic fusion model based on a Bayesian network. The output data of the redundant check layer is input into the probabilistic fusion model for joint decoding to obtain decoded formation parameters. The transmission modes include mud pulse mode, electromagnetic wave mode, and fiber mode.

[0023] The drilling tool includes a vertical drill string 11 and a drilling fluid circulation system 12 connected to the drill string 11. The specific structure of the drilling tool is conventional. The downhole acquisition unit includes an ultrasonic imaging device 2, a resistivity imaging device 1, a conventional logging instrument 3 installed in the drill string 11, and a conditioning circuit 4 connected to the ultrasonic imaging device 2, the resistivity imaging device 1, and the conventional logging instrument 3, respectively. The formation parameters acquired by the downhole acquisition unit include ultrasonic imaging data, resistivity imaging data, and conventional logging data. The conventional logging instrument 3 includes a natural gamma ray meter, a natural potential logger, an acoustic logger, a density logger, a resistivity logger, and a caliper logger. Conventional logging data includes natural gamma ray, natural potential, acoustic wave time difference, formation density, formation resistivity, and wellbore diameter. Natural gamma rays, emitted by radioactive elements in formations, are captured by natural gamma logging instruments and can aid in lithology classification. Natural potential, the potential difference between the formation and the drill fluid measured by natural potential logging instruments, can aid in determining lithology and permeability. Acoustic transit time can be used to correlate porosity with lithology. Formation density, measured by density logging instruments using gamma scattering, can be used to infer porosity. Formation resistivity can be used to identify oil-water layers, and wellbore diameter can be used to reflect wellbore conditions. The downhole acquisition unit also integrates existing temperature and vibration compensation modules, supporting stable data acquisition in environments ranging from -20°C to 170°C and 0 to 20,000g. Conditioning circuit 4 utilizes the NI9237 signal conditioning module, supporting multi-channel analog signal conditioning. It amplifies, filters, and level-converts weak signals output by ultrasonic imaging and resistivity imaging equipment, meeting logging data preprocessing requirements. Ultrasonic imaging equipment 2 utilizes the UIS ultrasonic imaging logging system from COSL, and resistivity imaging equipment 1 utilizes an array resistivity logging module from Jereh.

[0024] Conditioning circuit 4 performs preprocessing, namely converting ultrasonic imaging data, resistivity imaging data, and conventional logging data into standardized data frames. Specifically, the NI 9237 signal conditioning module first filters the ultrasonic imaging data, resistivity imaging data, and conventional logging data with its built-in anti-aliasing filter. The filtered data is then amplified by a programmable gain amplifier. The amplified data is converted into digital quantities by a 24-bit ADC and output to the digital processing unit. The digital processing unit then identifies the data type based on the channel and maps it to a text-defined identification field, such as converting ultrasonic imaging data 0001 to 0x01, resistivity imaging data 0010 to 0x02, and conventional logging data 0100 to 0x04. The data is then concatenated according to a fixed format of frame header 0xAA55 + identification field + data length + digital data body output by the 9237 + CRC16 check bits to generate a standardized data frame containing synchronization identification, type distinction, data body, and error detection functions. The frame is finally output to the transmission unit, completing the process from analog signal conditioning to standardized frame encapsulation. This process is a prior art.

[0025] After preprocessing, the conditioning circuit 4 embeds different identification fields in the header of the standardized data frame. Specifically, the identification field corresponding to the ultrasonic imaging data is "0001", the identification field corresponding to the resistivity imaging data is "0010", and the identification field corresponding to the conventional logging data is "0100".

[0026] The transmission unit includes a mud pulse modulator 6, an electromagnetic wave coupler 7, an optical fiber slip ring 8 and a mode switching controller 5. The mud pulse modulator 6 is used to encode the preprocessed standardized data frame into a pressure wave and form a mud pulse mode with a low-frequency transmission channel of 0 to 10 kHz. The electromagnetic wave coupler 7 is used to encode the preprocessed standardized data frame into an electromagnetic wave and form an electromagnetic wave mode with a medium-frequency transmission channel of 10 kHz to 1 MHz. The optical fiber slip ring 8 is used to encode the preprocessed standardized data frame into an optical signal and form a fiber mode with a high-frequency fiber channel.

[0027] The mode switching controller 5 of the transmission unit selects different transmission modes to transmit the formation parameters in real time according to the formation parameter category, well depth and mud viscosity. Specifically, when the well depth is less than the set well depth threshold and the mud viscosity is less than the set viscosity threshold, the transmission unit selects the electromagnetic wave mode and the optical fiber mode for joint transmission; otherwise, the transmission unit selects the mud pulse mode and the optical fiber mode for joint transmission. The mode switching controller 5 determines the category of the transmitted data through the identification field, and allocates the transmission ratio according to the data category under the joint transmission mode selected by the transmission unit. Specifically, when the electromagnetic wave mode and the optical fiber mode are selected for joint transmission, for ultrasonic imaging data and resistivity imaging data, the optical fiber mode is used to transmit at least 80% of the total ultrasonic imaging data and 80% of the total resistivity imaging data, and the electromagnetic wave mode is used to transmit the remaining data. For conventional logging parameters, the optical fiber mode is used to transmit at least 60% of the conventional logging data, and the electromagnetic wave mode is used to transmit the remaining data. When the mud pulse mode and the optical fiber mode are selected for joint transmission, for ultrasonic imaging data and resistivity imaging data, the optical fiber mode is used to transmit at least 80% of the total ultrasonic imaging data and 80% of the total resistivity imaging data, and the mud pulse mode is used to transmit the remaining data. For conventional logging parameters, the optical fiber mode is used to transmit at least 60% of the conventional logging data, and the mud pulse mode is used to transmit the remaining data.

[0028] The depth encoder on the drill string 11 can directly measure the well depth, and the mud viscosity is detected by a high-temperature and high-pressure mud viscometer installed on the drill string 11. The well depth threshold is set to 3000m, and the viscosity threshold is set to 50mPa.s.

[0029] The mode switching controller 5 is located in the instrument sub in the middle of the drill string 11. The mud pulse modulator 6 is installed at the lower portion of the drill string 11, near the pumping system. The electromagnetic wave coupler 7 surrounds or is embedded in the drill string 11. The fiber optic slip ring 8 is located at the top of the drill string 11, where it connects to the surface top drive system. A rotary joint connects the dynamic drill string 11 to the static surface optical fiber. Each component is designed as a cylindrical unit that adapts to the structure of the drill string 11, ensuring stable operation in high-temperature, high-pressure, and high-vibration environments.

[0030] The ground decoding unit 9 independent decoding layer according to the formula The received formation parameters x ( t ) to perform wavelet transform, a is the scale parameter, b is the translation parameter, As the mother wavelet function, the modal signals corresponding to the three transmission modes are separated by setting the characteristic scale intervals of mud pulse (low frequency), electromagnetic wave (medium frequency), and optical fiber signal (high frequency). a When >100, the modal signal corresponding to the mud pulse mode is obtained , when setting 10< a When ≤100, the modal signal corresponding to the electromagnetic wave mode is obtained , when setting a When <10, the modal signal corresponding to the optical fiber mode is obtained , which can eliminate inter-modal crosstalk.

[0031] The redundant check layer is based on the formula Calculating modal information S i With modal information S j If the mutual information between I ( S i , S j )<information threshold, then the modal information is determined S i With modal information S j For conflicting data, according to the formula Calculating modal information S i With modal information S j The correlation, if C ij < correlation threshold, the modal information S i With modal information S j Conflicting data points are marked as having low consistency, otherwise they are not marked. i , j =1,2,3 and i ≠ j , To calculate information entropy, Modal information S i No. k Sample data, N For modal information S i The number of sample data, Indicates when Returns 1 if yes, otherwise returns 0, 1≤ k ≤ N Among them, the information threshold is set to 0.2 and the correlation threshold is set to 90%.

[0032] The redundancy check layer also includes an adaptive equalizer. The marked conflicting data points are used as input to the adaptive equalizer. The adaptive equalizer uses the minimum mean square error algorithm. The step size factor of the minimum mean square error algorithm is dynamically adjusted according to the error between the output and input of the adaptive equalizer to repair the conflicting data. The repaired data and the unmarked data are used together as the new modal information. .

[0033] More specifically, let the input signal of the adaptive equalizer be , the expected output signal is , the filter coefficient vector is , the iterative update formula is , , is the step factor. When the mud bubble noise breaks out, the error When the amplitude and power increase significantly, the instantaneous increase , let the filter coefficient vector Rapid update, forcibly catch up with the time-varying channel, and gradually reduce the error after the error is reduced due to parameter adjustment and the system approaches a steady state , fine-tune with small steps to avoid parameter oscillation caused by instantaneous fluctuation of mud bubbles. Excessive power, strong mud pulse interference, temporary constraints The upper limit prevents the equalizer from diverging due to excessive step sizes. In the early stages of iteration, a larger base step size and error feedback acceleration are proactively set to allow the equalizer to quickly capture channel characteristics. In the later stages of iteration, a smaller step size and error smoothing are used to stabilize noise compensation.

[0034] The probability fusion model of the fusion layer is expressed as ,in, is the decoded formation parameter, is the likelihood function, is the prior probability of the known formation parameters, The modal information when the formation parameter is D The conditional probability of The weighted coefficient is the reliability weight of each known modal information. In this embodiment, the reliability weight is set to: 0.6 for the optical fiber mode, 0.4 for the electromagnetic wave mode, and 0.4 for the mud pulse mode.

[0035] Table 1 shows the performance comparison between the present invention and traditional mud pulse transmission: Table 1 like Figure 2 As shown, the transmission method of the high-speed transmission system of logging while drilling based on multi-modal combination includes the following steps: Step S1: continuously collecting multiple types of formation parameters during the drilling process of the drill tool; Step S2: selecting different transmission modes according to formation parameter type, well depth, and mud viscosity to transmit formation parameters to the surface in real time; Step S3: First, the ground performs a wavelet transform on the received formation parameters to separate the modal signals corresponding to each transmission mode. Then, by calculating the correlation between different modal signals, conflicting data with low consistency is marked and the conflicting data is repaired. Finally, a probabilistic fusion model is constructed based on the Bayesian network. The repaired data and the unmarked data are input into the probabilistic fusion model to obtain the decoded formation parameters, where the transmission modes include mud pulse mode, electromagnetic wave mode and optical fiber mode.

[0036] The above description is merely a preferred embodiment of the present invention and therefore cannot be used to limit the scope of the present invention. In other words, equivalent changes and modifications made according to the scope of the patent application and the contents of the specification should still fall within the scope of the patent of the present invention.

Claims

1. A high-speed transmission system for logging while drilling based on multi-modal combination, characterized by: The system includes a downhole acquisition unit, a transmission unit and a ground decoding unit. The downhole acquisition unit continuously collects multiple types of formation parameters and generates standardized data frames during the drilling process of the drill bit. The transmission unit selects different transmission modes according to the formation parameter category, well depth and mud viscosity to transmit the standardized data frames in real time. The ground decoding unit includes an independent decoding layer, a redundant check layer and a fusion layer. The independent decoding layer performs wavelet transform on the received standardized data frames to separate the modal signals corresponding to each transmission mode. The redundant check layer marks conflicting data with low consistency by calculating the correlation between different modal signals and repairs the conflicting data. The fusion layer constructs a probabilistic fusion model based on the Bayesian network. The output data of the redundant check layer is input into the probabilistic fusion model to obtain the decoded formation parameters. The transmission modes include mud pulse mode, electromagnetic wave mode and optical fiber mode.

2. The high-speed transmission system for logging while drilling based on multi-modal combination according to claim 1, characterized in that: The downhole acquisition unit includes an ultrasonic imaging device, a resistivity imaging device and a conventional logging instrument installed in the drilling tool. The formation parameters acquired by the downhole acquisition unit include ultrasonic imaging data, resistivity imaging data and conventional logging data. The conventional logging instrument includes a natural gamma ray meter, a natural potential logging instrument, an acoustic logging instrument, a density logging instrument, a resistivity logging instrument and a caliper logging instrument. The conventional logging data includes natural gamma related to lithology, natural potential related to lithology and permeability, acoustic wave time difference related to porosity and permeability, formation density related to porosity, formation resistivity related to oil and water layers, and wellbore diameter related to well wall conditions.

3. The high-speed transmission system for logging while drilling based on multi-modal combination according to claim 2, characterized in that: The transmission unit selects different transmission modes to transmit the formation parameters in real time according to the formation parameter type, well depth and mud viscosity, specifically including: when the well depth is less than a set well depth threshold and the mud viscosity is less than a set viscosity threshold, the transmission unit selects the electromagnetic wave mode and the optical fiber mode for joint transmission; otherwise, the transmission unit selects the mud pulse mode and the optical fiber mode for joint transmission; when the electromagnetic wave mode and the optical fiber mode are selected for joint transmission, for the ultrasonic imaging data and the resistivity imaging data, at least 80% of the total data volume of the ultrasonic imaging data and 80% of the total data volume of the resistivity imaging data are transmitted using the optical fiber mode; The remaining data is transmitted using the electromagnetic wave mode. For conventional logging parameters, at least 60% of the conventional logging data is transmitted using the optical fiber mode, and the remaining data is transmitted using the electromagnetic wave mode. When the mud pulse mode and the optical fiber mode are jointly transmitted, for ultrasonic imaging data and resistivity imaging data, at least 80% of the total ultrasonic imaging data and 80% of the total resistivity imaging data are transmitted using the optical fiber mode, and the remaining data is transmitted using the mud pulse mode. For conventional logging parameters, at least 60% of the conventional logging data is transmitted using the optical fiber mode, and the remaining data is transmitted using the mud pulse mode.

4. The high-speed transmission system for logging while drilling based on multi-modal combination according to claim 3 is characterized in that: The downhole acquisition unit embeds different identification fields in the headers of standardized data frames corresponding to ultrasonic imaging data, resistivity imaging data and conventional logging data, and the transmission unit determines the category of the transmitted data according to the identification fields.

5. The high-speed transmission system for logging while drilling based on multi-modal combination according to any one of claims 1 to 4, characterized in that: The transmission unit includes a mud pulse modulator, an electromagnetic wave coupler and an optical fiber slip ring. The mud pulse modulator is used to encode data into pressure waves and form a mud pulse mode with a low-frequency transmission channel of 0 to 10 kHz. The electromagnetic wave coupler is used to encode data into electromagnetic waves and form an electromagnetic wave mode with a medium-frequency transmission channel of 10 kHz to 1 MHz. The optical fiber slip ring is used to encode data into optical signals and form an optical fiber mode with a high-frequency optical fiber channel.

6. The high-speed transmission system for logging while drilling based on multi-modal combination according to any one of claims 1 to 4, characterized in that: The independent decoding layer is based on the formula The received formation parameters x ( t ) to perform wavelet transform, a is the scale parameter, b is the translation parameter, is the mother wavelet function, when setting a When >100, the modal signal corresponding to the mud pulse mode is obtained , when setting 10< a When ≤100, the modal signal corresponding to the electromagnetic wave mode is obtained , when setting a When <10, the modal signal corresponding to the optical fiber mode is obtained .

7. The high-speed transmission system for logging while drilling based on multi-modal combination according to claim 6, characterized in that: The redundancy check layer is based on the formula Calculating modal information S i With modal information S j If the mutual information between I ( S i , S j )<information threshold, then the modal information is determined S i With modal information S j For conflicting data, according to the formula Calculating modal information S i With modal information S j The correlation, if C ij < correlation threshold, the modal information S i With modal information S j Conflicting data points are marked as having low consistency, otherwise they are not marked. i , j =1,2,3 and i ≠ j , To calculate information entropy, For modal information S i No. k Sample data, N Modal information S i The number of sample data, Indicates when Returns 1 if yes, otherwise returns 0, 1≤ k ≤ N .

8. The high-speed transmission system for logging while drilling based on multi-modal combination according to claim 7, characterized in that: The redundancy check layer also includes an adaptive equalizer. The marked conflict data points are used as input to the adaptive equalizer. The adaptive equalizer uses a minimum mean square error algorithm. The step size factor of the minimum mean square error algorithm is dynamically adjusted according to the error between the output and input of the adaptive equalizer to repair the conflicting data. The repaired data and the unmarked data are used together as new modal information. .

9. The high-speed transmission system for logging while drilling based on multi-modal combination according to claim 8, characterized in that: The probabilistic fusion model of the fusion layer is expressed as ,in, is the decoded formation parameter, is the likelihood function, is the prior probability of the known formation parameters, The modal information when the formation parameter is D The conditional probability of The weighted coefficient is the reliability weight of each known modal information.

10. The transmission method of the multi-modal combined logging while drilling high-speed transmission system according to any one of claims 1 to 9, characterized in that: The steps include: Step S1: continuously collecting multiple types of formation parameters during the drilling process of the drilling tool; Step S2: selecting different transmission modes according to formation parameter type, well depth, and mud viscosity to transmit formation parameters to the surface in real time; Step S3: First, the ground performs a wavelet transform on the received formation parameters to separate the modal signals corresponding to each transmission mode. Then, by calculating the correlation between different modal signals, conflicting data with low consistency is marked and the conflicting data is repaired. Finally, a probabilistic fusion model is constructed based on the Bayesian network. The repaired data and the unmarked data are input into the probabilistic fusion model to obtain the decoded formation parameters, where the transmission modes include mud pulse mode, electromagnetic wave mode and optical fiber mode.

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