Wireless communication method for downhole intelligent release mechanism

Abstract

The application discloses a kind of wireless communication methods of downhole intelligent release mechanism, it is related to wireless communication technical field, and the method includes steps: obtaining the environment detection parameter of the detection position where logging instrument is located and real-time communication index;Based on the environment detection parameter, formation environment degree of optimization is calculated, and the formation environment degree of optimization is used to characterize the suitable degree of formation environment at detection position for wireless communication;Based on the formation environment degree of optimization and the real-time communication index, coil frequency demand index is calculated;The first transmission frequency of last time transmission coil is obtained, and the signal transmission frequency under current time is calculated based on the first transmission frequency and the coil frequency demand index.The application achieves the technical effect of improving the wireless communication efficiency of logging instrument intelligent release mechanism.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, in particular to a wireless communication method of an intelligent release mechanism in a well. BACKGROUND

[0002] Through-the-bit logging is a kind of efficient logging technology for complex wells such as horizontal wells, which carries logging instruments by drilling tools, combines with mud pump to advance to the target area, and then collects and monitors the formation conditions of the target area in the well. The intelligent release mechanism of the logging instrument includes upper and lower release short sections. When the logging instrument encounters well conditions that are difficult to pass through as a whole, the release mechanism can be disconnected and advanced in turn to improve the working efficiency of the logging instrument.

[0003] The wireless communication process of the intelligent release mechanism in the well mainly includes the communication of the upper release short section and the top remote transmission short section, and the communication of the lower release short section and the bottom storage control short section. The upper and lower release short sections are internally provided with transmitting coils, which can send communication signals of a certain frequency to the corresponding receiving short sections to meet the data transmission tasks such as logging command issuing and collected data uploading. At present, the transmitting frequency of the transmitting coil in the release short section is usually a fixed value. However, the demand for the transmitting frequency of the communication signal is different in different well conditions in the actual logging scene. The fixed transmitting frequency method has low adaptability to the actual logging scene, which reduces the wireless communication efficiency of the intelligent release mechanism of the logging instrument. SUMMARY

[0004] The main purpose of the present application is to provide a wireless communication method of an intelligent release mechanism in a well, which aims to solve the technical problem in the related art that the transmitting frequency of the transmitting coil in the release short section is set to a fixed value, the fixed transmitting frequency method has low adaptability to the actual logging scene, and the wireless communication efficiency of the intelligent release mechanism of the logging instrument is reduced.

[0005] To achieve the above-mentioned purpose, the embodiments of the present application provide a wireless communication method of an intelligent release mechanism in a well, which comprises:

[0006] Obtain the environmental detection parameters of the detection position of the logging instrument and the real-time communication index;

[0007] Based on the environmental detection parameters, the formation environment fitness is calculated, which is used to represent the suitability of the formation environment at the detection position for wireless communication;

[0008] Based on the formation environment fitness and the real-time communication index, the coil frequency requirement index is calculated;

[0009] Obtain the first transmitting frequency of the transmitting coil at the last moment, and based on the first transmitting frequency and the coil frequency requirement index, the signal transmitting frequency at the current moment is calculated.

[0010] In a possible implementation of the present application, the formation environment placement degree is calculated based on the environmental detection parameters, including:

[0011] The temperature data, pressure data, mud resistivity and mud dielectric constant of the detection position are determined based on the environmental detection parameters;

[0012] The temperature-pressure excellent coefficient of the detection position is calculated based on the temperature data and the pressure data, and the temperature-pressure excellent coefficient is corrected;

[0013] The mud magnetic interference strength is calculated based on the mud resistivity and the mud dielectric constant;

[0014] The formation environment placement degree is calculated according to the corrected temperature-pressure excellent coefficient and the mud magnetic interference strength.

[0015] In a possible implementation of the present application, the temperature-pressure excellent coefficient of the detection position is calculated based on the temperature data and the pressure data, including:

[0016] The first reciprocal of the temperature data and the second reciprocal of the pressure data are calculated respectively;

[0017] The temperature-pressure excellent coefficient is calculated based on the product between the first reciprocal and the second reciprocal.

[0018] In a possible implementation of the present application, the temperature-pressure excellent coefficient is corrected, including:

[0019] The time series data set corresponding to the temperature-pressure excellent coefficient in the historical preset time period of the logging instrument is acquired;

[0020] The first standard deviation of the time series data set and the overall standard deviation of the temperature-pressure excellent coefficient between the time period from the start of the logging instrument to the current time are calculated;

[0021] The correction coefficient is calculated based on the first standard deviation and the overall standard deviation;

[0022] The temperature-pressure excellent coefficient is corrected by the correction coefficient.

[0023] In a possible implementation of the present application, the coil frequency requirement index is calculated based on the formation environment placement degree and the real-time communication index, including:

[0024] The frequency over-standard degree of the intelligent release mechanism in the logging instrument is calculated based on the formation environment placement degree and the real-time communication index;

[0025] The communication stability degree of the intelligent release mechanism is calculated based on the video resolution and the error rate in the real-time communication index;

[0026] Extract the gamma value in the environmental detection parameter, and calculate a gamma detection mutation parameter based on the gamma value;

[0027] Calculate a coil frequency demand index based on the frequency over-standard degree, the communication stability degree, and the gamma detection mutation parameter.

[0028] In a possible implementation of the present application, the real-time communication index comprises a received signal, and a frequency over-standard degree of an intelligent release mechanism in the logging instrument is calculated based on the stratum environment optimization degree and the real-time communication index, and comprises:

[0029] Perform frequency domain decomposition processing on a signal output by the intelligent release mechanism and received by other modules in the logging instrument to obtain a high-frequency component and a low-frequency component;

[0030] Calculate a high-frequency interference factor based on a ratio between the high-frequency component and the low-frequency component;

[0031] Calculate the frequency over-standard degree of the intelligent release mechanism based on the stratum environment optimization degree and the high-frequency interference factor.

[0032] In a possible implementation of the present application, the high-frequency interference factor is calculated based on a ratio between the high-frequency component and the low-frequency component, and comprises:

[0033] Calculate an energy ratio parameter between the high-frequency component and the low-frequency component at the current time;

[0034] Calculate a maximum value of the energy ratio parameter between the high-frequency component and the low-frequency component corresponding to all historical times in the logging process;

[0035] Calculate the high-frequency interference factor based on a ratio between the energy ratio parameter and the maximum value of the energy ratio parameter.

[0036] In a possible implementation of the present application, the gamma detection mutation parameter is calculated based on the gamma value, and comprises:

[0037] Obtain a gamma value time domain curve in a historical preset time period;

[0038] Perform fitting processing on the gamma value time domain curve to obtain a gamma fitting straight line and a slope of the gamma fitting straight line;

[0039] Calculate the gamma detection mutation parameter based on a product between the gamma value at the current time and the slope.

[0040] In a possible implementation of the present application, the coil frequency demand index is calculated based on the frequency over-standard degree, the communication stability degree, and the gamma detection mutation parameter, and comprises:

[0041] Calculate a third reciprocal of the frequency over-standard degree and a fourth reciprocal of the gamma detection mutation parameter, respectively.

[0042] The coil frequency demand index is calculated based on the product between the communication stability degree, the third reciprocal and the fourth reciprocal.

[0043] In a possible implementation of the present application, the signal transmission frequency at the current moment is calculated based on the first transmission frequency and the coil frequency demand index, comprising:

[0044] The coil frequency demand index at the previous moment is determined.

[0045] The adjustment coefficient of the transmission frequency at the current moment is calculated based on the coil frequency demand index at the current moment and the coil frequency demand index at the previous moment.

[0046] The signal transmission frequency at the current moment is calculated based on the product between the adjustment coefficient and the first transmission frequency.

[0047] The present application provides a wireless communication method for an intelligent release mechanism of a downhole logging instrument, and compared with the related art, in which a fixed value is used to set the transmission frequency of a transmission coil in a release short section, the fixed transmission frequency method has a low adaptability to the actual logging scene, and the wireless communication efficiency of the intelligent release mechanism of the logging instrument is reduced, in the present application, the environmental detection parameters of a detection position where the logging instrument is located and real-time communication indexes are acquired, the bottom environmental optimization degree is calculated according to the environmental detection parameters, the coil frequency demand index is calculated based on the bottom environmental optimization degree and the real-time communication indexes, and then the signal transmission frequency at the current moment is calculated based on the first transmission frequency at the previous moment and the coil frequency demand index, the transmission frequency of the transmission coil with a higher adaptability to the current environment is obtained by combining and analyzing the communication performance corresponding to the environmental detection parameters of the actual detection position and the real-time communication indexes, and thus the wireless communication efficiency of the intelligent release mechanism of the downhole logging instrument is improved. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 The flowchart of the first embodiment of the wireless communication method for the intelligent release mechanism of the downhole logging instrument is shown in the figure.

[0049] Figure 2 The schematic diagram of the release mechanism of the logging instrument involved in the wireless communication method for the intelligent release mechanism of the downhole logging instrument is shown in the figure.

[0050] Figure 3 The schematic diagram of the communication structure of the logging instrument involved in the wireless communication method for the intelligent release mechanism of the downhole logging instrument is shown in the figure.

[0051] Figure 4 The schematic diagram of the overall implementation process involved in the wireless communication method for the intelligent release mechanism of the downhole logging instrument is shown in the figure.

[0052] Figure 5This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of the present invention. Detailed Implementation

[0053] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0054] This invention provides a wireless communication method for a downhole intelligent release mechanism. In the first embodiment of this invention, referring to... Figure 1 The methods include:

[0055] Step S10: Obtain environmental detection parameters and real-time communication indicators at the detection location of the logging tool;

[0056] Step S20: Based on the environmental detection parameters, the geological environment suitability is calculated. The geological environment suitability is used to characterize the suitability of the geological environment at the detection location for wireless communication.

[0057] Step S30: Based on the geological environment superiority and real-time communication indicators, the coil frequency demand index is calculated.

[0058] Step S40: Obtain the first transmission frequency of the transmitting coil at the previous moment, and calculate the signal transmission frequency at the current moment based on the first transmission frequency and the coil frequency requirement index.

[0059] This embodiment aims to: combine and analyze the environmental detection parameters of the actual detection location and the communication performance corresponding to the real-time communication indicators to obtain the transmission frequency of the transmitting coil with higher adaptability to the current environment, thereby improving the wireless communication efficiency of the intelligent release mechanism of the downhole logging tool.

[0060] The specific steps are as follows:

[0061] Step S10: Obtain environmental monitoring parameters and real-time communication indicators at the detection location of the logging tool.

[0062] As an example, the wireless communication method for downhole intelligent release mechanisms can be applied to downhole intelligent release mechanism wireless communication devices, which belong to downhole intelligent release mechanism wireless communication systems, and these systems belong to downhole intelligent release mechanism wireless communication equipment.

[0063] As an example, the wireless communication method for downhole intelligent release mechanisms can also be applied to logging tools, where a schematic diagram of the release mechanism of the logging tool is shown below. Figure 2As shown, it includes an upper line 1, a power section 2, a release mechanism 3, a retrieval head 4, a landing sleeve 5, and a lower line 6. When the logging tool encounters a difficult well condition during the exploration process, the release mechanism releases the logging tool, resulting in two parts, an upper and a lower section, which then pass through the complex well condition area in sequence.

[0064] Specifically, the communication structure diagram of the logging tool's intelligent release mechanism is as follows: Figure 3 As shown, the wireless communication process of the logging tool mainly includes communication between the upper release section and the top remote transmission section in the upper release mechanism, and communication between the lower release section and the bottom storage control section. The release section has a built-in transmitting coil, which can transmit a certain frequency transmission signal to the corresponding receiving section to realize internal communication of the logging equipment.

[0065] As an example, environmental monitoring parameters could include real-time temperature and pressure data at the logging tool's detection location, resistivity and dielectric constant data of the mud, and gamma value data of the geology at the detection location; real-time communication indicators could include resolution data of the logging tool's detection video, bit error rate data during data transmission, and received signals.

[0066] As an example, environmental monitoring parameters and real-time communication indicators can be obtained in the following ways:

[0067] 1. First, the temperature and pressure data at the location detected in real time by the logging tool are read through the temperature and pressure sensing module;

[0068] 2. Read the resistivity and dielectric constant data of the mud at the real-time detection location through the mud electrical parameter sensing module;

[0069] 3. Read the resolution data of the logging tool's detection video through the video monitoring module;

[0070] 4. Read the real-time bit error rate data within 5s / 8s (the exact time is not limited) through the data transmission module;

[0071] 5. Read the gamma value data of the geology at the well location through the gamma ray monitoring module;

[0072] 6. Read the received signal data through the signal receiving module;

[0073] 7. Perform data cleaning and preprocessing on the read data;

[0074] Finally, the preprocessed data is uploaded to the data acquisition system for subsequent analysis.

[0075] Step S20: Based on the environmental detection parameters, the geological environment suitability is calculated. The geological environment suitability is used to characterize the suitability of the geological environment at the detection location for wireless communication.

[0076] As an example, the purpose of this embodiment of the invention is to adaptively adjust the signal transmission frequency of the built-in transmitting coil of the release section of the logging tool. First, the interference level of the communication field is analyzed based on the geological environment / environmental detection parameters at the detection location. Then, the formation environment eugenics of the downhole is evaluated in real time. The formation environment eugenics is used to characterize the suitability of the formation environment at the detection location for wireless communication. The higher the formation environment eugenics, the more suitable the formation environment at the detection location is for wireless communication.

[0077] The step S20 of wireless communication for the downhole intelligent release mechanism further includes steps S21 to S24, including:

[0078] Step S21: Based on environmental detection parameters, determine the temperature data, pressure data, mud resistivity, and mud dielectric constant at the detection location.

[0079] As an example, environmental monitoring parameters include temperature data, pressure data, mud resistivity, and mud dielectric constant at the detection location. When used for analysis / calculation, the corresponding data can be directly extracted. These data can be obtained directly through sensor detection, and the specific detection process will not be elaborated here.

[0080] Step S22: Based on temperature and pressure data, calculate the temperature and pressure excellence coefficient of the detection location, and then correct the temperature and pressure excellence coefficient.

[0081] As an example, the logging tool is propelled into the well to the target section before casing is installed by the combined action of the drill bit in front and the mud pump behind to collect data. However, the temperature and pressure conditions at deeper wells are complex and may cause changes in the magnetic field, which may increase communication interference. Therefore, the temperature and pressure excellence coefficient is first determined based on the temperature and pressure at the detection location. The temperature and pressure excellence coefficient is used to characterize the temperature and pressure performance at the detection location, thereby quantifying the degree of magnetic field interference that may occur at that location.

[0082] As an example, since the temperature and pressure performance at the current detection location may be good, but the temperature and pressure may fluctuate strongly in a short period of time, the temperature and pressure performance coefficient needs to be corrected in combination with the temperature and pressure changes in a short period of time. Since the magnetic field interference changes are disordered when the temperature and pressure fluctuates violently, which will affect the communication of the intelligent release mechanism of the real-time logging tool, it is necessary to correct the temperature and pressure performance coefficient in combination with the temperature and pressure changes in a short period of time.

[0083] Step S22, which calculates the temperature-pressure excellence coefficient of the detection location based on temperature and pressure data, includes:

[0084] Calculate the first reciprocal of the temperature data and the second reciprocal of the pressure data, respectively;

[0085] The temperature and pressure excellence coefficient is calculated based on the product of the first and second reciprocals.

[0086] As an example, the temperature and pressure performance at the detection location is inversely proportional to the magnitude of the temperature and pressure data. High temperatures increase the thermal motion of atoms inside the material, leading to the disorder of electron spin direction and disrupting the directional arrangement of magnetic domains. Under high pressure, some materials in the geological interior may undergo crystal structure changes (such as iron changing from body-centered cubic to hexagonal close-packed), resulting in changes in magnetic order. Therefore, the stronger the temperature and pressure performance at the well location of the real-time logging tool, the stronger the magnetic field interference experienced by the logging tool during communication, and vice versa. Thus, the temperature and pressure excellence coefficient is calculated based on the product of the first reciprocal of the temperature data and the second reciprocal of the pressure data.

[0087] As an example, the temperature and pressure excellence coefficient Q can be calculated as follows:

[0088]

[0089] Where C represents temperature data, Indicates the first reciprocal. Indicates pressure data, This indicates the second reciprocal, and norm() indicates normalization calculation.

[0090] The step S22, which corrects the temperature and pressure performance coefficient, further includes:

[0091] Obtain the time-series dataset corresponding to the temperature and pressure excellence coefficients within a preset historical time period of the logging tool;

[0092] Calculate the first standard deviation of the time series dataset, and the overall standard deviation of the temperature and pressure excellence coefficients for the time period from the start of the logging tool's operation to the current moment.

[0093] As an example, the preset historical time period can be 7 seconds, 8 seconds, etc., and there is no specific limitation.

[0094] As an example, by setting one second as a moment, a time series dataset consisting of the temperature and pressure excellence coefficients at multiple moments within a short period of time can be obtained from the logging tool. The first standard deviation of this time series dataset is then calculated and denoted as the standard deviation. Furthermore, the overall standard deviation of the temperature and pressure excellence coefficients of the logging tool during the time period from the start of operation to the current moment is calculated and denoted as the overall standard deviation. .

[0095] The correction factor is calculated based on the first standard deviation and the overall standard deviation;

[0096] The temperature and pressure excellence coefficient is corrected using a correction factor.

[0097] As an example, the correction factor is expressed as:

[0098]

[0099] in, The first standard deviation, The overall standard deviation is It is a natural constant.

[0100] As an example, the temperature and pressure excellence coefficient is corrected by a correction factor to obtain the corrected temperature and pressure excellence coefficient. The correction process can be handled as follows:

[0101]

[0102] In the above formula, Indicates the coefficient of performance in temperature and pressure. This represents the correction coefficient. If the temperature and pressure performance fluctuates more strongly in a short real-time period compared to the level in a historical period, it indicates that the magnetic field is more disordered, which means that the confidence level of the magnetic field at the real time is lower, and the temperature and pressure performance coefficient needs to be adjusted more.

[0103] Step S23: Calculate the magnetic interference intensity of the mud based on the resistivity and dielectric constant of the mud.

[0104] As an example, the resistivity and dielectric constant of mud have different effects on the attenuation of high-frequency transmitted signals. Based on the relevant data of mud resistivity and dielectric constant, the degree of interference of mud on the signal, that is, the intensity of mud magnetic interference, is calculated to determine the type of transmission frequency (low frequency or high frequency) required at the current detection location.

[0105] As an example, the mud magnetic interference intensity G can be calculated as follows:

[0106]

[0107] in, The resistivity of the mud is... is the dielectric constant of the mud.

[0108] Specifically, high resistivity mud (such as oil-based mud) attenuates electromagnetic waves less, allowing high-frequency signals to penetrate deeper; low resistivity mud (such as water-based mud with high salt content) has high conductivity, causing high-frequency signals to attenuate quickly, requiring a lower transmission frequency to increase penetration depth; the dielectric constant reflects the mud's ability to polarize an electric field, and high dielectric constant mud (such as water-based mud) enhances the polarization effect of electromagnetic waves, leading to increased attenuation, requiring a lower frequency to suit detection and communication tasks.

[0109] In summary, the lower the resistivity of the mud and the higher the dielectric constant of the mud, the greater the signal attenuation, and the lower the matching between the mud and the high-frequency transmission signal.

[0110] Step S24: Calculate the formation environment preference based on the corrected temperature and pressure excellence coefficient and mud magnetic interference intensity.

[0111] As an example, a higher corrected temperature-pressure superiority coefficient and a lower mud magnetic interference intensity indicate a better formation environment at the detection location. Therefore, the formation environment superiority coefficient U can be calculated.

[0112]

[0113] Where norm() represents normalization calculation, This represents the corrected temperature and pressure performance coefficient. This indicates the intensity of magnetic interference in the mud.

[0114] Step S30: Based on the geological environment eugenics and real-time communication indicators, the coil frequency demand index is calculated.

[0115] As an example, in addition to considering the eugenics of the geological environment, it is also necessary to analyze the real-time communication indicators to determine the frequency requirements corresponding to the transmitting coil. These frequency requirements can be high-frequency or low-frequency, and then the coil frequency requirement indicators can be calculated.

[0116] The step S30, which calculates the coil frequency demand index based on the geological environment dominance and real-time communication indicators, includes:

[0117] Step S31: Based on the formation environment superiority and real-time communication indicators, calculate the frequency exceeding limit of the intelligent release mechanism in the logging tool.

[0118] As an example, the frequency exceedance level indicates the degree to which the actual signal frequency exceeds the required transmission signal frequency. For instance, if the current required transmission signal frequency is 800 Hz, but the actual transmission signal frequency is 1000 Hz, then the actual signal frequency exceeds the required transmission signal frequency. In the analysis process, the frequency exceedance level is calculated based on the dominance of the geological environment and the degree of change of relevant interference factors.

[0119] Among them, the real-time communication index includes the received signal. Step S31, which calculates the frequency exceedance degree of the intelligent release mechanism in the logging tool based on the formation environment dominance and the real-time communication index, includes:

[0120] The signals received by other modules in the logging tool from the intelligent release mechanism are processed by frequency domain decomposition to obtain high-frequency and low-frequency components.

[0121] As an example, in the communication process of the logging tool, the intelligent release mechanism is divided into an upper release section and a lower release section. Both release sections are equipped with a transmitting coil. The communication signal emitted by the upper release section is received by the top remote transmission section, and the signal emitted by the lower release section is received by the lower storage and control section. The signals received by these modules are analyzed and processed to determine the high-frequency interference factor in the received signals.

[0122] As an example, the frequency domain decomposition process can be EMD (Empirical Mode Decomposition) frequency domain decomposition, which is used to decompose complex nonlinear and non-stationary signals into several intrinsic mode functions (IMFs). The IMF component decomposition level is selected as a preset 6 levels, with each IMF representing a component. The order of IMF1 to IMF6 gradually increases, but the energy gradually decreases. The specific decomposition process is an existing technology and will not be elaborated here. Noise energy is usually concentrated in the high-frequency band, resulting in the energy of low-order IMFs being significantly higher than that of high-order IMFs. Therefore, the high-frequency interference factor of the received signal is obtained based on the proportion of high-frequency components to low-frequency components.

[0123] The high-frequency interference factor is calculated based on the ratio between the high-frequency component and the low-frequency component.

[0124] As an example, the degree of interference from high noise received during communication at the current moment can be determined based on the ratio between high-frequency and low-frequency components at different times.

[0125] The step of calculating the high-frequency interference factor based on the ratio between the high-frequency and low-frequency components includes:

[0126] Calculate the energy ratio parameter between the high-frequency component and the low-frequency component at the current moment;

[0127] Calculate the maximum energy ratio parameter between the high-frequency and low-frequency components corresponding to all historical moments during the well logging process.

[0128] As an example, the energy ratio parameter of the high-low frequency components is obtained by comparing the average energy of the lowest-order high-frequency component IMF1 with the average energy of the highest-order low-frequency component IMF6. .

[0129] As an example, the maximum energy ratio parameter between the high-frequency and low-frequency components at all historical moments during the well logging process is calculated. .

[0130] The high-frequency interference factor is calculated based on the ratio between the energy ratio parameter and the maximum value of the energy ratio parameter.

[0131] As an example, the high-frequency interference factor H can be calculated as follows:

[0132]

[0133] in, This represents the energy ratio parameter. This indicates the maximum value of the energy ratio parameter.

[0134] Specifically, the greater the energy ratio between high and low frequencies after EMD decomposition of the received signal at the current moment compared to the historical process, the greater the possibility that the real-time logging tool's intelligent release mechanism is affected by high noise during communication.

[0135] Based on the geological environment dominance and high-frequency interference factors, the degree of frequency exceeding the standard of the intelligent release mechanism was calculated.

[0136] As an example, if the formation environment at the location detected by the real-time logging tool is favorable... The smaller the value, the lower the high-frequency interference factor of the signals received by other modules of the real-time logging tool from the intelligent release mechanism. The higher the value, the easier it is for the signal to attenuate, and the lower the required transmission frequency. This means the actual signal frequency is more likely to exceed the limit. The degree of frequency exceeding the limit, f, can be calculated as follows:

[0137]

[0138] Where H represents the high-frequency interference factor, The value represents the dominance of the formation environment, and norm() represents the normalization calculation.

[0139] Step S32: Based on the video resolution and bit error rate in the real-time communication indicators, the communication stability of the intelligent release mechanism is calculated.

[0140] As an example, the communication stability of the release mechanism can be determined based on the video resolution and bit error rate in real-time communication indicators. When communication is relatively stable, the detection video acquired and transmitted by the logging tool has a high resolution, and the bit error rate of the data in the short term is low. However, when the communication process is subject to strong interference, the transmission video resolution and transmission data bit error rate show opposite trends. The communication stability level A can be calculated as follows:

[0141]

[0142] Where V represents video resolution and S represents bit error rate, the higher the detection video resolution and the lower the bit error rate during real-time data transmission of the logging tool's intelligent release mechanism, the more stable the communication performance.

[0143] Step S33: Extract the gamma value from the environmental detection parameters, and calculate the gamma detection mutation parameter based on the gamma value.

[0144] As an example, during well logging, the gamma value can reflect the surrounding geological lithology to a certain extent. When the gamma value suddenly increases, it may indicate that the well is close to the top mudstone of the reservoir. The well logging tool's trajectory needs to be adjusted in time to keep it on the optimal trajectory. At this time, the transmission signal should be adjusted to a low frequency to ensure the accuracy of the overall trajectory (the signal attenuation is weak at low frequencies, which makes the accuracy of grasping the overall trajectory during exploration better, while the signal attenuation is strong at high frequencies, which is suitable for near-end geological analysis, but the noise at far ends is too strong, and the grasp of the overall exploration trajectory is relatively poor).

[0145] Step S33, which calculates the gamma detection mutation parameters based on the gamma value, includes:

[0146] Obtain the time-domain curve of gamma values ​​within a preset historical time period;

[0147] The time-domain curve of the gamma value is fitted to obtain the gamma fitting line and the slope of the gamma fitting line.

[0148] The gamma detection mutation parameters are calculated based on the product of the gamma value at the current moment and the slope.

[0149] As an example, the time-domain curve of the gamma value over an 8-second period in history is obtained, and the gamma-fitting line of the time-domain curve is obtained by the least squares linear fitting method. After obtaining the gamma-fitting line, the slope K of the fitted line is obtained.

[0150] As an example, the gamma detection mutation parameter Z at the current moment can be calculated as follows:

[0151]

[0152] Where M represents the gamma value at the current moment, K represents the slope of the gamma fitting line, and norm() represents the normalization calculation. In the above formula, the higher the real-time gamma value at the logging tool position, and the more the gamma value changes in the preset period before the current moment tends to increase, the more the logging tool needs to perform trajectory analysis to adjust the trajectory. At this time, the demand for low-frequency transmission signals is higher.

[0153] Step S34: Based on the degree of frequency exceeding the standard, the degree of communication stability, and the gamma detection mutation parameters, the coil frequency demand index is calculated.

[0154] As an example, the coil frequency demand index is used to represent the frequency demand of the signal emitted by the transmitting coil at the current moment. The smaller the coil frequency demand index, the lower the required signal frequency, and vice versa.

[0155] As an example, if the logging tool monitors sudden changes in gamma parameters in real time... The higher the value, the greater the logging tool's real-time requirement for low frequencies, and the higher the communication stability. The lower the frequency, the stronger the noise performance, which further indicates that the transmission frequency needs to be lowered to obtain better communication and tracking effects. This is especially true if the real-time communication and tracking effect of the logging tool's intelligent release mechanism is poor, and if the logging tool's real-time frequency exceeds the limit. The lower the value, the higher the demand for high frequency. In other words, the communication stability A is directly proportional to the coil frequency demand index, while the frequency exceedance and gamma detection mutation parameters are inversely proportional to the coil frequency demand index.

[0156] Step S34, which calculates the coil frequency demand index based on the degree of frequency exceeding the limit, the degree of communication stability, and the gamma detection mutation parameters, includes:

[0157] Calculate the third reciprocal of the frequency exceeding the standard and the fourth reciprocal of the gamma detection mutation parameter, respectively;

[0158] The coil frequency demand index is calculated based on the communication stability level and the product of the third and fourth reciprocals.

[0159] As an example, coil frequency demand index The calculation method can be:

[0160]

[0161] in, Indicates the stability of communication. Indicates the degree to which the frequency exceeds the limit. Indicates the third reciprocal. This indicates the parameters for gamma detection mutations. This indicates the fourth reciprocal, and thus, the coil frequency demand index of the intelligent release mechanism of the logging tool at the current moment and the previous moment is obtained.

[0162] Step S40: Obtain the first transmission frequency of the transmitting coil at the previous moment, and calculate the signal transmission frequency at the current moment based on the first transmission frequency and the coil frequency requirement index.

[0163] As an example, the first transmission frequency of the transmitting coil at the previous moment can be obtained through historical data. At the beginning of operation, the first transmission frequency is the initially set transmission frequency. Then, the signal transmission frequency is adjusted according to the first transmission frequency and the coil frequency requirement index to obtain a signal transmission frequency that is suitable for the current environment.

[0164] The step S40, which calculates the signal transmission frequency at the current moment based on the first transmission frequency and the coil frequency demand index, includes:

[0165] Determine the coil frequency demand index at the previous moment;

[0166] Based on the coil frequency demand index at the current moment and the coil frequency demand index at the previous moment, the adjustment coefficient of the transmission frequency at the current moment is calculated.

[0167] The signal transmission frequency at the current moment is calculated based on the product of the adjustment coefficient and the first transmission frequency.

[0168] As an example, the signal transmission frequency at the current moment The calculation method can be:

[0169]

[0170] in, Indicates the first transmission frequency. Indicates the adjustment factor. This indicates the coil frequency demand index at the current moment. The coil frequency demand index represents the previous time step, and th() represents the normalization function, with the function expression Tanh(x), used for normalization, and the range is (-1, 1).

[0171] In the above formula, the greater the coil frequency requirement index is compared to the previous time, the higher the transmission frequency needs to be; conversely, the lower the frequency needs to be, thus obtaining the real-time signal transmission frequency of the communication transmission coil of the logging tool's intelligent release mechanism.

[0172] Specifically, the main workflow of a logging tool is as follows:

[0173] First, the logging tool's intelligent release mechanism uploads the adaptive transmission frequency to the transmission coil module inside the release section. The transmission coil outputs the transmission frequency signal, and the receiving coil inside the corresponding storage and control and remote transmission section receives the signal. Then, through the communication interaction between the release section and the storage and control section, the multi-source data collected downhole is transmitted to the surface end within the intelligent release mechanism.

[0174] At the same time, through the communication interaction between the upper release sub and the remote transmission sub, the ground-end command information is transmitted to the logging tool execution module;

[0175] If the downhole storage instrument returns an error code, the surface system marks the fault and suspends operations;

[0176] After the downhole storage instrument completes logging, it is retrieved to the surface by a retrieval device, and the wireless module automatically enters a low-power sleep mode.

[0177] In this embodiment, the overall implementation process is illustrated as follows: Figure 4As shown, preliminary preparations are first carried out by collecting relevant environmental monitoring parameters and real-time communication indicators, calculating the temperature and pressure excellence coefficient and mud magnetic interference intensity, and then obtaining the formation environment superiority. By performing frequency domain analysis on the received signal, the degree of frequency exceeding the standard is obtained. Then, based on the presentation effect of real-time communication and the sudden change performance of gamma value, the coil frequency demand index is obtained. The transmission frequency at the current moment is then adjusted through the coil frequency demand index. Finally, the complete process of downhole wireless communication is completed.

[0178] This invention provides a wireless communication method for a downhole intelligent release mechanism. Compared to related technologies that use a fixed transmission frequency for the transmitting coil in the release section, which has low adaptability to actual logging scenarios and reduces the wireless communication efficiency of the intelligent release mechanism, this invention acquires environmental detection parameters and real-time communication indicators at the logging tool's detection location. Based on the environmental detection parameters, the formation environment eugenics is calculated. Then, using the formation environment eugenics and real-time communication indicators, the coil frequency demand index is calculated. Furthermore, based on the first transmission frequency at the previous moment and the coil frequency demand index, the signal transmission frequency at the current moment is calculated. By combining and analyzing the communication performance corresponding to the actual detection location's environmental detection parameters and real-time communication indicators, a transmission frequency of the transmitting coil with higher adaptability to the current environment is obtained, thereby improving the wireless communication efficiency of the downhole logging tool's intelligent release mechanism.

[0179] Reference Figure 5 , Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of the present invention.

[0180] like Figure 5 As shown, the wireless communication device for the downhole intelligent release mechanism may include: a processor 1001, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to realize the connection and communication between the processor 1001 and the memory 1005.

[0181] Optionally, the wireless communication equipment for the downhole intelligent release mechanism may also include a user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, a WiFi module, etc. The user interface may include a display screen and an input submodule such as a keyboard; optional user interfaces may also include standard wired or wireless interfaces. The network interface may include standard wired or wireless interfaces (such as a Wi-Fi interface).

[0182] Those skilled in the art will understand that Figure 5The structure of the wireless communication device for the downhole intelligent release mechanism shown in the figure does not constitute a limitation on the wireless communication device for the downhole intelligent release mechanism. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0183] like Figure 5 As shown, the memory 1005, serving as a storage medium, may include an operating system, a network communication module, and a wireless communication program for the downhole intelligent release mechanism. The operating system is a program that manages and controls the hardware and software resources of the downhole intelligent release mechanism's wireless communication equipment, supporting the operation of the wireless communication program and other software and / or programs. The network communication module is used to enable communication between the various components within the memory 1005, as well as communication with other hardware and software in the downhole intelligent release mechanism's wireless communication system.

[0184] exist Figure 5 In the wireless communication device for the downhole intelligent release mechanism shown, the processor 1001 is used to execute the wireless communication program for the downhole intelligent release mechanism stored in the memory 1005 to implement the steps of the wireless communication method for the downhole intelligent release mechanism described above.

[0185] The specific implementation of the wireless communication device for the downhole intelligent release mechanism of the present invention is basically the same as the embodiments of the wireless communication method for the downhole intelligent release mechanism described above, and will not be repeated here.

[0186] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0187] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0188] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0189] The above are merely preferred embodiments of the present invention and do not limit the scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of protection of the present invention.

[0190] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0191] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A wireless communication method for an intelligent release mechanism in a well, characterized in that, The method includes: Acquire environmental monitoring parameters and real-time communication indicators at the location of the logging tool; Based on the environmental detection parameters, the formation environment suitability is calculated, which is used to characterize the suitability of the formation environment at the detection location for wireless communication. Based on the geological environment preference and the real-time communication index, the coil frequency demand index is calculated. Obtain the first transmission frequency of the transmitting coil at the previous moment, and calculate the signal transmission frequency at the current moment based on the first transmission frequency and the coil frequency demand index; The calculation of the formation environment dominance based on the environmental monitoring parameters includes: Based on the environmental detection parameters, the temperature data, pressure data, mud resistivity, and mud dielectric constant of the detection location are determined. Based on the temperature data and the pressure data, the temperature and pressure excellence coefficient of the detection location is calculated, and the temperature and pressure excellence coefficient is corrected. Based on the resistivity and dielectric constant of the mud, the intensity of magnetic interference in the mud was calculated. Based on the corrected temperature and pressure excellence coefficient and the mud magnetic interference intensity, the formation environment superiority is calculated; The calculation of the temperature-pressure excellence coefficient at the detection location based on the temperature data and the pressure data includes: Calculate the first reciprocal of the temperature data and the second reciprocal of the pressure data, respectively; The temperature and pressure excellence coefficient is calculated based on the product of the first reciprocal and the second reciprocal. The calculation of the coil frequency demand index based on the formation environment dominance and the real-time communication index includes: Based on the formation environment preference and the real-time communication index, the degree of frequency overrun of the intelligent release mechanism in the logging tool is calculated. Based on the video resolution and bit error rate in the real-time communication indicators, the communication stability of the intelligent release mechanism is calculated. Extract the gamma value from the environmental detection parameters, and calculate the gamma detection mutation parameter based on the gamma value; Based on the frequency exceedance level, communication stability, and gamma detection mutation parameters, the coil frequency demand index is calculated.

2. The wireless communication method for the downhole intelligent release mechanism as described in claim 1, characterized in that, The correction process for the temperature and pressure excellence coefficient includes: Obtain the time-series dataset corresponding to the temperature and pressure excellence coefficients within a preset historical time period of the logging tool; Calculate the first standard deviation of the time series dataset, and the overall standard deviation of the temperature and pressure excellence coefficient for the time period from the start of operation of the logging tool to the current time. The correction factor is calculated based on the first standard deviation and the overall standard deviation; The temperature and pressure excellence coefficient is corrected using the aforementioned correction factor.

3. The wireless communication method for the downhole intelligent release mechanism as described in claim 1, characterized in that, The real-time communication indicators include received signals. The calculation of the frequency exceedance degree of the intelligent release mechanism in the logging tool based on the formation environment dominance and the real-time communication indicators includes: The signals received by other modules in the logging tool from the output of the intelligent release mechanism are processed by frequency domain decomposition to obtain high-frequency components and low-frequency components; The high-frequency interference factor is calculated based on the ratio between the high-frequency component and the low-frequency component. Based on the geological environment preference and the high-frequency interference factor, the degree of frequency exceedance of the intelligent release mechanism is calculated.

4. The wireless communication method for the downhole intelligent release mechanism as described in claim 3, characterized in that, The calculation of the high-frequency interference factor based on the ratio between the high-frequency component and the low-frequency component includes: Calculate the energy ratio parameter between the high-frequency component and the low-frequency component at the current moment; Calculate the maximum energy ratio parameter between the high-frequency component and the low-frequency component corresponding to all historical moments during the well logging process; The high-frequency interference factor is calculated based on the ratio between the energy ratio parameter and the maximum value of the energy ratio parameter.

5. The wireless communication method for the downhole intelligent release mechanism as described in claim 1, characterized in that, The calculation of gamma detection mutation parameters based on the gamma value includes: Obtain the time-domain curve of gamma values ​​within a preset historical time period; The time-domain curve of the gamma value is fitted to obtain the gamma fitting line and the slope of the gamma fitting line. The gamma detection mutation parameter is calculated based on the product of the gamma value at the current moment and the slope.

6. The wireless communication method for the downhole intelligent release mechanism as described in claim 1, characterized in that, The coil frequency demand index is calculated based on the frequency exceedance level, communication stability, and gamma detection mutation parameters, including: Calculate the third reciprocal of the frequency exceeding the standard and the fourth reciprocal of the gamma detection mutation parameter, respectively; The coil frequency demand index is calculated based on the communication stability level, the product of the third reciprocal and the fourth reciprocal.

7. The wireless communication method for the downhole intelligent release mechanism as described in claim 1, characterized in that, The step of calculating the signal transmission frequency at the current moment based on the first transmission frequency and the coil frequency demand index includes: Determine the coil frequency demand index at the previous moment; Based on the coil frequency demand index at the current moment and the coil frequency demand index at the previous moment, the adjustment coefficient of the transmission frequency at the current moment is calculated. The signal transmission frequency at the current moment is calculated based on the product of the adjustment coefficient and the first transmission frequency.

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