A high-cold area mud logging stratum analysis data remote monitoring system

Abstract

The present application relates to the technical field of remote monitoring, in particular to a kind of high-cold area mud logging stratum analysis data remote monitoring system, system includes stratum mutation monitoring module, data paragraph integrity identification module, monitoring priority order construction module, environmental mutation excitation monitoring module and channel path dynamic scheduling module.The present application, by double judgment to the variation value of methane concentration and the range of rock debris particle size, can accurately identify the depth paragraph of stratum mutation, and by comparing the integrity of mud logging channel data, according to the mutation degree and the structure integrity degree, when sudden disturbance occurs outside the mud logging environment, dynamically evaluate the stability of communication channel and switch path, improve the reliability and response efficiency of data link under extreme climate conditions, under the condition of remote unmanned garrison, consider mutation identification, data integrity protection and link stable transmission, realize accurate monitoring and remote operation and maintenance support for high-cold area mud logging data.

Description

Technical Field

[0001] This invention relates to the field of remote monitoring technology, and in particular to a remote monitoring system for well logging formation analysis data in high-altitude and cold regions. Background Technology

[0002] Remote monitoring technology involves the real-time acquisition, transmission, processing, and control of geographically dispersed equipment, systems, or environments via communication networks. This technology is widely used in industrial automation, energy management, transportation, environmental monitoring, and oil and gas exploration. Its core components include sensor terminals, data acquisition and transmission modules, backend server processing units, and a visual monitoring platform. Remote monitoring systems utilize wireless communication and edge computing technologies to continuously monitor equipment status or environmental data in remote environments. Combined with data processing algorithms, they perform anomaly detection, trend analysis, and early warning control, thereby reducing manual intervention, improving monitoring accuracy and response efficiency. This is particularly suitable for equipment operation monitoring and remote maintenance support in extreme environments or remote areas.

[0003] The remote monitoring system for well logging formation analysis data in high-altitude and cold regions is a specific application of remote monitoring technology in oil and gas well logging operations. This system is used for real-time remote acquisition, transmission, and processing of well logging formation analysis data generated during drilling in high-altitude and cold regions. Its purpose is to achieve real-time uploading and remote visualization of formation parameters without relying on on-site manual monitoring, providing auxiliary analysis and judgment for geological engineers, thereby ensuring the continuity, safety, and data integrity of drilling operations in high-altitude and cold regions. The system can also adapt to the stable operation requirements in low-temperature environments and has functions such as network outage caching, automatic data retransmission, and remote operation and maintenance.

[0004] Traditional monitoring systems rely on wireless communication and edge computing for remote transmission and processing of logging data. However, when faced with frequent and sudden environmental disturbances and communication quality fluctuations in high-altitude and cold regions, they lack mechanisms for identifying and prioritizing critical geological abrupt changes. This results in delayed uploading of abrupt change information, affecting the real-time nature of backend analysis and judgment. Traditional systems also fail to distinguish the structural integrity of data segments, leading to missing segments not being detected and retransmitted in a timely manner, impacting the continuity and accuracy of data analysis. Furthermore, communication links are not dynamically evaluated and switched in conjunction with environmental fluctuation characteristics. When the performance of the main channel degrades, the original path is still used, posing a risk of link interruption. In extreme climates and remote environments, this can easily lead to remote monitoring failure. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a remote monitoring system for logging formation analysis data in high-altitude and cold regions.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a remote monitoring system for well logging formation analysis data in high-altitude and cold regions, the system comprising:

[0007] The formation mutation monitoring module acquires the methane concentration data sequence and rock cutting particle size data sequence generated in real time during the logging operation. It calculates the average difference between adjacent data in the methane concentration sequence within each depth segment, statistically analyzes the range in the rock cutting particle size data sequence of the segment, identifies formation mutation point segments, and generates mutation segment monitoring record information.

[0008] The data paragraph integrity identification module calls the mutation section monitoring record information to determine whether there are consecutive missing items with a length greater than the missing item tolerance threshold, marks the missing item positions, and generates a list of paragraphs with incomplete structure.

[0009] The monitoring priority order construction module evaluates the monitoring priority level of the segments based on the monitoring record information of the abrupt change segment and the list of incomplete segment labels, reconstructs the scheduling order of logging formation monitoring instructions in the current transmission scheduling cache, and generates a monitoring scheduling priority segment sequence.

[0010] The environmental mutation excitation monitoring module acquires the wind speed change value, air temperature gradient, relative humidity change rate and geomagnetic disturbance intensity monitored in real time by the external environment monitoring unit of the logging well, records the time of environmental excitation interference, and generates a list of environmental interference intervals.

[0011] The present invention is improved in that the monitoring and recording information of the mutation section specifically includes the mutation section number, depth start and end interval, gas concentration jump value and rock cutting particle size variation; the list of incomplete structural sections includes the missing section number, missing data unit name and missing length interval; the monitoring and scheduling priority section sequence specifically includes the section priority level value, monitoring instruction call order and transmission scheduling index; and the environmental interference section list includes the interference start time, interference duration and excitation parameter category.

[0012] The present invention is improved in that the formation abrupt change monitoring module includes:

[0013] The sequence data extraction submodule acquires the methane concentration data sequence and cuttings particle size data sequence generated in real time during the logging operation, extracts the corresponding data points within a fixed depth segment, obtains the concentration sequence and particle size sequence in the depth segment, and obtains the target data extraction set;

[0014] The difference numerical calculation submodule extracts the target data set, calculates the difference between adjacent data in the methane concentration series according to the methane concentration series and the particle size series, calls the difference between the maximum and minimum values ​​in the particle size series as the rock cutting particle size range value, calculates and obtains the formation mutation degree index value, and generates formation mutation degree information.

[0015] The mutation segment identification submodule calls the formation mutation degree information, compares it with the set mutation judgment benchmark value, determines whether it exceeds the set differentiation limit range, marks the mutation segment number and start and end depth positions, establishes a segment attribute and mutation status index table, and obtains mutation segment monitoring record information.

[0016] The present invention is improved in that the data paragraph integrity identification module includes:

[0017] The depth segment data extraction submodule calls the monitoring and recording information of the mutation segment, locates the target data area in the real-time logging data cache according to the number and depth range corresponding to each segment, extracts the index number list of each logging data unit in the area, and generates a segment index number set;

[0018] The index sequence missing item identification submodule calls the logging channel index sequence in the complete segment standard template according to the segment index number set, and judges whether there are interval missing items in the segment index number by the sequence number, counts the length of consecutive missing segments, compares it with the missing item tolerance threshold, filters missing segments that exceed the tolerance length, and obtains the missing segment filtering results.

[0019] The missing segment annotation generation submodule, based on the missing segment filtering results, assigns a number and name to each missing segment according to the marked start and end numbers of the missing segment and the channel identifier, establishes a correspondence between the segment number and the missing channel, annotates the segment attributes, and generates a list of incomplete segment annotations.

[0020] The present invention is improved in that the monitoring priority order construction module includes:

[0021] The paragraph intersection identification submodule calls the mutation segment monitoring record information and the list of structurally incomplete paragraphs, identifies overlapping paragraphs based on the consistency of the numbers, extracts the paragraph numbers that simultaneously possess mutation state and structural missing features, and generates dual-attribute paragraph identification results.

[0022] The priority level calculation submodule extracts the mutation attribute weight value and the structural missing attribute weight value based on the dual-attribute paragraph identification results, calculates and obtains the monitoring priority level value of each paragraph, and obtains the paragraph priority level set.

[0023] The scheduling order sorting submodule sorts the segments according to the priority level set and the monitoring priority level value, establishes a mapping relationship between the segment number and the scheduling instruction sequence, and rearranges the logging formation monitoring instruction index in the current transmission buffer to obtain the monitoring scheduling priority segment sequence.

[0024] The present invention is improved in that the environmental mutation excitation monitoring module includes:

[0025] The environmental data acquisition submodule acquires the wind speed change value, air temperature gradient, relative humidity change rate and geomagnetic disturbance intensity monitored in real time by the external environmental monitoring unit of the logging well. It calculates the moving difference for each data sequence within a fixed time window, calculates the average value of the moving difference sequence, and generates a set of environmental disturbance mean values.

[0026] The threshold exceedance judgment submodule calls the wind speed sudden change limit, temperature gradient change limit, humidity jump amplitude threshold and geomagnetic disturbance limit according to the set of environmental disturbance average values, compares the four average values ​​with the corresponding threshold values ​​in turn, determines whether any one of them exceeds the threshold standard, and obtains the exceedance index judgment result.

[0027] The interference period calibration submodule, based on the judgment result of the over-limit index, aggregates the consecutive over-limit time points according to the time point sequence marked as over-limit state, extracts the start and end times of the interference, calibrates the corresponding time period interval, establishes the correspondence between time segments and disturbance types, and obtains a list of environmental interference intervals.

[0028] The present invention has an improvement, wherein the system further includes:

[0029] The channel path dynamic scheduling module calls the environmental interference interval list, calculates the stability score of the current channel, compares it with the current measurement value of the candidate channels, selects the channel with the highest stability score as the replacement object, and implements remote data transmission according to the monitoring and scheduling priority segment sequence to generate a remote link switching transmission record.

[0030] The remote link switching transmission record specifically refers to the switching time, original channel identifier, target channel number, and switching trigger basis.

[0031] The present invention is improved in that the channel path dynamic scheduling module includes:

[0032] The link index acquisition submodule calls the environmental interference interval list, extracts the round-trip delay measurement, signal strength sequence and packet reception rate of the main channel in each interference period, calculates the average value, standard deviation and variability index of the three data, establishes the channel characteristic summary value of each interference segment, and generates the main channel stability parameter set.

[0033] The stability score calculation submodule, based on the main channel stability parameter set, sequentially calls the current state parameters of the candidate channels, normalizes the round-trip delay difference, the mean signal strength difference, and the degree of receiver variation, constructs a comparability score, calculates and obtains the stability score value of each candidate channel, filters the channel number with the largest score value, and obtains the channel switching target number.

[0034] The remote data scheduling submodule performs channel path switching based on the channel switching target number. After the switching is completed, it calls the segment scheduling index corresponding to the monitoring scheduling priority segment sequence, redistributes the scheduling task according to the new channel path order, records the channel access status according to the switching time, establishes a complete communication path tracking entry, and obtains the remote link switching transmission record.

[0035] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0036] In this invention, by dually judging the methane concentration change value and the rock cutting particle size range, the depth segment of the formation change can be accurately identified. By comparing the integrity of the logging channel data, abnormal segments with missing data structure can be effectively located. Priority levels are assigned according to the degree of change and structural integrity, and the monitoring and scheduling order is reconstructed to ensure that key change segments are prioritized for remote transmission and processing. When sudden disturbances occur outside the logging environment, the stability of the communication channel is dynamically evaluated and the optimal path is switched, improving the reliability and response efficiency of the data link under extreme weather conditions. Under remote unmanned conditions, it takes into account the identification of changes, the protection of data integrity, and the stable transmission of the link, realizing accurate monitoring and remote operation and maintenance support for logging data in high-altitude and cold regions. Attached Figure Description

[0037] Figure 1 This is a system flowchart of the present invention;

[0038] Figure 2 This is a flowchart of the formation change monitoring module of the present invention;

[0039] Figure 3 This is a flowchart of the data segment integrity identification module of the present invention;

[0040] Figure 4 This is a flowchart of the monitoring priority order construction module of the present invention;

[0041] Figure 5 This is a flowchart of the environmental mutation excitation monitoring module of the present invention;

[0042] Figure 6 This is a flowchart of the channel path dynamic scheduling module of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0044] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0045] Please see Figure 1 The present invention provides a technical solution: a remote monitoring system for well logging formation analysis data in high-altitude and cold regions, the system including a formation change monitoring module, a data segment integrity identification module, a monitoring priority order construction module, an environmental change triggering monitoring module, and a channel path dynamic scheduling module;

[0046] The formation mutation monitoring module acquires real-time methane concentration data sequences and cuttings particle size data sequences generated during logging operations. It sets fixed depth segments, calculates the average difference between adjacent data in the methane concentration sequence within each depth segment, and statistically analyzes the range of the cuttings particle size data sequence in the segment. It then calls the set methane concentration variation threshold and particle size range threshold to determine whether the two values ​​exceed the limits. Based on the judgment result, it determines whether the current segment is a formation mutation point segment and generates mutation segment monitoring record information.

[0047] The methane concentration variation threshold is a commonly used indicator for determining abrupt changes in downhole gas logging operations. It is usually identified based on a methane concentration change exceeding the background concentration by more than 20%.

[0048] The data segment integrity identification module calls the monitoring and recording information of the mutation segment. Based on the segment number and the corresponding depth range, it extracts the index sequence of multiple data units within the range from the real-time logging data cache. It compares the sequence with the logging channel sequence in the complete segment standard template to determine whether there are consecutive missing items with a length greater than the missing item tolerance threshold. It then marks the missing item positions and generates a list of incomplete segment annotations.

[0049] The monitoring priority order construction module determines whether the formation mutation point segment appears in the list of incomplete structural segments simultaneously based on the monitoring record information of the mutation segment and the list of incomplete structural segments. It assigns mutation attribute weight value and structural missing attribute weight value to the identified segments respectively, evaluates the monitoring priority level of the segments, sorts them according to the priority level, reconstructs the scheduling order of logging formation monitoring instructions in the current transmission scheduling cache, and generates a monitoring scheduling priority segment sequence.

[0050] The environmental abrupt change excitation monitoring module acquires the wind speed change value, air temperature gradient, relative humidity change rate and geomagnetic disturbance intensity monitored in real time by the external environmental monitoring unit of the logging. Within a fixed time window, it calculates the average sliding difference of the four indicators and compares them with the wind speed abrupt change limit, temperature gradient change limit, humidity jump amplitude threshold and geomagnetic disturbance limit to determine whether any one of them exceeds the limit. If it meets the limit, the time point is marked as the environmental excitation disturbance moment and the duration is recorded to generate a list of environmental disturbance intervals.

[0051] The geomagnetic disturbance index is an internationally recognized indicator of geomagnetic disturbance; a negative value indicates that the geomagnetic field is under pressure disturbance.

[0052] The channel path dynamic scheduling module calls the list of environmental interference intervals. Based on the time period when interference exists, it extracts the round-trip delay measurement, signal strength sequence and packet reception rate of the current main channel in the corresponding time period, calculates the stability score of the current channel, compares it with the current measurement value of the candidate channel, selects the channel with the highest stability score as the replacement object, performs channel switching, and implements remote data transmission according to the monitoring and scheduling priority segment sequence, generating a remote link switching transmission record.

[0053] The information recorded in the monitoring records of abrupt change sections includes the abrupt change section number, depth start and end interval, gas concentration jump value, and rock cutting particle size variation. The list of incomplete structural sections includes the missing section number, missing data unit name, and missing length interval. The monitoring and scheduling priority section sequence includes the section priority level value, monitoring command call order, and transmission scheduling index. The list of environmental interference intervals includes the interference start time, interference duration, and excitation parameter category. The remote link switching transmission record specifically refers to the switching time, original channel identifier, target channel number, and switching trigger basis.

[0054] Please see Figure 2 The formation change monitoring module includes:

[0055] The sequence data extraction submodule acquires the methane concentration data sequence and cuttings particle size data sequence generated in real time during the logging operation, extracts the corresponding data points within a fixed depth segment, obtains the concentration sequence and particle size sequence in the depth segment, and obtains the target data extraction set;

[0056] The process of acquiring real-time methane concentration data sequences and cuttings particle size data sequences generated during logging operations requires a clear distinction between the data source and the depth positioning identifier. Specifically, the gas composition numerical sequence recorded by the methane concentration detection module and the particle size numerical sequence generated by the cuttings image recognition module are collected separately through downhole sensor devices. The data acquisition frequency is uniformly set to record one set of values ​​every 1 meter of depth.

[0057] In the specific implementation process, it is assumed that the drilling depth is from to A total of 101 sets of methane concentration data and 101 sets of particle size data were collected and constructed into one-dimensional arrays. and Each of these and These represent the methane concentration values ​​collected at the corresponding depth points (unit: methane). ) and the maximum particle size of rock cuttings (unit: The target depth segment is extracted using the depth segment range limitation module. to Given all data within the range, obtain a subsequence. and This constitutes the target data extraction set corresponding to this paragraph, which is used for subsequent indicator calculations.

[0058] The difference numerical calculation submodule extracts the target data set and calculates the difference between adjacent data in the methane concentration series based on the methane concentration series and the grain size series. It then uses the difference between the maximum and minimum values ​​in the grain size series as the range of rock cutting grain size, employing the following formula:

[0059] ;

[0060] The calculation obtains the index value of the degree of stratigraphic abrupt change, and generates information on the degree of stratigraphic abrupt change.

[0061] in, This represents the average value of the methane concentration difference in the current paragraph. This represents the threshold for methane concentration variation. This indicates the range of rock cuttings size in the current segment. Indicates the threshold of particle size range. This represents the normalized value indicating the length of the current depth segment. This is a stability interference correction factor. This represents the variance of the methane concentration difference per unit depth. Values ​​representing the degree of abrupt changes in formation;

[0062] Regarding the index value of the degree of abrupt change in formation :

[0063] This index value is used to measure whether there are abrupt changes in lithology or gas logging characteristics at the current depth. The calculation formula is as follows:

[0064] ;

[0065] The formula consists of three parts. The first part is the normalized ratio of mutation intensity, where... This represents the average value of the methane concentration difference, in ppm. The concentration abrupt change threshold is also expressed in ppm; therefore, the difference between the two is in the same unit as the denominator, and the quotient is a dimensionless quantity. Particle size range term. Rather than the threshold The units are all millimeters, and similarly, the quotient is also dimensionless, so the entire parenthetical item is unitless.

[0066] Part Two is This represents the normalized length adjustment term for the current depth segment. The term has been dimensionlessly normalized, therefore it is unitless.

[0067] The third part is the disturbance adjustment function. This is a dimensionless correction factor. This represents the variance of the methane difference per unit depth, in ppm² / m. Since the natural logarithm function ln requires a dimensionless input, therefore... Multiplied by Afterwards, its unit influence was eliminated, that is... In dimensional processing, through Normalization converts the result to a dimensionless value, allowing for safe logarithmic calculations, and the final result remains dimensionless.

[0068] Therefore, the result obtained after dimensional balancing of all terms in the entire formula is... It is a unitless quantitative indicator, suitable for subsequent classification, comparison and sorting operations.

[0069] Based on the extracted set, the difference operation is first performed on adjacent data points in the methane concentration sequence. That is, the difference between each point in the sequence and its preceding data point is taken as the absolute value, in the form of: A total of 20 difference terms were obtained. The sum of the 20 results and the result was divided by the number of terms, 20, to obtain the average value of the methane concentration difference. To illustrate with a real-world data example, if the corresponding set of differences is... Then the summation value is set as , Then, obtain the maximum and minimum values ​​from the particle size series and set them as follows: , Then the particle size range value Here, a threshold for methane concentration variation is set. Particle size range threshold methane concentration variation threshold The settings are based on vertical depth. to The 75th percentile of the historical logging concentration difference distribution, in practical engineering, This corresponds to the upper quartile distribution boundary in the statistical analysis of concentration differences across multiple paragraphs, effectively covering the boundary of non-abnormal paragraph changes without omitting high-fluctuation segments; particle size range threshold. The settings are based on the median of the grain size differences corresponding to different rock fragment types in lithological identification. In the mixed region, particle size analysis data shows that the median particle size range is concentrated in... The value is set to approximately [left / right] to ensure the ability to distinguish between regions with abrupt changes in particle size; the depth segment length is [length missing]. In the whole well After normalization within the range, we get The variance of the methane concentration difference is:

[0070] ;

[0071] Taking actual difference data as an example, substitute the variance example value. Stability interference correction factor The setting references the drilling condition complexity level, which is classified into three levels (single-layer homogeneous, interlayer transition, and mixed interlayer). The coefficient value is selected for the mixed interlayer environment. This value is obtained by fitting the effect of variance term adjustment on index changes through comparative analysis of different sections. It is suitable for judgment scenarios with high interference conditions. Therefore, it is substituted into the formula:

[0072] ;

[0073] The calculations are as follows:

[0074] Differences are grouped into a portion:

[0075] ;

[0076] ;

[0077] ;

[0078] √ term part:

[0079] ;

[0080] Logarithmic term part:

[0081] ;

[0082] Total Calculation:

[0083] ;

[0084] This result indicates that the formation abrupt change index value corresponding to the current depth segment is... This value can be used to compare with the mutation determination benchmark value, forming the basis for subsequent mutation segment identification.

[0085] The mutation determination benchmark value is set as follows The numerical values ​​are derived from a comparison of the stratigraphic abruptness index between 200 historical depth segments without abrupt changes and 50 typical depth segments with abrupt changes. The setpoint is the maximum value for depth segments without abrupt changes. A 5% increment of the value is used as a boundary value to avoid misjudging critical paragraphs as abrupt changes, while ensuring reliable identification of abrupt changes.

[0086] Table 1. Statistical Table of Methane Concentration Difference and Particle Size Parameters

[0087]

[0088] Table 1 lists the calculation parameters and final mutation index values ​​for the corresponding depth segments, which are used for subsequent mutation segment identification and analysis.

[0089] The mutation zone identification submodule calls the formation mutation degree information, compares it with the set mutation judgment benchmark value, determines whether it exceeds the set differentiation limit range, marks the mutation zone number and start and end depth positions, establishes a section attribute and mutation status index table, and obtains mutation zone monitoring record information.

[0090] In obtaining the mutation degree index value Then, this value is compared with the preset mutation judgment benchmark value. Let's assume the set mutation judgment benchmark value is... ,when If the threshold value of a certain segment is not met, it is determined that the segment has not reached the mutation standard and is not marked. If so, the mutation segment identification process is executed, and the starting and ending depths of the segment are used to form numbered entries, such as DAB_0001. The corresponding segment information is stored in the mutation record index table. Combined with historical drilling data, the start and end positions of the mutation segment, the mutation index value, and the associated methane concentration range and particle size range value are updated in real time, and the following monitoring record data is constructed.

[0091] Table 2 Mutation Segment Identification Record Table

[0092]

[0093] Referring to Table 2, the currently identified abrupt change segments have been clearly marked with identification numbers and range information, which are used for status indexing and real-time drilling monitoring linkage processing in the logging analysis system.

[0094] Please see Figure 3 The data paragraph integrity identification module includes:

[0095] The depth segment data extraction submodule calls the monitoring and recording information of the mutation segment, locates the target data area in the real-time logging data cache according to the number and depth range of each segment, extracts the index number list of each logging data unit in the area, and generates a segment index number set;

[0096] The system retrieves the corresponding numbers and depth ranges for each segment in the mutation segment monitoring record information. First, it reads the number and corresponding start and end depths for each record in the mutation record table. Specifically, it iterates through each entry in the mutation segment record, reading the number (e.g., "DAB_0001") and the start depth. Termination depth The data, in the current logging data cache, uses a depth-based positioning mapping index to... and The start and end numbers of the corresponding data units are found in the cached data. If each meter of the cache is designated as one data unit, then the range of index numbers corresponding to this segment is: There are a total of 21 data units; then, a batch extraction operation is performed on this number range, combining each index number into a number list set in sequential order, such as the index set corresponding to segment DAB_0001. The index number sets of each segment are organized and output in a unified format. A hash index mapping table is formed with the segment number as the key and the corresponding index set as the value, which constitutes the segment index number set and is used for index integrity comparison.

[0097] The index sequence missing item identification submodule calls the logging channel index sequence in the complete segment standard template based on the segment index number set. It judges whether there are missing items at intervals in the segment index number by the sequence number, counts the length of consecutive missing segments, compares it with the missing item tolerance threshold, filters out missing segments that exceed the tolerance length, and obtains the missing segment filtering results.

[0098] Based on the segment index number set, the logging channel index sequence in the complete segment standard template is called. This standard template defines the set of channel data numbers that an ideal segment should contain. For example, if the complete standard segment channel numbering is set to 10 channel records per meter, then for the depth segment... to The corresponding standard template is a sequence of channel numbers for each depth point. , covering The standard index numbers form a set of standard sequences. ; Compare each segment index number extracted from the segment index number set to see if it is completely contained in the standard template sequence. If a number is not contained, it is considered a missing item; Sort all missing items in ascending order by number, mark consecutively missing sequence segments, and calculate the consecutive missing length of each missing segment, for example, number This constitutes a continuous missing paragraph, with a continuous missing length of . The missing term tolerance threshold is set to The threshold is set based on the longest average recovery period for a logging system channel failure. Combined with sampling interval redundancy reservation The maximum acceptable missing length is To ensure that a small number of faults do not affect the determination of data integrity, all missing data exceeding a certain length are filtered out after comparison. The missing paragraphs are filtered out.

[0099] The missing section annotation generation submodule, based on the missing paragraph filtering results, assigns a number and name to each missing section according to the start and end numbers of the marked missing sections and the channel identifier, establishes a correspondence between the section number and the missing channel, annotates the paragraph attributes, and generates a list of paragraphs with incomplete structure annotations.

[0100] Based on the start and end numbers of the missing segments and their corresponding channel identifiers indicated in the missing segment filtering results, each missing segment is assigned a number and named according to the format "MSD_channel number_start number_end number". For example, if the start number of the missing segment is 1057, the end number is 1060, and the channel number is T03, then the number is named "MSD_T03_1057_1060". Subsequently, a mapping table between the number and the corresponding channel is established, and its segment attributes are marked, including the start and end numbers, the corresponding depth value (calculated based on a 1-meter group of numbers), and the channel category, generating a list of incomplete segment annotations.

[0101] Table 3 List of missing sections

[0102]

[0103] As shown in Table 3, for the identified and numbered incomplete paragraphs, key attribute information such as the number of each missing section, the number range, the corresponding depth, and the channel identifier are clearly listed for subsequent paragraph removal, completion, or review operations.

[0104] Please see Figure 4 The monitoring priority building module includes:

[0105] The paragraph intersection recognition submodule calls the mutation section monitoring record information and the list of paragraphs with incomplete structure annotations. It identifies the overlapping paragraphs based on the consistency of the numbers, extracts the paragraph numbers that have both mutation state and structural missing features, and generates dual-attribute paragraph recognition results.

[0106] The process involves retrieving the mutation segment monitoring record information and the segment numbers from the structurally incomplete segment annotation list. First, all segment entries in both lists are traversed, and the segment number field is extracted. The segment number in the mutation record information is like "DAB_0001", and the number in the structurally incomplete annotation list is like "MSD_T03_1057_1060". To achieve intersection recognition, a standardized conversion rule is used to unify the segment number comparison format. "MSD_T03_1057_1060" is converted into an equivalent logical number "DAB_1057_1" based on its depth range. The sequence “060” is compared with the sequence number “DAB_xxx” in the mutation record in a unified format. If the start and end number ranges match completely, it is determined to be a segment intersection match. The original number of each matching segment is extracted to form a dual-attribute segment number set, that is, a segment number set that exists in both the mutation segment and the structural missing segment annotation. For example, if “DAB_1057_1060” and “MSD_T03_1057_1060” overlap in the standard numbering, then the segment is extracted. Finally, the dual-attribute segment identification result is generated as the input set for priority scheduling processing.

[0107] The priority calculation submodule extracts the weight values ​​of the mutation attribute and the structural missing attribute based on the dual-attribute paragraph identification results, using the following formula:

[0108] ;

[0109] The algorithm calculates the monitoring priority level value for each paragraph and obtains a set of paragraph priority levels.

[0110] in, Indicates the first The monitoring priority value for each paragraph. Indicates the first The weighting factor of mutation attributes in each paragraph. Indicates the first The weighting factor of structural missing attributes in each paragraph. Indicates the first The mutation attribute weight value of each paragraph, Indicates the first The structural missing attribute weight values ​​for each paragraph This represents the fluctuation adjustment coefficient for the mutation index, used to control the amplification of the normalized mutation index value in the grade calculation. Indicates the first The normalized value of the abrupt change index for each paragraph. Indicates the first Normalized value of the depth span of each paragraph. This represents the missing information distribution adjustment coefficient, used to adjust the degree of influence of the number of missing items on the overall grade. Indicates the first The number of missing data units in each paragraph;

[0111] Regarding monitoring priority levels :

[0112] This value is used to determine the priority of each segment's monitoring tasks during scheduling and execution. The calculation formula is as follows:

[0113] ;

[0114] The first part on the left side of the formula is a weighted composite of mutation attributes and structural integrity attributes, with weighting factors. , System-defined, dimensionless; mutation attribute weight values. and structural missing attribute weight values All values ​​are derived from normalized standard calculations and are also unitless; therefore, this part as a whole is dimensionless.

[0115] Part Two middle, This is the mutation regulation coefficient, which has no unit. The values ​​are normalized stratigraphic abrupt change indices and are unitless; therefore, the weighted result is a dimensionless value. The product of all terms is also unitless.

[0116] The right side of the formula is the missing depth adjustment term. This represents the normalized value of the paragraph depth span. This is a missing adjustment coefficient, without units. The number of missing data units is a pure count value, and the denominator is a unitless value, so the fraction is a unitless ratio.

[0117] In summary, the result of the entire formula calculation It serves as the sorting criterion under a unified dimension, without physical units, and is specifically used to control the order of paragraph scheduling, logically satisfying the requirement of dimensional consistency.

[0118] Based on the paragraph numbers in the dual-attribute paragraph recognition results, extract the corresponding mutation attribute weight values ​​for each item. Weight values ​​of structural missing attributes For example, the mutation attribute weight of the paragraph "DAB_1057_1060" is set to The weight of the missing structural attribute is Then set the weighting factor. , The weighting factor is set based on the following: In historical early warning responses, areas of sudden change are more sensitive to geological risks than areas of structural loss. By fitting the response impact scores of 50 early warning records, sudden changes contribute 60% to the improvement in risk level, while structural loss contributes 40%. Based on this, the weighting factor is set as follows: , Further extract the normalized values ​​of mutation indicators Depth span normalized value Number of missing data units Set adjustment coefficient , , The setting is based on the sensitivity analysis of the mutation index to changes in priority level in the range of 0.5 to 0.9. The optimal amplification factor is set to 1.2, which can amplify the impact of the mutation index on the level value to an increase of about 12% in the overall mean. The settings are based on the suppression trend analysis of missing units on rank values ​​within a range of 5 to 10 groups. To ensure that the impact of missing groups on the priority value does not exceed 25% when the number of missing groups is below 10, the following formula is used for calculation:

[0119] ;

[0120] The calculation steps are as follows:

[0121] Weighting terms:

[0122] ;

[0123] √ item:

[0124] ;

[0125] Missing penalty item:

[0126] ;

[0127] Overall priority level:

[0128] ;

[0129] The calculation result shows that the priority level of the paragraph "DAB_1057_1060" is [value missing]. A higher value indicates a higher priority.

[0130] Table 4 Priority Calculation Results

[0131]

[0132] As shown in Table 4, paragraphs with higher priority values ​​will be scheduled first.

[0133] The scheduling order sorting submodule sorts the segments according to the priority level set and the monitoring priority level value, establishes a mapping relationship between the segment number and the scheduling instruction sequence, and rearranges the logging formation monitoring instruction index in the current transmission buffer to obtain the monitoring scheduling priority segment sequence.

[0134] Based on the priority values ​​in the paragraph priority level set, all calculated paragraphs are first sorted by value, and a priority list is established in descending order. For example, the priority level value of paragraph "DAB_1057_1060" is 1.0296, which is higher than that of paragraph "DAB_1101_1105" (0.9557), so it is ranked first. Then, a bidirectional mapping table between paragraph numbers and scheduling sequence numbers is established. For example, the first scheduling instruction corresponds to "DAB_1057_1060", and the second instruction corresponds to "DAB_1101_1105". Based on this mapping relationship, a scheduling index reordering operation is performed in the transmission buffer of the current logging system. According to the sorted priority order, the processing instructions of high-priority paragraphs are written into the scheduling stack in advance, and updated to the new monitoring scheduling priority segment sequence, ensuring that the system can process key paragraph data according to the priority response order.

[0135] Please see Figure 5 The environmental mutation triggering monitoring module includes:

[0136] The environmental data acquisition submodule acquires the wind speed change value, air temperature gradient, relative humidity change rate and geomagnetic disturbance intensity monitored in real time by the external environmental monitoring unit of the logging well. It calculates the moving difference for each data sequence within a fixed time window, calculates the average value of the moving difference sequence, and generates a set of environmental disturbance mean values.

[0137] To obtain wind speed variation, air temperature gradient, relative humidity change rate, and geomagnetic disturbance intensity from the external environment monitoring unit of the logging system, it is first necessary to connect to an external sensor substation through the logging system to collect continuous monitoring data within a set time window. Assuming the time window length is 30 minutes and the sampling frequency is once per minute, each environmental parameter will obtain 30 continuous sample data points, represented as follows: Wind speed sequence Temperature gradient sequence Humidity change rate sequence Geomagnetic disturbance sequence Then, a sliding difference calculation is performed on each parameter sequence, with the sliding window size set to 1. This means that the difference between any two adjacent data points is calculated and the absolute value is taken to construct the difference sequence.

[0138] ;

[0139] The other three parameters follow the same pattern, resulting in a difference sequence. , , Each difference sequence contains 29 elements. The mean of each sequence is calculated to obtain the mean wind speed disturbance. Mean temperature disturbance Humidity disturbance mean Mean of geomagnetic disturbance This constitutes the set of mean environmental disturbance values ​​for the four parameters. The mean values ​​are used to characterize the intensity of fluctuations in various environmental factors during the time period, and are a comprehensive indicator of rapid environmental disturbances.

[0140] The threshold exceedance judgment submodule calls the wind speed sudden change limit, temperature gradient change limit, humidity jump amplitude threshold and geomagnetic disturbance limit based on the set of environmental disturbance mean values, compares the four mean values ​​with the corresponding threshold values ​​in turn, determines whether any one of them exceeds the threshold standard, and obtains the exceedance index judgment result.

[0141] Based on the parameter values ​​in the mean set of environmental disturbances, their respective preset thresholds are compared and judged, and the wind speed sudden change limit is set as follows. Temperature gradient variation limit is The threshold for humidity jump amplitude is Geomagnetic disturbance limit is The thresholds are set based on the following criteria: The values ​​are based on statistics of wind speed disturbances at drilling sites over the past 10 years, where the proportion of extreme disturbances corresponding to a frequency of change exceeding 2.5 m / s is less than 5%. This represents the upper limit of the 95% confidence interval for short-term temperature changes in typical diurnal temperature range areas. Referring to historical monitoring peak values ​​of relative humidity changes, 3.0% / min can cover the pre-rainy climate fluctuation period; The lower limit standard for regional abnormal fluctuations is derived from the annual report on geomagnetic disturbance monitoring. The average values ​​of the four disturbances are... Perform comparison operations with the threshold sequentially:

[0142] like The wind speed was deemed to be exceeding the limit.

[0143] like The temperature is deemed to be above the limit.

[0144] like The humidity level is deemed to be above the limit.

[0145] like To determine if the geomagnetic field exceeds the limit.

[0146] If the mean of any parameter exceeds the corresponding threshold, an out-of-limit disturbance event is considered to have occurred in the current time window, which is recorded as an out-of-limit state, and the state value and the corresponding time point index are recorded.

[0147] Table 5 Comparison of Mean and Threshold Values ​​of Environmental Disturbance

[0148]

[0149] As shown in Table 5, when both wind speed and geomagnetic index exceed the limit within this time window, the system determines this time point as a state of combined disturbance exceeding the limit.

[0150] The interference period calibration submodule, based on the result of the limit violation index judgment, aggregates consecutive limit violation time points according to the time point sequence marked as limit violation state, extracts the start and end times of the interference occurrence, calibrates the corresponding time period interval, establishes the correspondence between time intervals and disturbance types, and obtains a list of environmental interference intervals.

[0151] Based on the time sequence of time points marked as exceeding limits in the exceeding limit index judgment results, the system continuously records the start and end points of exceeding limits in consecutive time windows. For example, if exceeding limits exists in 5 consecutive time windows, it is aggregated into a disturbance period. Suppose the start time of the first exceeding limit window is 08:00 on June 27, 2025, and the continuous exceeding limits continue until 08:25, the system records this period as a disturbance interval, with a start and end time of [missing information]. The disturbance type was identified as a "wind speed + geomagnetic" composite disturbance. This information was then written into the disturbance range list according to structural standards, including start and end times, disturbance type, and out-of-limit parameters, forming the following structured record:

[0152] Table 6. List of Environmental Interference Sections

[0153]

[0154] As shown in Table 6, the correspondence between time periods and disturbance types has been successfully established through the calibration of the operating system, and a list of environmental interference intervals has been formed, which is used for the entry condition judgment of the subsequent data masking and error compensation processing flow.

[0155] Please see Figure 6 The channel path dynamic scheduling module includes:

[0156] The link index acquisition submodule calls the list of environmental interference intervals, extracts the round-trip delay measurement, signal strength sequence and packet reception rate of the main channel in each interference period, calculates the average value, standard deviation and rate of change of the three data, establishes the channel characteristic summary value of each interference segment, and generates the main channel stability parameter set.

[0157] The system retrieves the interference time periods marked in the environmental interference interval list, reads the start and end times of each interference segment one by one, and uses this time range as an index to locate the transmission data records of the main channel in the logging communication module during this time period. It then extracts three key link parameters within this time range: round-trip delay value sequence. (Unit is) ), signal strength sequence (Unit is) Packet reception rate sequence (Unit: percentage); the sampling period is set to 1 second. If the duration of a certain interference segment is 5 minutes, each sequence will contain 300 data points. Then, the mean, standard deviation, and rate of change are calculated for each of the three sequences, as follows:

[0158] Average round-trip delay Standard deviation rate of change ;

[0159] Average signal strength Standard deviation rate of change ;

[0160] Average packet reception rate Standard deviation rate of change .

[0161] Each set of statistics is integrated according to the interference segment dimension to generate a set of stability parameters of the main channel in that segment, including the mean round-trip delay, mean signal strength, mean packet reception rate and the corresponding standard deviation and rate of change, which constitute the main channel stability parameter set. This parameter set will serve as a reference standard for candidate channel scoring during channel handover and will be used to compare the performance differences of candidate channels in the future.

[0162] The stability score calculation submodule, based on the main channel stability parameter set, sequentially calls the current state parameters of candidate channels, normalizes the round-trip delay difference, the mean signal strength difference, and the receiver variability, and constructs a comparability score using the formula:

[0163] ;

[0164] The stability score of each candidate channel is calculated, the channel number with the highest score is selected, and the channel switching target number is obtained.

[0165] in, Indicates the first The stability score of each candidate channel. Indicates the first The normalized value of packet reception rate for each channel. Indicates the first The normalized mean of the round-trip delay of each channel. Indicates the first Normalized standard deviation of signal strength for each channel. Indicates the first The normalized mean value of the signal strength of each channel. Indicates the first The normalized value of the round-trip delay variance of each channel. This is a time delay variance adjustment factor, used to control the weight of variance in the score penalty. This is the signal strength variance scaling factor, used to control the amplification factor of the standard deviation influence term. This is an intensity enhancement factor, used to increase the proportion of the mean signal strength in the overall score;

[0166] Regarding channel stability score :

[0167] This value is used to evaluate and filter the stability of candidate channels in a multi-channel environment, and the formula is as follows:

[0168] ;

[0169] in, This is a unitless adjustment factor used to control the impact of round-trip time delay variance. This is the normalized round-trip time delay variance, which is a dimensionless value. Therefore, the denominator is unitless, and the whole is a proportional adjustment term.

[0170] The first part within the parentheses is a harmonic representation of receiver reception versus latency and signal fluctuation. , , All values ​​are normalized and have no units. The standard deviation scaling factor is also unitless; therefore, this fraction is a unitless ratio. Part Two middle, To enhance the weighting coefficients of signal strength, The normalized mean signal strength is represented by , and both are unitless, as is the product.

[0171] Final stability score It is a purely quantitative, unitless index that can be used for cross-channel comparisons and selection decisions.

[0172] Based on three indicators in the main channel stability parameter set, the mean round-trip delay is extracted respectively. Standard deviation Mean signal strength Standard deviation Average packet reception rate Following a normalization process, parameter transformation is performed on each candidate channel to obtain the normalized index for each channel. The normalization process uses an interval standardization method, calculating the relative magnitude of each difference based on the main channel:

[0173] , , , , ;

[0174] Set scoring control parameters: , , The above parameter settings are based on the following: As the round-trip delay variance control factor, simulation scoring results in 10 channels show that... The time score has too low a discrimination factor; The weight of the influence of signal variance can be increased to a secondary item, accounting for about 15% of the final score; By setting the signal strength score increase range, the influence of the average strength value is controlled to approximately 25% of the score weight, and then substituted into the scoring formula:

[0175] ;

[0176] With channel For example, the possible values ​​are as follows:

[0177] , , , , ;

[0178] The calculation is as follows:

[0179] Latency penalty items:

[0180] ;

[0181] Receive rate + strength:

[0182] ;

[0183] Final rating:

[0184] ;

[0185] Table 7 Summary of Candidate Channel Stability Scores

[0186]

[0187] As shown in Table 7, candidate channel 3 has the highest stability score. Based on this, the system selects the channel as the handover target number.

[0188] The remote data scheduling submodule performs channel path switching based on the channel switching target number. After the switching is completed, it calls the segment scheduling index corresponding to the monitoring scheduling priority segment sequence, redistributes the scheduling task according to the new channel path order, records the channel access status according to the switching time, establishes a complete communication path tracking entry, and obtains the remote link switching transmission record.

[0189] Based on the target channel number, the system first sends a handshake and activation command to the target channel interface. After confirming the reachability of the target channel, it closes the current main channel path and records the link switching path, including the start time, target number, original number, and operation completion time. For example, switching from number "C01" to "C03" starts at 08:30:05 and ends at 08:30:10. Subsequently, the system calls the previously generated monitoring and scheduling priority segment sequence to redirect the path of each segment index in the scheduling task, updates the communication channel on which the task execution depends to "C03", and writes it into the scheduling cache in the original order. Finally, a complete link switching transmission record is established, with fields including segment index, original channel number, target channel number, switching time, and current transmission status, forming a complete remote scheduling link tracing.

[0190] Table 8 Remote Link Switching Transmission Record Table

[0191]

[0192] As shown in Table 8, the communication path reconstruction and switching of the high-priority segment has been completed, and complete link operation information has been recorded for subsequent debugging or recovery operations.

[0193] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A remote monitoring system for well logging formation analysis data in high-altitude and cold regions, characterized in that, The system includes: The formation mutation monitoring module acquires the methane concentration data sequence and rock cutting particle size data sequence generated in real time during the logging operation. It calculates the average difference of adjacent data in the methane concentration sequence within each depth segment, statistically analyzes the range of rock cutting particle size data sequence in the segment, identifies formation mutation point segments, and generates mutation segment monitoring record information. The data paragraph integrity identification module calls the mutation section monitoring record information to determine whether there are consecutive missing items with a length greater than the missing item tolerance threshold, marks the missing item positions, and generates a list of paragraphs with incomplete structure. The monitoring priority order construction module evaluates the monitoring priority level of the segments based on the monitoring record information of the abrupt change segment and the list of incomplete segment labels, reconstructs the scheduling order of logging formation monitoring instructions in the current transmission scheduling cache, and generates a monitoring scheduling priority segment sequence. The environmental mutation excitation monitoring module acquires the wind speed change value, air temperature gradient, relative humidity change rate and geomagnetic disturbance intensity monitored in real time by the external environmental monitoring unit of the logging, the time of environmental excitation interference, and records the duration period, generating a list of environmental interference intervals; The information recorded in the monitoring of the mutation section specifically includes the mutation section number, depth start and end interval, gas concentration jump value, and rock cutting particle size variation. The list of incomplete structural sections includes the missing section number, missing data unit name, and missing length interval. The monitoring and scheduling priority section sequence specifically includes the section priority level value, monitoring instruction call order, and transmission scheduling index. The list of environmental interference intervals includes the interference start time, interference duration, and excitation parameter category. The system also includes: The channel path dynamic scheduling module calls the environmental interference interval list, calculates the stability score of the current channel, compares it with the current measurement value of the candidate channels, selects the channel with the highest stability score as the replacement object, and implements remote data transmission according to the monitoring and scheduling priority segment sequence to generate a remote link switching transmission record. The remote link switching transmission record specifically refers to the switching time, original channel identifier, target channel number, and switching trigger basis.

2. The remote monitoring system for well logging formation analysis data in high-altitude and cold regions according to claim 1, characterized in that, The formation abrupt change monitoring module includes: The sequence data extraction submodule acquires the methane concentration data sequence and cuttings particle size data sequence generated in real time during the logging operation, extracts the corresponding data points within a fixed depth segment, obtains the concentration sequence and particle size sequence in the depth segment, and obtains the target data extraction set; The difference numerical calculation submodule extracts the target data set, calculates the difference between adjacent data in the methane concentration series according to the methane concentration series and the particle size series, calls the difference between the maximum and minimum values ​​in the particle size series as the rock cutting particle size range value, calculates and obtains the formation mutation degree index value, and generates formation mutation degree information. The mutation segment identification submodule calls the formation mutation degree information, compares it with the set mutation judgment benchmark value, determines whether it exceeds the set differentiation limit range, marks the mutation segment number and start and end depth positions, establishes a segment attribute and mutation status index table, and obtains mutation segment monitoring record information.

3. The remote monitoring system for well logging formation analysis data in high-altitude and cold regions according to claim 2, characterized in that, The data segment integrity identification module includes: The depth segment data extraction submodule calls the monitoring and recording information of the mutation segment, locates the target data area in the real-time logging data cache according to the number and depth range corresponding to each segment, extracts the index number list of each logging data unit in the area, and generates a segment index number set; The index sequence missing item identification submodule calls the logging channel index sequence in the complete segment standard template according to the segment index number set, and judges whether there are interval missing items in the segment index number by the sequence number, counts the length of consecutive missing segments, compares it with the missing item tolerance threshold, filters missing segments that exceed the tolerance length, and obtains the missing segment filtering results. The missing segment annotation generation submodule, based on the missing segment filtering results, assigns a number and name to each missing segment according to the marked start and end numbers of the missing segment and the channel identifier, establishes a correspondence between the segment number and the missing channel, annotates the segment attributes, and generates a list of incomplete segment annotations.

4. The remote monitoring system for well logging formation analysis data in high-altitude and cold regions according to claim 3, characterized in that, The monitoring priority order construction module includes: The paragraph intersection identification submodule calls the mutation segment monitoring record information and the list of structurally incomplete paragraphs, identifies overlapping paragraphs based on the consistency of the numbers, extracts the paragraph numbers that simultaneously possess mutation state and structural missing features, and generates dual-attribute paragraph identification results. The priority level calculation submodule extracts the mutation attribute weight value and the structural missing attribute weight value based on the dual-attribute paragraph identification results, calculates and obtains the monitoring priority level value of each paragraph, and obtains the paragraph priority level set. The scheduling order sorting submodule sorts the segments according to the priority level set and the monitoring priority level value, establishes a mapping relationship between the segment number and the scheduling instruction sequence, and rearranges the logging formation monitoring instruction index in the current transmission buffer to obtain the monitoring scheduling priority segment sequence.

5. The remote monitoring system for well logging formation analysis data in high-altitude and cold regions according to claim 4, characterized in that, The environmental mutation triggering monitoring module includes: The environmental data acquisition submodule acquires the wind speed change value, air temperature gradient, relative humidity change rate and geomagnetic disturbance intensity monitored in real time by the external environmental monitoring unit of the logging well. It calculates the moving difference for each data sequence within a fixed time window, calculates the average value of the moving difference sequence, and generates a set of environmental disturbance mean values. The threshold exceedance judgment submodule calls the wind speed sudden change limit, temperature gradient change limit, humidity jump amplitude threshold and geomagnetic disturbance limit according to the set of environmental disturbance average values, compares the four average values ​​with the corresponding threshold values ​​in turn, determines whether any one of them exceeds the threshold standard, and obtains the exceedance index judgment result. The interference period calibration submodule, based on the judgment result of the over-limit index, aggregates the consecutive over-limit time points according to the time point sequence marked as over-limit state, extracts the start and end times of the interference, calibrates the corresponding time period interval, establishes the correspondence between time segments and disturbance types, and obtains a list of environmental interference intervals.

6. The remote monitoring system for well logging formation analysis data in high-altitude and cold regions according to claim 1, characterized in that, The channel path dynamic scheduling module includes: The link index acquisition submodule calls the environmental interference interval list, extracts the round-trip delay measurement, signal strength sequence and packet reception rate of the main channel in each interference period, calculates the average value, standard deviation and variability index of the three data, establishes the channel characteristic summary value of each interference segment, and generates the main channel stability parameter set. The stability score calculation submodule, based on the main channel stability parameter set, sequentially calls the current state parameters of the candidate channels, normalizes the round-trip delay difference, the mean signal strength difference, and the degree of receiver variation, constructs a comparability score, calculates and obtains the stability score value of each candidate channel, filters the channel number with the largest score value, and obtains the channel switching target number. The remote data scheduling submodule performs channel path switching based on the channel switching target number. After the switching is completed, it calls the segment scheduling index corresponding to the monitoring scheduling priority segment sequence, redistributes the scheduling task according to the new channel path order, records the channel access status according to the switching time, establishes a complete communication path tracking entry, and obtains the remote link switching transmission record.

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