Oilfield data transmission method and system based on Beidou satellite

Abstract

The invention relates to the technical field of data transmission, and discloses an oil field data transmission method and system based on a Beidou satellite, and the method comprises the steps: obtaining oil field on-site data and a data emergency level, carrying out the feature detection operation according to the oil field on-site data, and obtaining an information type corresponding to the oil field on-site data, performing feature value extraction on the information type to obtain a type feature value, performing deviation calculation operation on the type feature value and a preset normal value to obtain a deviation value, performing probability conversion operation according to the deviation value to obtain an information sensitivity degree, and performing probability conversion operation according to the information sensitivity degree and the data emergency level to obtain a data emergency level. And encrypting and compressing the oil field on-site data to obtain a to-be-sent data packet, and carrying out encrypted transmission on the to-be-sent data packet. According to the method, when the Beidou satellite is used for oil field wellhead information transmission, the reliability and safety of data transmission are improved, and meanwhile, the high efficiency of data transmission is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a Beidou satellite-based oilfield data transmission method and system. Background Art

[0002] With the continuous development of oil resources, in order to reduce the impact of oil resource development on the environment, the oil extraction process needs to not only reduce wastewater discharge, but also reduce energy consumption as much as possible. This not only helps to protect the environment, but also saves oil resources and related ancillary resources. In the underground oil extraction process, the extraction volume and underground pressure are important factors affecting the sustainable extraction of oil. Therefore, accurate monitoring of these parameters can effectively reduce energy consumption in the extraction process and reduce the impact on the environment.

[0003] In one existing technology, a method for monitoring the oil extraction process includes a method based on collecting data at the oil field wellhead. The data is transmitted to the ground for analysis via a wired network, which usually uses cables for transmission. In addition, oil extraction involves the coordinated work of multiple devices and machines to achieve the expected target effect.

[0004] In the prior art, the equipment and machines used in oil field exploitation may be subject to external attacks or fraudulent tampering, and there are problems such as unstable data transmission and insufficient security. Summary of the invention

[0005] The present invention provides an oilfield data transmission method and system based on Beidou satellites, so as to realize designing a real-time, efficient and safe transmission method in combination with the oilfield data type, characteristics and sensitivity when using Beidou satellites to transmit oilfield wellhead information, thereby improving the reliability and security of data transmission and ensuring the efficiency of data transmission.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides an oilfield data transmission method based on Beidou satellite, which is executed by a data sending end and includes: Acquiring oilfield field data and data emergency level, wherein the oilfield field data includes temperature, pressure and seepage information of the oilfield collection wellhead; Performing feature detection operations according to the oilfield field data to obtain information types corresponding to the oilfield field data; Extracting characteristic values ​​of the information type to obtain type characteristic values; Performing a deviation calculation operation on the type characteristic value and a preset normal value to obtain a deviation value; According to the deviation value, a probability conversion operation is performed to obtain the information sensitivity; According to the information sensitivity and the data urgency level, the oilfield on-site data is encrypted and compressed to obtain a data packet to be sent, and the data packet to be sent is encrypted and transmitted.

[0007] As an optional implementation manner, after the data packet to be sent is encrypted and transmitted, the method is executed by the data receiving end and further includes: The data receiving end receives the data packet to be sent and obtains an encrypted data packet; The data receiving end performs calculations based on the encrypted data packet using a statistical decision model to obtain a statistical quantity; According to the statistics, a sensitivity evaluation operation is performed on each segment of data information of the encrypted data packet to obtain a sensitivity evaluation result of each segment of data; The data receiving end determines whether to re-receive the data packet to be sent according to the sensitivity assessment result of each data segment; The data receiving end sends the statistical quantity to the data sending end, and the data sending end determines whether to re-encrypt, compress and transmit the oilfield field data according to the statistical quantity.

[0008] As an optional implementation manner, performing a feature detection operation according to the oilfield field data to obtain the information type corresponding to the oilfield field data includes: Compare and judge the oil field field data with the preset field data normal value to obtain a judgment result; The normal values ​​of the field data include normal values ​​of temperature, normal values ​​of pressure and normal values ​​of seepage information, and the type characteristic values ​​include temperature characteristic values, pressure characteristic values ​​and seepage characteristic values; According to the judgment result, the normal situation information, over-limit information and over-limit characteristic value of the oilfield field data and the information type corresponding to the oilfield field data are obtained.

[0009] As an optional implementation manner, the information type determination method of the oilfield field data includes: Determining whether the type characteristic value exceeds the preset normal value of the field data; When the type characteristic value exceeds the limit, further determining the information type of the oilfield field data, and storing the oilfield field data as numerical data or characteristic data; The numerical data include wellhead temperature, pressure, and seepage parameters, and the characteristic data include abnormal data.

[0010] As an optional implementation manner, a probability conversion operation is performed according to the deviation value to obtain the information sensitivity, including: When the transmitted data includes numerical data of the oil field field data, calculating the deviation value of the numerical data, and converting the deviation value into probability to obtain a probability result; According to the probability result, the numerical data is divided into three sensitive ranges: When the probability result of the numerical data is lower than the mean by one standard deviation, the numerical data belongs to the first sensitive range; When the probability result of the numerical data exceeds the mean by one standard deviation and is lower than the mean plus two standard deviations, the numerical data belongs to the second sensitive range; When the probability result of the numerical data is higher than the mean plus two standard deviations, the numerical data belongs to the third sensitive range; The data in the first sensitive range and the second sensitive range are sensitive data, and the data in the third sensitive range are very sensitive data.

[0011] As an optional implementation manner, the method of judging the abnormality of the transmitted data after the transmitted data includes the characteristic data of the oil field field data includes: For temperature information, when the temperature characteristic value exceeds the normal range of oil well temperature by one preset value, it is a general abnormality; when the temperature characteristic value exceeds the normal range by two preset values, it is a serious abnormality; For pressure information, when the pressure characteristic value exceeds the normal range of oil well pressure by one preset value, it is a general abnormality; when the pressure characteristic value exceeds the normal range by two preset values, it is a serious abnormality; For the seepage information, when the seepage characteristic value is lower than the normal range of oil well seepage by one preset value, it is a general abnormality; when the seepage characteristic value is lower than the normal range by two preset values, it is a serious abnormality.

[0012] As an optional implementation, the method of encrypting and compressing the oilfield field data includes: Set normal data level and abnormal data level; For the data in the third sensitive range, the general abnormality and the serious abnormality, a separate encryption and compression method is adopted; For the normal data, a weak encryption and a weak compression method are adopted; For the abnormal data, strong encryption and strong compression are adopted; The encryption and compression results of the abnormal data are transmitted in segments with a fixed length, and the encryption and compression results of the normal data are transmitted dynamically according to demand.

[0013] As an optional implementation, the method of strongly encrypting and strongly compressing the abnormal data includes: storing the abnormal data in a specific area; Counting the amount and length of the abnormal data, establishing a statistical model, analyzing the statistical characteristics of the abnormal data, and obtaining attributes such as the length of the abnormal data, the distribution of the abnormal data, and the discreteness of the abnormal data; Obtaining a compression parameter based on the length or weighted distribution of the length of the abnormal data; A key is generated based on the statistical model, and the abnormal data is encrypted using the key.

[0014] In a second aspect, the present invention provides an oilfield data transmission system based on Beidou satellite, which is configured at a data sending end and includes: A data acquisition module, used to acquire oilfield field data and data emergency level, wherein the oilfield field data includes temperature, pressure and seepage information of the oilfield collection wellhead; A feature detection module, used to perform feature detection operations according to the oilfield field data to obtain information types corresponding to the oilfield field data; A feature value extraction module extracts feature values ​​of the information type to obtain type feature values; A deviation calculation module performs a deviation calculation operation on the type characteristic value and a preset normal value to obtain a deviation value; A probability conversion module performs a probability conversion operation according to the deviation value to obtain the information sensitivity; The oilfield site data packet transmission module encrypts and compresses the oilfield site data according to the information sensitivity and the data urgency level to obtain the data packet to be sent, and transmits the data packet to be sent.

[0015] In a third aspect, the present invention also provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements any one of the above-mentioned Beidou satellite-based oilfield data transmission methods.

[0016] In a fourth aspect, the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned Beidou satellite-based oilfield data transmission methods.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides an oilfield data transmission method based on Beidou satellite, comprising: acquiring oilfield field data and data emergency level, performing feature detection operation according to the oilfield field data to obtain information type corresponding to the oilfield field data, performing feature value extraction on the information type to obtain type feature value, performing deviation calculation operation on the type feature value and a preset normal value to obtain a deviation value, performing probability conversion operation according to the deviation value to obtain information sensitivity, encrypting and compressing the oilfield field data according to the information sensitivity and the data emergency level to obtain a data packet to be sent, and encrypting and transmitting the data packet to be sent.

[0018] When the method uses Beidou satellite to transmit oilfield wellhead information, the data sending end obtains the temperature, pressure, and seepage information of the wellhead, performs feature detection, and judges the type of information, calculates its deviation from the normal value, judges its sensitivity, and classifies, encrypts, and compresses the information according to different sensitivity levels and emergency situations. The data is encrypted and transmitted by the data sending end, thereby improving the reliability and security of data transmission.

[0019] In addition, during the data encryption transmission process, the present invention introduces a statistical model of data transmission, uses statistics to evaluate the sensitivity of the transmitted data, reduces data expansion, and improves system throughput. At the same time, based on the retransmission probability and transmission effect, retransmission decisions are made and different algorithms and parameters are selected to optimize the efficiency of data transmission and improve the flexibility and practicality of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flowchart of a Beidou satellite-based oilfield data transmission method provided by an embodiment of the present invention; Figure 2 is a schematic diagram of a data transmission process provided by an embodiment of the present invention; Figure 3 It is a structural schematic diagram of a Beidou satellite-based oilfield data transmission system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] With the continuous development of oil resources, in order to reduce the impact of oil resource development on the environment, the oil extraction process needs to not only reduce wastewater discharge, but also reduce energy consumption as much as possible. This not only helps to protect the environment, but also saves oil resources and related ancillary resources. In the underground oil extraction process, the extraction volume and underground pressure are important factors affecting the sustainable extraction of oil. Therefore, accurate monitoring of these parameters can effectively reduce energy consumption in the extraction process and reduce the impact on the environment.

[0023] In one existing technology, a method for monitoring the oil extraction process includes a method based on collecting data at the oil field wellhead. The data is transmitted to the ground for analysis via a wired network, which usually uses cables for transmission. In addition, oil extraction involves the coordinated work of multiple devices and machines to achieve the expected target effect.

[0024] In the prior art, oil field mining equipment and machines may be subject to external attacks or fraudulent tampering, and there are problems such as unstable data transmission and insufficient security.

[0025] To solve the above problems, refer to Figure 1 The first embodiment of the present invention provides an oilfield data transmission method based on Beidou satellite, comprising the following steps: S1, obtaining oilfield field data and data emergency level, wherein the oilfield field data includes temperature, pressure and seepage information of the oilfield collection wellhead; S2, performing a feature detection operation according to the oilfield field data to obtain an information type corresponding to the oilfield field data; S3, extracting feature values ​​of the information type to obtain type feature values; S4, performing a deviation calculation operation on the type characteristic value and a preset normal value to obtain a deviation value; S5, performing a probability conversion operation according to the deviation value to obtain the information sensitivity; S6, encrypting and compressing the oilfield field data according to the information sensitivity and the data urgency level to obtain a data packet to be sent, and encrypting and transmitting the data packet to be sent.

[0026] In step S1, oil field field data and data emergency level are obtained.

[0027] In one implementation, the data sending end obtains the real-time temperature, pressure and seepage information of the oil field wellhead, and obtains the data emergency level according to the real-time temperature, pressure and seepage information of the wellhead.

[0028] It should be noted that the acquisition of real-time information at the wellhead of an oil field is achieved by installing a variety of sensors, such as temperature sensors, pressure sensors, flow meters, etc., at key locations in the oil field, such as the wellhead and equipment monitoring points, to achieve real-time collection of key parameters in oil field production. In the process of determining the emergency level, the system will judge the urgency of the data based on preset rules, such as setting the emergency level based on whether parameters such as temperature and pressure exceed the preset normal range. This judgment process is automatically completed by the data acquisition terminal. In special cases, the operator manually adjusts the emergency level of the data according to actual needs to ensure that important information is given priority.

[0029] In step S2, a feature detection operation is performed based on the oilfield field data to obtain information types corresponding to the oilfield field data.

[0030] In one implementation, performing a feature detection operation according to the oilfield field data to obtain the information type corresponding to the oilfield field data includes: Compare and judge the oil field field data with the preset field data normal value to obtain a judgment result; The normal values ​​of the field data include normal values ​​of temperature, normal values ​​of pressure and normal values ​​of seepage information, and the type characteristic values ​​include temperature characteristic values, pressure characteristic values ​​and seepage characteristic values; According to the judgment result, the normal situation information, over-limit information and over-limit characteristic value of the oilfield field data and the information type corresponding to the oilfield field data are obtained.

[0031] Furthermore, the information type determination method of the oilfield field data includes: Determining whether the type characteristic value exceeds the preset normal value of the field data; When the type characteristic value exceeds the limit, further determining the information type of the oilfield field data, and storing the oilfield field data as numerical data or characteristic data; The numerical data include wellhead temperature, pressure, and seepage parameters, and the characteristic data include abnormal data.

[0032] It should be noted that the method for obtaining the preset normal values ​​of the field data of the current wellhead temperature, pressure and seepage information includes: calculating the mean and standard deviation of the wellhead parameters in different time periods based on the historical parameter measurement values ​​of the wellhead, obtaining the mapping relationship between the mean and standard deviation and time, bringing the acquired real-time measurement value into the mapping relationship, calculating the corresponding standard score, and then calculating the corresponding probability and confidence level according to the check table to obtain the preset normal value.

[0033] It should be noted that the data sending end presets the normal value of the field data, and judges the wellhead temperature, pressure, and seepage information obtained in real time to determine whether it is within the value range of the normal value of the field data, and obtains the data type of the current wellhead temperature, pressure, and seepage information. Among them, the data type of the current wellhead temperature, pressure, and seepage information includes: normal situation information, over-limit information, and over-limit characteristic value of the current wellhead temperature, normal situation information, over-limit information, and over-limit characteristic value of the pressure, and normal situation information, over-limit information, and over-limit characteristic value of the seepage.

[0034] Among them, the method for judging the degree of over-limit information of the current wellhead temperature, pressure and seepage includes: judging whether the characteristic values ​​of the temperature, pressure and seepage data exceed the preset normal values ​​of the field data; if exceeded, judging the data type of the current temperature, pressure and seepage data, storing the data in different sensitive information, and dividing the data into numerical data and characteristic data, the numerical data includes the wellhead temperature, pressure and seepage parameters, and the characteristic data includes abnormal data.

[0035] Furthermore, after the transmitted data includes the characteristic data of the oil field field data, the method of judging the abnormality of the transmitted data includes: For temperature information, when the temperature characteristic value exceeds the normal range of oil well temperature by one preset value, it is a general abnormality; when the temperature characteristic value exceeds the normal range by two preset values, it is a serious abnormality; For pressure information, when the pressure characteristic value exceeds the normal range of oil well pressure by one preset value, it is a general abnormality; when the pressure characteristic value exceeds the normal range by two preset values, it is a serious abnormality; For the seepage information, when the seepage characteristic value is lower than the normal range of oil well seepage by one preset value, it is a general abnormality; when the seepage characteristic value is lower than the normal range by two preset values, it is a serious abnormality.

[0036] It should be noted that for temperature information, when the temperature characteristic value exceeds the normal temperature range of the oil well by a preset value, it is judged as a general abnormality, which usually indicates that the oil well may have slight temperature fluctuations, but will not seriously affect production. When the temperature characteristic value exceeds the normal range by two preset values, it is judged as a serious abnormality. At this time, the obvious change in temperature may indicate a potential production risk, which requires further investigation and processing.

[0037] For pressure information, when the pressure characteristic value exceeds the normal pressure range of the oil well by a preset value, it is classified as a general abnormality, indicating that the pressure fluctuates within a certain range, which may have a certain impact on production, but has not yet reached a critical level. When the pressure characteristic value exceeds the normal range by two preset values, it is classified as a severe abnormality, indicating that the oil well may face a greater risk of pressure changes, indicating that immediate measures need to be taken.

[0038] For seepage information, when the seepage characteristic value is lower than a preset value in the normal seepage range of the oil well, it is a general abnormality, indicating that the seepage has decreased to a certain extent, which may affect the oil well production. When the seepage characteristic value is lower than two preset values ​​in the normal range, it is a serious abnormality, indicating that the seepage has decreased significantly, indicating that the oil well is blocked or has other problems.

[0039] In step S3, feature value extraction is performed on the information type to obtain a type feature value.

[0040] In one implementation, the data sending end presets the normal value of the field data, and judges the wellhead temperature, pressure, and seepage information obtained in real time to determine whether it is within the value range of the normal value of the field data, and obtains the characteristic value of the current wellhead temperature, the characteristic value of the pressure, and the characteristic value of the seepage.

[0041] It should be noted that the determination of whether the wellhead temperature, pressure and seepage information obtained in real time is within the range of normal values ​​of field data includes: For the wellhead temperature, the preset normal temperature range is set to 60°C to 80°C. When the real-time collected wellhead temperature is 75°C, the temperature value is within the preset normal range, so the temperature value is recorded as a normal temperature characteristic value. When the real-time temperature data is 85°C, which exceeds the normal range by one preset value, the temperature characteristic value is marked as "general abnormality". When the real-time temperature data reaches or exceeds 90°C, which exceeds the normal range by two preset values, the temperature characteristic value will be marked as "serious abnormality".

[0042] For pressure information, the preset normal pressure range is set to 2MPa to 5MPa. When the real-time collected pressure value is 4MPa, which is within the normal range, the pressure value will be used as the normal pressure characteristic value. When the real-time pressure is 1MPa, which is one preset value lower than the normal range, the pressure characteristic value will be marked as "general abnormality". When the real-time pressure drops to 0.5MPa, which is two preset values ​​lower than the normal range, the pressure characteristic value will be marked as "serious abnormality".

[0043] For seepage information, the preset normal seepage range is set to 10m³ / h to 15m³ / h. When the real-time seepage data is 12m³ / h, the seepage characteristic value is within the normal range. When the real-time seepage data drops to 8m³ / h, which is one preset value lower than the normal range, the seepage characteristic value will be marked as "general abnormality". If the real-time seepage data further drops to 5m³ / h, which is two preset values ​​lower than the normal range, the seepage characteristic value will be marked as "serious abnormality".

[0044] In step S4, a deviation calculation operation is performed on the type characteristic value and a preset normal value to obtain a deviation value.

[0045] In one implementation, the data receiving end calculates the deviation value according to the type characteristic value and the preset normal value of the field data according to the deviation calculation formula.

[0046] It should be noted that the deviation calculation formula can be expressed as:

[0047] in, Indicates The deviation value of the class data, It means to obtain temperature characteristic value, pressure characteristic value and seepage characteristic value in real time. Indicates The default normal value for class data.

[0048] In step S5, a probability conversion operation is performed according to the deviation value to obtain the information sensitivity, including: When the transmitted data includes numerical data of the oil field field data, calculating the deviation value of the numerical data, and converting the deviation value into probability to obtain a probability result; According to the probability result, the numerical data is divided into three sensitive ranges: When the probability result of the numerical data is lower than the mean by one standard deviation, the numerical data belongs to the first sensitive range; When the probability result of the numerical data exceeds the mean by one standard deviation and is lower than the mean plus two standard deviations, the numerical data belongs to the second sensitive range; When the probability result of the numerical data is higher than the mean plus two standard deviations, the numerical data belongs to the third sensitive range; The data in the first sensitive range and the second sensitive range are sensitive data, and the data in the third sensitive range are very sensitive data.

[0049] It should be noted that when obtaining the deviation value Then, using statistical models or distribution functions, the deviation values Convert it into a probability value and get the probability result The probability result indicates the degree of abnormality of the data. The larger the probability, the greater the deviation of the data.

[0050] Based on this probability result, the numerical data can be divided into the following three sensitive ranges: First sensitive range: when the probability result Below the mean minus one standard deviation When , the data belongs to the first sensitive range. At this time, the data deviates from the normal range to a small extent and is usually considered to be a slight fluctuation.

[0051] Second sensitive range: when the probability result Between one standard deviation from the mean and two standard deviations from the mean (i.e. ), the data belongs to the second sensitive range, indicating that the data deviates more significantly from the normal range and there is a certain risk.

[0052] The third sensitive range: when the probability result Above the mean plus two standard deviations When the data is in the third sensitive range, it means that the data seriously deviates from the normal range. At this time, the data is in an abnormal state and is considered to be very sensitive, requiring immediate attention and processing.

[0053] In step S6, the oilfield on-site data is encrypted and compressed according to the information sensitivity and the data urgency level to obtain a data packet to be sent, and the data packet to be sent is encrypted for transmission.

[0054] In one implementation, the method of encrypting and compressing the oilfield field data includes: Set normal data level and abnormal data level; For the data in the third sensitive range, the general abnormality and the serious abnormality, a separate encryption and compression method is adopted; For the normal data, a weak encryption and a weak compression method are adopted; For the abnormal data, strong encryption and strong compression are adopted; The encryption and compression results of the abnormal data are transmitted in segments with a fixed length, and the encryption and compression results of the normal data are transmitted dynamically according to demand.

[0055] Furthermore, the method of strongly encrypting and strongly compressing the abnormal data includes: storing the abnormal data in a specific area; Counting the amount and length of the abnormal data, establishing a statistical model, analyzing the statistical characteristics of the abnormal data, and obtaining attributes such as the length of the abnormal data, the distribution of the abnormal data, and the discreteness of the abnormal data; Obtaining a compression parameter based on the length or weighted distribution of the length of the abnormal data; A key is generated based on the statistical model, and the abnormal data is encrypted using the key.

[0056] Furthermore, the data with general abnormality is compressed at level three, the data with serious abnormality is compressed at level four, and the normal data of different levels is compressed at level one. The encryption and compression results of the abnormal data are sent in segments with a fixed length, and the encryption and compression results of the normal data are transmitted dynamically according to demand.

[0057] It should be noted that the implementation methods of the first-stage compression, the second-stage compression and the third-stage compression include: Level 1 compression: Determine the value of normal data. For large numbers of data, divide them into data segments of equal length. Convert the data segments into binary data, convert continuous binary data into discrete data, and compress them. After compression, convert the data into 8-bit binary data. Then, based on the statistical model, perform statistical judgment on the data segments in the statistical model, delete redundant character strings, and mark them.

[0058] Secondary compression: Determine the value of normal data. For large numbers of data, divide them into data segments of equal length. Convert the data segments into binary data, convert continuous binary data into discrete data, and compress them. After compression, convert the data into 8-bit binary data. Then, based on the statistical model, perform statistical judgment on the data segments in the statistical model, delete redundant character strings, and mark them.

[0059] Level 3 compression: Determine the value of normal data. For large data, divide it into data segments of equal length. Convert the data segments into binary data. Convert continuous binary data into discrete data for compression. Convert the data into 8-bit binary data after compression. Perform statistical judgment on the data segments in the statistical model according to the statistical model, delete redundant character strings, and mark them.

[0060] Furthermore, the weakened encryption and weakened compression implementations include: An additive encryption or multiplicative encryption model is established based on the data and statistical model, that is, F(x)=f((k1x1+k2x2+k3x3+…+knxn)mod 255), a statistical dictionary is established, and the encryption result is compressed, where F(·) represents the encryption function, f(·) represents the compression function, k1-0knn∈R, xn is the value at each moment, and 0kn≤n.

[0061] In order to facilitate the understanding of the present invention, some preferred embodiments of the present invention are further described below.

[0062] In a preferred embodiment, after the data packet to be sent is encrypted and transmitted, the method is executed by the data receiving end and further includes: The data receiving end receives the data packet to be sent and obtains an encrypted data packet; The data receiving end performs calculations based on the encrypted data packet using a statistical decision model to obtain a statistical quantity; According to the statistics, a sensitivity evaluation operation is performed on each segment of data information of the encrypted data packet to obtain a sensitivity evaluation result of each segment of data; The data receiving end determines whether to re-receive the data packet to be sent according to the sensitivity assessment result of each data segment; The data receiving end sends the statistical quantity to the data sending end, and the data sending end determines whether to re-encrypt, compress and transmit the oilfield field data according to the statistical quantity.

[0063] It should be noted that the statistic can be used as a quantitative indicator of the current data packet status for subsequent sensitivity assessment and data integrity judgment. The sensitivity assessment operation can be achieved by comparing the degree of abnormality of each data segment in the data packet, such as deviation or fluctuation, so as to determine which data segments are more important or need priority processing. The evaluation results are used to judge the reliability and transmission quality of the data packet.

[0064] The statistics are expressed as:

[0065] in, is a statistic, It is Statistics of segment data, is the number of data segments, It is The weight of the segment data, The calculation is as follows: , It is The transmission time of the packet data, It is The sensitivity of the packet data, It is The transmission time requirements of the segment data information, It is the abnormality of the data transmission process.

[0066] The following describes the working process of the present invention using a relatively common scenario as an example. The working process is as follows: Step 1: Collect data from the oil field, perform feature detection, and determine the type of information; Step 2: Determine the deviation between the characteristic value of the information type and the preset normal value, and calculate the sensitivity of the information. The information is collected at the data sending end, and the collected data is subjected to feature detection to determine the information type, determine the deviation between the characteristic value and the preset normal value, and calculate its sensitivity. Step 3: Classify, encrypt and compress the data according to its sensitivity and urgency, and then encrypt and transmit it at the data sender; Step 4: The data receiving end receives the data, obtains statistics, and evaluates the sensitivity of the transmitted data; Preferably, in step 2, the information types include three types, each of which corresponds to a certain information characteristic value. The information characteristic value that deviates greatly from the preset normal value is a sensitive information type, and the corresponding information sensitivity is high. After obtaining the information requirements of the data receiving end, the data sending end performs a characteristic test on the collected information to determine its information type and the deviation from the preset normal value. If the information type is "0", it will not be sent, and if it is "1", it will be sent.

[0067] Preferably, in step 3, the sensitivity of the information is set to α, and the emergency situation of the data is set to β. The transmission process is divided into two steps. In the first step, the data sending end encrypts the collected information, and encrypts the sensitive information of (α×β) using an advanced encryption algorithm to obtain an encrypted data packet γ. The data sending end compresses the collected information, and compresses the normal data of β(1-α) according to the sensitivity using run-length coding or Huffman coding to obtain a compressed data packet φ. In the second step, the encrypted data packet γ and the compressed data packet φ are combined into a new data packet η for transmission. When the combined length of the encrypted data packet γ and the compressed data packet φ exceeds a preset length, a method in which the compressed data packet φ accounts for a large proportion in each packet of transmitted data is selected to ensure that the encrypted data packet γ is sent first.

[0068] It should be noted that encryption and compression are classified according to the sensitivity and urgency of the data. The specific methods include: Classification and encryption of data: In the step of data classification, non-important data such as time, GPS location, current and other data are defined as 0, and important data such as pressure, temperature and seepage are defined as 1. The importance of each field, that is, the sensitivity of the data, is calculated, and the data with a sensitivity of 1 is encrypted by AES, and the data with a sensitivity of 0 is not encrypted. In the step of data encryption, the data is represented as a hexadecimal string, grouped into groups of 64 bits, and a 16 / 64-bit key is added. The part less than 64 bits is filled with 0. Each data block is encoded after being concatenated with the key. An 8-bit non-zero integer is used to represent a valid code. If it is greater than 1, the complement is performed before encoding. The code is iterated multiple times, and byte replacement and row shift operations are performed in each iteration.

[0069] Data compression processing: calculate the importance of each field, perform lossy compression on data with a sensitivity of 1, perform unimportant data such as time, GPS positioning, etc., and do not compress data with a sensitivity of 0. The data compression method uses run-length coding and Huffman coding. Based on the principle of large compression ratio, different coding methods are used for different types of data. Run-length coding is an algorithm for compressing data sequences. First, the number of occurrences of the encoding object character is counted, and a series of repeated characters are represented by this character and the number of repetitions. For example, when the original data is "FFFFFF", the run-length coding is W12, when the original data is "ABABABAAAB", the run-length coding is A16B12; when the original data is "ABABAAAB", the run-length coding is A16B8. Huffman coding is a data representation method that defines the encoding length of a character according to probability. In order to increase the encoding efficiency, the character with the smallest probability is always used as the root node when encoding characters. The choice of left or right exit is made on the branch with a smaller probability, and it is defined by binary 0 and 1. In the character encoding process, each character corresponds to a path, and finally a branched tree structure is obtained. During transmission, it is transmitted according to the symbol sequence corresponding to the path.

[0070] Preferably, in step 4, during the encrypted transmission process, the data receiving end determines the importance of the data by evaluating the data transmission volume. When it is determined that the length of the encrypted data packet γ exceeds the preset length, it indicates that the importance level α is greater than 1, that is, it is considered that new important data has occurred. The data receiving end needs to stop receiving the original data and give priority to receiving the important data until the important data transmission is completed, thereby ensuring the real-time data transmission.

[0071] Reference Figure 2 The data sender decides whether to transmit, retransmit, compress, or encrypt data frame information based on the size of the statistics. The data receiver evaluates the data sensitivity based on the statistics to decide whether it needs to be received again. The data receiver then decides on the transmission plan based on these statistics, reducing the number of data transmissions and the error rate, so as to improve the accuracy and security of data transmission.

[0072] It should be noted that the statistics are expressed as:

[0073] in, is a statistic, It is Statistics of segment data, is the number of data segments, It is The weight of the segment data, The calculation is as follows: , It is The transmission time of the packet data, It is The sensitivity of the packet data, It is The transmission time requirements of the segment data information, It is the abnormality of the data transmission process.

[0074] In summary, in the present invention, the temperature, pressure, and seepage information of the wellhead are obtained through the data sending end, feature detection is performed, and the information type is judged, its deviation from the normal value is calculated, its sensitivity is judged, and statistical models and statistical decisions are used to classify, encrypt and compress according to different sensitivity levels and emergency situations. The data is encrypted and transmitted by the data sending end. During the transmission process, the sensitivity of each segment of transmission data is evaluated by statistics to avoid data expansion during encryption and compression. In the encryption process, the present invention introduces a statistical model of data transmission, uses statistics to evaluate the sensitivity of transmission data, reduces data expansion, and improves system throughput. At the same time, according to the retransmission probability and transmission effect, retransmission decisions are adopted, and different algorithms and parameters are selected to optimize the efficiency of data transmission and improve the flexibility and practicality of the system.

[0075] Reference Figure 3 The second embodiment of the present invention provides an oilfield data transmission system based on Beidou satellite, comprising: 101 data acquisition module, used to acquire oil field field data and data emergency level, the oil field field data includes temperature, pressure and seepage information of oil field collection wellhead; 102 a feature detection module, used to perform a feature detection operation according to the oilfield field data to obtain information types corresponding to the oilfield field data; 103 a feature value extraction module, extracting feature values ​​of the information type to obtain type feature values; 104, a deviation calculation module, performs a deviation calculation operation on the type characteristic value and a preset normal value to obtain a deviation value; 105 probability conversion module, performing probability conversion operation according to the deviation value to obtain information sensitivity; 106 The oilfield site data packet transmission module encrypts and compresses the oilfield site data according to the information sensitivity and the data urgency level to obtain a data packet to be sent, and transmits the data packet to be sent.

[0076] It should be noted that the Beidou satellite-based oilfield data transmission system provided in an embodiment of the present invention is used to execute all the process steps of the Beidou satellite-based oilfield data transmission method in the above embodiment. The working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0077] In summary, the present invention provides an oilfield data transmission method based on Beidou satellite, comprising: acquiring oilfield field data and data urgency level, performing feature detection operation according to the oilfield field data to obtain information type corresponding to the oilfield field data, performing feature value extraction on the information type to obtain type feature value, performing deviation calculation operation on the type feature value and a preset normal value to obtain a deviation value, performing probability conversion operation according to the deviation value to obtain information sensitivity, encrypting and compressing the oilfield field data according to the information sensitivity and the data urgency level to obtain a data packet to be sent, and encrypting and transmitting the data packet to be sent.

[0078] When the method uses Beidou satellite to transmit oilfield wellhead information, the data sending end obtains the temperature, pressure, and seepage information of the wellhead, performs feature detection, and judges the type of information, calculates its deviation from the normal value, judges its sensitivity, and classifies, encrypts, and compresses the information according to different sensitivity levels and emergency situations. The data is encrypted and transmitted by the data sending end, thereby improving the reliability and security of data transmission.

[0079] In addition, during the data encryption transmission process, the present invention introduces a statistical model of data transmission, uses statistics to evaluate the sensitivity of the transmitted data, reduces data expansion, and improves system throughput. At the same time, based on the retransmission probability and transmission effect, retransmission decisions are made and different algorithms and parameters are selected to optimize the efficiency of data transmission and improve the flexibility and practicality of the system.

[0080] The embodiment of the present invention also provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a Beidou satellite-based oilfield data transmission method program. When the processor executes the computer program, the steps in the above-mentioned Beidou satellite-based oilfield data transmission method embodiments are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are realized, such as the data acquisition module.

[0081] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0082] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0083] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0084] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0085] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0086] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0087] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A Beidou satellite-based oilfield data transmission method, characterized in that: Executed by the data sender, including: Acquiring oilfield field data and data emergency level, wherein the oilfield field data includes temperature, pressure and seepage information of the oilfield collection wellhead; Performing feature detection operations according to the oilfield field data to obtain information types corresponding to the oilfield field data; Extracting characteristic values ​​of the information type to obtain type characteristic values; Performing a deviation calculation operation on the type characteristic value and a preset normal value to obtain a deviation value; According to the deviation value, a probability conversion operation is performed to obtain the information sensitivity; According to the information sensitivity and the data urgency level, the oilfield on-site data is encrypted and compressed to obtain a data packet to be sent, and the data packet to be sent is encrypted and transmitted.

2. The method for oilfield data transmission based on Beidou satellite according to claim 1, characterized in that: After the data packet to be sent is encrypted and transmitted, the method is executed by the data receiving end, and further includes: The data receiving end receives the data packet to be sent and obtains an encrypted data packet; The data receiving end calculates according to the encrypted data packet using a statistical decision model to obtain a statistical quantity; According to the statistics, a sensitivity evaluation operation is performed on each segment of data information of the encrypted data packet to obtain a sensitivity evaluation result of each segment of data; The data receiving end determines whether to re-receive the data packet to be sent according to the sensitivity assessment result of each data segment; The data receiving end sends the statistical quantity to the data sending end, and the data sending end determines whether to re-encrypt, compress and transmit the oilfield field data according to the statistical quantity.

3. The method for oilfield data transmission based on Beidou satellite according to claim 1, characterized in that: The feature detection operation is performed according to the oilfield field data to obtain the information type corresponding to the oilfield field data, including: Compare and judge the oil field field data with the preset field data normal value to obtain a judgment result; The normal values ​​of the field data include normal values ​​of temperature, normal values ​​of pressure and normal values ​​of seepage information, and the type characteristic values ​​include temperature characteristic values, pressure characteristic values ​​and seepage characteristic values; According to the judgment result, the normal situation information, over-limit information and over-limit characteristic value of the oilfield field data and the information type corresponding to the oilfield field data are obtained.

4. The Beidou satellite-based oilfield data transmission method according to claim 3 is characterized in that: The information type determination method of the oilfield field data includes: Determining whether the type characteristic value exceeds the preset normal value of the field data; When the type characteristic value exceeds the limit, further determining the information type of the oilfield field data, and storing the oilfield field data as numerical data or characteristic data; The numerical data include wellhead temperature, pressure, and seepage parameters, and the characteristic data include abnormal data.

5. The method for oilfield data transmission based on Beidou satellite according to claim 4 is characterized in that: According to the deviation value, a probability conversion operation is performed to obtain the information sensitivity, including: When the transmitted data includes numerical data of the oil field field data, calculating the deviation value of the numerical data, and converting the deviation value into probability to obtain a probability result; According to the probability result, the numerical data is divided into three sensitive ranges: When the probability result of the numerical data is lower than the mean by one standard deviation, the numerical data belongs to the first sensitive range; When the probability result of the numerical data exceeds the mean by one standard deviation and is lower than the mean plus two standard deviations, the numerical data belongs to the second sensitive range; When the probability result of the numerical data is higher than the mean plus two standard deviations, the numerical data belongs to the third sensitive range; The data in the first sensitive range and the second sensitive range are sensitive data, and the data in the third sensitive range are very sensitive data.

6. The Beidou satellite-based oilfield data transmission method according to claim 5, characterized in that: After the transmitted data includes the characteristic data of the oil field field data, the method of judging the abnormality of the transmitted data includes: For temperature information, when the temperature characteristic value exceeds the normal range of oil well temperature by one preset value, it is a general abnormality; when the temperature characteristic value exceeds the normal range by two preset values, it is a serious abnormality; For pressure information, when the pressure characteristic value exceeds the normal range of oil well pressure by one preset value, it is a general abnormality; when the pressure characteristic value exceeds the normal range by two preset values, it is a serious abnormality; For the seepage information, when the seepage characteristic value is lower than the normal range of oil well seepage by one preset value, it is a general abnormality; when the seepage characteristic value is lower than the normal range by two preset values, it is a serious abnormality.

7. The Beidou satellite-based oilfield data transmission method according to claim 6, characterized in that: The method of encrypting and compressing the oilfield field data includes: Set normal data level and abnormal data level; For the data in the third sensitive range, the general abnormality and the serious abnormality, a separate encryption and compression method is adopted; For the normal data, a weak encryption and a weak compression method are adopted; For the abnormal data, strong encryption and strong compression are adopted; The encryption and compression results of the abnormal data are transmitted in segments with a fixed length, and the encryption and compression results of the normal data are transmitted dynamically according to demand.

8. The Beidou satellite-based oilfield data transmission method according to claim 7, characterized in that: The method of strongly encrypting and strongly compressing the abnormal data includes: storing the abnormal data in a specific area; Counting the amount and length of the abnormal data, establishing a statistical model, analyzing the statistical characteristics of the abnormal data, and obtaining attributes such as the length of the abnormal data, the distribution of the abnormal data, and the discreteness of the abnormal data; Obtaining a compression parameter based on the length or weighted distribution of the length of the abnormal data; A key is generated based on the statistical model, and the abnormal data is encrypted using the key.

9. An oilfield data transmission system based on Beidou satellite, characterized in that: Configuration on the data sending end includes: A data acquisition module, used to acquire oilfield field data and data emergency level, wherein the oilfield field data includes temperature, pressure and seepage information of the oilfield collection wellhead; A feature detection module, used to perform feature detection operations according to the oilfield field data to obtain information types corresponding to the oilfield field data; A feature value extraction module extracts feature values ​​of the information type to obtain type feature values; A deviation calculation module performs a deviation calculation operation on the type characteristic value and a preset normal value to obtain a deviation value; A probability conversion module performs a probability conversion operation according to the deviation value to obtain the information sensitivity; The oilfield site data packet transmission module encrypts and compresses the oilfield site data according to the information sensitivity and the data urgency level to obtain the data packet to be sent, and transmits the data packet to be sent.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the Beidou satellite-based oilfield data transmission method as described in any one of claims 1 to 8.

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