Microseismic data transmission method and device

Abstract

The application provides a microseismic data transmission method and device, comprising the following steps: sending a request command to a central server; judging whether normal data transmission work can be performed based on the request command; if yes, sending microseismic data to the central server by using a relay communication mode based on a first mode; and if no, sending the microseismic data to the central server through an optimal data multi-hop path based on a second mode, so that real-time transmission of the microseismic data is ensured and the demand for real-time monitoring of microseismic events is met.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of microseismic, in particular to a microseismic data transmission method and device. BACKGROUND

[0002] In recent years, with the development of economy, people's demand for energy is increasing, and the intensity of energy exploitation is also increasing. In the process of energy exploitation, due to the change of stress field, the soil layer and rock mass structure of the exploitation tunnel are destroyed, and then a low energy earthquake, i.e. microseismic event, is caused. Through real-time monitoring of microseismic, the reservoir reconstruction fracture network can be effectively characterized, and the geometric direction and spatial distribution of the fracturing fracture can be inverted, so as to guide the adjustment of fracturing parameters on site, evaluate the fracturing effect. Based on this, it is necessary to monitor microseismic in real time and obtain microseismic related data, and then use the wireless access point as a relay to transmit the data back to the center server in a relay communication mode, and use the center server to process the microseismic related data. However, when the energy of the wireless access point is insufficient, data transmission cannot be performed, and thus the microseismic related data cannot be transmitted back to the center server in real time. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a microseismic data transmission method and device, which can ensure real-time transmission of microseismic data when the wireless access point cannot relay communication due to insufficient energy, and achieve the purpose of real-time monitoring of microseismic events.

[0004] In a first aspect, the present application provides a microseismic data transmission method, characterized in that it comprises:

[0005] Step 1: sending a request command to a center server;

[0006] Step 2: determining whether normal data transmission work can be performed based on the request command;

[0007] Step 3: if yes, based on a first mode, using a relay communication mode to send microseismic data to the center server;

[0008] If not, based on a second mode, the microseismic data is sent to the center server through an optimal data multi-hop path.

[0009] The optimal data multi-hop path is obtained through a fuzzy comprehensive evaluation model, and the fuzzy comprehensive evaluation model is established through a network model and an energy model.

[0010] Preferably, the optimal data multi-hop path is obtained through a fuzzy comprehensive evaluation model, which comprises:

[0011] A communication path is established by route selection, and a routing path is obtained based on the communication path;

[0012] The routing path is evaluated by the fuzzy comprehensive evaluation model to obtain the optimal data multi-hop path.

[0013] Preferably, the energy model comprises:

[0014] a set of indicators, a set of weights, and a set of comments,

[0015] The set of indicators includes a first set of indicators and a second set of indicators. The first set of indicators is X, which includes first indicator factors x1, x2, and x3, and is represented by the following formula:

[0016] X = (x1, x2, x3)

[0017] The second set of indicators is U, which includes second indicator factors u1, u2,..., u n , and is represented by the following formula:

[0018] U = (u1, u2,..., u n )

[0019] The set of weights is U ki , which indicates the weights corresponding to the second set of indicators, where k = 1, 2, 3, 4, and i = 1, 2,..., n, and is represented by the following formula:

[0020] U ki = (u k1 ,u k2 ,...,u kn )

[0021] The set of comments is P j , where j = 1, 2, 3, 4, and is represented by the following formula:

[0022] P j = (p1, p2, p3, p4)

[0023] Preferably, the fuzzy comprehensive evaluation model is established by a network model and an energy model, comprising:

[0024] Step 101: Obtain a fuzzy evaluation matrix R k based on the network model and the energy model;

[0025] Step 102: Obtain a membership matrix R k based on the fuzzy evaluation matrix R k ;

[0026] Step 103: Establish a fuzzy comprehensive evaluation model based on the membership matrix R k .

[0027] Preferably, the fuzzy evaluation matrix R is obtained based on the network model and the energy model. k include:

[0028] Based on the network model and energy model, the membership degree r is obtained. ij Based on the membership degree r ij Obtain the fuzzy evaluation matrix R k ;

[0029] The membership degree r ij This can be expressed by the following formula:

[0030]

[0031] The fuzzy evaluation matrix is ​​R. k , where i = 1, 2, ..., s; j = 1, 2, 3, 4, is represented by the following formula:

[0032]

[0033] Preferably, the step based on the fuzzy evaluation matrix R k Obtaining the membership matrix R includes:

[0034] For the fuzzy evaluation matrix R k Perform fuzzy processing to obtain the membership vector B. k Based on the membership vector B k Obtain the membership matrix R;

[0035] The membership vector B k This can be expressed by the following formula:

[0036] B k =A k ×R k =(b k1 b k2 b k3 b k4 )

[0037] The membership matrix R is expressed by the following formula:

[0038]

[0039] Preferably, establishing the fuzzy comprehensive evaluation model based on the membership matrix R includes:

[0040] The membership matrix R is subjected to fuzzy transformation to obtain the membership vector B. The membership vector B is normalized to obtain the membership degree B. A fuzzy comprehensive evaluation model is established based on the membership degree B.

[0041] In a second aspect, an embodiment of the present application provides a microseismic data transmission device, characterized in that comprising:

[0042] The command sending module sends a request command to the center server.

[0043] The judgment module judges whether normal data transmission work can be performed based on the request command.

[0044] The data sending module sends the microseismic data to the center server based on a first mode by using a relay communication mode if yes.

[0045] The data sending module sends the microseismic data to the center server through an optimal data multi-hop path based on a second mode if no.

[0046] In a third aspect, an embodiment of the present application provides a computing device, characterized in that comprising:

[0047] One or more processing units;

[0048] A storage unit for storing one or more programs,

[0049] When the one or more programs are executed by the one or more processing units, the one or more processing units execute the method of the first aspect.

[0050] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium having non-volatile program code executable by a processor, characterized in that the computer program is executed by the processor to implement the method of the first aspect.

[0051] The embodiment of the present application has the following beneficial effects: by sending a request command to the center server and judging whether normal data transmission work can be performed based on the request command, if yes, sending the microseismic data to the center server based on a first mode by using a relay communication mode, and if no, sending the microseismic data to the center server through an optimal data multi-hop path based on a second mode, the microseismic data can be transmitted in real time in the case that the wireless access point as a relay point is insufficient in energy and cannot transmit data, and the purpose of real-time monitoring of microseismic events is achieved.

[0052] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be learned from practice of the present application. The purpose and other advantages of the present application will be achieved and obtained in the structure specifically pointed out in the specification, claims and drawings.

[0053] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the following preferred embodiments are specifically described below, and the accompanying drawings are referred to. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the specific embodiments or prior art of the present application, the drawings needed to be used in the description of the specific embodiments or prior art will be briefly introduced as follows. Obviously, the drawings described below are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0055] Figure 1 A microseismic data transmission method flow chart provided for an embodiment of the present application;

[0056] Figure 2 A microseismic data transmission method seismic acquisition node schematic diagram provided for an embodiment of the present application;

[0057] Figure 3 A microseismic data transmission method node seismograph quantity statistical diagram of nodes capable of communication before and after interrupting AP provided for an embodiment of the present application;

[0058] Figure 4 A microseismic data transmission method center server data packet receiving quantity statistical diagram before and after interrupting AP provided for an embodiment of the present application;

[0059] Figure 5 A microseismic data transmission method network average delay statistical diagram before and after interrupting AP provided for an embodiment of the present application;

[0060] Figure 6 A microseismic data transmission method data packet sending rate statistical diagram before and after interrupting AP provided for an embodiment of the present application;

[0061] Figure 7 A microseismic data transmission device schematic diagram provided for an embodiment of the present application. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the present application will be described clearly and completely below with reference to the drawings. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0063] In order to facilitate the understanding of the present embodiment, the drawings will be combined with Figure 1 A seismic data transmission method disclosed in the embodiments of the present application will be described in detail.

[0064] Embodiment 1:

[0065] The microseismic data transmission method disclosed by the embodiment of the application is implemented in the following steps:

[0066] Step 1: sending a request command to the central server, including: sending a request command to the central server based on a first seismic acquisition node;

[0067] The first seismic acquisition node is a seismic acquisition node that needs to send microseismic data, as shown in FIG. 1, each seismic acquisition node includes a three-component geophone and a node seismograph, the three-component geophone is arranged underground and connected with the node seismograph, and the node seismograph includes the following units: a power supply unit, a data acquisition unit, a wireless transmission unit and a control unit. Figure 2

[0068] The power supply unit is used for power supply of the node seismograph and includes a voltage conversion module and a power supply module.

[0069] The data acquisition unit is used for acquiring microseismic data from the three-component geophone and includes an ADS1282 analog-to-digital conversion chip and a data preprocessing module, the data preprocessing module is used for compression coding and filtering shaping of the microseismic data.

[0070] The wireless transmission unit is used for wireless data communication and includes a mode selection module, a 5.8GHz wireless communication module, a 2.4GHz wireless communication module and a WIFI control module, the mode selection module is used for selecting a first mode or a second mode for wireless data communication, the first mode is a single-hop mode and the second mode is a multi-hop mode; when the node seismograph is in the first mode, the wireless transmission unit can only perform data sending work and cannot perform data receiving work; when the node seismograph is in the second mode, the wireless transmission unit can perform data sending work and data receiving work.

[0071] The control unit is used for receiving microseismic data from the data acquisition unit and sending the microseismic data to the wireless transmission unit and includes a CPLD operation control module, a status indicator light, an STM32F429 processor, a data transmission module, a Bluetooth transmission module, a GPS positioning and timing module and a data storage module, the Bluetooth transmission module is used for transmitting the microseismic data to a mobile user terminal, the GPS positioning and timing module is used for completing positioning and timing work, and the data storage module is used for storing the microseismic data in an SD card.

[0072] ​Specifically, the first seismic acquisition node and the center server can communicate in a direct communication or a relay communication, wherein the direct communication is that the first seismic acquisition node directly sends a request command to the center server; the relay communication is that the first seismic acquisition node sends a request command to a neighboring access point (AP) as a relay, and the AP neighboring the first seismic acquisition node in a geographical position sends the request command to the center server.

[0073] In the embodiment, the frequency of sending the request command is once per minute, and the request command includes a Hello packet and state information of the seismic acquisition node; the Hello packet is sent to ensure that the seismic acquisition node is in a working state; the state information is parameter information of the seismic acquisition node, including node energy, remaining storage capacity, and position coordinates, wherein the state information of the first seismic acquisition node is first state information.

[0074] Step 2: determining whether normal data transmission work can be performed based on the request command;

[0075] The normal data transmission work includes that the first seismic acquisition node communicates with the center server by using the relay communication. The microseismic data is obtained by a seismic data acquisition system, and the microseismic data is observation data related to microseismic, including but not limited to seismographic data, geomagnetic data, geoelectric data, underground fluid data, and land deformation data.

[0076] Specifically, after the first seismic acquisition node sends the request command to the center server, if the first seismic acquisition node receives an ACK packet from the center server within a specified time, it is determined that the center server and the first seismic acquisition node can perform normal data transmission work; if the first seismic acquisition node does not receive the ACK packet from the center server within the specified time, or the center server does not receive the state information from the first seismic acquisition node within the specified time, it is determined that the center server and the first seismic acquisition node cannot perform normal data transmission work.

[0077] The specified time is a time period set by a machine, and in the embodiment, the time period is 20 s.

[0078] Step 3: if yes, based on a first mode, sending the microseismic data to the center server by using the relay communication;

[0079] If no, based on a second mode, sending the microseismic data to the center server by using an optimal data multi-hop path.

[0080] When the microseismic data is sent to the center server by using the relay communication based on the first mode, the following steps are included:

[0081] The three-component geophone in the first seismic acquisition node acquires microseismic data and transmits the microseismic data to an ADS1282 analog-to-digital conversion chip for analog-to-digital conversion, transmits the microseismic data after the mode conversion to a data preprocessing module for compression coding and filtering shaping, and transmits to a control unit, and an STM32F429 processor transmits the microseismic data to a wireless transmission unit based on a data transmission unit, wherein a mode selection module switches the node seismograph to a first mode, selects a 2.4GHz wireless communication module or a 5.8GHz wireless communication module based on a communication environment, and sends the microseismic data to a neighboring AP, and the neighboring AP forwards the microseismic data from the first seismic acquisition node to a central server.

[0082] When the microseismic data is sent to the central server based on the second mode using the optimal data multi-hop path, the method specifically includes the following steps:

[0083] The three-component geophone in the first seismic acquisition node acquires microseismic data and transmits the microseismic data to an ADS1282 analog-to-digital conversion chip for analog-to-digital conversion, transmits the microseismic data after the mode conversion to a data preprocessing module for compression coding and filtering shaping, and transmits to a control unit, and an STM32F429 processor transmits the microseismic data to a wireless transmission unit based on a data transmission unit, wherein a mode selection module switches the node seismograph to a second mode, selects a 2.4GHz wireless communication module or a 5.8GHz wireless communication module based on a communication environment, and sends the microseismic data to a central server through an optimal data multi-hop path.

[0084] Preferably, the optimal data multi-hop path is obtained through a fuzzy comprehensive evaluation model, including:

[0085] The communication path is established through routing selection, and the routing path is obtained based on the communication path; the routing path is evaluated through the fuzzy comprehensive evaluation model to obtain the optimal data multi-hop path;

[0086] Specifically, the first seismic acquisition node selects a second seismic acquisition node as a cluster head for routing selection, and sends the first state information to the second seismic acquisition node in a broadcast manner, and the second seismic acquisition node is a neighboring acquisition node of the first seismic acquisition node;

[0087] After receiving the first state information, the second seismic acquisition node adds state information from the second seismic acquisition node itself to the first state information to obtain second state information, and continues to select other seismic acquisition nodes as cluster heads for routing selection, and sends the second state information to the other seismic acquisition nodes, and the other seismic acquisition nodes repeat the above steps after receiving the second state information until the central server adjacent to the seismic acquisition nodes can establish a communication path with the first seismic acquisition node;

[0088] The first seismic acquisition node establishes a routing table based on the seismic acquisition nodes through which the communication path passes, and sends the routing table to the central server, at which time the central server can send instructions to the first seismic acquisition node based on the routing table and obtain the state information of all seismic acquisition nodes through which the communication path passes, i.e., the communication path node state information; the central server obtains all routing paths based on the communication path node state information, and evaluates each routing path through a fuzzy comprehensive evaluation model to select the routing path with the highest evaluation value as the optimal data multi-hop path.

[0089] In this embodiment, the geographical position of the seismic acquisition node is affected by factors including the terrain, resulting in that some seismic acquisition nodes cannot directly communicate with the central server and other seismic acquisition nodes, and thus cannot serve as cluster heads for routing selection.

[0090] The microseismic data transmission method and device disclosed in the embodiment of the application can solve the problem of real-time processing of microseismic data caused by the fact that microseismic data cannot be returned due to AP interruption. In combination with Figures 3 to 6 , the number of node seismographs that can communicate before and after the interruption of the AP, the central server data packet reception amount, the network average delay, and the data packet transmission rate in the field monitoring area can be obtained.

[0091] Exemplarily, 100 seismic acquisition nodes are arranged in the field monitoring area, and after the communication network is stable, the seismic acquisition nodes are continuously monitored for 60 minutes. After 30 minutes of monitoring the seismic acquisition nodes, the AP is interrupted for 2 to 3 minutes. After the interruption of the AP ends, the method and device provided in the embodiment of the application are used to make the seismic acquisition nodes reestablish a communication path with the central server. The number of APs interrupted is 2, 3, and 4, respectively.

[0092] The number of node seismographs that can communicate before and after the interruption of the AP, the central server data packet reception amount, and the network average delay are monitored before and after the interruption of the AP. The network average delay is the average value of the communication network delay when all seismic acquisition nodes communicate with the central server.

[0093] The data packet transmission rate before the interruption of the AP and the data packet transmission rate after the interruption of the AP are monitored. The data packet transmission rate is monitored after 31 minutes of monitoring the seismic acquisition nodes, and the data packet transmission rate is monitored using and not using the microseismic data transmission method and device disclosed in the embodiment of the application.

[0094] In combination with Figure 3 , the number of node seismographs that can communicate before and after the interruption of the AP can be obtained.

[0095] Specifically, before the AP interruption, the monitoring found that the number of node seismographs capable of communication was 98 due to the existence of environmental obstructions including building and vegetation obstructions; after the AP interruption, when the monitoring time was 31 to 33 minutes, the number of node seismographs capable of communication suddenly decreased, wherein when the number of AP interruptions was 2, the number of node seismographs capable of communication decreased to 55, when the number of AP interruptions was 3, the number of node seismographs capable of communication decreased to 25, and when the number of AP interruptions was 4, the number of node seismographs capable of communication decreased to 2; after the monitoring time was 33 minutes, based on the microseismic data transmission method and device disclosed in the embodiment of the application, the number of node seismographs capable of communication rapidly increased to 93.

[0096] Due to the change of the communication path of the seismic acquisition node, the fact that some communication paths cannot transmit signals due to environmental obstructions, and the fact that individual node seismographs are dead after sudden communication interruption, the number of node seismographs after the AP interruption is slightly lower than the number of node seismographs before the AP interruption; wherein the number of node seismographs after the AP interruption is only less than 5% than the number of node seismographs before the AP interruption, which can meet the real-time transmission of microseismic data in reality.

[0097] In combination with Figure 4 The data packet reception amount of the central server before and after the AP interruption can be known.

[0098] Specifically, before the AP interruption, the data packet reception amount of the central server was about 65 MB per minute; after the AP interruption, when the monitoring time was 31 to 33 minutes, the data packet reception amount of the central server suddenly decreased, wherein when the number of AP interruptions was 2, the data packet reception amount of the central server decreased to 30 MB per minute, when the number of AP interruptions was 3, the data packet reception amount of the central server decreased to 16 MB per minute, and when the number of AP interruptions was 4, the data packet reception amount of the central server decreased to 0 MB per minute due to the fact that no seismic acquisition node communicated with the central server; after the monitoring time was 33 minutes, based on the microseismic data transmission method and device disclosed in the embodiment of the application, the data packet reception amount of the central server rapidly increased to about 62 MB per minute.

[0099] After the AP interruption, the data packet reception amount of the central server is only less than 5% than the data packet reception amount of the central server before the AP interruption, which can meet the real-time transmission of microseismic data in reality.

[0100] In combination with Figure 5 The network average delay before and after the AP interruption can be known.

[0101] Specifically, before the AP is interrupted, the center server receives about 300 ms fluctuating network average delay per minute of data packet; after the AP is interrupted, when the monitoring time is 31 to 33 minutes, the network average delay suddenly increases, wherein, when the number of interrupted APs is 2, the network average delay increases to 380 ms, when the number of interrupted APs is 3, the network average delay increases to 420 ms, and when the number of interrupted APs is 4, the network average delay has exceeded 500 ms, and the microseismic data cannot be transmitted; after the monitoring time is 33 minutes, based on the microseismic data transmission method and device disclosed in the embodiment of the application, the network average delay can be reduced to below 350 ms, wherein, the communication network occasionally has high delay, and the fluctuation of the communication network is larger than that before the AP is interrupted, but can still meet the real-time transmission of microseismic data in reality.

[0102] In combination Figure 6 It can be known that the data packet sending rate before the AP is interrupted and the data packet sending rate after the AP is interrupted using and not using the microseismic data transmission method and device disclosed in the embodiment of the application, wherein, as shown by the broken line 1, the data packet sending rate before the AP is interrupted is 98% or more; as shown by the broken line 2, the data packet sending rate after the AP is interrupted using the microseismic data transmission method and device disclosed in the embodiment of the application is 98% or more; and as shown by the broken line 3, the data packet sending rate not using the microseismic data transmission method and device disclosed in the embodiment of the application is 96% to 98%;

[0103] Wherein, since the seismic acquisition node needs to bear a high data packet sending amount, the packet loss rate of the microseismic data will rise, resulting in a decrease in the transmission success rate of the data packet, so the data packet sending rate using the microseismic data transmission method and device disclosed in the embodiment of the application is higher than the data packet sending rate not using the microseismic data transmission method and device disclosed in the embodiment of the application, and is slightly lower than the data packet sending rate before the AP is interrupted;

[0104] In summary, based on the microseismic data transmission method and device disclosed in the embodiment of the application, the number of nodes capable of communicating can be increased, the data packet receiving amount of the center server can be increased, and the network average delay can be reduced, so that the real-time transmission of the microseismic data can be ensured, and the demand for real-time monitoring of the microseismic event can be met.

[0105] Embodiment 2

[0106] Based on the seismic data transmission method disclosed in embodiment 1, the fuzzy comprehensive evaluation model is further supplemented and described, wherein the fuzzy comprehensive evaluation model is established through a network model and an energy model, and specifically includes the following steps:

[0107] Step 101: obtaining a fuzzy evaluation matrix R based on a network model and an energy model k , including: obtaining a membership degree r ij based on the network model and the energy model ij , obtaining a fuzzy evaluation matrix R k based on the membership degree r i ;

[0108] Specifically, obtaining a second index factor u j based on the network model and the energy model ij , obtaining a membership degree r ij of a jth level of comment P k based on the membership degree r n , obtaining a fuzzy evaluation matrix R n of the second index set based on the membership degree r ki ;

[0109] The network model includes a center server and a plurality of seismic acquisition nodes, the geographical positions of the seismic acquisition nodes are fixed, the sensing ability, the processing ability, the storage ability, the communication ability and the initial total electric quantity of each seismic acquisition node are the same, and the initial electric quantity is an electric quantity before the seismic acquisition node is in a working state;

[0110] Preferably, the energy model includes an index set, a weight set and a comment set;

[0111] The index set includes a first index set and a second index set, the first index set is X, the first index set includes first index factors x1, x2 and x3, and is represented by the following formula:

[0112] X = (x1, x2, x3)

[0113] The second index set is U, is established based on the first index set, and includes second index factors u1, u2,..., u n , and is represented by the following formula:

[0114] U = (u1, u2,..., u n )

[0115] The weight set is U ki , which is used to indicate the corresponding weight of the second index set, wherein k = 1, 2, 3, 4, i = 1, 2,..., n, and is represented by the following formula:

[0116] U ki = (u k1 ,u k2 ,...,u kn )

[0117] The comment set is P j , wherein j = 1, 2, 3, 4, and is represented by the following formula:

[0118] P j= (p1, p2, p3, p4)

[0119] wherein p1, p2, p3, p4 represent four levels of comments of good, better, best and worst respectively.

[0120] Membership degree r ij is expressed by the following formula:

[0121]

[0122] wherein the membership degree r ij is obtained based on the Delphi method, and by sorting the expert rating table, for U ki , P i1 p1-level comments can be obtained, P i2 p2-level comments, P i3 p3-level comments, and P i4 p4-level comments.

[0123] The fuzzy evaluation matrix of the second index set is R k , which is obtained by the membership degree r ij , wherein i = 1, 2,..., s; j = 1, 2, 3, 4, and is expressed by the following formula:

[0124]

[0125] In this embodiment, the first index factor and the second index factor are specifically shown in Table 1:

[0126] Table 1

[0127]

[0128] Specifically, the percentage of the remaining power of the seismic acquisition node is E r .

[0129] Specifically, the remaining power of the seismic acquisition node is E T , and the relationship between E r and E T is expressed by the following formula:

[0130]

[0131] wherein E t is the initial total power of the seismic acquisition node.

[0132] Specifically, the energy consumed by sending the microseismic data is E T,i(J) is the energy consumed by the seismic acquisition node when transmitting the microseismic data packet, wherein the factors affecting the energy consumed by the seismic acquisition node when transmitting the data packet include the transmission distance d of each two adjacent seismic acquisition nodes and the data packet transmission amount E borne by the seismic acquisition node dp，i ;

[0133] The transmission distance d of each two adjacent seismic acquisition nodes is calculated based on the latitude and longitude coordinates of the seismic acquisition node, and is represented by the following formula:

[0134] d = R * arcos [cos (Lati i ) * cos (Lati j ) * cos (Longi i - Longi j ) + sin (Lati i ) * sin (Lati j )]

[0135] Wherein, R is the radius of the earth; the i-th seismic acquisition node and the j-th seismic acquisition node are adjacent acquisition nodes, that is, the seismic acquisition node i and the seismic acquisition node j are adjacent seismic acquisition nodes, wherein the latitude and longitude coordinates of the seismic acquisition node i are (Longi i , Lati i ), and the latitude and longitude coordinates of the seismic acquisition node j are (Longi j , Lati j );

[0136] The data packet transmission amount E dp，i borne by the seismic acquisition node i is obtained based on the energy E s consumed by the seismic acquisition node i when transmitting a single data packet, and is represented by the following formula:

[0137] E dp，i = ρ * i * E s

[0138] Wherein, ρ is a linear constant, and E s is obtained by the following formula:

[0139]

[0140] Wherein, Ps(W) is the power required to transmit a unit data packet per unit distance; T(s) is the time required to transmit a unit data packet; α is a constant, and α ∈ [0.1, 1], wherein the farther the transmission distance of a unit data packet, the smaller the value of α; β is a constant, and β ∈ [1, 10], wherein the larger the value of Ps(W), the smaller the value of β;

[0141] Specifically, the energy consumed by the instrument operation is the energy consumed by the seismic acquisition node itself when running, including the energy E0 consumed by the instrument chip operation, and the energy E needed by the seismic acquisition node when sensing data and generating data s,i (J), wherein the energy needed by the seismic acquisition node when sensing data and generating data is represented by the following formula:

[0142] E s,i (J) = P s,i (W) × 8 × Packetsize i (bit) × T(s)

[0143] Wherein, P s,i (W) is the power needed by the seismic acquisition node i to generate a unit bit of data, Packetsize i is the size of the data packet generated by the seismic acquisition node i, and T(s) represents the time consumed for generating the data packet.

[0144] Step 102: obtaining the membership degree matrix R based on the fuzzy evaluation matrix R k The membership degree matrix R is obtained, including:

[0145] The fuzzy evaluation matrix R k is processed to obtain the membership vector B k , and the membership degree matrix R is obtained based on the membership vector B k ;

[0146] Specifically, the fuzzy evaluation matrix R k is processed to obtain the membership vector B j of the first index set with respect to the comment set P k , and the membership vector B k is represented by the following formula:

[0147] B k = A k × R k = (b k1 , b k2 , b k3 , b k4 )

[0148] The membership degree matrix R is obtained based on the membership vector B k , and the membership degree matrix R is represented by the following formula:

[0149]

[0150] Step 103: establishing a fuzzy comprehensive evaluation model based on the membership degree matrix R, including:

[0151] The membership degree matrix R is subjected to fuzzy transformation to obtain a membership vector B, and the membership vector B is normalized to obtain a membership degree Based on the membership degree A fuzzy comprehensive evaluation model is established, and the fuzzy comprehensive evaluation model is used to obtain an optimal data multi-hop path

[0152] Specifically, the membership degree matrix R is subjected to fuzzy transformation to obtain a first index set X k The membership vector B of the comment set P j is expressed by the following formula:

[0153]

[0154] When , the membership vector B is normalized by the following formula, where j = 1, 2, 3, and 4:

[0155]

[0156] Based on the normalized membership vector B, the membership degree of the first index set with respect to the comment set P j is obtained and expressed by the following formula:

[0157]

[0158] The membership degree is used to indicate the performance mode of the seismic acquisition node existing in the communication path with the second seismic acquisition node as the cluster head, respectively indicating a high-performance mode, a medium-performance mode, a low-performance mode, and an ultra-low-performance mode.

[0159] In this embodiment, the performance mode of the seismic acquisition node is classified in the following manner: when there are n seismic acquisition nodes in the communication path, and n is greater than or equal to 4, the first n / 4 seismic acquisition nodes close to the cluster head in the communication path adopt the high-performance mode, the next n / 4 seismic acquisition nodes close to the cluster head adopt the medium-performance mode, the next n / 4 seismic acquisition nodes close to the cluster head adopt the low-performance mode, and the last n / 4 seismic acquisition nodes adopt the ultra-low-performance mode; when n is less than 4, the second seismic acquisition node as the cluster head adopts the high-performance mode, the seismic acquisition node adjacent to the cluster head adopts the medium-performance mode, the next seismic acquisition node adjacent to the cluster head adopts the low-performance mode, and the seismic acquisition node as the terminal node in the communication path adopts the ultra-low-performance mode.

[0160] The evaluation result T is obtained by the membership degree B, a fuzzy comprehensive evaluation model is established based on the evaluation result T, and the fuzzy comprehensive evaluation model is used to obtain an optimal data multi-hop path, where the evaluation result T is expressed in the following manner:​

[0161]

[0162] wherein, T i is a fuzzy evaluation value, i.e., a value obtained by human evaluation on the communication link; n is the number of seismic acquisition nodes in each communication link;

[0163] When the same second seismic acquisition node is taken as the cluster head, if there are multiple multi-hop routing paths with the same T value, the central server finds the second seismic acquisition node as the cluster head with the same T value, excludes all communication paths with the seismic acquisition node as the cluster head, selects all communication paths with other second seismic acquisition nodes as the cluster head, calculates the T value again, selects another communication path with the highest T value as the multi-hop routing path, until all communication paths with the second seismic node as the cluster head are filtered by the central server, and finally obtains the multi-hop routing path with the highest T value as the optimal data multi-hop path.

[0164] Embodiment 3

[0165] In combination Figure 7 , the embodiment provides a microseismic data transmission device, comprising:

[0166] a command sending module configured to send a request command to a central server;

[0167] a judgment module configured to judge whether normal data transmission work can be performed based on the request command;

[0168] a data sending module configured to, if yes, send microseismic data to the central server in a relay communication mode based on a first mode;

[0169] and if no, send the microseismic data to the central server through an optimal data multi-hop path based on a second mode.

[0170] In the embodiment, a microseismic data transmission device is disclosed, which can realize all contents of the microseismic data transmission method disclosed in Embodiment 1 and Embodiment 2 of the present application.

[0171] Embodiment 4

[0172] The computing device disclosed in the embodiment of the present application comprises:

[0173] one or more processing units;

[0174] a storage unit configured to store one or more programs,

[0175] When the one or more programs are executed by the one or more processing units, the one or more processing units are enabled to perform the entire content of the microseismic data transmission method disclosed in Embodiment 1, Embodiment 2 of the present application.

[0176] Embodiment 5:

[0177] The computer readable storage medium with the non-volatile program code executable by the processor disclosed in the embodiments of the present application,

[0178] When the computer program is executed by the processor, the entire content of the microseismic data transmission method disclosed in Embodiment 1, Embodiment 2 of the present application can be realized.

[0179] Finally, it should be noted that the above-described embodiments are merely specific embodiments of the present application, which are used to illustrate the technical solutions of the present application, but not to limit the same. The protection scope of the present application is not limited to this. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can make modifications or easy changes to the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or can make equivalent replacements to some technical features; and these modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for transmitting microseismic data, characterized in that, include: Step 1: Send a request command to the central server; Step 2: Determine whether normal data transmission can proceed based on the requested command; Step 3: If possible, based on the first mode, send microseismic data to the central server using relay communication; If not, based on the second mode, the microseismic data is sent to the central server through the optimal data multi-hop path; The optimal data multi-hop path is obtained through a fuzzy comprehensive evaluation model, which is established by combining a network model and an energy model. The energy model includes: an index set, a weight set, and a comment set; The network model includes a central server and multiple seismic acquisition nodes; The fuzzy comprehensive evaluation model is established through a network model and an energy model, including: Step 101: Obtain the fuzzy evaluation matrix R based on the network model and the energy model. k ; Step 102: Based on the fuzzy evaluation matrix R k Obtain the membership matrix R; Step 103: Establish a fuzzy comprehensive evaluation model based on the membership matrix R; The establishment of the fuzzy comprehensive evaluation model based on the membership matrix R includes: The membership matrix R is subjected to fuzzy transformation to obtain the membership vector B, and the membership vector B is normalized to obtain the membership degree. Based on the membership degree Establish a fuzzy comprehensive evaluation model; Among them, based on the membership degree Establishing a fuzzy comprehensive evaluation model includes using membership degrees. It is possible to obtain the evaluation result T and establish a fuzzy comprehensive evaluation model based on the evaluation result T.

2. The microseismic data transmission method according to claim 1, characterized in that, The optimal data multi-hop path is obtained through a fuzzy comprehensive evaluation model, including: A communication path is established through routing selection, and a routing path is obtained based on the communication path. The optimal data multi-hop path is obtained by evaluating the routing path using the fuzzy comprehensive evaluation model.

3. The microseismic data transmission method according to claim 1, characterized in that, The indicator set includes a first indicator set and a second indicator set. The first indicator set is X, which includes first indicator factors x1, x2, and x3, and is represented by the following formula: X = (x1, x2, x3) The second set of indicators is U, which includes the second indicator factors u1, u2, ..., u n It can be expressed by the following formula: U=(u1,u2,...,u n ) The weight set is U ki , used to indicate the weights corresponding to the second index set, where k = 1, 2, 3, 4, i = 1, 2, ..., n, and expressed by the following formula: IN ki =(in k1 ,in k2 ,...,in kn ) The set of comments is P. j Where j = 1, 2, 3, 4, it is represented by the following formula: P j =(p1,p2,p3,p4)。 4. The microseismic data transmission method according to claim 1, characterized in that, The fuzzy evaluation matrix R is obtained based on the network model and energy model. k include: Based on the network model and the energy model, the membership degree r is obtained. ij Based on the membership degree r ij Obtain the fuzzy evaluation matrix R k ; The membership degree r ij This can be expressed by the following formula: The fuzzy evaluation matrix is ​​R. k , where i = 1, 2, ..., s; j = 1, 2, 3, 4, is represented by the following formula:

5. The microseismic data transmission method according to claim 1, characterized in that, The fuzzy evaluation matrix R k Obtaining the membership matrix R includes: For the fuzzy evaluation matrix R k Perform fuzzy processing to obtain the membership vector B. k Based on the membership vector B k Obtain the membership matrix R; The membership vector B k This can be expressed by the following formula: B k =A k ×R k =(b k1 ,b k2 ,b k3 ,b k4 ) The membership matrix R is expressed by the following formula:

6. A microseismic data transmission device, characterized in that, include: Command sending module: Sends request commands to the central server; Judgment module: Determines whether normal data transmission can proceed based on the requested command; Data transmission module: If possible, based on the first mode, transmit the microseismic data to the central server using relay communication; If not, based on the second mode, the microseismic data is sent to the central server through the optimal data multi-hop path; The optimal data multi-hop path is obtained through a fuzzy comprehensive evaluation model, which is established by combining a network model and an energy model. The energy model includes: an index set, a weight set, and a comment set; The network model includes a central server and multiple seismic acquisition nodes; The fuzzy comprehensive evaluation model is established through a network model and an energy model, including: Step 101: Obtain the fuzzy evaluation matrix R based on the network model and the energy model. k ; Step 102: Based on the fuzzy evaluation matrix R k Obtain the membership matrix R; Step 103: Establish a fuzzy comprehensive evaluation model based on the membership matrix R; The establishment of the fuzzy comprehensive evaluation model based on the membership matrix R includes: The membership matrix R is subjected to fuzzy transformation to obtain the membership vector B, and the membership vector B is normalized to obtain the membership degree. Based on the membership degree Establish a fuzzy comprehensive evaluation model; Among them, based on the membership degree Establishing a fuzzy comprehensive evaluation model includes using membership degrees. It is possible to obtain the evaluation result T and establish a fuzzy comprehensive evaluation model based on the evaluation result T.

7. A computing device, characterized in that, include: One or more processing units; A storage unit is used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processing units, the one or more processing units perform the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having processor-executable non-volatile program code, characterized in that, When the program code is executed by the processor, it implements the steps of the method as described in any one of claims 1 to 5.

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