WO2018192260A1 - 一种co2地质封存区域的传感网络节点定位优化方法 - Google Patents

一种co2地质封存区域的传感网络节点定位优化方法 Download PDF

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WO2018192260A1
WO2018192260A1 PCT/CN2017/118951 CN2017118951W WO2018192260A1 WO 2018192260 A1 WO2018192260 A1 WO 2018192260A1 CN 2017118951 W CN2017118951 W CN 2017118951W WO 2018192260 A1 WO2018192260 A1 WO 2018192260A1
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geological
storage area
slope
geological storage
map
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PCT/CN2017/118951
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French (fr)
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杨慧
吴萌萌
秦勇
王永波
张小露
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中国矿业大学
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Priority to US16/485,116 priority Critical patent/US10808502B2/en
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V20/00—Geomodelling in general
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B41/00—Equipment or details not covered by groups E21B15/00 - E21B40/00
    • E21B41/005—Waste disposal systems
    • E21B41/0057—Disposal of a fluid by injection into a subterranean formation
    • E21B41/0064—Carbon dioxide sequestration
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V9/00—Prospecting or detecting by methods not provided for in groups G01V1/00 - G01V8/00
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/282—Application of seismic models, synthetic seismograms
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02C—CAPTURE, STORAGE, SEQUESTRATION OR DISPOSAL OF GREENHOUSE GASES [GHG]
    • Y02C20/00—Capture or disposal of greenhouse gases
    • Y02C20/40—Capture or disposal of greenhouse gases of CO2

Definitions

  • the invention relates to a wireless sensor network node positioning method, in particular to a sensor network node positioning optimization method for a CO 2 geological storage area.
  • a more direct and effective method is to store CO 2 from a fixed point source for long-term storage in a relatively closed geological structure or ocean, thereby preventing or significantly reducing the anthropogenic emissions of CO 2 into the atmosphere, but geological storage
  • geological storage After the CO 2 must rely on the pressure of the formation to maintain the supercritical fluid state, once it leaks to the surface through channels such as faults, fissures or oil and gas wells, it will form a gas cloud heavier than air near the surface, for human health, life safety and ecological environment. Serious impacts have made the fight against global warming unpredictable.
  • perfect monitoring technology is needed to provide guarantee. Accurate monitoring equipment can improve the understanding of the sealing process and confirm its effectiveness.
  • the key to verifying the persistence and safety of CO 2 geological storage is Continuous automatic monitoring.
  • the traditional network monitoring coverage control scheme often randomly or evenly distributes discrete sensing nodes in the monitoring area. However, it does not solve the problem of optimally setting the network coverage nodes in the practical application sense, resulting in an increase in detection cost and waste.
  • Patent No. 200810201237.0 discloses an optimization method for wireless sensor network node layout for area monitoring. This method utilizes particle swarm optimization algorithm and Hungarian algorithm to improve coverage of monitoring area from the perspective of target detection function, and efficiently solves wireless problem.
  • the above-mentioned optimization method for wireless sensor network node layout has certain limitations in the complex geographical and geological environment of the detection area, and in the optimization method, the sensor is disposed in the detection area by airdrop to determine the initial position, which is difficult to determine. The scientificity and accuracy of the airdrop position.
  • Patent No. 201310118083.X discloses a wireless sensor network node coverage optimization method, which uses a differential evolution algorithm to perform iterative improvement, and further optimizes the group by using a method of constraining the center of the circle and reducing multiple circle overlaps, using as few as possible.
  • the sensor achieves the highest possible area coverage.
  • the sensor coverage network optimization is more concerned with the different geographical geological features of different monitoring points in the detection area, the node density of the monitoring point sensor network and the possible
  • the wireless sensor network node coverage optimization method is unrealizable in this respect due to different degrees of interference factors.
  • the present invention provides a sensing network node positioning optimization method for a CO 2 geological storage area, which has strong network coverage capability and network connectivity, and can reduce node redundancy. Degree and communication overhead.
  • a sensing network node positioning optimization method for a CO 2 geological storage area includes the following steps:
  • Step 2) according to different sensitivity levels of the CO 2 geological storage area, using different density network coverage control algorithms to deploy the sensing monitoring node;
  • Step 3 Perform a Delaunay split on the set of sensor nodes deployed in the CO 2 geological storage area to complete the description and optimized expression of the overlay network.
  • the specific step of determining the weight is: constructing an evaluation index system for environmentally sensitive impact factors of the CO 2 geological storage area according to the set of influence factors of the CO 2 leakage event in the extracted storage area; It consists of a target layer, a criterion layer and a discriminating layer.
  • the primary evaluation index is monitoring environmental sensitivity A.
  • the primary evaluation indicators include: geological reservoir B 1 , topographical B 2 , meteorological wind field B 3 ;
  • the second-level evaluation indicators include the three-level evaluation indicators: burial depth C 1 , fault activity C 2 , reservoir permeability C 3 , reservoir porosity C 4 , geothermal condition C 5 , slope C 6 , slope direction C 7.
  • Mine location C 8 land use C 9 , surface cover C 10 , soil type C 11 , prevailing wind C 12 , prevailing wind direction C 13 ; based on the impact factor hierarchy of the evaluation index system, use the tomographic analysis method to construct the judgment matrix The calculation and comparison are carried out, and the total ranking weight of the first-level index layer to the first-level index layer is obtained after layer-by-layer iterative calculation.
  • the GIS spatial analysis technology is used to obtain a map of the sensitivity level of the CO 2 geological storage area, which specifically includes the following steps:
  • the influence factors are spatially superimposed by weighted superposition to obtain the potential leakage channel of CO 2 in the CO 2 geological storage area, and the buffer analysis is performed to obtain the influence degree and spatial distribution layer of CO 2 leakage;
  • the slope direction analysis shows the terrain slope map and the terrain slope map.
  • the terrain slope map and the terrain slope map are respectively re-classified by the grid to obtain the slope grade map and the slope direction classification map.
  • the classification criteria are: the slope of the terrain In the figure, less than 15° is defined as a gentle slope, and greater than or equal to 15° is defined as a steep slope; in the topographic slope diagram, the slope is divided into southward, northward, eastward, westward, southeastward, southwestward, northeastward, and Eight directions to the northwest;
  • the land use status, soil resource types and vegetation cover status of CO 2 geological storage areas were extracted, and the relative positions of CO 2 geological storage areas, urban residential areas and other artificial CO 2 emission sources were confirmed on site, and distance analysis was carried out. And the results of the analysis are reclassified according to the four distance levels, and the influence range of the artificial CO 2 emission source is obtained;
  • the impact degree and spatial distribution status layer of the CO 2 leakage, the artificial CO 2 emission source influence range layer, the windward slope, the leeward slope and the downwind slope wind field The spatial distribution layer is weighted and superimposed according to the weights of the evaluation index system by using GIS technology, and the leakage monitoring sensitivity comprehensive index of each evaluation unit is calculated respectively, and the sensitivity distribution map of CO 2 geological storage area is obtained and carried out.
  • the five grades are reclassified to obtain the spatial distribution map of the sensitivity level of the CO 2 geological storage area, which are highly sensitive, highly sensitive, generally sensitive, less sensitive and less sensitive.
  • the step 2) is specifically: assuming that each sensing node performs omnidirectional monitoring, and its coverage is a circular area with a sensing radius of r, and each sensing node has the same transmitting power. That is, the detection radii r of all the sensing nodes are equal; the coverage density is indirectly represented by the distance a between the sensing nodes, and the sensitivity is different according to the CO 2 geological storage area, with the sensing node as the center and the distance a between the sensing nodes as The length of the grid is long, and the sensor nodes in the six directions perform regular triangulation on the CO 2 geological storage area, and satisfy the condition: if the sensitivity level of the CO 2 geological storage area is higher, the distance a between the sensing nodes is smaller. .
  • step 3 includes the following specific steps:
  • the center calculates the spatial position of the set of sensor nodes from six directions, and sequentially determines whether the sensor nodes are in Voronoi, adds the sensor nodes falling in the Voronoi domain to the growth point set, and adds new transmissions. Sensitive nodes are used as new growth points for sensitivity judgment again, until the set of sensor nodes of all growth nodes in the Voronoi domain are outside the Voronoi domain.
  • the method of the present invention analyzes the set of influence factors of the leakage event, and uses the variable density node to arranging and optimize the deployment scheme of the wireless network sensing node in different storage areas. It has strong network coverage and network connectivity, while reducing node redundancy and communication overhead. It can reduce the cost of deployment, improve the quality of monitoring and prolong life time, and improve the real-time, predictability and effectiveness of leak monitoring and early warning.
  • FIG. 1 is a flow chart of a sensor network node positioning optimization method for a CO 2 geological storage area according to the present invention.
  • FIG 3 is a partial map of the present invention for determining the leakage sensitivity of the CO 2 geological storage area.
  • FIG. 4 is a diagram showing the effect of high-density node layout of the variable density sensing node deployment model of the present invention.
  • FIG. 5 is a diagram showing a high density node layout effect of the variable density sensing node deployment model of the present invention.
  • FIG. 6 is a diagram showing a general density node layout effect of the variable density sensing node deployment model of the present invention.
  • FIG. 7 is a diagram showing the effect of lower density node layout in the variable density sensing node deployment model of the present invention.
  • FIG. 8 is a diagram showing the effect of low density node layout in the variable density sensing node deployment model of the present invention.
  • FIG. 9 is a flow chart of a variable density network optimized overlay algorithm of the present invention.
  • FIG. 10 is a schematic diagram of an optimized deployment scenario of a CO 2 storage area monitoring network in a simulated area coal seam according to the present invention.
  • ⁇ in the figure indicates the location of the sensor node layout.
  • the invention adopts 5000m*4000m of coal seam CO 2 injection zone in Qinshui Basin as monitoring simulation area, performs monitoring sensitivity analysis with 100m*100m resolution grid, and uses 14 CH 4 production wells as cluster head nodes for routine monitoring and sensing.
  • the present invention provides a method of targeting optimization sensor network node CO 2 geological storage region a main flowchart, firstly, by analyzing geological, geographical and weather data storage area of the geological CO 2, CO 2 geological storage region is obtained The influence factors of the CO 2 leakage event are collected and weighted, and then the GIS spatial analysis technique is used to obtain the sensitivity map of the CO 2 geological storage area. Secondly, the monitoring and sensing network node coverage control schemes with different densities are designed. Different density network coverage control algorithms are used according to different sensitivity levels of the storage area or the sensing monitoring nodes are densely or sparsely arranged. Finally, the Delauna y is divided into the set of sensing nodes deployed in the CO 2 geological storage area to complete the description and optimized expression of the overlay network.
  • the specific steps for determining the weight are: constructing an evaluation index system for environmentally sensitive impact factors of the CO 2 geological storage area according to the set of influence factors of the CO 2 leakage event in the sealed storage area.
  • the evaluation index system consists of the target layer, the criterion layer and the discriminating layer.
  • the first-level evaluation index is the monitoring environmental sensitivity A.
  • the first-level evaluation indicators include the secondary evaluation indicators: geological reservoir B 1 , topography B 2 , meteorological wind Field B 3 ;
  • the third-level evaluation indicators include: burial depth C 1 , fault activity C 2 , reservoir permeability C 3 , reservoir porosity C 4 , geothermal condition C 5 , slope C 6 , slope To C 7 , mine location C 8 , land use C 9 , surface cover C 10 , soil type C 11 , prevailing wind C 12 , prevailing wind direction C 13 .
  • the influence of each impact factor on the sensitivity of the storage area is not the same.
  • the judgment matrix is constructed by the analytic hierarchy process to calculate and compare. After the layer is iteratively calculated, the final level of the indicator layer is obtained. The total sorting weight of the layer, as shown in Table 2.
  • Table 2 The total ranking weight of the third-level indicator layer (C)
  • the GIS spatial analysis technique is used to obtain the sensitivity map of the CO 2 geological storage area, which includes the following steps:
  • the influence factors are spatially superimposed by weighted superposition to obtain the potential leakage channel of CO 2 in the CO 2 geological storage area, and the buffer analysis is carried out to obtain the influence degree and spatial distribution layer of CO 2 leakage.
  • the digital elevation model data based on CO 2 geological storage area has been acquired, the location and extent of CO 2 to confirm the geological storage region, and collecting natural geographical features CO 2 geological storage area.
  • the obtained digital elevation model data is used to analyze the slope and the slope direction, and the terrain slope map and the terrain slope map are obtained.
  • the terrain slope map and the terrain slope map are respectively reclassified by the grid to obtain the slope grade map and the slope direction classification.
  • the classification criteria are: in the terrain slope map, less than 15° is defined as a gentle slope, and greater than or equal to 15° is defined as a steep slope; in the terrain slope diagram, the slope is divided into south, north, east, and west. Eight directions to the southeast, southwest, northeast, and northwest.
  • the land use status, soil resource types and vegetation cover status of CO 2 geological storage areas were extracted, and the relative positions of CO 2 geological storage areas, urban residential areas and other artificial CO 2 emission sources were confirmed on site, and distance analysis was carried out. And the analysis results are raster reclassified according to the four distance levels, and the influence range of the artificial CO 2 emission source is obtained.
  • the sensitivity of the storage area different network coverage control algorithms are designed or densely or sparsely arranged.
  • the higher the sensitivity level of the CO 2 geological storage area the smaller the distance a between the sensing nodes.
  • each sensor node performs omnidirectional monitoring, and its coverage is used as a circular area with a sensing radius of r, and each sensing node has the same transmitting power, that is, the sensing radius r of all sensing nodes Equal; the coverage density is indirectly expressed by the distance a between the sensing nodes.
  • the sensing node is centered, and the distance a between the sensing nodes is used as the length of the grid, and the sensing is added in six directions.
  • the CO 2 concentration of the uncovered area can be obtained by spatial interpolation.
  • the initial Delaunay triangulation is constructed by using the CO 2 injection well as the cluster head node to solve the initial Voronoi domain of the cluster head node; the cluster head node is used as the initial growth point, and the area according to the initial growth point is monitored.
  • the sensitivity level selects different sensor node distances a as the grid layout, and the equilateral triangle is used as the grid division unit.
  • the spatial position of the set of sensor nodes is calculated from the six directions from the initial growth point.

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Abstract

本发明公开了一种CO2地质封存区域的传感网络节点定位优化方法，通过分析监测区域的地质、地理和气象等数据，解析CO2泄漏事件的影响因子并确定敏感度分区，设计不同的监测传感网络节点的覆盖控制方案，或密集或稀疏地布设传感监测节点，基于Delaunay三角网对覆盖网络进行描述和优化表达。二氧化碳地质封存区域的传感网络节点定位方法，可根据检测区域地质地理特征动态调整无线传感网络节点的布设密度，真正实现煤层二氧化碳注入区泄露动态监测传感网络优化部署。该方法尽可能的减少节点冗余度和通信开销，且具有较强的网络覆盖能力和网络连通性。

Description

一种CO 2地质封存区域的传感网络节点定位优化方法 技术领域
本发明涉及无线传感网络节点定位方法，尤其涉及一种CO 2地质封存区域的传感网络节点定位优化方法。
背景技术
全球变暖问题已经引起国际的密切关注，二氧化碳作为最重要的温室气体亦是全球变暖的主要原因。目前，中国现已成为第二大CO 2排放国，并且将长期依赖矿物燃料特别是煤、石油和天然气等作为主要能源，是CO 2潜在的第一大排放国。虽然，大气中的CO 2可以通过陆地生态系统中的植被、微生物和土壤，以及海洋生态系统中的浮游生物吸收，但生物和其它固碳方式所产生的效果十分有限，因此还需要通过地质固碳等其它途径缓减CO 2气体排放的增长速度。一种较为直接、有效的方法是将固定点源产生的CO 2，捕集后长期储存于相对封闭的地质构造或海洋中，从而阻止或显著减少CO 2向大气中的人为排放，但是地质封存后的CO 2必须依靠地层的压力维持超临界流体态，一旦通过断层、裂隙或油气井等通道泄漏到地表，会在近地表形成比空气重的气云，对人类健康、生命安全及生态环境产生严重影响，使得对抗全球变暖的努力付之东流。为了确保CO 2能够长期安全封存在地下，就需要完善的监测技术提供保障，精准的监测设备能够提高对封存过程的认识并证实其有效性，验证CO 2地质封存持久性和安全性的关键是连续自动监测。传统的网络监测覆盖控制方案往往是在监测区域中或随机、或均匀地布设离散的传感节点，然而并没有从实际应用意义上解决网络覆盖的节点优化布设问题，造成了检测成本的增加和浪费。
与本发明最为相近的已有技术有：
专利号为200810201237.0公开了一种面向区域监测的无线传感器网络节点布设的优化方法，该方法利用粒子群优化算法和匈牙利算法从目标检测功能的角度来提高监测区域的覆盖率，高效地解决了无线传感器网络节点布设优化所面临的高维优化问题。然而上述无线传感器网络节点布设的优化方法面对检测区域复杂的地理、地质环境具有一定的局限性，且在该优化方法中，通过空投方式将传感器布撒在检测区域来确定初始位置，难以确定空投位置的科学性及准确性。
专利号为201310118083.X公开了一种无线传感器网络节点覆盖优化方法，该方法采用微分进化算法进行迭代改进，同时采用约束圆心范围、减少多个圆重叠的方法对群体进一步优化，使用尽量少的传感器完成尽可能高的区域覆盖率。但是针对二氧化碳地质封存监测传感器覆盖网而言，由于封存区域地质地理环境多元化，传感器覆盖网优化更多考虑的是检测区域内不同监测点的不同地理地质特征、监测点传感器网络节点密度以及可能出现的不同程度的干扰因素，该无线传感器网络节点覆盖优化方法在本方面具有不可实现性。
发明内容
发明目的：为了克服现有技术中存在的不足，本发明提供一种CO 2地质封存区域的 传感网络节点定位优化方法，具有较强的网络覆盖能力和网络连通性，同时可以减少节点冗余度和通信开销。
技术方案：为实现上述目的，本发明采用的技术方案为：
一种CO 2地质封存区域的传感网络节点定位优化方法，包括如下步骤：
步骤1)，通过分析CO 2地质封存区域的地质、地理和气象数据，获得CO 2地质封存区域的CO 2泄漏事件的影响因子集合并确定权重，然后运用GIS空间分析技术得出CO 2地质封存区域敏感程度分布图；
步骤2)，根据CO 2地质封存区域的不同敏感等级，采用不同密度的网络覆盖控制算法布设传感监测节点；
步骤3)，对CO 2地质封存区域中部署的传感节点集合进行Delaunay剖分，完成对覆盖网络的描述和优化表达。
进一步的，所述步骤1)中，确定权重的具体步骤为：根据提取的封存区域CO 2泄露事件的影响因子集合，构建CO 2地质封存区域环境敏感影响因子评价指标体系；所述评价指标体系由目标层、准则层和判别层组成，其中一级评估指标为监测环境敏感度A；一级评估指标包括的二级评估指标有：地质储层B 1、地形地貌B 2、气象风场B 3；二级评估指标包括的三级评估指标有：埋藏深度C 1、断裂活动C 2、储层渗透度C 3、储层孔隙度C 4、地热条件C 5、坡度C 6、坡向C 7、矿井位置C 8、土地利用C 9、地表覆盖C 10、土壤类型C 11、盛行风力C 12、盛行风向C 13；依据评价指标体系的影响因子层次结构，采用层析分析法构建判断矩阵进行计算比较，经层层迭代计算后得到最后一级指标层对一级指标层的总排序权重。
进一步的，所述步骤1)中，运用GIS空间分析技术得出CO 2地质封存区域敏感程度分布图，具体包括如下步骤：
a，分析地质调查和矿井专题地图数据，得到CO 2地质封存区域煤储层及其围岩的孔隙度、渗透度、地热条件、埋藏深度和断裂活动影响因子的值，利用GIS技术将各单项影响因子通过加权叠加进行空间叠加，获得CO 2地质封存区域的CO 2潜在泄漏通道，并对其进行缓冲区分析得出CO 2泄漏的影响程度和空间分布状况图层；
b，基于CO 2地质封存区域已获取的数字高程模型数据，确认CO 2地质封存区域的地理位置及范围，并采集CO 2地质封存区域的自然地理特征；运用获取的数字高程模型数据进行坡度和坡向分析，得出地形坡度图以及地形坡向图；并对地形坡度图和地形坡向图分别进行栅格重分类，得到坡度分级图和坡向分类图；其中分类标准为：在地形坡度图中将小于15°定义为缓坡，大于等于15°定义为陡坡；在地形坡向图中将坡向分为向南、向北、向东、向西、向东南、向西南、向东北和向西北8个方向；
基于遥感数据提取CO 2地质封存区域的土地利用现状、土壤资源类型和植被覆盖现状，并现场确认CO 2地质封存区域、城镇居民点以及其他人为CO 2排放源的相对位置，对其进行距离分析，并将分析结果按照四个距离层次进行栅格重分类，得出人为CO 2排放源影响范围图层；
c，提取CO 2地质封存区域内的最小、平均和最大风速，对CO 2地质封存区域内主导风向进行编码，结合地形坡度图以及地形坡向图生成迎风坡、背风坡和顺风坡的风场空间分布图层；然后以矿井位置为原点，以主导风向为轴线，在矿井下风向画扇形区域作为泄露扩散蓄积区分布，所述扇形区域应包括整个CO 2地质封存区域；
d，运用ArcGIS地理信息处理软件，将所述CO 2泄漏的影响程度和空间分布状况图层、所述人为CO 2排放源影响范围图层、所述迎风坡、背风坡和顺风坡的风场空间分布图层运用GIS技术按照所述评价指标体系所得权重进行加权叠加，分别计算出每个评价单元的泄露监测敏感度综合指数，得出CO 2地质封存区域敏感程度分布图，并对其进行五个等级重分类，得出CO 2地质封存区域敏感等级空间分布图，分别为高敏感、较高敏感、一般敏感、较低敏感和低敏感。
进一步的，所述步骤2)具体为：假设每个传感节点均实行全方位监测，将其覆盖范围作为感知半径为r的圆形区域，且发各传感节点都具有相同的发射功率，即所有的传感节点的检测半径r均相等；以传感节点间距离a间接表示覆盖密度，根据CO 2地质封存区域敏感等级不同，以传感节点为中心，以传感节点间距离a作为格网边长，六个方向新增传感节点对CO 2地质封存区域进行规则三角网剖分，并满足条件：若CO 2地质封存区域敏感等级越高，则传感节点间距离a越小。
进一步的，所述步骤3)包括如下具体步骤：
a，以CO 2注入井作为簇头节点构建初始Delaunay三角网剖分，求解簇头节点的初始Voronoi域；
b，将簇头节点作为初始生长点，根据初始生长点所处区域的监测敏感度级别选择不同的传感节点距离a作为格网布设，以正三角形作为格网划分单元，以初始生长点为中心从六个方向计算拟增传感节点点集的空间位置，依次判断拟增传感节点是否在Voronoi中，将落在Voronoi域中的传感节点添加进生长点集中，并将新增传感节点作为新的生长点再次进行敏感度判断，直至Voronoi域所有生长节点的拟增传感节点点集都在Voronoi域外。
c，结合簇头节点和感知节点，求解Delaunay监测网络优化覆盖控制方案。有益效果：本发明方法根据CO 2地质封存区域的地质、地理和气象等数据，分析出泄漏事件的影响因子集合，采用可变密度节点布设优化不同封存区域内的无线网络传感节点部署方案，具有较强的网络覆盖能力和网络连通性，同时可以减少节点冗余度和通信开销。能够降低布设成本、提高监测质量和延长生命时间，提高泄漏监测预警的实时性、预见性和有效性。
附图说明
图1是本发明一种CO 2地质封存区域的传感网络节点定位优化方法的流程图。
图2是本发明确定CO 2地质封存区域泄露敏感度分区技术路线图。
图3是本发明确定CO 2地质封存区域泄露敏感度分区图。
图4是本发明可变密度传感节点部署模型高密度节点布设效果图。
图5是本发明可变密度传感节点部署模型较高密度节点布设效果图。
图6是本发明可变密度传感节点部署模型一般密度节点布设效果图。
图7是本发明可变密度传感节点部署模型较低密度节点布设效果图。
图8是本发明可变密度传感节点部署模型低密度节点布设效果图。
图9是本发明可变密度的网络优化覆盖算法流程图。
图10是本发明仿真区域煤层CO 2封存区域监测网络优化部署场景效果图。
注：图中●表示传感节点布设位置。
具体实施方式
下面结合附图对本发明作更进一步的说明。
本发明以沁水盆地煤层CO 2注入区5000m*4000m作为监测仿真区域，以100m*100m分辨率栅格进行监测敏感度分析，以14个CH 4开采井作为簇头节点进行常规监测，传感节点的感知半径r＝100m，按照监测敏感程度优化部署算法布设监测场景。
如图1所示，本发明一种CO 2地质封存区域的传感网络节点定位优化方法主要流程图，首先，通过分析CO 2地质封存区域的地质、地理和气象数据，获得CO 2地质封存区域的CO 2泄漏事件的影响因子集合并确定权重，然后运用GIS空间分析技术得出CO 2地质封存区域敏感程度分布图。其次，设计不同密度的监测传感网络节点覆盖控制方案，根据封存区域的不同敏感等级采用不同密度的网络覆盖控制算法或密集或稀疏地布设传感监测节点。最后，对CO 2地质封存区域中部署的传感节点集合进行Delauna y剖分，完成对覆盖网络的描述和优化表达。
如表1所示，确定权重的具体步骤为：根据提取的封存区域CO 2泄露事件的影响因子集合，构建CO 2地质封存区域环境敏感影响因子评价指标体系。评价指标体系由目标层、准则层和判别层组成，一级评估指标为监测环境敏感度A；一级评估指标包括的二级评估指标有：地质储层B 1、地形地貌B 2、气象风场B 3；二级评估指标包括的三级评估指标有：埋藏深度C 1、断裂活动C 2、储层渗透度C 3、储层孔隙度C 4、地热条件C 5、坡度C 6、坡向C 7、矿井位置C 8、土地利用C 9、地表覆盖C 10、土壤类型C 11、盛行风力C 12、盛行风向C 13。
表1 CO 2地质封存区域泄露监测敏感度影响因子体系表
Figure PCTCN2017118951-appb-000001
各影响因子对封存区域敏感程度的影响并不相同，依据评价指标体系影响因子层次结构，采用层次分析法构建判断矩阵进行计算比较，经层层迭代计算后得到最后一级指标层对一级指标层的总排序权重，如表2所示。
表2三级指标层(C)的总排序权重
Figure PCTCN2017118951-appb-000002
如图2所示，运用GIS空间分析技术得出CO 2地质封存区域敏感程度分布图，具体包括如下步骤：
a，分析地质调查和矿井专题地图数据，得到CO 2地质封存区域煤储层及其围岩的孔隙度、渗透度、地热条件、埋藏深度和断裂活动影响因子的值，利用GIS技术将各单项影响因子通过加权叠加进行空间叠加，获得CO 2地质封存区域的CO 2潜在泄漏通道，并对其进行缓冲区分析得出CO 2泄漏的影响程度和空间分布状况图层。
b，基于CO 2地质封存区域已获取的数字高程模型数据，确认CO 2地质封存区域的地理位置及范围，并采集CO 2地质封存区域的自然地理特征。运用获取的数字高程模型数据进行坡度和坡向分析，得出地形坡度图以及地形坡向图；并对地形坡度图和地形坡向图分别进行栅格重分类，得到坡度分级图和坡向分类图；其中分类标准为：在地形坡度图中将小于15°定义为缓坡，大于等于15°定义为陡坡；在地形坡向图中将坡向分为向南、向北、向东、向西、向东南、向西南、向东北和向西北8个方向。
基于遥感数据提取CO 2地质封存区域的土地利用现状、土壤资源类型和植被覆盖现状，并现场确认CO 2地质封存区域、城镇居民点以及其他人为CO 2排放源的相对位置，对其进行距离分析，并将分析结果按照四个距离层次进行栅格重分类，得出人为CO 2排放源影响范围图层。
c，提取CO 2地质封存区域内的最小、平均和最大风速，对CO 2地质封存区域内主导风向进行编码，结合地形坡度图以及地形坡向图生成迎风坡、背风坡和顺风坡的风场空间分布图层。然后以矿井位置为原点，以主导风向为轴线，在矿井下风向画扇形区域作为泄露扩散蓄积区分布，所述扇形区域应包括整个CO 2地质封存区域。
d，运用ArcGIS1O.2地理信息处理软件，将CO 2泄漏的影响程度和空间分布状况图层、人为CO 2排放源影响范围图层、迎风坡、背风坡和顺风坡的风场空间分布图层运用GIS技术按照所述评价指标体系所得权重进行加权叠加，分别计算出每个评价单元的泄露监测敏感度综合指数，监测区域中一个栅格为一个评价单元，得出CO 2封存区域敏感程度分布图，并对其进行五个等级重分类，得出CO 2封存区域敏感等级空间分布图，分别为高敏感、较高敏感、一般敏感、较低敏感和低敏感，定性地给出煤层CO 2注入区泄露监测敏感度定量分区方案，如图3所示。
根据封存区域敏感程度不同，设计不同的网络覆盖控制算法或密集、或稀疏地布设传感节点，CO 2地质封存区域敏感等级越高，传感节点间距离a越小。假设每个传感节点均实行全方位监测，将其覆盖范围作为感知半径为r的圆形区域，且设各传感节点都具有相同的发射功率，即所有的传感节点的检测半径r均相等；以传感节点间距离a间接表示覆盖密度，根据CO 2封存区域敏感程度不同，以传感节点为中心，以传感节点间距离a作为格网边长，六个方向新增传感节点对CO 2封存区域进行规则三角网剖分，并满足条件：CO 2封存区域敏感等级越高，传感节点间距离a越小。即对于高敏感区域采用高密度节点布设(a＝r)，如 图4所示；对于较高敏感区域采用较高密度节点布设
Figure PCTCN2017118951-appb-000003
如图5所示；对于中敏感区域其采用一般密度节点布设
Figure PCTCN2017118951-appb-000004
如图6所示；对于较低敏感区域和低敏感区域，分别采用较低密度节点布设(a＝2r)和低密度节点布设(a＝4r)，如图7、8所示，如需了解未覆盖区域的CO 2浓度，可通过空间插值法得出。
如图9所示，以CO 2注入井作为簇头节点构建初始Delaunay三角网剖分，求解簇头节点的初始Voronoi域；将簇头节点作为初始生长点，根据初始生长点所处区域的监测敏感度级别选择不同的传感节点距离a作为格网布设，以正三角形作为格网划分单元，以初始生长点为中心从六个方向计算拟增传感节点点集的空间位置，依次判断拟增传感节点是否在Voronoi中，将落在Voronoi域中的传感节点添加进生长点集中，并将新增传感节点作为新的生长点再次进行敏感度判断，直至Voronoi域所有生长节点的拟增传感节点点集都在Voronoi域外。结合簇头节点和感知节点，求解Delaunay监测网络优化覆盖控制方案，结果如图10所示。
以上所述仅是本发明的优选实施方式，应当指出：对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (5)

  1. 一种CO 2地质封存区域的传感网络节点定位优化方法，其特征在于，包括如下步骤：
    步骤1)，通过分析CO 2地质封存区域的地质、地理和气象数据，获得CO 2地质封存区域的CO 2泄漏事件的影响因子集合并确定权重，然后运用GIS空间分析技术得出CO 2地质封存区域敏感程度分布图；
    步骤2)，根据CO 2地质封存区域的不同敏感等级，采用不同密度的网络覆盖控制算法布设传感监测节点；
    步骤3)，对CO 2地质封存区域中部署的传感节点集合进行Delaunay剖分，完成对覆盖网络的描述和优化表达。
  2. 根据权利要求1所述的一种CO 2地质封存区域的传感网络节点定位优化方法，其特征在于，所述步骤1)中，确定权重的具体步骤为：根据提取的封存区域CO 2泄露事件的影响因子集合，构建CO 2地质封存区域环境敏感影响因子评价指标体系；所述评价指标体系由目标层、准则层和判别层组成，其中一级评估指标为监测环境敏感度A；一级评估指标包括的二级评估指标有：地质储层B 1、地形地貌B 2、气象风场B 3；二级评估指标包括的三级评估指标有：埋藏深度C 1、断裂活动C 2、储层渗透度C 3、储层孔隙度C 4、地热条件C 5、坡度C 6、坡向C 7、矿井位置C 8、土地利用C 9、地表覆盖C 10、土壤类型C 11、盛行风力C 12、盛行风向C 13；依据评价指标体系的影响因子层次结构，采用层析分析法构建判断矩阵进行计算比较，经层层迭代计算后得到最后一级指标层对一级指标层的总排序权重。
  3. 根据权利要求2所述的一种CO 2地质封存区域的传感网络节点定位优化方法，其特征在于，所述步骤1)中，运用GIS空间分析技术得出CO 2地质封存区域敏感程度分布图，具体包括如下步骤：
    a，分析地质调查和矿井专题地图数据，得到CO 2地质封存区域煤储层及其围岩的孔隙度、渗透度、地热条件、埋藏深度和断裂活动影响因子的值，利用GIS技术将各单项影响因子通过加权叠加进行空间叠加，获得CO 2地质封存区域的CO 2潜在泄漏通道，并对其进行缓冲区分析得出CO 2泄漏的影响程度和空间分布状况图层；
    b，基于CO 2地质封存区域已获取的数字高程模型数据，确认CO 2地质封存区域的地理位置及范围，并采集CO 2地质封存区域的自然地理特征；运用获取的数字高程模型数据进行坡度和坡向分析，得出地形坡度图以及地形坡向图；并对地形坡度图和地形坡向图分别进行栅格重分类，得到坡度分级图和坡向分类图；其中分类标准为：在地形坡度图中将小于15°定义为缓坡，大于等于15°定义为陡坡；在地形坡向图中将坡向分为向南、向北、向东、向西、向东南、向西南、向东北和向西北8个方向；
    基于遥感数据提取CO 2地质封存区域的土地利用现状、土壤资源类型和植被覆盖现状，并现场确认CO 2地质封存区域、城镇居民点以及其他人为CO 2排放源的相对位置，对其进行距离分析，并将分析结果按照四个距离层次进行栅格重分类，得出人为CO 2排放源影响范围图层；
    c，提取CO 2地质封存区域内的最小、平均和最大风速，对CO 2地质封存区域内主导风向进行编码，结合地形坡度图以及地形坡向图生成迎风坡、背风坡和顺风坡的风场空间分布图层；然后以矿井位置为原点，以主导风向为轴线，在矿井下风向画扇形区域作为泄露扩散蓄积区分布，所述扇形区域应包括整个CO 2地质封存区域；
    d，运用ArcGIS地理信息处理软件，将所述CO 2泄漏的影响程度和空间分布状况图层、所 述人为CO 2排放源影响范围图层、所述迎风坡、背风坡和顺风坡的风场空间分布图层运用GIS技术按照所述评价指标体系所得权重进行加权叠加，分别计算出每个评价单元的泄露监测敏感度综合指数，得出CO 2地质封存区域敏感程度分布图，并对其进行五个等级重分类，得出CO 2地质封存区域敏感等级空间分布图，分别为高敏感、较高敏感、一般敏感、较低敏感和低敏感。
  4. 根据权利要求1所述的一种CO 2地质封存区域的传感网络节点定位优化方法，其特征在于，所述步骤2)具体为：假设每个传感节点均实行全方位监测，将其覆盖范围作为感知半径为r的圆形区域，且设各传感节点都具有相同的发射功率，即所有的传感节点的检测半径r均相等；以传感节点间距离a间接表示覆盖密度，根据CO 2地质封存区域敏感等级不同，以传感节点为中心，以传感节点间距离a作为格网边长，六个方向新增传感节点对CO 2地质封存区域进行规则三角网剖分，并满足条件：若CO 2地质封存区域敏感等级越高，则传感节点间距离a越小。
  5. 根据权利要求4所述的一种CO 2地质封存区域的传感网络节点定位优化方法，其特征在于，所述步骤3)包括如下具体步骤：
    a，以CO 2注入井作为簇头节点构建初始Delaunay三角网剖分，求解簇头节点的初始Voronoi域；
    b，将簇头节点作为初始生长点，根据初始生长点所处区域的监测敏感度级别选择不同的传感节点距离a作为格网布设，以正三角形作为格网划分单元，以初始生长点为中心从六个方向计算拟增传感节点点集的空间位置，依次判断拟增传感节点是否在Voronoi中，将落在Voronoi域中的传感节点添加进生长点集中，并将新增传感节点作为新的生长点再次进行敏感度判断，直至Voronoi域所有生长节点的拟增传感节点点集都在Voronoi域外。
    c，结合簇头节点和感知节点，求解Delaunay监测网络优化覆盖控制方案。
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