{"id":62012,"date":"2023-11-23T06:00:06","date_gmt":"2023-11-22T22:00:06","guid":{"rendered":"http:\/\/learncmg.cn\/?p=62012"},"modified":"2023-11-23T06:00:06","modified_gmt":"2023-11-22T22:00:06","slug":"334-%e4%ba%8c%e6%b0%a7%e5%8c%96%e7%a2%b3%e6%9d%82%e8%b4%a8%e5%af%b9%e5%b0%81%e5%ad%98%e6%95%88%e6%9e%9c%e5%92%8c%e4%bf%9d%e8%af%81%e7%9a%84%e5%bd%b1%e5%93%8d","status":"publish","type":"post","link":"http:\/\/learncmg.cn\/?p=62012","title":{"rendered":"334. \u4e8c\u6c27\u5316\u78b3\u6742\u8d28\u5bf9\u5c01\u5b58\u6548\u679c\u548c\u4fdd\u969c\u7684\u5f71\u54cd"},"content":{"rendered":"

Impact of CO2 Impurities on Storage Performance and Assurance<\/strong><\/a><\/span><\/h3>\n

\u8be5\u7814\u7a76\u65e8\u5728\u63a2\u7a76N2\u3001O2\u548cAr\u7b49\u6742\u8d28\uff08\u53ef\u80fd\u8fd8\u6709CH4\u7b49\u5e38\u89c1\u6742\u8d28\uff0c\u901a\u5e38\u4ee5\u9971\u548c\u6c34\u5e73\u5b58\u5728\u4e8e\u5730\u4e0b\uff09\u5bf9CO2\u7fbd\u6d41\u52a8\u529b\u5b66\u3001\u6ce8\u5165\u80fd\u529b\u548c\u5bb9\u91cf\u7684\u5f71\u54cd\u3002\u7814\u7a76\u8003\u8651\u4e86N2\u4f53\u79ef15\uff05\u3001O2\u4f53\u79ef5\uff05\u548cAr\u4f53\u79ef5\uff05\u7684\u60c5\u51b5\u3002\u4f46\u672a\u8003\u8651CO\u3001H2\u548cSOx\u7b49\u5176\u4ed6\u6c14\u4f53\uff0c\u8fd9\u4e9b\u6c14\u4f53\u7684\u6469\u5c14\u5206\u6570\u53ef\u80fd\u5e76\u4e0d\u53ef\u5ffd\u7565\u3002\u4e3a\u4e86\u4f7f\u7528\u7cbe\u786e\u7684PVT\u6570\u636e\uff08Peng-Robinson EOS\uff09\uff0c\u5728\u7814\u7a76\u521d\u671f\u8fdb\u884c\u4e86\u5b9e\u9a8c\u5ba4\u5b9e\u9a8c\uff0c\u4ee5\u83b7\u5f97\u6df7\u5408\u7269\u7684\u7c98\u5ea6\u548c\u5bc6\u5ea6\u3002CMG-GEM\u4f9d\u8d56\u4e8e\u591a\u79cd\u7ecf\u9a8c\u6df7\u5408\u89c4\u5219\u8fdb\u884c\u5bc6\u5ea6\u548c\u7c98\u5ea6\u8ba1\u7b97\uff0c\u8fd9\u4e9b\u89c4\u5219\u9700\u8981\u8fdb\u884c\u6821\u51c6\u548c\u8c03\u6574\u3002\u540c\u65f6\uff0c\u901a\u8fc7\u5bf9\u6587\u732e\u8fdb\u884c\u5e7f\u6cdb\u8c03\u67e5\uff0c\u6536\u96c6\u4e86\u5173\u4e8e\u8fd9\u4e9b\u4e0d\u540c\u6df7\u5408\u7269\u6210\u5206\u5728\u4e0d\u540c\u5730\u4e0b\u538b\u529b\u3001\u6e29\u5ea6\u548c\u76d0\u5ea6\u6761\u4ef6\u4e0b\u7684\u6eb6\u89e3\u6027\u4fe1\u606f\u3002\u6c14\u4f53\u6210\u5206\u5728\u6c34\u76f8\u4e2d\u7684\u5206\u914d\u5dee\u5f02\u4f1a\u5bf9\u6c14\u76f8\u7ec4\u6210\u4ea7\u751f\u5f71\u54cd\u3002\u672c\u7814\u7a76\u63d0\u51fa\u7684\u5de5\u4f5c\u662f\u66f4\u5927\u7814\u7a76\u7684\u4e00\u90e8\u5206\uff0c\u8be5\u7814\u7a76\u8fd8\u5305\u62ec\u6742\u8d28\u7684\u5730\u7403\u5316\u5b66\u5f71\u54cd\uff08\u6c14\u4f53\u6210\u5206\u4e0e\u5176\u4ed6\u6210\u5206\u548c\u77ff\u7269\u7684\u53cd\u5e94\u6d3b\u6027\uff09\uff0c\u4f46\u8fd9\u65b9\u9762\u5728\u6b64\u5904\u672a\u8fdb\u884c\u5904\u7406\u3002\u603b\u4f53\u800c\u8a00\uff0c\u5730\u7403\u5316\u5b66\u8fc7\u7a0b\u53ef\u80fd\u4f1a\u5f71\u54cd\u8fd1\u573a\u6027\u8d28\uff0c\u5982\u6ce8\u5165\u80fd\u529b\u548c\u4e95\u5b8c\u6574\u6027\uff0c\u800c\u5bf9\u8f83\u5927\u5c3a\u5ea6\u533a\u57df\u7684\u5f71\u54cd\u53ef\u4ee5\u901a\u8fc7\u5bf9\u7fbd\u6d41\u52a8\u529b\u5b66\u7684\u7406\u89e3\u6765\u7814\u7a76\u3002\u4e00\u4e2a\u91cd\u8981\u7684\u89c2\u5bdf\u662f\uff0c\u4e0e\u76f8\u540c\u6e29\u5ea6\u548c\u538b\u529b\u4e0b\u7684\u7eafCO2\u76f8\u6bd4\uff0c\u6df7\u5408\u7269\u7684\u7c98\u5ea6\u548c\u5bc6\u5ea6\u8f83\u4f4e\u3002\u540c\u6837\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u968f\u7740\u6df1\u5ea6\u7684\u589e\u52a0\uff0c\u6df7\u5408\u7269\u4e0e\u7eafCO2\u4e4b\u95f4\u7684\u7c98\u5ea6\u548c\u5bc6\u5ea6\u5bf9\u6bd4\u9010\u6e10\u51cf\u5c0f\u3002<\/span><\/p>\n

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Executive Summary.<\/span><\/h5>\n

The goal of this study was to understand the impact of impurities (mostly N2, O2, and Ar, to which might be added CH4, commonly present to saturation levels in the subsurface) on CO2 plume dynamics, injectivity, and capacity. The study considered up to 15% volume for N2, 5% volume for O2, and 5% volume for Ar. Other gases such as CO, H2, and SOx, which could have non-negligible mole fractions, are not considered in the study. The problem is approached through an extended desktop study using the numerical modeling tool (multiphase flow code CMG-GEM). In order to work with accurate PVT data (Peng-Robinson EOS), laboratory experiments were performed early in the study to access viscosity and density of the mixtures. CMG-GEM relies on many empirical mixing rules for density and viscosity calculations that need to be calibrated and tuned. In parallel, a comprehensive literature survey was undertaken to collect information on solubility of those various mixture components into the aqueous phase under various subsurface pressure, temperature, and salinity conditions. The differential partitioning of gas components in the aqueous phase impacts the gas phase composition. The work presented in this document is part of a larger study that includes geochemical impact of impurities (reactivity of gas components with other components and with minerals), an aspect not treated here. Overall, geochemical processes could affect near-field properties such as injectivity and well integrity whereas larger-scale regional impacts can be studied through an understanding of plume dynamics. An important observation controlling all the results of the study is that viscosity and density of mixtures are lower than that of neat CO2 at identical temperature and pressure. Equally important to note, viscosity and density contrast between mixtures and neat CO2 decreases with depth.<\/span>
\nThe numerical models used grow in complexity from simple box-like generic models, to which heterogeneity is added in a second step, to more realistic models constructed from two actual U.S. Gulf Coast Region locations (clastic sediments) and from a Canadian (Alberta) carbonate formation but representative of many sites around the world. The objective was to reproduce end-members of aquifer architecture such as (1) clean homogeneous, medium permeability sand; (2) homogeneous sand\/clay, and (3) heterogeneous sand with discontinuous shale partings and continuous baffles. Progressively more complex systems, binary, ternary, and beyond, were investigated. The results are normalized with respect to corresponding neat CO2 case and draw on two key metrics, time to hit the top and maximum extent, are contrasted for 2 depths \u201cshallow\u201d (~5,000 ft, ~60\u00baC, 2500 psi, 100,000 mg\/L) and \u201cdeep\u201c (~10,000 ft, 125\u00baC, 4500 psi, 180,000 mg\/L). Because O2, N2, and Ar have similar properties and behavior, they impact the CO2-dominated mixtures in a similar way, particularly at the concentration level of a couple percent molar and they can be merged in one unique component with properties of N2. However, the approximation deviates from the \u201ctrue case\u201d beyond a few percents. Impurities impact density and viscosity of the CO2-rich mixture. A lower density impacts CO2 capacity not only because of the smaller fraction injected and space needed for storing impurities but also because of the generally lower density of the impurities at the same conditions. An approximate proxy for capacity change owing to impurities is given by the density ratio. The loss in capacity can be as high as >50% at very shallow depths (~3000 ft, CO2 and 15% molar N2) but the difference quickly decreases with depth. Similarly, mass injectivity, that can be represented by the proxy metric of density over viscosity ratio, also shows a decreased value at very shallow depths that quickly recovers with increasing depth.<\/span>
\nIn terms of plume shape and extent, the impact of impurities is again more marked at shallow depth where the contrast in density and viscosity with neat CO2 is the largest. It decreases with depth. For example, about 4% mole fraction in a binary system suffices to increase plume length in \u201cshallow\u201d low-dip sloping layers by 25% whereas 9 to 15%, depending on the component, are needed in a \u201cdeep\u201d system. In all cases, plume extent is greater with impurities however residual trapping occurs faster. This relationship mostly holds for all systems whatever the level of heterogeneity and complexity. The contrast is most extreme in very simple systems and heterogeneity assuming adequate operational choices seems to dampen impacts of impurities. This presumably occurs because heterogeneity creates multiple tongues blunting the impact of impurities.<\/span>
\nIt also suggests a trade-off between plume extent (area of review with risk of CO2 leakage) and decreased risk owing to faster trapping. A larger plume translates into a larger area to inspect for leakage pathways such as faults and abandoned wells but a faster trapping translates into a shorter period of time to monitor the site.<\/span>
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Impact of CO2 Impurities on Storage Performance anContinue Reading<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[159],"tags":[251,458],"_links":{"self":[{"href":"http:\/\/learncmg.cn\/index.php?rest_route=\/wp\/v2\/posts\/62012"}],"collection":[{"href":"http:\/\/learncmg.cn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/learncmg.cn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/learncmg.cn\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/learncmg.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=62012"}],"version-history":[{"count":0,"href":"http:\/\/learncmg.cn\/index.php?rest_route=\/wp\/v2\/posts\/62012\/revisions"}],"wp:attachment":[{"href":"http:\/\/learncmg.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=62012"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/learncmg.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=62012"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/learncmg.cn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=62012"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}