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作者简介:

刘瑛(1976—),女,浙江临海人,高级工程师,从事油气田开发方面的研究与管理工作。E-mail:liuy_2012@163.com。

通讯作者:

杨红(1986—),男,湖北仙桃人,高级工程师,硕士。E-mail:yh_cup2011@sina.com。

中图分类号:TE348

文献标识码:A

文章编号:1009-9603(2023)02-0144-09

DOI:10.13673/j.cnki.cn37-1359/te.202211026

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目录contents

    摘要

    黄土塬地区地表条件复杂,特低渗透油藏CO2驱井网密度大、注入压力高、易气窜以及为减缓气窜以水气交替开发为主的特点造成 CO2泄漏点源多、强度高,以致该区域 CO2监测点位布局和监测精度要求高,现有安全监测体系难以适应。通过对黄土塬地区特低渗透油藏CO2泄漏风险进行识别,分析CO2在地质体的空间运移特征,构建了涵盖盖层、井筒、深层和浅层地下水、地表土壤、地表水和大气的立体化多指标CO2安全监测体系,并在此基础上,开展了矿场CO2安全监测实践,进一步建立了CO2封存安全评价体系。安全监测和评价结果表明,CO2注入后各指标未出现异常,试验区未发生CO2地质泄漏,CO2封存安全等级为Ⅰ级。

    Abstract

    The loess tableland has complex surface conditions,and CO2 flooding in ultra-low permeability reservoirs faces the high density of well patterns,the high injection pressure,and the easy gas channeling. Moreover,the development is characterized by water-alternating-gas injection to mitigate gas-channeling.As a result,there are multiple CO2 leakage points and high intensity in this area,so the layout and monitoring accuracy of CO2 monitoring points are demanding,and the existing safety monitoring systems are hardly applicable. In view of these problems,according to the identification of CO2 leakage risks in ultra-low permeability reservoirs in the loess tableland and the analysis of CO2 spatial migration in geological bodies,a three-dimensional multi-index CO2 safety monitoring system was established,covering cap rock,well-bores,deep and shallow groundwater,soil,surface water,and atmosphere. Besides,CO2 safety monitoring was practically carried out to further build a safety evaluation system of CO2 storage. From the results of safety monitoring and evaluation, there was no abnormality for all indexes after CO2 injection and no CO2 geological leakage occured in the test area. The safe- ty of CO2 storage was at the levelⅠ.

  • 碳捕集、利用与封存(CCUS)作为一项为应对温室气体减排而发展起来的新兴技术,能够在实现 CO2大规模减排中发挥重要作用。2020年国际能源署(IEA)研究表明,在可持续发展情景下,CCUS 技术对 CO2累积减排量的贡献可达 15%[1]。CO2驱油与封存作为 CCUS 技术的重要组成和发展方向,具有经济和环保双重效益,被认为是当前经济和技术条件下CO2减排的理想选择[2-3]。在CO2驱油提高采收率的同时,由于地质构造、黏滞力和毛细管力作用、CO2在地层流体中的溶解及其与地层岩石矿物和流体相互作用,绝大部分 CO2 会封存在油藏中[4-6],但由于地质条件本身的不确定性和油藏开发过程中的人为因素,注入的 CO2依然具有一定的泄漏风险[7-10]。一旦CO2发生泄漏,会对生态环境和社会安全产生重大影响,建立系统全面的 CO2安全监测体系并进行有效监测是目前降低CO2泄漏风险和保障CO2封存安全的主要方法。

  • 为构建 CO2驱油与封存安全监测体系,中外众多学者开展了广泛研究。 WHITTAKER 等基于 Weyburn 和 Pembina 油田地质特征,建立了涵盖储层、盖层、地下流体和近地表环境的CO2安全监测体系[11-12]。MA 等通过评估乔家洼油区储盖层条件,设计了覆盖储层和近地表环境的 CO2安全监测体系[13]。李琦等利用 MST 软件提出了针对胜利油田的 CO2安全监测体系框架[14]。ZHANG 等在吉林油田构建了包括井筒完整性、储层和环境的 CO2安全监测体系[15]。中国环保部发布的《二氧化碳捕集、利用与封存环境风险评估技术指南(试行)》,对 CCUS 项目环境风险识别和评估做了进一步规范[16]。综上分析,中外学者针对特定油藏已建立了完整性不同的 CO2安全监测体系并开展了相应监测,但在黄土塬地区特低渗透油藏 CO2安全监测体系方面还缺少系统研究。由于特低渗透油藏储层物性差、非均质性强、天然和人工裂缝交错,油藏开发具有井网密度大、注入压力高、易气窜以及为减缓气窜以水气交替开发为主的特点,造成油藏 CO2 泄漏呈现点源多、强度高的风险特征[17-18];另外,黄土塬地区地表沟壑纵横,且覆盖有较厚的疏松黄土层,近地表 CO2监测受监测点位和气象条件影响较大,对该区域 CO2监测点位布局和监测精度要求更高[19-20]。上述特点造成现有的安全监测体系难以适用于黄土塬地区特低渗透油藏CO2驱油与封存。

  • 为此,笔者在分析黄土塬地区特低渗透油藏 CO2泄漏途径和风险识别的基础上,通过明确CO2在地质体的空间运移特征,提出了 CO2泄漏安全监测指标,构建了立体化多指标CO2安全监测体系,并针对性开展了矿场CO2泄漏监测,保障了CO2驱油与封存示范工程的安全性。同时,结合安全监测体系和矿场安全监测实践进一步建立了适合黄土塬地区特低渗透油藏的 CO2封存安全评价体系,为高效开展 CO2驱油与封存项目的安全监测和评价提供依据。

  • 1 CO2泄漏风险识别

  • CO2泄漏风险识别是指判别能引起 CO2泄漏的各种事件,分析风险发生的潜在原因[21]。一般来说,CO2驱油与封存泄漏风险主要来自注入井、生产井、废弃井等工程设施和地层裂缝、断层等地质构造,由于鄂尔多斯盆地地质构造较为稳定,断层基本不发育,本文主要分析由井筒和地层裂缝可能引发的CO2泄漏。

  • CO2注入会引发井筒内温度和压力的交替变化,导致井筒组合体(套管、水泥、地层岩石)发生非均匀热膨胀和收缩,井筒出现动态拉伸和收缩破坏,造成在套管/水泥环和水泥环/地层的界面产生裂纹[22-24]。同时,由于 CO2对套管和水泥环的化学腐蚀作用,CO2长期注入后,存在套管穿孔及水泥环产生空隙、裂缝和径向裂纹的风险[25-26],这些都是 CO2在注入井井筒发生泄漏的通道。需要注意的是,特低渗透油藏开发井网密度大、注入压力高和水气交替开发的特点,造成交变应力和腐蚀作用对井筒的破坏性增强,井筒 CO2泄漏点源增多,致使 CO2泄漏风险大幅增加。因此,为保障特低渗透油藏CO2注入与封存安全,必须扩大井筒监测范围,提高监测频率。

  • 特低渗透油藏天然裂缝发育,受压裂改造形成的人工裂缝也普遍存在,在较高的注入压力下,裂缝开启和生成会造成 CO2泄漏风险进一步增大,需对储盖层裂缝进行动态监测[27]。通过监测储层CO2 运移情况,明确其运移方向和范围以判断 CO2潜在泄漏方位,并指导开展其他监测。同时,盖层既是阻碍 CO2向上迁移的有效屏障,也是泄漏通道。由于特低渗透储层上覆盖层多为泥岩,其突破压力高、厚度大且分布连续性好,CO2一般难以通过渗透和扩散方式突破盖层发生泄漏[28]。为降低盖层裂缝开启和生成的风险,防止CO2泄漏,可通过长期监测盖层中的微地震事件以确保盖层良好的封盖效果。

  • 2 CO2安全监测体系构建

  • 2.1 CO2泄漏空间运移特征

  • 由于储层及其上部地层条件复杂,CO2在地层的迁移转化方式多样。受浮力作用影响,注入储层的 CO2纵向迁移速度高于横向,注入初期以纵向运移为主,在CO2羽流到达盖层底部后,受盖层阻隔作用控制,开始在储层大规模横向运移。随着注入量增大和储层压力不断升高,CO2通过渗透和扩散作用缓慢进入盖层,由于盖层泥质含量高、厚度大、突破压力高,CO2通过上述2种机制一般难以有效突破盖层,但特低渗透油藏注入压力高,盖层存在裂缝开启和生成的风险,这些裂缝可为 CO2突破盖层提供泄漏通道。

  • 突破盖层或沿井筒泄漏的CO2会进入深层地下水,并从泄漏点向上快速扩散。由于深层地下水受次级盖层的阻隔作用,上覆地层流体对其扰动较小,水体流动缓慢,当 CO2为点状泄漏且速率较低时,CO2羽流在纵向上呈窄带状垂向分布,随着 CO2 泄漏速率增大,羽流幅围逐渐变宽并向上泄漏至浅层地下水[20]。与深层地下水层相比,浅层地下水层渗透率高,CO2在其中扩散更快。同时,由于浅层地下水与地表水连通性好,黄土塬地区地表土壤良好的透水性会促使地表降水入渗作用增强,由此造成浅层地下水流动速度相对较快,CO2泄漏一般具有显著的随水流向下游运移的方向性特征,因此,为确保 CO2封存安全,应对下游位置进行重点监测。此外,由于浅层地下水还是重要工农业生产和居民生活水源,因此,其是开展CO2泄漏监测的重点区域。

  • CO2突破浅层地下水体后会向上泄漏至土壤、大气等地表环境。由于黄土塬地区地表土质疏松、孔隙度大,CO2在土壤中运移阻力小且扩散速度快,使得CO2泄漏具有横向多向性和纵向泄漏面积大的特点[19],考虑区域覆盖黄土层较厚,应对不同深度的土壤进行监测。CO2泄漏至大气后,受地势和气象条件的影响,易在下风向和黄土塬地区河谷等地势低洼区聚集,进而形成高浓度CO2聚集区。因此,在进行大气 CO2监测时,应重点监测井场下风向和河谷区。

  • 2.2 CO2安全监测指标

  • CO2泄漏至储层上部地层空间后会引起地层及其赋存流体性质的变化,为快速高效监测 CO2泄漏情况,需根据不同监测层位的 CO2泄漏空间运移特征,建立技术上可操作性强且经济可行的 CO2安全监测指标。

  • 2.2.1 微地震事件

  • CO2注入储层后,在地层压力梯度和浮力的共同作用下,CO2羽流发生横向和纵向迁移并产生压力扰动,甚至在地层局部出现压力聚集,诱发储层和上覆盖层裂缝开启或生成,甚至会活化断层,产生不同级别的微地震事件[29-30]。利用微地震技术监测地层发生的微地震事件,可以评估 CO2封存的安全性。Weyburn 油田微地震监测发现,在储层的上覆和下伏地层出现多个震级为 1~3 级的微地震事件[29]。Illinois 盆地咸水层 CO2封存项目,在 22 个月的注入时间内,在储层下部地层监测到 10 123次震级为 1~2 级的微地震事件,分析认为注入的 CO2活化了该区域的多个小断层[31]

  • 特低渗透油藏由于 CO2注入压力高,运移过程中产生的压力扰动大,进而诱发裂缝的风险也增大,利用微地震技术对储层和盖层进行重点监测,分析产生的原因,并着重评估 CO2注入后的盖层完整性。

  • 2.2.2 腐蚀监测

  • CO2溶于水后形成的酸性流体会对油管和套管造成不同程度的腐蚀,随着腐蚀损伤累积,管柱的物理化学特性发生改变,导致其结构稳定性和耐久性降低,进而破坏井筒的完整性,严重影响CO2的安全注入与封存。大庆长垣外围油田CO2驱油试验区井筒点滴式加注缓蚀剂后,进行腐蚀速率监测显示,不同深度油井井筒平均腐蚀速率为 0.025 6 mm/ a [32]。长岭气田气井管柱腐蚀速率监测发现,加注缓蚀剂后,生产管柱的腐蚀速率控制在行业标准范围内[33]。相关研究结果均表明,向油套环空加注缓蚀剂并对注采管柱进行腐蚀监测,是保持井筒完整性,确保CO2注入与封存安全的有效手段[34-38]

  • 与富 CO2相环境相比,富 H2O 相中溶有更多杂质,碳钢管材在富 H2O 相中比在富 CO2相中面临更严重的腐蚀[39]。特低渗透油藏CO2和水交替注入的开发方式进一步加剧了流体对管柱的腐蚀,在制定严格的腐蚀防护措施的基础上,需对注采管柱进行高频率的腐蚀速率、采出水铁离子质量浓度等指标监测,及时分析注采管柱腐蚀情况,最大限度地降低CO2沿管柱泄漏的风险。

  • 2.2.3 pH值

  • 黄土塬地区地下水和地表水均呈中性-偏弱碱性,CO2泄漏至地下水体后,溶于地层水并生成碳酸,从而引起水体酸化,pH 值降低。杜尚海等以美国某试验场地为例,模拟了 CO2泄漏对浅层地下水的影响,结果表明,CO2泄漏进入浅层地下水后,水体 pH 值从初始的 7.96 降低至 4.98[40]。姜玲模拟研究得出,当泄漏速率为0.000 5 kg/s时,地下水pH值迅速降低至饮用水标准范围以下[41]。LITTLE 等对美国 17个地区的含水层进行 CO2注入实验发现,所有样品中的 H+ 质量浓度均升高了 1~2个数量级[42]。张丙华等通过实验发现,不同泄漏速率条件下,CO2 发生泄漏 48 h 后,地表水 pH 值均以不同速度由 7.7 下降至约 5.3 [43]。因此,pH 值可作为一项水体监测指标以判断CO2是否泄漏。

  • 2.2.4 Ca2+ 和Mg2+ 质量浓度

  • CO2泄漏造成水体酸化会改变原始地层中的水岩平衡环境,诱发方解石、伊利石、斜长石、绿泥石等矿物溶解和蒙脱石等矿物沉淀,从而引发水体中离子质量浓度发生变化。LI 等以延长油田浅层地下水为例,研究了 CO2泄漏对地下水化学组成的影响[44]。研究表明:在 CO2泄漏速率为 0.000 1 kg/s 的条件下,在泄漏初始阶段,由于泄漏点附近水体中方解石、伊利石、斜长石和绿泥石等矿物溶解,Ca2+ 和 Mg2+ 质量浓度急剧升高;CO2泄漏 10 a后,受上述矿物溶解和钠蒙脱石、钙蒙脱石沉淀作用的影响, Ca2+ 质量浓度开始缓慢升高,Mg2+ 质量浓度快速下降;但 CO2泄漏 100 a 后,Mg2+ 质量浓度依然远高于其初始值。因此,基于CO2泄漏至地下水体后,水体中 Ca2+ 和 Mg2+ 质量浓度显著升高的变化规律,可将其作为一项监测水体CO2泄漏的重要指标。

  • 2.2.5 CO2浓度

  • CO2突破浅层地下水体后,受环境温度和压力降低的影响,开始以气态的形式扩散运移。CO2泄漏至土壤层后,快速置换土壤中的原生气体,造成 CO2浓度升高。由于黄土塬地区地表土壤以支架大孔隙结构为主[45],具有无层理、极松散、多孔隙的特点,CO2 在该地区土壤层中的迁移速度高且强度大[46-47]。CO2泄漏至大气后,由于 CO2较空气重,一定时间内泄漏点附近和地表低洼地带大气中CO2浓度会显著升高。因此,可将CO2浓度作为一项监测指标,用于监测CO2在地表土壤和大气中的泄漏情况。

  • 2.2.6 碳同位素组成δ13C

  • 碳同位素反映了碳源物质的组成及相对含量,可用来追踪 CO2的来源,近年来被广泛应用于气候与环境变化研究[48]。薛璐等利用靖边乔家洼 CCUS 试验区土壤开展 CO2泄漏模拟实验,通过研究不同体积分数 CO2对 C3和 C4植物 δ13C 的影响,认为利用 C4植物 δ13C可有效识别 CO2泄漏[49]。王晓晓通过开展雪玉洞周边地区植被和土壤等的 δ13C 监测,明确了洞穴内CO2主要来源为地下河[50]。CO2注入前,黄土塬地区地表土壤气 δ13C 值为-39.3‰~-25.6‰,大气 δ13C 值为-34.3‰~-26.1‰,油藏注入的 CO2为煤化工尾气,其 δ13C 值为-17.0‰~-15.0‰,由于注入 CO2与监测环境中地表土壤气和大气中 CO2δ13C 值差异较大,故可将碳同位素组成 δ13C 作为黄土塬地区地表土壤和大气的CO2泄漏监测指标。

  • 2.3 CO2安全监测体系

  • 特低渗透油藏 CO2注入压力高,随着 CO2注入量增大,储层压力升高,导致CO2沿盖层原生裂缝向上迁移的风险增大。同时,特低渗透油藏注采井网密度大,CO2沿井筒泄漏点源多。突破盖层或沿井筒泄漏的 CO2受地下水浮力作用,在纵向上向深层和浅层地下水迁移,并具有沿地下水流向下游横向迁移的特征。当CO2泄漏量增大时,CO2会突破深层和浅层地下水进入地表浅层土壤,并在黄土塬地区疏松土壤层中发生多向扩散运移,直至泄漏至近地表和大气中,并在泄漏点附近及地势低洼区聚集。因此,为全面监测CO2泄漏情况,需建立黄土塬地区特低渗透油藏立体化 CO2安全监测体系,该体系需在纵向上覆盖多层位,平面上控制重点区(表1)。

  • 纵向上,CO2突破盖层或腐蚀井筒后进入深层和浅层地下水,甚至泄漏至地表土壤、地表水和大气中,形成自下而上的泄漏路径。针对 CO2纵向泄漏特征,建立了涵盖盖层、井筒、深层和浅层地下水、地表土壤、地表水和大气的多层位纵向CO2安全监测体系。在地面和监测井中布设检波器,实时监测盖层中微地震事件;在注入井不同深度安装腐蚀挂片,并取样检测生产井采出水中Fe2+ 和Fe3+ 质量浓度;取样检测深层和浅层地下水及地表水的 pH值、 Ca2+ 和 Mg2+ 质量浓度;利用土壤-大气一体化监测设备,原位监测不同深度地表土壤气和大气中 CO2浓度,同时取样分析地表土壤气和大气的碳同位素组成δ13C。

  • 平面上,由于CO2泄漏路径受盖层完整性、注采井网、浅层地下水水流方向、黄土塬地区地形和气象条件等因素的影响,CO2在不同层位迁移方向多、运移范围大。针对 CO2平面泄漏特征,黄土塬地区特低渗透油藏CO2监测点位应确保覆盖试验区和控制重点区,具体为:尽量将注入井置于所有层位平面监测网的中心位置;盖层监测点位布设需参照储层CO2运移范围,并对薄弱区加密监测点;深层和浅层地下水、地表水监测点位应重点布设在下游位置;地表土壤和大气监测点位应集中布设在下风向和低洼地带。

  • 表1 黄土塬地区特低渗透油藏CO2安全监测体系

  • Table1 CO2 safety monitoring system for ultra-low permeability reservoir in loess tableland

  • 3 CO2安全监测实践

  • 基于 CO2安全监测体系,对黄土塬地区特低渗透油藏开展了盖层、井筒、深层和浅层地下水、地表土壤、地表水及大气的立体化CO2安全监测。

  • 通过在地面布设观测台站和井中储盖层段下入检波器,联合监测 CO2驱油与封存过程中产生的微地震事件来评估盖层的完整性。井地联合微地震监测结果显示,在 CO2注入过程中,共监测到 28 个微地震事件,均位于长 6 段储层中上部注入井附近,说明在CO2驱油与封存过程中,盖层完整性未受影响。结合 VSP 监测发现,CO2扩散运移集中在埋深为 1 380~1 500 m 的储层内,即 CO2垂直运移深度为1 500 m。

  • 加注缓蚀剂后的注采管柱腐蚀监测发现,注入井在埋深 400,1 000 和 1 600 m 处油管内外壁腐蚀速率为 0.008~0.016 mm/a,低于行业标准规定的腐蚀速率;生产井采出水中Fe2+ 和Fe3+ 质量浓度分别为 6.52~9.25 和 0.22~0.63 mg/L,该值与注气前采出水中Fe2+ 和Fe3+ 质量浓度相比,未出现明显变化。这表明加注缓蚀剂后,CO2驱油与封存过程中注采管柱未发生严重腐蚀。

  • 地下水持续监测显示,深层地下水 pH 值为 6.87~7.17,Ca2+ 和Mg2+ 的质量浓度分别为3.95~20.84 和 167.73~360.71 mg/L;浅层地下水 pH 值为 7.72~7.95,Ca2+ 和 Mg2+ 的质量浓度分别为 86.25~138.95 和 55.07~99.89 mg/L,且上下游监测点位获取的监测数据未见明显差异,初步判断 CO2未泄漏至地下含水层。

  • 大气和地表土壤气CO2浓度采用一体化集成设备进行监测,其中,大气CO2浓度监测点位的高度距离地面约为50 cm,地表土壤气CO2浓度监测点位在地表以下 1.20 m。梁卯区和河谷区监测结果(图1) 均显示,注气前后大气 CO2体积分数均为 0.04%~0.041%;受黄土塬地区林草地植物根系呼吸作用和微生物活动影响,地表土壤气 CO2浓度表现出夏季高、冬季低的变化特征,其中,夏季和冬季地表土壤气 CO2 体积分数分别为 0.91%~1.38% 和 0.40%~0.72%,但注气前后不同地形地表土壤气CO2浓度呈现的季节性变化规律均一致。CO2注入前后大气和地表土壤气 δ13C 值监测结果一致,且均与注入气 δ13C 值差异明显。上下游地表水长期监测结果显示,pH 值为 7.68~8.07,Ca2+ 和 Mg2+ 的质量浓度分别为 55.34~56.99 和 37.99~41.06 mg/L。由此,结合大气和地表土壤气CO2浓度、δ13C和地表水监测结果可判断CO2未泄漏至近地表和大气环境。

  • 综合立体化 CO2安全监测结果,认为黄土塬地区特低渗透油藏 CO2驱油与封存过程中未发生 CO2 地质泄漏,除部分 CO2随生产井产出外,注入的 CO2 均已实现安全有效封存。

  • 4 CO2封存安全评价体系建立

  • 参考饮用水水源评价体系[51],将 CO2封存安全评价体系划分为Ⅰ(非常安全)、Ⅱ(安全)、Ⅲ(基本安全)、Ⅳ(不安全)和Ⅴ(很不安全)5个等级(表2)。其中,CO2垂直运移深度安全等级取值范围主要根据 CO2驱油与封存项目储层、直接盖层和上覆盖层的厚度进行划分;腐蚀速率的安全等级取值范围基于美国腐蚀工程师协会对平均腐蚀程度的规定和中国碎屑岩油藏注水水质控制指标中对平均腐蚀速率的要求[52-53];参考中国对地下水质量常规指标及限值的规定[54] 划分 pH 值和 Ca2+ 质量浓度安全等级;根据试验区土壤气和注入气 δ13C 值差异,确定 δ13C不同安全等级的取值范围;CO2浓度安全等级取值范围参照神华 CO2咸水层封存项目安全评价体系[55]

  • 图1 注气前后不同地形大气和地表土壤气CO2体积分数

  • Fig.1 CO2 concentration in atmosphere and surface soil gas under different terrains before and after CO2 injection

  • 目标体系的安全等级采用综合指数法来确定。通过对评价体系中各指标数据进行标准化处理,并确定各指标的权重后,即可计算目标体系的安全等级,其表达式为:

  • Wij=AijXij'
    (1)
  • 将数值越大对CO2封存安全越有利的指标如评价体系中 CO2垂直运移深度和 pH 值等数据进行标准化处理,其表达式为:

  • Xij'=Xij-Xj,minXj,max-Xj,min
    (2)
  • 将数值越小对CO2封存安全越有利的指标如评价体系中腐蚀速率、Ca2+ 质量浓度、δ13C 和 CO2浓度等数据进行标准化处理,其表达式为:

  • Xij'=Xj,max-XijXj,max-Xj,min
    (3)
  • 各指标的权重采用层次分析法确定。其中,判断矩阵主要通过具有多年CCUS项目经验的专家打分来建立。经计算,CO2垂直运移深度、腐蚀速率、 pH 值、Ca2+ 质量浓度、δ13C 和 CO2浓度的权重分别为 0.441 8,0.228 8,0.130 9,0.108 1,0.056 6和0.033 9。

  • 黄土塬地区特低渗透油藏CO2驱油与封存安全监测实践显示,试验区的CO2垂直运移深度为1 500 m、腐蚀速率为 0.016 mm/ a、深层地下水 pH 值为 6.87、浅层地下水 Ca2+ 质量浓度为 138.95 mg/L、地表土壤气 δ13C 值为-25.6‰、大气 CO2 体积分数为 0.041%,其安全指数为0.859 5,CO2封存安全等级为 Ⅰ级。

  • 5 结论

  • 基于 CO2泄漏风险识别及其空间运移特征分析,构建了涵盖盖层、井筒、深层和浅层地下水、地表土壤、地表水和大气的黄土塬地区特低渗透油藏立体化多指标CO2安全监测体系。矿场安全监测结果表明,CO2注入后各监测指标未出现异常,试验区未发生 CO2地质泄漏,实现了 CO2安全有效封存。结合 CO2安全监测体系和矿场安全监测实践,建立了包含6项指标、5个等级的黄土塬地区特低渗透油藏CO2封存安全评价体系,评价结果表明试验区CO2 封存安全等级为Ⅰ级。

  • 表2 黄土塬地区特低渗透油藏CO2封存安全评价体系

  • Table2 Safety evaluation system of CO2 sequestration for ultra-low permeability reservoirs in loess tableland

  • 符号解释

  • Aij——第i年和第j个指标的权重;

  • i——评价时间,a;

  • j——评价指标;

  • Wij——安全指数;

  • Xij——第i年和第j个指标的监测数据;

  • X' ij——第 i年和第 j个指标监测数据标准化处理后的数值;

  • Xj,max——第j个指标监测数据的最大值;

  • Xj,min——第j个指标监测数据的最小值。

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