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Can acceptance of location-specific carbon capture and storage be tipped? The causal effects of information and question framing 特定地点的碳捕获和储存能否被接受?信息和问题框架的因果效应
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-02-01 Epub Date: 2026-01-14 DOI: 10.1016/j.ijggc.2026.104566
Jacob Ladenburg, Matteo Zuch, Jiwon Kim
Today, Carbon Capture and Storage (CCS) is an emerging technology that remains relatively unknown to the public. Informing and educating lay people about the technology, including, e.g., technical processes, potential and associated risks, is essential for obtaining well-informed public opinions about the technology, its deployment, and choices between storage locations. Based on the stated acceptance of offshore, nearshore, rural onshore and urban onshore CCS from 3877–3879 respondents from a Danish national survey, we test how three information experiments and question framing (order) affect location-specific acceptance and relative cross location acceptance while controlling for CCS familiarity. We find significant effects from information about international CCS experience, Danish onshore underground gas storage experience and question order effects. The significance of the effects, though, varies with CCS location. The results also denote that information and question order effects significantly affect the relative acceptance of nearshore CCS, onshore rural and urban CCS, but not offshore CCS. Offshore CCS is always significantly more accepted than the other CCS locations. Finally, we find a significant positive correlation between CCS familiarity and accepting offshore, nearshore and rural CCS locations.
如今,碳捕获与封存(CCS)是一项新兴技术,公众对其知之甚少。向非专业人员提供有关技术的信息和教育,包括技术流程、潜在风险和相关风险,这对于获得有关该技术、其部署以及在存储地点之间选择的充分知情的公众意见至关重要。根据来自丹麦全国调查的3877-3879名受访者对海上、近岸、农村陆上和城市陆上CCS的接受程度,我们测试了三个信息实验和问题框架(顺序)如何影响特定地点接受程度和相对跨地点接受程度,同时控制CCS熟悉程度。我们从国际CCS经验、丹麦陆上地下储气库经验和问题顺序效应中发现了显著的影响。然而,影响的重要性因CCS的位置而异。结果还表明,信息和问题顺序效应显著影响近岸CCS、岸上农村和城市CCS的相对接受度,但对海上CCS没有影响。海上CCS总是比其他CCS地点更容易被接受。最后,我们发现CCS熟悉度与接受近海、近岸和农村CCS地点之间存在显著的正相关关系。
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引用次数: 0
Unified deep-learning workflow for uncertainty reduction in subsurface carbon storage modeling through data assimilation of seismic-inverted CO2 maps 统一深度学习工作流程,通过地震反演CO2图的数据同化降低地下碳储量建模的不确定性
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-02-01 Epub Date: 2026-01-22 DOI: 10.1016/j.ijggc.2026.104582
Moises Velasco-Lozano , Bailian Chen , Zhiwei Ma , Rajesh Pawar
Prediction of dynamic CO2 saturation evolution in subsurface storage sites is critical to support carbon capture and storage deployment. Machine learning has gained important relevance to model CO2 injection in real time, reducing the uncertainty through inverse modeling techniques. However, conventional models rely on monitoring data from a limited number of wells to update the initial reservoir realizations. In this work, we introduce a deep-learning workflow for the use of inverted CO2 maps from seismic as an innovative data source for improved data assimilation.
We first built a deep-learning model (forward model engine) based on convolutional neural networks (CNN) and Fourier neural operators to predict CO2 saturation from reservoir properties and operational conditions. Next, we applied a deep CNN model to invert seismic gathers into encoded and reconstructed CO2 map responses. Finally, we developed a data assimilation module coupled with the forward model engine to reduce the uncertainty in the predicted CO2 saturation using the geophysics-derived CO2 maps from seismic gathers. To verify the applicability of our framework, we investigated the Frio-II storage site. The results obtained demonstrate the importance of assimilating inverted CO2 maps, enabling a correct match of the spatial and temporal advance of the ground truth CO2 plumes with discrepancies in the root mean square error less than 0.05. In addition, the calibrated permeability distributions resulted in maps very similar to the ground truth model. The work presented here describes a novel framework to generate more accurate data-driven estimations exploring the assimilation of inverted seismic information.
地下储存区二氧化碳饱和度的动态演化预测是支持碳捕集与封存部署的关键。机器学习在实时模拟二氧化碳注入方面具有重要意义,通过逆建模技术减少了不确定性。然而,传统模型依赖于有限数量井的监测数据来更新初始油藏认识。在这项工作中,我们引入了一种深度学习工作流程,将地震反演的二氧化碳图作为改进数据同化的创新数据源。首先,我们建立了一个基于卷积神经网络(CNN)和傅立叶神经算子的深度学习模型(前向模型引擎),根据储层性质和操作条件预测二氧化碳饱和度。接下来,我们应用深度CNN模型将地震聚集反演为编码和重建的CO2图响应。最后,我们开发了一个与正演模型引擎相结合的数据同化模块,以减少利用地震聚集的地球物理导出的二氧化碳图预测二氧化碳饱和度的不确定性。为了验证我们的框架的适用性,我们调查了Frio-II存储地点。得到的结果表明,同化倒排CO2图的重要性,使地面真实CO2羽流的时空推进得到正确匹配,差异均方根误差小于0.05。此外,校正后的渗透率分布结果与地面真值模型非常相似。本文介绍的工作描述了一种新的框架,用于生成更准确的数据驱动估计,探索反向地震信息的同化。
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引用次数: 0
Increasing carbon mitigation through enhanced oil recovery 通过提高石油采收率来减少碳排放
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-02-01 Epub Date: 2026-01-23 DOI: 10.1016/j.ijggc.2026.104580
YanJun Lu , QianBo Fan , JinXuan Han , ManPing Yang , JianGuo Ma , DaXin Zhou , HongJian Zhu , Yu Qi , HaoRan Ge
Carbon Capture, Utilization and Storage - Enhanced Oil Recovery (CCUS-EOR) technology, as a key carbon reduction solution for achieving the goals of "carbon peak" and "carbon neutrality", has broad application prospects. Taking the Tree 16 block of Daqing Oilfield as an example, the system studied the methods for calculating and evaluating the emission reduction throughout the entire chain of the CCUS-EOR project. By identifying the emission sources of each system (CO2 capture, oil displacement and storage), determining the equipment energy consumption, setting the accounting boundaries and baseline emissions, a carbon net emission reduction calculation model for the carbon capture and oil displacement storage process was established. The research results show that from 2014 to 2023, the cumulative energy consumption of the CO2 injection equipment in Block 16 of the tree was 258,000 tons, and the cumulative net reduction in emissions reached 455,000 tons, with an emission reduction rate of 59.21%. This study not only confirmed that the CCUS-EOR technology in Block 16 of the tree has the dual benefits of reducing emissions and increasing production, but also provided key data support for creating a "low-carbon stable production" demonstration block, striving for policy and market advantages, and offering a systematic solution for the carbon emission reduction calculation of the CCUS-EOR technology. It is of great significance for promoting the integration of CCUS-EOR projects into the carbon trading market and achieving efficient development of carbon assets in CO2-driven oil and gas field projects.
碳捕集、利用与封存-提高采收率(CCUS-EOR)技术作为实现“碳峰值”和“碳中和”目标的关键减碳解决方案,具有广阔的应用前景。该系统以大庆油田树16区块为例,研究了CCUS-EOR项目全链条减排量的计算与评价方法。通过确定各系统(CO2捕集、驱油和封存)的排放源,确定设备能耗,设置核算边界和基线排放,建立了碳捕集和驱油封存过程的碳净减排计算模型。研究结果表明,2014 - 2023年,采油树16区块CO2喷射设备累计能耗25.8万吨,累计净减排45.5万吨,减排率59.21%。本研究不仅证实了该采油树16区块CCUS-EOR技术具有减排和增产的双重效益,也为打造“低碳稳产”示范区块、争取政策和市场优势提供了关键数据支持,为CCUS-EOR技术的碳减排计算提供了系统解决方案。这对于推动CCUS-EOR项目融入碳交易市场,实现二氧化碳驱动油气田项目碳资产的高效开发具有重要意义。
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引用次数: 0
Maximizing the CO2 storage capacity in the depleted oil reservoirs: A case study of a mature oil field in Cuu Long Basin, Vietnam 枯竭油藏中最大限度地提高二氧化碳储存能力:以越南Cuu Long盆地某成熟油田为例
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-02-01 Epub Date: 2026-01-24 DOI: 10.1016/j.ijggc.2026.104579
Trong Vinh Bui , Quoc Dung Ta
Among numerous potential candidates for the upcoming projects of carbon sequestration in Vietnam, several depleted hydrocarbon reservoirs in Cuu Long basin have been selected for permanent trapping of CO2 underground. One of the most concerning issues associated with the injection technique is how to maximize the storage capacity of CO2 with the available surface facilities and gas resources. In this study, we attempt to numerically identify the most feasible CO2 injection method compatible with the current availability of the surface conditions for a mature oil field in Cuu Long basin. To this end, a total of twenty-one simulation cases are conducted on two different reservoir models, one of which represents a section of another full-scale model. In the small-scale model, sixteen injection cases of four scenarios are performed to address the effects of hydrocarbon gas, CO2, and water-alternating-gas technique on the ultimate carbon storage capacity. The best performance in each scenario is then verified in the upscaled model. The results show that a period of gas injection with production allowed can improve up to 58% the ultimate storage capacity of CO2 in the reservoir. When the amount of CO2 is limited for a pre-slug, the injection of discharged hydrocarbon gas becomes the most relevant option to efficiently displace liquid from the pore space, favoring the subsequent CO2 sequestration process. A buffer of a hydrocarbon gas for a certain period before the initiation of CO2 also shows an extra 11% CO2 being totally trapped in the field. The introduction of an aqueous phase under the water-alternating-gas technique helps increase a notable volume of oil production due to higher sweep efficiency, but it may partly impede the global occupancy of CO2, eventually reducing total CO2 storage capacity. Although the abovementioned results can be translated qualitatively between two reservoir models, however, a further inspection regarding the optimal injection timeline will be recommended for the full-scale model to deal with the upscaling issues.
在越南即将开展的碳封存项目的众多潜在候选项目中,Cuu Long盆地的几个枯竭的油气储层已被选中用于永久捕获二氧化碳的地下。与注入技术相关的最受关注的问题之一是如何利用现有的地面设施和天然气资源最大限度地提高二氧化碳的储存能力。在这项研究中,我们试图在数值上确定与目前Cuu Long盆地成熟油田地面条件相适应的最可行的CO2注入方法。为此,对两个不同的油藏模型进行了21个模拟案例,其中一个模型代表另一个全尺寸模型的一部分。在小规模模型中,进行了4种情况下的16个注入案例,以解决烃类气体、CO2和水-气交替技术对最终碳储量的影响。然后在升级模型中验证每个场景中的最佳性能。结果表明,在允许生产的情况下,一段时间的注气可使储层中CO2的最终储存量提高58%。当预段塞段的二氧化碳含量有限时,注入排出的烃类气体成为有效取代孔隙中液体的最相关选择,有利于后续的二氧化碳封存过程。在二氧化碳产生之前的一段时间内,碳氢化合物气体的缓冲也表明,额外的11%的二氧化碳被完全捕获在油田中。在水-气交替技术中引入水相,由于扫描效率更高,有助于显著提高产油量,但它可能在一定程度上阻碍了二氧化碳的全球占用,最终降低了二氧化碳的总储存容量。尽管上述结果可以在两种油藏模型之间进行定性转换,但是,建议对全尺寸模型进行进一步检查,确定最佳注入时间,以解决放大问题。
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引用次数: 0
Accelerated CCS site screening using Fourier Neural Operator based surrogates for flow simulations 使用基于傅立叶神经算子的流量模拟代理加速CCS站点筛选
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-02-01 Epub Date: 2026-01-21 DOI: 10.1016/j.ijggc.2026.104583
Suraj Pawar , Aniruddha Panda , Anirban Chandra , Pandu Devarakota , Faruk O. Alpak , Jeroen Snippe , Detlef Hohl
<div><div>One of the key elements for large scale deployment of carbon capture and storage (CCS) is the selection of appropriate sites to store the captured <span><math><msub><mrow><mtext>CO</mtext></mrow><mrow><mn>2</mn></mrow></msub></math></span>. To achieve this goal, various factors such as plume migration, storage capacity, and containment need to be validated over long-time horizons. Flow simulators, which accurately model the complex interplay of buoyancy, viscous, and capillary forces, are typically used for modeling plume migration, and thereby optimizing storage efficiency subject to subsurface constraints. However, large reservoirs and long-time horizons associated with CCS often render conventional flow simulators computationally expensive to apply. The computational efficiency challenge is further intensified for site screening applications in which typically large ensembles of forward simulations are necessary due to the uncertainty associated with subsurface variables. We develop a novel FNO-based surrogate modeling framework for the rapid prediction of plume-migration quantified by spatio-temporal evolution of <span><math><msub><mrow><mtext>CO</mtext></mrow><mrow><mn>2</mn></mrow></msub></math></span> accumulation and saturation fields. The FNO can approximate underlying physics such as multiphase/multicomponent reservoir simulation equations by using large, annotated datasets of input–output pairs. Finite-volume method based subsurface fluid flow simulation is used to generate a comprehensive dataset for a wide range of realistic subsurface parameters that are encountered in CCS sites globally. The outcome of the surrogate model is spatial distributions of <span><math><msub><mrow><mtext>CO</mtext></mrow><mrow><mn>2</mn></mrow></msub></math></span> accumulation and saturation for multiple time snapshots from end-of-injection to the end of a long-term migration period (1000 years post end-of-injection). To evaluate the performance of FNO-based surrogate models in the context of CCS site screening applications, we propose a range of novel physics-based metrics, such as plume distance to the injection location and normalized cumulative <span><math><msub><mrow><mtext>CO</mtext></mrow><mrow><mn>2</mn></mrow></msub></math></span> accumulation. The evaluation of the FNO-based model within probabilistic assessment workflow demonstrates that the statistics of different metrics is captured with high accuracy, including extreme cases. We also obtain <span><math><mrow><mi>O</mi><mrow><mo>(</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>3</mn></mrow></msup><mspace></mspace><mtext>to</mtext><mspace></mspace><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>4</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span> computational acceleration when compared to numerical simulations used in this work, with minimal sacrifice of prediction accuracy for <span><math><msub><mrow><mtext>CO</mtext></mrow><mrow><mn>2</mn></mrow></msub></math></span>
大规模部署碳捕集与封存(CCS)的关键因素之一是选择合适的地点来储存捕获的二氧化碳。为了实现这一目标,需要在较长时间内验证羽流迁移、存储容量和遏制等各种因素。流动模拟器可以精确地模拟浮力、粘性和毛细力的复杂相互作用,通常用于模拟羽流迁移,从而在地下约束条件下优化储存效率。然而,与CCS相关的大型油藏和长地层往往使传统的流动模拟器在计算上昂贵。在现场筛选应用中,由于地下变量的不确定性,通常需要大量的正演模拟,这进一步加剧了计算效率的挑战。我们开发了一个新的基于fno的代理建模框架,用于通过CO2积累和饱和场的时空演变量化羽流迁移。FNO可以通过使用大型的、带注释的输入输出对数据集来近似底层物理,例如多相/多组分油藏模拟方程。基于有限体积方法的地下流体流动模拟用于生成一个全面的数据集,该数据集涵盖了全球CCS站点遇到的各种真实地下参数。代理模型的结果是从注入结束到长期迁移期结束(注入结束后1000年)的多个时间快照的CO2积累和饱和度的空间分布。为了评估基于fno的替代模型在CCS现场筛选应用中的性能,我们提出了一系列新的基于物理的指标,如到注入位置的烟羽距离和标准化的二氧化碳累积量。在概率评估工作流中对基于fno的模型的评估表明,不同度量的统计数据被高精度地捕获,包括极端情况。与本工作中使用的数值模拟相比,我们还获得了0 (103to104)的计算加速,并且以最小的代价牺牲了CO2积累和饱和度的预测精度。
{"title":"Accelerated CCS site screening using Fourier Neural Operator based surrogates for flow simulations","authors":"Suraj Pawar ,&nbsp;Aniruddha Panda ,&nbsp;Anirban Chandra ,&nbsp;Pandu Devarakota ,&nbsp;Faruk O. Alpak ,&nbsp;Jeroen Snippe ,&nbsp;Detlef Hohl","doi":"10.1016/j.ijggc.2026.104583","DOIUrl":"10.1016/j.ijggc.2026.104583","url":null,"abstract":"&lt;div&gt;&lt;div&gt;One of the key elements for large scale deployment of carbon capture and storage (CCS) is the selection of appropriate sites to store the captured &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mtext&gt;CO&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;. To achieve this goal, various factors such as plume migration, storage capacity, and containment need to be validated over long-time horizons. Flow simulators, which accurately model the complex interplay of buoyancy, viscous, and capillary forces, are typically used for modeling plume migration, and thereby optimizing storage efficiency subject to subsurface constraints. However, large reservoirs and long-time horizons associated with CCS often render conventional flow simulators computationally expensive to apply. The computational efficiency challenge is further intensified for site screening applications in which typically large ensembles of forward simulations are necessary due to the uncertainty associated with subsurface variables. We develop a novel FNO-based surrogate modeling framework for the rapid prediction of plume-migration quantified by spatio-temporal evolution of &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mtext&gt;CO&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; accumulation and saturation fields. The FNO can approximate underlying physics such as multiphase/multicomponent reservoir simulation equations by using large, annotated datasets of input–output pairs. Finite-volume method based subsurface fluid flow simulation is used to generate a comprehensive dataset for a wide range of realistic subsurface parameters that are encountered in CCS sites globally. The outcome of the surrogate model is spatial distributions of &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mtext&gt;CO&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; accumulation and saturation for multiple time snapshots from end-of-injection to the end of a long-term migration period (1000 years post end-of-injection). To evaluate the performance of FNO-based surrogate models in the context of CCS site screening applications, we propose a range of novel physics-based metrics, such as plume distance to the injection location and normalized cumulative &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mtext&gt;CO&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; accumulation. The evaluation of the FNO-based model within probabilistic assessment workflow demonstrates that the statistics of different metrics is captured with high accuracy, including extreme cases. We also obtain &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mtext&gt;to&lt;/mtext&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;4&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; computational acceleration when compared to numerical simulations used in this work, with minimal sacrifice of prediction accuracy for &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mtext&gt;CO&lt;/mtext&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; ","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"150 ","pages":"Article 104583"},"PeriodicalIF":5.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimization of carbon capture, utilization, and storage supply chains for the hard-to-abate industry in Türkiye 优化碳捕集、利用和储存供应链,为难以减少的行业在<s:1> rkiye
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-02-01 Epub Date: 2026-01-14 DOI: 10.1016/j.ijggc.2026.104568
Sena Kumcu , Bahar Özyörük , Fabrizio Bezzo , Federico d'Amore
Carbon dioxide plays a central role in driving climate change. Carbon capture, utilization, and storage (CCUS) has emerged as a critical mitigation option, particularly for hard-to-abate industrial sectors. This study introduces an optimization framework to evaluate the technical and economic feasibility of establishing a large-scale CO2 infrastructure for the iron and steel, cement, and refining industries in Türkiye. The framework, developed using a mixed-integer linear programming approach, seeks to minimize the overall system costs by integrating multiple capture technologies, transportation means, geological storage options, and the possibility of CO2 utilization through electro-Methanol production. The results indicate that the most economically efficient solution is achieved under a scenario which combines rail and pipeline transportation, and geological storage within national borders. For a 10% carbon reduction target, the lowest specific CO2 avoidance cost is 68.0 €/t, while for a 90% target, the cost rises to 110.2 €/t.
二氧化碳在推动气候变化方面起着核心作用。碳捕集、利用和封存(CCUS)已成为一个关键的减排选择,特别是对于难以减排的工业部门。本研究介绍了一个优化框架,以评估在泰国为钢铁、水泥和炼油行业建立大规模二氧化碳基础设施的技术和经济可行性。该框架采用混合整数线性规划方法开发,旨在通过整合多种捕获技术、运输手段、地质储存选择以及通过电甲醇生产利用二氧化碳的可能性,最大限度地降低整体系统成本。结果表明,最经济有效的解决方案是将铁路和管道运输结合起来,并在国家境内进行地质储存。对于10%的碳减排目标,最低的特定二氧化碳避免成本为68.0€/t,而对于90%的目标,成本上升到110.2€/t。
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引用次数: 0
Assessment of prospective CO2 geological storage resources in the Taiwan Strait 台湾海峡未来二氧化碳地质储存资源评估
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-02-01 Epub Date: 2026-01-21 DOI: 10.1016/j.ijggc.2026.104578
Jianghui Li , Yanni Hou , Fengling Yu , Daolong Zhou , Hengnian Dong , Xiaokang Zhang
Geological storage of carbon dioxide (CO2) is a viable option for achieving large-scale and cost-effective reduction in global CO2 emissions. The Taixi Basin, spanning the Taiwan Strait, is a potential storage field for reducing CO2 emissions in the Fujian and Taiwan regions. It hosts multiple effective reservoir-seal combinations, with abundant sandstone formations. These combinations divide the Taixi Basin into five dominant sags, namely the Taizhong Sag, Xinzhu Sag, Jiulongjiang Sag, Jinjiang Sag, and Chongwu Sag. However, the resource assessment of CO2 storage in the Taixi Basin is typically conducted at the basin-scale, which makes it difficult to determine the resources of the target areas with optimal burial depths and superior reservoir conditions. This study estimates the prospective CO2 storage resources for each sag of the Taixi Basin using DOE volumetric methods, both without and with considering the pressure limitations. This approach allows for a more in-depth and accurate characterization of regional storage resources. The results show that the theoretical storage resources of the Taixi Basin range between 16.3 Gt and 62.2 Gt, and the effective resources range between 5.03 Gt and 12.3 Gt. This not only provides a clear range of theoretical and effective storage resources but also serves as a guide for implementing real-world CO2 storage projects.
地质储存二氧化碳(CO2)是实现大规模和经济有效地减少全球二氧化碳排放的可行选择。横跨台湾海峡的太西盆地是减少福建和台湾地区二氧化碳排放的潜在储存区。它拥有多种有效的储层密封组合,具有丰富的砂岩地层。这些组合将太西盆地划分为五大优势凹陷,即台中凹陷、新竹凹陷、九龙江凹陷、晋江凹陷和崇武凹陷。然而,太西盆地CO2储量资源评价通常是在盆地尺度上进行的,难以确定最佳埋藏深度和储层条件优越的目标区资源。在不考虑压力限制和考虑压力限制的情况下,采用DOE容积法对太西盆地各凹陷的未来CO2储量进行了估算。这种方法允许对区域存储资源进行更深入和准确的表征。结果表明,太西盆地理论库存量在16.3 ~ 62.2 Gt之间,有效库存量在5.03 ~ 12.3 Gt之间。这不仅为理论库存量和有效库存量提供了明确的范围,也为实际CO2库存量项目的实施提供了指导。
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引用次数: 0
Towards carbon geosequestration: comparing the wettability performance of Western Australian altered basaltic rock/CO2/water systems 走向碳地球固存:比较西澳大利亚蚀变玄武岩/二氧化碳/水系统的润湿性性能
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-01 Epub Date: 2025-12-24 DOI: 10.1016/j.ijggc.2025.104554
Seyi Philemon Akanji , Rossen Sedev , Lionel Esteban , Ausama Giwelli , Trevor Beardsmore , Heather Howard , Joel Sarout , Alireza Keshavarz , Stefan Iglauer
Geosequestration of carbon dioxide in basaltic rock formations is considered to have the potential to safely and permanently store significant quantities of this greenhouse gas and thereby mitigate its potential global warming effect. The success of this storage method is primarily dependent on the wettability behaviour of the rock-water-CO2 system, which significantly affects fluid distribution, fluid transport, storage capacity and containment security. This study investigates the wettability performance of several Western Australian altered basaltic rocks, of similar geochemistry, porosity and inter-connection. The wettability behaviour of the basaltic materials is assessed using water containing ions that have been leached from the rock samples used in this investigation (Synthetic Formational Water). Under realistic geo-storage conditions, most samples exhibited intermediate -wet behaviour at pressures of 10 to 80 bar and a temperature of 50 °C. Further increase in pressure from 80 to 100 bar at 50 °C changed the wettability of the altered basaltic rock samples with most samples changing from an intermediate-wet state to weakly CO2-wet state, while the other sample maintained this intermediate-wet at 100 bar and 50 °C temperature. This study highlights the potential of Western Australian altered basaltic rocks to be used for the mineral storage of CO2.
在玄武岩地层中封存二氧化碳被认为有可能安全、永久地储存大量这种温室气体,从而减轻其潜在的全球变暖效应。这种储存方法的成功主要取决于岩石-水-二氧化碳体系的润湿性,这对流体分布、流体输送、储存能力和密封安全性有很大影响。本文研究了几种具有相似地球化学特征、孔隙度和相互关系的西澳大利亚蚀变玄武岩的润湿性。玄武岩材料的润湿性行为是用含离子的水来评估的,这些离子是从本研究中使用的岩石样品中浸出的(合成地层水)。在实际的地质储存条件下,大多数样品在10至80 bar的压力和50°C的温度下表现出中间湿态。在50℃、80 ~ 100 bar的压力下,蚀变玄武岩样品的润湿性发生变化,大部分样品由中湿状态转变为弱co2湿状态,其余样品在100 bar、50℃温度下保持中湿状态。这项研究强调了西澳大利亚变质玄武岩用于二氧化碳矿物储存的潜力。
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引用次数: 0
Influence of CO2 partial pressure on electrochemical behavior of corrosion-resistant alloys for CO2 injection tubing of carbon capture and storage system CO2分压对碳捕集与封存系统CO2注入管耐腐蚀合金电化学行为的影响
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-01 Epub Date: 2025-12-27 DOI: 10.1016/j.ijggc.2025.104564
Maryam Eslami , Xi Wang , Yoon-Seok Choi
Four different corrosion-resistant alloys (13Cr, super 13Cr, 25Cr duplex stainless, 25Cr super duplex stainless steel) were studied under two different CO2 partial pressures (0 and 13.8 MPa) at high temperature (150 °C) in a 3 wt.% NaCl solution. Electrochemical and exposure experiments were conducted at a consistent initial pH for comparison. The results indicate that 13Cr exhibits active corrosion behavior, whereas super 13Cr demonstrates typical passive behavior without re-passivation under the testing conditions. Both 25Cr duplex and 25Cr super duplex steels show exceptional corrosion resistance and passive behavior, with re-passivation potentials higher than corrosion potential in nearly all testing conditions. Passive films show similar composition and forward-scan responses under both experimental conditions; however, in the CO2 environment, the alloys repassivated only at more negative potentials than in the CO₂-free condition.
研究了4种不同的耐蚀合金(13Cr、超级13Cr、25Cr双相不锈钢、25Cr超级双相不锈钢)在高温(150℃)下CO2分压(0和13.8 MPa)和3wt .% NaCl溶液中的腐蚀性能。在相同的初始pH下进行电化学和暴露实验进行比较。结果表明:在试验条件下,13Cr合金表现为主动腐蚀行为,而超级13Cr合金表现为典型的无再钝化被动腐蚀行为。25Cr双相钢和25Cr超级双相钢都表现出优异的耐腐蚀性和被动行为,在几乎所有测试条件下,其再钝化电位都高于腐蚀电位。被动膜在两种实验条件下均表现出相似的成分和正向扫描响应;然而,在CO2环境中,合金只在负电位下比在无CO2条件下重钝化。
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引用次数: 0
Does the release of toxic metals due to subsurface CO2 storage in basalts pose an environmental hazard? 由于玄武岩地下二氧化碳储存而释放的有毒金属是否会对环境造成危害?
IF 5.2 3区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-01 Epub Date: 2025-12-02 DOI: 10.1016/j.ijggc.2025.104526
Deirdre E. Clark , Iwona M. Galeczka , Sigurður R. Gíslason , Sandra Ó. Snæbjörnsdóttir , Ingvi Gunnarsson , Eric H. Oelkers
Carbon dioxide storage through the carbonation of subsurface basaltic rocks is currently being explored to limit carbon emissions to the atmosphere. Basaltic rocks, however, contain trace and toxic metals that could potentially be mobilized by the carbonation process. This study reports the degree to which selected trace and toxic metals were mobilized during CarbFix1 and CarbFix2 projects. CarbFix1 injected 175 tons of CO2-charged water followed by 73 tons of CO2/H2S-charged water into basalts at 35 °C, whereas CarbFix2 continuously injected CO2/H2S-charged water into basalts at >250 °C. In most cases dissolved concentrations of Ba, Sr, Mo, Cu, Cr, Ni, Cd, and Pb in monitoring well fluids remained low. Although these fluids are not intended for human consumption, the aqueous trace element concentrations were generally below the WHO, EU, and Iceland drinking water standards, except for Fe and Mn in CarbFix1. Aluminum and As concentrations exceeded these standards during CarbFix2, but were elevated before injection. The low concentrations of most trace and toxic metals are consistent with their removal by secondary processes, particularly co-precipitation into carbonate and sulfide minerals formed during gas-water-basalt interaction. Solid precipitates recovered from CarbFix1 show strong enrichment of transition metals in calcite, consistent with natural and engineered analogues. As the two CarbFix injections bound the lower and upper temperature ranges of likely mineral carbon storage efforts, these results suggest limited risk of water contamination due to toxic and trace element release from subsurface basalts due to the injection of dissolved CO2 and H2S.
目前正在探索通过地下玄武岩的碳酸化来储存二氧化碳,以限制碳排放到大气中。然而,玄武岩中含有微量和有毒的金属,这些金属可能会通过碳化过程被动员起来。本研究报告了在CarbFix1和CarbFix2项目中选定的痕量和有毒金属的动员程度。CarbFix1先向玄武岩注入175吨含二氧化碳的水,然后在35℃下注入73吨含二氧化碳/硫化氢的水,而CarbFix2则在250℃下连续向玄武岩注入含二氧化碳/硫化氢的水。在大多数情况下,监测井流体中Ba、Sr、Mo、Cu、Cr、Ni、Cd和Pb的溶解浓度仍然很低。虽然这些液体不是供人类饮用的,但水中微量元素的浓度普遍低于世界卫生组织、欧盟和冰岛的饮用水标准,除了CarbFix1中的铁和锰。在CarbFix2期间,铝和砷的浓度超过了这些标准,但在注射前升高。大多数微量和有毒金属的低浓度与它们通过二次过程去除一致,特别是在气-水-玄武岩相互作用过程中形成的碳酸盐和硫化物矿物中共沉淀。从CarbFix1中回收的固体沉淀物显示方解石中过渡金属的富集,与天然和工程类似物一致。由于两次CarbFix注入限制了可能的矿物碳储存工作的上下温度范围,因此这些结果表明,由于注入溶解的CO2和H2S,地下玄武岩释放出有毒和微量元素,因此水污染的风险有限。
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引用次数: 0
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International Journal of Greenhouse Gas Control
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