International Journal of Greenhouse Gas Control最新文献_第2页

Corrigendum to “Cross-sectoral assessment of CO2 capture from U.S. industrial flue gases for fuels and chemicals manufacture” [International Journal of Greenhouse Gas Control 135 (2024) 1-20 / 104137] "美国燃料和化学品制造工业烟气二氧化碳捕集跨部门评估 "更正[《国际温室气体控制杂志》135 (2024) 1-20 / 104137]

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-10-01 DOI: 10.1016/j.ijggc.2024.104264

M. Jibran S․ Zuberi, Arman Shehabi, Prakash Rao

引用次数: 0

Simulation analysis of salt precipitation in large-scale CO2 storage using periodic injection via a horizontal well 通过水平井定期注入大规模二氧化碳封存中盐沉淀的模拟分析

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-10-01 DOI: 10.1016/j.ijggc.2024.104263

Maryam Khosravi, Erling H. Stenby, Wei Yan

This simulation study investigates the novel aspects of salt precipitation and formation damage near a horizontal injector during CO₂ storage in an offshore depleted oil reservoir with high water saturation and non-negligible residual oil. Built upon prior experimental findings, our study delves into the intricate interplay between displacement, evaporation, and capillary backflow during periodic CO₂ injection, necessitating fine gridding (e.g., down to 2 cm) near the wellbore and an equivalent representation of the wellbore area to capture salt precipitation dynamics accurately. A key contribution of this work is the identification and detailed quantitative characterization of three distinct drying regimes—evaporative, capillary, and viscous—based on gas flux at the perforation, which poses unique challenges in reservoir simulation. Notably, our study is the first to demonstrate these drying regimes specifically along a single CO₂ injector well, providing critical insights for reservoir management. The results highlight the significant impact of the capillary regime on injectivity loss and underscore the necessity of refined wellbore grid resolution to mitigate potential total plugging risks. Furthermore, this work evaluates the effects of injection temperature and trapped oil, revealing their suppressive effects on salt precipitation. Importantly, employing a 3D sector model, we explore extreme scenarios such as complete perforation plugging within the capillary regime, showcasing redirection of gas flux to preserve injectivity. Overall, this study advances the field by offering detailed quantitative assessments of drying regimes and underscores the critical importance of tailored simulation approaches for effective reservoir management in complex offshore environments with residual oil.

本模拟研究调查了在高水饱和度和不可忽略的残余油的近海枯竭油藏中进行二氧化碳封存时，水平注入器附近盐沉淀和地层破坏的新情况。基于之前的实验结果，我们的研究深入探讨了周期性二氧化碳注入过程中位移、蒸发和毛细管回流之间错综复杂的相互作用，这就需要在井筒附近进行精细网格划分（如细至 2 厘米），并对井筒区域进行等效表示，以准确捕捉盐沉淀动态。这项工作的一个主要贡献是根据射孔处的气体通量，识别并详细定量描述了三种不同的干燥机制--蒸发、毛细和粘性，这给储层模拟带来了独特的挑战。值得注意的是，我们的研究首次具体展示了单口二氧化碳注入井的这些干燥机制，为储层管理提供了重要的启示。研究结果凸显了毛细管机制对注入率损失的重大影响，并强调了细化井筒网格分辨率以降低潜在总堵塞风险的必要性。此外，这项研究还评估了注入温度和截留油的影响，揭示了它们对盐沉淀的抑制作用。重要的是，我们采用三维扇形模型探索了极端情况，如在毛细管系统内射孔完全堵塞，展示了气体流量的重新定向以保持注入率。总之，这项研究通过对干燥机制进行详细的定量评估，推动了该领域的发展，并强调了在有剩余油的复杂近海环境中，量身定制的模拟方法对于有效的储层管理至关重要。

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引用次数: 0

Development of carbon capture and storage (CCS) hubs in Kazakhstan 在哈萨克斯坦发展碳捕集与封存（CCS）中心

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-10-01 DOI: 10.1016/j.ijggc.2024.104259

Nurgabyl Khoyashov , Gaini Serik , Amina Togay , Yerdaulet Abuov , Alisher Alibekov , Woojin Lee

The competitiveness of both the power and industry sectors in Kazakhstan is due to the use of cheap fossil fuels. Due to the projected large-scale deployment of renewable energy sources in the future, some portions of cheap coal and hydrocarbon use are planned to be phased out in Kazakhstan. In its net-zero journey, the country still intends to have GHG emissions from reduced use of fossil fuels and “hard-to-electrify” industries such as chemicals, cement, and iron/steel sectors. Carbon capture and storage (CCS) is a decarbonization solution to existing fossil fuel-fired power plants and other hard-to-abate industries in the net-zero age, which Kazakhstan officially plans to reach by 2060. This study covers three major research tasks on large-scale CCS deployment in Kazakhstan. The study first reveals the “low-hanging fruits” of CO₂ capture in the natural gas processing and ammonia production industries, with a low cost of capture of $29 per ton of CO₂ captured each, by comparing the costs of capture in Kazakhstan with those of power plants, steel factories, cement plants, refineries, and hydrogen plants. Secondly, this work shows that developing CCS projects in hubs of multiple emitters can bring cost-efficient deployment of CCS in Kazakhstan. Lastly, we presented our vision of how CCS could be a part of Kazakhstan's big net-zero plan in 2060. Our estimates show that 8 CCS hubs in Kazakhstan with a total capacity of 115 Mt CO₂/year could cost $87 billion in capital expenditures (CAPEX) until 2060. While CO₂ capture remains the most expensive component of CCS process chains globally, compressing and transporting CO₂ poses significant cost challenges in Kazakhstan due to the long distances between emission sources and storage sites. Future research endeavors could explore automated tools to optimize logistical considerations and enhance the accuracy of cost estimations. Moreover, further studies should incorporate site-specific data to reduce assumptions and refine CCS potential assessments in Kazakhstan.

哈萨克斯坦的电力和工业部门之所以具有竞争力，是因为使用了廉价的化石燃料。由于预计未来将大规模部署可再生能源，哈萨克斯坦计划逐步淘汰部分廉价煤炭和碳氢化合物的使用。在实现净零排放的过程中，哈萨克斯坦仍打算减少化石燃料和 "难以电气化 "行业（如化工、水泥和钢铁行业）的温室气体排放。碳捕集与封存（CCS）是现有化石燃料发电厂和其他难以消减行业在净零时代的脱碳解决方案，哈萨克斯坦官方计划到 2060 年实现净零时代。本研究涵盖在哈萨克斯坦大规模部署 CCS 的三大研究任务。研究首先通过比较哈萨克斯坦与发电厂、钢铁厂、水泥厂、炼油厂和制氢厂的二氧化碳捕集成本，揭示了天然气加工和合成氨生产行业二氧化碳捕集的 "低垂果实"，每吨二氧化碳捕集成本低至 29 美元。其次，这项工作表明，在多排放源中心开发二氧化碳捕集与封存（CCS）项目可以在哈萨克斯坦实现具有成本效益的二氧化碳捕集与封存（CCS）部署。最后，我们介绍了CCS如何成为哈萨克斯坦2060年净零排放大计划的一部分。我们的估算显示，在2060年之前，哈萨克斯坦8个CCS中心（总产能为每年1.15亿吨二氧化碳）的资本支出（CAPEX）将达到870亿美元。虽然二氧化碳捕集仍是全球二氧化碳捕集工艺链中最昂贵的部分，但由于排放源与贮存地点之间距离遥远，压缩和运输二氧化碳在哈萨克斯坦构成了巨大的成本挑战。未来的研究工作可以探索自动化工具，以优化物流考虑因素，提高成本估算的准确性。此外，进一步的研究应纳入具体地点的数据，以减少假设并完善哈萨克斯坦的 CCS 潜力评估。

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引用次数: 0

Optimization of pressure management strategies for geological CO2 storage using surrogate model-based reinforcement learning 利用基于代用模型的强化学习优化二氧化碳地质封存的压力管理策略

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-10-01 DOI: 10.1016/j.ijggc.2024.104262

Jungang Chen , Eduardo Gildin , Georgy Kompantsev

Injecting greenhouse gas (e.g. CO2) into deep underground reservoirs for permanent storage can inadvertently lead to fault reactivation, caprock fracturing and greenhouse gas leakage when the injection-induced stress exceeds the critical threshold. It is essential to monitor the evolution of pressure and the movement of the CO2 plume closely during the injection to allow for timely remediation actions or rapid adjustments to the storage design. Extraction of pre-existing fluids at various stages of the injection process, referred as pressure management, can mitigate associated risks and lessen environmental impact. However, identifying optimal pressure management strategies typically requires thousands of simulations, making the process computationally prohibitive. This paper introduces a novel surrogate model-based reinforcement learning method for devising optimal pressure management strategies for geological CO2 sequestration efficiently. Our approach comprises of two steps. The first step involves developing a surrogate model using the embed to control method, which employs an encoder-transition-decoder structure to learn dynamics in a latent or reduced space. The second step, leveraging this proxy model, utilizes reinforcement learning to find an optimal strategy that maximizes economic benefits while satisfying various control constraints. The reinforcement learning agent receives the latent state representation and immediate reward tailored for CO2 sequestration and choose real-time controls which are subject to predefined engineering constraints in order to maximize the long-term cumulative rewards. To demonstrate its effectiveness, this framework is applied to a compositional simulation model where CO2 is injected into saline aquifer. The results reveal that our surrogate model-based reinforcement learning approach significantly optimizes CO2 sequestration strategies, leading to notable economic gains compared to baseline scenarios.

向地下深层储层注入温室气体（如二氧化碳）进行永久封存，当注入引起的应力超过临界值时，可能会无意中导致断层再活化、毛岩断裂和温室气体泄漏。在注入过程中，必须密切监测压力的变化和二氧化碳羽流的移动，以便及时采取补救措施或快速调整储层设计。在注入过程的不同阶段抽取预先存在的流体，即压力管理，可以降低相关风险，减少对环境的影响。然而，确定最佳压力管理策略通常需要进行数千次模拟，因此计算成本过高。本文介绍了一种新颖的基于代用模型的强化学习方法，用于有效设计二氧化碳地质封存的最佳压力管理策略。我们的方法包括两个步骤。第一步是利用嵌入到控制方法开发一个代理模型，该方法采用编码器-转换器-解码器结构来学习潜空间或缩小空间中的动态。第二步，利用该代理模型，通过强化学习找到一个最优策略，在满足各种控制约束条件的同时实现经济效益最大化。强化学习代理接收为二氧化碳封存量身定制的潜在状态表示和即时奖励，并根据预定义的工程约束条件选择实时控制，以实现长期累积奖励的最大化。为了证明该框架的有效性，我们将其应用于将二氧化碳注入含盐含水层的组成模拟模型。结果表明，我们基于代用模型的强化学习方法大大优化了二氧化碳封存策略，与基线方案相比取得了显著的经济效益。

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引用次数: 0

Techno-economic-environmental study of CO2 and aqueous formate solution injection for geologic carbon storage and enhanced oil recovery 注入二氧化碳和甲酸盐水溶液用于地质碳封存和提高石油采收率的技术经济环境研究

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-10-01 DOI: 10.1016/j.ijggc.2024.104257

Abouzar Mirzaei-Paiaman , Omar A. Carrasco-Jaim , Ryosuke Okuno

As carbon capture, utilization, and storage (CCUS), carbon-dioxide enhanced oil recovery (CO₂ EOR) has inherent shortcomings, such as inefficient oil recovery and carbon storage, and low storage security with mobile CO₂. This paper presents a techno-economic-environmental analysis of using formate species, a product of CO₂ electrochemical reduction, as an alternative carbon carrier for sequestration and EOR in a carbonate oil reservoir in the Gulf of Mexico Basin. CO₂ injection, water-alternating-CO₂ injection, and aqueous formate solution injection were compared using a compositional reservoir simulation model and an economic calculator. Formate solution injection yielded greater levels of oil recovery and net carbon storage, where the carbon-bearing species resided in the dense aqueous phase without having to rely on petrophysical trapping mechanisms (structural and capillary). The enhanced oil production, net carbon storage, and storage security can be promoted by providing formate-based CCUS with more incentives (e.g., greater tax credit) in comparison to CO₂-based CCUS for EOR and the manufacture of chemicals and products. In establishing carbon storage incentive policies and regulations, policymakers should include alternative carbon carriers.

作为碳捕集、利用和封存（CCUS）的一种，二氧化碳提高石油采收率（CO2 EOR）具有固有的缺陷，如石油采收和碳封存效率低、流动二氧化碳的封存安全性低等。本文对使用二氧化碳电化学还原产物甲酸盐作为墨西哥湾盆地碳酸盐岩油藏封存和 EOR 的替代碳载体进行了技术-经济-环境分析。使用成分储层模拟模型和经济计算器对二氧化碳注入、水替代二氧化碳注入和甲酸盐水溶液注入进行了比较。甲酸盐溶液注入提高了石油采收率和净碳储量，其中含碳物质停留在高密度水相中，无需依赖岩石物理捕集机制（结构和毛细管）。与用于 EOR 和化学品及产品制造的基于 CO2 的 CCUS 相比，通过为基于格式的 CCUS 提供更多激励措施（如更大的税收减免），可以提高石油产量、净碳封存和封存安全性。在制定碳封存激励政策和法规时，政策制定者应将替代碳载体纳入其中。

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引用次数: 0

Surrogate model optimization of vacuum pressure swing adsorption using a flexible metal organic framework with hysteretic sigmoidal isotherms 利用具有滞后西格玛等温线的柔性金属有机框架优化真空变压吸附的替代模型

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-10-01 DOI: 10.1016/j.ijggc.2024.104260

Yuya Takakura , Suryateja Ravutla , Jinsu Kim , Keisuke Ikeda , Hiroshi Kajiro , Tomoyuki Yajima , Junpei Fujiki , Fani Boukouvala , Matthew Realff , Yoshiaki Kawajiri

This study presents a process optimization study for a vacuum pressure swing adsorption (VPSA) process using a flexible metal-organic framework (MOF), which is gaining attention as a material to realize energy-efficient carbon dioxide capture processes. Many flexible MOFs exhibit sigmoidal adsorption isotherms with hysteresis, posing a challenge for simulation and optimization using a rigorous process model. In this study, we employ surrogate model optimization, where surrogate models using machine-learning algorithms were constructed from simulation of 903 operating conditions generated by Latin hypercube sampling. The surrogate models with the best performance were identified from 18 different surrogate options considering four design variables—adsorption pressure, desorption pressure, adsorption time, and desorption time. Using the best surrogate models, a multi-objective optimization problem was solved to identify the Pareto front among recovery, energy consumption, and bed size factor. Our analysis identified a distinct characteristic of VPSA using a flexible-MOF where purity and recovery are hardly affected by the feed volume.

本研究针对使用柔性金属有机框架（MOF）的真空变压吸附（VPSA）工艺进行了工艺优化研究。许多柔性 MOF 表现出具有滞后性的西格玛吸附等温线，这给使用严格的工艺模型进行模拟和优化带来了挑战。在本研究中，我们采用了代用模型优化方法，通过对拉丁超立方采样生成的 903 种操作条件进行模拟，利用机器学习算法构建代用模型。考虑到吸附压力、解吸压力、吸附时间和解吸时间这四个设计变量，从 18 种不同的代用方案中确定了性能最佳的代用模型。利用最佳代用模型，我们解决了一个多目标优化问题，以确定回收率、能耗和床层尺寸系数之间的帕累托前沿。我们的分析确定了使用柔性 MOF 的 VPSA 的一个显著特点，即纯度和回收率几乎不受进料量的影响。

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引用次数: 0

Feasibility of carbon dioxide geological storage in abandoned coal mine: A fully coupled model with validated multi-physical interactions 废弃煤矿二氧化碳地质封存的可行性：经过验证的多物理相互作用全耦合模型

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-10-01 DOI: 10.1016/j.ijggc.2024.104256

Teng Teng , Shiqiang Yang , Peng Yi , Shengli Yang , Chaoyang Ren , Guoliang Gao

It has gained wide attention that Carbon dioxide (CO₂) is to be injected into abandoned coal mines for geological storage of CO₂-enhanced coalbed methane recovery. Although abundantly evidences in literature indicate that the injection of CO₂ will cause lots of interactions among the mechanical characteristics of coal and the properties of CO₂ flow, further studies on these multi-physical interactions are still necessary. In this work, a series of laboratory experiments to elucidate the multi-physical interactions of CO₂ adsorption, softening effect of coal and the non-Darcy gas flow were conducted. Based on the experimental results, theoretical and empirical models to describe these coal-CO₂ interactions were meticulously proposed and validated, the results turned out to be satisfactory. Consequently, the compressive strength and elasticity modulus of coal decrease exponentially with the increased injection CO₂ pressure. The gas flow in coal obeys the Izbash non-Darcy model, and coal permeability can be well modified by the volumetric stress. By taking these coal-CO₂ interactions into account, this study established of a fully coupled model for coal deformation and CO₂ conservation. The model was then implemented into the numerical simulations of CO₂ storage in abandoned coal mine by using the finite element method. A series of scenario-based numerical simulations was conducted to investigate the feasibility and limitation of CO₂ storage in abandoned coal mine. The conducted experiments, models and numerical simulation will offer implications on the multi-physical interactions between coal and gas especially in CO₂ storage in abandoned coal mines.

在废弃煤矿中注入二氧化碳（CO2）进行地质封存，以提高煤层气的采收率，已引起广泛关注。尽管大量文献表明，注入二氧化碳会引起煤的力学特性和二氧化碳流动特性之间的许多相互作用，但对这些多物理相互作用的进一步研究仍然是必要的。在这项工作中，进行了一系列实验室实验，以阐明 CO2 吸附、煤的软化效应和非达西气流的多物理相互作用。在实验结果的基础上，细致地提出并验证了描述这些煤-CO2 相互作用的理论和经验模型，结果令人满意。结果表明，煤的抗压强度和弹性模量随注入 CO2 压力的增加呈指数下降。煤炭中的气体流动遵循 Izbash 非达西模型，煤炭的渗透性可以很好地受到体积应力的影响。考虑到煤与 CO2 的相互作用，本研究建立了煤变形与 CO2 保存的完全耦合模型。然后，利用有限元法将该模型应用于废弃煤矿中二氧化碳封存的数值模拟。通过一系列基于场景的数值模拟，研究了在废弃煤矿中封存二氧化碳的可行性和局限性。所进行的实验、模型和数值模拟将为煤与瓦斯之间的多物理相互作用，特别是废弃煤矿中的二氧化碳封存提供启示。

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引用次数: 0

Multiphase flow modelling of gas migration from a hypothetical integrity-compromised petroleum well in the peace region of North-eastern British Columbia, Canada 加拿大不列颠哥伦比亚省东北部和平地区一口假定完整性受损油井的天然气迁移多相流模型

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-09-28 DOI: 10.1016/j.ijggc.2024.104261

Amirsaman Rezaeyan , Roger D. Beckie , Aaron G. Cahill

Well-integrity failure occurs in a small subset of petroleum wells, resulting in release of fugitive gas into intersected geologic formations. Released fugitive gas from geoenergy systems is a growing environmental concern that can contaminate groundwater aquifers and emit greenhouse gases (GHGs) to atmosphere. Currently, the roles of well-cement quality and properties of intersected geologic formations on the environmental outcomes of well-integrity failure is poorly understood. To advance understanding, we numerically modelled a hypothetical fugitive methane release from a petroleum well intersecting the Sunset Paleovalley aquifer system in Northeast British Columbia, Canada. We simulate a 10-year release and migration of fugitive gas into a two dimensional, two-phase, two-component advective flow field with the subsurface properties informed by field and laboratory data. We evaluate the effects of cement quality, gas release depth, and geologic heterogeneity on fugitive-gas containment or emission by defining and/or evaluating three key numbers: a) emission-retention ratio (ERR), b) well integrity index (WII), and c) fugitive gas mobility ratio (MR) over relevant spatiotemporal scales. We show that ERR and WII capture the bifurcated impacts of fugitive gas from petroleum wells, including groundwater contamination and atmospheric emissions. A WII close to one reduces vertical fugitive-gas migration along the well bore, fosters lateral migration into intersected geologic materials and significantly limits GHG emissions to atmosphere. MR and ERR values show fugitive-gas migration and fate are primarily controlled by the casing annulus cement quality, particularly when fugitive gas is released at shallow depths. We conclude that the quality of petroleum-well cement is among the parameters controlling the migration pathways, impacts, and fate of fugitive-gas release.

油井完整性失效发生在一小部分油井中，导致逸散气体释放到相交的地质构造中。地质能源系统释放的逸散气体会污染地下含水层，并向大气排放温室气体（GHGs），是一个日益严重的环境问题。目前，人们还不太了解油井水泥质量和相交地层的性质对油井完整性失效的环境影响所起的作用。为了加深了解，我们对加拿大不列颠哥伦比亚省东北部与 Sunset Paleovalley 含水层系统相交的一口石油井的甲烷逃逸释放进行了数值模拟。我们模拟了逸散气体在二维、两相、双组分平流场中的 10 年释放和迁移过程，其地下属性参考了现场和实验室数据。我们通过定义和/或评估以下三个关键数据来评估水泥质量、气体释放深度和地质异质性对逸散气体封存或排放的影响：a）排放滞留率（ERR）；b）油井完整性指数（WII）；c）相关时空尺度上的逸散气体流动比率（MR）。我们的研究表明，ERR 和 WII 能够捕捉到石油油井逸散气体的分叉影响，包括地下水污染和大气排放。接近 1 的 WII 可减少沿井眼的纵向逸散气体迁移，促进横向迁移到相交的地质材料中，并显著限制向大气的温室气体排放。MR和ERR值表明，逸散气体的迁移和归宿主要受套管环空水泥质量的控制，尤其是当逸散气体在浅层释放时。我们的结论是，石油井水泥质量是控制逃逸气体释放的迁移路径、影响和归宿的参数之一。

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引用次数: 0

Stochastic control of geological carbon storage operations using geophysical monitoring and deep reinforcement learning 利用地球物理监测和深度强化学习对地质碳储存操作进行随机控制

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-09-18 DOI: 10.1016/j.ijggc.2024.104238

Kyubo Noh, Andrei Swidinsky

Geological carbon storage (GCS) is the process of injecting and storing carbon dioxide (CO₂) in the subsurface to reduce greenhouse gas emissions. Safe and profitable GCS operations require effective decision-making in the presence of uncertain geological models, a process which can often be facilitated with geophysical monitoring. In this study, we examine how sequential decision-making algorithms can be combined with geophysical measurements for the optimal control of GCS operations. Specifically, we develop an artificial intelligence model using deep reinforcement learning (DRL) that takes geophysical time-lapse gravity and well pressure monitoring data as input and delivers an optimal CO₂ injection policy. The objective of the problem at hand is to maximize the profit of a hypothetical GCS operation while mitigating the potential for induced seismicity, by training DRL agents using combined geostatistical, reservoir and geophysical simulation. Comparisons against two benchmarks – a constant injection strategy and an injection schedule optimized using a commercial reservoir simulator toolbox – show that the stochastic control of such operations from subsurface monitoring data using deep reinforcement learning is feasible. Evaluation results show that DRL agent behavior generates profits which are on average 1 to 8 percent higher than what is possible through a constant injection approach. Furthermore, we show that DRL can generate optimal injection policies applicable to the true (yet previously unseen) subsurface given carefully managed levels of uncertainty.

地质碳封存（GCS）是在地下注入并封存二氧化碳（CO2）以减少温室气体排放的过程。安全、盈利的地质碳封存操作需要在地质模型不确定的情况下做出有效决策，而地球物理监测通常可以促进这一过程。在本研究中，我们探讨了如何将顺序决策算法与地球物理测量相结合，以实现对 GCS 作业的优化控制。具体来说，我们利用深度强化学习（DRL）开发了一个人工智能模型，将地球物理延时重力和井压监测数据作为输入，并提供最佳二氧化碳注入策略。当前问题的目标是通过使用综合地质统计、储层和地球物理模拟来训练 DRL 代理，使假设的 GCS 作业利润最大化，同时降低诱发地震的可能性。与两个基准--恒定注入策略和使用商业储层模拟器工具箱优化的注入计划--的比较表明，利用深度强化学习从地下监测数据对此类操作进行随机控制是可行的。评估结果表明，DRL 代理行为产生的利润比恒定注水方法平均高出 1%-8%。此外，我们还展示了 DRL 能够生成适用于真实（但之前未见过）地下的最佳注入策略，并对不确定性水平进行了精心管理。

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引用次数: 0

Investment in CCUS under technical uncertainty considering investor's risk aversion: An exotic compound real-options approach 考虑到投资者的风险规避，技术不确定性下的 CCUS 投资：一种奇特的复合实物期权方法

IF 4.6 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2024-09-14 DOI: 10.1016/j.ijggc.2024.104241

Sanaz Sheikhtajian , Jafar Bagherinejad , Emran Mohammadi

Carbon capture, utilization, and storage (CCUS) technology is effective and value-adding solution for reducing emissions. However, the development and commercialization of these technologies are challenging due to high investment costs and several uncertainties. This study develops a novel comprehensive real-options-based model to evaluate investment in CCUS projects considering the technical risk and the investor's risk aversion. This study proposed an exotic compound real options model that combines American and barrier options. First, applying the Poison process, the technical risk is explicitly modeled. Secondly, the investor's risk aversion is defined as a barrier level for the barrier option part of the proposed model. Thirdly, the value of the project is evaluated through the exotic compound real option. Finally, we assess the economic viability of the project under multiple scenarios. The results of implementing the model for a real case show that the integrated technical risk assessment and the barrier option appropriately address investors' risk aversion. Furthermore, the comparison indicates that the proposed compound real options model is more effective than the traditional NPV (Net Present Value). Regarding policymaking, the results reveal that setting an appropriate carbon tax that considers the costs of carbon capture would be more beneficial. Further, the model provides investors helpful guidance to make proper investment decisions for CCUS technology projects under uncertainties.

碳捕集、利用和封存（CCUS）技术是一种有效且具有附加值的减排解决方案。然而，由于高昂的投资成本和一些不确定因素，这些技术的开发和商业化面临挑战。考虑到技术风险和投资者的风险规避，本研究开发了一种基于实物期权的新型综合模型，用于评估 CCUS 项目的投资。本研究提出了一种结合美式期权和障碍期权的奇异复合实物期权模型。首先，应用泊松过程，对技术风险进行了明确建模。其次，将投资者的风险规避定义为模型中障碍期权部分的障碍水平。第三，通过外来复合实物期权评估项目价值。最后，我们评估了项目在多种情况下的经济可行性。在实际案例中实施该模型的结果表明，综合技术风险评估和障碍期权恰当地解决了投资者的风险规避问题。此外，比较结果表明，建议的复合实物期权模型比传统的净现值（NPV）更有效。在政策制定方面，研究结果表明，考虑碳捕集成本的适当碳税制定将更为有利。此外，该模型还为投资者在不确定情况下对 CCUS 技术项目做出正确的投资决策提供了有益的指导。

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引用次数: 0