International Journal of Greenhouse Gas Control最新文献

{"title":"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]","authors":"M. Jibran S․ Zuberi, Arman Shehabi, Prakash Rao","doi":"10.1016/j.ijggc.2024.104264","DOIUrl":"10.1016/j.ijggc.2024.104264","url":null,"abstract":"","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104264"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of carbon capture and storage (CCS) hubs in Kazakhstan","authors":"Nurgabyl Khoyashov ,&nbsp;Gaini Serik ,&nbsp;Amina Togay ,&nbsp;Yerdaulet Abuov ,&nbsp;Alisher Alibekov ,&nbsp;Woojin Lee","doi":"10.1016/j.ijggc.2024.104259","DOIUrl":"10.1016/j.ijggc.2024.104259","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104259"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142357643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation analysis of salt precipitation in large-scale CO2 storage using periodic injection via a horizontal well","authors":"Maryam Khosravi,&nbsp;Erling H. Stenby,&nbsp;Wei Yan","doi":"10.1016/j.ijggc.2024.104263","DOIUrl":"10.1016/j.ijggc.2024.104263","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104263"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of pressure management strategies for geological CO2 storage using surrogate model-based reinforcement learning","authors":"Jungang Chen ,&nbsp;Eduardo Gildin ,&nbsp;Georgy Kompantsev","doi":"10.1016/j.ijggc.2024.104262","DOIUrl":"10.1016/j.ijggc.2024.104262","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104262"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424080","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}

{"title":"Techno-economic-environmental study of CO2 and aqueous formate solution injection for geologic carbon storage and enhanced oil recovery","authors":"Abouzar Mirzaei-Paiaman ,&nbsp;Omar A. Carrasco-Jaim ,&nbsp;Ryosuke Okuno","doi":"10.1016/j.ijggc.2024.104257","DOIUrl":"10.1016/j.ijggc.2024.104257","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104257"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528853","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}

{"title":"Surrogate model optimization of vacuum pressure swing adsorption using a flexible metal organic framework with hysteretic sigmoidal isotherms","authors":"Yuya Takakura ,&nbsp;Suryateja Ravutla ,&nbsp;Jinsu Kim ,&nbsp;Keisuke Ikeda ,&nbsp;Hiroshi Kajiro ,&nbsp;Tomoyuki Yajima ,&nbsp;Junpei Fujiki ,&nbsp;Fani Boukouvala ,&nbsp;Matthew Realff ,&nbsp;Yoshiaki Kawajiri","doi":"10.1016/j.ijggc.2024.104260","DOIUrl":"10.1016/j.ijggc.2024.104260","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104260"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility of carbon dioxide geological storage in abandoned coal mine: A fully coupled model with validated multi-physical interactions","authors":"Teng Teng ,&nbsp;Shiqiang Yang ,&nbsp;Peng Yi ,&nbsp;Shengli Yang ,&nbsp;Chaoyang Ren ,&nbsp;Guoliang Gao","doi":"10.1016/j.ijggc.2024.104256","DOIUrl":"10.1016/j.ijggc.2024.104256","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104256"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528852","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}

{"title":"Multiphase flow modelling of gas migration from a hypothetical integrity-compromised petroleum well in the peace region of North-eastern British Columbia, Canada","authors":"Amirsaman Rezaeyan ,&nbsp;Roger D. Beckie ,&nbsp;Aaron G. Cahill","doi":"10.1016/j.ijggc.2024.104261","DOIUrl":"10.1016/j.ijggc.2024.104261","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104261"},"PeriodicalIF":4.6,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic control of geological carbon storage operations using geophysical monitoring and deep reinforcement learning","authors":"Kyubo Noh,&nbsp;Andrei Swidinsky","doi":"10.1016/j.ijggc.2024.104238","DOIUrl":"10.1016/j.ijggc.2024.104238","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104238"},"PeriodicalIF":4.6,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1750583624001816/pdfft?md5=7d5cc03498cb28d8fd8c0d3a0dcc2d6b&pid=1-s2.0-S1750583624001816-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investment in CCUS under technical uncertainty considering investor's risk aversion: An exotic compound real-options approach","authors":"Sanaz Sheikhtajian ,&nbsp;Jafar Bagherinejad ,&nbsp;Emran Mohammadi","doi":"10.1016/j.ijggc.2024.104241","DOIUrl":"10.1016/j.ijggc.2024.104241","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":334,"journal":{"name":"International Journal of Greenhouse Gas Control","volume":"138 ","pages":"Article 104241"},"PeriodicalIF":4.6,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142228640","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}