International Journal of Greenhouse Gas Control最新文献_第8页

Experimental investigation into CO2 sequestration and associated ecological behaviours of carbon-negative backfilling with coal gangues 煤矸石负碳充填CO2固存及相关生态行为实验研究

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-10-01 DOI: 10.1016/j.ijggc.2025.104494

Baiyi Li , Kang Long , Wenbo Cheng , Xinghui Fu , Jiayuan Ma , Shuaijie Zhang

Carbon-negative backfilling was proposed to facilitate the co-disposal of the solid waste and CO₂, based on the mineralization characteristics of calcium-containing solid waste from coal mining. However, uncertainties remain regarding the carbon sequestration capacity and potential environmental impacts following backfilling. In this study, carbon sequestration tests were conducted with a sealed mixing tank by injecting CO₂ into gangue slurry, and the heavy metals leaching from the slurry were recorded. The results indicated that the coal gangue backfilling slurry (CGBS) demonstrated the capacity to absorb 11.17 g·kg⁻¹ of CO₂ at an initial pressure of 1 MPa, alongside a decrease in the four kinds of heavy metal concentration. The maximum carbon sequestration and efficiency were observed at 100 °C, yielding 23.49 g·kg⁻¹ and 74.42%, respectively. The leaching content of heavy metals decreased after the CO₂ mixing treatment, indicating that the carbonization process significantly mitigates the environmental risks associated with CGBS leakage during underground backfilling, reducing the water exudation of coal gangue slurry and inhibiting the leaching of most heavy metals. This study provides a theoretical foundation for advancing the carbon-negative backfilling techniques and enhancing solid waste resource utilization by mitigating the environmental impact.

根据采煤含钙固体废弃物的矿化特征，提出了有利于固体废弃物与CO2共处置的负碳充填法。然而，关于回填后的固碳能力和潜在的环境影响仍然存在不确定性。本研究在密闭的混合池中通过向矸石浆中注入CO2进行固碳试验，并记录了矸石浆中重金属的浸出情况。结果表明，在初始压力为1mpa时，煤矸石充填浆（CGBS）的吸附能力为11.17 g·kg⁻¹，4种重金属浓度均有所下降。在100°C时，固碳量和效率最高，分别为23.49 g·kg⁻¹和74.42%。CO2混合处理后重金属浸出含量降低，说明碳化过程显著减轻了地下回填过程中CGBS渗漏的环境风险，减少了煤矸石浆的渗水，抑制了大部分重金属的浸出。本研究为推进负碳回填技术，减轻环境影响，提高固体废物资源化利用水平提供了理论基础。

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引用次数: 0

Enhanced viscosification of supercritical CO2 by a new polyolefin copolymer: Insights from solubility and displacement of brine and oil in porous media flow 一种新型聚烯烃共聚物对超临界CO2的增粘作用：从多孔介质流中盐水和油的溶解度和驱替的见解

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-10-01 DOI: 10.1016/j.ijggc.2025.104496

Rongbin Li , Abbas Firoozabadi

Low-cost, low concentration, and environmentally friendly thickeners are of great significance for enhancing carbon dioxide (CO₂) geological storage efficiency and oil recovery. In this study, a new approach (the accumulator dilution method) is proposed to measure solubility and viscosification of a dozen olefin oligomers and copolymers in supercritical CO₂ (scCO₂). It is found that the solubility of oligomers and copolymers with different chain lengths and branching structures in scCO₂ follows specific trends. The unique branching of these molecules differentiates them from those studied in the literature, enabling new insights into effective viscosification at low concentrations. Among the oligomers, the copolymer of 1-octene and 1-dodecene with an average repeat unit of 32 has high performance, enhancing scCO₂ viscosity by approximately 2.5 times at 0.30 wt % at 35 °C and 3500 psi. An important characteristic of the new branched oligomer is high efficiency in both brine and oil displacement in porous media. In CO₂ sequestration, the new copolymer can effectively increase the displacement of brine (at 3500 psi and 90 °C) by 32 % and 22 % in horizontal and vertical displacements, respectively. The crude oil (at 3500 psi and 120 °C) recovery is increased by 33 % and 28 % in the secondary and tertiary processes. The combination of effective viscosification and residual liquid saturation reduction makes the new molecule promising for both applications. Future investigations will focus on exploring alternative branching configurations, such as a copolymer of 1-hexene and 1-tetradecene, to achieve improved performance at even lower concentrations and higher viscosification.

低成本、低浓度、环境友好型增稠剂对提高二氧化碳地质封存效率和提高采收率具有重要意义。在这项研究中，提出了一种新的方法（蓄能器稀释法）来测量十几种烯烃低聚物和共聚物在超临界CO2 （scCO2）中的溶解度和粘度。发现不同链长和分支结构的低聚物和共聚物在scCO2中的溶解度有一定的变化趋势。这些分子的独特分支使它们与文献中研究的分子区别开来，使人们对低浓度下的有效粘化有了新的认识。在低聚物中，平均重复单位为32的1-辛烯和1-十二烯共聚物具有高性能，在35°C和3500 psi下，在0.30 wt %的条件下，scCO2粘度提高了约2.5倍。新型支化低聚物的一个重要特点是在多孔介质中具有较高的驱盐水和驱油效率。在CO2固井中，新型共聚物可以有效地将盐水的水平驱替和垂直驱替（在3500psi和90°C下）分别提高32%和22%。在3500psi和120°C条件下，原油采收率分别提高了33%和28%。有效增粘和降低残余液体饱和度的结合使得新分子在这两种应用中都有前景。未来的研究将集中于探索其他分支构型，如1-己烯和1-十四烯的共聚物，以在更低浓度和更高粘度下实现更好的性能。

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引用次数: 0

Characterisation of a potential CO2 storage complex and first-order containment risk assessment in the Cambay Basin, India 印度Cambay盆地潜在二氧化碳储存综合体的特征和一级遏制风险评估

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-10-01 DOI: 10.1016/j.ijggc.2025.104497

John D.O. Williams , Somali Roy , Nabarun Pal , Paul Bridger , Vikram Vishal , Kaustav Nag

High-level studies have identified potential for subsurface CO₂ storage in India, however lack of detailed technical appraisals aimed at understanding and de-risking the storage resource presents a major challenge to development of CO₂ storage. The onshore Cambay Basin has been identified as a promising target for CO₂ storage given its history of hydrocarbon production and proximity to emission sources. To expedite subsurface characterisation activities in the region, this study uses a 350 km² 3D seismic volume and well dataset to identify a stratigraphic succession suitable for consideration in a CO₂ storage complex. The Middle to Upper Eocene Ankleshwar Formation comprises several potential reservoir and top seal units which may be considered for storage. A high-level assessment of the stratigraphic and structural characteristics of the Ankleshwar Formation is presented, along with a first-order assessment of the principal containment risks and associated uncertainties. Remaining uncertainties are identified along with suggested appraisal activities to reduce uncertainty and further de-risk the storage concept. Whilst there is considerable uncertainty related to the lateral migration of CO₂ within the storage system, the high number of legacy wells in the study area presents the most significant risk to CO₂ containment.

高级别研究已经确定了印度地下二氧化碳储存的潜力，但是缺乏旨在了解和降低储存资源风险的详细技术评估，这对二氧化碳储存的发展构成了重大挑战。鉴于其油气生产历史和靠近排放源，陆上Cambay盆地已被确定为一个有希望的二氧化碳储存目标。为了加快该地区的地下特征活动，该研究使用了350平方公里的三维地震体积和井数据集来确定适合二氧化碳储存复合体的地层演替。中至上始新统踝什瓦尔组由多个潜在储层和顶封单元组成，可考虑储层。本文对Ankleshwar组的地层和构造特征进行了高级评估，并对主要安全壳风险和相关不确定性进行了一级评估。剩余的不确定因素将与建议的评估活动一起确定，以减少不确定性并进一步降低存储概念的风险。虽然二氧化碳在储存系统内的横向运移存在相当大的不确定性，但研究区域的大量遗留井对二氧化碳控制构成了最大的风险。

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引用次数: 0

Hub scale subsurface fluid injection of GCS and SWD wells: Implications on inter-project interferences and regional pressure buildup GCS和SWD井轮毂规模地下流体注入：对项目间干扰和区域压力积累的影响

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-10-01 DOI: 10.1016/j.ijggc.2025.104477

Zhicheng Wang, Seyyed A. Hosseini, Alexander P. Bump

The injection of CO₂ into geological formations can result in pressure interference among different projects. With the increasing number of Geological Carbon Storage (GCS) well applications, new projects will inevitably affect both local and regional pressure distribution. Therefore, it is crucial to model pressure buildup and the associated Area of Review (AoR) before initiating new projects, considering interactions with nearby injection operations. This study employs EASiTool, an analytical tool designed to predict pressure distribution and the associated AoR. We assess basin-scale, multi-site CO₂ injection in the Gulf Coast, focusing on potential pressure interference among GCS projects targeting Eocene, Oligocene, Miocene, and Pliocene-age intervals. A key outcome of this work is a map-view representation of AoRs, particularly their shapes. Rather than developing a definitive model, this study explores the use of EASiTool for rapid assessment, providing quick evaluations of pressure interference risks, identifying key variables controlling bottomhole pressure, and assessing the impact of existing Saltwater Disposal (SWD) wells on GCS projects. Our findings indicate that announced projects could collectively alter pressure distribution across large areas, extending far beyond individual AoRs. Visual analyses reveal that overlapping projects may merge AoRs, significantly expanding the pressure footprint. We evaluate pressure interference both among GCS projects (Class VI) and between SWD (Class II) wells and CO₂ injection wells. Additionally, a sensitivity analysis examines how varying critical pressure build-up thresholds influence AoR size.

向地质地层注入二氧化碳会导致不同项目之间的压力干扰。随着地质储碳井（GCS）应用数量的增加，新项目不可避免地会影响当地和区域的压力分布。因此，在启动新项目之前，考虑与附近注入作业的相互作用，对压力累积和相关的审查区域（AoR）进行建模至关重要。本研究采用EASiTool，一种用于预测压力分布和相关AoR的分析工具。我们评估了墨西哥湾沿岸盆地尺度、多地点的CO2注入，重点关注始新世、渐新世、中新世和上新世时期的GCS项目之间的潜在压力干扰。这项工作的一个关键成果是AoRs的地图视图表示，特别是它们的形状。本研究不是开发一个确定的模型，而是探索EASiTool的快速评估使用，提供压力干扰风险的快速评估，识别控制井底压力的关键变量，并评估现有的盐水处理（SWD）井对GCS项目的影响。我们的研究结果表明，已宣布的项目可以共同改变大面积的压力分布，远远超出单个AoRs。可视化分析显示，重叠的项目可能会合并aor，从而显著扩大压力足迹。我们评估了GCS项目（VI类）和SWD井（II类）与CO2注入井之间的压力干扰。此外，敏感性分析考察了不同的临界压力积累阈值如何影响AoR大小。

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引用次数: 0

Multi-scale dynamic modeling and validation of radial flow fixed bed contactors for post-combustion CO2 capture using bench scale and pilot plant data 基于实验规模和中试工厂数据的径向流固定床接触器燃烧后二氧化碳捕集的多尺度动态建模和验证

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-09-26 DOI: 10.1016/j.ijggc.2025.104481

Ana Flávia Monteiro , David Gribble , Ambal Jayaraman , Gokhan Alptekin , Ryan Hughes , Goutham Kotamreddy , Benjamin Omell , Michael Matuszewski , Debangsu Bhattacharyya

In this work, a multi-scale model of a radial flow fixed bed contactor packed with a carbon sorbent is developed and validated with laboratory-scale and pilot plant scale dynamic data. For the lab scale system, the model results were compared with low, medium and high gas and sweep flowrates, yielding root mean square error (RMSE) of 0.80, 0.63, 0.96 CO₂ mol%, respectively, for the outlet CO₂ concentration profile considering the entire A-D cycle. For the bed outer temperature profile, maximum RMSE was found to be 5.5 °C considering all flowrates and entire A-D cycles. An experimental campaign was developed and applied to a pilot plant at Technology Center Mongstad (TCM), Norway. Approaches were developed for pre-processing of data including consideration of the effect of gas mixing, measurement delay, and determination of cyclic steady-state conditions. Considering profiles during A-D cycles for all test runs, it was found that the maximum RMSE for pressure drop, temperature for the outer section of the bed, temperature for the middle section of the bed, and outlet CO₂ concentration profile remained less than 1.5 mbar, 3.5 °C, 2.8 °C, and 1.3 CO₂ mol%, respectively. The validated model was used to perform sensitivity studies on several key design operating variables for the adsorption-desorption cycle. It was found that the flow rate and concentration of flue gas have dominant nonlinear effects on the breakthrough time while the desorption time was strongly affected by the sweep gas flowrate for the specific sorbent being evaluated in this study.

本文建立了含碳吸附剂的径向流固定床接触器的多尺度模型，并用实验室规模和中试工厂规模的动态数据进行了验证。对于实验室规模的系统，将模型结果与低、中、高气体和扫描流量进行比较，考虑整个A-D循环的出口CO2浓度曲线的均方根误差（RMSE）分别为0.80、0.63、0.96 CO2 mol%。对于床层外部温度分布，考虑到所有流量和整个A-D循环，最大RMSE为5.5°C。在挪威蒙斯塔德技术中心（TCM）的一个试验工厂开展了一项实验活动并加以应用。开发了数据预处理的方法，包括考虑气体混合的影响、测量延迟和循环稳态条件的确定。考虑所有测试运行的A-D循环的分布情况，发现压力降、床外侧温度、床中部温度和出口CO2浓度分布的最大RMSE分别小于1.5 mbar、3.5°C、2.8°C和1.3 CO2 mol%。该验证模型用于对吸附-解吸循环的几个关键设计操作变量进行敏感性研究。研究发现，烟气流量和浓度对突破时间的非线性影响占主导地位，而对特定吸附剂的脱附时间则受扫气流量的强烈影响。

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引用次数: 0

Integrated multi-attribute transform and seismic driven machine learning technique for geomechanical assessment of Cenozoic reservoirs and seal integrity for carbon storage in the Central Gulf of Mexico 综合多属性变换和地震驱动机器学习技术在墨西哥湾中部新生代储层地质力学评价和封存完整性中的应用

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-09-25 DOI: 10.1016/j.ijggc.2025.104480

J.A. Ademilola, Jack C. Pashin

Assessing the geomechanical integrity of seals and storage reservoirs is important prior to carbon dioxide (CO₂) storage because it can determine the safety of storage, containment and stability of a proposed storage, and helps minimize the possibility of CO₂ leakage. This study has integrated simultaneous seismic inversion, multi-attribute transform, and a probabilistic neural network, and uses geophysical well logs to evaluate geomechanical parameters for reservoir and seal integrity assessment of Cenozoic strata. Results indicate that candidate reservoir and seal units identified from wells in the study area possesses greater failure strength than the in-situ stresses and are geomechanically stable. However, there is possibility of tensile failure occurring when the injection get to the mature stage and the effective minimum stress crosses the zero effective normal stress line. Each candidate reservoir storage unit has higher rock strength than its overlying shale layer. The thickness of the caprock units is adequately high to provide effective seal and the thickness of the reservoirs are sufficient to support optimal CO₂ storage resources in the study area. The friction angle of Pliocene–Pleistocene strata is adequately high especially in the eastern part of the study area to minimize the risk of fault reactivation and associated deformation. Additional work can be performed to simulate the response of seals, reservoirs, and geomechanical deformation at variable rates and durations of injection.

在二氧化碳封存之前，评估密封和储层的地质力学完整性非常重要，因为它可以确定封存的安全性、密封和稳定性，并有助于减少二氧化碳泄漏的可能性。本研究将同步地震反演、多属性变换和概率神经网络相结合，利用地球物理测井资料对地质力学参数进行评价，用于新生代地层储层和密封完整性评价。结果表明，研究区的候选储层和密封单元的破坏强度大于地应力，具有良好的地质力学稳定性。然而，当注射到成熟阶段，有效最小应力超过零有效法向应力线时，有可能发生拉伸破坏。每个候选储层存储单元具有比其上覆页岩层更高的岩石强度。盖层单元的厚度足以提供有效的密封，储层的厚度足以支持研究区最佳的CO2储存资源。特别是研究区东部，上新世—更新世地层的摩擦角足够大，以尽量减少断层再活化和相关变形的风险。还可以进行额外的工作来模拟不同速率和注入时间下密封圈、储层和地质力学变形的响应。

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引用次数: 0

Experimentation of a novel sequential moving-bed DAC System 一种新型顺序移动床DAC系统的实验研究

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-09-25 DOI: 10.1016/j.ijggc.2025.104472

Alex Marcil , Marc-Antoine Lacroix , Thierry Hotte-Bélanger , Gabriel Vézina , Martin Brouillette

Solid sorbent Direct Air Capture (DAC) technologies face significant challenges due to the high energy demands associated with adsorption and regeneration phases. Overcoming these limitations is essential to improve the scalability and sustainability of carbon removal solutions. This study investigates the performance of a novel sequential moving-bed (SMB) DAC architecture that utilizes solid sorbent cells circulating through three distinct zones: adsorption, regeneration, and heat exchange, in order to increase system duty cycle and allow for heat recovery between sorption and desorption. The primary objective is to evaluate the energy and capture performance of this configuration in comparison to a conventional fixed-bed system, using the same sorbent under the same operating conditions. Compared to a conventional fixed-bed system, the SMB configuration increased CO₂ uptake by nearly 30% while reducing total energy intensity by more than 35%, to just over 1000 Wh/kgCO₂. These gains are attributed to reduced sorbent working mass, lower pressure drops, and efficient heat recovery. The findings highlight the potential of the SMB approach to enhance the performance and energy efficiency of DAC systems, offering a pathway toward more sustainable and scalable carbon removal solutions.

固体吸附剂直接空气捕获（DAC）技术面临着巨大的挑战，因为与吸附和再生阶段相关的高能量需求。克服这些限制对于提高碳去除解决方案的可扩展性和可持续性至关重要。本研究研究了一种新型连续移动床（SMB） DAC结构的性能，该结构利用固体吸附细胞在三个不同的区域循环：吸附、再生和热交换，以增加系统占空比，并允许在吸附和解吸之间进行热回收。主要目的是评估该配置与传统固定床系统相比的能量和捕获性能，在相同的操作条件下使用相同的吸附剂。与传统的固定床系统相比，SMB配置增加了近30%的二氧化碳吸收量，同时将总能源强度降低了35%以上，仅略高于1000 Wh/kgCO2。这些收益归因于减少吸附剂的工作质量，更低的压力降，和有效的热回收。研究结果强调了SMB方法在提高DAC系统性能和能效方面的潜力，为更可持续和可扩展的碳去除解决方案提供了一条途径。

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引用次数: 0

Invertible Neural Networks based petrophysical inversion for carbon sequestration projects 基于可逆神经网络的固碳项目岩石物理反演

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-09-24 DOI: 10.1016/j.ijggc.2025.104460

Arnab Dhara, Sohini Dasgupta, Mrinal K. Sen

Time-lapse seismic data has shown great promise in accurate monitoring of CO₂ injection sites. There are many sources of uncertainty in derived rock porosity and CO₂ saturation from time lapse seismic data. Variability in noise during data acquisition and noise inherent in seismic data can degrade signal quality and contribute to uncertainty in derived saturation estimates. The process of deriving saturation estimates involves solving an ill-posed, non-unique and highly non-linear seismic petrophysical inversion. Deep learning, particularly utilizing convolutional neural networks (CNNs), has demonstrated potential in addressing such complex and nonlinear seismic inversion challenges. Neural networks frequently find it challenging to offer reliable uncertainty estimates similar to those achieved with Markov Chain Monte Carlo (MCMC) techniques which are widely recognized for their statistical rigor in solving inverse problems. However, MCMC techniques are computationally expensive due to the need for repeated forward model evaluations to adequately sample the posterior distribution. To address this issue, we investigate the use of Invertible Neural Networks (INNs) to predict the full posterior distribution of porosity and CO₂ saturation directly from time lapse data and capture the related uncertainty. INNs provide bijective mapping between data (input) and models (output) and uses a latent vector sampled from a Gaussian distribution to model the uncertainty. Our proposed approach is validated using two seismic vintages and well-logs from the Cranfield reservoir.

延时地震数据在精确监测二氧化碳注入点方面显示出巨大的前景。从时移地震数据中导出的岩石孔隙度和CO2饱和度存在许多不确定性来源。数据采集过程中的噪声变异性和地震数据中固有的噪声会降低信号质量，并导致导出的饱和度估计的不确定性。导出饱和度估计的过程涉及求解不适定、非唯一和高度非线性的地震岩石物理反演。深度学习，特别是利用卷积神经网络（cnn），在解决这些复杂和非线性的地震反演挑战方面已经显示出潜力。神经网络经常发现提供可靠的不确定性估计具有挑战性，类似于用马尔可夫链蒙特卡罗（MCMC）技术实现的不确定性估计，MCMC技术因其在解决反问题方面的统计严谨性而得到广泛认可。然而，MCMC技术的计算成本很高，因为需要重复的正演模型评估来充分采样后验分布。为了解决这个问题，我们研究了使用可逆神经网络（INNs）直接从时间推移数据中预测孔隙度和二氧化碳饱和度的完整后验分布，并捕获相关的不确定性。INNs提供数据（输入）和模型（输出）之间的双向映射，并使用从高斯分布中采样的潜在向量来建模不确定性。我们提出的方法通过两个地震年份和Cranfield油藏的测井进行了验证。

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引用次数: 0

The financial implications of injectivity risk in compartmentalized storage formations for geologic carbon sequestration 地质碳封存区隔储层注入风险的财务影响

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-09-20 DOI: 10.1016/j.ijggc.2025.104463

Christopher Deranian , Sahar Bakhshian , Susan D. Hovorka

Maintaining injectivity over the planned duration is a major driver of risk in CO

_{2}

storage projects. Current insurance considerations are largely focused on leakage and well remediation, while operational issues from past carbon storage projects have shown injectivity issues due to unanticipated formation compartmentalization is a real risk. The financial penalty due to the disruption of injection operations is large for a site operator. This study explores the effect of storage compartment size and geologic boundary condition on injectivity, and the subsequent financial implications. Risk profiles of injectivity are generated through reservoir simulations constrained by statistics from a CO

_{2}

storage prospect on the Gulf Coast. A financial tool is built to understand the impact on project value when an injectivity issue occurs and an offset well needs to be drilled. We observe that even in relatively closed boundary conditions, pressure arising from the CO

_{2}

injection can dissipate in the formation to allow injection over the project life. The economic feasibility of a storage project that does face an injectivity issue depends on the year of the injection issue occurrence. This study helps understand the injectivity risk, project contingency, and the financial feasibility of mitigation options required to establish robust assurance against this risk.

在计划持续时间内保持注入能力是二氧化碳封存项目风险的主要驱动因素。目前的保险主要集中在泄漏和油井修复上，而过去碳储存项目的运营问题表明，由于意外的地层分隔导致的注入性问题是真正的风险。对于现场作业者来说，由于注入作业中断而造成的经济损失是巨大的。本研究探讨了储层尺寸和地质边界条件对注入能力的影响，以及随后的经济影响。注入风险概况是通过油藏模拟得出的，受墨西哥湾沿岸二氧化碳封存前景统计数据的约束。当发生注入问题，需要钻一口邻井时，建立了一个财务工具来了解对项目价值的影响。我们观察到，即使在相对封闭的边界条件下，二氧化碳注入产生的压力也会在地层中消散，从而在整个项目生命周期内允许注入。面临注入问题的储能项目的经济可行性取决于注入问题发生的年份。本研究有助于了解注入性风险、项目偶然性以及建立针对该风险的可靠保证所需的缓解方案的财务可行性。

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引用次数: 0

De-risking overburden and caprocks for CO2 storage using machine-learning seismic fault attributes 利用机器学习地震断层属性降低二氧化碳储存覆盖层和盖层的风险

IF 5.2 3区工程技术 Q2 ENERGY & FUELS

International Journal of Greenhouse Gas Control

Pub Date : 2025-09-18 DOI: 10.1016/j.ijggc.2025.104471

Julián L. Gómez , Ane Elisabet Lothe

Fault and fracture geometries, densities, and distributions play a critical role in assessing and mitigating risks associated with potential CO₂ storage sites in sedimentary basins, particularly saline aquifers. To enhance fault detection in 3D seismic data, we have developed, trained, and deployed a lightweight machine learning segmentation algorithm. This deep learning model, trained on synthetic seismic data, generates fault scores—pixel-scale classifications ranging from 0 to 1—where higher values indicate a greater likelihood of structural discontinuities. These fault scores are used to derive a fault density attribute, which summarizes the expected fault network distribution along seismic sections. Our workflow is computationally efficient and provides interpreters with valuable insight into the lateral and vertical distribution of faults. We apply this methodology to a 3D seismic survey of the Smeaheia area, Norway, covering the N-S trending Vette Fault and sections of the Øygarden Fault Complex (ØFC). Fault mapping was conducted at the reservoir level, as well as in the caprock and overburden. The detected fault patterns at the top of the Draupne Formation, the presumed caprock unit in the region, and fault pattern at the Top Cromer Knoll Group, align well with manual interpretations. Additionally, in the footwall of the deep-crustal ØFC, we identify faults extending to the seafloor, suggesting that a non-negligible fault density may be present within the caprock. Our results are compared with 3D variance and 3D semblance seismic attributes, further validating the efficacy of our approach.

断层和裂缝的几何形状、密度和分布在评估和减轻沉积盆地（特别是含盐含水层）潜在CO 2储存地点相关风险方面发挥着关键作用。为了增强三维地震数据的故障检测，我们开发、训练并部署了一种轻量级的机器学习分割算法。这种深度学习模型在合成地震数据上进行训练，生成断层评分——像素级分类，范围从0到1，其中越高的值表明结构不连续的可能性越大。这些断层分数用于导出断层密度属性，该属性总结了沿地震剖面的预期断层网分布。我们的工作流程计算效率高，为解释人员提供了对断层横向和垂直分布的宝贵见解。我们将这种方法应用到挪威Smeaheia地区的三维地震调查中，该地区覆盖了N-S走向的Vette断层和Øygarden断层复合体的部分（ØFC）。在储层以及盖层和上覆层进行了断层测绘。探测到的Draupne组（该地区假定的盖层单元）顶部的断层模式和top Cromer Knoll组的断层模式与人工解释的结果吻合得很好。此外，在深部地壳ØFC下盘，我们发现了延伸到海底的断层，这表明盖层内可能存在不可忽略的断层密度。我们的结果与三维方差和三维相似地震属性进行了比较，进一步验证了我们方法的有效性。

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