Risks and uncertainties in carbon capture, transport, and storage projects: A comprehensive review

Mahjour, Seyed Kourosh; Faroughi, Salah A.

doi:10.1016/j.jgsce.2023.205117

Cited by 27 publications

(9 citation statements)

References 265 publications

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“…By incorporating maximum amplitude values into the seismic vulnerability index, it becomes possible to identify areas where structures face greater risk. This prompts the implementation of stricter building codes and retrofitting measures (Alkan & Akkaya, 2023;Mahjour & Faroughi, 2023).…”

Section: Vulnerability Index Of Seismic Resultsmentioning

confidence: 99%

“…Furthermore, it explores the collective influence of these parameters on various aspects of seismic risk assessment, including infrastructure resilience and geothermal operations. The multifaceted nature of this relationship is thoroughly examined and analyzed, providing valuable insights and knowledge in these areas (Gori et al, 2023;Mahjour & Faroughi, 2023).…”

Section: Discussionmentioning

confidence: 99%

“…The inclusion of these parameters renders the vulnerability index a comprehensive tool, which takes into account not only the seismicity of the region but also the specific characteristics of structures and the geological formations on which they are situated. This integrated approach empowers authorities and engineers to allocate resources efficiently by prioritizing areas with heightened vulnerabilities, and implement targeted interventions to enhance the resilience of critical infrastructure and communities (Gori et al, 2023;Mahjour & Faroughi, 2023).…”

Section: Figure 7 Vulnerability Index Distribution Mapmentioning

confidence: 99%

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Analysis of the Effect of Local Magnitude on Peak Ground Acceleration and Seismic Vulnerability Index for Geothermal Field Monitoring Using Microearthquake

Utama,

Indriani,

Garini

2023

jppipa, pendidikan ipa, fisika, biologi, kimia

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Intensive exploitation of geothermal injection and production can trigger microearthquakes which it signals come from dynamic fractures. The purpose of this study is to decide the impact of local magnitude on mitigation in geothermal fields based on soil acceleration and vulnerability of seismic in geothermal fields. This study uses seismic wave recording data and the geology of the research area. It is focable on calculating local magnitude, ground acceleration and seismic susceptibility index to earthquakes based on ground acceleration and seismic susceptibility index in geothermal fields. The maximum amplitude value represent that the medium classification class (3<A0<6) is associated with a moderate degree of deformation. Natural frequency value are found with a moderate classification (4<f0<10) around the area of injection wells and production wells, indicating that the research area has a moderate level of soil hardness structure. The peak ground acceleration in the study area is classified as moderate (0.25<PGA<0.7) which means that the area has a moderate level of risk. Vulnerability of seismic in the study area is included in the low classification (Kg<10). The local magnitude impact on soil acceleration and vulnerability of seismic in this study has a moderate risk and can be categorised as safe. In the future, this research serves as a basis for proper decision-making in geothermal energy operations, monitoring, and infrastructure development

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Section: Vulnerability Index Of Seismic Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Figure 7 Vulnerability Index Distribution Mapmentioning

confidence: 99%

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Analysis of the Effect of Local Magnitude on Peak Ground Acceleration and Seismic Vulnerability Index for Geothermal Field Monitoring Using Microearthquake

Utama,

Indriani,

Garini

2023

jppipa, pendidikan ipa, fisika, biologi, kimia

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“…Therefore, it is necessary to further update and refine the existing CCUS-EOR reservoir screening criteria to develop a set of criteria that align with the specific characteristics of reservoirs in China. Furthermore, the formulation of a complete set of CCUS-EOR screening criteria should ideally consider both technical and non-technical indices [23]. Technical indices include indicators of CO 2 capture capacity, CO 2 -EOR capability, and CO 2 storage capacity.…”

Section: Introductionmentioning

confidence: 99%

Research and Application of Carbon Capture, Utilization, and Storage–Enhanced Oil Recovery Reservoir Screening Criteria and Method for Continental Reservoirs in China

Cao,

Gao,

Liu

et al. 2024

Energies

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CCUS-EOR is a crucial technology for reducing carbon emissions and enhancing reservoir recovery. It enables the achievement of dual objectives: improving economic efficiency and protecting the environment. To explore a set of CCUS-EOR reservoir screening criteria suitable for continental reservoirs in China, this study investigated and compared the CCUS-EOR reservoir screening criteria outside and in China, sorted out the main reservoir parameters that affect CO2 flooding, and optimized the indices and scope of CCUS-EOR reservoir screening criteria in China. The weights of parameters with respect to their influences on CCUS-EOR were determined through principal component analysis. The results show that there are 14 key parameters affecting CO2 flooding, which can be categorized into four levels. For the first level, the crude oil-CO2 miscibility index holds the greatest weight of 0.479. It encompasses seven parameters: initial formation pressure, current formation pressure, temperature, depth, C2–C15 molar content, residual oil saturation, and minimum miscibility pressure. The second level consists of the crude oil mobility index, which has a weight of 0.249. This index includes four parameters: porosity, permeability, density, and viscosity. The third level pertains to the index of reservoir tectonic characteristics, with a weight of 0.141. It comprises two parameters: permeability variation coefficient and average effective thickness. Lastly, the fourth level focuses on the index of reservoir property change, with a weight of 0.131, which solely considers the pressure maintenance level. Based on the CCUS-EOR reservoir screening criteria and index weights established in this study, comprehensive scores for CCUS-EOR were calculated for six blocks in China. Among these, five blocks are deemed suitable for CCUS-EOR. Based on the comprehensive scoring results, a planning for field application of CCUS-EOR is proposed. The study provides a rational method to evaluate the CCUS-EOR reservoir screening and field application in continental reservoirs in China.

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“…The evaluation and quantification of geological uncertainties have become increasingly crucial in industries dedicated to decarbonization [2,9,10]. The geological structure of a storage reservoir, coupled with variations in its petrophysical characteristics, constitutes the primary origin of geological uncertainty [11]. Traditional approaches to assessing geological uncertainty involve the generation of numerous potential GRs and the analysis of statistical metrics derived from ensemble objective functions [1].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning

Mahjour,

Badhan,

Faroughi

2024

Energies

Self Cite

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Evaluating uncertainty in CO2 injection projections often requires numerous high-resolution geological realizations (GRs) which, although effective, are computationally demanding. This study proposes the use of representative geological realizations (RGRs) as an efficient approach to capture the uncertainty range of the full set while reducing computational costs. A predetermined number of RGRs is selected using an integrated unsupervised machine learning (UML) framework, which includes Euclidean distance measurement, multidimensional scaling (MDS), and a deterministic K-means (DK-means) clustering algorithm. In the context of the intricate 3D aquifer CO2 storage model, PUNQ-S3, these algorithms are utilized. The UML methodology selects five RGRs from a pool of 25 possibilities (20% of the total), taking into account the reservoir quality index (RQI) as a static parameter of the reservoir. To determine the credibility of these RGRs, their simulation results are scrutinized through the application of the Kolmogorov–Smirnov (KS) test, which analyzes the distribution of the output. In this assessment, 40 CO2 injection wells cover the entire reservoir alongside the full set. The end-point simulation results indicate that the CO2 structural, residual, and solubility trapping within the RGRs and full set follow the same distribution. Simulating five RGRs alongside the full set of 25 GRs over 200 years, involving 10 years of CO2 injection, reveals consistently similar trapping distribution patterns, with an average value of Dmax of 0.21 remaining lower than Dcritical (0.66). Using this methodology, computational expenses related to scenario testing and development planning for CO2 storage reservoirs in the presence of geological uncertainties can be substantially reduced.

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Risks and uncertainties in carbon capture, transport, and storage projects: A comprehensive review

Cited by 27 publications

References 265 publications

Analysis of the Effect of Local Magnitude on Peak Ground Acceleration and Seismic Vulnerability Index for Geothermal Field Monitoring Using Microearthquake

Analysis of the Effect of Local Magnitude on Peak Ground Acceleration and Seismic Vulnerability Index for Geothermal Field Monitoring Using Microearthquake

Research and Application of Carbon Capture, Utilization, and Storage–Enhanced Oil Recovery Reservoir Screening Criteria and Method for Continental Reservoirs in China

Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning

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