Review of progress and implication of machine learning in geological carbon dioxide storage

Rapid industrialization and urbanization in the 20th century have led to increasing volumes of carbon dioxide being released into the atmosphere[...]

Carbon dioxide geological storage is one of the important means to mitigate the greenhouse effect and curb global warming. The key to carbon dioxide (CO2) geological storage is to select a suitable storage site. Using the geological analysis method and analytic hierarchy process (AHP)–fuzzy comprehensive evaluation method, combining the qualitative analysis of geological conditions with the quantitative calculation of site parameters, this study determines a site target area suitable for CO2 geological storage in Tianjin. First, the regional crustal stability of Tianjin is discussed, and the characteristics of regional gravity field anomaly, regional crustal thickness, and regional aeromagnetic characteristics are comprehensively analyzed. The site is focused on Banqiao sag, a class ⅳ tectonic unit in Bohai Bay Basin. Second, aiming at the storability, safety, and economy of the site, the expert investigation method is used to construct the target area evaluation index system, including four primary indexes and ten secondary indexes. The weight of each index is determined using the analytic hierarchy process. A two-level fuzzy comprehensive evaluation mathematical model is constructed. The suitability of CO2 geological storage in three sites (site A, site B, and site C) in Banqiao sag is evaluated. The results are as follows: the comprehensive membership of site A, site B, and site C is 0.8629, 0.3926 and 0.1750, respectively. The comprehensive membership of site A is the largest. The evaluation results show that the preferred target area of Tianjin local carbon dioxide geological storage site is located in ‘site A’ near Dazhangtuo fault in Banqiao sag, Huanghua depression, Bohai Bay Basin (with an area of about 5 km2). In this study, a suitable target area is delineated for the local CO2 geological storage site in Tianjin, which can be used as an advantageous location for CO2 geological storage. The conclusion has a positive response to the problem of CO2 emission reduction in Tianjin.

Liability issues are a major concern for final disposal of radioactive waste (RW) and for geological storage of carbon dioxide (CO2). We develop a list of overarching questions that drive liability and present a discussion of where managing liability for geological CO2 storage and RW disposal is fundamentally different and where it is similar. Governments have been trying to manage high-level RW from civilian reactors for over 40 years and there are ample lessons in the interplay between technology, policy, politics and society that are relevant for both future nuclear energy and geological CO2 storage projects. We examine the history of managing liability for RW using case studies on Germany, France, Finland and the USA to better understand how liability for RW is currently structured. We compare this to potential liabilities for geological CO2 storage and outline current proposals for managing liability in the US and European Union. From this, we develop ‘lessons learned’ from past management of RW that could help to both structure liability and ultimately deploy future RW and geological CO2 storage projects. We conclude that while establishment of a legal framework is important for future development of nuclear energy and geological CO2 storage, it is insufficient to guarantee deployment. Rather, legal liability is embedded within a larger socio-political context and addressing these broader concerns is vital for future RW disposal and geological CO2 storage deployment.

Given a scarcity of commercial-scale carbon capture and storage (CCS) projects, there is a great deal of uncertainty in the risks, liability, and their cost implications for geologic storage of carbon dioxide (CO2). The probabilities of leakage and the risk of induced seismicity could be remote, but the volume of geologic CO2 storage (GCS) projected to be necessary to have a significant impact on increasing CO2 concentrations in the atmosphere is far greater than the volumes of CO2 injected thus far. National-level estimates of the technically accessible CO2 storage resource (TASR) onshore in the United States are on the order of thousands of gigatons of CO2 storage capacity, but such estimates generally assume away any pressure management issues. Pressure buildup in the storage reservoir is expected to be a primary source of risk associated with CO2 storage, and only a fraction of the theoretical TASR could be available unless the storage operator extracts the saltwater brines or other formation fluids that are already present in the geologic pore space targeted for CO2 storage. Institutions, legislation, and processes to manage the risk, liability, and economic issues with CO2 storage in the United States are beginning to emerge, but will need to progress further in order to allow a commercial-scale CO2 storage industry to develop in the country. The combination of economic tradeoffs, property rights definitions, liability issues, and risk considerations suggests that CO2 storage offshore of the United States may be more feasible than onshore, especially during the current (early) stages of industry development.

Implications of Surface Seepage on the Effectiveness of Geologic Storage of Carbon Dioxide as a Climate Change Mitigation Strategy

Analysis of the effect of formation dip angle and injection pressure on the injectivity and migration of CO2 during storage

The geological storage of carbon dioxide (CO2) represents a promising strategy for mitigating climate change by securely sequestering CO2 emissions. This review article aims to provide a comprehensive overview of the current state of research and development in the field of geological carbon dioxide (CO2) sequestration. We systematically examined a wide range of recent literature, focusing on advancements in numerical simulations, experimental studies, risk assessments, and monitoring techniques related to CO2 sequestration. Literature was selected based on relevance, recency, and contribution to the understanding of key challenges and solutions in CO2 storage, with sources spanning peer‐reviewed journals, conference proceedings, and significant technical reports. Our review highlights several key themes: the integration of machine learning and advanced numerical models in predicting CO2 behavior in subsurface formations; innovative experimental approaches to understanding the physicochemical interactions between CO2, brine, and geological substrates; and the development of robust risk assessment frameworks to address potential leakage and induced seismicity. We also explore recent advancements in monitoring technologies, emphasizing their critical role in ensuring the long‐term integrity and effectiveness of CO2 storage sites. Overall, this review synthesizes the latest findings and identifies gaps in current knowledge, providing a roadmap for future research directions. Our aim is to enhance the understanding of CO2 sequestration processes, support the development of safer and more efficient storage methods, and contribute to the global effort in mitigating climate change through effective carbon management strategies. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

Robust machine learning models of carbon dioxide trapping indexes at geological storage sites

Geological storage of carbon dioxide represents a viable solution to reduce the greenhouse gases in the atmosphere. Romania has initiatives to build a large-scale integrated CO2 capture and storage demonstration project and find suitable on-shore and off-shore CO2 storage locations. Numerical simulators are essential tools helping the design process. These simulators are required to be capable to represent the complex thermo-hydro-mechanical-chemical and biological phenomena accompanying the geological CO2 storage such as, multi-phase flow, compositional effects due to dissolution of CO2 into the brine, non-isothermal effects due to cold CO2 injection, geomechanical effects, mineralization at the reservoir-scale. These processes can be simulated accurately and efficiently with DuMux (www.dumux.org), a free- and open-source simulator. This article presents and reviews briefly these mathematical and numerical models.

Geological storage of carbon dioxide (CO2) is an efficient and safe long-term storage of this greenhouse-contributing gas. When applied to shales, CO2 injection can enhance shale gas recovery, as well as contribute to CO2 abatement by storing significant amounts of CO2 into its organic porosity and clay content. Shales are classified as unconventional reservoirs and the CO2 storage into this lithology has peculiar characteristics: storage through adsorption into the surface area microporous organic particles and clay minerals. Therefore, understanding shale's porosity and associated gas sorption patterns requires a detailed characterization of its organic and mineralogical composition. Parameters such as kerogen quantity, type, and maturity, are controlling factors of organic porosity and of CO2 adsorption and CH4 desorption processes, and consequently drive CO2 storage capacity and hydrocarbon production of organic-rich shales. This research aims to reduce uncertainties regarding CO2 storage in shales. It tests the hypothesis that the Irati Formation at Paran Basin, can be a feasible target for both CCUS and shale gas production in Brazil, due to its high organic content, large occurrence and proximity to major CO2 emitting sources within the country. Due to heterogeneity of Irati shales -which are attributed to the basin's complex thermal history, characterizing its organic and inorganic aspects in a regional scale is a challenging task. In this study, a combined analysis of organic geochemistry, petrology, mineralogy, and gas sorption isotherms is applied to Irati shale's characterization. Additionally, the interaction between the organic and inorganic component with CO2 as well as rock-fluid mechanisms in shales are investigated. The result is determining Irati shale's storage capacity and overall geological feasibility as a CO2 reservoir and as an unconventional hydrocarbon source-rock. Besides the geological aspects, the thesis brings a multidisciplinary approach towards CO2 storage prospects in Brazil. It presents a general overview of the potential for CCUS in the country and identifies the main legal and regulatory barriers to large-scale CCUS deployment.

Ensuring caprock integrity is essential for maintaining long-term containment security in geological carbon dioxide (CO2) storage. Fracture networks of caprocks act as leakage pathways for stored CO2. Interactions between brine and CO2 trigger salt precipitation within fractures, potentially sealing fractures to restrict further leakage. The mechanisms governing salt precipitation in structurally diverse fractures remain poorly understood at the pore-scale. We employed microfluidics to examine the effects of the fracture geometry, CO2 phase, and brine composition on salt precipitation, aggregation, and migration. The fracture geometry influences salt dynamics, with salt coverage 1.6- and 3.3-fold that of the unfractured model in discrete and interconnected models, respectively. The brine composition alters salt aggregation behavior: CaCl2 brine yields larger, more stable precipitated salt, resulting in up to ∼51% greater salt coverage than NaCl. The CO2 phase exerts dominant control-supercritical carbon dioxide (scCO2) displacement enhances NaCl precipitation by ∼683% compared with gas-phase CO2, due to improved brine film retention and evaporation. The brine film reaccumulation mechanism under scCO2 displacement further suppresses salt migration, sustaining salt aggregation in interconnected fractures. Our findings offer fundamental insights into salt sealing and migration in multiscale porous media, with vital influence on leakage risk assessment and injectivity control in geological CO2 storage.

Overview and current issues in geological storage of carbon dioxide

Permanent geological carbon dioxide (CO2) storage is a promising pathway to mitigate the greenhouse gas levels. Recently, seasonal underground storage of hydrogen (H2) has become of interest to fulfill energy demand uninterruptedly by periodic renewable energy supply. Caprock formations should be studied for both types of the storage to inhibit the leakage of buoyancy-driven CO2 and H2. Cores of two caprock representatives – Eau Claire and Maquoketa groups – are collected from CO2 storage sites in Illinois Basin and tested for the breakthrough pressure with liquid CO2. The direct method is time-consuming due to the necessity of achieving full saturation and stepwise injection, such that the indirect method is often utilized to estimate the breakthrough pressure via the capillary pressure-saturation curve. The comparison between the two methods indicates that the direct method provides a higher value of the breakthrough pressure. The H2 breakthrough pressure of a given caprock is estimated by the indirect method to be approximately 2.4 times higher than that of CO2. However, we expect that the H2 breakthrough in very tight rock, like Maquoketa Shale, would occur through different leakage scenarios compared to CO2 breakthrough, suggesting that direct measurements under representative in-situ conditions should be conducted. INTRODUCTION Increased greenhouse gas levels in the atmosphere have a direct impact on climate change. Geological carbon dioxide (CO2) storage is one of the essential tools for mitigating its atmospheric level by storing CO2 captured at coal- or gas-fired power stations and industrial facilities in deep reservoirs (at depths below 800 m; IPCC, 2005). Hydrogen (H2) has higher energy content per unit mass compared to other gases such as methane and natural gas (Heinemann et al., 2018), such that converting surplus energy into H2 and storing it in a porous reservoir is a promising way to fulfill energy demand uninterruptedly by periodic renewable supply. The main goal of CO2 storage is its removal from the atmosphere, such that the withdrawal stage is not required and CO2 must remain in the subsurface for thousands of years. On the other hand, hydrogen is stored seasonally (about one full injection and production cycle per year). However, the most abundant geological formations for CO2 storage are similar to those for H2 storage: a porous reservoir saturated with saline water and overlying low permeable caprock.

The Donbass has the largest potential in Europe for the geological storage of carbon dioxide (CO2), which needs to be implemented on a large scale to mitigate the effects of global climate change. The environmental risks of CO2 leaks in the processes of capturing, transporting and geological storage of CO2 at the enterprises of the energy and industrial sectors of the economy of the eastern regions of Ukraine are analyzed. Geographic information systems have been created in these areas with layers of geological structures suitable for long-term storage of supercritical CO2. The impact of CO2 leaks from geological repositories on the environment is estimated. In the proposed CO2 storage areas, some CO2 leakagescenarios were analyzed due to the filtering of CO2 fluids through porous rock layers, through abandoned wells and tectonic faults of the Donbas geological structures. The potential effects of CO2 leakage on groundwater quality in the region are also assessed.

This paper presents a machine learning (ML) model designed to speed up the appraisal of geologic CO2 storage sites by predicting the effectiveness in trapping and accommodating CO2 in saline aquifers. Considering the urgency of de-risking as much geologic CO2 storage resources as possible to help with CO2 emission reduction Paris’ goal, ML-based reservoir modelling has been documented as proper tool when a faster, good approximate, and less expensive approach is needed to surrogate multiple assessments of storage sites traditionally performed by long-timeframe and multi-stage geologic CO2 storage numerical modelling approach. In this paper, a case study is presented. It consisted of a dataset comprised of six geologic aquifer parameters (CO2 residual saturation, horizontal permeability, vertical to horizontal permeability ratio, porosity, brine salinity, and CO2 flow rate) and elapsed time as input data, and as output data the CO2 trapping mechanism indices (Solubility Trapping Index, Residual Trapping Index, and Structural Trapping Index) along with the dynamic storage capacity (CO2 injected volume). Such dataset was used to train and test the artificial neural network (ANN) model. The dataset was generated from thousands of post-processed numerical realizations at several injection periods by applying design of experiment using a synthetic aquifer model derived from the Bunter Sandstone Closure 36 aquifer numerical model, from the Southern North Sea. The ANN architecture designed in Python consisted of 3 hidden layers and 40 nodes and its performance was assessed using the coefficient of determination (R2) and root mean squared error (RMSE). The ANN performance showed accuracies (R2) for training and testing with 96% and 95% of precision respectively. Practical application of the ANN model was successfully implemented to CO2 storage aquifer sites selected from CO2Stored® database which lacking numerical models (Bunter Closure 3, 9, 35, and 40), obtaining at the end of 100-years injection case a Structural, Residual, and Solubility Trapping Index averaging 83%, 11%, and 6% respectively, with low variation coefficient indicating that trapping indices were predicted properly because aquifers selected for ANN model application have similar structures (dome-like shape) and reservoir properties. In addition, CO2 injected volume predictions for 100-years injection case were ranging from 397 to 456 million ton (Mt) totalling 2.1 giga ton (Gt) of potential storage capacity which represents 70% of total theoretical volumetric capacity. These results show the significant impact to accelerate geologic CO2 storage sites assessment by implementing ML-based modelling to preliminary de-risking groups of saline aquifers and reasonably consider them technically feasible CO2 storage sites in UK.