Carbon Capture, Utilization, And Storage Research Articles

Optimization of hollow fiber membrane contactor system for CO2 mineralization using seawater brine: Comparative analysis of performance and transport mechanisms

Carbon mineralization is a promising approach for carbon capture, utilization, and storage (CCUS) but still faces technical and economic challenges. This study reports on CO2 mineralization using various hollow fiber membrane contactors (HFMCs) to optimize the system and understand the mass transport mechanism. We conducted a quantitative comparative assessment through theoretical and experimental approaches to evaluate the performance of three HFMC types with different morphological and chemical characteristics at various gas and liquid velocities. Results showed that the in-house developed highly porous hollow fiber (HF) membrane exhibited superior CO2 capture efficiency compared to commercial membranes. In contrast to other HFMCs showing a sharp decline in CO2 flux due to internal fouling caused by pore wetting and external fouling, the highly porous HF membrane with surface modification maintained stable performance during continuous operation due to its superhydrophobicity and surface roughness. The HF membrane also achieved the highest overall mass transfer coefficients, closely matching the theoretical non-wetted mode due to negligible partial wetting. We expect that this study will provide insights into optimizing HFMCs for enhanced carbon mineralization efficiency.

A numerical feasibility study of CO2 foam for carbon utilization and storage in a depleted, high salinity, carbonate oil reservoir

Carbon Capture, Utilization, and Storage (CCUS) offers a viable solution to reduce the carbon footprint in the petroleum industry, and foam injection presents a promising method to achieve this while simultaneously increasing oil recovery. In this work, we studied the feasibility of CO2 foam for co-optimizing enhanced oil recovery and CO2 storage in a high-salinity carbonate formation. The simulated hydrodynamic model is a depleted formation containing 30% residual oil, with three mechanisms for CO2 storage: solubility, residual, and mineralization trapping mechanisms. The results showed that after 20 years, oil recovery during foam injection was 2.7 times higher than CO2 injection, and the CO2 stored during foam flooding was 38% higher than CO2 injection. Notably, foam injection also increased CO2 storage capacity by 2.6 times, indicating the potential to store around 2 gigatons of CO2 in the simulated model. This was attributed to the ability of foam to significantly reduce gas mobility and thus form isolated bubbles through its Jamin effect. Residual trapping was the dominant trapping mechanism, contributing to over 70% of the total CO2 trapped, attributed to the reduction in the dissolution of CO2 in brine due to the high salinity of the aqueous medium. CO2 mineralization was also studied, showing the least trapping efficiency and the dissolution trend of all the carbonate minerals. This study illustrates a novel CO2 utilization and storage technique in which CO2 is concurrently sequestered while enhancing oil recovery in a depleted oil reservoir by injecting CO2 as foam. The relevance of this study lies in its potential to provide a dual benefit of reducing greenhouse gas emissions and boosting oil production, offering a sustainable approach for the petroleum industry.

Global feature capture and spatially-aware neural networks for predicting CO2-flooding performance in heterogeneous low-permeable reservoirs

CO2-flooding can enhance crude oil recovery rates by reducing the viscosity of crude oil, improving the mobility ratio between crude oil and water, and leveraging the swelling effects of crude oil components. Furthermore, it facilitates the sequestration of greenhouse gases, leading to the realization of carbon capture, utilization, and storage (CCUS), which holds significant strategic importance for mitigating climate change, safeguarding ecological environments, and achieving sustainable development. Consequently, predicting CO2-flooding performance in heterogeneous low-permeability reservoirs holds crucial significance in sustainable energy production. However, the drawbacks of numerical simulation techniques, such as extensive computational resource consumption and prolonged simulation durations, have prompted extensive research into the utilization of artificial intelligence technologies. Prevalent approaches often treat the problem as a time series issue, which proves inadequate for reservoirs lacking historical production data. Furthermore, this methodology is unable to fully exploit the complex implicit relationships between various factors and the prediction target. Our study proposes a novel method for predicting the performance, which stands apart from previous approaches by not treating the problem as a time series issue, eliminating the need for historical production data for each prediction, and can predict various production variables such as gas production, oil production, water production, etc. in a universal manner. We combine enhanced MultiScale Non-local Neural Networks with ConvNet to handle sparse well network matrices with injection-production parameters. Additionally, we employ MultiScale convolutional networks with spatial attention mechanism to address formation permeability fields with spatial distribution features. Experimental results demonstrate the superiority of our approach in accuracy, achieving a prediction accuracy of over 97%. This research provides an innovative and flexible method, making significant contributions to the intelligentization and sustainable development of the petroleum industry, aligned with global efforts to both reduce carbon emissions and neutralize the existing ones.

A generalized adsorption model of CO2-CH4 in shale based on the improved Langmuir model

CO2 enhanced shale gas recovery (CO2-ESGR), as one of the most promising carbon capture, utilization and storage (CCUS) technologies, can both improve the shale gas production for clean energy supply and mitigate greenhouse gas emissions for the goal of carbon neutrality. The adsorption characteristics of CO2 and CH4 in shale play a key role in the reserve assessment of shale gas and the implementation of CO2-ESGR. The problem of accurate prediction of the adsorption and competitive adsorption characteristics of CO2 and CH4 in shale is still one of the main challenges for CO2-ESGR. To bridge the gap, this work developed a generalized prediction model for the adsorption properties of CH4, CO2, and their mixed gas in shale by improving the Langmuir model, covering a large range of temperature, pressure, and total organic carbon content (TOC). The mathematical models for the key parameters of the Langmuir model, the saturated adsorption capacity Q0 and Langmuir pressure PL, were built for the single-component gas based on their functional relationship with temperature and TOC, and for the mixed gas based on their relationship with Q0 and PL of the single-component gas and CO2 content. Then an improved Langmuir model for the adsorption properties of CO2-CH4 in shale was established. The accuracy of the improved model was verified with a relative deviation below 5 % in a large range of temperature (303–363 K), pressure (0–15 MPa) and TOC (1.06 %-3.83 %) by comparing the calculated adsorption with the experimental data. This generalized adsorption model not only ensures the prediction accuracy of CO2-CH4 adsorption characteristics in shale but also expands its application convenience in a large range of temperatures, pressures and TOC, providing a certain theoretical basis for CO2-ESGR technology.

Safety-driven design of carbon capture utilization and storage (CCUS) supply chains: A multi-objective optimization approach

Carbon capture, utilization, and storage supply chains (CCUS) play a pivotal role in achieving sustainability targets but necessitate meticulous risk identification and mitigation measures. Traditional safety assessments often occur post-design, constraining proactive risk management efforts. Hence, there is a pressing need to optimize safety performance during the design stages. To address this challenge, a framework for evaluating and optimizing CCUS supply chain safety performance using inherent safety index system (ISI) is introduced. Recognizing the trade-offs between total cost, environmental impact reduction, and risk mitigation, our approach considers multi-objective optimization to concurrently address these sustainability objectives and generate a Pareto set of solutions. Utilizing the augmented ε-constraint method, we applied this framework to optimize CCUS networks and develop sustainable designs across three key objectives. The method was applied to a CCUS system that includes various CO2 utilization pathways to minimize the total annual cost, CO2 emissions, and safety risks. The resulting Pareto surface illustrates unique network configurations, each representing a distinct trade-off scenario. Through a case study, we optimized a CCUS network to achieve economic, environmental, and safety objectives. The most economically viable design, with a total annual cost of $97 million and a 40 % net carbon reduction, prioritizes CO2 utilization for value-added products, while limiting CO2 sequestration. Conversely, safety-focused designs shift utilization towards safer routes, including CO2 sequestration and algae production. The proposed framework offers a systematic approach to developing sustainable CCUS supply chain designs, balancing economic viability, environmental sustainability, and safety.

Potential assessment and development obstacle analysis of CCUS layout in China: A combined interpretive model based on GIS-DEMATEL-ISM

Although carbon capture, utilization, and storage (CCUS) has enormous emission reduction potential and application prospects, it still faces many obstacles and challenges in the actual deployment and promotion process. This study aims to evaluate the spatial suitability of the CCUS layout comprehensively and deeply analyze key development obstacles to provide a scientific basis for the promotion and layout of CCUS. Therefore, this article constructs a combination of Geographic Information Systems (GIS), Decision-making trial and evaluation laboratory (DEMATEL) method, and Interpretive structure model (ISM). Firstly, a comprehensive evaluation is conducted on the suitability of the CCUS layout in China based on GIS technology, identifying high-potential areas. The results indicate that when the threshold is 80% of the highest score for suitability, a total area of 1.46 million square kilometers is suitable for the CCUS project layout. When it dropped to 60%, this data increased to 2.04 million square kilometers. These areas are mainly distributed in large basin areas with abundant resources. Secondly, the DEMATEL-ISM analysis framework is improved to systematically identify and analyze the key obstacles that constrain the promotion of CCUS in China. The results indicate that there is a very complex relationship between the obstacles that constrain the development of CCUS, with the fundamental reasons being the lagging technological level and imperfect policies and regulations. Finally, goal-oriented suggestions and response measures were proposed, and targeted analysis was conducted on high-suitability areas. This study constructed an interdisciplinary methodology interpretive model to provide decision support for the CCUS layout and targeted strategies to break through current development barriers and promote the rapid development of CCUS.

Techno-economic assessment of large-scale sedimentary basin stored–CO2 geothermal power generation

One approach to reducing atmospheric carbon dioxide (CO2) emissions is to adopt carbon capture utilization and storage (CCUS) strategies. This is particularly crucial for countries to achieve their net-zero goal. In this study, we investigate the techno-economic viability of a proposed CCUS process that utilizes geologically stored CO2, associated with hydrogen (H2) production from fossil fuels, as a working fluid to extract geothermal energy from deep, large-scale, sedimentary storage formations. The process ensures permanent geological storage of all injected CO2 while generating adaptable geothermal power through supercritical CO2 turbine expansion, thus, bolstering revenue and reducing the final cost of blue hydrogen production. We simulate subsurface-wellbore fluid flow and heat transport for a representative 4-way closed anticlinal Arabian reservoir and optimize system power output, including a comprehensive and integrated economic analysis. We find that CO2 captured from an equivalent blue H2 production of ∼4.1 Mt./year can be injected at an annual rate of 0.92–1 million metric tons (Mt) per well, resulting in a cumulative sequestration of ∼1.15 gigatons (Gt) of CO2 over 11.5 years. To mitigate the risks of reaching the formation parting pressure at the crest of the anticline and ensuring sufficient CO2 saturation at the production wells, phased drilling schedules and pressure-controlled injection and production are essential. With horizontal production wells, our simulations generate an average geothermal net electricity of 164 MW. The base-case economic analysis reveals a Levelized Cost of Electricity (LCOE) of 77 $/MWh and a Net Present Value (NPV) of 480 million USD over 50 years. In contrast, vertical production wells double LCOE, and the project remains unprofitable throughout its life (negative NPV). Our economic sensitivity analysis further emphasizes how the capacity factor, electricity selling price, and drilling costs govern LCOE and NPV. On the other hand, discount rates and Opex fraction are influential yet uncertain parameters affecting the system's techno-economic outlook. Therefore, our study provides valuable insights into the benefits of geothermal energy production from over 1 Gt of stored CO2 and the associated economic landscape.

A Comprehensive Review of Carbon Capture, Utilization, and Storage (CCUS): Technological Advances, Environmental Impact, and Economic Feasibility

Carbon capture, utilisation, and storage (CCUS) technologies are critical to reducing CO2 exhalations on a global scale. This review study synthesizes the many elements of CCUS over 50 years, from R&D to deployment scales, in terms of their mitigation potential for global emission reductions. Next, it discusses existing and new carbon capture techniques from an automation standpoint (e.g., pre-combustion capture, post-combustion capture combustion), as well as the economic feasibility of CCUS regionally in terms of capital retail price, operating expenses, and value in the form of potential revenue streams based on CO2, aided by significant range-scaling building blocks such as rising nation. Each technique is thoroughly evaluated in terms of its environmental impact and associated risks, and case studies are used to illustrate practical lessons learnt. The paper also discusses the arguments around what future advances may exist in CCUS technology, and opportunities to scale these up (including research needs for this support), drawing lessons past policy. The findings underscore the importance of integrating CCUS into broader climate strategies to achieve net-zero exhalations while addressing the economic and environmental challenges that remain.

Establishment of a one-dimensional model for CO2 Pipeline rupture process and design recommendations

Pipelines serve as a critical means of transporting CO2 within Carbon Capture, Utilization, and Storage (CCUS) technology. Elevated transport pressures may lead to unforeseen pipeline ruptures. To provide practical recommendations for the design of CO2 pipelines and mitigate the risk of ruptures, this study establishes a one-dimensional Homogeneous Equilibrium Mixture (HEM) model. The model is currently used to predict the decompression behavior in existing pure CO2 rupture tests. Future work will address rupture tests and predictions involving impure CO2. The results indicate that due to differences in pressure reduction caused by decompression waves, the likelihood of long-range ruptures occurring in density CO2 pipelines is lower compared to supercritical CO2 pipelines. The crack propagation velocity and crack arrest pressure of pipelines designed according to ASME B31.3 are calculated using the High Strength Line Pipe Committee (HLP) model. Although the crack propagation velocity is lower than the decompression wave speed, the crack arrest pressure may fall below the rupture pressure, with the pressure at 1.6 m from the rupture point remaining above the crack arrest level for 1 ms post-rupture, a duration that is especially prolonged in larger-diameter pipelines. It is recommended to consider additional thickness beyond the calculated minimum thickness.

Strategic management of CO2: A scalable model for CCS in decarbonised societies

In future decarbonised energy systems, residual carbon emissions require strategic planning and management. In environmental management, an evaluation of carbon removal considering local geographic frameworks is needed. This paper introduces a scalable and adaptable model for evaluating the economics and geography of future carbon capture and storage (CCS) configurations across geographical scales, covering capture, transport, and storage of carbon. The model is applied to the North Denmark Region, showing that future energy production carbon sources will be concentrated in Thisted and Jammerbugt, while industrial sources remain in Aalborg and Rebild municipalities. Carbon transport configurations, including truck, pipeline, and shipping are assessed, for the carbon to be stored in onshore and offshore geological storages. The regional scale findings suggest that pipelines and onshore storage provide the most economical configuration. However, a sensitivity study using a smaller geographical scope indicates potential for optimising carbon transport by evaluating both carbon volume and distance. The paper discusses how the model's flexibility and scalability enable the integration of alternate cost components, thereby supporting the calculation of the carbon repurposing potentials, including carbon capture, utilisation, and storage (CCUS) configurations.

CCUS source-sink matching model based on sink well placement optimization

Realizing the dual-carbon target is a major strategic plan made by the Party Central Committee and a solemn commitment to address climate change of global significance. Source-sink matching technology in carbon capture, utilization, and storage (CCUS) technology is crucial to achieving the dual-carbon target. However, most previous studies constructed source-sink matching models based on sink-fixed sequestration potential, making it difficult to accurately assess the potential of sequestration sites and thus affect the source-sink matching scheme. Therefore, a dynamic storage potential assessment model has been established which can quickly assess the injection capacity of sinks under different well deployment schemes and then a source-sink matching model based on the overall optimization of sink deployment schemes has been constructed by combining the dynamic storage potential assessment model. The model considers the source matching problem as a mixed-integer linear programming (MILP) problem and obtains the computational results of the dynamic storage potential assessment model to realize the correct matching and simultaneous optimization of the source-sink pipeline network layout and the sink-well deployment scheme. With the proposed model, source-sink matching cases for national-level and project-level have been analyzed. It has been shown that the dynamic storage potential assessment model and the combined method improve the accuracy of the source-sink matching model in the form of MILP while minimizing the total cost and additional computations.

Estimation of CO2-Brine Interfacial Tension Based on an Advanced Intelligent Algorithm Model: Application for Carbon Saline Aquifer Sequestration.

The emission reduction of the main greenhouse gas, CO2, can be achieved via carbon capture, utilization, and storage (CCUS) technology. Geological carbon storage (GCS) projects, especially CO2 storage in deep saline aquifers, are the most promising methods for meeting the net zero emission goal. The safety and efficiency of CO2 saline aquifer storage are primarily controlled by structural and capillary trapping, which are significantly influenced by the interactions between fluid and solid phases in terms of the interfacial tension (IFT) between the injected CO2 and brine at the reservoir site. In this study, a model based on the random forest (RF) model and the Bayesian optimization (BO) algorithm was developed to estimate the IFT between the pure and impure gas-brine binary systems for application to CO2 saline aquifer sequestration. Then three heuristic algorithms were applied to validate the accuracy and efficiency of the established model. The results of this study indicate that among the four mixed models, the Bayesian optimized random forest model fits the experimental data with the smallest root-mean-square error (RMSE = 1.7705) and mean absolute percentage error (MAPE = 2.0687%) and a high coefficient of determination (R2 = 0.9729). Then the IFT values predicted via this model were used as an input parameter to estimate the CO2 sequestration capacity of saline aquifers at different depths in the Tarim Basin of Xinjiang, China. The burial depth had a limited influence on the CO2 storage capacity.

Effects of pore characteristics on CO2 adsorption performance of coal slime with different metamorphic degrees

With the rapid development of Carbon Capture, Utilization and Storage (CCUS) technology, it is necessary to explore the feasibility of coal slime as a porous carbon material for CO2 capture. In this paper, scanning electron microscopy (SEM) was used to observe the morphological characteristics of coal slime samples with different metamorphic degrees, and the pore structure of coal slime was explored by low temperature N2 adsorption and low-pressure CO2 adsorption experiments. The pore distribution characteristics were analyzed, and the adsorption law of different metamorphic degrees were summarized through CO2 isothermal adsorption experiments. The results showed that: The specific surface area (SSA) and pore volume (PV) of the mesopores of the coal slime exhibited a U-shaped distribution with coal rank, and are much smaller than that of its micropores. Micropores less than 2 nm are the main adsorption space of coal slime, its PV accounted for 59%, 60%, 71%, and SSA accounted for 92%, 93%, 95%, obviously, which are dominant at all stages. The linear correlation fitting coefficients R2 between the limiting adsorbed amount a of CO2 and the micropores PV and the SSA were up to 0.830 and 0.887, respectively. The coal slime has good adsorption performance for CO2. Based on the Langmuir model to fit the limit adsorption amount, a-value can reach 41.774 cm3 g−1, 32.072 cm3 g−1, 38.457 cm3 g−1 at 303 K with the increase of Rmax. Studying the impact of coal slime on CO2 adsorption performance provides a theoretical basis for the subsequent preparation of energy storage materials and is of great significance for the safe, efficient and economic capture and sequestration of CO2, to alleviate the serious situation of the environment and realizing the dual-carbon goal.

Accelerated CO2 preferential permeation using graphene oxide confined ionic liquid membranes for CO2/H2 separation

Due to the enhanced mass transfer process of nanochannels and the high affinity of ionic liquids (ILs) for carbon dioxide (CO2), the membranes combined with 2D nanosheets and ILs have attracted significant attention in carbon capture, utilization, and storage (CCUS). However, regulating the structure of IL to enhance the separation performance of CO2 remains a big challenge. Herein, we selected different imidazolium-based ILs and proposed a simple strategy to prepare nano-confined IL membranes by intercalating ILs into graphene oxide (GO). These membranes are subsequently used to remove CO2 from industrial syngases, where they display an abnormal CO2 preferential permeation process relative to the smaller H2 molecule. Meanwhile, CO2 permeation decreases gradually with the increase of alkyl chain length, whereas CO2/H2 selectivity shows a tendency to first increase and then decrease. Interestingly, all GO-confined IL membranes surpass the Robeson upper bound, achieving peak CO2 permeance of 13.85 GPU and CO2/H2 selectivity of 13.58, respectively. Further characterization of the interlayer spacing and density functional theory (DFT) calculations reveal that the high CO2/H2 separation performance mainly arises from the fact that nano-confined ILs can block the transit of H2 through the dense packing structure, simultaneously enhancing CO2 solubility and permeability through the membrane. These quantitative insights into the nanoconfined IL membrane not only deepen the scientific understanding of the abnormal transfer process within the nanochannel but also propose novel methodologies for preparing high-performance CO2 capture membranes.

Assessment of CO2 Sequestration Capacity in a Low-Permeability Oil Reservoir Using Machine Learning Methods

The CO2 sequestration capacity evaluation of reservoirs is a critical procedure for carbon capture, utilization, and storage (CCUS) techniques. However, calculating the sequestration amount for CO2 flooding in low-permeability reservoirs is challenging. Herein, a method combining numerical simulation technology with artificial intelligence is proposed. Based on the typical geological and fluid characteristics of low-permeability oil reservoirs in the Liaohe oilfield, the CMG 2020 version software GEM module is used to establish a model for CO2 flooding and sequestration. Meanwhile, a calculation method for the effective sequestration coefficient of CO2 is established. We systematically study the sequestration rules in low-permeability reservoirs under varying conditions of permeability, reservoir temperature, and initial reservoir pressure. The results indicate that, as the permeability and sequestration pressure of the reservoir increase, oil recovery gradually increases. The proportion of structurally bound sequestration volume increases from 55% to 60%. Reservoir temperature has minimal impact on both the recovery rate and the improvement in sequestration efficiency. Sequestration pressure primarily improves sequestration efficiency by increasing the dissolution of CO2 in the remaining oil and water. The calculation chart for the effective sequestration coefficient, developed using artificial intelligence algorithms under multi-factor conditions, enables accurate and rapid evaluation of the sequestration potential and the identification of favorable sequestration areas in low-permeability reservoirs. This approach provides valuable technical support for CO2 flooding and sequestration in pilot applications.

Biomimetic mineralization of hydrated magnesium carbonate for hydrogel reinforcement and heavy metal adsorption

With excessive Mn(Ⅱ) and Cu(Ⅱ) pollution in aquatic environments posing potential health risks to inhabitants, the emergence of carbon capture, utilization and storage (CCUS) technology has promoted the improvement of heavy metal remediation technologies. Using hydrothermal sediment as a crystal seed, rhamnolipid was used to mediate biomimetic mineralization to prepare hydrated magnesium carbonate (HMC) composites to enhance the Mn(Ⅱ)/Cu(Ⅱ) adsorption performance of alginate hydrogels. Hydrothermal sediment is beneficial for accelerating biomimetic mineralization, while rhamnolipid can induce a crystalline phase transformation from dypingite to nesquehonite. The addition of sediment significantly enhanced the compressive mechanical properties and thermal stability of the hydrogels. The adsorption performances of the nesquehonite and dypingite hydrogels were better for Mn(II) and Cu(II), respectively. An increase in the amount of sediment improved the adsorption of Cu(II) by the hydrogels appropriately, resulting in stronger selectivity for Cu(II). The adsorption of Mn(II) and Cu(II) on the hydrogel beads was thermodynamically spontaneous. The inhibitory effects of sodium dodecyl benzene sulfonate (SDBS), fulvic acid (FA) and alginate on Cu(II) adsorption were more obvious than those of bovine serum albumin (BSA). Both the complexation of functional groups on alginate and mineralization by HMC participated in the adsorption of Mn(II) and Cu(II).

Experimental evaluation of various flow meters using gaseous CO2

The need for accurate flow measurement within the Carbon Capture, Utilisation and Storage (CCUS) transport network is widely reported and understood as a requirement of Emission Trading Schemes and commercial contracts. In meeting this requirement, traceable calibration is needed in conditions which closely mimic the process conditions. However, currently accredited calibration facilities cannot meet the conditions for calibrating in gaseous CO2 and so a likely alternative solution for these custody transfer flow meters is to be calibrated with an alternative fluid and the calibration transferred. In this article, which was produced under the framework of the EMPIR project “Metrology for Decarbonising the Gas Grid”, the authors will investigate this approach with a number of flow meters tested in natural gas, nitrogen gas and finally in carbon dioxide gas at varying pressures. The results of which will suggest that orifice and Coriolis meters can be calibrated in another fluid however, an ultrasonic meter would require further work and potentially require calibration in CO2. This article will also investigate the effects of impurities in a CO2 gas stream for a rotary displacement flow meter and a thermal mass flow controller compared against a piston prover which provides a primary reference flow standard.

Study of the effect of glycine on the growth and mobility of CO2 hydrate slurries in the loop

The stability of CO2 hydrate slurry mobility is essential for the progression of diverse potential Carbon Capture, Utilization, and Storage (CCUS) applications, while also playing a critical role in maintaining the safety of gas–liquid two-phase flow transportation pipelines. In this study, the effect of glycine on the growth and flowing characteristics of CO2 hydrate slurry was investigated for the first time using a high-pressure recirculating flow loop. A comprehensive analysis of the hydrate growth, morphology, and rheological behavior was performed. The results show that the induction time of CO2 hydrate formation could be effectively prolonged by the presence of glycine in the loop, but it cannot inhibit its rapid formation in the rapid growth period. Meanwhile, agglomeration of the slurry and adsorption on the pipe wall during the flow process were observed with the presence of glycine. The flow pattern of pure CO2 hydrate slurry was gradually transitioned from expansion flow to pseudoplastic flow with the increase of hydrate amount, and shear thinning was observed when the slurry content was not less than 7.6%. The addition of glycine significantly increases the viscosity of the slurry, which makes the slurry behave as an expanding fluid in a wider range. The tendency of shear thickening and the range of shear thickening of the slurry were enlarged. This study raises mobility security concerns for the potential application value of glycine as an LDHI. It also serves as a valuable reference for furthering the advancement of CO2 slurry as a potential application for CCUS.

Harnessing 3D seismic data for mapping natural CO2 distribution: Paving the way for future CCS/CCUS implementation in the Lower Talang Akar Formation, Jabung Block, South Sumatra Basin

Hydrocarbon reservoirs saturated with CO2 are naturally widespread in the Lower Talang Akar Formation (LTAF) and deposited in the Jabung Block, South Sumatra Basin, Indonesia. The different CO2 saturation contents stored in the reservoirs pose a challenge to planning future carbon capture and storage (CCS) and carbon capture, utilization, and storage (CCUS) in the area. This study integrates poststack 3D seismic data and existing wells in the western part of the Jabung Block. It utilizes seismic attribute methods such as sum of negative amplitude, relative impedance, variance, and ant tracking to predict the origin, saturation, and distribution of CO2-saturated hydrocarbon accumulations in the sandstone reservoirs of the LTAF. The results show that CO2 originated from the Betara Deep source rock in the study area's eastern side and migrated to the reservoirs through major northwest–southeast-trending fault zones. The saturation of CO2 in the reservoirs is mainly controlled by the distance from the source and the reservoir depths, faulting, and fracturing intensity. The fields closer to the Betara source rock tend to be filled with higher contents of CO2 saturation. The results provide valuable guidance in CO2 identification and mapping for future CCS and CCUS implementation in the study area.

Leakage monitoring of carbon dioxide injection well string using distributed optical fiber sensor

Whether the oil and gas fields in the Carbon Capture, Utilization, and Storage (CCUS) project use underground storage or energy supplementation to enhance oil recovery, they must be injected or monitored through the wellbore. Thus, the foundation and requirement for the safety of carbon dioxide (CO2) storage is the wellbore's integrity. When CO2 is dissolved in water, carbonic acid is created, and this acid strongly corrodes underground pipes. Therefore, the integrity issue with CO2 injection wells is more noticeable than with other wellbores. An annular pressure during gas injection is the primary symptom of gas injection string leakage in CO2 injection wells. This study aims to provide real-time pipe string monitoring using a distributed optical fiber temperature sensing system (DTS) and a distributed optical fiber acoustic sensing system (DAS). Variations in temperature and vibration are caused by annulus pressure relief or gas injection. Optical fiber logging, in contrast to traditional logging, has better performance indicators for optical fiber sensing apparatus. To adapt to complex wellbore conditions, it is necessary to enhance the temperature accuracy of DTS and the sensitivity and signal-to-noise ratio of DAS in CO2 drive injection wells based on the features of the gas injection string. To differentiate the leakage signal from the regular fluid flow signal, the energy calculation in the frequency band is done for DAS based on noise reduction, and the signal processing in the frequency band is done by the spectrum characteristics of the CO2 wellbore signal. The translation invariant wavelet algorithm is the primary denoising method for DTS, overcoming the shortcomings of traditional wavelet threshold algorithms such as excessive smoothing and the pseudo-Gibbs phenomenon. Furthermore, the depth correction during the optical cable lowering process is also examined in this paper. A CO2 gas injection well field experiment was conducted using this technology. A 1671m well was dug, and 1631m of optical cable were installed in the tubing. The tubing leakage position was successfully identified through gas injection, annulus pressure relief, and a comparison of DAS and DTS data. The field results demonstrate the accuracy with which the gas injection string integrity can be accurately monitored in real-time using distributed optical fiber sensing technology for CO2 injection wells.