CO2 Plume Research Articles

CO2 Injection Monitoring: Enhancing Time-Lapse Seismic Inversion for Injected Volume Estimation in the Utsira Formation, Sleipner Field, North Sea

This article presents an in-depth study of CO2 injection monitoring in the Sleipner Field, focusing on the Utsira Formation. The research leverages advanced time-lapse inversion techniques and 4D seismic data analysis to enhance the accuracy of volume estimations and provide a comprehensive understanding of the dynamic behavior of the injected CO2 plume. The analysis encompasses cross correlation, time shift, predictability, and other key elements to yield robust insights into the reservoir’s response to CO2 injection. Cross-correlation analysis results of 60% to 100% outside the injection zone and less than 50% within the injection zone reveal a distinct dissimilarity between the injection and non-injection zones, emphasizing phase, time, and frequency content changes due to CO2 injection. Time shifts are meticulously calibrated globally on a trace-by-trace basis, to account for shallow statics and velocity changes, improving the overall alignment of seismic data. Predictability analysis results of 0 to 0.34 within the injection zone and 0.45 to 0.96 at the background further reinforce the findings, highlighting high predictability values in areas untouched by production and markedly lower values within the injection zone. These results provide a measure of the reliability of the seismic data and its ability to reflect the subtle changes occurring in the reservoir. Crucially, the time-lapse inversion process excels in capturing the evolving state of the CO2 plume within the Utsira Formation. The seismic data reveals the migration and expansion of the plume over time and the dynamic nature of the reservoir’s response to CO2 injection. Integrating various data facets reduces non-uniqueness in inversion results, allowing for more precise volume estimations.

A potential for climate benign direct air CO2 capture with CO2-driven geothermal utilization and storage (DACCUS)

To reduce the overaccumulation of carbon dioxide (CO2) in the atmosphere, direct air CO2 capture (DACC) technologies must (a) satisfy the process requirements for heat and electricity with energy that has few if any CO2 emissions, and (b) physically isolate the CO2 from the atmosphere after its extraction from the air. To isolate the CO2 from the atmosphere at meaningful scale, the CO2 will likely need to be geologically stored in deep saline aquifers. Here we propose to leverage geologic CO2 storage (GCS) in sedimentary basin geothermal resources to produce geothermal heat and electricity for the process energy requirements of solid sorbent DACC. This sedimentary basin CO2-driven geothermal utilization (SB-CO2DGU, also known as CO2 Plume Geothermal) circulates some of the emplaced CO2 to extract geothermal heat in a closed loop between the subsurface reservoir and surface geothermal facility. The proposed integration of DACC and CO2-driven geothermal Utilization and Storage (DACCUS) adds CO2 from the air to this closed loop system that produces renewable energy for use in the DACC process. The strategy first primes the GCS reservoir with CO2 from large point sources, and then integrates CO2 from DACC facility to form the DACCUS system. We focus on the process integration of DACCUS and present a case study of its potential deployment and scaling in the Gulf Coast of the United States. We combine data from prior analyses for a novel investigation of two DACCUS configurations: (1) a DACCUS heat system uses the geothermal heat to regenerate the solid sorbent in the DACC process, and (2) a DACCUS heat and power system uses the electricity generated from the produced geothermal heat for the DACC process. In general, deeper CO2 storage reservoirs (>3.5 km) with higher geothermal temperature gradients (>35 °C km−1), may provide sufficient production wellhead temperatures (>100 °C), and satisfy the electric load in 93% of the combinations of reservoir characteristics we examined.

Assessing the potential of composite confining systems for secure and long-term CO2 retention in geosequestration

A potential geologic target for CO2 storage should ensure secure containment of injected CO2. Traditionally, this objective has been achieved by targeting reservoirs with overlying seals-regionally extensive, low permeability units that have been proven capable of retaining buoyant fluid accumulations over geologic time. However, considering that the amount of CO2 is limited by a decadal injection period, vertical migration of CO2 can be effectively halted by a composite system of discontinuous shale/silt/mudstone barriers in bedded sedimentary rocks. Here, we studied the impact of depositional architectures in a composite confining system on CO2 migration and confinement at reservoir scale. We stochastically generated lithologically heterogeneous reservoir models containing discontinuous barriers consistent with statistical distributions of net-sand-to-gross-shale ratio (NTG) and horizontal correlation lengths derived from well log data and observations of producing hydrocarbon fields in Southern Louisiana. We then performed an extensive suite of reservoir simulations of CO2 injection and post-injection to evaluate the sensitivity of CO2 plume migration and pressure response of the composite system to a series of geologic and fluid parameters including the lateral continuity of barriers, NTG, permeability anisotropy within the sand body, and capillary pressure contrast between the sand and shale facies. The results indicate that lateral continuity of barriers and NTG are the dominant controls on CO2 plume geometry and pressure build-up in the reservoir, while the impact of NTG is particularly pronounced. The significance of intraformational barriers becomes apparent as they facilitate the local capillary trapping of CO2. Those barriers improve the pore space occupancy by promoting a more dispersed shape of the plume and ultimately retard the buoyancy-driven upward migration of the plume post injection.

Numerical Simulation of Membrane Separation Characteristics of Supercritical Carbon Dioxide and Water.

To solve the problem of water carryover in the supercritical CO2 separation and mining process in the CO2 plume geothermal system, a three-dimensional shell-tube hollow fiber membrane absorption separator is designed in this study. A coupled species transport model, a porous medium model, and an absorption mathematical model are established, and the flow field and separation characteristics in the circular and flat tubes are analyzed using numerical simulation. The results show that the membrane separation efficiency increases with an increase in the flatness and membrane tube length. When the inlet velocity of the mixture is 0.1 m/s, the separation efficiency can reach 75.92%. Selecting a smaller flow Reynolds number and a more significant membrane tube flatness will reduce the water mass fraction at the outlet. When adding baffles of different shapes to the membrane tube, the mixture fluid in the membrane tube meanders forward and flows in the shape of "Z" under the blocking effect of the arcuate baffles. With an increase in the number of arcuate baffles in the membrane tube, the membrane separation efficiency of the separator increases continuously. The mixture fluid flows in the membrane tube with the built-in torsional baffles in a spiral manner, and the separation efficiency of the membrane separator increases with a torsion ratio reduction in the membrane tube.

Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants

Abstract. Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (<15 %) uncertainties. However, as the constellation of CO2-observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources.

Determining the brine extraction well type, location, and rate for optimal pressure and carbon dioxide plume management

Brine extraction strategies can be applied in carbon capture and storage (CCS) projects to overcome two technical barriers to the commercial deployment of CCS technology: (1) managing reservoir pressure and (2) controlling the carbon dioxide (CO2) plume in the subsurface. Numerical simulations were performed to evaluate changes in reservoir pressure and CO2 saturation during brine extraction. A series of scenarios were simulated to determine the optimal brine extraction strategies through the sensitivity study of well type, well location, extraction rate, and perforation interval. The simulation results were analyzed for their efficacy to manage reservoir pressure and the CO2 plume. Differential pressure, CO2 storage efficiency, and the distance of the CO2 plume to the extraction well were used as metrics to evaluate performance. With an injection-to-extraction ratio of 1:1 (volumetric balance), the optimal location for a vertical extraction well is in a direction perpendicular to high hydraulic conductivity direction, and on the down-dip side, with perforation(s) within the injection zone. A horizontal extraction well has the following advantages over a vertical extraction well: it presents less risk of drilling into an existing CO2 plume; CO2 storage efficiency is improved; a lower extraction rate, thus less volume of brine extraction, is required to move the CO2 plume and reduce reservoir pressure; and it has less impact on the lateral movement of the CO2 plume, which could result in lower CO2 storage efficiency and CO2 plume leaving the area of review. To minimize brine extraction yet have a noticeable effect on reservoir pressure and movement of the CO2 plume, this study recommends injection-to-extraction ratios of 2:1 for a vertical well and 4:1 for a horizontal well, which correspond to extraction rates of 10,000 and 5,000 stb/day, respectively, when injecting 1 million metric tons of CO2 per annum. These findings can be used to guide similar studies on brine extraction to manage CO2 storage.

Detection of a CO2 plume by time-lapse analysis of Rayleigh-wave amplitudes extracted from downhole DAS recordings of ocean microseisms

Amplitudes of Rayleigh waves are known to decrease exponentially away from the surface. If elastic properties of the solid are stratified on a scale much smaller than the wavelength, the Rayleigh-wave amplitude at a given depth should also be affected by the formation properties at that depth: the softer the medium, the larger the amplitude. An increasingly widespread deployment of fiber-optic cables in wells makes it possible to record this depth variation of Rayleigh-wave strain amplitudes and their variations over time (due to changes of formation properties) using distributed acoustic sensing (DAS). To investigate this opportunity, we have explored temporal variations of downhole DAS amplitudes of ocean-generated Rayleigh waves during injection of CO2 into a water-saturated thin porous layer. Analysis of these data clearly shows changes of these amplitudes related to the CO2 injection. To understand these amplitude variations, we perform a theoretical analysis and numerical simulations, which explain our field observations. In particular, analysis of downhole DAS data and theoretical modeling show that Rayleigh-wave amplitudes measured with vertical fiber-optic cables can be used to detect thin layers in the subsurface. Furthermore, time-lapse analysis of these amplitudes indicates temporal changes of stiffness of these layers, such as changes in saturation or pressure of the fluid in a porous layer in the vicinity of the borehole. In particular, Rayleigh-wave amplitudes are sensitive to the presence in the vicinity of the wellbore of a CO2 plume created as a result of a small injection into a thin porous reservoir layer. Our analysis also shows that the effect of a thin layer on Rayleigh-wave amplitudes strongly depends on frequency so that at different frequencies the amplitude is affected by different combinations of elastic properties. This opens an opportunity to use amplitude variations with depth at different frequencies to separately estimate changes in bulk and shear moduli.

Induced Seismicity Hazard Assessment for a Potential CO2 Storage Site in the Southern San Joaquin Basin, CA

California’s Central Valley offers vast opportunities for CO2 storage in deep saline aquifers. We conducted an induced seismicity hazard assessment for a potential injection site in the southern San Joaquin Basin for 18 years of injection at 0.68 MtCO2/yr and 100 years of monitoring. We mapped stress, faults, and seismicity in a 30 km radius around the site to build a geomechanical model and resolve the stresses on major faults. From a 3D hydromechanical simulation of the CO2 plume, we calculated the change in pressure over time on these faults and determined the conditions for safe injection. Lacking any subsurface imaging, we also conducted a probabilistic fault slip analysis using numerous random distributions of faults and a range of geomechanical parameters. Our results show that the change in probability of fault slip can be minimized by controlling the size, migration, and magnitude of the pressure plume. We also constructed a seismic catalog for the last 20 years around the site and characterized the natural patterns of seismicity. We use these results to establish criteria for evaluating potential-induced events during the storage period and to develop a traffic light response system. This study represents a first-order procedure to evaluate the seismic hazards presented by CO2 storage and incorporate uncertainties in hydrological and geomechanical parameters.

Numerical analysis on the direction of groundwater flux effects on the early post-injection migration of a CO2 plume

Several parameters have been analysed in the field of carbon dioxide (CO2) subsurface storage efficiency and security, including the aquifer dip and background water flow, for proper selection of CO2 storage aquifer sites. However, less importance has been assigned to the impact of the direction of groundwater flow on the migration of the injected CO2 plume, and hence the aquifer storage performance. This study investigates, using a numerical modelling method, the effect of the direction and magnitude of groundwater flux on the CO2 plume displacement and trapping in dipping aquifers during the early stages of the post-injection migration. The groundwater flow is established using water injection and production wells at the extremities of the model, while the direction of flow is altered from downdip to updip by swapping the locations of these wells. The study estimates and compares the extent of the total injected plume and the mobile portion of the plume, in addition to the instantaneous velocity of the leading tip of the plume, when groundwater flows downdip and when it flows updip. Our results indicate that when the groundwater flows downdip, counter to the overall direction of the CO2 plume migration, the plume is more stretched in both the updip and downdip directions than when groundwater flows updip. The size of mobile CO2 plume enlarges to a greater extent with downdip groundwater flow, causing the advancing tip to accelerate during its updip migration due to increasing buoyancy, with the effect being more pronounced at lower flow velocities. This increases the risk of CO2 leakage during the early stages of the plume migration when groundwater flows downdip. On the other hand, updip groundwater flow reduces the risk of leakage by reducing the velocity and extent of the plume, and increasing the impact of trapping mechanisms. Thus, the direction of groundwater flow can control the migration velocity of the CO2 plume in dipping storage aquifers, not due primarily to any induced viscous force, but due to the impact of trapping on buoyancy. Therefore, choosing the appropriate injection location for CO2 relative to the direction of flux is important for storage efficiency.

The CCS greensand project: CO2 pilot injection and monitoring

The CCS greensand project: CO2 pilot injection and monitoring

Synergy scenario for renewable energy production, CO2 and H2 storage in the Baltic offshore structure

CO2 Capture, Transport, Use and Storage (CCUS) is one of the core technologies to mitigate climate change. New techno-economic and techno-ecological concept of a synergy of CO2 geological storage (CGS), CO2 use, hydrogen (H2) production from different eco-friendly renewable energy recovery technologies and underground H2 storage (UHS), which we call here Geological Power Bank (Geo-PB), in Cambrian Deimena Formation sandstones in different compartments of the E6 structure offshore Latvia is presented for the first time. A five-phase circular economy concept of E6 geological structure energy and CO2 storage hub was developed in this study. The workflow is techno-ecological, eco-friendly, self-supporting, cost-competitive, and economically feasible. It consists of (1) CO2 transport by ships to the rig, (2) CO2 injection for CGS and CO2 Plume Geothermal technology (CPG), (3) H2 production, (4) Geo-PB, and (5) H2 transport by the same ships to the customers. The concept is supporting a win8 situation - innovative elements of techno-ecological synergy in one site: (1) CGS, (2) CPG, (3) solar energy, (4) wind energy, (5) sea currents energy, (6) H2 production (7) Geo-PB and (8) H2 transport to consumers. The proposed cycle is closed, demonstrating the principles of circular economy, which will increase the total efficiency of the concept. CGS and CPG are planned in the E6-A compartment of the E6 geological structure with an average CO2 storage capacity of 365 Mt in an optimistic approach and Geo-PB is planned in E6-B with an H2 storage capacity of 119 kt.The Baltic offshore scenario is ambitious and innovative, proposed new technologies, synergy with renewable energy (geothermal, solar, wind and sea current), large storage capacity, including CO2 storage and use captured by a CCUS clusters of emission sources from energy production, cement industry and bio-emissions from Estonia, Latvia and Lithuania. The concept aimed to decrease the artificial impact of climate change by avoiding CO2 emissions to the atmosphere and implementing circular economy principles. It will increase public and policymakers’ acceptance of new underground CO2 and energy storage technologies. The proposed synergy solution for CGS and energy storage projects will make such a business economically feasible and attractive for investors. Our study demonstrates a new era, the next generation of cost-competitive, self-supporting conceptual techno-ecological examples of a possible synergy of storage concepts with renewable energies combined using circular economy approaches.

Solving multiphysics-based inverse problems with learned surrogates and constraints

Solving multiphysics-based inverse problems for geological carbon storage monitoring can be challenging when multimodal time-lapse data are expensive to collect and costly to simulate numerically. We overcome these challenges by combining computationally cheap learned surrogates with learned constraints. Not only does this combination lead to vastly improved inversions for the important fluid-flow property, permeability, it also provides a natural platform for inverting multimodal data including well measurements and active-source time-lapse seismic data. By adding a learned constraint, we arrive at a computationally feasible inversion approach that remains accurate. This is accomplished by including a trained deep neural network, known as a normalizing flow, which forces the model iterates to remain in-distribution, thereby safeguarding the accuracy of trained Fourier neural operators that act as surrogates for the computationally expensive multiphase flow simulations involving partial differential equation solves. By means of carefully selected experiments, centered around the problem of geological carbon storage, we demonstrate the efficacy of the proposed constrained optimization method on two different data modalities, namely time-lapse well and time-lapse seismic data. While permeability inversions from both these two modalities have their pluses and minuses, their joint inversion benefits from either, yielding valuable superior permeability inversions and CO2 plume predictions near, and far away, from the monitoring wells.

Dynamic modeling of geological carbon storage in an oil reservoir, Bredasdorp Basin, South Africa

Geological carbon storage provides an efficient technology for the large-scale reduction of atmospheric carbon, and the drive for net-zero emissions may necessitate the future usage of oil reservoirs for CO2 projects (without oil production), hence, dynamic modeling of an oil reservoir for CO2 storage in the Bredasdorp basin, South Africa, was therefore conducted. Injection into the reservoir was for 20 years (2030–2050), and 100 years (2050–2150) to study the CO2–brine–oil interactions, with sensitivities carried out on reservoir boundary conditions. The closed boundary scenario experienced pressure buildup with a target injection rate of 0.5 Mt/year, and a cutback on injection rate progressively until 2050 to not exceed the fracture pressure of the reservoir. The CO2 plume migration was not rapid due to the reduced volume of CO2 injected and the confining pressure. The system was gravity dominated, and gravity stability was not attained at the end of the simulation as fluid interfaces were not yet flat. The open boundary reservoir did not experience a pressure buildup because all boundaries were open, the target injection rate was achieved, and it was a viscous-dominated system. In both cases, the dissolution of CO2 in oil and brine was active, and there was a growing increase of CO2 fraction dissolved in water and oil, a decline in gaseous mobile CO2 phase between 2050 and 2150, and active trapping mechanisms were structural trapping, dissolution in oil and water, and residual trapping. The study showed that boundary condition was very crucial to the success of the project, with direct impacts on injection rate and pressure. This pioneering study has opened a vista on the injection of CO2 into an oil reservoir, and CO2–brine–oil interactions, with sensitivities carried out on reservoir boundary conditions in a closed and an open hydrocarbon system in South Africa.

BCH modelling studies on biocementation process in mitigating leaks from a CO2 sequestrated aquifer

BCH modelling studies on biocementation process in mitigating leaks from a CO2 sequestrated aquifer

Integrated Formation Evaluation for Site-Specific Evaluation, Optimization, and Permitting of Carbon Storage Projects

Participation in over 80 carbon capture and sequestration (CCS) projects spanning 25 years has led to the evolution of a recommended well-based appraisal workflow for CO2 sequestration in saline aquifers. Interpretation methods are expressly adapted for CCS applications to resolve key reservoir parameters, constrain field-scale modeling, provide answers required for the permitting process, and de-risk unique CCS evaluation challenges, such as Storage capacity Injectivity Containment. A challenge complicating all of the above is the eventual impact of three-way interaction among rock matrix, brine, and (impure) CO2 streams. Most logging, sampling, and laboratory techniques are adapted from established domains such as enhanced oil recovery, underground gas storage, and unconventional reservoir evaluation, though some CCS-specific innovation is also needed. Storage evaluation begins with established methods for lithology, porosity, permeability, and pressure, while special core analysis (SCAL) determines CO2 storage efficiency and relative permeability. Containment evaluation spans multiple disciplines and methods: the petrophysicist’s task to quantify seal capacity relies heavily on laboratory analysis, while geologists leverage downhole imaging tools to verify caprock structural/tectonic integrity. Geomechanics engineers define safe injection pressure via mechanical earth models (MEMs) built on advanced acoustic logs calibrated by core geomechanics, wellbore failure observations, and in-situ stress tests. The impact of rock-brine-CO2 interactions is studied via custom SCAL experiments and/or pore-scale digital rock simulations that rigorously represent chemical and thermal processes. Wireline formation tester samples provide representative formation brine as feedstock for SCAL. Water samples also enable operators to prove injection within regulatory limits while establishing baselines for future monitoring programs. Examples applied to recent CCS projects in North America are presented. All of the above data need to be integrated into a CCS model predicting the CO2 plume behavior across the area of interest and within multiple horizons.

Numerical simulation of potential site for CO2 sequestration in a depleted oil reservoir in northern Thailand

Due to the effects of an anthropogenic global warming, the concern about the emissions of carbon dioxide (CO2) into the environment has increased in various industries like petroleum industry. Currently, the use of the geological storage techniques, such as carbon capture and sequestration (CCS), is the most promising way to mitigate these emissions. The objective of this study on a numerical simulation is to investigate CO2 onshore geological storage in the depleted oilfields in the North of Thailand. The geological modelling is a critical step in proving the suitability of a geologic formation for a CCS project. The simulations of the pressure build-up, CO2 plume movement and the amount of CO2 stored are the main points of this research. The development of the 3D reservoir model is performed by means of CMG-GEM, and CMG-WINPROP. This study performs how CO2 sequestration is injected with the flow rate of 1000–4000 tons/day into a reservoir with a depth of 2120-2161 m. The result indicates that CO2 moves up to the top formation. Moreover, 0.583 Mt of CO2 can be stored into the reservoir. This presents the preliminary study for the CO2 sequestration in Northern Thailand, which aids in the next phase of CCS projects in Thailand.

Three‐axis borehole gravity monitoring for CO2 storage using machine learning coupled to fluid flow simulator

AbstractThe field of geophysics faces the daunting task of monitoring complex reservoir dynamics and imaging carbon dioxide storage up to several decades into the future. This presents numerous challenges, including sensitivity to parameter changes, resolution of obtained results and the cost of long‐term deployment. To effectively store CO2 subsurface, it is necessary to monitor and account for the injected CO2. The gravity method provides several advantages for CO2 monitoring, as changes in fluid saturation correspond directly and uniquely to observed density changes. Three‐axis borehole gravity has demonstrated significant promise as a next‐generation tool for reliably monitoring reservoir dynamics across a range of depths and sizes. However, the gravity inverse problem is highly ill‐posed, necessitating regularization that incorporates prior knowledge. To address this issue, we propose using a feed‐forward neural network, a machine learning method, to invert time‐lapse three‐axis borehole gravity data and monitor CO2 movement within a reservoir. By training the neural network on models that analyse changes in density and corresponding gravity responses resulting from perturbations made to the reservoir model, we can create scenarios that train the algorithm to identify unexpected CO2 migration in addition to the normal movement of CO2. Our method is demonstrated using reservoir models for the Johansen formation in offshore Norway. We convert reservoir saturation models into density changes and generate their corresponding three‐axis gravity data in a set of boreholes. Our results show that the developed machine learning inversion algorithm has high reliability and resolution for imaging density change associated with CO2 plumes, as demonstrated in the Johansen reservoir models utilized by the simulator. We also investigate machine learning inversion using regularization parameters and show that it is robust, with a strong tolerance for higher levels of noise. Our study demonstrates that the developed machine learning algorithm is a powerful tool for inverting three‐axis borehole gravity data and monitoring the migration and long‐term storage of injected CO2.

Assessing the impact of dip angle on carbon storage in saline reservoirs to aid site selection

Reservoir dip angle and permeability significantly impact CO2 plume migration and the amount of secondary phase trapping in storage formations. There is a fundamental trade-off between up-dip plume migration and secondary trapping that can be advantageous, or disadvantageous, for selecting an optimal CO2 storage site. For example, low permeability reservoirs have limited plume migration up-dip, consequently, residual and solubility trapping are also limited. On the contrary, for highly permeable reservoirs, up-dip migration can be fast and extensive, leading to accelerated residual and solubility trapping. By performing a systematic simulation study of plume migration and secondary trapping in reservoirs with a range of permeabilities and dip angles, we found that having a dip angle of at least 1° and permeability of at least 500mD results in up to 88% of the plume being immobilized 100 years post-injection. In reservoirs with a permeability of at least 500mD, we can optimize the amount of immobilized CO2 while limiting the amount of plume migration. As reservoir dip angles increase up to 2° and permeability increases, CO2 plume migration increases progressively, and up to 8x more mass of CO2 can migrate up-dip versus down-dip. At the same time, CO2 solubility in brine and residual trapping work to decrease the plume volume and can immobilize 28% to 90% of the CO2 plume over 100 years post-injection. Five influential parameters were identified that strongly influence the plume volume during the post-injection period for these dipping reservoirs: CO2 saturation, residual gas saturation, CO2 solubility in brine, CO2 density, and formation permeability. We also investigated the impact of simulation grid resolution, the maximum non-wetting phase saturation, and the pore-size distribution parameter on predicted plume behavior. This work provides simple, reliable relationships between key site screening metrics, reservoir dip angle, and permeability to inform the site selection process and monitoring, measurement, and verification (MMV) design.

Modeling pore-scale CO2 plume migration with a hypergravity model

Understanding site-scale carbon dioxide migration in saline aquifers is crucial for storage safety. High time and economic costs make establishing a full-scale model of this long-term and large-scale process difficult. Hypergravity model shortens the length and time scale, which has been applied to physical modeling of two-phase immiscible displacement. To evaluate the feasibility of hypergravity modeling two-phase displacement in porous media at pore scale, CO2 migration in saline aquifer is a suitable and classic problem. We used the phase field method to simulate the vertical displacement of brine by carbon dioxide due to buoyancy and pressure at the pore scale. The pore-scale phenomena of the two-phase displacement process were obtained by assessing different flow rates with or without gravity. We systematically analyzed the feasibility of the hypergravity model to evaluate CO2 migration in the geological domain by evaluating the hypergravity effect and using dimensionless analysis. We provide suggestions for performing the hypergravity model to evaluate and predict immiscible displacement in two-phase system.

Plume detection and emission estimate for biomass burning plumes from TROPOMI carbon monoxide observations using APE v1.1

Abstract. This paper presents the automated plume detection and emission estimation algorithm (APE), developed to detect CO plumes from isolated biomass burning events and to quantify the corresponding CO emission rate. APE uses the CO product of the Tropospheric Monitoring Instrument (TROPOMI) on board the Copernicus Sentinel-5 Precursor (S5P) satellite, launched in 2017, and collocated active fire data from the Visible Infrared Imaging Radiometer Suite (VIIRS), the latter flying 3 min ahead of S5P. After identifying appropriate fire events using VIIRS data, an automated plume detection algorithm based on traditional image processing algorithms selects plumes for further data interpretation. The approach is based on thresholds optimized for data over the United States in September 2020. Subsequently, the CO emission rate is estimated using the cross-sectional flux method, which requires horizontal wind fields at the plume height. Three different plume heights were considered, and the ECMWF Reanalysis v5 (ERA5) data were used to compute emissions. A varying plume height in the downwind direction based on three-dimensional Lagrangian simulation was considered appropriate. APE is verified for observations over Australia and Siberia. For all fire sources identified by VIIRS, only 16 % of the data corresponded to clear-sky TROPOMI CO data with plume signature. Furthermore, the quality filters of APE resulted in emission estimations for 26 % of the TROPOMI CO data with plume signatures. Visual filtering of the APE's output showed a true-positive confidence level of 97.7 %. Finally, we provide an estimate of the emission uncertainties. The greatest contribution of error comes from the uncertainty in Global Fire Assimilation System (GFAS) injection height that leads to emission errors <100 %, followed by systematic errors in the ERA5 wind data. The assumption of constant emission during plume formation and spatial under-sampling of CO column concentration by TROPOMI yields an error of <20 %. The randomized errors from the ensemble ERA5 wind data are found to be less than 20 % for 97 % of the cases.