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Monitoring is an important component of geological carbon storage operations because it provides data that can be used to estimate key quantities such as CO 2 plume location. The design of the monitoring strategy is complicated, however, because the monitoring plan must be established prior to the availability of extensive flow data. In this work, we present and apply a framework that integrates monitoring well optimization and (subsequent) history matching. The monitoring well optimization entails finding the locations of monitoring wells such that, with the data acquired at those locations, the expected uncertainty reduction in a particular flow quantity is maximized. This optimization requires the simulation of a large set of prior models, though these simulations need only be performed once for a given injection scenario. Once the monitoring wells are in place and CO 2 injection begins, history matching is performed using the monitoring data. This is accomplished here using an ensemble smoother with multiple data assimilation. The overall framework is applied to variogram-based geomodels that are representative of an actual storage project under development in the USA. Two injection scenarios are considered with two different (synthetic) 'true' models, which provide the observed data. History matched models are constructed using data from both optimally located and heuristically placed monitoring wells. Posterior uncertainty, evaluated in terms of the cumulative distribution function for a metric related to plume extent over the ensemble of history matched models, is shown to be minimized through use of optimized monitoring wells. These results demonstrate the importance of optimizing the monitoring plan, and the degree of uncertainty reduction that can be realistically achieved. [ABSTRACT FROM AUTHOR]

Carbon capture and storage (CCS) is an essential technology for achieving carbon neutrality. Depositional environments with sandstone and interbedded shale layers are promising for CO 2 storage because they can retain CO 2 beneath continuous and discontinuous shale layers. However, conventional numerical simulation of shale–sandstone systems is computationally challenging due to the large contrast in properties between the shale and sandstone layers and significant impact of thin shale layers on CO 2 migration. Extending recent advancements in Fourier neural operators (FNOs), we propose a new deep learning architecture, the RU-FNO, to predict CO 2 migration in complex shale–sandstone reservoirs under various reservoir conditions, injection designs, and rock properties. The gas saturation plume and pressure buildup predictions of the RU-FNO model are 8000-times faster than traditional numerical models and exhibit remarkable accuracy. We utilize the model's fast prediction to investigate the impact of shale layer characteristics on plume migration and pressure buildup. These case studies show that shale–sandstone reservoirs with moderate heterogeneity and spatial continuity can minimize the plume footprint and maximize storage efficiency. [ABSTRACT FROM AUTHOR]

Spontaneous imbibition—the process of a wetting fluid displacing a nonwetting fluid purely by capillary forces—is a ubiquitous phenomenon in porous and fibrous materials. Here we present a new experimental method for quantification of spontaneous imbibition in geologic materials. This method makes it possible to perform spontaneous imbibition under elevated pressure conditions relevant to environmental and energy resource applications. Computed tomography imaging reveals a new time‐independent scaling relationship that describes local imbibition rates as a function of water saturation. Imbibition capillary pressure curves are calculated with this wetting‐phase pressure and flow rate characterization, with no assumptions about the functional form, end point behavior, or scaling factors. Calculated end point capillary pressure is nonzero, in agreement with recent pore‐scale measurements of capillary pressure of trapped nonwetting phase. This work provides a new approach and insights into trapping and remobilization of nonwetting fluids in CO2 storage reservoirs and contaminated groundwater aquifers. Plain Language Summary: Spontaneous flow of fluids in porous and fibrous materials is a common process that causes fluids to soak clothing, diapers, and paper and is an important process controlling the long‐term movement of slow‐moving fluids below the surface of the Earth. In this study, we describe a new experimental method for understanding this spontaneous fluid flow in porous rocks and map the fluid movement with a medical imaging system. We present new experimental observations of this type of flow behavior and explain the results with a mathematical model. The results of this work have important implications for how fluids interact and become trapped in carbon sequestration reservoirs, fractured geothermal reservoirs, and contaminated aquifers. Key Points: A new experimental method is described for performing cocurrent spontaneous imbibition under elevated pressure conditionsSpontaneous imbibition front roughening and local flow rate are described by t−1/4 saturation‐dependent scalingNumerically calculated capillary pressure is found to be nonzero at the residual gas saturation [ABSTRACT FROM AUTHOR]

Accurate descriptions of heterogeneity in porous media are important for understanding and modeling single phase (e.g. contaminant transport, saltwater intrusion) and multiphase (e.g. geologic carbon storage, enhanced oil recovery) transport problems. Application of medical imaging to experimentally quantify these processes has led to significant progress in material characterization and understanding fluid transport behavior at laboratory scales. While widely utilized in cancer diagnosis and management, cardiology, and neurology, positron emission tomography (PET) has had relatively limited applications in earth science. This study utilizes a small-bore micro-PET scanner to image and quantify the transport behavior of pulses of a conservative aqueous radiotracer injected during single and multiphase flow experiments in two heterogeneous Berea sandstone cores. The cores are discretized into axial-parallel streamtubes, and using the reconstructed micro-PET data, expressions are derived from spatial moment analysis for calculating sub-core tracer flux and pore water velocity. Using the flux and velocity measurements, it is possible to calculate porosity and saturation from volumetric flux balance, and calculate permeability and water relative permeability from Darcy’s law. Second spatial moment analysis enables measurement of sub-core solute dispersion during both single phase and multiphase experiments. A numerical simulation model is developed to verify the assumptions of the streamtube dimension reduction technique. A variation of the reactor ratio is presented as a diagnostic metric to efficiently determine the validity of the streamtube approximation in core and column-scale experiments. This study introduces a new method to quantify sub-core permeability, relative permeability, and dispersion. These experimental and analytical methods provide a foundation for future work on experimental measurements of differences in transport behavior across scales. [ABSTRACT FROM AUTHOR]

We report results from an experimental investigation on the hysteretic behaviour of the capillary pressure curve for the supercritical CO 2 -water system in a Berea Sandstone core. Previous observations have highlighted the importance of subcore-scale capillary heterogeneity in developing local saturations during drainage; we show in this study that the same is true for the imbibition process. Spatially distributed drainage and imbibition scanning curves were obtained for mm-scale subsets of the rock sample non-invasively using X-ray CT imagery. Core- and subcore-scale measurements are well described using the Brooks–Corey formalism, which uses a linear trapping model to compute mobile saturations during imbibition. Capillary scaling yields two separate universal drainage and imbibition curves that are representative of the full subcore-scale data set. This enables accurate parameterisation of rock properties at the subcore-scale in terms of capillary scaling factors and permeability, which in turn serve as effective indicators of heterogeneity at the same scale even when hysteresis is a factor. As such, the proposed core-analysis workflow is quite general and provides the required information to populate numerical models that can be used to extend core-flooding experiments to conditions prevalent in the subsurface, which would be otherwise not attainable in the laboratory. [ABSTRACT FROM AUTHOR]

A recently developed technique to accurately characterize sub-core scale heterogeneity is applied to investigate the factors responsible for flowrate-dependent effective relative permeability curves measured on core samples in the laboratory. The dependency of laboratory measured relative permeability on flowrate has long been both supported and challenged by a number of investigators. Studies have shown that this apparent flowrate dependency is a result of both sub-core scale heterogeneity and outlet boundary effects. However this has only been demonstrated numerically for highly simplified models of porous media. In this paper, flowrate dependency of effective relative permeability is demonstrated using two rock cores, a Berea Sandstone and a heterogeneous sandstone from the Otway Basin Pilot Project in Australia. Numerical simulations of steady-state coreflooding experiments are conducted at a number of injection rates using a single set of input characteristic relative permeability curves. Effective relative permeability is then calculated from the simulation data using standard interpretation methods for calculating relative permeability from steady-state tests. Results show that simplified approaches may be used to determine flowrate-independent characteristic relative permeability provided flow rate is sufficiently high, and the core heterogeneity is relatively low. It is also shown that characteristic relative permeability can be determined at any typical flowrate, and even for geologically complex models, when using accurate three-dimensional models. [ABSTRACT FROM AUTHOR]

Recent advancements in experimental techniques allow sub-core-scale heterogeneities to be quantified in a high resolution. Based on the observations of heterogeneity distributions in natural core samples, we perform simulations to study the influence of small-scale heterogeneities on large-scale CO 2 migration during geological storage. We observe that even the heterogeneities at millimeter scale (the scale of a Representative Elementary Volume for sandstones) can affect large-scale buoyancy-driven upward CO 2 migration. For the representative examples we study, ignoring small-scale heterogeneities can lead to an overestimation of the migration speed by a factor of two. To analyze the cause of such overestimation, we introduce a dimensionless heterogeneity factor to characterize different levels of heterogeneity. The influence on CO 2 migration is quantified with respect to a variety of heterogeneity factors, correlation lengths, and fluid viscosity ratios for isotropic and anisotropic media. Our findings suggest that small-scale heterogeneities should not be ignored in core analysis, even for cores that appear relatively homogeneous and do not have distinguishable heterogeneous patterns. In addition, relative-permeability curves measured from core-flood experiments under high-flow-velocity conditions (a common practice to eliminate capillary end-effects) should not be directly used in modeling low-velocity CO 2 migration if small-scale heterogeneities are present. [ABSTRACT FROM AUTHOR]

Here we provide a comprehensive study of the fundamental physics both numerically and analytically, of the combined influence of heterogeneity, viscous forces, gravity, and capillarity on multiphase flow of CO 2 and brine. Specifically, steady-state 3D coreflood displacements in heterogeneous cores over a range of relevant conditions are simulated to study the impact of sub-core heterogeneity on CO 2 /brine displacements over a wide range of flowrates. Various degrees of heterogeneity are generated based on the normal random distribution as well as for real models of cores based on 3D X-Ray tomography. A 2D semi-analytical model considering gravity and permeability heterogeneity is developed for predicting brine displacement efficiency over a wide range of capillary numbers that provides good agreement with the simulated 3D results. The analytical derivation is general and the provided solution can estimate the flow regimes for horizontal core floods efficiently. [ABSTRACT FROM AUTHOR]

Almost 20 years ago, the first CO2 capture and storage (CCS) project began injecting CO2 into a deep geological formation in an offshore aquifer. Relevant science has advanced in areas such as chemical engineering, geophysics, and social psychology. Governments have generously funded demonstrations. As a result, a handful of industrial-scale CCS projects are currently injecting about 15 megatons of CO2 underground annually that contribute to climate change mitigation. However, CCS is struggling to gain a foothold in the set of options for dealing with climate change. This review explores why and discusses critical conditions for CCS to emerge as a viable mitigation option. Explanations for this struggle include the absence of government action on climate change, economic crisis-induced low carbon prices, public skepticism, increasing costs, and advances in other options including renewables and shale gas. Climate change action is identified as a critical condition for progress in CCS, in addition to community support, safe storage, robust policy support, and favorable CCS market conditions. [ABSTRACT FROM AUTHOR]

A combination of declining costs and policy measures motivated by greenhouse gas (GHG) emissions reduction and energy security have driven rapid growth in the global installed capacity of solar photovoltaics (PV). This paper develops a number of unique data sets, namely the following: calculation of distribution of global capacity factor for PV deployment; meta-analysis of energy consumption in PV system manufacture and deployment; and documentation of reduction in energetic costs of PV system production. These data are used as input into a new net energy analysis of the global PV industry, as opposed to device level analysis. In addition, the paper introduces a new concept: a model tracking energetic costs of manufacturing and installing PV systems, including balance of system (BOS) components. The model is used to forecast electrical energy requirements to scale up the PV industry and determine the electricity balance of the global PV industry to 2020. Results suggest that the industry was a net consumer of electricity as recently as 2010. However, there is a >50% that in 2012 the PV industry is a net electricity provider and will "pay back" the electrical energy required for its early growth before 2020. Further reducing energetic costs of PV deployment will enable more rapid growth of the PV industry. There is also great potential to increase the capacity factor of PV deployment. These conclusions have a number of implications for R&D and deployment, including the following: monitoring of the energy embodied within PV systems; designing more efficient and durable systems; and deploying PV systems in locations that will achieve high capacity factors. [ABSTRACT FROM AUTHOR]

To encourage and guide decarbonization efforts, better tools are needed to monitor real-time CO 2 and criteria air pollutant emissions from electricity consumption, production, imports, and exports. Using real-time data from the electricity system is especially challenging for quantitative applications requiring high quality and physically consistent data. Until now, time-intensive, ad-hoc and manual data verification and cleaning strategies have been used to prepare the data for quantitative analysis. As an alternative to existing techniques, here we provide a physics-informed framework to greatly accelerate and automate data processing to enable internally consistent electric system consumption, production, import, and export data in near real-time. A key component of this framework is an optimization program to minimize the data adjustments required to satisfy energy conservation equations. The effectiveness of this method is demonstrated by applying it to the continental United States electricity network. The resulting publicly-available data set, which provides in near-real time, hourly updates on electricity generation, consumption, imports, exports and associated emissions, is the first of this nature. • Optimal data cleaning algorithm relies on energy conservation equations. • Enables near-real time analysis of electric generation, consumption, and emissions. • Publicly available data set for 68 continental US balancing areas is updated hourly. [ABSTRACT FROM AUTHOR]

• A new macroscopic capillary number for horizontally layered systems is presented. • Effective flow-rate dependent saturation functions are derived analytically. • A model is presented to predict the impact of laminations on CO 2 plume migration. We investigate the impact of sub-grid scale horizontal lamination on the migration of the CO 2 plume during geologic sequestration. A new physics-based model that includes the effects of capillary and viscous forces is used to obtain effective flow-rate dependent capillary pressure and relative permeability functions. For this purpose a macroscopic capillary number is derived that accurately describes the viscous-capillary force balance. The model is based on the fractional flow approach and is implemented in an extended radial Buckley-Leverett solution. This provides an easy way to investigate the impact of mm to m scale laminae on the frontal advance of the plume. Our work shows that at injection rates and volumes commonly used at geologic sequestration sites, capillary number dependency is important during the initial phase of the injection period. At later stages, the use of a capillary limit solution will be a valid approximation, even close to the injection well. [ABSTRACT FROM AUTHOR]

Understanding electricity consumption and production patterns is a necessary first step toward reducing the health and climate impacts of associated emissions. In this work, the economic input-output model is adapted to track emissions flows through electric grids and quantify the pollution embodied in electricity production, exchanges, and, ultimately, consumption for the 66 continental US Balancing Authorities (BAs). The hourly and BA-level dataset we generate and release leverages multiple publicly available datasets for the year 2016. Our analysis demonstrates the importance of considering location and temporal effects as well as electricity exchanges in estimating emissions footprints. While increasing electricity exchanges makes the integration of renewable electricity easier, importing electricity may also run counter to climate-change goals, and citizens in regions exporting electricity from high-emission-generating sources bear a disproportionate air-pollution burden. For example, 40% of the carbon emissions related to electricity consumption in California's main BA were produced in a different region. From 30 to 50% of the sulfur dioxide and nitrogen oxides released in some of the coal-heavy Rocky Mountain regions were related to electricity produced that was then exported. Whether for policymakers designing energy efficiency and renewable programs, regulators enforcing emissions standards, or large electricity consumers greening their supply, greater resolution is needed for electric-sector emissions indices to evaluate progress against current and future goals. [ABSTRACT FROM AUTHOR]

The authors discuss what needs to be done in the U.S. to reduce energy demand and promote alternative energy sources. A crucial first step is disabusing the public of several widely-held but false beliefs about adopting alternative sources, including the fear of resulting harm to the U.S. economy. Other helpful measures include greater funding for research and more involvement on the part of physicists and educators in raising awareness.

The author discusses efforts to reduce greenhouse gas (GHG) emissions, focusing on bioenergy with carbon capture and storage (BECCS) methods of carbon dioxide removal (CDR). Topics include the processes involved in BECCS including microbial fermentation, gasification, and combustion, cost considerations of the technology, and the environmental benefits of negative-emissions systems.

The study of natural CO 2 storage reservoirs has demonstrated that carbon mineral trapping is the safest mechanism for subsurface CO 2 storage. The slow rate of fluid-rock reactions makes it imperative to use reactive transport simulations as a tool for estimating reservoir scale carbon mineral trapping capacities. However, there is often a disparity in the estimations of carbon mineral trapping capacities determined from reactive transport simulations and recorded in natural CO 2 storage reservoirs. This might be due to several factors such as the uncertainty around simulations parameters such as mineral reactive surface areas as well as the neglect of sub-core scale lithological heterogeneity in reservoir scale simulations. This study points to the importance of the latter to reconcile the mismatch. Multiphase reactive transport simulations were run on a cm-scale resolution geological model (CRM) of the Paaratte Formation, Otway Basin (Australia), where mm- to cm-scale lithological heterogeneity is incorporated via upscaled rock parameters. Simulations were also run on a m-scale resolution model (MRM) of the same transect to quantify the difference in the predicted secondary mineral composition due to the incorporation of sub-core scale heterogeneity in reservoir scale simulations. The simulation outcomes for both the models were compared to the data from the Pretty Hill Formation, a natural CO 2 storage analogue within the Otway Basin with similar primary mineral composition. The results from the CRM compare well with the secondary carbonate mineralogy of the Pretty Hill Formation. In contrast, the MRM strongly underestimates carbonate mineral formation. The results highlight that the incorporation of mm- to cm-scale lithological interfaces in reservoir scale reactive transport simulations can increase carbon mineralization estimates in siliciclastic formations by 3–6 orders of magnitude as these interfaces are sites for mineral precipitation. • Carbon mineral trapping potential is assessed using numerical simulations. • Results from simulations and natural analogues usually show a disparity. • A reason for this mismatch is the neglect of fine lamina in reservoir models. • The study aims to reduce the disparity by accounting for cm-scale heterogeneity. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Health and Safety Risks of Carbon Capture and Storage," by John Fogarty and Michael McCally in the 2010 issue, as well as a response from the article's authors.

Battery vehicles and fuel cell vehicles can facilitate the use of low-carbon energy sources in stationary applications, as well as for transportation. For instance, battery vehicles might enable peak load shifting and short-term electricity storage when connected to the electric grid. Hydrogen infrastructure that provides refueling of fuel cell vehicles might also absorb peak solar generation, and provide hydrogen to the natural gas network. Here, the cost and emissions impacts of these system-level effects are integrated into an overall cost-benefit analysis of battery vehicles and fuel cell vehicles. An integrated analysis of a community energy system under various electric vehicle penetration scenarios is conducted, using a linear cost optimization model. The model determines the cost-optimal energy infrastructure mix in different penetration rate scenarios, using hourly time series data for the community's power generation and energy demand. The optimization considers a wide variety of technical and economic parameters, and determines results for 2025 and 2035. The findings show, that while both battery vehicles and fuel cell vehicles can modestly reduce the community's overall carbon dioxide emissions, the latter carry higher overall costs, primarily due to the hydrogen generation infrastructure. Battery vehicles are therefore a more cost-efficient choice for reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Various methods have been proposed to measure fracture aperture distributions, including X-ray computed tomography (CT) imaging, which has the advantage that it can be combined with dynamic flow experiments. In this paper, we present a calibration-free missing CT attenuation (CFMA) imaging method for measuring fracture apertures that avoids time-consuming calibration. In addition, this model does not assume a homogeneous matrix and thus provides a good estimate of fracture apertures even when rock properties are heterogeneous. The validity of the CFMA model is established by four approaches: comparing apertures calculated with the conventional calibration-based method; evaluating model predictability at different scanner voxel sizes; comparing with calibration coefficients in the literature from a number of experiments with different rocks and X-ray scanners; and comparing aperture measurements for dry and wet scans. We analyze the systematic error and the random error introduced by rock heterogeneities and CT scanning and show that by averaging 5 replicate scans, we reduce the aperture measurement error to ~22 µm. [ABSTRACT FROM AUTHOR]

CO2 was injected into a coal fire burning at a depth of 15 m in the subsurface in southwestern Colorado, USA. Measurements were made of the 13CO2 isotopic signature of gas exhaust from an observation well and two surface fissures. The goal of the test was to determine (1) whether CO2 with a distinct isotopic signature could be used as a tracer to identify flow pathways and travel times in a combustion setting where CO2 was present in significant quantities in the gases being emitted from the coalbed fire, and (2) to confirm the existence of a self-propagating system of air-intake and combustion gas exhaust that has been previously proposed. CO2 was injected in three separate periods. The 13CO2 isotopic signature was measured at high frequency (0.5 Hz) before, during, and after the injection periods for gas flowing from fissures over the fire and from gas entering an observation well drilled into the formation just above the fire but near the combustion zone. In two cases, a shift in the isotopic signature of outgassing CO2 provided clear evidence that injected CO2 had traveled from the injection well to the observation point, while in a third case, no response was seen and the fissure could not be assumed to have a flowpath connected with the injection well. High-frequency measurements of the 13CO2 signature of gas in observation wells is identified as a viable technique for tracking CO2 injected into subsurface formations in real-time. In addition, a chimney-like coupled air-intake and exhaust outlet system feeding the combustion of the coal seam was confirmed. This can be used to further develop strategies for extinguishing the fire. [ABSTRACT FROM AUTHOR]

• CCSNet provides instant predictions to outputs needed for subsurface flow problems. • Temporal-3d convolutional neural network with superb performance and applicability. • Massive simulation data set representing most potential scenarios for CO 2 storage. • Rigorous sweep efficiency and solubility trapping estimations for site selection. [Display omitted] Numerical simulation is an essential tool for many applications involving subsurface flow and transport, yet often suffers from computational challenges due to the multi-physics nature, highly non-linear governing equations, inherent parameter uncertainties, and the need for high spatial resolutions to capture multi-scale heterogeneity. We developed CCSNet, a deep-learning modeling suite that can act as an alternative to conventional numerical simulators for carbon capture and storage (CCS) problems well-represented by a 2D radial grid, for example, injection into an infinite acting saline formation with no or very small dip. CCSNet consists of a sequence of deep learning models producing all the outputs that a numerical simulator typically provides, including saturation distributions, pressure buildup, dry-out, fluid densities, mass balance, solubility trapping, and sweep efficiency. The results are 10 3 to 10 4 times faster than conventional numerical simulators. As an application of CCSNet illustrating the value of its high computational efficiency, we developed rigorous estimation techniques for the sweep efficiency and solubility trapping. [ABSTRACT FROM AUTHOR]

Quantitatively assessing seismic attenuation caused by fluid pressure diffusion (FPD) in partially saturated rocks is challenging because of its sensitivity to the spatial fluid distribution. To address this challenge we performed depressurization experiments to induce the exsolution of carbon dioxide from water in a Berea sandstone sample. In a first set of experiments we used medical X‐ray computed tomography (CT) to characterize the fluid distribution. At an equilibrium pressure of approximately 1 MPa and applying a fluid pressure decline rate of approximately 0.6 MPa per minute, we allowed a change in saturation of less than 1%. The gas was heterogeneously distributed along the length of the sample, with most of the gas exsolving near the sample outlet. In a second set of experiments, at the same pressure and temperature, following a very similar exsolution protocol, we measured the frequency dependent attenuation and modulus dispersion between 0.1 and 1,000 Hz using the forced oscillation method. We observed significant attenuation and dispersion in the extensional and bulk deformation modes, however, not in the shear mode. Lastly, we use the fluid distribution derived from the X‐ray CT as an input for numerical simulations of FPD to compute the attenuation and modulus dispersion. The numerical solutions are in close agreement with the attenuation and modulus dispersion measured in the laboratory. Our approach allows for accurately relating attenuation and dispersion to the fluid distribution, which can be applied to improving the seismic monitoring of the subsurface. Key Points: Measurements of seismic wave attenuation and dispersion in a partially saturated sandstonePartial saturation was achieved by exsolution of carbon dioxide and was characterized with X‐ray computed tomographyFluid distribution was used to numerically simulate attenuation and dispersion due to fluid pressure diffusion [ABSTRACT FROM AUTHOR]

Highlights • Positron emission tomography can quantify unique attributes of fluid flow in rocks. • Important PET experimental methodological considerations are described. • A new geo-specific method for PET data quality optimization is presented. • Spatial resolution and sensitivity of different PET imaging platforms is quantified. • Examples of previous and future applications are discussed. Abstract Recent studies have demonstrated that positron emission tomography (PET) is a valuable tool for in-situ characterization of fluid transport in porous and fractured geologic media at the laboratory scale. While PET imaging is routinely used for clinical cancer diagnosis and preclinical medical research—and therefore imaging facilities are available at most research institutes—widespread adoption for applications in water resources and subsurface energy resources engineering have been limited by real and perceived challenges of working with this technique. In this study we discuss and address these challenges, and provide detailed analysis highlighting how positron emission tomography can complement and improve laboratory characterization of different subsurface fluid transport problems. The physics of PET are reviewed to provide a fundamental understanding of the sources of noise, resolution limits, and safety considerations. We then layout the methodology required to perform laboratory experiments imaged with PET, including a new protocol for radioactivity dosing optimization for imaging in geologic materials. Signal-to-noise and sensitivity analysis comparisons between PET and clinical X-ray computed tomography are performed to highlight how PET data can complement more traditional characterization methods, particularly for solute transport problems. Finally, prior work is critically reviewed and discussed to provide a better understanding of the strengths and weakness of PET and how to best utilize PET-derived data for future studies. [ABSTRACT FROM AUTHOR]

Highlights • PET imaging of pulse-tracer tests in random beadpack and microporous limestone. • Two transport models (ADE and MRMT) are evaluated against the experimental data. • Residence time distribution analysis shows a flow rate effect in the limestone. • Tracer spreading can be reduced using a dispersion-echo technique. Abstract The analysis of dispersive flows in heterogeneous porous media is complicated by the appearance of anomalous transport. Novel laboratory protocols are needed to probe the mixing process by measuring the spatial structure of the concentration field in the medium. Here, we report on a systematic investigation of miscible displacements in a microporous limestone over the range of Péclet numbers, 20 < Pe < 600. Our approach combines pulse-tracer tests with the simultaneous imaging of the flow by Positron Emission Tomography (PET). Validation of the experimental protocol is achieved by means of control experiments on random beadpacks, as well as by comparing observations with both brine- and radio-tracers (labelled with 11C or 18F). The application of residence time distribution functions reveals mass transport limitations in the porous rock in the form of a characteristic flow-rate effect. Two transport models, namely the Advection Dispersion Equation (ADE) and the Multi-Rate Mass Transfer (MRMT) model, are thoroughly evaluated with both the experimental breakthrough curves and the internal concentration profiles. We observe that the dispersion coefficient scales linearly with the Péclet number for both porous systems. The tracer profiles acquired on the rock sample are successfully described upon application of the MRMT model that uses two representative grain sizes and a fraction of intra-granular pore space that is independent of the fluid velocity. The analysis of the PET images evidences the presence of macrodispersive spreading caused by subcore-scale heterogeneities, which contribute significantly to the value of the estimated core-scale dispersivity. This effect can be significantly reduced upon application of the 'dispersion-echo' technique, which enables decoupling the effects of spreading and mixing in heterogeneous porous media. These observations are likely to apply to any laboratory-scale rock sample and the approach presented here provides a practical means to study anomalous transport in these systems. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract Improved methods for predicting fluid transport and vesicle connectivity in heterogeneous basalts are critical for determining the long-term reaction and trapping behavior of sequestered carbon dioxide and maximizing the efficiency of geothermal energy production. In this study we measured vesicle geometry, pore connectivity, and vesicle surface area of three basalt cores from the CarbFix carbon storage project in Iceland using a combination of micro-computed tomography, clinical computed tomography, and micro-positron emission tomography. A vesicle percolation simulator was then constructed to quantify vesicle connectivity across a complete range of porosities, pore size distributions, and microporosity conditions. Percolation simulations that incorporate important geologic features such as microporosity are able to describe the trend of experimental measurements made in this study and in previous work, without relying on statistical or empirical techniques. Simulation results highlight and quantify the trade-off between storage capacity and reactive surface area in high porosity basalts. Experiment and simulation results also indicate that there is very limited connected pore space below total porosity values of 15%, guiding improved site selection for large scale CO 2 storage projects. Use of this stochastic percolation simulation method for basalt storage reservoir evaluation will enable more accurate storage capacity and mineral trapping estimates. [ABSTRACT FROM AUTHOR]

Bioenergy with carbon capture and storage (BECCS) is a negative-emissions technology that may play a crucial role in climate change mitigation. BECCS relies on the capture and sequestration of carbon dioxide (CO2) following bioenergy production to remove and reliably sequester atmospheric CO2. Previous BECCS deployment assessments have largely overlooked the potential lack of spatial colocation of suitable storage basins and biomass availability, in the absence of long-distance biomass and CO2 transport. These conditions could constrain the near-term technical deployment potential of BECCS due to social and economic barriers that exist for biomass and CO2 transport. This study leverages biomass production data and site-specific injection and storage capacity estimates at high spatial resolution to assess the near-term deployment opportunities for BECCS in the United States. If the total biomass resource available in the United States was mobilized for BECCS, an estimated 370 Mt CO2⋅y-1 of negative emissions could be supplied in 2020. However, the absence of long-distance biomass and CO2 transport, as well as limitations imposed by unsuitable regional storage and injection capacities, collectively decrease the technical potential of negative emissions to 100 Mt CO2⋅y-1. Meeting this technical potential may require large-scale deployment of BECCS technology in more than 1,000 counties, as well as widespread deployment of dedicated energy crops. Specifically, the Illinois basin, Gulf region, and western North Dakota have the greatest potential for near-term BECCS deployment. Highresolution spatial assessment as conducted in this study can inform near-term opportunities that minimize social and economic barriers to BECCS deployment. [ABSTRACT FROM AUTHOR]

This study utilizes synchrotron X-ray micro-tomography and pore scale modeling to investigate the process of gas exsolution and how it affects non-wetting phase relative permeability. Exsolved gas distributions are measured on Domengine and Boise sandstone samples using synchrotron X-ray micro-tomography. Observed gas phase distributions are compared to a new model that simulates the growth and distribution of exsolved gas phase at the pore-scale. Water relative permeability curves are calculated using a Stokes flow simulator with modeled and observed gas distributions, under various conditions, such as rock geometry, and pressure depletion rates. By comparing the actual bubble distributions with modeled distributions, we conclude that exsolved gas is more likely to form and accumulate at locations with higher water velocities. This suggests that convective delivery of CO 2 to the gas bubble is a primary mechanism for bubble growth, as compared to diffusive transport through the aqueous phase. For carbonated brine flowing up a fault at half a meter per day, with 5% exsolved gas, the water relative permeability is estimated to be 0.6∼0.8 for various sandstones. The reduction of water mobility reduces upward brine migration when even a small amount of exsolution occurs. [ABSTRACT FROM AUTHOR]

A multi-scale synchrotron-based X-ray microtomographic dataset of residually trapped air after gravity-driven brine imbibition was acquired for three samples with differing pore topologies and morphologies; image volumes were reconstructed with voxel sizes from 4.44 µm down to 0.64 µm. Capillary pressure distributions among the population of trapped ganglia were investigated by calculating interfacial curvature in order to assess the potential for remobilization of residually-trapped non-wetting ganglia due to differences in capillary pressure presented by neighbor ganglia. For each sample, sintered glass beads, Boise sandstone and Fontainebleau sandstone, sub-volumes with different voxel sizes were analyzed to quantify air/brine interfaces and interfacial curvatures and investigate the effect of image resolution on both fluid phase identification and curvature estimates. Results show that the method developed for interfacial curvature estimation leads to reliable capillary pressure estimates for gas ganglia. Higher resolution images increase confidence in curvature calculations, especially for the sandstone samples that display smaller gas-brine interfaces which are then represented by a higher number of voxels when imaged with a micron or sub-micron voxels size. The analysis of sub-volumes from the Boise and Fontainebleau dataset highlights the presence of a residually-trapped gas phase consisting of ganglia located in one or few pores and presenting significantly different capillary pressures, especially in the case of Fontainebleau sandstone. As a result, Ostwald ripening could occur, leading to gas transfer from ganglia with higher capillary pressure to surrounding ganglia with lower capillary pressures. More generally, at the pore-scale, most gas ganglia do present similar capillary pressures and Ostwald ripening would then not represent a major mechanism for residually-trapped gas transfer and remobilization. [ABSTRACT FROM AUTHOR]

Imbibition plays a central role during multiphase flows in geological media; yet, our understanding of imbibition dynamics across the multiscale features of rocks, including fractures, microcracks, and heterogeneous matrices is limited. Here, we deployed a unique combination of micro- and clinical X-ray CT imaging to probe directly the spatiotemporal evolution of imbibition in a natural, multiscale shale sample. The method enabled unraveling of mixed imbibition behavior, with spontaneous imbibition rates in the matrix pores and microcracks driven by capillarity proceeding as ∝ t − 1 / 2 , whereas pressure-driven flows in the macroscopic fractures yield apparent imbibition rates with ∝ t − 1 scaling. Regardless of the aperture, we showed that spontaneous imbibition proceeds uniformly away from the fractures. The effects of microcracks are further investigated by comparing the dynamics of the imbibition fronts with and without microcracks. These results highlight the paramount role of microcracks on anomalous front roughening and the need to account for microcracks appropriately in the development of predictive theoretical models. [Display omitted] • Unraveled μ m-scale mixed imbibition phenomena using X-ray CT techniques. • Pronounced imbibition dynamics, irrespective of the size of fracture apertures. • Micro-cracks played a dominant role in anomalous front broadening in shales. [ABSTRACT FROM AUTHOR]

[Display omitted] • Experiments with zone-level temperature set points in commercial buildings. • 385 daily samples are used to estimate the cyber-physical response of six buildings. • The uncertainty in building flexibility is quantified by statistical models. • Our stress test approach is a scalable method to estimate real life flexibility. Buildings represent over half of global electricity demand. Cooling buildings already accounts for over 9% of global electricity demand and is expected to grow rapidly due to climate-change induced hot-spells and increasing prosperity in developing economies. In the US, commercial buildings represent 35% of nationwide electricity consumption. Increased electricity demand for cooling services will challenge already stressed power grids, particularly during times of peak demand. This work explores the flexibility and demand response potential of large Heating, Ventilation and Air Conditioning (HVAC) systems based on an extensive set of measurements from six commercial buildings in a Warm-summer Mediterranean climate. Over a three-month summer period, zone-level temperature set points were adjusted daily in six commercial buildings to determine the effect on chilled water and electricity loads, as well as on zone-level temperatures. External weather conditions were measured continuously during the testing period. The experimental data that were collected are published with this article. These experiments confirmed the potential to provide flexibility by reducing energy demands based on modest zone-level temperature set point adjustments. A two-degree Fahrenheit increase of the cooling set point resulted in a 13–28% reduction in daily building-level cooling loads on average for four office buildings and 3–4% for two laboratory buildings. The impact on electric loads was less than 2% (excluding for cooling water but including for ventilation). Zone-level temperature increases were measurable but temperatures remained within the target ranges. By collecting 385 experiment-days of experiment data, we were able to parameterize statistical models for the response of the buildings. These models provide statistical guarantees on the reliability of thermal demand response. This work provides a blueprint for constructing building and zone-level energy-response functions and highlights the value of testing buildings repeatedly and across a range of weather conditions. Providing statistical performance guarantees will be critical for widespread adoption of demand response technology to provide the flexibility needed to meet peak electricity demands. Combined with thermal storage, the daily flexibility studied here would also unlock daily and sub-daily electrical flexibility, and can also be integrated with sub-daily flexibility from building-level electrical loads. [ABSTRACT FROM AUTHOR]

• Hub scale storage requires large-scale screening using a multi-stage workflow. • A quantitative, criteria-driven methodology allows for storage site selection. • Technical, regulatory, economic, and environmental constraints are considered. • Testing in the Gulf of Mexico identified 31 fields for further study. Carbon capture and sequestration (CCS) is playing a role in mitigating carbon emissions and that role is expected to grow dramatically with time. Clustering CO 2 sources and sinks through hubs is one way to achieve large-scale deployment of CCS and widespread decarbonization of the energy sector. A key element to the success of hub projects is finding a suitable sequestration site to store these combined emissions. In this study, a quantitative, criteria-driven methodology was developed to assess the potential suitability of depleted oil and gas reservoirs for carbon storage. The methodology utilizes a three-stage process that screens, ranks, and characterizes potential sites based on three categories: (1) capacity and injectivity optimization, (2) retention and geomechanical risk minimization, and (3) siting and economic constraints. Many potential sites are assessable using this methodology until an optimal depleted reservoir, or geographically adjacent set of reservoirs, is identified. The framework is designed to provide insights into the suitability of depleted reservoirs in a variety of different geological environments as well as to be adaptable to a project's specifications. Specifically, the criteria-driven workflow was applied to fields in the Gulf of Mexico and screened 1,317 fields to identify 10 clusters of 31 fields for further assessment and then ranked those fields and clusters to identify the most suitable sites for secure storage. [ABSTRACT FROM AUTHOR]

There is high demand for efficient, robust and automated routines for tomographic data reduction, particularly for synchrotron data. Registration of the rotation axis in data processing is a critical step affecting the quality of the reconstruction and is not easily implemented with automation. Existing methods for calculating the center of rotation have been reviewed and an improved algorithm to register the rotation axis in tomographic data is presented. The performance of the proposed method is evaluated using synchrotron-based microtomography data on geological samples with and without artificial reduction of the signal-to-noise ratio. The proposed method improves the reconstruction quality by correcting both the tilting error and the translational offset of the rotation axis. The limitation of this promising method is also discussed. [ABSTRACT FROM AUTHOR]

Numerical simulation of multiphase flow in porous media is essential for many geoscience applications. Machine learning models trained with numerical simulation data can provide a faster alternative to traditional simulators. Here we present U-FNO, a novel neural network architecture for solving multiphase flow problems with superior accuracy, speed, and data efficiency. U-FNO is designed based on the newly proposed Fourier neural operator (FNO), which has shown excellent performance in single-phase flows. We extend the FNO-based architecture to a highly complex CO 2 -water multiphase problem with wide ranges of permeability and porosity heterogeneity, anisotropy, reservoir conditions, injection configurations, flow rates, and multiphase flow properties. The U-FNO architecture is more accurate in gas saturation and pressure buildup predictions than the original FNO and a state-of-the-art convolutional neural network (CNN) benchmark. Meanwhile, it has superior data utilization efficiency, requiring only a third of the training data to achieve the equivalent accuracy as CNN. U-FNO provides superior performance in highly heterogeneous geological formations and critically important applications such as gas saturation and pressure buildup "fronts" determination. The trained model can serve as a general-purpose alternative to routine numerical simulations of 2D-radial CO 2 injection problems with significant speed-ups than traditional simulators. • U-FNO model for multiphase flow designed based on Fourier neural operator. • Data-efficient multiphase flow predictions for gas saturation and pressure buildup. • Results are significantly faster and more accurate than state-of-the-art CNNs. [ABSTRACT FROM AUTHOR]

Abstract: In this study, carbon dioxide exsolution from carbonated water is directly observed under reservoir conditions (9MPa and 45°C). Fluorescence microscopy and image analysis are used to quantitatively characterize bubble formation, morphology, and mobility. Observations indicate the strong influence of interfacial tension and pore-geometry on bubble growth and evolution. Most of the gas exhibits little mobility during the course of depressurization and clogs water flow paths. However, a snap-off mechanism mobilizes a small portion of the trapped gas along the water flow paths. This feature contributes to the transport of the dispersed exsolved gas phase and the formation of intermittent gas flow. A new definition of critical gas saturation is proposed accordingly as the minimum saturation that snap-off starts to produce mobile bubbles. Low mobility of the water phase and CO2 phase in exsolution is explained by formation of dispersed CO2 bubbles which block water flow and lack the connectivity to create a mobile gas phase. [Copyright &y& Elsevier]

Determination of representative saturation functions for permeable reservoir sandstones requires consideration of mm-cm scale laminations and crossbedding common in these heterogeneous porous media. Modelling selected laminated sandstones from CO2CRC's Otway International Test Centre in Victoria, Australia as bimodal composites of different rock types, we analyse drainage relative permeability parallel and perpendicular to the laminae for a range of driving gradients. The results from these numeric drainage experiments are curve fit across a continuous range of flow rates between the capillary and viscous limits. Our analysis shows that laminae-related small, but spatially correlated grainsize and permeability variations give rise to flow-rate dependent drainage behaviour at the bed scale. The flow direction- and rate-dependent behaviour is captured by a new set of anisotropic extended saturation functions that are implemented and presented in a form that is suitable for compositional simulation in the system CO 2 –H 2 O–NaCl. For the first time, these new constitutive relationships permit an investigation of feedbacks between the reservoir-scale flow regime and bed-scale phase mobility. To illustrate the application of these functions in reservoir simulation, meter-scale plume spreading simulations are presented for a suite of ten homogenised fluvial-to-estuarine sandstones from the Otway facility. • New flow-velocity dependent anisotropic relative permeability and p c. • The derived functions are suitable for compositional simulation. • Modelled flow behaviour spans full range of viscous/capillary force balances. • Model facilitates feedback between flow regime, sweep and displacement efficiency. • Upscaling impact of bedform heterogeneity of storage formations. [ABSTRACT FROM AUTHOR]

• Developed a macroscopic percolation simulator to quantify CO 2 residual trapping. • Models confirm trapping generally increases with the degree of heterogeneity. • Leaky capillary barriers prevent post-imbibition capillary heterogeneity trapping. • CO 2 residual trapping ability increase nonlinearly with the degree of heterogeneity. • Empirical residual trapping (linear or Land) relationships are scale dependent. Capillary heterogeneity trapping caused by mesoscale heterogeneity at the millimeter scale has been shown to have a great potential in immobilizing a significant amount of CO 2 in CO 2 geologic storage. The goal of this study is to develop and apply a macroscopic percolation simulator to better understand how post-imbibition CO 2 capillary heterogeneity trapping varies with different types and degrees of mesoscale heterogeneity as well as to quantify and compare its contribution to the pore-scale snap-off/bypass residual trapping mechanism. Using invasion percolation during drainage and ordinary percolation with macroscopic trapping during imbibition, the macroscopic percolation simulator can rapidly simulate both post-drainage and post-imbibition CO 2 saturation fields under capillary-gravity equilibrium, producing results that are validated by a full-physics reservoir simulator with a speedup of 10 to 100 times. The macroscopic percolation simulation results have shown that for domains that are completely uncorrelated or with nonleaky downstream capillary barriers, CO 2 heterogeneity trapping contribution always increases with the degree of heterogeneity of the domain. This is consistent with previous experimental results. However, the relationship between the CO 2 residual trapping ability of a domain also depends on the spatial structure of the heterogeneity and trapping ability does not always increase linearly with the degree of heterogeneity as previously shown. Additionally, when the capillary barrier is leaky, then regardless of the degree of heterogeneity, no extra capillary heterogeneity trapping can be achieved after long-term imbibition. Finally, this study demonstrates how residual trapping relationships may not be scale-invariant and calls for more sophisticated upscaling methods such as the macroscopic percolation simulation method presented here. [ABSTRACT FROM AUTHOR]

The elevated level of atmospheric carbon dioxide (CO2) has caused serious concern of the progression of global warming. Geological sequestration is considered as one of the most promising techniques for mitigating the damaging effect of global climate change. Investigations over wide range of length-scales are important for systematic evaluation of the underground formations from prospective CO2 reservoir. Understanding the relationship between the micro morphology and the observed macro phenomena is even more crucial. Here we show Synchrotron based X-ray micro tomographic study of the morphological buildup of Sandstones. We present a numerical method to extract the pore sizes distribution of the porous structure directly, without approximation or complex calculation. We have also demonstrated its capability in predicting the capillary pressure curve in a mercury intrusion porosimetry (MIP) measurement. The method presented in this work can be directly applied to the morphological studies of heterogeneous systems in various research fields, ranging from Carbon Capture and Storage, and Enhanced Oil Recovery to environmental remediation in the vadose zone. [ABSTRACT FROM AUTHOR]