CO2 Interim storage: Technical characteristics and potential role in CO2 market development

AbstractIn the absence of legislation that imposes a price on CO2 emissions, few significant economic incentives currently exist for largescale commercial application of CO2 Capture and Storage (CCS). A novel technique, currently under development, shows potential to add value to sequestered CO2, promote its utilization, and bridge the gap between its supply and demand, thus allowing the development of fully-integrated and reliable CO2 market. This technique is referred to as “ CO2 Interim Storage”, or briefly, CIS. CIS involves storing CO2 for a finite period of time to be subsequently utilized in CO2 Enhanced Oil Recovery (EOR) and potentially other industrial processes. The feasibility of CO2 storage is assessed based on three major variables: The distance between CO2 source and storage medium, the general trend of CO2 storage in and delivery from the storage medium (primarily governed by the market dynamics of supply and demand), as well as the frequency of CO2 injection into and extraction from the storage medium. The importance of CIS as a major tool for CO2 market and infrastructure development becomes clear upon comparing this new technology to the widely implemented underground natural gas (NG) storage and assessing its role in energy hybridization and in meeting variable and localized CO2 demand. In this study, the flow of CO2 in underground storage reservoirs is numerically simulated to provide general analysis of the technical aspects associated with varying CO2 injection rates. The simulations show that the CO2 plume and pressure buildup profiles are comparable for constant and variable injection rates. Also, in the cases of variable injection, the pressure variation dampens as injection proceeds with time. In addition, a casestudy is conducted in which CIS is implemented to meet the CO2 demand for EOR operations in the state of Wyoming from CO2 emissions of in-state coal power plants. This is achieved via modeling an integrated source-sink CO2 network. The results show that the economic attractiveness of the project is dependent on the availability of CO2, the distance between CO2 sources, interim storage sites, and sinks, as well as the price and demand of CO2 for EOR

Capacity investigation of brine-bearing sands of the Frio Formation for geologic sequestration of CO2

The capacity of fluvial brine-bearing formations to sequester CO2 is investigated using numerical simulations of CO2 injection and storage. Capacity is defined as the volume fraction of the subsurface available for CO2 storage and is conceptualized as a product of factors that account for two-phase flow and transport processes, formation geometry, formation heterogeneity, and formation porosity. The space and time domains used to define capacity must be chosen with care to obtain meaningful results, especially when comparing different authors’ work. Physical factors that impact capacity include permeability anisotropy and relative permeability to CO2, brine/CO2 density and viscosity ratios, the shape of the trapping structure, formation porosity and the presence of low permeability layering.National Energy Technology LaboratoryBureau of Economic Geolog

Optimization of electric vehicle charging in a fully (nearly) electric campus energy system

The goal of this work is to build a set of computational tools to aid decision making for the modelling and operations of integrated urban energy systems that actively interact with the power grid of the future. District heating and cooling networks incorporating heat recovery and large-scale thermal storage, such as the Stanford campus system, dramatically reduce energy waste and greenhouse gas emissions. They have historically played a small, but important role at a local level. Here we explore the potential for other co-benefits, including the provision of load following services to the electrical grid, carbon emissions reductions or demand charge management. We formulate and solve the problem of optimally scheduling daily operations for different energy assets under a demand-charge-based tariff, given available historical data. We also explore the interaction and interdependence of an electrified thermal energy network with actively managed power sources and sinks that concurrently draw from the same electrical distribution feeder. At Stanford University, large-scale electric vehicle charging, on-site photovoltaic generation and controllable building loads could each separately represent up to 5 MW, or 15% of the aggregate annual peak power consumption in the very near future. We cooptimize financial savings from peak power reductions and shifting consumption to lower price periods and assess the flexibility of both the different components and the integrated energy system as a whole. We find that thermal storage, especially complemented with electric vehicle charging, can play the role that is often proposed for electrochemical storage for demand charge management applications and quantitatively evaluate potential revenue generators for an integrated urban energy system. Although there is little value to smart charging strategies for low penetrations of electric vehicles, they are needed to avoid significant increases in costs once penetration reaches a certain threshold – in the Stanford case, 750-1,000 vehicles, or 25% of the vehicle commuter population

X-ray CT and multiphase flow characterization of a 'bio-grouted' sandstone core : the effect of dissolution on seal longevity

Microbially induced carbonate precipitation (MICP) is a novel method for controlling permeability in the subsurface with potential for sealing or reducing leakage from subsurface engineering works such as carbon sequestration reservoirs. The purpose of this research was to measure, at core scale, the change in reservoir permeability and capillary pressure due to MICP during seal formation, then to monitor the integrity of the seal when exposed to acidic groundwater capable of causing dissolution. The experiment was carried out with a Berea sandstone core mounted in a high pressure core holder within a medical X-ray CT scanner. Multiple full volume CT scans gave spatially resolved maps of the changing porosity and saturation states throughout the experiment. Porosity and permeability decreased with MICP whilst capillary pressure was increased. Dissolution restored much of the original porosity, but not permeability nor capillary pressure. This lead to the conclusion that injection pathways were coupled with carbonate precipitation hence preferential flow paths sealed first and transport of the dissolution fluid was limited. Provided a high enough reduction in permeability can be achieved over a substantial volume, MICP may prove to be a durable bio-grout, even in acidic environments such as a carbon sequestration reservoir

Characterization of CO2 storage properties using core analysis techniques and thin section data

AbstractCarbon dioxide capture and sequestration in saline aquifers is considered one of the most important technologies for short and medium term climate change mitigation. There are many challenges for wide scale deployment of sequestration, including developing a sufficiently accurate fundamental understanding of the processes which govern the movement of supercritical CO2 in saline aquifers. A method for testing our understanding of the underlying physics is to conduct numerical simulations intended to replicate a multiphase flow experiment in which CO2 is injected into a brine saturated rock core. This paper focuses on methods to integrate pore scale rock properties into permeability models of cores subjected to such experiments. We use thin sections to measure pore scale features of rocks, and test correlations that relate permeability to porosity using the Carman–Kozeny equation. Incorporation of these pore scale features into sub-core scale maps of permeability is being used to history match core-scale multi-phase flow experiments

Real-time high-resolution CO2_2 geological storage prediction using nested Fourier neural operators

Carbon capture and storage (CCS) plays an essential role in global decarbonization. Scaling up CCS deployment requires accurate and high-resolution modeling of the storage reservoir pressure buildup and the gaseous plume migration. However, such modeling is very challenging at scale due to the high computational costs of existing numerical methods. This challenge leads to significant uncertainties in evaluating storage opportunities, which can delay the pace of large-scale CCS deployment. We introduce Nested Fourier Neural Operator (FNO), a machine-learning framework for high-resolution dynamic 3D CO2 storage modeling at a basin scale. Nested FNO produces forecasts at different refinement levels using a hierarchy of FNOs and speeds up flow prediction nearly 700,000 times compared to existing methods. By learning the solution operator for the family of governing partial differential equations, Nested FNO creates a general-purpose numerical simulator alternative for CO2 storage with diverse reservoir conditions, geological heterogeneity, and injection schemes. Our framework enables unprecedented real-time modeling and probabilistic simulations that can support the scale-up of global CCS deployment

The role of optimality in characterizing CO2 seepage from geological carbon sequestration sites

Storage of large amounts of carbon dioxide (CO{sub 2}) in deep geological formations for greenhouse gas mitigation is gaining momentum and moving from its conceptual and testing stages towards widespread application. In this work we explore various optimization strategies for characterizing surface leakage (seepage) using near-surface measurement approaches such as accumulation chambers and eddy covariance towers. Seepage characterization objectives and limitations need to be defined carefully from the outset especially in light of large natural background variations that can mask seepage. The cost and sensitivity of seepage detection are related to four critical length scales pertaining to the size of the: (1) region that needs to be monitored; (2) footprint of the measurement approach, and (3) main seepage zone; and (4) region in which concentrations or fluxes are influenced by seepage. Seepage characterization objectives may include one or all of the tasks of detecting, locating, and quantifying seepage. Each of these tasks has its own optimal strategy. Detecting and locating seepage in a region in which there is no expected or preferred location for seepage nor existing evidence for seepage requires monitoring on a fixed grid, e.g., using eddy covariance towers. The fixed-grid approaches needed to detect seepage are expected to require large numbers of eddy covariance towers for large-scale geologic CO{sub 2} storage. Once seepage has been detected and roughly located, seepage zones and features can be optimally pinpointed through a dynamic search strategy, e.g., employing accumulation chambers and/or soil-gas sampling. Quantification of seepage rates can be done through measurements on a localized fixed grid once the seepage is pinpointed. Background measurements are essential for seepage detection in natural ecosystems. Artificial neural networks are considered as regression models useful for distinguishing natural system behavior from anomalous behavior suggestive of CO{sub 2} seepage without need for detailed understanding of natural system processes. Because of the local extrema in CO{sub 2} fluxes and concentrations in natural systems, simple steepest-descent algorithms are not effective and evolutionary computation algorithms are proposed as a paradigm for dynamic monitoring networks to pinpoint CO{sub 2} seepage areas

Well blowout rates and consequences in California Oil and Gas District 4 from 1991 to 2005: Implications for geological storage of carbon dioxide

Well blowout rates in oil fields undergoing thermally enhanced recovery (via steam injection) in California Oil and Gas District 4 from 1991 to 2005 were on the order of 1 per 1,000 well construction operations, 1 per 10,000 active wells per year, and 1 per 100,000 shut-in/idle and plugged/abandoned wells per year. This allows some initial inferences about leakage of CO2 via wells, which is considered perhaps the greatest leakage risk for geological storage of CO2. During the study period, 9% of the oil produced in the United States was from District 4, and 59% of this production was via thermally enhanced recovery. There was only one possible blowout from an unknown or poorly located well, despite over a century of well drilling and production activities in the district. The blowout rate declined dramatically during the study period, most likely as a result of increasing experience, improved technology, and/or changes in safety culture. If so, this decline indicates the blowout rate in CO2-storage fields can be significantly minimized both initially and with increasing experience over time. Comparable studies should be conducted in other areas. These studies would be particularly valuable in regions with CO2-enhanced oil recovery (EOR) and natural gas storage