• Energy Research

Abstract Hydrocarbon depleted fractured shale (HDFS) formations could be attractive for geologic carbon dioxide (CO2) storage. Shale formations may be able to leverage existing infrastructure, have larger capacities, and be more secure than saline aquifers. We compared regional storage capacities and integrated CO2 capture, transport, and storage systems that use HDFS with those that use saline aquifers in a region of the United States with extensive shale development that overlies prospective saline aquifers. We estimated HDFS storage capacities with a production-based method and costs by adapting methods developed for saline aquifers and found that HDFS formations in this region might be able to store with less cost an estimated ∼14× more CO2 on average than saline aquifers at the same location. The potential for smaller Areas of Review and less investment in infrastructure accounted for up to 84% of the difference in estimated storage costs. We implemented an engineering-economic geospatial optimization model to determine and compare the viability of storage capacity for these two storage resources. Across the state-specific and regional scenarios we investigated, our results for this region suggest that integrated CCS systems using HDFS could be more centralized, require less pipelines, prioritize different routes for trunklines, and be 6.4–6.8% ($5-10/tCO2) cheaper than systems using saline aquifers. Overall, CO2 storage in HDFS could be technically and economically attractive and may lower barriers to large scale CO2 storage if they can be permitted.

CO2 capture and storage (CCS) is a climate-change mitigation technology that can significantly reduce greenhouse gas emissions in the near future. To have a meaningful impact, CCS infrastructure will have to be deployed on a massive scale; in the U.S. this will require capturing CO2 from hundreds of fossil fuel power plants and building a dedicated pipeline network to transport a volume of CO2 greater than domestic oil consumption. In this paper, we analyze the effect of geologic reservoir uncertainty on constructing CCS infrastructure—geologic uncertainty can impact reservoir cost and capacity estimates by as much as an order of magnitude. This uncertainty propagates through the capture–transport–storage system, influencing decisions including where and how much CO2 should be captured. We demonstrate the effect of geologic uncertainty using a proposed oil shale industry that could generate tens of millions of tonnes of CO2 each year. We show that uncertainty can make transport and storage costs deviate by over 100% and that CCS infrastructure, particularly the optimal pipeline network, can considerably diverge spatially. Finally, we draw conclusions on how geologic uncertainty may end up being a driving factor on how major industries decide to manage produced CO2.

We describe state-of-the-art science and technology related to modeling of CO2 capture and storage (CCS) at four different process scales: pore, reservoir, site, and region scale. We present novel research at each scale to demonstrate why each scale is important for a comprehensive understanding of CCS. Further, we illustrate research linking adjacent process scales, such that critical information is passed from one process scale to the next adjacent scale. We demonstrate this cross-scale approach using real world CO2 capture and storage data, including a scenario managing CO2 emissions from a large U.S. electric utility. At the pore scale, we present a new method for incorporating pore-scale surface tension effects into a relative permeability model of CO2-brine multiphase flow at the reservoir scale. We benchmark a reduced complexity model for site-scale analysis against a rigorous physics-based reservoir simulator, and include new system level considerations including local site-scale pipeline routing analysis (i.e., reservoir to site scale). We also include costs associated with brine production and treatment at the site scale, a significant issue often overlooked in CCS studies. All models that comprise our total system include parameter uncertainty which leads to results that have ranges of probability. Results suggest that research at one scale is able to inform models at adjacent process scales, and that these scale connections can inform policy makers and utility managers of overall system behavior including the impacts of uncertainty.

Efforts to mitigate the impacts of climate change will require deep reductions in anthropogenic CO2 emissions on the scale of gigatonnes per year. CO2 capture and utilization and/or storage technologies are a class of approaches that can substantially reduce CO2 emissions. Even though examples of this approach, such as CO2-enhanced oil recovery, are already being practiced on a scale >0.05 Gt/year, little attention has been focused on the supply of CO2 for these projects. Here, facility-scale data newly collected by the U.S. Environmental Protection Agency was processed to produce the first comprehensive map of CO2 sources from industrial sectors currently supplying CO2 in the United States. Collectively these sources produce 0.16 Gt/year, but the data reveal the presence of large areas without access to CO2 at an industrially relevant scale (>25 kt/year). Even though some facilities with the capability to capture CO2 are not doing so and in some regions pipeline networks are being built to link CO2 sources and sinks, much of the country exists in "CO2 deserts". A life cycle analysis of the sources reveals that the predominant source of CO2, dedicated wells, has the largest carbon footprint further confounding prospects for rational carbon management strategies.

AbstractThe increasing demand for bioenergy crops presents our society with the opportunity to design more sustainable landscapes. We have created a Biomass Location for Optimal Sustainability Model (BLOSM) to test the hypothesis that landscape design of cellulosic bioenergy crop plantings may simultaneously improve water quality (i.e. decrease concentrations of sediment, total phosphorus, and total nitrogen) and increase profits for farmer‐producers while achieving a feedstock‐production goal. BLOSM was run using six scenarios to identify switchgrass (Panicum virgatum) planting locations that might supply a commercial‐scale biorefinery planned for the Lower Little Tennessee (LLT) watershed. Each scenario sought to achieve different sustainability goals: improving water quality through reduced nitrogen, phosphorus, or sediment concentrations; maximizing profit; a balance of these conditions; or a balance of these conditions with the additional constraint of converting no more than 25% of agricultural land. Scenario results were compared to a baseline case of no land‐use conversion. BLOSM results indicate that a combined economic and environmental optimization approach can achieve multiple objectives simultaneously when a small proportion (1.3%) of the LLT watershed is planted with perennial switchgrass. The multimetric optimization approach described here can be used as a research tool to consider bioenergy plantings for other feedstocks, sustainability criteria, and regions. Published in 2012 by John Wiley & Sons, Ltd

AbstractWidespread adoption of carbon [dioxide] capture and storage (CCS) is limited by infrastructure, market, and cost barriers. Like most nascent technologies, it will be critical to overcome these barriers to fully realize the potential of CCS. Capturing CO2 from the oil refining process and using this CO2 for enhanced oil recovery (EOR) is an appealing scenario for knocking down these barriers, jumpstarting a CCS industry, and driving down the cost of CCS technology. CO2 capture from oil refineries can be relatively inexpensive when compared to other stationary sources (supply), EOR provides a market for CO2 (demand), and the spatial proximity of oil fields and refineries reduces transportation issues (cost, right of way, etc.). The oil industry should play a key role in the evolution of CCS since it has vested interests and experience with capturing, transporting, and injecting (and storing) CO2 underground.In this paper we study the deployment of CCS infrastructure to support CO2 capture from the oil refining industry and EOR and long term geologic storage of the CO2 for the US Gulf States. This region accounts for approximately 45% of US refining capacity, a large percentage of active EOR projects, and an extensive network of pipeline rights-of-way (natural gas, crude and refined oil) including over 80% of the existing CO2 pipelines. Presently, the oil industry predominantly uses natural sources of CO2 for EOR; an obvious goal of integrating CCS technology into the oil industry is displace the natural CO2 sources with anthropogenic CO2. The region is also responsible for approximately 450 Mt CO2 emissions annually from fossil-fuel electricity generation; an oil industry-driven CO2 market and CCS infrastructure could provide the necessary stimulus for capturing this CO2 in the coming decades.Our approach uses an economic-engineering model to geospatially deploy CCS infrastructure (capture, transportation, and storage) in response to a price on CO2 or a desired CO2 capture amount. The model considers and integrates each of the interdependent CCS components. It calculates at which oil refineries it is cost -effective to capture CO2, where and how new CO2 pipelines should be networked together, and which EOR oil fields balance CCS costs and CO2 credit as well as providing the best long term storage potential. The combination of capture, transport, and storage infrastructure is highly dependent on the CO2 price, both as an inducement (for EOR) and disincentive (price to emit CO2). Consequently, we examine how the expansion of CCS infrastructure could develop given differing CO2 scenarios, including variation in capture and storage costs. Our results show how a CO2 management network (capture, transport, and storage infrastructure) could develop given a set of oil refineries and EOR reservoirs in the US Gulf Coast region. The model outputs and results can be used to help plan policy and regulation for CO2 capture and storage, and help guide how the oil industry could jumpstart a CCS industry.

Abstract Wind is a clean, enduring energy resource with the capacity to satisfy 20% or more of U.S. electricity demand. Presently, wind potential is limited by a paucity of electrical transmission lines and/or capacity between promising wind resources and primary load centers. We present the model SimWIND to address this shortfall. SimWIND is an integrated optimization model for the geospatial arrangement and cost minimization of wind-power generation–transmission–delivery infrastructure. Given a set of possible wind-farm sites, the model simultaneously determines (1) where and how much power to generate and (2) where to build new transmission infrastructure and with what capacity in order to minimize the cost for delivering a targeted amount of power to load. Costs and routing of transmission lines consider geographic and social constraints as well as electricity losses. We apply our model to the Electric Reliability Council of Texas (ERCOT) Interconnection, considering scenarios that deliver up to 20 GW of new wind power. We show that SimWIND could potentially reduce ERCOT's projected ∼$5B transmission network upgrade line length and associated costs by 50%. These results suggest that SimWIND's coupled generation–transmission–delivery modeling approach could play a critical role in enhancing planning efforts and reducing costs for wind energy integration.

Like it or not, coal is here to stay, for the next few decades at least. Continued use of coal in this age of growing greenhouse gas controls will require removing carbon dioxide from the coal waste stream. We already remove toxicants such as sulfur dioxide and mercury, and the removal of CO₂ is the next step in reducing the environmental impacts of using coal as an energy source (i.e., greening coal). This paper outlines some of the complexities encountered in capturing CO₂ from coal, transporting it large distances through pipelines, and storing it safely underground.

This study develops a statistical method to perform uncertainty quantification for understanding CO2 storage potential within an enhanced oil recovery (EOR) environment at the Farnsworth Unit of the Anadarko Basin in northern Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil-water flow and reactive transport in the Morrow formation are conducted for global sensitivity and statistical analysis of the major uncertainty metrics: net CO2 injection, cumulative oil production, cumulative gas (CH4) production, and net water injection. A global sensitivity and response surface analysis indicates that reservoir permeability, porosity, and thickness are the major intrinsic reservoir parameters that control net CO2 injection/storage and oil/gas recovery rates. The well spacing and the initial water saturation also have large impact on the oil/gas recovery rates. Further, this study has revealed key insights into the potential behavior and the operational parameters of CO2 sequestration at CO2-EOR sites, including the impact of reservoir characterization uncertainty; understanding this uncertainty is critical in terms of economic decision making and the cost-effectiveness of CO2 storage through EOR. 9 pages, 6 figures, in press, Energy Procedia, 2014