Researchers propose framework for CCS infrastructure optimization to reduce GHG emissions from oil sands extraction and processing
Two researchers from Los Alamos National Laboratory and Stanford University have developed an integrated framework that simultaneously considers economic and engineering decisions for the capture, transport, and storage of oil sands CO2 emissions (CCS). The model, developed by Richard Middleton (LANL) and Adam Brandt (Stanford) optimizes CO2 management infrastructure at a variety of carbon prices for the oil sands industry.
In a paper published in the ACS journal Environmental Science & Technology, they report that the oil sands industry lends itself well to development of CO2 trunk lines due to geographic coincidence of sources and sinks. This reduces the relative importance of transport costs compared to nonintegrated transport systems.
The amount of managed oil sands CO2 emissions, and therefore the CCS infrastructure, is very sensitive to the carbon price; significant capture and storage occurs only above 110$/tonne CO2 in their simulations. Deployment of infrastructure is also sensitive to CO2 capture decisions and technology, particularly the fraction of capturable CO2 from oil sands upgrading and steam generation facilities. The framework will help stakeholders and policy makers understand how CCS infrastructure, including an extensive pipeline system, can be safely and cost-effectively deployed, they suggest.
The Alberta oil sands industry is expected to rapidly expand in coming decades; production could double or more in the next 10−15 years alone. Thus, there will be an ever-increasing need to reduce the environmental impacts, in particular CO2 emissions. This expansion means there will be many new and large CO2 sources coming online, sources which should be integrated into an iterative, time-dependent version of our framework. In that case, the benefits of sensible planning and system-wide optimization will be even larger when compared to piecemeal unoptimized infrastructure development.
This time-dependent model would likely show interesting results, such as the early “over-building” of infrastructure like CO2 trunk lines, in order to accommodate larger capture and storage volumes in the future. In addition, future work should account for the co-benefits associated with CO2 utilization (e.g., EOR); EOR can reduce CO2 management cost for early adopters of CCS as well as reduce the carbon footprint associated with conventional oil production.—Middleton and Brandt
Their work integrated four streams of scientific research to improve understanding how the cost of CO2 emissions mitigation varies with the size and extent of CO2 infrastructure in the oil sands region. They developed a suite of optimal infrastructure investment plans for capturing, transporting, and injecting/storing up to 36 MtCO2/yr from the Alberta oil sands industry.
The study is divided into four sequential steps:
Analysis of the engineering and economics of capturing CO2 from the oil sands industry.
Identification of a set of spatially dispersed reservoirs capable of securely storing oil sands CO2 emissions. These sites are characterized using a combination of existing acid gas injection data and the CO2-PENS risk assessment model.
Identify of a candidate network of routes where CO2 pipelines could be constructed.
Use of the SimCCS optimization framework to integrate CO2 capture, storage, and transportation decisions in order to understand how the oil sands industry might respond to six different prices on CO2 emissions.
Among their findings were that:
At a low CO2 price, only the most cost-effective CO2 streams are captured, while only a relatively short pipeline network is needed to transport CO2 to favorable storage reservoirs.
Generally, CO2 is first captured (1.6 MtCO2/yr, a 4% reduction in CO2 emissions) when the emissions price reaches $38/ tCO2—a much higher price than Alberta’s $15/tCO2 “tax”. Even though the capture cost is only $19.74/tCO2, the cost to transport ($14.70/tCO2) is high because a 488 km pipeline network is required.
Until the emissions price reaches $62/tCO2, no additional CO2 is captured—i.e., it is cheaper to pay the emissions tax rather than install CCS infrastructure.
Between the $80 and $85/tCO2 scenarios, captured CO2 rises from 2.4 to 9.0 MtCO2/yr, although the network length increases only from 541 to 563 km—i.e., larger pipeline along same trunk line route. In other words, a relatively small increase ($5/tCO2) in the CO2 tax has a large impact on CCS infrastructure (almost four times more CO2 captured) and CO2 emissions in this case study; at 9.0 MtCO2/yr, total CO2 emissions are reduced by 23%).
The $113/tCO2 scenario captures 19.6 MtCO2/yr (50% emissions reduction), while the $110/tCO2 scenario manages 10.6 MtCO2/yr or 27% of emissions). This large increase in captured CO2 not only increases the network length to 758 km, the main trunk line now takes a more easterly route compared to all previous scenarios. Three new sinks are used for the first time, and one of the two sinks used in previous scenarios is no longer cost-optimal.
Increasing the tax to just $114/tCO2 significantly increases managed CO2 (24.5 MtCO2/yr, 61% emissions reduction), network length (854 km), as well as pushing the major trunk line back to the typical westerly route.
The rapid increase in captured CO2 relative to small changes in the CO2 price can be explained by the step function of the capturable CO2 amounts and the extra costs incurred to transport larger amounts of CO2. The maximum amount of captured CO2 (i.e., 90% reduction in CO2 emissions) is achieved when the tax rises to $155/tCO using a 1239 km pipeline network and seven storage reservoirs. At high capture rates, economies of scale in transport infrastructure are observed: instead of a web of pipelines being built, the most cost-effective system design relies on a relatively small number of large-diameter “trunk” lines that serve to move bulk CO2 from the concentration of sources to the concentration of sinks. Even when all CO2 emissions are captured, expensive sinks...and distant sinks...are never utilized.
The use of infrastructure optimization techniques can help the oil sands industry reduce their carbon footprint and assists policy makers and regulators in understanding how best to set a price for CO2 emissions. Our results clearly show the benefits of building an integrated, large-scale system, rather than “one-off” pipelines between sources and sinks. Planning with foresight will aid in reducing the impacts of CO2 emissions from oil sands operations at least cost (economically and environmentally) to society and consumers.—Middleton and Brandt
Richard S. Middleton and Adam R. Brandt (2012) Using Infrastructure Optimization to Reduce Greenhouse Gas Emissions from Oil Sands Extraction and Processing. Environmental Science & Technology doi: 10.1021/es3035895