skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Putting the genie back in the bottle: Decarbonizing petroleum with direct air capture and enhanced oil recovery
This study reports the cradle-to-wheel life cycle greenhouse gas (GHG) emissions resulting from enhanced oil recovery (EOR) using CO2 sourced from direct air capture (DAC). A Monte Carlo simulation model representing variability in technology, location, and supply chain is used to model the possible range of carbon intensities (CI) of oil produced through DAC-EOR. Crude oil produced through DAC-EOR is expected to have a CI of 449 tCO2/ mbbl. With 95% confidence, the CI is between 345 tCO2/mbbl to 553 tCO2/mbbl. Producing net-zero GHG emission oil through DAC-EOR is thus highly improbable. An example case of DAC-EOR in the U.S. Permian Basin shows that only in the unlikely instance of the most storage efficient sites using 100% renewable energy does DAC-EOR result in “carbon-negative” oil production.  more » « less
Award ID(s):
2132022
PAR ID:
10635079
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
Elsevier
Date Published:
Journal Name:
International Journal of Greenhouse Gas Control
Volume:
139
Issue:
C
ISSN:
1750-5836
Page Range / eLocation ID:
104281
Subject(s) / Keyword(s):
direct air capture enhanced oil recovery maximum entropy distribution Monte Carlo simulation life cycle assessment carbon intensity
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. (, SPE)
    This study introduces an innovative physics-informed machine learning approach to predict the cumulative oil production, CO2 stored, and CO2 adsorbed during CO2 injection. The developed model can be utilized to maximize both oil recovery and CO2 storage in naturally fractured reservoirs (NDR). While existing research has largely focused on maximizing oil recovery and net present value (NPV) through CO2 injection, our methodology integrates comprehensive physics data to fine-tune gas injection processes. We consider a wide span of reservoir characteristics in five-spot injection pattern. We developed dual-permeability, naturally fractured numerical compositional models incorporating sorption to simulate flow mechanisms during injection accurately. Using Langmuir's adsorption dynamics in our simulation integrates well designs and injection strategies. Data from these simulations were trained using Artificial Neural Networks (ANN) to create a robust production prediction proxy model for different gas injection designs. The ANN model demonstrates high accuracy, reflecting its potential for optimizing oil production and carbon storage. The developed model facilitated the screening and optimization process for the considered system as it provides the optimized design in a few seconds compared to days. This study not only highlights the cost-efficiency of using machine learning algorithms in optimization processes but also deepens our understanding of their potential applications in enhanced oil recovery (EOR) and carbon capture and storage (CCUS). The developed models can be used to provide new insights into the interactions between fluid compositions and the complex physical phenomena of sorption, underscoring the transformative potential of integrating advanced machine learning with traditional petroleum engineering techniques. 
    more » « less
  2. ; ; ; ; ; ; ; ; (, Applied Sciences)
    With increasing energy demands and depleting oil accessibility in reservoirs, the investigation of more effective enhanced oil recovery (EOR) methods for deep and tight reservoirs is imminent. This study investigates a novel hybrid EOR method, a synergistic approach of nonionic surfactant flooding with intermediate CO2-based oil swelling. This study is focused on the efficiency of surfactant flooding and low-pressure oil swelling in oil recovery. We conducted a fluorescence-based microscopic analysis in a microchannel to explore the effect of sodium dodecyl sulfate (SDS) surfactant on CO2 diffusion in Texas crude oil. Based on the change in emission intensity of oil, the results revealed that SDS enhanced CO2 diffusion at low pressure in oil, primarily due to SDS aggregation and reduced interfacial tension at the CO2 gas–oil interface. To validate the feasibility of our proposed EOR method, we adopted a ‘reservoir-on-a-chip’ approach, incorporating flooding tests in a polymethylmethacrylate (PMMA)-based micromodel. We estimated the cumulative oil recovery by comparing the results of two-stage surfactant flooding with intermediate CO2 swelling at different pressures. This novel hybrid approach test consisted of a three-stage sequence: an initial flooding stage, followed by intermediate CO2 swelling, and a second flooding stage. The results revealed an increase in cumulative oil recovery by nearly 10% upon a 2% (w/v) solution of SDS and water flooding compared to just water flooding. The results showed the visual phenomenon of oil imbibition during the surfactant flooding process. This innovative approach holds immense potential for future EOR processes, characterized by its unique combination of surfactant flooding and CO2 swelling, yielding higher oil recovery. 
    more » « less
  3. ; ; ; (, Proceedings of the National Academy of Sciences)
    Research investments in crop improvements, including by national and international agricultural research centers, have made significant contributions to raising yields of staple food crops in developing countries. Although mostly intended to improve food security and rural incomes, innovations in crop production also have major implications for the environment. Building on the latest productivity estimates from historical crop improvements in developing countries and using a gridded (0.25 degrees) equilibrium model of global agriculture, we assess the impacts of improved crop varieties on cropland use, threatened biodiversity, and terrestrial carbon stocks over 1961–2015. We replicate a historical baseline and produce a counterfactual scenario which shows the impact of omitting productivity improvements from these technologies. The results show that higher crop productivity generally lowered commodity prices, which reduced incentives to expand cropland except in those areas where productivity gains outweighed price declines. The net global effect of technology adoption was to limit conversion of natural habitat to agricultural use, although it did cause cropland to expand in some areas. We estimate that adoption of improved crop varieties in developing countries saved on net 16.03 [95% CI, 12.33 to 20.89] million hectares worldwide. With more natural habitat preserved, around 1,043 [95% CI, 616 to 1,503] threatened animal and plant species extinctions were avoided over this period. In addition, net land use savings from the improved crop varieties resulted in avoided terrestrial greenhouse gas (GHG) emissions of around 5.35 [95% CI, 3.75 to 7.22] billion metric tons CO2equivalent retained in terrestrial carbon stocks. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, Science Advances)
    The rising atmospheric CO2concentration is one of the biggest challenges human civilization faces. Direct air capture (DAC) that removes CO2from the atmosphere provides great potential in carbon neutralization. However, the massive land use and capital investment of centralized DAC plants and the energy-intensive process of adsorbent regeneration limit its wide employment. We develop a distributed carbon nanofiber (CNF)–based DAC air filter capable of adsorbing CO2downstream in ventilation systems. The DAC air filter not only has the potential to remove 596 MtCO2year−1globally but can also decrease energy consumption in existing building systems. The CNF-based adsorbent has a capacity of 4 mmol/g and can be regenerated via solar thermal or electrothermal methods with low carbon footprints. Through life cycle assessment, the CNF air filter shows a carbon removal efficiency of 92.1% from cradle to grave. Additionally, techno-economic analysis estimates a cost of $209 to 668 in capturing and storing 1 tonne of CO2from direct air. 
    more » « less
  5. ; ; ; ; ; (, Journal of the American Chemical Society)
    Escalating carbon dioxide (CO2) emissions have intensified the greenhouse effect, posing a significant long-term threat to environmental sustainability. Direct air capture (DAC) has emerged as a promising approach to achieving a net-zero carbon future, which offers several practical advantages, such as independence from specific CO2 emission sources, economic feasibility, flexible deployment, and minimal risk of CO2 leakage. The design and optimization of DAC sorbents are crucial for accelerating industrial adoption. Metal-organic frameworks (MOFs), with high structural order and tunable pore sizes, present an ideal solution for achieving strong guest-host interactions under trace CO2 conditions. This perspective highlights recent advancements in using MOFs for DAC, examines the molecular-level effects of water vapor on trace CO2 capture, reviews data-driven computational screening methods to develop a molecularly programmable MOF platform for identifying optimal DAC sorbents, and discusses scale-up and cost of MOFs for DAC. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email