Abstract
NMR (Nuclear magnetic resonance) is widely used as a logging tool in reservoir exploration and provides information on pore size distribution, fluid distribution, and insights into wettability. Towards better utilizing NMR log data, it is essential to assess the current models of NMR relaxation. To this end, we explicitly calculate the NMR dipole-dipole relaxation in model hydrocarbons and water for single state points and dipole-dipole and spin-rotation relaxation in methane for a range of state-points spanning the vapor, super-critical, and liquid phases. We can successfully predict 1H NMR T1,2 relaxation and diffusion, but the relaxation behavior siginificantly deviate from those based on classical hard sphere models that are often used to interpret the relaxation behavior.
Original language | English |
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Pages | 101-102 |
Number of pages | 2 |
DOIs | |
State | Published - 2018 |
Externally published | Yes |
Event | SEG/AAPG/EAGE/SPE Research and Development Petroleum Conference and Exhibition 2018, RDP 2018 - Abu Dhabi, United Arab Emirates Duration: May 9 2018 → May 10 2018 |
Conference
Conference | SEG/AAPG/EAGE/SPE Research and Development Petroleum Conference and Exhibition 2018, RDP 2018 |
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Country/Territory | United Arab Emirates |
City | Abu Dhabi |
Period | 05/9/18 → 05/10/18 |
Funding
This work was funded by the Rice University Consortium on Processes in Porous Media, and the American Chemical Society Petroleum Research Fund [ACS-PRF-58859-ND6]. We gratefully acknowledge the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U. S. Department of Energy [DE-AC02-05CH11231] for HPC time and support. We also gratefully acknowledge the Texas Advanced Computing Center (TACC) at the University of Texas at Austin (www.tacc.utexas.edu) for providing HPC resources.
Funders | Funder number |
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National Energy Research Scientific Computing Center | |
U. S. Department of Energy | |
U.S. Department of Energy | DE-AC02-05CH11231 |
Office of Science | |
Advanced Scientific Computing Research | |
American Chemical Society Petroleum Research Fund | ACS-PRF-58859-ND6 |
Rice University |