Characterizing and Interpreting the In Situ Strain Tensor During CO2 Injection
- Clemson University, SC (United States)
- East Carolina University, Greenville, NC (United States)
Injecting fluid into a well creates an evolving strain tensor field in the rocks enveloping the well. Understanding the strain field has the potential to improve the effectiveness of CO2 storage, but the strain tensor had never been measured during injection. The objective of this project was to evaluate how the strain tensor can be measured and interpreted to improve the assessment of geomechanical properties and advance an understanding of geomechanical processes that may present risks to CO2 storage. The project consisted of three primary tasks related to 1) developing instruments for measuring the strain tensor with high precision; 2) developing methods for analyzing strain signals; and 3) demonstrating the approach at a CO2 storage analog site.
- Research Organization:
- Clemson Univ., SC (United States)
- Sponsoring Organization:
- USDOE Office of Fossil Energy (FE), Clean Coal and Carbon Management
- DOE Contract Number:
- FE0023313
- OSTI ID:
- 1529100
- Report Number(s):
- DE-FE0023313
- Resource Relation:
- Related Information: FDSN/IRIS for all raw data: 10.7914/SN/2J_20161A Shut-In: March 31 thru April 7, 2017: 10.18141/15053739A Injection: October 11 thru October 17, 2017: 10.18141/15053749A Injection: November 28 thru December 1, 2017: 10.18141/15053759A Injection: June 28 thru July 23, 2018: 10.18141/1505376
- Country of Publication:
- United States
- Language:
- English
Similar Records
Robust In-Situ Strain Measurements to Monitor CO2 Storage
Feasibility of using in situ deformation to monitor CO2 storage
Related Subjects
20 FOSSIL-FUELED POWER PLANTS
42 ENGINEERING
47 OTHER INSTRUMENTATION
54 ENVIRONMENTAL SCIENCES
58 GEOSCIENCES
97 MATHEMATICS AND COMPUTING
99 GENERAL AND MISCELLANEOUS
carbon storage
strain
stress
reservoir characterization
monitoring
deformation
seismicity
faulting
well testing
strainmeter
strain instrument
inversion
poroelastic
stochastic inversion
asymptotic analysis