TY  - JOUR
A1  - Afshari Moein, Mohammad J.
A1  - Somogyvári, Márk
A1  - Valley, Benoît
A1  - Jalali, Mohammadreza
A1  - Löw, Simon
A1  - Bayer, Peter
T1  - Fracture network characterization using stress-based tomography
JF  - Journal of geophysical research : JGR
N2  - Information on structural features of a fracture network at early stages of Enhanced Geothermal System development is mostly restricted to borehole images and, if available, outcrop data. However, using this information to image discontinuities in deep reservoirs is difficult. Wellbore failure data provides only some information on components of the in situ stress state and its heterogeneity. Our working hypothesis is that slip on natural fractures primarily controls these stress heterogeneities. Based on this, we introduce stress-based tomography in a Bayesian framework to characterize the fracture network and its heterogeneity in potential Enhanced Geothermal System reservoirs. In this procedure, first a random initial discrete fracture network (DFN) realization is generated based on prior information about the network. The observations needed to calibrate the DFN are based on local variations of the orientation and magnitude of at least one principal stress component along boreholes. A Markov Chain Monte Carlo sequence is employed to update the DFN iteratively by a fracture translation within the domain. The Markov sequence compares the simulated stress profile with the observed stress profiles in the borehole, evaluates each iteration with Metropolis-Hastings acceptance criteria, and stores acceptable DFN realizations in an ensemble. Finally, this obtained ensemble is used to visualize the potential occurrence of fractures in a probability map, indicating possible fracture locations and lengths. We test this methodology to reconstruct simple synthetic and more complex outcrop-based fracture networks and successfully image the significant fractures in the domain.
KW  - fracture network
KW  - Bayesian inversion
KW  - stress variability
KW  - rock mechanics
Y1  - 2018
U6  - https://doi.org/10.1029/2018JB016438
SN  - 2169-9313
SN  - 2169-9356
VL  - 123
IS  - 11
SP  - 9324
EP  - 9340
PB  - American Geophysical Union
CY  - Washington
ER  -