• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.50-59
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• 2006

The risk of fault reactivation in the Gippsland Basin was calculated using the FAST (Fault Analysis Seal Technology) technique, which determines fault reactivation risk by estimating the increase in pore pressure required to cause reactivation within the present-day stress field. The stress regime in the Gippsland Basin is on the boundary between strike-slip and reverse faulting: maximum horizontal stress $({\sim}\;40.5\;Mpa/km)$ > vertical stress (21 Mpa/km) ${\sim}$ minimum horizontal stress (20 MPa/km). Pore pressure is hydrostatic above the Campanian Volcanics of the Golden Beach Subgroup. The NW-SE maximum horizontal stress orientation $(139^{\circ}N)$ determined herein is broadly consistent with previous estimates, and verifies a NW-SE maximum horizontal stress orientation in the Gippsland Basin. Fault reactivation risk in the Gippsland Basin was calculated using two fault strength scenarios; cohesionless faults $(C=0;{\mu}=0.65)$ and healed faults $(C=5.4;\;{\mu}=0.78)$. The orientations of faults with relatively high and relatively low reactivation potential are almost identical for healed and cohesionless fault strength scenarios. High-angle faults striking NE-SW are unlikely to reactivate in the current stress regime. High-angle faults oriented SSE-NNW and ENE-WSW have the highest fault reactivation risk. Additionally, low-angle faults (thrust faults) striking NE-SW have a relatively high risk of reactivation. The highest reactivation risk for optimally oriented faults corresponds to an estimated pore pressure increase (Delta-P) of 3.8 MPa $({\sim}548\;psi)$ for cohesionless faults and 15.6 MPa $({\sim}2262\;psi)$ for healed faults. The absolute values of pore pressure increase obtained from fault reactivation analysis presented in this paper are subject to large errors because of uncertainties in the geomechanical model (in situ stress and rock strength data). In particular, the maximum horizontal stress magnitude and fault strength data are poorly constrained. Therefore, fault reactivation analysis cannot be used to directly measure the maximum allowable pore pressure increase within a reservoir. We argue that fault reactivation analysis of this type can only be used for assessing the relative risk of fault reactivation and not to determine the maximum allowable pore pressure increase a fault can withstand prior to reactivation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.