Unified Reservoir And Seismic Simulation With Explicit Representation Of Fractures And Faults

In the context of remote sensing, the vast disparity in characteristic scales between seismic deformation (e.g. milliseconds) and transient flow (e.g. hours) allows a "two-model paradigm" for geophysics and reservoir simulation. In the context of flow-induced geohazard risk mitigation and micro-seismic data integration, this paradigm breaks down. Under micro-seismic deformation, events occur with high-frequency, and over sustained duration during which the rock-fluid coupling is significant. In risk mitigation scenarios, the onset of seismic deformation is directly tied to quasi-static coupling periods. This work develops an approach to reservoir simulation modeling that allows simultaneous resolution of transient (inertial) poromechanics and multiphase fluid flow in the presence of fracture. A mixed discretization scheme combining the extended finite element method (XFEM) and the embedded discrete fracture model (EDFM) is extended using a second-order implicit Newmark time integration scheme for the inertial mechanics. A Lagrange multiplier method is developed to model pressure-dependent contact traction in fractures. The contact constraints are adapted to accommodate fracture opening. Slip-weakening fracture friction models are incorporated. Finally, a time-step controller is proposed to combine local discretization error with contact traction and slip-rate control along the fractures. This strategy allows automatic adaptation to resolve quasi-static, inter-seismic triggering, and co-seismic spontaneous rupture periods within one model. The model is verified to simulate complete induced earthquake sequences, including inter-seismic and dynamic rupture phases. The performance of the adaptive model is illustrated for cases with various set-ups of production and injection periods in a fractured reservoir with explicit fracture representation.

A MPM framework for large deformation seismic response analysis

Landslides are often triggered by earthquakes and can cause immense damage due to large mass movements. To model such large-deformation events, the material point method (MPM) has become increasingly popular in recent years. A limitation of existing MPM implementations is the lack of appropriate boundary conditions to perform seismic response analysis of slopes. In this article, an extension to the basic MPM framework is proposed for simulating the seismic triggering and subsequent collapse of slopes within a single analysis step. Original implementations of a compliant base boundary and free-field boundary conditions in the MPM framework are presented, enabling the application of input ground motions while accounting for the absorption of outgoing waves and the free-ground movement at the lateral boundaries. An example slope is analysed to illustrate the proposed procedure and to benchmark it against the results obtained using an independent simulation technique, based on a three-step FE analysis. The comparison generally shows a good agreement of the results obtained from the two independent procedures and highlights advantages of the presented “all-in-one” MPM approach, in particular for long duration strong motions.

Realignments of the Colorado River by ~2 m.y. of rotational bedrock landsliding: The Surprise Valley landslide complex, Grand Canyon, Arizona

The Surprise Valley landslide complex is the name used here for a group of prominent river-damming landslides in Grand Canyon (Arizona, USA) that has shifted the path of the Colorado River several times in the past 2 m.y. We document a sequence of eight landslides. Three are Toreva-block landslides containing back-rotated but only mildly disrupted bedrock stratigraphy. The largest of these landslides, Surprise Valley landslide, is hypothesized to have dammed the Colorado River, cut off a meander loop through Surprise Valley, and rerouted the river 2.5 km south to near its present course at the Granite Narrows. Another bedrock landslide, Poncho’s runup, involved a mass detachment from the north side of the river that drove a kilometer-scale bedrock slab across the river and up the south canyon wall to a height of 823 m above the river. A lake behind this landslide is inferred from the presence of mainstem gravels atop the slide that represent the approximate spillway elevation. We postulate that this landslide lake facilitated the upriver 133 Mile slide detachment and Toreva block formation. The other five landslides are subsequent slides that consist of debris from the primary slides; these also partially blocked and diverted the Colorado River as well as the Deer Creek and Tapeats Creek tributaries into new bedrock gorges over the past 1 m.y. The sequence of landslides is reconstructed from inset relationships revealed by geologic mapping and restored cross-sections. Relative ages are estimated by measuring landslide base height above the modern river level in locations where landslides filled paleochannels of the Colorado River and its tributaries. We calculate an average bedrock incision rate of 138 m/m.y. as determined by a 0.674 ± 0.022 Ma detrital sanidine maximum depositional age of the paleoriver channel fill of the Piano slide, which has its base 70 m above the river level and ~93 m above bedrock level beneath the modern river channel. This date is within error of, and significantly refines, the prior cosmogenic burial date of 0.88 ± 0.44 Ma on paleochannel cobbles. Assuming steady incision at 138 m/m.y., the age of Surprise Valley landslide is estimated to be ca. 2.1 Ma; Poncho’s runup is estimated to be ca. 610 ka; and diversion of Deer Creek to form modern Deer Creek Falls is estimated to be ca. 400 ka. The age of the most recent slide, Backeddy slide, is estimated to be ca. 170 ka based on its near-river-level position. Our proposed triggering mechanism for Surprise Valley landslides involves groundwater saturation of a failure plane in the weak Bright Angel Formation resulting from large volumes of Grand Canyon north-rim groundwater recharge prior to establishment of the modern Deer, Thunder, and Tapeats springs. Poncho’s and Piano landslides may have been triggered by shale saturation caused by 600–650 ka lava dams that formed 45 river miles (73 river km; river miles are measured along the Colorado River downstream from Lees Ferry, with 1 river mile = 1.62 river kms) downstream near Lava Falls. We cannot rule out effects from seismic triggering along the nearby Sinyala fault. Each of the inferred landslide dams was quickly overtopped (tens of years), filled with sediment (hundreds of years), and removed (thousands of years) by the Colorado River, as is also the potential fate of modern dams.

Remote Triggering of Icequakes at Mt. Erebus, Antarctica by Large Teleseismic Earthquakes

Recent studies have shown that the Antarctic cryosphere is sensitive to external disturbances such as tidal stresses or dynamic stresses from remote large earthquakes. In this study, we systematically examine evidence of remotely triggered microseismicity around Mount (Mt.) Erebus, an active high elevation stratovolcano located on Ross Island, Antarctica. We detect microearthquakes recorded by multiple stations from the Mt. Erebus Volcano Observatory Seismic Network one day before and after 43 large teleseismic earthquakes, and find that seven large earthquakes (including the 2010 Mw 8.8 Maule, Chile, and 2012 Mw 8.6 Indian Ocean events) triggered local seismicity on the volcano, with most triggered events occurring during the passage of the shorter-period Rayleigh waves. In addition, their waveforms and locations for the triggered events are different when comparing with seismic events arising from the persistent small-scale eruptions, but similar to other detected events before and after the mainshocks. Based on the waveform characteristics and their locations, we infer that these triggered events are likely shallow icequakes triggered by dilatational stress perturbations from teleseismic surface waves. We show that teleseismic earthquakes with higher peak dynamic stress changes are more capable of triggering icequakes at Mt. Erebus. We also find that the icequakes in this study are more likely to be triggered during the austral summer months. Our study motivates the continued monitoring of Mount Erebus with dense seismic instrumentation to better understand interactions between dynamic seismic triggering, crospheric processes, and volcanic activity.

Simulation of Instant and Delayed Seismic Triggering Observed After the 30 October 2020 Samos Earthquake at Nearby Faults

<p>The 30 October 2020 Samos Earthquake (Mw=7.0) ruptured a north-dipping offshore normal fault, north of the Samos Island with an extensional mechanism. Aftershocks mainly occurred at the western and eastern ends of the rupture plane in agreement with the Coulomb static stress changes. Mechanism of aftershocks located west of the rupture area supported activation of the neighboring strike-slip fault almost instantly. In addition, a seismic cluster including events with magnitudes reaching close to 4 has emerged fifty hours later at the SE side of Samos Island. This off-plane cluster displays a clear example of delayed seismic triggering that produced small magnitude earthquakes at nearby active faults. In this study, numerical simulations are conducted using rate-and-state friction dependent quasi-static&full-dynamic spring slider model with shear-normal stress coupling to mimic the instant and delayed seismic triggering observed after this event. Coulomb static stress changes and seismic waveforms recorded at nearby strong-motion stations are used as static and dynamic triggers during simulations. According to our results, earthquakes with Mw<3.5 can be triggered almost instantly at the rupture edge and failure time of earthquakes with Mw>3.5 advances for both strike-slip and normal faults which may explain the delayed triggering observed SE of Samos Island. Moreover, simulations revealed that the shear-normal stress coupling increases the triggering potential.</p>

Seismic repeaters linked to weak rock-mass creep in deep excavation mining

SUMMARY Seismic repeaters are a phenomenon rarely observed in mining environments. In this study, we show that repeaters and associated aseismic slip can be the governing mechanism behind seismic triggering in response to excavation mining, providing new perspectives for rethinking and improving standard procedures for seismic rock burst hazard assessment and mining monitoring. Evidence comes from an extensive multiplet analysis on dense spatiotemporal microseismic event clusters (−2.5 < Mw < 1) that was recorded by a local microseismic network at the Lappberget orebody in the Garpenberg mine in Sweden at around 1 km depth. Analysis involved template matching, clustering, double-difference relocation, source parameter and mechanism estimation, as well as interevent time analysis. The results show that almost 80 per cent of the analysed events can be interpreted as seismic repeaters. Source mechanisms demonstrate systematic strike-slip faulting with a significant reverse faulting component, indicating that triggering of the repeaters is sensitive to increases in the horizontal compressive stresses. We suggest that seismic repeaters represent brittle frictional parts (asperity) of creeping, planar shaped, pre-exiting structures of several metres composed of weak rock-mass materials (e.g. talc) associated with strengthening friction behaviours. This repeater model and the here used definition of asperity thus slightly differs from its meaning in classical seismological models where repeating events are related to the locked fault patches along a creeping fault. In addition, we identified different asperity types for the different repeater families that we interpret as different friction properties. Some multiplet families represent rather a transitional case between multiplet and repeater occurrences that might imply a mixture of weakening and strengthening friction processes, that is, creep and brittle rupture along neighboured plane shaped anisotropies in a heterogeneous rock mass. The exact nature of asperities and seismic and aseismic coupling of the rock mass as well as the propagation mechanism of strain and stress associated with short-term (days to weeks) and long-term (months to years) post-blast creep remains uncertain and needs to be addressed by future investigations. The understanding of these processes is particularly important for assessing hazard of larger dynamic ruptures.

2015 Nepal Earthquake: A Comparison between Landslide Inventories

<p>Three landslide inventories were prepared for the area affected by the 7.8 Mw Nepal earthquake (April 25, 2015). The first inventory contains 21,151 earthquake-induced landslides (EQL), directly associated to the 7.8Mw earthquake, mapped by using Google Earth’s pre and post-earthquake images, helicopter footage and Google Crisis data. Landslides were classified as debris flows, shallow translational landslides and rotational landslides. This last class included a relatively small number of events.  The second inventory includes only pre-event shallow landslides (PESL) to evidence those landslides which were already active before the 2015 earthquake. This inventory includes more than 2,500 landslides. The third inventory includes almost 20,000 large landslides (LL), consisting mostly of rock avalanches, slumps, rockslides, and deep-seated gravitational slope deformations (DSGSD). The spatial distribution of the three inventories was analysed with respect to land surface parameters. The EQL inventory shows in general a different spatial distribution with respect to the other two inventories. This is probably related to the seismic triggering and to the characteristics of the geographic area. A joint analysis of the LL and the EQL inventories shows that only a few earthquake-induced landslides (about 15 %) are directly associated to reactivation of LL.</p><p>A Principal Component Analysis (PCA) and a Discriminant Analysis were performed to analyse the controlling parameters on EQL and PESL. The analyses were based on: 1) land surface parameters, 2) hydrological parameters, 3) seismic parameters, 4) lithological parameters, 5) land cover, and 6) meteorological parameters. The statistical analyses show that the most critical variables for landslide triggering during an earthquake are associated to the land surface parameters, in association with the cosesimic displacement and the PGA,  that show an effect on the landslide size and density respectively. PESL seem to be mainly controlled by land surface parameters, with some of them (e.g. elevation) showing a slightly inverse relationship with landslide density. Agricultural land use, slope gradient and rainfall (reference period 1980-2000) show a high correlation with the PESL landslide triggering in absence of earthquakes.</p>