A stochastic model for induced seismicity based on non-linear pressure diffusion and irreversible permeability enhancement

During deep reservoir engineering projects, in which permeability is enhanced by high-pressure fluid injection, seismicity is invariably induced, posing nuisance to the local population and a potential hazard for structures. Hazard and risk assessment tools that can operate in real-time during reservoir stimulation depend on the ability to efficiently model induced seismicity. We here propose a novel modelling approach based on a combination of physical considerations and stochastic elements. It can model a large number of synthetic event catalogues, and at the same time is constrained by observations of hydraulic behaviour in the injection well. We model fluid flow using non-linear pressure diffusion equations, in which permeability increases irreversibly above a prescribed pressure threshold. The transient pressure field is used to trigger events at so-called ‘seed points' that are distributed randomly in space and represent potential earthquake hypocentres. We assign to each seed point a differential stress based on the mean estimates of the in situ stress field and add a normal distributed random value. Assuming a fault orientation with respect to the stress field and a Mohr-Coulomb failure criterion, we evaluate at each time step, if a seed point is triggered through a pressure increase. A negative proportional relationship between differential stress and b values is further assumed as observed from tectonic earthquakes and in laboratory experiments. As soon as an event is triggered, we draw a random magnitude from a power-law distribution with a b value corresponding to the differential stress at the triggered seed point. We thus obtain time-dependent catalogues of seismic events including magnitude. The strategy of modelling flow and seismicity in a decoupled manner ensures efficiency and flexibility of the model. The model parameters are calibrated using observations from the Basel deep geothermal experiment in 2006. We are able to reproduce the hydraulic behaviour, the space-time evolution of the seismicity and its frequency-magnitude distribution. A large number of simulations of the calibrated model are then used to capture the variability of the process, an important input to compute probabilistic seismic hazard. We also use the calibrated model to explore alternative injection scenarios by varying injection volume, pressure as well as depth, and show the possible effect of those parameters on seismic hazar

Adaptively Smoothed Seismicity Earthquake Forecasts for Italy

We present a model for estimating the probabilities of future earthquakes of magnitudes m > 4.95 in Italy. The model, a slightly modified version of the one proposed for California by Helmstetter et al. (2007) and Werner et al. (2010), approximates seismicity by a spatially heterogeneous, temporally homogeneous Poisson point process. The temporal, spatial and magnitude dimensions are entirely decoupled. Magnitudes are independently and identically distributed according to a tapered Gutenberg-Richter magnitude distribution. We estimated the spatial distribution of future seismicity by smoothing the locations of past earthquakes listed in two Italian catalogs: a short instrumental catalog and a longer instrumental and historical catalog. The bandwidth of the adaptive spatial kernel is estimated by optimizing the predictive power of the kernel estimate of the spatial earthquake density in retrospective forecasts. When available and trustworthy, we used small earthquakes m>2.95 to illuminate active fault structures and likely future epicenters. By calibrating the model on two catalogs of different duration to create two forecasts, we intend to quantify the loss (or gain) of predictability incurred when only a short but recent data record is available. Both forecasts, scaled to five and ten years, were submitted to the Italian prospective forecasting experiment of the global Collaboratory for the Study of Earthquake Predictability (CSEP). An earlier forecast from the model was submitted by Helmstetter et al. (2007) to the Regional Earthquake Likelihood Model (RELM) experiment in California, and, with over half of the five-year experiment over, the forecast performs better than its competitors.Comment: revised manuscript. 22 pages, 3 figures, 2 table

Balancing reservoir creation and seismic hazard in enhanced geothermal systems

Fracture shear-dilatancy is an essential process for enhancing the permeability of deep geothermal reservoirs, and is usually accompanied by the radiation of seismic waves. However, the hazard and risk perspective of induced seismicity research typically focuses only on the question of how to reduce the occurrence of induced earthquakes. Here we present a quantitative analysis of seismic hazard as a function of the two key factors defining an enhanced geothermal system: The permeability enhancement, and the size of the stimulated reservoir. Our model has two coupled components: (1) a pressure diffusion model and (2) a stochastic seismicity model. Permeability is increased in the source area of each induced earthquake depending on the amount of slip, which is determined by the magnitude. We show that the few largest earthquakes (i.e. 5-10 events with M ≥ 1.5) contribute more than half of the total reservoir stimulation. The results further indicate that planning and controlling of reservoir engineering operations may be compromised by the considerable variability of maximum observed magnitude, reservoir size, the Gutenberg-Richter b-value and Shapiro's seismogenic index (i.e. a measure of seismic reactivity of a reservoir) that arises from the intrinsic stochastic nature of induced seismicity. We also find that injection volume has a large impact on both reservoir size and seismic hazard. Injection rate and injection scheme have a negligible effect. The impact of site-specific parameters on seismicity and reservoir properties is greater than that of the injected volume. In particular, conditions that lead to high b-values—possibly a low differential stress level—have a high impact on seismic hazard, but also reduce the efficiency of the stimulation in terms of permeability enhancement. Under such conditions, target reservoir permeability can still be achieved without reaching an unacceptable level of seismic hazard, if either the initial reservoir permeability is high or if several fractures are stimulated. The proposed methodology is a first step towards including induced seismic hazard analysis into the design of reservoir stimulation in a quantitative and robust manne

The 1997 Kagoshima (Japan) earthquake doublet: A quantitative analysis of aftershock rate changes

We quantitatively map relative rate changes for the aftershock sequence following the second mainshock of the 1997 earthquake doublet (M_W = 6.1, M_W = 6.0) in the Kagoshima province (Japan). Using the spatial distribution of the modified Omori law parameters for aftershocks that occurred during the 47.8 days between the two mainshocks, we forecast the aftershock activity in the next 50 days and compare it to the actually observed rates. The relative rate change map reveals four regions with statistically significant relative rate changes - three negative and one positive. “Our analysis suggests that the coseismic rate changes for off-fault aftershocks could be explained by changes in static stress. However, to explain the activation and deactivation of on-fault seismicity, other mechanism such as unusual crustal properties and the presence of abundant crustal fluids are required.

Statistical analysis of the induced Basel 2006 earthquake sequence: Introducing a probability-based monitoring approach for Enhanced Geothermal Systems

ISSN:0956-540XISSN:1365-246

Statistical analysis of the induced Basel 2006 earthquake sequence: introducing a probability-based monitoring approach for Enhanced Geothermal Systems

Geothermal energy is becoming an important clean energy source, however, the stimulation of a reservoir for an Enhanced Geothermal System (EGS) is associated with seismic risk due to induced seismicity. Seismicity occurring due to the water injection at depth have to be well recorded and monitored. To mitigate the seismic risk of a damaging event, an appropriate alarm system needs to be in place for each individual experiment. In recent experiments, the so-called traffic-light alarm system, based on public response, local magnitude and peak ground velocity, was used. We aim to improve the pre-defined alarm system by introducing a probability-based approach; we retrospectively model the ongoing seismicity in real time with multiple statistical forecast models and then translate the forecast to seismic hazard in terms of probabilities of exceeding a ground motion intensity level. One class of models accounts for the water injection rate, the main parameter that can be controlled by the operators during an experiment. By translating the models into time-varying probabilities of exceeding various intensity levels, we provide tools which are well understood by the decision makers and can be used to determine thresholds non-exceedance during a reservoir stimulation; this, however, remains an entrepreneurial or political decision of the responsible project coordinators. We introduce forecast models based on the data set of an EGS experiment in the city of Basel. Between 2006 December 2 and 8, approximately 11 500 m3 of water was injected into a 5-km-deep well at high pressures. A six-sensor borehole array, was installed by the company Geothermal Explorers Limited (GEL) at depths between 300 and 2700 m around the well to monitor the induced seismicity. The network recorded approximately 11 200 events during the injection phase, more than 3500 of which were located. With the traffic-light system, actions where implemented after an ML 2.7 event, the water injection was reduced and then stopped after another ML 2.5 event. A few hours later, an earthquake with ML 3.4, felt within the city, occurred, which led to bleed-off of the well. A risk study was later issued with the outcome that the experiment could not be resumed. We analyse the statistical features of the sequence and show that the sequence is well modelled with the Omori-Utsu law following the termination of water injection. Based on this model, the sequence will last 31+29/−14 years to reach the background level. We introduce statistical models based on Reasenberg and Jones and Epidemic Type Aftershock Sequence (ETAS) models, commonly used to model aftershock sequences. We compare and test different model setups to simulate the sequences, varying the number of fixed and free parameters. For one class of the ETAS models, we account for the flow rate at the injection borehole. We test the models against the observed data with standard likelihood tests and find the ETAS model accounting for the on flow rate to perform best. Such a model may in future serve as a valuable tool for designing probabilistic alarm systems for EGS experiment

Size distribution of Parkfield's microearthquakes reflects changes in surface creep rate

The nucleation area of the series of M6 events in Parkfield has been shown to be characterized by low b-values throughout the seismic cycle. Since low b-values represent high differential stresses, the asperity structure seems to be always stably stressed and even unaffected by the latest main shock in 2004. However, because fault loading rates and applied shear stress vary with time, some degree of temporal variability of the b-value within stable blocks is to be expected. We discuss in this study adequate techniques and uncertainty treatment for a detailed analysis of the temporal evolution of b-values. We show that the derived signal for the Parkfield asperity correlates with changes in surface creep, suggesting a sensitive time resolution of the b-value stress meter, and confirming near-critical loading conditions within the Parkfield asperit

A smoothed stochastic earthquake rate model considering seismicity and fault moment release for Europe

We present a time-independent gridded earthquake rate forecast for the European region including Turkey. The spatial component of our model is based on kernel density estimation techniques, which we applied to both past earthquake locations and fault moment release on mapped crustal faults and subduction zone interfaces with assigned slip rates. Our forecast relies on the assumption that the locations of past seismicity is a good guide to future seismicity, and that future large-magnitude events occur more likely in the vicinity of known faults. We show that the optimal weighted sum of the corresponding two spatial densities depends on the magnitude range considered. The kernel bandwidths and density weighting function are optimized using retrospective likelihood-based forecast experiments. We computed earthquake activity rates (a- and b-value) of the truncated Gutenberg-Richter distribution separately for crustal and subduction seismicity based on a maximum likelihood approach that considers the spatial and temporal completeness history of the catalogue. The final annual rate of our forecast is purely driven by the maximum likelihood fit of activity rates to the catalogue data, whereas its spatial component incorporates contributions from both earthquake and fault moment-rate densities. Our model constitutes one branch of the earthquake source model logic tree of the 2013 European seismic hazard model released by the EU-FP7 project ‘Seismic HAzard haRmonization in Europe' (SHARE) and contributes to the assessment of epistemic uncertainties in earthquake activity rates. We performed retrospective and pseudo-prospective likelihood consistency tests to underline the reliability of our model and SHARE's area source model (ASM) using the testing algorithms applied in the collaboratory for the study of earthquake predictability (CSEP). We comparatively tested our model's forecasting skill against the ASM and find a statistically significant better performance for testing periods of 10-20yr. The testing results suggest that our model is a viable candidate model to serve for long-term forecasting on timescales of years to decades for the European regio

Spatial distribution and energy release of nonvolcanic tremor at Parkfield, California

Nonvolcanic tremors (NVTs) are observed in transition zones between freely slipping andlocked sections of faults and normally occur below the seismogenic zone. Based on NVT recordings in theParkfield region of the San Andreas Fault, we provide a novel approach to assess the energy release of theseevents and assign magnitudes (Me) that are compatible with size estimates of small earthquakes in the sameregion. To assess the energy magnitude of a detected tremor, we refine the estimate of its duration andperform a spectral analysis that accounts for local attenuation. For the 218 NVTs that we were able to process,we resolveMevalues in the range of 0.67 to 0.84. For events, which we could not process using the spectralanalysis technique, we propose a statistical model to estimateMevalues using observable characteristics,such as peak amplitude, spectral velocity at the source corner frequency, and duration. We furthermoreprovide seismic moment and moment magnitude estimates and calculate stress drops in a range of 3–10 kPa.As a result of our spectral analyses, wefind strong indications regarding the ongoing debate aboutpotential NVT location hypotheses: the Parkfield NVTs have a higher probability to be located in the proposedthree-dimensional cloud-like cluster than in any other suggested location distributi

News from NERIES, SAFER, SEISTRAIN and Other Transnational European Projects

News from NERIES, SAFER, SEISTRAIN and Other Transnational European Project