Kristy F. Tiampo

Hydraulic Fracturing and Seismicity in the Western Canada Sedimentary Basin

The development of most unconventional oil and gas resources relies upon subsurface injection of very large volumes of fluids, which can induce earthquakes by activating slip on a nearby fault. During the last 5 years, accelerated oilfield fluid injection has led to a sharp increase in the rate of earthquakes in some parts of North America. In the central United States, most induced seismicity is linked to deep disposal of coproduced wastewater from oil and gas extraction. In contrast, in western Canada most recent cases of induced seismicity are highly correlated in time and space with hydraulic fracturing, during which fluids are injected under high pressure during well completion to induce localized fracturing of rock. Furthermore, it appears that the maximum-observed magnitude of events associated with hydraulic fracturing may exceed the predictions of an often-cited relationship between the volume of injected fluid and the maximum expected magnitude. These findings have far-reaching implications for assessment of inducedseismicity hazards.

Investigating Canada's Lithosphere and earthquake hazards with portable arrays

A multi-institutional research initiative, POLARIS, is providing scientists with unprecedented opportunities to map Earth structure and assess earthquake hazards across Canada. By completion of the initiatives installation phase in August 2005, deployments of POLARIS (Portable Observatories for Lithospheric Analysis and Research Investigating Seismicity) instruments will include 100 telemetered broadband seismograph systems, 10 with continuous-recording magnetotelluric (MT) devices (devices that record natural variations in the geomagnetic field). Data from these observatories are transmitted by satellite (with a latency of 5 s) to data acquisition hubs in London (Canada) and Ottawa, where they are made available in near real-time by an automatic data-request manager (AutoDRM). Conceived in 2000 by an interdisciplinary group of 10 geoscientists, the 4-year, C

A simultaneous inversion for deformation rates and topographic errors of DInSAR data utilizing linear least square inversion technique

11 million infrastructure project is fostering strong partnerships between academia, government laboratories, and the private sector.

Application of DInSAR-GPS Optimization for Derivation of Fine-Scale Surface Motion Maps of Southern California

We demonstrate here a computer code for calculation of time series and also mean and linear deformation rates from a set of coregistered unwrapped differential interferograms using a linear least-squares inversion technique based on the small baseline subset (SBAS) algorithm. The computer code is written in C and uses a singular value decomposition (SVD) routine from the LAPACK library and the fast Fourier transform for spatial filtering from the FFTW library. Various offset estimation and topographic correction algorithms are implemented, including simultaneous inversion for deformation rates and residual topographic error. This approach is particularly useful when applied to ALOS PALSAR interferograms that are coherent even at large perpendicular baselines and acquired with orbital parameters correlated with the time of acquisition. This methodology is applied to produce time series of ground deformation at Tauhara and Wairakei geothermal fields (Taupo Volcanic Zone, North Island, New Zealand) from 12 ALOS PALSAR images acquired between July 2007 and December 2009. We also present here a high-resolution deformation map of the ground subsidence caused by the extraction of geothermal groundwater for power generation, with maximum rates of subsidence of about 7cm/y.

Analytical optimization of a DInSAR and GPS dataset for derivation of three-dimensional surface motion

A method based on random field theory and Gibbs-Markov random fields equivalency within Bayesian statistical framework is used to derive 3-D surface motion maps from sparse global positioning system (GPS) measurements and differential interferometric synthetic aperture radar (DInSAR) interferogram in the southern California region. The minimization of the Gibbs energy function is performed analytically, which is possible in the case when neighboring pixels are considered independent. The problem is well posed and the solution is unique and stable and not biased by the continuity condition. The technique produces a 3-D field containing estimates of surface motion on the spatial scale of the DInSAR image, over a given time period, complete with error estimates. Significant improvement in the accuracy of the vertical component and moderate improvement in the accuracy of the horizontal components of velocity are achieved in comparison with the GPS data alone. The method can be expanded to account for other available data sets, such as additional interferograms, lidar, or leveling data, in order to achieve even higher accuracy

Surface uplift and time-dependent seismic hazard due to fluid injection in eastern Texas.

A revised method for derivation of three-dimensional surface motions maps from sparse global positioning system (GPS) measurements and two differential interferometric synthetic aperture radar (DInSAR) interferograms based on a random field theory and Gibbs-Markov random fields equivalency within Bayesian statistical framework is proposed. It is shown that the Gibbs energy function can be optimized analytically in the absence of a neighboring relationship between sites of a regular lattice. Because the problem is well posed, its solution is unique and stable, and additional regularization in the form of smoothness is not required. The proposed algorithm is simple in realization, does not require extensive computer power, and is very quick in execution. The results of inverse computer modeling are presented and show a drastic improvement of accuracy when both GPS and DInSAR data are used.

Nonlinear Network Dynamics on Earthquake Fault Systems

Observations that unequivocally link seismicity and wastewater injection are scarce. Here we show that wastewater injection in eastern Texas causes uplift, detectable in radar interferometric data up to >8 kilometers from the wells. Using measurements of uplift, reported injection data, and a poroelastic model, we computed the crustal strain and pore pressure. We infer that an increase of >1 megapascal in pore pressure in rocks with low compressibility triggers earthquakes, including the 4.8–moment magnitude event that occurred on 17 May 2012, the largest earthquake recorded in eastern Texas. Seismic activity increased even while injection rates declined, owing to diffusion of pore pressure from earlier periods with higher injection rates. Induced seismicity potential is suppressed where tight confining formations prevent pore pressure from propagating into crystalline basement rocks.

Space-time clustering and correlations of major earthquakes.

Earthquake faults occur in interacting networks having emergent space-time modes of behavior not displayed by isolated faults. Using simulations of the major faults in southern California, we find that the physics depends on the elastic interactions among the faults defined by network topology, as well as on the nonlinear physics of stress dissipation arising from friction on the faults. Our results have broad applications to other leaky threshold systems such as integrate-and-fire neural networks.

A simulation-based approach to forecasting the next great San Francisco earthquake

Earthquake occurrence in nature is thought to result from correlated elastic stresses, leading to clustering in space and time. We show that the occurrence of major earthquakes in California correlates with time intervals when fluctuations in small earthquakes are suppressed relative to the long term average. We estimate a probability of less than 1% that this coincidence is due to random clustering.

Local quaternion Fourier transform and color image texture analysis

In 1906 the great San Francisco earthquake and fire destroyed much of the city. As we approach the 100-year anniversary of that event, a critical concern is the hazard posed by another such earthquake. In this article, we examine the assumptions presently used to compute the probability of occurrence of these earthquakes. We also present the results of a numerical simulation of interacting faults on the San Andreas system. Called Virtual California, this simulation can be used to compute the times, locations, and magnitudes of simulated earthquakes on the San Andreas fault in the vicinity of San Francisco. Of particular importance are results for the statistical distribution of recurrence times between great earthquakes, results that are difficult or impossible to obtain from a purely field-based approach.