Matthew M. Haney

Rheologic and structural controls on the deformation of Okmok volcano, Alaska: FEMs, InSAR, and ambient noise tomography

Received 23 January 2009; revised 5 August 2009; accepted 13 October 2009; published 27 February 2010. [1] Interferometric synthetic aperture radar (InSAR) data indicate that the caldera of Okmok volcano, Alaska, subsided more than a meter during its eruption in 1997. The large deformation suggests a relatively shallow magma reservoir beneath Okmok. Seismic tomography using ambient ocean noise reveals two low-velocity zones (LVZs). The shallow LVZ corresponds to a region of weak, fluid-saturated materials within the caldera and extends from the caldera surface to a depth of 2 km. The deep LVZ clearly indicates the presence of the magma reservoir beneath Okmok that is significantly deeper (>4 km depth) compared to previous geodetic-based estimates (3 km depth). The deep LVZ associated with the magma reservoir suggests magma remains in a molten state between eruptions. We construct finite element models (FEMs) to simulate deformation caused by mass extraction from a magma reservoir that is surrounded by a viscoelastic rind of country rock embedded in an elastic domain that is partitioned to account for the weak caldera materials observed with tomography. This configuration allows us to reduce the estimated magma reservoir depressurization to within lithostatic constraints, while simultaneously maintaining the magnitude of deformation required to predict the InSAR data. More precisely, the InSAR data are best predicted by an FEM simulating a rind viscosity of 7.5 � 10 16 Pa s and a mass flux of � 4.2 � 10 9 kg/d from the magma reservoir. The shallow weak layer within the caldera provides a coeruption stress regime and neutral buoyancy horizon that support lateral magma propagation from the central magma reservoir to extrusion near the rim of the caldera.

Comprehensive approaches to 3D inversion of magnetic data affected by remanent magnetization

Three-dimensional 3D inversion of magnetic data to recover a distribution of magnetic susceptibility has been successfullyusedformineralexplorationduringthelastdecade. However, the unknown direction of magnetization has limited the use of this technique when significant remanence is present. We have developed a comprehensive methodology for solving this problem by examining two classes of approaches and have formulated a suite of methods of practical utility. The first class focuses on estimating total magnetization direction and then incorporating the resultant direction into an inversion algorithm that assumes a known direction. Thesecondclassfocusesondirectinversionoftheamplitude of the magnetic anomaly vector. Amplitude data depend weaklyuponmagnetizationdirectionandareamenabletodirect inversion for the magnitude of magnetization vector in 3D subsurface. Two sets of high-resolution aeromagnetic dataacquiredfordiamondexplorationintheCanadianArctic areusedtoillustratethemethods’usefulness.

Eruption of Alaska volcano breaks historic pattern

In the late morning of 12 July 2008, the Alaska Volcano Observatory (AVO) received an unexpected call from the U.S. Coast Guard, reporting an explosive volcanic eruption in the central Aleutians in the vicinity of Okmok volcano, a relatively young (∼2000-year-old) caldera. The Coast Guard had received an emergency call requesting assistance from a family living at a cattle ranch on the flanks of the volcano, who reported loud “thunder,” lightning, and noontime darkness due to ashfall. AVO staff immediately confirmed the report by observing a strong eruption signal recorded on the Okmok seismic network and the presence of a large dark ash cloud above Okmok in satellite imagery. Within 5 minutes of the call, AVO declared the volcano at aviation code red, signifying that a highly explosive, ash-rich eruption was under way.

The Virtual Refraction: Useful Spurious Energy in Seismic Interferometry

Seismic interferometry is rapidly becoming an established technique to recover the Green’s function between receivers, but practical limitations in the source-energy distribution inevitably lead to spurious energy in the results. Instead of attempting to suppress all such energy, we use a spurious wave associated with the crosscorrelation of refracted energy at both receivers to infer estimates of subsurface parameters. We named this spurious event the virtual refraction. Illustrated by a numerical two-layer example, we found that the slope of the virtual refraction defines the velocity of the faster medium and that the stationary-phase point in the correlation gather provides the critical offset. With the associated critical time derived from the real shot record, this approach includes all of the necessary information to estimate wave speeds and interface depth without the need of inferences from other wave types.

Geophysics: A moving fluid pulse in a fault zone

In the Gulf of Mexico, fault zones are linked with a complex and dynamic system of plumbing in the Earths subsurface. Here we use time-lapse seismic-reflection imaging to reveal a pulse of fluid ascending rapidly inside one of these fault zones. Such intermittent fault ‘burping’ is likely to be an important factor in the migration of subsurface hydrocarbons.

Observation and modeling of source effects in coda wave interferometry at Pavlof volcano

Sorting out source and path effects for seismic waves at volcanoes is critical for the proper interpretation of underlying volcanic processes. Source or path effects imply that seismic waves interact strongly with the volcanic subsurface, either through partial resonance in a conduit (Garces et al., 2000; Sturton and Neuberg, 2006) or by random scattering in the heterogeneous volcanic edifice (Wegler and Luhr, 2001). As a result, both source and path effects can cause seismic waves to repeatedly sample parts of the volcano, leading to enhanced sensitivity to small changes in material properties at those locations. The challenge for volcano seismologists is to detect and reliably interpret these subtle changes for the purpose of monitoring eruptions.

Distinguishing high surf from volcanic long‐period earthquakes

Repeating long-period (LP) earthquakes are observed at active volcanoes worldwide and are typically attributed to unsteady pressure fluctuations associated with fluid migration through the volcanic plumbing system. Nonvolcanic sources of LP signals include ice movement and glacial outburst floods, and the waveform characteristics and frequency content of these events often make them difficult to distinguish from volcanic LP events. We analyze seismic and infrasound data from an LP swarm recorded at Pagan volcano on 12–14 October 2013 and compare the results to ocean wave data from a nearby buoy. We demonstrate that although the events show strong similarity to volcanic LP signals, the events are not volcanic but due to intense surf generated by a passing typhoon. Seismo-acoustic methods allow for rapid distinction of volcanic LP signals from those generated by large surf and other sources, a critical task for volcano monitoring.

Causal Instrument Corrections for Short‐Period and Broadband Seismometers

Online Material: Matlab codes and data example of instrument corrections. Of all the filters applied to recordings of seismic waves, which include source, path, and site effects, the one we know most precisely is the instrument filter. Therefore, it behooves seismologists to accurately remove the effect of the instrument from raw seismograms. Applying instrument corrections allows analysis of the seismogram in terms of physical units (e.g., displacement or particle velocity of the Earth’s surface) instead of the output of the instrument (e.g., digital counts). The instrument correction can be considered the most fundamental processing step in seismology since it relates the raw data to an observable quantity of interest to seismologists. Complicating matters is the fact that, in practice, the term “instrument correction” refers to more than simply the seismometer. The instrument correction compensates for the complete recording system including the seismometer, telemetry, digitizer, and any anti‐alias filters. Knowledge of all these components is necessary to perform an accurate instrument correction. The subject of instrument corrections has been covered extensively in the literature (Seidl, 1980; Scherbaum, 1996). However, the prospect of applying instrument corrections still evokes angst among many seismologists—the authors of this paper included. There may be several reasons for this. For instance, the seminal paper by Seidl (1980) exists in a journal that is not currently available in electronic format and cannot be accessed online. Also, a standard method for applying instrument corrections involves the programs TRANSFER and EVALRESP in the Seismic Analysis Code (SAC) package (Goldstein et al. , 2003). The exact mathematical methods implemented in these codes are not thoroughly described in the documentation accompanying SAC. We describe a general method for causal instrument correction that is applicable to data from a wide range of seismometers and present a set of codes for implementing the …

PS-wave moveout inversion for tilted TI media: A physical-modeling study

Mode-converted PS-waves can provide critically important information for velocity analysis in transversely isotropic TI media. We demonstrate, with physical-modeling data, that the combinationoflong-spreadreflectiontraveltimesofPP-andPSwaves can be inverted for the parameters of a horizontalTI layer with a tilted symmetry axis. The 2D multicomponent reflection data are acquired over a phenolic sample manufactured to simulatetheeffectivemediumformedbysteeplydippingfracturesets orshalelayers. The reflection moveout of PS-waves in this model is asymmetric with respect to the source and receiver positions, and the moveout-asymmetryattributesplayacrucialroleinconstraining theTIparameters.ApplyingthemodifiedPP + PS = SSmethod to the PP and PS traveltimes recorded in the symmetry-axis plane, we compute the time and offset asymmetry attributes of the PS-waves along with the traveltimes of the pure SS reflections. The algorithm of Dewangan and Tsvankin is then used to invertthecombinationofthemoveoutattributesofPP-,SS-,and PS-waves for the medium parameters and the thickness of the sample. It should be emphasized that the pure-modePPand SS traveltimes alone are insufficient for the inversion, even if 3D wide-azimuthdataareavailable. Our estimates of the symmetry axis tilt and layer thickness almost coincide with the actual values. The inverted model is also validatedbyreproducingtheresultsoftransmissionexperiments with both P- and S-wave sources. The transmitted SV wavefield exhibits a prominent cusp triplication accurately predicted by theparameter-estimationresults.

Volcanic tremor and plume height hysteresis from Pavlof Volcano, Alaska

Hearing a volcanic plume Monitoring remote eruptions—such as that of Pavlof Volcano, Alaska, in 2016—is challenging. Fee et al. found that the height of the ash plume during the Pavlof eruption could be inferred from sound waves detected by distant infrasound arrays and measurements of seismic tremor. The use of sound waves for monitoring is uncommon but well suited for remote eruptions, especially when we lack visual or satellite observations. Science, this issue p. 45 The seismic and infrasonic volcanic tremors track ash plume height from the 2016 eruption of Pavlof Volcano. The March 2016 eruption of Pavlof Volcano, Alaska, produced an ash plume that caused the cancellation of more than 100 flights in North America. The eruption generated strong tremor that was recorded by seismic and remote low-frequency acoustic (infrasound) stations, including the EarthScope Transportable Array. The relationship between the tremor amplitudes and plume height changes considerably between the waxing and waning portions of the eruption. Similar hysteresis has been observed between seismic river noise and discharge during storms, suggesting that flow and erosional processes in both rivers and volcanoes can produce irreversible structural changes that are detectable in geophysical data. We propose that the time-varying relationship at Pavlof arose from changes in the tremor source related to volcanic vent erosion. This relationship may improve estimates of volcanic emissions and characterization of eruption size and intensity.