Structure Seismology

1.1 Seismic Imaging of the Midcontinent Rift

The Midcontinent Rift (MCR), hosting several world-class ore deposits, is the fossil remnant of a massive Mesoproterozoic rifting event (1.1 Ga) that did not lead to the formation of an ocean basin. To better understand the lithospheric processes associated with the rifting stage and its subsequent failure, we developed a novel full-waveform joint inversion method using ambient noise data and teleseismic P waves for this seismically inactive region. We apply this approach to three years (2011-2013) of seismic recordings from the Superior Province Rifting EarthScope Experiment (SPREE) (~12 km average station spacing) and the USArray Transportable Array (~70 km average station spacing), and obtain a new 3D high-resolution Vs model down to 100 km depth, as well as Vp and density models down to 60 km depth. The model shows major velocity anomalies in agreement with previous seismic studies for the western arm of the MCR. In particular, we observe high density (2.8-3.0 g/cm3), Vp (6.3-6.5 km/s), and Vs (3.6-3.7 km/s) structures in the shallow upper crust within the rift, likely associated with volcanic rocks. Similar to a previously identified underplated layer, we also observe extensive normal-to-high Vs (3.8-4.2 km/s) along the whole rift axis and Vp (6.8-7.5 km/s) beneath the northern segment of the rift within the lower crust. However, the Vs and Vp values are lower than average for typical underplated materials. We suggest that this underplated layer may represent a combination of different intrusive rock types (e.g., gabbro, anorthosite) developed during magma differentiation processes, or contamination of the mafic magma by surrounding crustal material, or intrusions of sills.

Related Publication: Crustal and uppermost mantle structures of the North American Midcontinent Rift revealed by joint full-waveform inversion of ambient-noise data and teleseismic P waves, Earth and Planetary Science Letters, 641 (118797), https://doi.org/10.1016/j.epsl.2024.118797.

Several questions remail unclear for the MRS. Come back and see more work in near future.

1.2 Suture zone and Subduction zone imaging

Increasing deployment of dense arrays has facilitated detailed structure imaging for tectonic investigation, hazard assessment and resource exploration. Strong velocity heterogeneity and topographic changes have to be considered during passive source imaging. However, it is quite challenging for ray-based methods, such as Kirchhoff migration or the widely used teleseismic receiver function, to handle these problems. In this study, we propose a 3-D passive source reverse time migration strategy based on the spectral element method. It is realized by decomposing the time reversal full elastic wavefield into amplitude-preserved vector P and S wavefields by solving the corresponding weak-form solutions, followed by a dot-product imaging condition to get images for the subsurface structures. It enables us to use regional 3-D migration velocity models and take topographic variations into account, helping us to locate reflectors at more accurate positions than traditional 1-D model-based methods, like teleseismic receiver functions. Two synthetic tests are used to demonstrate the advantages of the proposed method to handle topographic variations and complex velocity heterogeneities. Furthermore, applications to the Laramie array data using both teleseismic P and S waves enable us to identify several south-dipping structures beneath the Laramie basin in southeast Wyoming, which are interpreted as the Cheyenne Belt suture zone and agree with, and improve upon previous geological interpretations.

Related Publication: Passive source reverse time migration based on the spectral element method, under review

1.3 On-going Project: Building Multi-parameter Community Velocity Models for Cascadia Region Earthquake Center (CRESCENT)

Stage 1: We have conducted joint inversion of Rayleigh wave dispersion curves and receiver functions (more than 20-years of recordings, including OBS data) to obtain the generation 0 velocity model (Vsv)

Stage 2: Starting from our generation 0 velocity model, we are refining the velocity model by doing full waveform inversion and will obtain the radial and azimuthal anisotropy parameters in the future.

Stage 3: Refine the basin structures in the future

Seismic Exploration

2.1 Migration velocity analysis using seismic reflection data

The accuracy of the background velocity analysis is critical to image the subsurface structure in seismology. Wave-equation migration velocity analysis using source-domain common-image gathers requires picking the relative moveouts based on semblance analysis. However, the picking process is complex and time-consuming. To avoid picking and maintain efficiency in generating CIGs, an automatic wave-equation migration velocity analysis method is proposed utilizing the focusing properties of the Radon-domain common-image gathers. Seismic events in the Radon-domain common-image gathers appear focused if an accurate migration velocity model is used; otherwise, the resultant events will be unfocused. The objective function is defined in the Radon domain to measure focus of the common-image gathers automatically. The proposed migration velocity analysis method links the defocusing information to the migration velocity update under the assumption that model perturbations only result in slope shifts in the common-image gathers. This method provides a reasonably accurate background velocity model for imaging and full-waveform inversion without requiring an accurate initial velocity model. Tests on synthetic and field data demonstrate the effectiveness of the method. This method is tolerable to both inaccurate initial velocity models and the lack of low-frequency data.

Related Publication: Bin He, Yike Liu, Wave‐equation migration velocity analysis using Radon‐domain common‐image gathers, 2020, Journal of Geophysical Research: Solid Earth, 125 (2),  https://doi.org/10.1029/2019JB018938.

2.2 Controlled Order Multiple Full Waveform Inversion

Traditional full-waveform inversion (FWI) seeks to find the best model by minimizing an objective function defined as the difference between the model-predicted and observed data in amplitude and phase. In principle, FWI should fit all wave types including direct waves, diving waves, primaries, and multiples. However, when an initial model is far from the true model, FWI will encounter difficulties in matching multiples. Physically, multiples may contain more subsurface information compared to primary and diving waves. Multiples cover a wide range of reflection angles during wave propagation and offer the advantage of imaging the shadow zones that cannot be reached or are poorly illuminated by primary reflections. We have developed a new method of waveform inversion using multiples. We first separate the multiples into different orders. The objective function we seek to minimize consists of the data difference between the modeled data using a lower order multiple as the source and the higher order multiple as data. This method is called controlled-order multiple waveform inversion (CMWI). Our numerical examples determined that the CMWI is a promising method to improve velocity updates.

Related Publication: Yike Liu, Bin He, Yingcai Zheng, Controlled-order multiple waveform inversion, 2020, Geophysics, 85(3), https://doi.org/10.1190/geo2019-0658.1.