Lecture 10

Part II: Geophysics and Tectonics

Introduction

In the study of Earth sciences, geophysics and tectonics play pivotal roles, particularly in understanding the Earth's internal structure and processes through imaging techniques. This section synthesizes content from earlier lectures, detailing the theoretical foundations and practical applications of Earth imaging as it pertains to geophysical data acquisition and analysis.

Overview of Earth Imaging

The initial lectures provided a foundational backdrop for comprehending the methodologies employed in Earth imaging. These methods facilitate the construction of detailed models that delineate the Earth’s interior, thereby improving our understanding of geological processes and the distribution of resources.

Data Grooming

Data grooming is a critical preprocessing step in geophysical studies:

• Definition: Data grooming refers to the systematic identification and removal of noise and anomalous measurements from datasets.

• Importance: It enhances the signal-to-noise ratio, which is essential for extracting accurate geophysical insights. Ignoring noise can lead to incorrect interpretations, thus data grooming serves as a filter that increases the reliability of subsequent analyses.

Ray-Bundling (Stacking)

Ray-bundling is an innovative technique employed to compile and enhance seismic data:

• Concept: This technique involves aggregating rays with similar source and receiver locations, effectively stacking the data together. This approach improves the visibility of meaningful signals while suppressing irrelevant noise.

• Application: By combining measurements from numerous sources, this method amplifies the effective signal strength, yielding clearer images of subsurface structures; it allows for a robust interpretation of seismic events, which may otherwise be obscured by random noise fluctuations.

Initial Model Importance

The inversion process in geophysical modeling is heavily reliant on the quality of the initial model:

• Significance: A well-constructed initial model is essential for the inversion to yield valid solutions. This is vital, as geophysical inverse problems are frequently ill-posed, which means there can be multiple plausible solutions that fit the observed data.

• Linear Approximation: A sound initial model stabilizes the linearization of the problem, decreasing ambiguity during the inversion phase. By positioning the model close to a feasible solution, researchers enhance the probability of convergence towards a physically realistic model, facilitating more accurate interpretations of Earth’s subsurface characteristics.

Seismic Focus

The emphasis of the research has primarily been on seismic imaging, which utilizes various seismic waveforms:

• 3-component Seismograms: Analysis includes three-dimensional components of seismic waves which allow for comprehensive understanding of wave propagation.

• Body and Surface Wave Propagation: Both wave types are instrumental; body waves travel through Earth’s interior, while surface waves propagate across the surface, each offering unique insights into different strata of the Earth.

• Ray Theory: An essential framework used to simulate elastic wave propagation, ray theory provides a mathematical basis for predicting seismic wave paths.

Geophysical Inverse Problem

The foundation of many geophysical models lies in formulating and solving inverse problems:

• Definition: Geophysical inverse problems involve deducing Earth properties from observational data through formulated mathematical equations.

• Regularization Methods: Regularization techniques are crucial to selecting the optimal model from various possibilities while preventing overfitting of models to noisy data. Regularization adds a degree of constraint to the model, thus refining the solution space and improving the overall integrity of the findings.

Synthetic Reconstruction Tests

To verify methodological robustness, synthetic reconstruction tests are employed:

• Purpose: These tests generate synthetic data from known models to evaluate how well a given method can reconstruct those models.

• Outcomes: By assessing reconstructed features against known benchmarks, researchers can ascertain the reliability and effectiveness of imaging methodologies, identifying strengths and limitations in model recovery.

Case Studies

This comprehensive study will explore key case studies that exemplify the practical applications of the concepts covered:

1. Global Body Wave Tomography

Advancements: The progressive field of global body wave tomography has evolved since Adam Dziewonski’s foundational work:

• Seismic Phases: Utilization of various seismic phases including P, S, PP, SS, PcP, ScP, SKS, and PKIKP greatly enhances model resolution and depth comprehension.

• Model Parameterization: While traditional spherical harmonics are utilized, recent studies often adopt block, grid, or variable parameterizations that adapt to data irregularities and biases, particularly due to the uneven geographical distribution of earthquake events and seismic stations.

Full Waveform Inversion (FWI): This cutting-edge methodology allows for refined imaging of body waves:

• Description: FWI seeks to reconstruct observed seismic waveforms to match predictions derived from numerical solutions based on elastic wave theory.

• Goals: The intent is to produce global body wave images with resolution on par with conventional traveltime methods — all while capturing intricate details of subsurface structures.

Iterative Non-linear Approach:The methodology employs an iterative approach:

• Cycle Skipping: This issue emerges if waveforms are misaligned, leading to convergence at incorrect minima. To mitigate this risk, inversions initially utilize long-period waves, progressively integrating shorter periods as the model improves.

• Application: This adaptive approach reduces cycle skipping potential by carefully constructing waveforms that progressively refine the model as data converges towards a solution.

Case Study - SMUCB-WM1 Model:

• Findings: Data slices through the SMUCB-WM1 global shear wave model demonstrate the presence of low shear-wave velocity zones emanating from core-mantle boundaries. These findings correlate with finite frequency tomography results, underscoring the model’s credibility.

• Challenges: Computational demands make it difficult to validate the robustness of FWI solutions, requiring caution in interpretation and utilization of findings in geological applications.

LLNL Global P-wave Model:Major focus on the LLNL global P-wave model constructed by Simmons et al. in 2012:

• Earthquake Location: Highlights the necessity of precise earthquake location methods, employing Bayesloc — a probabilistic non-linear scheme designed to quantify location uncertainty.

  • Observations: Standard locations provided by the International Seismological Centre (ISC) can possess localization errors, introducing potential inaccuracies into tomographic models.

• Parameterization Strategy: This model utilizes a sophisticated spherical tessellation grid to eliminate polar distortions typically associated with latitude-longitude grids.

  • Depth Variability: The model adeptly constructs variable depth surfaces, including the Mohorovičić Discontinuity (Moho), allowing multifaceted representation of stratified layers and velocity variances within Earth’s crust and mantle layouts.

Inversion Strategy:The accuracy of this inversion relies on robust techniques:

• Methodology: An iterative strategy was developed to address the weakly non-linear inverse problem. This includes solving linearized inverse problems through regularized least squares and advanced ray tracing algorithms employing a bending method to emulate the sinusoidal paths of seismic waves.

  • Smoothing Techniques: Applying large smoothing parameters initially aids in stabilizing estimates, which are subsequently refined as iterations progress, ensuring that the final model accurately represents underlying geology.

Model Results:

• Outcomes: The model successfully explains 2.8 million P-wave arrivals, achieving an impressive standard deviation of 0.96 seconds, reflecting a 64% variance reduction. Notably, it captures heightened velocities beneath continental shields and delineates subduction zones, corroborating the Big Mantle Wedge model in conjunction with volcanic activities across Eastern Asia.

2. Surface Wave Tomography

Surface wave tomography represents a sophisticated method for analyzing earthquake data:

• Wave Types: Surface waves include high-amplitude, late-arriving components; specifically, Love waves (transverse) and Rayleigh waves (vertical and radial).

• Sensitivity Analysis: The sensitivity of Rayleigh waves to shear wave velocity (SV) and Love waves to horizontal shear wave velocity (SH) enables joint inversions to facilitate comprehensive constraint of both SV and SH velocities, leading to insights into radial anisotropy.

Dispersion Characteristics:

• Dispersive Nature: Surface waves exhibit a velocity dependency on frequency, indicating significant depth variations in wave speed.

• Dispersion Curves: These curves illustrate variation in group or phase velocity over periods, where inverting these curves provides a path-average 1-D shear velocity structure; this is fundamental in reconstructing localized geological configurations.

Path Average Models:

• Leveraging spatially diverse seismic data networks allows the reconstruction of lateral variations in shear wave speed.

• 2-D Velocity Models: By synthesizing individual path-average models, researchers devise 2-D velocity models illustrating lateral variances that satisfy seismic data across various depths. This involves solving systematic equations tailored to seismic ray paths.

Case Study - Fishwick and Rawlinson (2012):

• Study Area: Focused on earthquakes across active Australian plate boundaries, this research inverted vertical component Rayleigh waves to produce extensive path-average 1-D SV models of the upper mantle.

• Incorporation of Crustal Structure: Prior crustal structural information was integrated, leveraging the sensitivity of longer-period body waves to bolster the models’ consistency without biasing from shorter-period data.

• Representation: The resulting 2-D model, employing smooth transitions represented by piecewise cubic polynomials, provides an insight into evolving geological structure, combined with a multi-scale method to encompass both coarse and fine-scale variants during iterative refinements.

Model Results:

• Summary: The final model extends to a depth of 300 km, revealing distinct contrasts among the Precambrian continental shield, Phanerozoic orogenic regions, and oceanic lithosphere.

• Geological Correlations: Notably, findings indicated a correlation between gold deposits and variations in the mantle lithosphere velocity, embedding economic implications for mining industries in synchrony with geological investigations.

3. Ambient Noise Tomography

Ambient noise tomography is a modern imaging technique utilizing continuous seismic activity:

• Background Noise: This technique focuses on the use of low-level background vibrations induced by oceanic and atmospheric phenomena, producing constant ‘Earth’s hum’ instead of relying solely on robust seismic events.

• Advantages Over Traditional Methods:

  • Wider Data Coverage: The dependency on station distribution over seismic events expands the practical applicability of data.

  • Microseismic Peaks: The ability to image crustal structures at shorter periods than traditional earthquake surface waves enhances resolution and detail in subsurface imaging.

Cross-Correlation Techniques:

• By applying cross-correlation methods between paired seismic stations, researchers can derive meaningful signals from the inherent noise, enhancing the clarity of the travel time differences between these stations.

• Fresnel Zones: Constructive interference occurring within Fresnel zones leads to amplifying discrete signals at variably timed intervals, yielding robust features essential for precise geological mapping.

Applications:

• Ambient noise imaging techniques have successfully elucidated crustal structures, particularly when combined with longer period data from traditional surface waves, allowing comprehensive joint imaging of crustal and upper mantle environments.

• Body Wave Recovery: Recent advancements have amplified the recovery of body wave data, necessitating extensive and dense seismic arrays for high-resolution imaging.

Case Study - Pilia et al. (2015):

• This influential study employed stations around Bass Strait to elucidate crustal features, facilitating the extraction of clear inter-station Rayleigh wave signals through effective cross-correlations of long-term recordings.

• Non-linear Schemes: Utilizing fully non-linear methodologies, this study showcases enhanced capabilities in exploring model spaces thoroughly, yielding comprehensive ensembles of solutions as opposed to traditional linearized approaches.

• Insights from the Bass Strait Model: Resulting data unveiled low-velocity structures in the Bass and Gippsland basins, specifically identifying low-velocity anomalies within the mid-lower crust beneath the Bass Basin. The elevation in detail facilitated real-time applications of data compared to typical teleseismic surface-derived information.

4. Intraplate Volcanism in Southeast Australia

Intraplate volcanism is a significant phenomenon observed in Eastern Australia, characterized by complex geological activity:

• Cenozoic Volcanism: This phase of volcanism encompasses extensive activity where both age-progressive and non-age-progressive volcanic initiatives have been identified:

  • Age-progressive Volcanism: Attributed to a stationary mantle plume positioned beneath a mobile plate, creating sequential volcanic features across geological time.

  • Non-age-progressive Volcanism: Associated with the Australian plate's northward acceleration around 43 million years ago, driven by mechanisms involving edge-driven convection and shear-driven upwelling, potentially leading to unique volcanic patterns distinctive to localized geology.

Styles of Volcanism: Three main types elucidate the complexities surrounding this geological occurrence:

• Lava Fields: Exhibiting no discernible time-space progression, characterized predominantly by alkaline and tholeiitic types of basalts.

• Central Volcanoes: Bimodal shield formations showcasing age progression related to the broader northward advance of the Australian plate.

• Leucitite Suite: Characterized by low volume, potassium-rich lavas that demonstrate age progression, further emphasizing the variegation of volcanic activity in the region.

Teleseismic Tomography: An advance in understanding upper mantle velocity structures utilizes comprehensive data gathered by dense transportable arrays of seismic stations:

• Modeling Techniques: Utilizes an eikonal solver to effectively map wavefronts’ travel paths through heterogeneous models, predicting arrival time residuals to invert for P-wave velocities.

• Lithospheric Thickness and Composition: Empirical methodologies correlate seismic velocity models to lithospheric thickness, revealing that variations dictate the volume and composition of magma derived from plume activity, essential for understanding eruptive behaviors.

LAB Model Results:

• The final Lithosphere-Asthenosphere Boundary (LAB) model underscores that intraplate volcanism occurs predominantly above regions characterized by thinner lithosphere; with findings concluding that no significant volcanic activity occurs above areas of thicker lithosphere, except for the leucitite suite — suggesting specialized potency for more profound melting at intermediate lithospheric thicknesses.

• Cosgrove Track Analysis: Identification of a single hotspot track, known as the Cosgrove track, connects northern and southern volcanic tracks, revealing significant geological implications.

  • Predictive Models: Utilizing absolute plate motion models provides volcanic location predictions that are subsequently validated by Argon-Argon geochronology techniques which confirm age assessments, contributing depth to understanding the explosive behaviors evident in the region.

• Trace Element Analysis: Key findings indicate that leucitites possess higher concentrations of incompatible trace elements with significant Gd/Lu ratios, indicative of low-degree partial melting at depths more significant than typical eruption characterization.

• Magma Dynamics: Variations in lithospheric thickness exert critical influences on magma volumes and compositions through controlling uplift heights and influencing the extent of partial melting; where thinner lithosphere (northern Queensland) promotes significant melting while thicker areas suppress it, ultimately dictating the volcanic features observed.

Conclusion

This comprehensive study outlines the critical components of geophysics and tectonics with meticulous coverage of key imaging techniques, methodologies, and case studies exemplifying their applications. Each section compiles essential scientific principles and real-world applications, ensuring coherence and depth of knowledge for university-level students. Enhanced explanations of complex concepts serve to elucidate their significance in ongoing research, paving pathways for further inquiry into Earth science’s dynamisms.