Receiver Functions in the San Fernando Valley, California: Graph-Regularized Bayesian Approach for Gravity-Informed Mapping

Valeria Villa; Robert W. Clayton; Patricia Persaud

Home/Archive/arXiv

arXiv · 2601.02575

Receiver Functions in the San Fernando Valley, California: Graph-Regularized Bayesian Approach for Gravity-Informed Mapping

Valeria Villa·Robert W. Clayton·Patricia Persaud

View original source ↗Read source document ↗Export metadata ↓

Abstract

The San Fernando Valley (SFV) in Southern California is a complex sedimentary basin whose shape strongly influences ground shaking. We develop a fully quantitative, probabilistic graph-regularized inference model that integrates both gravity and receiver function (RF) constraints and evaluate its ability to determine the basin's shape. The sediment-basement interface in single-station RFs is often difficult to interpret due to scattering and noise, which can render isolated stations unusable. By using RFs from a dense seismic array and incorporating gravity, we address the issue of non-uniqueness in converting the times of RF phases to layer thickness by comparing the predicted gravity to observations at each station. In areas where the density contrast may change, Bayesian inference with a graph Laplacian allows us to determine the effective density contrast by taking into account its neighbors' picks and densities. This method promotes spatial smoothness between neighboring stations, while preserving sharp contrasts in locations supported by the RF and gravity data. We applied this method to a dataset that was acquired in fall 2023, when 140 nodes were installed in the SFV. Our results show the deep Sylmar sub-basin, the San Fernando sub-basin, and the Leadwell high found in a previous study (Juárez-Zúñiga and Persaud, 2025), and our results also show good agreement with the industry seismic reflection profiles across the valley. This method demonstrates how to incorporate gravity with lateral density variations into receiver function interpretation to better map interfaces in the subsurface.

Explore related subjects

physics.geo-ph

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Valeria Villa, Robert W. Clayton, Patricia Persaud. 2026-01-05. Receiver Functions in the San Fernando Valley, California: Graph-Regularized Bayesian Approach for Gravity-Informed Mapping. https://arxiv.org/abs/2601.02575

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Direction-Aware Masked Pretraining for 3D Seismic Representation Learning and Transfer to Cross-Area Acoustic Impedance Inversion

Large archives of unlabeled three-dimensional seismic data offer opportunities for self-supervised representation learning and subsequent transfer to acoustic impedance inversion. However, conventional masked pretraining often treats three axes equivalently, overlooking differences between lateral reflector structure and vertical waveform characteristics. We propose a direction-aware masked autoencoder for three-dimensional post-stack seismic data, combining anisotropic tokenization, direction-aware representation, trace-aligned tube masking, and reconstruction constraints designed for reflector continuity and waveform characteristics. We evaluate reconstruction quality and downstream transferability using field data through masked reconstruction and cross-area acoustic impedance inversion. Reconstruction is more sensitive to lateral token resolution than to moderate changes in vertical patch length. Within the evaluated configurations, increasing encoder capacity does not fully compensate for reconstruction fidelity loss associated with coarser tokenization. Preferred token scales and masking strategies differ between reconstruction and inversion, indicating that reconstruction fidelity alone is not a reliable indicator of transferability. For cross-area inversion, the pretrained model is fine-tuned in the source area and applied to the target area without further parameter updates. With limited target-area well control, the proposed framework reduces normalized root-mean-square error by 20.8% relative to a pretrained conventional masked autoencoder across eight target-area test wells under matched tokenization and downstream settings. These results demonstrate the value of direction-aware masked pretraining for field seismic inversion and show that token scale and masking strategy should be selected according to downstream-task requirements rather than reconstruction accuracy alone.

physics.geo-ph↗

arXiv2026

Predicting the Elastic Properties of a Cemented Granular Material during Chemical Damage (Debonding)

While underground reservoirs emerge as essential elements to face global warming, these systems represent complex multi-physical and multiscale problems. The considered injection of fluids during hydrogen storage, carbon dioxide sequestration, or geothermal energy recovery involves a modification of the chemical equilibrium of the fluid in the porous reservoir. Chemical reactions can induce microstructural changes of the rock matrix, leading to a reduction of elastic properties of the material, and to potential settlement or stress redistribution. Consequently, it becomes pivotal to establish predictive behavior laws to describe the effect of chemical damage on elastic properties. Facing the difficulties to estimate experimentally the impact of chemical damage on mechanical properties, a Digital Rock Physics approach is proposed in this contribution. This numerical homogenization scheme is used to compare two distinct types of microstructure models: the first one consists in a Discrete Element Model, while the second one employs a continuous description. This continuous formulation is based on a Phase-Field description to predict the evolution of the microstructure subjected to chemical alterations and on the Fast Fourier Transform to estimate the macroscopic properties of the material. Finally, these frameworks establish different softening laws that can be used as constitutive ingredients for a cemented material during its weathering.

physics.geo-ph↗

arXiv2026

Determination of Physical Height Differences from Time Transfer via the ACES Mission -- A Simulation Study

The determination of physical height differences using highly stable atomic clocks has emerged as a novel approach in relativistic geodesy, exploiting the gravitational redshift as a direct observable of geopotential differences. In this study, we investigate the feasibility of satellite-based clock comparisons using the Atomic Clock Ensemble in Space (ACES) onboard the International Space Station, which enables time transfer via microwave (MWL) and optical (ELT) links. Since operational optical data are not yet available, a comprehensive full-scale simulation of realistic ACES observation scenarios is performed, including detailed noise models of clocks and links. A slope-based estimation method is applied to time series of clock comparisons in order to extract the relativistic redshift signal and derive height differences between the ground stations. The performance of the approach is evaluated for quasi-common view, non-common view, and split non-common view configurations, where the latter divides the observation period into shorter intervals. The results show that optical links enable faster convergence and can achieve height accuracies at the decimeter level within a few days and at the centimeter level over longer periods, while microwave links are more strongly affected by noise and bias contributions. Non-common view processing significantly increases observation availability with only minor loss in accuracy, and the split approach provides robust solutions for larger networks. These findings demonstrate the strong potential of satellite-based clock comparisons as a remote-sensing technique for determining physical height differences on a continental scale.

physics.geo-ph↗