Geophysical evaluations supporting national security
We develop geophysical techniques to probe the solid earth and use near-real-time science to enable actionable decision-making for the national security mission.
We combine research, modeling and data collection using a wide range of geophysical techniques to evaluate near-surface phenomena relevant to critical national security applications.
Our staff have technical expertise in understanding geodynamic processes, with particular interest in the transmission of seismic signals through the Earth and infrasound signals through the atmosphere. We also have a team specializing in collecting geophysical data using Uncrewed Aerial System (UAS) platforms and developing techniques to convert data to knowledge about the Earth's near-surface. Our experts study and apply seismic, infrasound and acoustic modeling plus numerical modeling across scales, including near-field explosive and shock propagation, coupled solid/fluid interactions, regional-scale seismic and large-scale tectonic processes that influence the lithosphere stress state. We also conduct lab-scale research in the nonlinear properties of Earth materials, model rock fracture mechanics and use seismology to evaluate the interaction of porous rocks and fluids.
Combination of applied geophysics, radiochemistry, ground coupling, cratering, ground shock, subsurface fluid flow and tracer monitoring for containment design of explosive testing. The team applies knowledge to verify design performance and support stockpile stewardship and Comprehensive Test Ban Treaty monitoring.
Test bed design and development.
Underground nuclear explosion detection, monitoring and discrimination.
Diagnostic device placement and optimization.
Maintenance of the Lab’s test-readiness capabilities.
Analysis of underground tests to improve physics calculation performance.
Use of state-of-the-art numerical methods to better understand and characterize geomechanical processes and geologic materials.
Develop, maintain and support of the HOSS (Hybrid Optimization Software Suite) – a state-of-the-art combined finite-discrete element methodologies (FDEM), consisting of finite element analysis (FEA) and discrete element methods (DEM).
Advanced material modeling approaches based on hyper- and hypo-elastic elasto-plastic formulations.
Integration of machine learning solutions for material modeling and fracture propagation purposes.
Extension of the numerical platforms to new computing architectures, such as GPGPU.
Remote Data Collection
Integration of geologic, geomorphic and remote sensing observations to achieve national security objectives, while also utilizing the same data to understand seismic and climate-related hazards.
Integration of geologic, geomorphic and structural geologic observations with novel near-surface remote sensing tools to discriminate and analyze surface changes to achieve national and global security objectives.
Develop new algorithms and coupling strategies for monitoring signals using optical fiber distributed acoustic sensing (DAS).
Operate, maintain and analyze data from the Los Alamos Seismic Network (LASN) in support of the Lab’s Seismic Hazards Program.
Laboratory-scale acoustics experiments on porous rocks in support of oil and gas research.
Utilize seismic observations to locate and model the source properties of earthquakes.
Implementation of research focused on better understanding the regional geologic setting to better constrain uncertainties in hazards calculations.
Provide geologic characterization and consult on the potential seismic geology hazards to new and existing Lab facilities.
3D subsurface geoscience, geophysics and geology, which includes 3D geologic framework modeling and subsurface interpretation, seismology and seismic data interpretation and surface geology.
Production of local-to-global cartographic assignments and geospatial analyses in GIS and ESRI online applications.
Full 3D waveform measurements using laser vibrometry.
Combining field-based and remotely sensed observations to assess faults, volcanoes and ice sheets to better understand their geologic and climate hazards.
Geophysical Explosion Monitoring
Geophysical and multi-modal research of explosion and related phenomena to support the nation’s efforts to better quantify, understand and monitor for nuclear testing activity.
Coordinate and perform large-scale physical and virtual monitoring experiments of buried and aboveground explosions.
Exploit new technologies to develop next-generation capabilities that include Distributed Acoustic Sensing (DAS), Machine Learning and Artificial Intelligence and virtual containers.
Measure and quantify impacts of climate change on stratospheric sound propagation, hydroacoustic propagation in the Arctic, and generation of methane-sourced gas emission craters in the Russian Arctic.
Expertise and sensing capability to fuse multi-domain, geophysical observations of explosion sources and their background emissions.
Provide cutting edge, quantitative uncertainty analysis of explosion source parameters via a toolbox of empirical and mathematical techniques.
Orphan Wells (UOWP): collaboration across five national labs to identify and characterize unidentified oil and gas wells utilizing airborne (UAV) sensors and ground-based field mapping.
Produce accurate, empirical estimates of explosion yields from scattered seismic waveform coda.
Quantify and greatly reduce the uncertainties in moment tensors (MTUQ), using seismic observations collected at regional distances from underground nuclear test sites.
Predict 3-D ray-paths from both stationary and moving infrasound sources over the whole atmospheric column (infraGA).
Leverage Bayesian methods to produce joint, seismo-acoustic locations from near surface explosion sources.
Use graph-theory methods to quantify false association and event building errors in seismic networks.
Combine multiple Rayleigh wave polarization measurement techniques to characterize explosion sources is very complex tectonic environments.
Empower big data techniques to predict high-fidelity maps of seismic attenuation over the entire globe.
Demonstrate probabilistic methods to predictively screen small earthquakes from explosions at local distances with seismic phase ratios.
Develop novel data stream fusion methods to integrate evidence of explosions from multiple waveform and optical modalities, for both signal detection and source identification.
Advance generalized hypothesis testing techniques to adaptively detect and characterize noisy threat sources in challenging signal environments.
Characterize climate-induced variability in both infrasonic and hydroacoustic signal environments to quantify propagation uncertainties.
Development of adaptive, eigen-processing techniques to detect signals and quantify performance of IMS arrays in near-real time.