“Advancing Geophysics,
for a Better Future”
Geophysics enables us to image what lies beneath the Earth’s and other planets’ surface using the principles of physics. It plays a vital role in sectors such as energy and climate change.
We apply this knowledge to address some of today’s greatest challenges, advancing cleaner and more reliable energy for the benefit of humanity. The mission is to use geophysics to help create a safer, more sustainable world for generations to come.
Sustainable Future
Mapping the way to a sustainable future! Empowering sustainable solutions.
Clean Energy
The key to sustainable living! Creating energy for a sustainable future.
Climate
Sustainable solutions for a changing climate! Climate Action, Sustainable Progress.
What I do
I study the physics of seismic wave propagation by solving the elastic wave equation to understand how mechanical energy transmits through heterogeneous media. The recorded waveforms represent solutions to this equation, where wave speed, attenuation, and scattering are governed by the Earth’s elastic moduli and density structure. This physical understanding enables me to infer subsurface properties for applications in geothermal energy exploration, subsurface imaging, and the search for critical resources like lithium. I complement these physics-based approaches with deep learning methods for seismic wave picking to improve the accuracy and efficiency of data analysis. I am broadly engaged in geophysics and its role in advancing both fundamental science and practical solutions.
Seismic Absorption and Scattering
Seismic attenuation, the loss of energy as waves propagate through the Earth, occurs through three primary mechanisms. Absorption (intrinsic attenuation) dissipates energy through frictional heating and anelastic processes, quantified by the quality factor Q, and preferentially affects higher frequencies. Scattering redistributes energy due to subsurface heterogeneities, causing wavefront distortion. Geometrical spreading accounts for the decrease in wave amplitude as the wavefront expands over increasing distances.
I analyse attenuation by separating it into absorption and scattering components to image and delineate areas of elevated temperature and fluid content, features that are critical for geothermal energy systems and for detecting geothermal brines enriched with critical metals such as lithium. This type of attenuation analysis provides essential constraints for reservoir characterisation and subsurface imaging in both energy and resource exploration.
Travel-Time Tomography
Travel-time tomography leverages Fermat’s principle and the eikonal equation to solve the inverse problem for subsurface velocity structure by analysing the finite-frequency sensitivity of seismic wave arrivals. I apply this physics-based approach to reconstruct three-dimensional distributions of compressional wave velocity (Vp), shear wave velocity (Vs), and their ratio Vp/Vs, critical parameters that respond distinctly to fluid phase changes, porosity variations, and fracture networks. Elevated Vp/Vs ratios particularly serve as sensitive indicators of fluid saturation, enabling me to delineate geothermal reservoirs and mineralised zones where hydrothermal fluids alter the elastic moduli of host rocks. This methodology provides quantitative constraints on fluid distribution essential for both geothermal energy exploration and targeting critical minerals.
Ambient Noise Tomography
The solid Earth is never truly silent. Even without earthquakes, the ground vibrates continuously at 0.05–1 Hz — driven by ocean waves coupling energy into the seafloor, atmospheric pressure loading the crust, and turbulent river flow. This ambient seismic noise was long treated as contamination to be filtered out. Ambient Noise Tomography (ANT) inverts this perspective entirely: it treats the noise itself as the signal.
The foundation rests on a result from diffuse-field theory: the cross-correlation of a wavefield recorded at two receivers converges, over sufficient averaging time, to the empirical Green’s function (EGF) of the medium between them. If stations A and B record continuous ground velocity \(u_A(t)\) and \(u_B(t)\), their cross-correlation is
\[ C_{AB}(\tau) = \int_{-\infty}^{+\infty} u_A(t)\, u_B(t+\tau)\, dt \]
The lag \(\tau\) at which \(C_{AB}\) peaks gives the inter-station surface-wave travel time. Repeating this across a network of \(N\) stations provides up to \(N(N-1)/2\) independent path measurements, inverted tomographically to map lateral variations in surface-wave velocity. Because Rayleigh waves at longer periods penetrate deeper, a frequency-dependent velocity map can be further inverted — via depth-sensitivity kernels — into a three-dimensional \(V_S\) model of the crust and uppermost mantle.
ANT requires no earthquakes: a few months of continuous recording suffices to reconstruct Green’s functions at periods of 5–40 s, making it uniquely powerful for imaging seismically quiet but structurally complex regions such as mid-ocean ridges, volcanic arcs, and sedimentary basins.
Deep Learning Seismology
The Earth’s subsurface holds a vast amount of information encoded in seismic waveforms information that traditional processing methods only partially recover. My interest in deep learning seismology stems from a conviction that neural networks, trained directly on raw waveform data, can unlock patterns and sensitivities that classical approaches leave untouched.
One area I am interested on is automated phase picking and event location; identifying P and S wave arrival times from continuous seismic records. I am interested in how convolutional and other networks can handle this across varying noise conditions and at the scale of regional seismic networks.
I am also interested in applying deep learning to seismic tomography. Inverting waveforms for subsurface velocity structure is computationally demanding and ill-posed. I am exploring whether neural networks can learn this mapping effectively.
The third area is multiparameter geophysics; integrating P-wave velocity, S-wave velocity, gravity, conductivity and others.
Across all three areas and others, my interest is in approaches that are physically grounded, computationally tractable, and applicable to real data.
“ Science is the key to unlocking the mysteries of our planet.”
Geophysics
“Science: our window into the incredible complexity of our planet?”
Clean Energy
“Charting the unknown through the power of inquiry”
Climate
Let’s work together
Uncovering Solutions for a Better World
The key to sustainable living
Solutions for a better future!