- 3D Inversion of Marine Magnetotelluric Data for Subsurface Conductivity Imaging in Sedimentary Basins - Integrated Seismic Tomography and Gravity Inversion for Ore Deposit Delineation - Bayesian Inverse Modeling of Receiver Functions to Map Crustal Anisotropy - Passive Seismic Monitoring for Microseismic Hazard Assessment in Shallow Crust - Full-Wav eform Inversion for Reservoir Characterization Using Time-Lapse Seismic Data - Ambient Noise Tomography for Crustal Velocity Structure of Tectonic Boundaries - Magnetotelluric Sounding for Groundwater Prospecting in Fractured Rock Systems - Seafloor Deformation Monitoring via Joint Inversion of InSAR and Seafloor Seismic Data - Paleogeographic Reconstruction through Integrated Gravity and Magnetics in Unconventional Plays - Thermo-Hydro-Mechanical Modeling of Reservoir Mines for Enhanced Geothermal Systems - 4D Seismic Attribute Monitoring of CO2 Sequestration Sites - Gravity Gradient Inversion for Subsurface Density Anomalies in Urban Areas - Joint Seismic-Gravity Inversion for Fault Zone Characterization in Cratons - High-Resolution Tomography of Mantle Plumes Using Teleseismic Tomography and Ambient Seismic Noise - Seismic Phase-Arrival Inference Using Deep Learning for Low-Signal Environments - Integrated Geophysical Survey for Coastal Aquifer Delineation Using Electrical Resistivity and Ground Penetrating Radar - In-Situ Seismic Velocity Monitoring of Permafrost Degradation Using Passive Seismic Techniques - Mineral Prospectivity Modeling through Multi-Physics Geophysical Data Fusion - Time-Lapse Electrical Resistance Tomography for Thermal Recovery Projects in Fossil Reservoirs

Project Abstract

This study presents a holistic, multi-physics approach to subsurface characterization by integrating 3D inversion of marine magnetotelluric data, seismic tomography, gravity inversion, and time-lapse geophysical monitoring to image conductivity, velocity, density, and anisotropy across sedimentary basins, crustal boundaries, and near-surface reservoirs. The workflow combines robust data fusion, advanced inversion strategies, and uncertainty quantification to resolve complex heterogeneity due to fluid, mineralization, and structural features. We develop a modular inversion framework that simultaneously treats electromagnetic, seismic, and gravity data, enabling joint constraints on subsurface conductivity, P- and S-wave velocity, density, and anisotropic parameters. A Bayesian hierarchical approach is employed to propagate measurement, model, and prior uncertainties, yielding posterior probability distributions that inform risk assessment for exploration and hazard mitigation. First, the 3D marine magnetotelluric inversion leverages high-density offshore datasets to recover lateral and vertical conductivity variations within sedimentary sequences, highlighting fluid pathways, chert, and saline reservoirs. These MT results feed into seismic velocity and density inversions, improving structural resolution where electromagnetic and seismic sensitivities co-vary. The seismic component integrates full-waveform inversion and ambient noise tomography to delineate velocity structure and crustal anisotropy, with receiver-function-based Bayesian updates to map isotropic vs. anisotropic crustal fabrics. Gravity inversion is used to recover density contrasts associated with lithology changes, salt domes, and concealed intrusions, constrained by independent MT-derived conductivity and seismic-derived velocity models to reduce non-uniqueness. In near-surface and coastal environments, magnetotelluric sounding and integrated electrical resistivity with ground-penetrating radar inform groundwater prospects and fracture networks within fractured rock systems, while time-lapse electrical resistance tomography tracks thermal and fluid-front propagation during enhanced recovery and CO2 sequestration monitoring. Seafloor deformation is interpreted through joint inversion of InSAR, seafloor seismic data, and MT-informed velocity models to quantify vertical and horizontal strain coupled to fluid migration. Paleogeographic reconstructions are refined by assimilating gravity and magnetics data with time-lapse responses to reveal basin evolution and unconformities that influence current reservoir architecture. The methodology advances include regularized, multi-parameter joint inversion with cross-gradient and structural similarity constraints to preserve coherent geology across data types, and adaptive mesh refinement to capture sharp interfaces and low-contrast zones. Model parameterization supports non-linear relationships among conductivity, velocity, and density, enabling consistent cross-physics interpretation. Validation employs synthetic benchmarks, closed-loop field tests, and independent cross-checks against borehole logs, well-logs, and production data. Sensitivity analyses identify data types and acquisition geometries with the greatest impact on parameter recovery, guiding future survey design. The integrated framework enhances subsurface imaging in sedimentary basins, crustal fault zones, permafrost regions, and geothermal systems, delivering high-fidelity, probabilistic subsurface models to support resource discovery, hazard assessment, and environmental monitoring.

Project Overview

What This Project Is About

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A final-year project that explores how geophysical methods can map hidden underground properties. It covers several techniques that help scientists image subsurface features, such as rocks, fluids, and faults, using measurements taken at or near the Earth’s surface. The goal is to build a practical, easy-to-understand workflow suitable for an undergraduate student new to the field.

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The Problem It Addresses

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Many subsurface features are not visible on the surface, yet they affect water resources, energy, and hazards. Existing methods can be complex or require advanced data that's hard to obtain. This project aims to present a clear, beginner-friendly approach to combining multiple geophysical tools to identify underground structures and materials.

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Objectives of the Project

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1. Learn the basic ideas behind marine magnetotellurics, seismic tomography, gravity data, and related methods.
2. Understand how to combine different data types to reveal subsurface properties.
3. Develop a simple workflow for processing data and making visual, interpretable images.
4. Explain results in plain language and relate them to real-world problems like groundwater or minerals.
5. Reflect on limitations and ethical considerations in geophysical research.

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What You Will Do Step by Step

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1. Read foundational material to grasp basic concepts without heavy math.
2. Summarize one or two case studies where geophysics revealed subsurface features.
3. Learn data collection basics, including what measurements look like and how they’re recorded.
4. Practice simple data visualization to turn numbers into understandable images.
5. Work on a small, hypothetical dataset to create a subsurface model.
6. Write a concise report explaining methods, findings, and limitations.

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Expected Outcome

A clear, student-friendly overview of how multiple geophysical methods work together, plus a simple, reproducible workflow and sample figures that illustrate subsurface features. The project will prepare you to discuss geophysical data with non-specialists and to pursue further study or research in earth sciences.