Abstract Reliable interpretation of time-lapse (4D) seismic data is essential for monitoring injected CO and ensuring safe long-term storage, yet observed differences between vintages are often dominated by acquisition non-repeatability, near-surface variability, and imaging artifacts. We present an automated workflow that combines Local Orthogonalization Weighting (LOW), a physics-guided method that isolates dynamic fluid-induced changes, with a compact 3D deep learning model (TLNet) that predicts CO plume probability from paired baseline–monitor volumes. LOW suppresses repeatable geology and stabilizes the dynamic anomaly, enabling simple value and texture gates to produce volumetric plume labels without manual interpretation. TLNet learns from these seismic-driven labels, generating high-resolution plume probability volumes that capture thin-layer confinement, lateral variability, and intra-tier fingering. The workflow is demonstrated on the Sleipner CO storage project, and the LOW component is further evaluated on the Cranfield and Duri fields to assess robustness across marine and land surveys, shallow and deep targets, and CO and thermal-EOR settings.

Abstract Seismic full waveform inversion (FWI) is a powerful tool for monitoring subsurface changes during carbon capture and storage (CCS) operations, but its ill-posed nature makes uncertainty quantification (UQ) essential for reliable interpretation. Sampling-based Bayesian methods such as Markov chain Monte Carlo (McMC) provide rigorous UQ but are computationally demanding. In conventional FWI, elastic properties are assigned to densely discretized space-filling cells, resulting in a high-dimensional parameterization that makes large-scale elastic FWI computationally infeasible. To address this challenge, we propose a rock-physics-guided parameter-reduction strategy that compactly represents the CO2 plume geometry using cubic splines controlled by a limited number of nodes. This parsimonious parameterization not only significantly reduces the number of model parameters and the forward simulations required for an effective UQ using sampling methods but also has the potential to improve the practicality and efficiency of other types of UQ methods. Numerical experiments on a cross-well synthetic scenario and a field-scale case based on the Aquistore storage site in Saskatchewan, Canada, demonstrate that the method efficiently reconstructs the plume shape and its extent and that it converges to consistent posterior distributions across multiple Markov chains.

Abstract Characterizing carbonate aquifers presents significant challenges, especially when it involves determining groundwater flow zones at the field scale. The combination of seismic data and well logs, along with a suitable processing approach, supports this effort. We processed high-resolution reflection seismic data obtained from the Port Mayaca aquifer, located in Martin County, South Florida. We applied a forward solution algorithm to invert this data for impedance. The resulting images displayed anomalies associated with dense, tight limestone layers. These anomalies, combined with Formation MicroImager (FMI) data and micro-resistivity logs, lead to the existence of fractures. To enhance our analysis, we applied an artificial neural network (ANN) using seismic attributes from the seismic waveforms and the impedance data. The initial image produced by the ANN algorithm illustrates the pore space based on the aspect ratio log, which serves as the target data for the neural network model. The Python library Keras provided the framework needed to develop these network models. The application of the Keras software allows us to create images of pore aspect ratio, Stoneley (ST) wave permeability, and intrinsic permeability. The interpretation and analysis of these images revealed the connectivity of the pore space between narrow and wide channels, as well as the flow paths linked to the permeable zones. The ST wave permeability image highlights the major flow zones present in the inter-well region. The results of the data analysis demonstrate that a flow zone structure, defined by the aspect ratio, is part of a groundwater channel. We found that a permeable zone identified in the ST permeability image represents the total flow created by the interconnected vugs and fractures. We generated ELAN intrinsic permeability images to examine the aquifer’s pore structure, and we found that the areas with low-intrinsic permeability correlate with locations of dense, fractured limestone layers.

Abstract Monitoring CO2 storage sites over decades requires cost-effective, reliable strategies to ensure containment and conformance. Conventional approaches such as repeated 3D/4D seismic surveys are expensive and logistically challenging, particularly offshore. The SPARSE project, developed under ACT4, introduces a sparse nodebased multiphysics monitoring concept that integrates seismic, electromagnetics, gravity, and deformation measurements. This approach is designed to reduce survey frequency while maintaining sensitivity to pressure and saturation changes. We present results from onshore field trials at Carbon Management Canada’s Newell County site and offshore feasibility studies based on the Smeaheia CO2 storage model. Onshore tests demonstrate the feasibility of using permanent seismic sources, distributed acoustic sensing, and electromagnetic configurations within a sparse monitoring framework. Offshore modeling indicates that seismic, electromagnetic, and gravity signals can detect plume arrival, monitor its development over time, and distinguish between different migration scenarios under realistic noise conditions. These findings support the feasibility of sparsenode multiphysics monitoring as a scalable and costefficient approach for longterm CO2 storage assurance, complementing conventional methods and informing future deployment.

In episode 281 of SEG’s Seismic Soundoff podcast, Betty Johnson shares how her early career in gravity and magnetics grew from curiosity, hands-on learning, and rapidly changing technology. She explains how potential field methods remain valuable for addressing energy, water, and climate challenges because they are affordable, scalable, and deeply rooted in the earth’s history.

Abstract Electromagnetic (EM) methods are used in mineral exploration to detect conductive ore bodies. The ability of an EM system to detect geological targets at depth is partly dependent on the coupling the interaction between the transmitter’s primary magnetic field and the target conductor which is highly dependent on the target’s orientation. A novel three-component transmitter (3CTx) EM system was developed for ultimate implementation in airborne, semi-airborne, or ground systems. Its additional transmitter coils and multiple transmitter locations could provide a greater signal-to-noise ratio for deep geological bodies, while the co-orthogonal coils and resultant multiplicity of primary-field directions increased coupling with a wide range of target orientations. A prototype 3CTx system was designed, constructed, and field-tested. The primary objective was to validate the fundamental concept: that signals from the three transmitters could be acquired simultaneously by a receiver and then successfully separated during processing. Initial results from three field tests demonstrated that the individual transmitter signals could be separated with minimal cross-coupling, producing data comparable to that from a conventional single-component ground-loop system. This success validated the methodology, a crucial first step toward developing a full-scale system for deep exploration.

Abstract Airborne radiometric surveys use passive geophysical techniques to characterize geochemical variations at or near earth’s surface. These methods have been used for a variety of mapping applications, including mineral resource evaluation. However, detailed characterization of smaller geologic targets, including mine waste features, requires flying at lower altitudes and with tighter line spacing than is feasible with traditional aircraft. Here, a small uncrewed aircraft system (sUAS) equipped with a radiometric sensor was used to acquire high-resolution gamma-spectrometry over small mine waste features and a low-grade stockpile in southwestern New Mexico. The sUAS radiometric system mapped local variability within each survey area and revealed ~2–10 m wide zones where radioelements K, Th, and U may be elevated 2–10× the surrounding material. Additionally, the sUAS radiometric data revealed radioelement variability across survey sites, which correlated reasonably well with variability seen in geochemical samples at each survey site, even though samples collected from individual sites showed high local variability. The sUAS data characterized local heterogeneity within mine waste and other small geologic targets at scales of a few meters to tens of meters, which is not possible with traditional crewed aircraft, and with continuity of coverage that is not possible with ground surveys, thus filling a key gap in geophysical survey spatial resolution.

The November 2025 issue of TLE features a special section about geophysics for mineral exploration. This file includes the entire issue in PDF format.

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Abstract Carbon dioxide mineralization in basaltic rocks presents a promising approach for mitigating rising atmospheric CO2 levels. Although this method appears effective, hydrothermal alteration, which is common in many basaltic provinces worldwide, introduces significant challenges to efficient CO2 and rock interaction. Understanding the influence of such alteration is essential for assessing the suitability of basaltic reservoirs for carbon storage. This study focuses on basalt samples from the KLR-1 borehole in the eastern Deccan Volcanic Province, India. The samples are dominated by altered massive basalts containing chlorophaeite, an amorphous iron-rich silicate typically formed through the alteration of olivine. Due to its disordered structure and high water content, chlorophaeite can reduce seismic wave velocities substantially. Through geophysical, petrographic, and mineralogical observations, we discuss how the presence of such phases can affect elastic properties and complicate the interpretation of seismic monitoring techniques. Drawing from previous experimental and modeling studies, we explore possible scenarios where chlorophaeite may either promote or inhibit carbonate precipitation, depending on its reactivity. These insights underscore the need to consider the mineralogical state of altered basalts while evaluating their potential for long-term CO2 storage and highlight the importance of geophysical methods in tracking the changes in formation properties.