Abstract
In its most practical terms, the energy transition is a diversification of and systems-level approach to the natural resources and infrastructure therein required to meet the increasing global demand for accessible, affordable, and sustainable energy. Specifically, it manifests as an augmentation to traditional hydrocarbon-based energy solutions with additional energy sources such as nuclear, wind, ocean-wave, hydro, biomass, solar, and geothermal power. As such, the deep reservoir of knowledge matured through decades of research in oil and gas has opportunity to both broaden its impact and inspire new research in the emergent and rapidly evolving energy-technology landscape. The special section in this edition of The Leading Edge is dedicated to highlighting high-impact research in near-surface geophysics as it borrows from the past successes of exploration geophysics to shape the future of this landscape for the betterment of people everywhere.
Near-surface geophysics is often defined as the application of geophysical methods to investigate shallow (upper few tens to hundreds of meters) subsurface properties and processes. In the energy sector, where exploration depths extend to about 5 km, 1 to 2 km depths of investigation are relatively shallow, and less than 1 km is very shallow. This special section considers geophysical methods and data analysis approaches to better understand properties and processes, at these relatively shallow depths, as they relate to renewable energy resource characterization, monitoring, and production.
The range of contributions in this special section highlights the breadth of exploration needs in the renewable energy sector that near-surface geophysics can meet. For example, Pradhan et al. call attention to the importance of understanding induced fracture patterns in enhanced geothermal systems (EGS), in which water heated by latent crustal heat is extracted via opened or newly created fractures. EGS requires careful site characterization before and high-resolution imaging and data analysis after inducing fractures (a.k.a. enhancement). The authors present coda wave interferometry as an approach to monitoring changes in fracture patterns, which are incredibly difficult to predict and image, by utilizing late-arriving seismic scattering waves to detect small changes in the fracture network at the EGS Collab Experiment in South Dakota, USA.
A detailed understanding of subsurface structures is very important for offshore wind development. Caselitz et al. present a fast, high-resolution, 3D seismic survey approach that improves upon 2D seismic surveys in terms of data resolution, quantitative interpretation, and acquisition efficiency. Such improvements aid in estimating soil properties and building ground models necessary for wind farm design. The authors offer example results from Ten Noorden van de Waddeneilanden Wind Farm Zone off the coast of the Netherlands.
Rovetta et al. offer a compelling look into the future of computational geophysics through application of quantum computing to the challenge of deep-target seismic imaging in the presence of near-surface complexities. The resultant phase and amplitude residuals from a near-surface structure are analyzed in the context of a specialized quantum annealing process that exploits quantum superposition and tunneling to avoid well-known inefficiencies in traditional optimization-based approaches to stack-power maximization of seismic gathers. In their method, residuals are instead quantified by a discrete quadratic model with a hybrid solver that utilizes both classical and quantum optimization.
Addressing the challenge that anthropogenic clutter mapping poses in derisking exploration and characterization of previously developed sites, Mukherjee et al. demonstrate a novel application of artificial intelligence (AI) technology to magnetic field data. In contrast to target reconstruction via traditional inversion or trial-and-error curve fitting, the authors show how an AI workflow not only is capable of recovering the location and distribution of subsurface clutter but also offers a scalable framework for cases where the number of targets is large.
Lastly, Zhao et al. present a case study from the Tarim Basin, China, where near-surface complexities — similar to those found in the Arabian Peninsula and the Andes of South America — define a need for advanced seismic data acquisition and analysis to minimize uncertainty in deep reservoir characterization. To that end, they describe progress in four key areas: constrained near-surface tomography, long-offset acquisition for improved turning-ray tomography, finite-frequency wavefront tomography as an alternative to full-waveform inversion, and development of a comprehensive velocity model combining both diving and reflected seismic waves. They demonstrate how these concepts, applied in the Tarim Basin, can be utilized elsewhere in the world.
