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The term "full waveform inversion" (FWI) refers to a seismic imaging technique used in geophysics to reconstruct subsurface Earth models with high resolution. FWI is a full-physics method that aims to match observed seismic waveforms with synthetic waveforms generated from a subsurface model, adjusting the model iteratively to minimize the difference between the two. Unlike traditional reflection-based methods, FWI utilizes the entire seismic waveform, including both reflected and transmitted waves, to improve the accuracy of subsurface imaging.

The process begins with an initial Earth model, often derived from surface seismic data or well logs. Seismic sources generate waves that propagate through the subsurface, and receivers record the resulting waveforms. The recorded data is compared to synthetic waveforms computed from the initial model. By analyzing the discrepancies between observed and synthetic waveforms, FWI adjusts the model parameters—such as velocity, density, and other physical properties—using optimization algorithms like gradient-based methods. This iterative process continues until the synthetic waveforms closely approximate the observed data, yielding a refined subsurface model.

FWI is particularly valuable in complex geological environments where traditional methods may fail, such as in areas with significant lateral velocity variations or overthrust structures. It is widely applied in oil and gas exploration to improve reservoir characterization, reduce drilling risks, and enhance hydrocarbon recovery. However, FWI can be computationally intensive and requires high-quality seismic data and robust inversion algorithms to ensure reliable results. Advances in computing power and optimization techniques continue to expand its practical applications in geophysical exploration.