Point-Spread Function (PSF) Imaging
In-Depth Proprietary Technology
In the optical, astronomical, and medical imaging fields, images passing a through a lens are convolved with a Point-Spread Function (PSF), blurring the output image. When this lens contains irregularities or other flaws, this PSF can also introduce artifacts.
We can use time-honored optical imaging approaches to mitigate artifacts around complex geology by treating each subsurface ray as traveling through its own unique lens, modeling the resulting PSF, and deconvolving the final image in the 5D VOT/VAT domain to produce a result free of the associated artifacts and distortions.
Fig. 1. RTM Salt-body image with and without PSF Imaging. PSF Imaging, applied in the VOT/VAT domain, dramatically improves visibility and reduces artifacts in regions with complex geology.
Fig. 2. A comparison between clean (left) and noisy (right) modeled PSFs in seismic data. The artifacts present on the right were created due to the presence of a salt body, corrupting the image. These artifacts were removed using deconvolution, e.g. in Fig. 1.
Fig. 3. A brief explanation of PSF deconvolution, which is commonly applied in fields outside of seismic. If the PSF is constant and known, then an image can be deconvolved using the PSF in order to generate a higher-resolution result. In conventional seismic processing, the PSF is neither constant nor known. However, we can model a unique PSF for each individual ray path, allowing us to proceed with deconvolution despite the highly-variant nature of the subsurface.
Fig. 4. The famous M87 black hole image, acquired in 2019. This image utilized a similar deconvolution pipeline (CLEAN) to remove artifacts from noisy PSFs due to the limited spatial resolution of telescope arrays.