Abstract: A semiconductor structure includes a substrate that includes a base, a plurality of channel layers on the base, and an isolation layer between each of the channel layers. The semiconductor structure also includes a gate on the substrate, spanning a top and a portion of sidewalls of the channel layers. The semiconductor structure also includes a sidewall structure on sidewalls at two sides of the gate, a source/drain region in the substrate at two sides of the gate and the sidewall structure, a source/drain electrical connection layer on the source/drain region, and an isolation structure between the source/drain electrical connection layer and the gate. The isolation structure includes a cavity, including a first cavity region and a second cavity region located on the first cavity region. A width of the second cavity region is smaller than a width of the first cavity region.

Abstract: A method is described for estimating seismic velocity from seismic data by training a neural network using a subset of a seismic dataset and the velocity model; estimating a second velocity model using the neural network and a second subset of the seismic dataset; and displaying the second velocity model on a graphical user interface. The method may be executed by a computer system.

Abstract: A method is described for estimating seismic velocity from seismic data by training a neural network using a subset of a seismic dataset and the velocity model; estimating a second velocity model using the neural network and a second subset of the seismic dataset; and displaying the second velocity model on a graphical user interface. The method may be executed by a computer system.

Abstract: A method is described for seismic imaging including image enhancement using a trained neural network. The neural network may receive training pairs of low signal-to-noise ratio 3D seismic images and high signal-to-noise ratio 3D seismic images; train a neural network on the training pairs wherein the training uses atrous convolution; receive a seismic image representative of a subsurface volume of interest; apply the neural network to the seismic image to generate a second seismic image; and display the second seismic image on a graphical user interface. The method is executed by a computer system.