The signal energies of the rate (cause) and pressure (effect) are used to detect the fracture events in time, such as height growth, screen-out, and hydraulic fracture-natural fracture interactions. The energy of a range of frequency band can be computed from the wavelet transform, which is a powerful technique in signal processing. Hydraulic fracturing rate and pressure data are interrelated signals and can be subjected to signal processing techniques. Implementation results indicate the compression ratio is increased with less PSNR and also increases in speed with low power.
The architectures are designed using Xilinx SYSgen and implemented in the Zynq 7000S devices feature a single-core ARM Cortex™-A9 processor mated with 28 nm Artix®-7 based programmable logic processor. The discrete wavelet transforms for a 2-dimensional with balanced wavelet has been structured utilizing MATLAB program for individual modules like forwarding balanced Wavelet Transform and Inverse balanced Wavelet Transform to establish the peak signal to noise ratio (PSNR), correlation in between the recovered image and input image. The 2D architecture is realized by cascading two N points (1-D) owing to linearity, balance, and compact support of the multi-dimensionality of the biorthogonal wavelet.
An area-competent and low power pipelined direct mapping Very Large-Scale Integration Architecture for multidimensional (2D) balanced biorthogonal wavelets for image compression is discussed.
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