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Acoustic measurements based on guided sonic and ultrasonic wave propagation in multilayered structures are used for several different applications in the Oil and Gas (O&G) industry. One of these applications is borehole sonic logging where the propagation characteristics of these waves are recorded and analyzed as function of well bore depth. Petrophysicists can then develop methods to use these real-time measurements to estimate porosity, permeability, formation mechanical properties, fracture & lithology identification, stresses in thin layers, and borehole integrity. These inversion methods for analyzing sonic measurements are based on high fidelity, physics-based models and signal process algorithms to provide engineers reliable information so that they can make informed decision on the availability and safe production of hydrocarbons in an optimal time frame. The physics-based models that are required to generate the necessary synthetic data sets in real-time are computationally intensive, both in time and memory (RAM) This limits their integration into an integrated workflow that will help an engineer make informed decisions in real-time based on these sonic measurements. OnScale have developed fast time domain multiphysics FEA solvers and seamlessly integrated them with cloud high performance compute (HPC) capabilities that addresses these constraints. Further, OnScale can execute massively parallel simulations with an almost linear scalability, allowing users to consider problems far in excess of anything previously attainable from legacy FEA packages
In the rapidly developing world of Internet of Things (IoT), the radio frequency front-end (RFFE) of smart devices will have to handle higher data rates and access the full bandwidth of 4G/5G wireless technology. The reason for this, of course, is the growing demands of ubiquitous low latency data at higher operating frequencies required to accommodate enhanced data transmission capabilities and rapidly growing numbers of users.