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With the standardization of 5G, commercial millimeter wave (mmWave) communications has become a reality despite all the concerns about the unfavorable propagation characteristics of these frequencies. Even though the 5G systems are still being rolled out, it is argued that their gigabits per second rates may fall short in supporting many emerging applications, such as 3D gaming and extended reality. Such applications will require several hundreds of gigabits per second to several terabits per second data rates with low latency and high reliability, which are expected to be the design goals of the next generation 6G communications systems. Given the potential of terahertz (THz) communications systems to provide such data rates over short distances, they are widely regarded to be the next frontier for the wireless communications research. The primary goal of this chapter is to equip readers with sufficient background about the mmWave and THz bands so that they are able to both appreciate the necessity of using these bands for commercial communications in the current wireless landscape and to reason the key design considerations for the communications systems operating in these bands. Towards this goal, this chapter provides a unified treatment of these bands with particular emphasis on their propagation characteristics, channel models, design and implementation considerations, and potential applications to 6G wireless. A brief summary of the current standardization activities related to the use of these bands for commercial communications applications is also provided.

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Raageshwari Deep Gas (RDG) Field in the Southern part of Barmer Basin is a tight gas-condensate reservoir composed of a thick volcanic unit overlain by volcanogenically-derived clastic Fatehgarh formation. This tight reservoir hosts significant gas reserves and is being successfully exploited with the implementation of multi-stage hydraulic fracturing. For optimum hydraulic fracture stimulation, a clear understanding of the geomechanical properties of the reservoir and its seamless integration with petrophysical interpretation is of paramount importance to achieving long-term sustainable well performance. The key geomechanical factors in hydraulic fracturing of deep volcanic reservoirs form a niche subject as opposed to the widely published unconventional shale plays. This paper illustrates the workflow developed for construction of 1D-Geomechanical model in tight volcanics and its application for selecting perforation intervals and designing of frac jobs; its validation through diagnostic fluid injection, execution of hydraulic fracturing jobs and associated challenges. The one dimensional Geomechanical model integrates basic petrophysical logs, dipole sonic data, rock mechanical tests on core, processed image log data with break out analysis, regional tectonic history, existing natural fracture evidences and drilling data. Most importantly, the model is calibrated with field test data such as diagnostic fluid injectivity test (DFIT), step rate test (SRT) and mini-frac data. The workflow involves estimation of rock mechanical properties (Young's modulus, Poisson's ratio, uniaxial compressive strength) based on logs and calibration with core data and documented analogues. The next step is modelling of stresses in the field for identification of current stress regime. Integration of failure models with wellbore image data provides the understanding of maximum horizontal stress. Basic log data is used for estimation of over burden and pore pressure. Calibration of pore pressure is carried out from the DFIT data. The third step involves the assimilation of rock strength model with stress model to estimate minimum horizontal stress. In a geologically complex setting with multiple histories of tilting and faulting, tectonics plays an important role in the existing stresses. All these variables are captured and validated with field test data to construct a useful geomechanical model. As part of the recently concluded hydraulic-fracturing campaign, the 1D-Geomechanical model was successfully applied to identify approximately 125 fracture stages in 20 wells for multi-cluster hydro-fracturing in the field. An effective geomechanical model, along with petrophysical interpretation has proved to be helpful in enhancing recovery, improving frac success rate and ultimately, reducing cost on operations. The approach emphasizes the importance of continuous update of the model to deal with variation within the field area and heterogeneity in volcanic rocks.

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