Quantitative lithofacies modeling is important to understand the depositional and diagenetic history, and hydrocarbon potential of unconventional resources at a regional scale. The complex heterogeneous nature and large data dimensionality of unconventional mudstone reservoirs increase the challenge of lithofacies interpretation by conventional qualitative methods. Quantitative shale lithofacies, which are meaningful, mappable, and predictable at core, well log, and regional scales, can be defined based on mineralogy and Total Organic Carbon (TOC) derived from core analysis and advanced geochemical spectroscopy logs (e.g. Pulsed Neutron Spectroscopy, PNS). However, access to numerous and widespread core samples and geochemical log responses is typically limited by cost and time. We apply different mathematical techniques to ubiquitous conventional well log suites calibrated to rock types, defined by the limited number of wells with high-quality core and geochemical logs. The documented interrelationships between lithofacies and conventional logs are propagated with a quantified degree of accuracy in wells without advanced log or core data. Our study addresses issues of different approaches of quantitative lithofacies classification and

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The trend of increasing digital system performance by downscaling the device size poses daunting challenges in system design due to the increased power density, higher I/O count, interconnect bandwidth, and timing closure requirements. Silicon carrier with Through Silicon Vias (TSVs) or TSI technology is identified as a system and packaging level solution to overcome all those challenges. In this paper we describe the key electrical elements in a typical TSI digital system and discuss their impact on overall system performance. We also discuss the system level power integrity analysis for TSI as its power delivery is one of the major engineering challenges.