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Sexual dimorphism in brain and behavior are often among the most conspicuous forms of intraspecific variation. Gonadal state often shape differences between the sexes. Steroids may directly lead to changes in most of levels of biological organization. In the vertebrate brain for example, expression of steroid receptors and its ligands may lead to direct consequences from the motor systems to the limbic system. The songs of Alston’s singing mouse (Scotinomys teguina) are sexually dimorphic and are composed of a series of rapidly repeated, broad-bandith, frequency-modulated notes. Males sing more often than females. Castration makes songs softer, shorter, and less common. This decrease in performance can be rescued by the application of dihydrotestosterone suggesting that androgen receptors play a critical role. In this dissertation, I seek to further understand the role of the androgen receptor in influencing the singing behavior of this species by three interconnected aims. First, we map the sites of androgen sensitivity along a pathway that spans from limbic structures to vocal control regions and quantify differences in nuclear androgen receptor-like labeling in male and female brains. Second, we use a transsynaptic virus to examine how the forebrain connects to the motor control of the jaw and larynx. Third, we manipulate the hormonal milieu by castrating and then implanting DHT to observe changes in both brain and behavior. Together we gained better insight into not only how androgen receptors mediate changes to vocalization but also how gonadal state lead to variation between the sexes.

Distinct from conventional reservoirs, shale formations have limited pore connectivity and unique pore spatial-distribution. Consequently, theoretical pore-network models developed for conventional formations are not representative of the porous media in unconventional rocks. This work presents a novel theoretical pore-network model, the dendroidal model, based on the analysis of pore-scale model reconstruction extracted from Scanning Electron Microscope images. The dendroidal model is a “semi-acyclic” model, which characterizes the limited connectivity of void space without sacrificing the interaction among main flow paths. The dendroidal model infers pore-body distribution based on the hysteresis effect of isothermal adsorption/desorption measurements and characterizes pore-throat distribution using mercury drainage capillary pressure experiments. The use of dual-compressibility model in the pore-network model construction eliminates the compressibility effect of void space, including connected pores and dead-end pores, in mercury drainage experiments. The total organic carbon (TOC) content and minerology are measured by experiments to determine the composition of pore bodies and pore throats in the dendroidal model. The difference in mercury intrusion and extraction caused by the trapping hysteresis and contact-angle hysteresis affects the stochastically distributed parameters, including pore-throat length, pore-throat cross-sectional geometry, coordination number and pore-body spatial distribution. I validate the dendroidal model by predicting the absolute permeability of the core samples from Marcellus and Wolfcamp shales. This newly developed pore-network model integrates the aforementioned seven distinct types of experiments to capture the realistic pore structures of shales. Extracted pore-network modeling is an efficient and reliable way to provide a platform for mathematical simulation of fluid flow in porous media and for predicting the transport properties. However, the existing algorithms for pore-network extraction have deficiencies in characterizing the porous media of shale core samples in as much as they cannot capture the unique features of unconventional reservoirs. In nano-scale pores, the accurate characterization of the porous geometry is important, since the relative error will be significant without considering trivial information. The newly developed approach, based on the maximal-ball method, proposes a novel and enhanced algorithm for the classification of pore throats and pore bodies. It also has a better performance in characterizing the corresponding properties that include pore-throat length, pore size and geometric factors. The Marcellus shale core samples are scanned using scanning electron microscope imaging with the resolution of 4 nm. The pore-network models based on the tomographic images are constructed, and the aforementioned parameters are compared and analyzed. The quantification of liquid transport in liquid-rich shales is crucial for an economical exploitation of hydrocarbon. The laboratory measurement of permeability is challenging as it is time-consuming and includes large uncertainties. Direct pore-scale modeling and extracted pore-network modeling are alternatives for the prediction of transport properties. But due to its prohibitively high computational cost, its applications are limited to micro-scale. The emphasis of this work is to understand the mechanisms of nano-confined liquid transportation (nano-scale) and to quantify the liquid transport capacity in the scales of core samples (centi-scale). A modified Navier-Stokes equation is developed to integrate the variation of fluid properties with respect to the strength of liquid-wall interaction. To predict the apparent permeability in large scale, the dendroidal theoretical pore-network model is constructed by integrating mercury drainage/imbibition and isothermal adsorption/desorption experiments. The dendroidal model also integrates the data of Fourier Transform infra-red spectroscopy experiments to characterize the mineralogy distribution and total organic carbon to distinguish organic pores and inorganic pores. Results from molecular dynamics simulation indicate that the flow capacity of nano-confined liquid can be 1-3 orders different from that calculated by Navier-Stokes equation without considering the boundary-slippage effect. The geometry and composition also have considerable effect on the surface friction factor and viscosity in the near-wall fluid film, which in turn significantly influence the flow capacity in nano-pores. This work investigates the mechanisms of liquid flow in nano-confined pores with various composition and geometries. Accurate characterizations of liquid transport in shales will provide significant advantage in the field development planning of unconventional resources.

This thesis presents a novel analytical solution to predict the expansion of drainage volume for compound transient linear flow system consisting of stimulated-reservoir volume (SRV) and unstimulated shale/tight sandstone matrix volume. The distance of investigation (DOI) has been demonstrated to be a useful notion for production data analysis; e.g., optimization of spacing of hydraulic fractures, and evaluation of stimulated-reservoir volume (SRV). The DOI concept has been mainly used to evaluate dynamic drainage volume (DDV) for the linear flow system only within SRV. Thus, in view of production from both SRV and unstimulated shale/tight sand matrix; the DOI (or DDV) of transient linear flow in compound multi-stage fractured reservoirs has not been able to be determined yet. In this work, we derive the DDV equation analytically for compound transient linear flow system under constant-flowing-pressure and constant-production-rate condition for the compound linear flow system. To that end, coupled with the analytical equation calculating the pressure and DDV of linear flow within only SRV, the compound linear flow solution within both SRV and unstimulated matrix is derived. Laplace transform and numerical inversion are implemented to obtain the semi-analytical solution. The pressure front is calculated by implementing the impulse response concept, which is the maximum rate of pressure response. In addition, a relationship was established between DOI and square root of time using multivariable regression, based on the results of 2000 cases calculated from our semi-analytical solution. The cases capture the impact of several parameters, including different diffusivities within SRV and unstimulated matrix, hydraulic fracture length, and fracture spacing. Our solution suggested that the DOI demonstrates a linear relationship to the square-root-of-time for both linear flow within SRV and the compound linear flow system. The advancement of DDV within stimulated-reservoir volume is significantly faster than that within unstimulated matrix. The majority of production is attributed to size of stimulated-reservoir volume. To verify the accuracy of the new DDV equations, we analyze the synthetic production data from a series of fine-grid numerical simulations. Employing the DDV model and empirical equation, a novel workflow of integrated production data analysis is proposed to evaluate and predict the performance of multi-stage fractured horizontal well (MFHW). A weak (integral) form of macroscopic mass balance model with moving boundary is developed for the expanding productive region (drainage volume) during long-term transient-flow regimes in non-static shale reservoirs saturated with compressible fluids. The effects of stress-dependent reservoir and pressure-dependent fluid properties on production analysis are incorporated by a pressure-dependent correction factor. To verify the accuracy of our integrated analysis, firstly, we start with a synthetic simulation example with known parameters. In the next stages, several field examples are examined with our integrated analysis approach to evaluate and predict the performance of MFHW. The size of DDV and associated average reservoir pressure, recovery factor (RF) and average saturation (oil/gas/water) are achieved. The half-length of primary fracture and diffusivity within SRV are also evaluated by coupled with a correction factor, and the ultimate drainage volume (estimated as ultimate recovery, EUR) is also predicated at abandonment condition, which indicates the maximum size of system affected by single-well production for us to optimize well spacing. Moreover, the contributions of both unstimulated-reservoir matrix and stimulated-reservoir volume (SRV) are quantified with changing time, respectively. The proposed approach has the following novel contributions: (1) capability to ascertain DDV and associated average reservoir pressure throughout different transient-flow regimes; (2) incorporating non-static, fluid compressibility, multi-phase flow and moving flow boundary effects into production history analysis; and 3) simplicity and efficiency; does not require comprehensive inputs as opposed to sophisticated numerical simulations, but could obtain almost all of the necessary parameters for evaluation and prediction.