Streets make up the majority of our urban environment and are detrimental to a city's sustainability. While multiple studies focus on assessing street performance, they often exclude alleyways despite being a ubiquitous walking infrastructure that greatly increases network efficiency. This paper examines uses MCA to assess the impact of alleyways on a neighborhood's accessibility and on network betweenness. Results reveal that alleys increase neighborhood accessibility; however, they have varying impact on betweenness centrality. Further studies are needed to enable the interpretation of betweenness values to wholly understand street network performance.
The co-location of photovoltaic and crop production - often referred to as Agrivoltaic - has been proven to be an economically viable solution to mitigate the competition for land between food and solar energy production in temperate climates. In arid regions, where competition for land has a more marginal role, Agrivoltaic could, in contrast, help reclaim marginal land and enhance agricultural and solar energy production efficiency. When deployed above cropland, PV modules can substantially modify the surface energy budget, reduce sensible heat fluxes, and increase latent heat fluxes (evaporative cooling). However, the successful implementation of Agrivoltaic in arid regions also require the selection of crops able to endure shadowing and the harsh environmental conditions of the region. Here, we present a crop selection methodology for dryland agrivoltaic, based on the hydraulic, salt-tolerance and shadow-tolerance characteristics of different crops. Our results represent a benchmark for future agrivoltaic implementation in arid regions.
Pore network modeling was performed to calculate the absolute permeability of 3D micro-CT rock images. A regression-based renormalization method was applied to calculate the equivalent permeability of four different rock samples. And significant decreases on the relative error between the direct permeability and scaled permeability were observed by comparing the results obtained through original Karim and Krabbenhoft's renormalization method and the regression one, respectively.
This study adopts state-of-art transfer learning, into semantic segmentation of real 2D carbonate rock images. With pre-trained networks such as VGG16 and MobileNet-V2 used as the encoder of proposed semantic segmentation deep neural networks in literature, we obtained comparable results of training, validation, and testing metrics and minimize required computational time with low training samples.
Surfactants are used in oil industry for applications such as chemical enhanced oil recovery and hydraulic fracturing. While it is widely agreed that surfactants alter rock surface wettability towards a more desired wetness state, parameters and mechanisms responsible for such alteration have not been fully understood and require further investigation. This study involves experimental investigation of wettability alteration potential of surfactants as a function of rock minerology. To accomplish this, contact angle, surface properties, adsorption, pore structure and mineralogy of rocks pre and post applying surfactant are measured. Samples include carbonates and shales which are expected to cover a representable range of minerology. Moreover, contact angle determination is carried out at ambient and high-pressure operating conditions to reflect reservoir conditions. Surfactants utilized include cationic CTAB and anionic SDBS. Results are further complemented by image analysis. Results demonstrate a relationship between surfactant adsorption behavior to operating conditions, concentration and surfactant type.
A model for single-phase fluid flow in tight UCRs was previously produced by modifying the flow Forchheimer's equation. The new modification addresses the fluid transport phenomena into three scales incorporating a diffusion term. In this study, a new liner model, numerically solved, has been developed and deployed for a tight gas case study. Ideally, the new model suits fluid flow in tight UCRs. The modified Forchheimer's model presented is solved using the MATLAB numerical method for linear flow. Very simple profiles and flow dynamics of the main flow parameters have been established and a thorough parametric analysis and verifications were performed. It has been observed that the diffusion system becomes more prominent in regulating flow velocity with low permeability of the formation rock and low viscosity of the flowing fluid. The findings indicate a behavioral alignment with a previous hypothesis that matches actual reservoir behavior.
Polymer flooding is one of the promising enhanced oil recovery techniques being applied to improve oil recovery from various oil fields since the early 60s, with polymer adsorption being the one of major drawbacks. Polymer enhanced oil recovery technique has been widely used in sandstone reservoirs and has limited applicability to carbonate reservoirs mainly due to prevailing harsh conditions in these reservoirs. This paper provides a comparative study of polymer flooding focusing on polymer adsorption in both sandstone and carbonate reservoirs including the polymer adsorption types, adsorption mechanisms, and factors affecting polymer adsorptions in both reservoirs.
This paper aims to describe an investigative study behind the effect of fluid leak-off in a dual porosity system and hydraulic fracture propagation geometry on improving the hydrocarbon recovery. This is achieved through the application of the Perkin-Kern-Nordgren-Carter Equation II (PKN-C) and Pseudo Three-Dimensional-Carter Equation II (P3D-C) models in analyzing the fracture propagation geometry using an in-house numerical code. This investigation provides an insight to the complexities associated within hydraulic fracturing treatment design. Thus, this may ultimately assist future fracturing operations in the region.
For decades there has been an interest in water alternate gas (WAG) injection. WAG injection improves oil recovery on both microscopic and macroscopic levels by combining the benefits of conventional waterflooding and gas injection. This research is aimed at the optimization of WAG injection. The investigated field case study is named Volve, which is a decommissioned field in the North Sea. Sensitivity analysis of WAG injection on this base case was studied. The following parameters were considered; WAG ratio, time to start WAG, total gas slug size, cycle slug size, and tubing diameter. A full two-level factorial design was utilized for the sensitivity study. Sensitivity study results showed that the total slug size is the most important parameter followed by time to start WAG, and then cycle slug size. WAG ratio appeared on some of the interaction terms while tubing diameter effect was found to be negligible.
In this study, three new models that accommodate the sorption and desorption effects have been developed and studied for an unconventional tight reservoir by utilizing Knudsen's and Langmuir's models. The new models have been analyzed using synthetic data and compared to previously published models that cater to the same phenomena. The suggested new model presented is solved using MATLAB numerical method for linear flow. Comparing results using different fluid flow models has been analyzed and proved that the new modified model has better estimation utilizing various case studies. It has been observed that the diffusion system becomes more prominent in regulating flow velocity with low permeability of the formation rock and low viscosity of the flowing fluid. Additionally, the sorption mechanism contribution to the flow increases with low permeability of the medium and low viscosity of the flowing fluid leading to release gas trapped in pores and rock surfaces.
