Permeability and capillary pressures are important petrophysical properties. Permeability is one of the most important parameters for reservoir management and development. Capillary pressure data have been widely used in evaluating reservoir rock, sealing capacity, transition zone thickness, pay versus non pay, and absolute and relative permeability. We are working in this study modification tw...

This study was undertaken to determine in vivo permeability coefficients for fluoroquinolones and to assess its correlation with the permeability derived using reported models in the literature. Further, the aim was to develop novel QSPR model to predict corneal permeability for fluoroquinolones and test its suitability on other training sets. The in vivo permeability coefficient was determined...

Water permeability is a key concept when estimating load bearing capacity, mobility and infrastructure potential of a terrain. Northern sub-arctic areas have rather similar dominant soil types and thus prediction methods successful at Northern Finland may generalize to other arctic areas. In this paper we have predicted water permeability using publicly available natural resource data with regr...

The estimation of the formation permeability is considered a vital process in assessing reservoir deliverability. prediction such rock property with use minimum number inputs mandatory. In general, porosity and are independent petrophysical properties. Despite these observations, theoretical relationships have been proposed, as that by Kozeny–Carmen theory. This theory, however, treats highly c...

Abstract The large-scale grid-connected access to distributed PV power generation has posed a great challenge the new system. Distributed output and load have strong uncertainty volatility, which increases difficulty of distribution network net prediction certain extent. To improve accuracy grid power, paper proposes combined method based on XGBoost RBF neural networks. combination two algorith...

Permeability is one of the most important reservoir rock parameters in petroleum engineering, reservoir, and exploitation. This parameter causes movement hydrocarbon reserves rock. Therefore, it an from economic point view because greatly impacts amount extraction In this study, combined RBFNN-GA algorithm 200 data sets collected a field Middle East were used to predict permeability. Water satu...

We propose a novel deep learning framework for predicting permeability of porous media from their digital images. Unlike convolutional neural networks, instead feeding the whole image volume as inputs to network, we model boundary between solid matrix and pore spaces point clouds feed them network based on PointNet architecture. This approach overcomes challenge memory restriction graphics proc...