The feasibility of data based machine learning applied to ultrasound tomography is studied to estimate water-saturated porous material parameters. In this work, the data to train the neural networks is simulated by solving wave propagation in coupled poroviscoelastic-viscoelastic-acoustic media. As the forward model, a high-order discontinuous Galerkin method is considered, while deep convoluti...

The present paper is to focus on a boundary value problem in a homogeneous, isotropic, elastic body with double porosity. After developing mathematical formulation, a state space approach has been applied to investigate the problem. As an application of the approach, normal force has been taken to illustrate the utility of the approach. The expressions for the components of normal stress and eq...

The enactment of strict laws on reducing pollution and controlling combustion has given rise to the necessity of considering a new approach to energy supply in the future. One such approach is the use of hydrogen as an alternative to fossil fuels. Hydrogen and synthesis gas are typically produced through the partial oxidation of methane in porous media. This process was theoretically simula...

In this thesis, we study the relationship between size and depth for Boolean circuits. Over four decades, very few results were obtained for either special or general Boolean circuits since Spira gave the first related result. Spira showed in 1971 that any Boolean formula of size s can be simulated in depth O(log s). (A Boolean formula is a tree-like circuit, that is the fan-out of every gate i...

Downed logs are known to increase species diversity in many forest ecosystems by increasing resource and structural complexity and by altering fire behavior in fire-prone ecosystems. In a frequently burned oak savanna in central Missouri, combustion of downed logs formed patches that have remained free of herbaceous vegetation for more than 3 years. To assess the influence of ‘‘log burnouts’’ o...

In this paper I propose a computationally practical simulation estimator for large categories of the dynamic panel Tobit model with complicated dependence structures. I first apply the sequential decomposition methods introduced by Hendry and Richard (1992) to obtain the tractable simulated log-likelihood function of the dynamic panel Tobit model. I then maximize this log-likelihood function si...

We propose a preprocessing methodology for well-log geophysical data based on Fast Independent Component Analysis (FastICA) and Discrete Cosine Transform (DCT), in order to improve the success rate of the K-NN automatic classifier. The K-NN have been commonly applied to facies recognition in well-log geophysical data for hydrocarbon reservoir modeling and characterization. The preprocess was ma...

Lithofacies classification is a process to identify rock lithology by indirect measurements. Usually, the processed manually an experienced geoscientist. This research presents automated lithofacies using machine learning method increase computational power in shortening process's time consumption. The support vector (SVM) algorithm has been applied successfully Damar field, Indonesia. input va...

Assessment of the reservoir structure and determination of theinsitu stress direction arenecessary in oil production optimization andfield development. Today, the application of reservoir software and Image logsplay a central role in resolving this problem. Electricand ultrasonic imaging tools record vast amounts of high-resolution data within the borehole wall. This enables the geoscientists t...

Electrospun non-woven poly(ε-caprolactone) (PCL) microfiber meshes are described as biodegradable, mechanically robust, and reusable polymeric oil sorbents capable of selectively retrieving oil from simulated oil spills in both fresh and seawater scenarios. Hydrophobic PCL meshes have >99.5% (oil over water) oil selectivity and oil absorption capacities of ~10 grams of oil per gram of sorbent m...