We consider optimization of computational grids for petroleum reservoir flow simulations. In this context grid quality is determined by two independent error sources. On the one hand there is a loss of precision caused by upscaling of geological data from the fine geological grid to the coarser computational grid, and on the other hand there are numerical errors induced by a non-regular computa...

in this work, studies of underground gas storage (ugs) were performed on a partially depleted, naturally fractured gas reservoir through compositional simulation. reservoir dynamic model was calibrated by history matching of about 20 years of researvoir production. effects of fracture parameters, i.e. fracture shape factor, fracture permeability and porosity were studied. results showed that di...

Genetic Algorithms (GAs) application in the field of water resources engineering is of recent origin. Genetic Algorithms is one of the tools, which handles nonlinear optimization problems in an efficient manner. Optimal reservoir operation of reservoir for hydropower production involves constrained nonlinear optimization. The constrained problem is converted into unconstrained problem by using ...

Reservoir simulation is ubiquitous in the petroleum industry, and conditioning models to production data (history matching) has become an essential job of reservoir engineers. Traditional history matching methods directly perturb reservoir properties without regard to the existing geological continuity. When the geological heterogeneity is destroyed, the result is often a history-matched model ...

We consider a system-reservoir model where the reservoir is modulated by an external noise. Both the internal noise of the reservoir and the external noise are stationary, Gaussian, and are characterized by arbitrary decaying correlation functions. Based on a relation between the dissipation of the system and the response function of the reservoir driven by external noise, we numerically examin...

Reservoir computing (RC) is a new framework for neural computation. A reservoir is usually a recurrent neural network with fixed random connections. In this article, we propose an RC model in which the connections in the reservoir are modifiable. Specifically, we consider correlation-based learning (CBL), which modifies the connection weight between a given pair of neurons according to the corr...

Abstract The spontaneous emission spectrum from a driven three-level atom placed inside a double-band photonic crystal has been investigated. We use the model which assumes the upper levels of the atomic transition are coupled via a classical driving field. The transition from one of the upper levels to lower level couples to the modes of the modified reservoir, and the transition from the oth...

The mathematical model of Area-Reduction empirical method is written through MATLAB software. Three periods of the hydrologic survey are required to run, calibrate and validatethe model. The Dez Dam, which is one of the most significant dams of the Middle East with three periods of hydrographic surveys in 1972, 2002 and 2011, has been chosen for the investigation. The annual average of the inpu...

Modelling complex systems such as multiple-use reservoirs can be challenging. A legitimate question for scientists and modellers is how best to model their management under uncertain rainfall. This paper studies whether it is worth using a stochastic model that requires more effort than a much simpler deterministic model. Both models are applied to the management of a multiple-use reservoir in ...

the sefidrud dam was constructed and made operational in iran in 1962. the reservoir lost a considerable amount of its storage capacity in the first two decades of its operation when about 800 mcm sediment deposited in it and by considering the total capacity, 1800 mcm, the live storage capacity was reduced by 45 percent in 1980. the gilan project authorities have attempted to recreate the rese...