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...

enhanced oil recovery using nitrogen injection is a commonly applied method for pressuremaintenance in conventional reservoirs. numerical simulations can be practiced for the prediction ofa reservoir performance in the course of injection process; however, a detailed simulation might takeup enormous computer processing time. in such cases, a simple statistical model may be a goodapproach to the...

The spatial distribution of petrophysical properties within the reservoirs is one of the most important factors in reservoir characterization. Flow units are the continuous body over a specific reservoir volume within which the geological and petrophysical properties are the same. Accordingly, an accurate prediction of flow units is a major task to achieve a reliable petrophysical description o...

Gas injection into heavy oil reservoirs could result in high ultimate recovery of oil. Experimental studies showed that an application of a combined technology of Gas Assisted Gravity Drainage (GAGD) and Vapor Extraction (VAPEX) could increase final oil recovery of a candidate viscous oil reservoir. In this paper the results of laboratory investigation are presented, including Pressure-Volu...

This paper extends the notion of information processing capacity for non-independent input signals in the context of reservoir computing (RC). The presence of input autocorrelation makes worthwhile the treatment of forecasting and filtering problems for which we explicitly compute this generalized capacity as a function of the reservoir parameter values using a streamlined model. The reservoir ...

This letter addresses the reservoir design problem in the context of delay-based reservoir computers for multidimensional input signals, parallel architectures, and real-time multitasking. First, an approximating reservoir model is presented in those frameworks that provides an explicit functional link between the reservoir architecture and its performance in the execution of a specific task. S...

Reservoir Computing (RC) offers a computationally efficient and well performing technique for using the temporal processing power of Recurrent Neural Networks (RNNs), while avoiding the traditional long training times and stability problems. The method is both simple and elegant: a random RNN (called the reservoir) is constructed using only a few global parameters to tune the dynamics into a de...

This paper presents a method by which uncertainty in reservoir modeling can be reduced by integrating observed data in the estimation of model parameters. The problem is inverse and ill-posed. Further, since the observed data and the reservoir properties are non-linearly related, reducing uncertainty becomes a non-trivial task. The methodology involves generating multiple reservoir descriptions...

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...