The deliverability of liquid-dominated geothermal reservoirs is presented in terms of reservoir performance, and wellbore performance. Water influx modeling is used to match the performance of Wairakei in New Zealand, arid Ahuachapan in El Salvador. The inflow performance is given in terms of a linear productivity index for liquid-only flow, and a solution-gas drive relationship for two-phase f...

Synopsis Water quantity and quality are considered to be the main driving forces the reservoir operation. Barra Bonita reservoir, located in the southeast region of Brazil, is chosen as the case study for the application of the proposed methodology. Herein, optimization and artificial intelligence (AI) techniques are applied in the simulation and operation of the reservoir. A fuzzy stochastic d...

Three different uses of a recurrent neural network (RNN) as a reservoir that is not trained but instead read out by a simple external classification layer have been described in the literature: Liquid State Machines (LSMs), Echo State Networks (ESNs) and the Backpropagation Decorrelation (BPDC) learning rule. Individual descriptions of these techniques exist, but a overview is still lacking. He...

A reservoir operation model of Mun Bon and Lam Chae reservoirs was developed to simulate reservoir operation using a hedging policy. A variety of common hedging forms was specified, including one-point hedging, two-point hedging and zone-based hedging. The simulated results were compared with the standard operating policy and probability based rule curve. The percentage of failure frequency, av...

There is an increasing awareness among irrigation planners and engineers to design and operate reservoir systems for maximum efficiency to maximise their benefits. Accordingly, significant work has been done on reservoir operation for known total irrigation demand and on the optimal allocation of water available to crops at the farm level. This present paper deals with the development and compa...

Reservoir computing provides a promising approach to efficient training of recurrent neural networks, by exploiting the computational properties of the reservoir structure. Various approaches, ranging from suitable initialization to reservoir optimization by training have been proposed. In this paper we take a closer look at short-term memory capacity, introduced by Jaeger in case of echo state...

Current efforts toward achieving a cure for HIV are focused on developing strategies to eliminate latently infected CD4+ T cells, which represent the major barrier to virus eradication. Sensitive, precise, and practical assays that can reliably characterize and measure this HIV reservoir and can reliably measure the impact of a candidate treatment strategy are essential. PCR-based procedures fo...

Evaluation of hydrocarbon reservoir requires classification of petrophysical properties from available dataset. However, characterization of reservoir attributes is difficult due to the nonlinear and heterogeneous nature of the subsurface physical properties. In this context, present study proposes a generalized one class classification framework based on Support Vector Data Description (SVDD) ...

Most reservoirs offer a mean of managing and regulating the downstream water flow and demands over time and space. It is a challenging task for the reservoir operator to evaluate the trade-off during drought and heavy rainfall season. This study proposes a review on the application of different computational intelligent models, especially the Artificial Bee Colony (ABC) approach in reservoir in...