We propose a novel molecular computing approach based on reservoir computing. In reservoir computing, a dynamical core, called a reservoir, is perturbed with an external input signal while a readout layer maps the reservoir dynamics to a target output. Computation takes place as a transformation from the input space to a high-dimensional spatiotemporal feature space created by the transient dyn...

In deepwater-reservoir modeling, the proper representation of the spatial distribution of architectural elements is important to account for pore-volume distribution and the connectivity of reservoir sand bodies. This is especially critical for rock and fluid-volume estimates, reservoir-performance predictions, and development-well planning. A new integrated stochastic reservoir-modeling approa...

withdrawal of oil and gas from reservoirs causes a decrease in pore pressure and an increase in effective stress which results to a reservoir compaction. reservoir compaction will result in surface subsidence through the elastic response of the subsurface. usually in order to determine the subsidence above a hydrocarbon field, the reservoir compaction must be first calculated and then the effec...

The purpose of a reservoir offset is to enable the application of calibration data (μ(θ), e.g. Stuiver et al. 1998) developed for one reservoir (primary reservoir) to CRA’s from another (secondary reservoir). The usual approach has been to define the activity of the secondary reservoir as some form of constant offset (with error) from the primary reservoir (e.g. Stuiver and Braziunas 1993). In ...

In this paper, ant colony optimization (ACO) algorithms are proposed for reservoir operation. Through a collection of cooperative agents called ants, the near-optimum solution to the reservoir operation can be effectively achieved. To apply ACO algorithms, the problem is approached by considering a finite horizon with a time series of inflow, classifying the reservoir volume to several interval...

Echo state networks (ESNs) with multi-clustered reservoir topology perform better in reservoir computing and robustness than those with random reservoir topology. However, these ESNs have a complex reservoir topology, which leads to difficulties in reservoir generation. This study focuses on the reservoir generation problem when ESN is used in environments with sufficient priori data available....