Possible risks in reservoir flood control and regulation cannot be objectively assessed by deterministic flood forecasts, resulting in the probability of reservoir failure. We demonstrated a risk analysis of reservoir flood routing calculation accounting for inflow forecast uncertainty in a sub-basin of Huaihe River, China. The Xinanjiang model was used to provide deterministic flood forecasts,...

Smart field technology is an attractive research field, as it can find an optimal well control strategy to maximize the oil recovery or the net present value (NPV). As the subsurface geology is highly uncertain, the reservoir model is usually described by a set of reservoir models. In well control optimization for a reservoir described by a set of geological models, the expectation of NPV is op...

Permeability is the key parameter of the reservoir and has a significant impact on petroleum fields operations and reservoir management. In most reservoirs, permeability measurements are rare and therefore permeability must be measured in the laboratory from reservoir core samples or evaluated from well test data. However, core analysis and well test data are usually only available from a few w...

Accurate real-time reservoir inflow forecasting is an important requirement for operation, scheduling and planning conjunctive use in any basin. In this study, Time Delay Artificial Neural Network (TDANN) models, which are time lagged feed-formatted networks with delayed memory processing elements at the input layer, are applied to forecast the daily inflow into a planned Reservoir (Almopeos Ri...

Reservoir computing is a bio-inspired computing paradigm for processing time-dependent signals. Its hardware implementations have received much attention because of their simplicity and remarkable performance on a series of benchmark tasks. In previous experiments the output was uncoupled from the system and in most cases simply computed offline on a post-processing computer. However, numerical...

The purpose of this paper is to report the first preliminary study of the recently introduced Combinatorial Multilevel (CML) method for solver preconditioning in large-scale reservoir simulation with coupled geomechanics. The CML method is a variant of the popular Algebraic Multigrid (AMG) method yet with essential differences. The basic idea of this new approach is to construct a hierarchy of ...

Optical neural networks offer radically new avenues for ultrafast, energy-efficient hardware machine learning and artificial intelligence. Reservoir Computing (RC), given its high performance cheap training has attracted considerable attention photonic network implementations, principally based on semiconductor lasers (SLs). Among SLs, Vertical Cavity Surface Emitting Lasers (VCSELs) possess un...