Controlling the uncertainty in reservoir stochastic simulation

STOCHASTIC SIMULATION And RESERVOIR MODELING WORKFLOW

Statistical Uncertainty Analysis for Stochastic Simulation

When we use simulation to evaluate the performance of a stochastic system, the simulation often contains input distributions estimated from real-world data; therefore, there is both simulation and input uncertainty in the performance estimates. Ignoring either source of uncertainty underestimates the overall statistical error. Simulation uncertainty can be reduced by additional computation (e.g...

Reservoir Sedimentation under Uncertainty: Analytic Approach versus Simulation

Two methods are presented of estimating accumulated sediment yield stemming from erosion in a semiarid climate during a given time span, and the methods are compared from the viewpoint of the economic consequences evaluated within a Bayesian framework. The design of reservoirs requires the estimation of the random sediment volume Z accumulated over the lifetime of the project. An analytic and a...

Stochastic Reservoir Simulation Using Neural Networks Trained on Outcrop Data

Extensive outcrop data or photographs of present day depositions or even simple drawings from expert geologists contain precious structural information about spatial continuity that is beyond the present tools of geostatistics essentially limited to two-point statistics (histograms and covariances). A neural net can be learned to collect multiple point statistics from various training images, t...

Assessment of Ilam Reservoir Eutrophication Response in Controlling Water Inflow

In this research, a 2D laterally averaged model of hydrodynamics and water quality, CE-QUAL-W2, was applied to simulate water quality parameters in the Ilam reservoir. The water quality of Ilam reservoir was obtained between mesotrophic and eutrophic based on the measured data including chlorophyll a, total phosphorus and subsurface oxygen saturation. The CE-QUAL-W2 model was calibrated and ver...