Significance of Aeolian Deposits Resultant Drift Direction, Implications for Reservoir Prediction, Utilizing Subsurface and Analogue Data

AbstractIt is common to formulate the history-matching problem using Bayes’ theorem. From Bayes’, the conditional probability density function (pdf) of the uncertain model parameters is proportional to the prior pdf of the model parameters, multiplied by the likelihood of the measurements. The static model parameters are random variables characterizing the reservoir model while the observations include, e.g., historical rates of oil, gas, and water produced from the wells. The reservoir prediction model is assumed perfect, and there are no errors besides those in the static parameters. However, this formulation is flawed. The historical rate data only approximately represent the real production of the reservoir and contain errors. History-matching methods usually take these errors into account in the conditioning but neglect them when forcing the simulation model by the observed rates during the historical integration. Thus, the model prediction depends on some of the same data used in the conditioning. The paper presents a formulation of Bayes’ theorem that considers the data dependency of the simulation model. In the new formulation, one must update both the poorly known model parameters and the rate-data errors. The result is an improved posterior ensemble of prediction models that better cover the observations with more substantial and realistic uncertainty. The implementation accounts correctly for correlated measurement errors and demonstrates the critical role of these correlations in reducing the update’s magnitude. The paper also shows the consistency of the subspace inversion scheme by Evensen (Ocean Dyn. 54, 539–560 2004) in the case with correlated measurement errors and demonstrates its accuracy when using a “larger” ensemble of perturbations to represent the measurement error covariance matrix.

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3D Seismic attribute optimization technology and application for dissolution caved carbonate reservoir prediction

10.1190/1.3627592 ◽

2011 ◽

Author(s):

Lifeng Liu ◽

Sam Zandong Sun ◽

Haiyang Wang ◽

Haijun Yang ◽

Jianfa Han ◽

...

Keyword(s):

Carbonate Reservoir ◽

3D Seismic ◽

Reservoir Prediction ◽

Seismic Attribute

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Study and Application of FSC Reservoir Prediction methods based on Sedimentary Microfacies

10.1190/igcbeijing2016-025 ◽

2016 ◽

Author(s):

Liheng Xu* ◽

Huidong Yang ◽

Yu Liang ◽

Xiuli Zhang ◽

Qiuli He

Keyword(s):

Prediction Methods ◽

Reservoir Prediction ◽

Sedimentary Microfacies

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Adaptation in single units in visual cortex: The tuning of aftereffects in the spatial domain

Visual Neuroscience ◽

10.1017/s0952523800003527 ◽

1989 ◽

Vol 2 (6) ◽

pp. 593-607 ◽

Cited By ~ 65

Author(s):

A. B. Saul ◽

M. S. Cynader

Keyword(s):

Spatial Frequency ◽

Cortical Neurons ◽

Frequency Tuning ◽

Cortical Cell ◽

Selective Adaptation ◽

Single Units ◽

Spatial Frequency Tuning ◽

Sinusoidal Gratings ◽

A Cell ◽

Drift Direction

AbstractCat striate cortical neurons were investigated using a new method of studying adaptation aftereffects. Stimuli were sinusoidal gratings of variable contrast, spatial frequency, and drift direction and rate. A series of alternating adapting and test trials was presented while recording from single units. Control trials were completely integrated with the adapted trials in these experiments.Every cortical cell tested showed selective adaptation aftereffects. Adapting at suprathreshold contrasts invariably reduced contrast sensitivity. Significant aftereffects could be observed even when adapting at low contrasts.The spatial-frequency tuning of aftereffects varied from cell to cell. Adapting at a given spatial frequency generally resulted in a broad response reduction at test frequencies above and below the adapting frequency. Many cells lost responses predominantly at frequencies lower than the adapting frequency.The tuning of aftereffects varied with the adapting frequency. In particular, the strongest aftereffects occurred near the adapting frequency. Adapting at frequencies just above the optimum for a cell often altered the spatial-frequency tuning by shifting the peak toward lower frequencies. The fact that the tuning of aftereffects did not simply match the tuning of the cell, but depended on the adapting stimulus, implies that extrinsic mechanisms are involved in adaptation effects.

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Advanced Weathervaning in Ice

Volume 1: Offshore Technology; Polar and Arctic Sciences and Technology ◽

10.1115/omae2011-49154 ◽

2011 ◽

Author(s):

William Hidding ◽

Guillaume Bonnaffoux ◽

Mamoun Naciri

Keyword(s):

Rapid Change ◽

Ice Sheet ◽

Model Tests ◽

The Arctic ◽

Mooring System ◽

Sudden Increase ◽

Time Step ◽

Ice Loads ◽

Level Ice ◽

Drift Direction

The reported presence of one third of remaining fossil reserves in the Arctic has sparked a lot of interest from energy companies. This has raised the necessity of developing specific engineering tools to design safely and accurately arctic-compliant offshore structures. The mooring system design of a turret-moored vessel in ice-infested waters is a clear example of such a key engineering tool. In the arctic region, a turret-moored vessel shall be designed to face many ice features: level ice, ice ridges or even icebergs. Regarding specifically level ice, a turret-moored vessel will tend to align her heading (to weather vane) with the ice sheet drift direction in order to decrease the mooring loads applied by this ice sheet. For a vessel already embedded in an ice sheet, a rapid change in the ice drift direction will suddenly increase the ice loads before the weathervaning occurs. This sudden increase in mooring loads may be a governing event for the turret-mooring system and should therefore be understood and simulated properly to ensure a safe design. The paper presents ADWICE (Advanced Weathervaning in ICE), an engineering tool dedicated to the calculation of the weathervaning of ship-shaped vessels in level ice. In ADWICE, the ice load formulation relies on the Croasdale model. Ice loads are calculated and applied to the vessel quasi-statically at each time step. The software also updates the hull waterline contour at each time step in order to calculate precisely the locations of contact between the hull and the ice sheet. Model tests of a turret-moored vessel have been performed in an ice basin. Validation of the simulated response is performed by comparison with model tests results in terms of weathervaning time, maximum mooring loads, and vessel motions.

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