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The main objective of the interpretation in this case is to retrieve the characteristic inverse parameters of the 3D approximative model: depth to the top, thickness, extension in depth, extension in the strike direction, and direction and amount of dip.
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Using these models and a digital elevation model, the depth to sulfides could be adequately predicted.
We created a 1-km2 cell surface model of depth to bedrock derived from well depth information in the oil and gas wells database using inverse distance weighted interpolation (power = 1; number of points within radius = 12; maximum distance = 5000 meters).
Model depth is uniformly set to 12 km, and the top surface is based on topography.
When we extend the animal model for bill depth to account for repeated measurements and use individual as a random effect, we find that σ e 2 decreases.
Model depth and sentence length are positively related to the accuracy.
The two-dimensional finite difference model Depth Integrated Velocitiy and Solute Transport (DIVAST) was applied to several meanders, taking account of the cross-sectional velocity and depth distributions.
Prices start at €780,000 and can go up to €2.4 million depending on the model, depth rating and other options.
In their proposed model, depth information derived from monocular cues is propagated along surface contours using local recurrent interactions to obtain a globally consistent depth sorting of overlapping surfaces.
Error in 2D model depth prediction averaged 21%.
The effect of model depth (Fig. 9c) is substantial for depths less than about 50 m.
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