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In this paper, we address this heterogeneity problem by stratifying the reservoir sample among the underlying sub-streams.
In this work, we show how by switching the placement of the sample and water reservoir (sample in a sealed hydrostat and water reservoir in the ampoule) many of these drawbacks are overcome.
First, a fixed-size reservoir should be allocated to individual sub-streams optimally, specifically to have the stratified reservoir sample used to generate estimates at the level of either the whole data stream or the individual sub-streams.
In upscaling the reservoir sample, the two constraints were imposed.
Similar to the above two samples of the Middle Shajara Reservoir, sample SJ9 is described as medium-grained, moderately well sorted sandstone.
For each series of analysis, the ionic strength was held approximately constant whereas pH was varied by titrating the reservoir sample with the addition of 0.1 N HCl or 0.1 N NaOH.
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The relationship work best for well sorted reservoir samples.
We propose a novel adaptive stratified reservoir sampling algorithm designed to meet these challenges.
In this study; different laboratory experiments on one of the Iranian heavy oil and brine reservoir samples were performed.
Single-phase high-pH corefloods were completed using Berea sandstone and reservoir samples to calibrate and validate geochemical simulations.
Heterogeneity and anisotropy of ultra-tight reservoir samples adversely influence the laboratory correlation among various measured and estimated petrophysical properties.
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