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Current work uses finite element simulation to investigate swelling elastomer seal behavior in downhole petroleum applications.
Continuous microseismic monitoring of hydraulic fracturing is commonly used in many engineering, environmental, mining, and petroleum applications.
According to comparison between the obtained results, it shows that the improved method presented has better performance rather than empirical and current methods in neural network designing in petroleum applications for these predictions.
For hydrocarbon and petroleum applications, non-cubic equations of state have a limited range of application and a cubic equation of state departure function calculations possesses a systematic skew with respect to absolute and relative temperature.
In recent years, neural networks have gained popularity in petroleum applications.
They found that the SiO2 nanoparticles and wormlike micelles exhibit a synergistic effect in terms of foam rheology and stability, which significantly improves the proppant suspension capabilities for petroleum applications [25].
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Petroleum exploration applications of palynological assemblage successions in the flexure trend, Gulf of Mexico.
Reliable phase behaviour prediction is of great importance in chemical and petroleum engineering applications.
Nanofluids viscosity is one of the most important thermophysical properties in nanofluids usage especially in chemical and petroleum engineering applications.
Since we have specifically designed this algorithm for petroleum engineering applications, it performs clustering on highly-disjointed data sets.
One of these properties is viscosity that is very important especially for chemical and petroleum engineering applications.
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