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401.
Since its introduction in the late 1950s, hydraulic vibrators have become the dominant source for land seismic surveys. The hydraulic vibrators typically used for commercial land seismic acquisition, however, are large, costly to operate and expensive to purchase. This inhibits their use for small-scale and short-duration surveys as well as Vibroseis research. In this paper we describe, in detail, the construction of a portable vibrator from commercially available components for a cost of less than $US2,000. Data shows that the vibrator is able to successfully transmit sweeps from 15 to 180 Hz with different spectral contents. The vibrator produces a stronger signal than a sledgehammer and we estimate its output to be around 1 kN. The frequency content of the data was concentrated at lower frequencies (<100 Hz) and the ground-roll was far more energetic than that produced using a sledgehammer. 相似文献
402.
The zeta potential is one of the most important parameters influencing the electrokinetic coupling. Most reservoir rocks are saturated or partially saturated by natural water containing various types of ions (mostly monovalent and divalent ions). Therefore, understanding how the zeta potential behaves for mixtures of electrolytes is very important. In this work, measurements of the zeta potential for four different silica-based samples saturated by seven different mixtures of monovalent and divalent electrolytes are then carried out at a fixed ionic strength. It is seen that the magnitude of the measured zeta potential decreases with increasing divalent cation fraction. The experimental results are then explained by a model developed for mixtures of monovalent and divalent electrolytes. The result shows that the theoretical model is able to reproduce the main trend of the variation of the zeta potential with divalent cation fractions. Additionally, the model can fit the experimental data reported in literature well for reasonable values of the input parameters. 相似文献
403.
Tuan Nguyen-Sy Quy-Dong To Minh-Ngoc Vu The-Duong Nguyen Thoi-Trung Nguyen 《Geophysical Prospecting》2020,68(8):2557-2578
This paper aims to demonstrate that the elastic stiffnesses and the anisotropic parameters of rocks can be accurately predicted from geophysical features such as the porosity, the density, the compression stress, the pore pressure and the burial depth using relevant machine learning methods. It also suggests that the extreme gradient boosting method is the best method for this purpose. It is more accurate, extremely faster to train and more robust than the artificial neural networks and the support vector machine methods. Very high R-squared scores was obtained for the predicted elastic stiffnesses of a relevant dataset that is available in the literature. This dataset contains different types of rocks, and the values of the features are in large ranges. An optimal set of parameters was obtained by considering an appropriate sensitivity analysis. The optimized model is very easy to implement in Python for practical applications. 相似文献
404.
Acta Geotechnica - Wet agglomerates such as iron-ores, tablets, and aggregates are omnipresent in multi–field industries. However, our understanding of the impact dynamics of these materials... 相似文献