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This study used the 2D and 3D normalized total gradient (NTG) method of gravity anomalies to detect the gravity anomalies caused by oil-gas reservoirs. The NTG of gravity anomalies can be associated with known oil-gas reservoirs, and most of them seem to be a good coincidence with the reservoirs. The closed minima of the NTG of gravity anomalies indicate the existence and locations of the density deficient anomalies closely related to the possible oil-gas reservoirs. The reliability of the NTG method depends mainly on the Fourier-developed coefficient N. Here, N is optimally selected by the borehole data. The 2D, 3D normalized total gradient method is applied in the sedimentary basins of the Northeast Vietnam continental shelf. Borehole data confirm the results of the method.

The study area is bordered on the East China Sea, the Philippine Sea, and the Australian-Indo plate in the Northeast, in the East and in the South, respectively. It is a large area with the diversely complicated conditions of geological structure. In spite of over the past many years of investigation, marine geological structure in many places have remained poorly understood because of a thick seawater layer as well as of the sensitive conflicts among the countries in the region. In recent years, the satellite altimeter technology allows of enhancement the marine investigation in any area. The ocean surface height is measured by a very accurate radar altimeter mounted on a satellite. Then, that surface can be converted into marine gravity anomaly or bathymetry by using the mathematical model. It is the only way to achieve the data with a uniform resolution in acceptable time and cost. The satellite altimetry data and its variants are essential for understanding marine geological structure. They provide a reliable opportunity to geologists and geophysicists for studying the geological features beneath the ocean floor. Also satellite altimeter data is perfect for planning the more detailed shipboard surveys. Especially, it is more meaningful in the remote or sparsely surveyed regions. In this paper, the authors have effectively used the satellite altimetry and shipboard data in combination. Many geological features, such as seafloor spreading ridges, fault systems, volcanic chains as well as distribution of sedimentary basins are revealed through the 2D, 3D model methods of interpretation of satellite-shipboard-derived data and the others. These results are improved by existing boreholes and seismic data in the study area.

Comparing NLP systems to select the best one for a task of interest, such as named entity recognition, is critical for practitioners and researchers. A rigorous approach involves setting up a hypothesis testing scenario using the performance of the systems on query documents. However, often the hypothesis testing approach needs to send a lot of document queries to the systems, which can be problematic. In this paper, we present an effective alternative based on the multi-armed bandit (MAB). We propose a hierarchical generative model to represent the uncertainty in the performance measures of the competing systems, to be used by Thompson Sampling to solve the resulting MAB. Experimental results on both synthetic and real data show that our approach requires significantly fewer queries compared to the standard benchmarking technique to identify the best system according to F-measure.