Dual Skipping Networks

Inspired by the recent neuroscience studies on the left-right asymmetry of the human brain in processing low and high spatial frequency information, this paper introduces a dual skipping network which carries out coarse-to-fine object categorization. Such a network has two branches to simultaneously deal with both coarse and fine-grained classification tasks. Specifically, we propose a layer-skipping mechanism that learns a gating network to predict which layers to skip in the testing stage. This layer-skipping mechanism endows the network with good flexibility and capability in practice. Evaluations are conducted on several widely used coarse-to-fine object categorization benchmarks, and promising results are achieved by our proposed network model.Comment: CVPR 2018 (poster); fix typ

Hydrocarbon Detection Based on Phase Decomposition in Chaoshan Depression, Northern South China Sea

Located in the northern South China Sea, Chaoshan Depression is mainly a residual Mesozoic depression, with a construction of Meso-Cenozoic strata over 7000m thick and good hydrocarbon accumulation conditions. Amplitude attribute of -90°phase component derived by phase decomposition is employed to detect Hydrocarbon in the zone of interest (ZOI) in Chaoshan Depression. And it is found that there are evident amplitude anomalies occurring around ZOI. Phase decomposition is applied to forward modeling results of the ZOI, and high amplitudes occur on the -90°phase component more or less when ZOI is charged with hydrocarbon, which shows that the amplitude abnormality in ZOI is probably caused by oil and gas accumulation

Oil and gas prediction basing on seismic inversion of elastic properties in Chaoshan depression, south China sea

The marine Mesozoic is widely distributed in the northeastern waters of the South China Sea and is an important field for oil-gas exploration in the South China Sea. The Chaoshan Depression is the largest residual depression in this sea. At a previous well, LF35-1-1, no oil and gas have been discovered with then pre-drilling prediction techniques. Post-drill analysis shows that the physical properties of the Mesozoic reservoir are not favorable there. So, in accurate prediction of the oil-gas reservoirs is necessary. Since the drilling at the LF35-1-1, extensive surveys and studies have been carried out which shows a number of favorable trapping structures. In the middle low bulge of the Chaoshan Depression, the DS-A structures found with potential reservoirs, complete trap structures, and dual source hydrocarbon supply on both sides, making it the most favorable zone for oil-gas accumulation. We apply the state of art prediction techniques for it using pre-stack seismic raw gather. The sensitivity analysis results of reservoir physical properties indicate that the difference in P- wave velocity between sand and mudstone is 500 m/s, the difference in density is 0.02 g/cm3, and the Poisson’s ratio ranges between 0.11 and 0.33. The Mesozoic sandstone reservoirs in the Chaoshan Depression have characteristics of high velocity and low Poisson’s ratio, and the P-wave velocity, density, and Poisson’s ratio are the main sensitive parameters for predicting reservoir and its oil-gas bearing properties. The density inversion, P-wave impedance inversion, and S-wave impedance inversion jointly characterize the “wedge-shaped” sand body in the DS-A structural area, with a maximum thickness of over 400 m and an area of ∼130 km2. The overlap of the sand body contour map and Poisson’s ratio inversion results indicates that the “wedge-shaped” sand body is an oil-gas bearing sand body. It can be concluded that pre-stack elastic parameter inversion is an effective method for reservoir prediction in deep-sea no-well exploration areas. It has the characteristics of high signal-to-noise ratio, strong stability and reliability, and high accuracy, which is conducive to reduce the non-uniqueness and uncertainty of seismic inversion. The inversion results predict that the DS-A structure is an oil-gas bearing structure

Hydrocarbon Accumulation Analysis Based on Quasi-3D Seismic Data in the Turbulent Area of the Northern South China Sea

The Mesozoic strata in the northern South China Sea have good potential for oil and gas exploration. The Dongsha Waters, where the study area is located, have complex seismic and geological characteristics; in particular, turbulence is very prominent in this area, so it is difficult to implement 3D seismic data collection. The “single-source and single-cable quasi-3D seismic survey” method integrates some key technologies in acquisition and processing, thus improving the quality of seismic imaging. Based on the interpretation of the existing research results and new data, structure B-1 has good source–reservoir–cap combination conditions. The oil–gas accumulation mode is predicted, and the drilling well B-1-1 is given. In addition, the large-scale distribution of bottom-simulating reflectors (BSRs) and the discovery of gas seepage areas in the study area suggest the presence of gas hydrate. We suggest that deep thermogenic gas from the Mesozoic strata has migrated into the overlying strata along the fault system and mixed with microbial gas to form hydrate