Ground target detection, classification and sensor fusion in distributed fiber seismic sensor network - art. no. 683015

This paper describes the ground target detection, classification and sensor fusion problems in distributed fiber seismic sensor network. Compared with conventional piezoelectric seismic sensor used in UGS, fiber optic sensor has advantages of high sensitivity and resistance to electromagnetic disturbance. We have developed a fiber seismic sensor network for target detection and classification. However, ground target recognition based on seismic sensor is a very challenging problem because of the non-stationary characteristic of seismic signal and complicated real life application environment. To solve these difficulties, we study robust feature extraction and classification algorithms adapted to fiber sensor network. An united multi-feature (UMF) method is used. An adaptive threshold detection algorithm is proposed to minimize the false alarm rate. Three kinds of targets comprise personnel, wheeled vehicle and tracked vehicle are concerned in the system. The classification simulation result shows that the SVM classifier outperforms the GMM and BPNN. The sensor fusion method based on D-S evidence theory is discussed to fully utilize information of fiber sensor array and improve overall performance of the system. A field experiment is organized to test the performance of fiber sensor network and gather real signal of targets for classification testing.

Wavelet denoising and feature extraction of seismic signal for footstep detection

Seismic sensors are widely used to detect moving target in ground sensor networks. Footstep detection is very important for security surveillance and other applications. Because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. A novel wavelet denoising method based on singular value decomposition is used to solve these problems. The signal-to-noise ratio (SNR) of raw footstep signal is greatly improved using this strategy. The feature extraction method is also discussed after denosing procedure. Comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.

Characteristics and Formation Mechanism of Polygonal Faults in Qiongdongnan Basin, Northern South China Sea

Based on high-resolution 3D seismic data, we document the polygonal faults within the Miocene Meishan (sic) Formation and Huangliu (sic) Formation of the Qiongdongnan (sic) basin, northern South China Sea. Within the seismic section and time coherent slice, densely distributed extensional faults with small throw and polygonal shape were identified in map view. The orientation of the polygonal faults is almost isotropic, indicating a non-tectonic origin. The deformation is clearly layer-bounded, with horizontal extension of 11.2% to 16%, and 13.2% on average. The distribution of polygonal faults shows a negative correlation with that of gas chimneys. The development of polygonal faults may be triggered by over-pressure pore fluid which is restricted in the fine-grained sediments of bathyal facies when the sediments is compacted by the burden above. The polygonal faults developed to balance the volumetric contraction and restricted extension. The product of hydrocarbon in the Meishan Formation may have contributed to the development of the polygonal faults. In the study area, it was thought that the petroleum system of the Neogene post-rift sequence is disadvantageous because of poor migration pathway. However, the discovery of polygonal faults in the Miocene strata, which may play an important role on the fluid migration, may change this view. A new model of the petroleum system for the study area is proposed.

Petroleum System in Deepwater Basins of the Northern South China Sea

The northern South China Sea margin has experienced a rifting stage and a post-rifting stage during the Cenozoic. In the rifting stage, the margin received lacustrine and shallow marine facies sediments. In the post-rifting thermal subsidence, the margin accumulated shallow marine facies and hemipelagic deposits, and the deepwater basins formed. Petroleum systems of deepwater setting have been imaged from seismic data and drill wells. Two kinds of source rocks including Paleogene lacustrine black shale and Oligocene-Early Miocene mudstone were developed in the deepwater basin of the South China Sea. The deepwater reservoirs are characterized by the deep sea channel rill, mass flow complexes and drowned reef carbonate platform. Profitable capping rocks on the top are mudstones with huge thickness in the post-rifting stage. Meanwhile, the faults developed during the rifting stage provide a migration path favourable for the formation of reservoirs. The analysis of seismic and drilling data suggests that the joint structural and stratigraphic traps could form giant hydrocarbon fields and hydrocarbon reservoirs including syn-rifting graben subaqueous delta, deepwater submarine fan sandstone and reef carbonate reservoirs.