Analysis on deep crustal structure along the onshore-offshore seismic profile across the Binhai (littoral) fault zone in northeastern South China Sea

The onshore-offshore deep seismic experiment was carried out for the first time and filled the blankness of the seismic surveys in the transition area between South China and northeastern South China Sea. The seismic data were analyzed and processed. The different seismic phases were identified and their travel time arrivals were modeled by ray-tracing to study the P-wave velocity crustal structure of this area. The crustal structure of this area is the continental crust. The crust thickness is gradually decreasing southward along the on-shore-offshore seismic line. The low-velocity layer (5.5 similar to 5.9 km (.) s(-1)) exists generally in the middle crust (about 10.0 similar to 18.0km)with about 2.5 similar to 4.0 km thickness, which is also thinning seaward. No obvious high-velocity layer appears in the lower crust. The Binhai (littoral) fault zone is a low velocity zone, which is located about 35km southeast to the Nan'ao station and corresponding to the gradient belt of gravity & magnetism anomalies. The depth of the fault zone is close to the Moho discontinuity. The littoral fault zone is a boundary between the normal continental crust of South China and the thinned continental crust of the sea area.

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.

Seismic characteristics of a reef carbonate reservoir and implications for hydrocarbon exploration in deepwater of the Qiongdongnan Basin, northern South China Sea

Our analysis of approximately 40,000 km of multichannel 2-D seismic data, reef oil-field seismic data, and data from several boreholes led to the identification of two areas of reef carbonate reservoirs in deepwater areas (water depth >= 500 in) of the Qiongdongnan Basin (QDNB), northern South China Sea. High-resolution sequence stratigraphic analysis revealed that the transgressive and highstand system tracts of the mid-Miocene Meishan Formation in the Beijiao and Ledong-Lingshui Depressions developed reef carbonates. The seismic features of the reef carbonates in these two areas include chaotic bedding, intermittent internal reflections, chaotic or blank reflections, mounded reflections, and apparent amplitude anomalies, similar to the seismic characteristics of the LH11-1 reef reservoir in the Dongsha Uplift and Island Reef of the Salawati Basin, Indonesia, which house large oil fields. The impedance values of reefs in the Beijiao and Ledong-Lingshui Depressions are 8000-9000 g/cc x m/s. Impedance sections reveal that the impedance of the LH11-1 reef reservoir in the northern South China Sea is 800010000 g/cc x m/s, whereas that of pure limestone in BD23-1-1 is > 10000 g/cc x m/s. The mid-Miocene paleogeography of the Beijiao Depression was dominated by offshore and neritic environments, with only part of the southern Beijiao uplift emergent at that time. The input of terrigenous sediments was relatively minor in this area, meaning that terrigenous source areas were insignificant in terms of the Beijiao Depression: reef carbonates were probably widely distributed throughout the depression, as with the Ledong-Lingshui Depression. The combined geological and geophysical data indicate that shelf margin atolls were well developed in the Beijiao Depression, as in the Ledong-Lingshui Depression where small-scale patch or pinnacle reefs developed. These reef carbonates are promising reservoirs, representing important targets for deepwater hydrocarbon exploration. (C) 2008 Elsevier Ltd. All rights reserved.

Seismic stratigraphy of the Qiongdongnan deep sea channel system, northwest South China Sea

Based on more than 4000 km 2D seismic data and seismic stratigraphic analysis, we discussed the extent and formation mechanism of the Qiongdongnan deep sea channel. The Qiongdongnan deep sea channel is a large incised channel which extends from the east boundary of the Yinggehai Basin, through the whole Qiongdongnan and the Xisha trough, and terminates in the western part of the northwest subbasin of South China Sea. It is more than 570 km long and 4-8 km wide. The chaotic (or continuous) middle (or high) amplitude, middle (or high) continuity seismic facies of the channel reflect the different lithological distribution of the channel. The channel formed as a complex result of global sea level drop during early Pliocene, large scale of sediment supply to the Yinggehai Basin, inversion event of the Red River strike-slip fault, and tilted direction of the Qiongdongnan Basin. The large scale of sediment supply from Red River caused the shelf break of the Yinggehai Basin to move torwards the S and SE direction and developed large scale of prograding wedge from the Miocene, and the inversion of the Red River strike-slip fault induced the sediment slump which formed the Qiongdongnan deep sea channel.

Experimental Study of the Earthquake Recurrence Period and the Trend of Post-Seismic Development

In order to study the earthquake recurrence and the characteristics of earthquake series, rupture tests of rock samples and plexiglass samples were made. On rock samples, a number of acoustic emission (AE) and strain measuring points were deployed; the load was one side direct shear. The variation characteristics of AE and strain at different detecting points around the extra large fracture were observed and studied. On plexiglass samples, a series of inclined cracks were prefabricated by a small-scale compressive testing machine. The samples were then loaded on a shockproof platen, when the samples were loaded, the stress intensity factor (SIF) was determined by the laser interferometric technique and shadow optical method of caustics. The fracture conditions such as material toughness around the extra large fracture were also studied. From those experimental results and the theory of fracture mechanics, the earthquake recurrence period and the trend of post-seismic development were studied.

Weak Zone Related Seismic Cycles in Progressive Failure Leading to Collapse in Brittle Crust

Until quite recently our understanding of the basic mechanical process responsible for earthquakes and faulting was not well known. It can be argued that this was partly a consequence of the complex nature of fracture in crust and in part because evidence of brittle phenomena in the natural laboratory of the earth is often obliterated or obscured by other geological processes. While it is well understood that the spatial and temporal complexity of earthquakes and the fault structures emerge from geometrical and material built-in heterogeneities, one important open question is how the shearing becomes localized into a band of intense fractures. Here the authors address these questions through a numerical approach of a tectonic plate by considering rockmass heterogeneity both in microscopic scale and in mesoscopic scale. Numerical simulations of the progressive failure leading to collapse under long-range slow driving forces in the far-field show earthquake-like rupture behavior. $En Echelon$ crack-arrays are reproduced in the numerical simulation. It is demonstrated that the underlying fracturing induced acoustic emissions (or seismic events) display self-organized criticality------from disorder to order. The seismic cycles and the geometric structures of the fracture faces, which are found greatly depending on the material heterogeneity (especially on the macroscopic scale), agree with that observed experimentally in real brittle materials. It is concluded that in order to predict a main shock, one must have extremely detailed knowledge on very minor features of the earth's crust far from the place where the earthquake originated. If correct, the model proposed here seemingly provides an explanation as to why earthquakes to date are not predicted so successfully. The reason is not that the authors do not understand earthquake mechanisms very well but that they still know little about our earth's crust.

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.