We determine the degree of variation of model fitness,to a true model based on amplitude variation with angle (AVA)methodology for a synthetic gas hydrate model,using co-operative fuzzy c-means clustering,constrained to a rock physics model.When a homogeneous starting model is used,with only traditional least squares optimization scheme for inversion,the variance of the parameters is found to be comparatively high.In this co-operative methodology,the output from the least squares inversion is fed as an input to the fuzzy scheme.Tests with co-operative inversion using fuzzy c-means with damped least squares technique and constraints derived from empirical relationship based on rock properties model show improved stability,model fitness and variance for all the three parameters in comparison with the standard inversion alone.

Extreme wave events of 1000 and 1500 years (radiocarbon ages) have been recently reported in Mahabalipuram region, southeast coast of India. Subsequently, we carried out extensive sedimentological analysis in regions covering a total lateral coverage of 12 km with a new archeological site as the central portion of the study area. Twelve trenches in shore normal profiles exhibit landward thinning sequences as well as upward fining sequences confirming with the global signatures of extreme wave events. The sediment size ranges from fine-to-medium and moderately well sorted-to-well sorted, and exhibit positive skewness with platykurtic-to-leptokurtic nature. We now propose the abrupt winnowing or back and forth motion including unidirectional transport of these deposited sediments, which results in positive skewness. Textural analyses derived from scanning electron microscope studies (SEM) demonstrate the alteration produced, in the ilmenite mineral with vivid presence of pits and crescents with deformation observed on the surface due to extreme wave activities. This is further confirmed with the predominance of high-density mineral such as magnetite (5.2) and other heavy minerals in these deposits inferred the high-intensity of the reworking process of the beach shelf sediments.

Indian Ocean subduction zone is one of the most active plate margins of the globe as evident from its vast record of great magnitude earthquake and tsunami events.We use Bouguer admittance (Morlet isostatic response function)in Sumatra –Java subduction zones comprising both the subduction and over-riding plates to determine the lithospheric mechanical strength variations. We determine effective elastic thickness $(T_e)$ for five oceanic windows (size 990 × 990 km²) by analyzing the admittance using Bouguer gravity and bathymetry data. The results show bimodal $T_e$ values > 20 km for Sumatra and 20 –40 km for Java.The lower bimodal values obtained for Sumatra appears to correlate well with the zones of historical seismicity.This is in sharp contrast with Java subduction zone,which shows higher $T_e$ values (20 –40 km)and apparently associated with low magnitude earthquakes.We suggest a strong and wide interseismic coupling for Sumatra between the subducting and over-riding plates,and deeper mantle contributing to low strength,shallow focus –high magnitude seismicity and vice versa for Java,leading to their seismogenic zonation.

Global estimates of the elastic thickness (Te) of the structure of passive continental margins show wide and varying results owing to the use of different methodologies. Earlier estimates of the elastic thickness of the North Atlantic passive continental margins that used flexural modelling yielded a Te value of ∼20–100 km. Here, we compare these estimates with the Te value obtained using orthonormalized Hermite multitaper recovered isostatic coherence functions. We discuss how Te is correlated with heat flow distribution and depth of necking. The E–W segment in the southern study region comprising Nova Scotia and the Southern Grand Banks show low Te values, while the zones comprising the NE–SW zones, viz., Western Greenland, Labrador, Orphan Basin and the Northern Grand Bank show comparatively high Te values. As expected, Te broadly reflects the depth of the 200$–$400°C isotherm below the weak surface sediment layer at the time of loading, and at the margins most of the loading occurred during rifting. We infer that these low Te measurements indicate Te frozen into the lithosphere. This could be due to the passive nature of the margin when the loads were emplaced during the continental break-up process at high temperature gradients.

Written history’s limitation becomes apparent when attempting to document the predecessors of extreme coastal events in the Indian Ocean, from 550–700 years in Thailand and 1000 years in Indonesia. Detailed ground-penetrating radar (GPR) surveys in Mahabalipuram, southeast India, complemented with sedimentological analyses, magnetic susceptibility measurements, and optical dating provide strong evidence of extreme wave events during the past 3700 years. The diagnostic event signatures include the extent and elevation of the deposits, as well as morphologic similarity of buried erosional scarps to those reported in northern Sumatra region. Optical ages immediately overlying the imaged discontinuities that coincides with high concentration of heavy minerals date the erosional events to 340 ± 35, 350 ± 20, 490 ± 30, 880 ± 40, 1080 ± 60, 1175 ± 188, 2193 ± 266, 2235 ± 881, 2489 ± 293, 2450 ± 130, 2585 ± 609, 3710 ± 200 years ago. These evidences are crucial in reconstructing paleo extreme wave events and will pave the way for regional correlation of erosional horizons along the northern margin of Indian Ocean.

This work deals with a methodology applied to seismic early warning systems which are designed to provide real-time estimation of the magnitude of an event. We will reappraise the work of Simons et al. (2006), who on the basis of wavelet approach predicted a magnitude error of ±1. We will verify and improve upon the methodology of Simons et al. (2006) by applying an SVM statistical learning machine on the time-scale wavelet decomposition methods. We used the data of 108 events in central Japan with magnitude ranging from 3 to 7.4 recorded at KiK-net network stations, for a source–receiver distance of up to 150 km during the period 1998–2011. We applied a wavelet transform on the seismogram data and calculating scale-dependent threshold wavelet coefficients. These coefficients were then classified into low magnitude and high magnitude events by constructing a maximum margin hyperplane between the two classes, which forms the essence of SVMs. Further, the classified events from both the classes were picked up and linear regressions were plotted to determine the relationship between wavelet coefficient magnitude and earthquake magnitude, which in turn helped us to estimate the earthquake magnitude of an event given its threshold wavelet coefficient. At wavelet scale number 7, we predicted the earthquake magnitude of an event within 2.7 seconds. This means that a magnitude determination is available within 2.7 s after the initial onset of the P-wave. These results shed light on the application of SVM as a way to choose the optimal regression function to estimate the magnitude from a few seconds of an incoming seismogram. This would improve the approaches from Simons et al. (2006) which use an average of the two regression functions to estimate the magnitude.