In this paper we present a novel approach to detect salt bodies based on seismic attributes and supervised learning. We report on the use of a machine learning algorithm, Extremely Randomized Trees, to automatically identify and classify salt regions. We have worked with a complex synthetic seismic dataset from phase I model of the SEG Advanced Modeling Corporation (SEAM) that corresponds to de...

limited seismic data quality and complex tectonics make for less than ideal interpretation conditions. however, modern geometric attributes including coherency has shown to be effective in showing the lateral extents of subtle and small-scale geologic features not usually visible in conventional seismic sections. this geometric attributes are better suited than some older generation seismic att...

many steps of seismic data processing sequence suppose that data sets are sampled in time and spatial dimensions uniformly. today, this assumption is true but only in time dimension. modern seismic exploration equipment permits seismic data sets to be sampled uniformly and densely in time dimension. however, along spatial dimension uniform and dense sampling are not possible because of operatin...

Seismic interferometry processing is applied to an active seismic survey collected on ocean bottom seismometers (OBS) deployed at 900-m water depth over a carbonate/ hydrates mound in the Gulf of Mexico. Common midpoint processing and stacking of the extracted Green’s function gives the subsurface PP reflectivity, with a horizontal resolution of half the receiver spacing. The obtained seismic s...

This paper proposes a simplified analytical model for seismic response prediction of concentrically braced frames. In the proposed approach, a multistory frame model is reduced to an equivalent shear-building one by performing a static pushover analysis. The conventional shear-building model has been improved by introducing supplementary springs to account for flexural displacements in addition...

This paper focuses on an overview of kernel density estimation especially for what concerns the choice of bandwidth and intensity parameters according to local conditions. A case study inherent seismic risk analysis of the old town centre of Potenza hilltop town has been discussed, with particular attention to the evaluation of the possible local amplifying factors. This first integrated applic...

Intelligent reservoir characterization using seismic attributes and hydraulic flow units has a vital role in the description of oil and gas traps. The predicted model allows an accurate understanding of the reservoir quality, especially at the un-cored well location. This study was conducted in two major steps. In the first step, the survey compared different intelligent techniques to discover ...

Subsurface modeling from seismic and borehole data is important for reservoir prediction, geophysical exploration and production. A reasonable model should honor borehole rock properties and conform to seismic structural and stratigraphic features. Such a subsurface model can be di cult to create in cases complicated by faults and unconformities. Automatic and semi-automatic methods have been p...

Subsurface modeling from seismic and borehole data is important for reservoir prediction, geophysical exploration, and production. A reasonable model should honor borehole rock properties and conform to seismic structural and stratigraphic features. Such a subsurface model can be difficult to build in cases complicated by faults and unconformities. Automatic and semiautomatic methods have been ...

Seismological images represent maps of the earth’s structure. Apparent bandwidth limitation of seismic data prevents successful estimation of transition sharpness by the multiscale wavelet transform. We discuss the application of two recently developed techniques for (non-linear) singularity analysis designed for bandwidth limited data, such as imaged seismic reflectivity. The first method is a...