Seismic imaging generally relies on data quality, velocity reliability, and migration operator performance. Complex near-surface geological conditions in Kuqa depression cause extremely low signal-to-noise (S/N) ratios of seismic data. Salts penetrating into overthrust structures are widely distributed, vary in thickness and shape of complex geometries, and distort the imaging of subsalt faults, leading to complicated imaging problems. This article studies three key issues. In the preprocessing of prestack data, some innovative techniques combined with commercial techniques are employed by three levels to improve data quality and reconstruct the reflections from depths. Three-stage migration velocity analyses, subtle DMO velocity analysis, prestack time-migration, and prestack depth-migration velocity analyses are implemented to build a topology-preservation prestack-migration velocity model. The time-depth conversion of the prestack time-migration velocity model is performed based on the Kuqa-depression modeling of salt-related overthrust complex structures combined with the velocity-varying mapping technique. The well-constrained seismic inversion for low-frequency velocities is conducted to handle the syncretization of the well-building and migration-building velocity fields. Finally, prestack time and depth migrations are performed by a semi-analytic degenerate Fourier migrator that improves the imaging of high-wavenumber components. Applications to the Dabei, Bozi, Quele, Xiqiu10, and Xiqiu4 structures result in well-positioned images for salt-related overthrust complex structures.

Borehole instability in drilling engineering can bring about serious problems of drilling quality and safety. Based on the close relationships between seismic and well log information, the prediction method of borehole stability is presented to effectively control borehole instability. Conventional and nonlinear seismic attributes are extracted from borehole-side seismic traces of impending drilling well and drilled offset well respectively. Then the optimal attributes combinations sensitive to log properties are selected by using genetic algorithm and wavelet neural network technology together. A series of mapping models which reflect the nonlinear relationships between seismic attributes and acoustic and density log data of various formation intervals in drilled well are constructed through neural network modeling. With analysis of cutting logging data, seismic attributes of the formation under bit and corresponding mapping model can be used to predict acoustic and density log curves of this formation. Based on the predicted log data, log interpretation method, analysis technology of in-situ stress and mechanics model of borehole stability are employed to calculate in-situ stress, pore pressure, collapse pressure and fracture pressure, thus the safe drilling fluid density window which can keep borehole stable is determined. Prediction precision and real-time operation ability of the proposed method are satisfying, which have been proved in practical application in TR oil field.

This paper proposes the concept and the technology of social networking federation as a paradigm where information on various social network systems can be seamlessly integrated in order to provide users a uniform and semantic view of their social connections. Such a uniformly fused social network provides a single point of access where all information with respect to one's social networks can be queried and reasoned about. The goal of the research is to establish a foundation of integrating and assimilating information within multiple social network systems. We designed a reference model of social networking federation system in this paper, as well as some prototype application to demonstrate its paradigm. We believe our work would provide a novel vision of future online social network. [All rights reserved Elsevier].