DETECTION OF IGNEOUS BODIES IN HUAIBEI COAL MINESBY HIGH RESOLUTION MAGNETIC SURVEY

The present paper investigates the application of high resolution magnetic survey to detecting igneous bodies. The slight difference in magnetism between igneous bodies and their surrounding rocks is measured first and then the magnetic survey data are processed to determine whether there exist igneous bodies by analog among several measuring lines, and finally the modified Marquart inversion was used to determine the occurrence and distribution of the igneous bodies.

Simplifying the Integration of Petrophysics and Rock-Physics to Identify Hydrocarbon Bearing Rocks on Seismic

A considerable effort has been made in the literature for quality assurance (QA) and quality checking (QC) of the petrophysical log data for computation of reservoir rock property parameters. Well log data plays an integral role in building a rock physics model for quantitative interpretation (QI) work. A poor-quality rock physics model may lead to significant financial and HSSE implications by drilling wells in undesired locations. Historically, a variety of techniques have been used including histograms and cross plots for reviewing the feasibility of petrophysical logs for QI work. However, no attempt has ever been made to introduce a simplified workflow. This paper serves two-fold. It provides a simplified step by step approach for building a petrophysics/rock physics model. A case study has been presented to compare the synthetic seismogram generated from the simplified workflow with the actual seismic trace at well locations. Secondly, the paper shows how a few key cross plots and rock property parameters provide adequate information to validate petrophysical data, distinguish overburden and reservoir sections, and to help identify fluids and saturation trends within the reservoir sands. In the mentioned case study, the robustness of the simplified rock physics model has helped seismic data to successfully distinguish hydrocarbon bearing reservoir sands from non-reservoir shales.

Prejudgments for Reference Potential Determination to Quantitative EEG Interpretation:Amplitude Distribution and Ear-lobe Activation

This paper presents an automatic techruque of suitable reference potential selection for quantitative EEG interpretation.The 16-channels EEG recording under mono-polar derivation is analyzed.There are two prejudgments defined for checking the amplitude distribution and ear lobe activation.After prejudgments,the EEG is classified into several cases in cluding diffused case,non-diffused case,and artifact contami nation case.Due to the cases,an automatic reference selection method is applied in order to find out suitable reference potential.Finally,the referential derivation constructed according to the obtained reference potential,is evaluated for further EEG rhythm analysis.The presented technique can high light the EEG rhythm of interest,which is useful for quantitative EEG interpretation by both visual inspection and automatic evaluation.

A Neural Paradigm forTime-Varying Motion Segmentation

This paper proposes a new neural algorithm to perform the segmentation of an observed scene into regions corresponding to different moving objects byanalyzing a time-varying images sequence. The method consists of a classificationstep, where the motion of small patches is characterized through an optimizationapproach, and a segmentation step merging neighboring patches characterized bythe same motion. Classification of motion is performed without optical flow computation, but considering only the spatial and temporal image gradients into anappropriate energy function minimized with a Hopfield-like neural network givingas output directly the 3D motion parameter estimates. Network convergence is accelerated by integrating the quantitative estimation of motion parameters with aqualitative estimate of dominant motion using the geometric theory of differentialequations.