The Impact of Time-shift Estimation and Correction on Two 4D Attributes - Amplitude Difference and Velocity Change
4D seismic data can provide valuable insights to the reservoir and non-reservoir interpretation. Seismic attributes like amplitude difference and velocity change are commonly used to perform such task. All these attributes are computed after correlating monitor and base datasets, where time-shifts are observed. The technique responsible to correlate monitor and base amplitudes is called warping. In this study we apply the warping technique defined in Hale (2009) to the Norne field benchmark case. We investigate how uncertainties related to the choice of parameters used in Hale’s method impact on the time-shifts computation and in two 4D seismic derived attributes: amplitude difference and velocity change. We show that the time-shifts computation and the amplitude difference after time-shift correction are robust when considering different parameter values, while the results of velocity change are affected by the parameter choice.
In this paper, we suggested AdBoost algorithm for further improvising the performance of system. In the enhanced adaboost, the eigen vectors are computed for facial region & applied classification. In the process of classification, we opt for process of learning, training & testing. As observed from the result sessions in the previous paper [13] the outcomes from the reboost detection are observed. They provide the results in the form of Detection rate & false alarm rate. We applied the suggested methodology & improvising the performance of false alarm rate & detection rate. We have raised the rate of detection & false alarm rate. For presenting the contrasts, we have designed GUI window where comparisons are presented.