The purpose of this research is to enhance the methods of surface seismic data processing and interpretation operations by using the produced information of vertical seismic profile (measured velocity and corridor stack). Sindbad oil field (South of Iraq) is chosen to study goals and it's containing only one well with VSP survey (Snd2) that covering depth from Zubair to Sulaiy Formations and 2D seismic lines of Basrah Survey. The horizons were picked and used with low frequency contents from well data for the construction of low frequency model and it was used with high frequency of VSP to make the high frequency model that compensated to seismic main frequency through inversion process. Seismic inversion technique is performed on post stack of 2D seismic data (2Br2) through Hampson-Russell CGG program. The inversion model of low frequency shows 88.5% matching with relative seismic impedance while high frequency model 93.3% matching with lower error percent. The two impedance sections which resulted from inversion model were convoluted with best wavelet from VSP data to make a new seismic section. The LFM section was similar to original seismic section while the HFM section shows real enhancement of the Flatspot (DHI) feature and recoverable some missing reflectors.
Enhancement of Seismic reflectors by using VSP and Seismic Inversion in Sindbad oil field, south of Iraq
Seismic data processing
VSP
Seismic Inversion
Sindbad oilfield
Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Estimating the Survival Function for the Patients Suffer from the Lung Cancer Disease
Survival Function
Lung Cancer Disease
Complete Real Data
Maximum Likelihood Method
Shrinkage Method
Mean Squares Error and Mean Absolute Percentage Error.
In this paper, the survival function has been estimated for the patients with lung cancer using different parametric estimation methods depending on sample for completing real data which explain the period of survival for patients who were ill with the lung cancer based on the diagnosis of disease or the entire of patients in a hospital for a time of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the estimation of the survival function for the lung cancer by using pre-test singles stage shrinkage estimator method was the best . <
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