Study Of Seismic Processing Method On Desert Area

With potential oil & gas resource, Tarim Desert area is the emphasis andproblem area among prospect areas in western China. Being influenced by theproblem of surface static correction and low signal-to-noise, seismic data isrestricted to resolve geological problem. Therefore, it is in dire need to set up a set ofseismic data processing method suitable to low signal-to noise desert area.This article will mainly discuss about high resolution statics correction,pre-stack high fidelity noise removing and high frequency signal compensation andetc.. Statics correction is a kind of complicated problem, and any one sole methodcan't resolve completely statics correction problem actually. Based on the actualsituation, several methods of statics correction was applied in this area, includingfield sand dune curve statics, tomography inversion statics, multi-channel groundroll surface surveying statics, first arrival refraction wave statics, and field modelingstatics, as well as developing a new method, multinomial fitting surface velocitystatics, at last, result shows that this new method is stable, and resolving basicallystatics problem of middle wave length and long wave length, no miss tie existingbetween sections. Aiming at the characteristics that there are three main kinds ofnoise in Tarim basin including ground roll, refraction wave and secondary noise, allof which energy or frequency at least is the same as that of valid wave, so the studyincludes pre-stack multi-domain noise removing, post-stack noise removing. Whilepre-stack noise removing can improve the effect of deconvolution, on the other hand,it can increase signal-to-noise and the accuracy of velocity analysis,thus canincrease image accuracy of target zone. Meanwhile post-stack noise removing helpimprove signal-to-noise further, and attenuating noise arousing from processing. Testand final result proves its good effect.The study also includes a series of high frequency signal compensation, highfidelity processing method, practice proves the fidelity, resolution andsignal-to-noise improve much.