The Contrast And Study Of First Arrivals Detecting On Seismic Record

First arrivals detecting on Seismic Record is important at all time. It hassignificant function on the refraction static correction, VSP interpretation, shallowrefraction and seismic tomography surveys. First arrival detecting is accurate or notcan directly affect the result of processing. The workload of first arrival detecting isprodigious in seismic data processing, so its speed has crucial effect to the efficiencyof seismic data processing.By far, many methods and theories have been put forward, such as correlationmethod, ratio of energy method, maximal amplitude method, fractal dimensionmethod and neural network. For some areas that have simple first arrivals, it can reachthe require using normal method, but for complicated areas, first arrivals detecting isdifficult, it is a difficult problem for us for a long time, So it is worth to do research tofind a method that can improve its veracity and stability. It is also the main content ofthis paper's task.In this paper, the method and theory that seismic attributes within time windows,fractal dimension and artificial neural network can be used to pick seismic first breakare been compared and analyzed. And bring out a new method, it is statistical method.It has proposed advantages, disadvantages and conditions of these method byapplying these methods to practical seismic datum that have different areas anddifferent ratios of signal to noise.