| Oil as the economic lifeline of country, it plays a vital role in the development of the national economy, so it is very self-evident for development and utilization of oil. Due to collected seismic data containing abundant stratigraphic information, making seismic data processing become a very important job in seismic exploration, in order to obtain detailed stratigraphic information, and exploit more oil and gas reservoirs, it must be find a quick effective method to extract feature information contained in the signal.In this paper, aiming at the hidden oil and gas reservoir, non-linear and non-stationary characteristics of seismic signal as well as large seismic data, a effectively method of processing seismic data must be found in this paper:①Find the hidden oil and gas reservoirs. To the beginning of the twenty-first century, developers are facing the same dilemma on developing oil and gas:With the large-scale oil and gas fields being developed, most of the undiscovered oil and gas reservoirs are reserved dispersedly, thin, deep buried, and porosity conditions are complex while they are difficult to detect, so the difficulty of its exploration has become increasing, in order to find the hidden reservoir, and obtain the better seismic profiles of signal, the new signal processing technologies is found to process the collected signal more accurated and more sophisticated.②Process non-linear and non-stationary seismic signal. The most commonly signal processing methods was Fourier analysis and wavelet analysis in the time and frequency analysis field of seismic signals ago, there are many defects on both them. Hilbert Huang transform is based on local signal characteristics, and is adaptive by itself compare to Fourier analysis and wavelet analysis, it can identify the different vibration mode of the signal, but it also has its shortcomings, so the shortage is analyzed in the paper, a Hilbert-Huang transform algorithm based on extremum point optimization is presented, which can identify the different vibration mode of the signal, excluding the seismic signal noise and correctly identify the formation.③Owing to the amount of3D seismic data is very large, it is very difficult for serial algorithm to meet the needs of the growing computing power, which brings great challenges on the processing of seismic data, so it seems urgent to find a fast approach. In recent years, GPU (Graphics Processing Unit:Graphics Processor) technology has been rapid development, as a hardware of appropriative image protracting, GPU play great significance on the development of parallel algorithms, its main advantage is speed compared to the CPU, and its advantages are mainly form its unique hardware system design, developers can take advantage of this unique hardware architecture to develop the processing performance of software platform far more than the CPU’s. Therefore, the development of parallel software systems based on GPU acceleration has a very important practical significance. A parallel Hilbert Huang transform algorithms is presented to quickly obtain a higher resolution seismic attribute profile, and contribute to the underground reservoir, greatly improving the exploitation of oil and gas reservoirs.Five different sizes of seismic data are tested. Using presented algorithms to process3D seismic data can obtain much higher vertical resolution and improve the efficiency on the GPU. Experimental results show that:①Hilbert Huang Transform algorithm based on extreme point optimization can improve vertical resolution of the seismic profile to some extent, identify and analysis correctly thin stratum;②Parallel Hilbert Huang transform algorithm is used to process seismic data, it improves more than10times compared to the CPU processing speed, thus greatly improve the efficiency of oil and gas exploration. |
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