中文摘要：

地震属性技术广泛应用于油气勘探与开发，但因地震波在地球介质中传播的复杂性、地震数据采集观测系统的局限性以及噪音干扰等原因，地震属性用于地震资料解释仍然具有很大的不确定性，而地震属性的抗噪性直接影响着地震解释的可信度。灰色理论用于处理时间序列信号具有弱化随机性、增加规律性的能力。消除趋势波动法能有效地消除数据中的各种不确定性未知趋势本文将灰色理论和消除趋势波动法相结合，提出了基于灰色消除趋势波动法计算分形标度指数地震属性的新方法。论文以Weierstrass函数产生的非线性时间序列以及实际地震资料增加随机噪音为例，讨论了灰色一消除趋势波动法计算分形标度指数的抗噪能力，研究表明新方法计算的分形标度指数具有良好的抗噪能力。将该方法应用于四川东北部地区三维地震叠后偏移数据，与传统的消除趋势波动法提取的分形标度指数地震属性进行对比，结果表明新方法计算的分形标度指数地震属性与钻井等资料结合分析，能够更好地区分沉积相带的差异，揭示生物礁的发育带。

英文摘要：

Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition system, and noise interference, seismic attributes for seismic data interpretation have uncertainties. Especially, the antinoise ability of seismic attributes directly affects the reliability of seismic interpretations. Gray system theory is used in time series to minimize data randomness and increase data regularity. Detrended fluctuation analysis （DFA） can effectively reduce extrinsic data tendencies. In this study, by combining gray system theory and DFA, we propose a new method called gray detrended fluctuation analysis （GDFA） for calculating the fractal scaling exponent. We consider nonlinear time series generated by the Weierstrass function and add random noise to actual seismic data. Moreover, we discuss the antinoise ability of the fractal scaling exponent based on GDFA. The results suggest that the fractal scaling exponent calculated using the proposed method has good antinoise ability. We apply the proposed method to 3D poststack migration seismic data from southern China and compare fractal scaling exponents calculated using DFA and GDFA. The results suggest that the use of the GDFA-calculated fractal scaling exponent as a seismic attribute can match the known distribution of sedimentary facies.