【作者】 李明娟；

【导师】 唐世伟；

【作者基本信息】 东北石油大学 ， 石油工程计算技术， 2012， 硕士

【摘要】 随着油田勘探开发的不断深入，对地震资料解释精度的要求越来越高，对解释项目的完成周期要求越来越短，所以地震资料解释技术的发展方向是在高精度的前提下实现自动化的地震资料解释，因此在提取断层以后，对断层进行平滑处理越来越重要。目前在断层多边形平滑领域已经提出了许多方法，但是至今提出的相关理论和方法尚存在不足之处，在某些情况下仍然无法很好地对断层进行平滑，难以找到一种普遍适应性的断层多边形平滑方法。人工神经网络是计算机科学、信息科学和物理学交互发展形成的一门边缘学科，数字图像处理是人工神经网络目前较新的和最重要的应用领域之一，而图形平滑是图像处理的一个应用。因此，本文设计了一种人工神经网络和断层多边形平滑技术相结合的方法来实现高效率、高精度的断层多边形自动平滑。本文首先研究了图像平滑及曲线平滑的一般方法、传统多边形平滑方法，比较了各种方法的优缺点。其次，对人工神经网络常用模型进行分析，把模型应用于断层多边形平滑，并取得了明显的效果。最后，针对实际项目的要求设计了基于人工神经网络的断层多边形自动平滑方法，并将其应用到断层多边形平滑及解释系统中，该系统可以完成对有复杂断层分布和噪声干扰的区块，自动提取出的断层多边形进行自动平滑处理，再将人工交互处理结果输出到文件并进行保存等功能，该平滑方法平滑完成的断层多边形光顺、连续以及具有丰富的边缘细节。现今，已完成断层多边形平滑及解释系统的设计并将其应用到实际项目中，且取得了良好的使用效果，提高了断层解释的效率和精度，并缩短了解释周期。更多还原

【Abstract】 With the deepening development of the oil field exploration, it demands higher andhigher interpretation accuracy and shorter interpretation period for interpreting, so thedevelopment direction of seismic data interpretation technology is to realize automaticinterpretation on condition of high precision, therefore after extracting, the fault smoothing ismore and more important.At present many methods have been proposed in the fault polygon smooth field, but sofar there are still deficiencies for the related theory and method proposed, and in some casesthe effect is not very well, so it is hard to find a commonly adaptable fault polygon smoothingmethod. Artificial neural network is a borderline subject combined with computer science,information science and interaction of the formation of the development of physics. Thedigital image processing is a new and the most important one of the application in field ofartificial neural network at present.While graphics smooth is an application of the imageprocessing.Therefore, this paper designed a method which combined with artificial neuralnetwork and fault polygon smoothing technique to realize the high efficiency and highprecision after automatically smoothing.The paper first studied the general smoothing method for the image and curve and thetraditional polygon smoothing method, then compared the advantages and disadvantages ofeach method. Second, the artificial neural network model which is commonly used wasanalyzed, and the model is applied to fault polygon smooth, and have made an obvious effect.Lastly, according to the actual needs of the project it designed fault polygon automaticallysmoothing method based on artificial neural network, and the method is applied to faultpolygon smoothing and interpretation system.Using the system, it can smooth automaticallyfor blocks with complex fault distribution and noise, and extract fault polygon automatically,then save the output result.The practice proved that the result is smooth, continuous and is ofrich edge details.Today, it has completed the design of the fault polygon smooth andexplanation system.This system has been applied to the practical projects and achieved gooduse of effects, and using the system, the precision and efficiency of fault interpretation isimproved and the explanation cycle is shortened.更多还原