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地震剖面所能识别的断层断距通常大于１５ｍ，小断层的识别是油田地质研究中的一大难题。若将在同一地质作用下形成、产于同一地质体内的具有相同性质的所有断层视为一个总体，用帕雷托（Ｐａｒｅｔｏ）模型可以表示断层的总体分布。用图解法对未检测到的小断层进行预测时，要考虑地震测网密度对断层识别的影响。提出改进的图解法，计算给定地震测网密度下一特定规模的断层被检测到的概率（简称为检测概率），并以此检测概率为指导，用最小二乘法来估计断层的分布参数，以提高小断层预测的精度。在此基础上，可以根据断层断距和长度之间的统计关系，用一个参数的总体分布估算另一个参数的总体分布
Seismic section of the fault identification can be more than 15m, fault identification is a major problem in the field of geological research. All faults of the same nature produced in the same geological body can be considered as a whole if Pareto model is used to represent the overall fault distribution. When using the graphic method to predict undetected small faults, the influence of seismic net density on fault identification should be considered. An improved graph method is proposed to calculate the probability of fault detection (referred to as detection probability) of a given scale under a given seismic net density. Based on this detection probability, the least square method is used to estimate the distribution parameters of the fault, To improve the accuracy of small fault prediction. Based on this, the overall distribution of one parameter can be estimated based on the statistical relationship between the fault breakage and the length of the fault