油气储层岩心实验的样本量设计

油气储层实验数据是油气地质研究、岩石地球物理评价和油气藏工程理论计算的基础。然而，油气储层所用的岩心样品数量有限且实验费用高昂，难以获取大量的实验数据，这就造成了后续储层参数评价的不确定性。该文阐述了油气储层岩心实验数据的样本量设计方法，探讨了随机抽样方法下合理的样本量设计流程；结合实测油气储层实验数据，分析了样本量设计的效果。结果表明:利用相邻井岩心资料和测井信息可以有效地预估岩心实验的样本量，提高实验数据的应用效果。在岩心实验的设计中，应该充分重视实验样本量设计这一基本环节，并采用随机化、重复和区组化的实验设计策略，对于节约实验周期与成本、提升岩心实验数据的可靠性有着重要作用。 

Sample size design for oil and gas reservoir core-plug experiments

Experimental data of oil and gas reservoirs are the basis of oil and gas geology research, rock geophysical evaluation and petroleum engineering calculations. However, the number of core samples is limited and the experiment costs are high, making it difficult to obtain large amounts of data, resulting in the uncertainty of reservoir evaluation. This paper presented a sample size design method for the core data of oil and gas reservoirs, and discussed some reasonable sample size design steps using a random sampling method. The effect of sample size design was analyzed combined with the experimental data. The results showed that using adjacent well data and well logging data can effectively predict sample size, reduce experiment cost and improve the application effect of experimental data. In the design of core experiments, we should pay full attention to sample design, and adopt randomized, repeated and segmented experiment design strategies, which are important for saving experiment cycles and costs and improving the reliability of core experiment data.