For many decades most oil wells in Iran have produced using their natural flow potential and haven’t needed to be fractured. As time goes by, the reservoir pressure depletes and the need for hydraulic fracturing as a stimulation practice arises. Nonetheless there is no record of successful hydraulic fracturing in Iran.
The Bangestan reservoir with a suitable amount of oil in place and good rock reservoirs, has been selected for the present research work. In this work, the in situ stress profile was calculated by using the available petrophysical data. This is achieved by using poroelastic theory for the stresses, and the Mohr–Coulomb criterion to predict failure. The model leads to easily computed expressions for calculating the pressure required to maintain hydraulic fracturing. Then the appropriate depth for treatment was determined. The results indicate that Ilam and Sarvak formations could be good candidates for hydraulic fracturing. Then, for two layers, a hydraulic fracture was designed and the production was predicted and the Net Present Value (NPV) resulting from the fracture of both layers was investigated. 相似文献
提出了一种融合光谱和空间结构信息的高光谱遥感影像增量分类算法INC_SPEC_MPext。通过主成分分析(PCA)提取高光谱影像的若干主成分,利用数学形态学提取各主分量影像对应的形态学剖面(MP),再将所有主分量影像的形态学剖面归并联结,组成扩展的形态学剖面(MPext)。将MPext与光谱信息相结合以增加知识,最大限度地挖掘未标记样本的有用信息,优化分类器的学习能力。不断从分类器对未标记样本的预测结果中甄选置信度高的样本加入训练集,并迭代地利用扩大的训练集进行分类器构建和样本预测。以不同地表覆盖类型的AVIRIS Indian Pines和Hyperion EO-1Botswana作为测试数据,分别与基于光谱、MPext、光谱和MPext融合的分类方法进行比对。试验结果表明,在训练样本数量有限情况下,INC_SPEC_MPext算法在降低分类成本的同时,分类精度和Kappa系数都有不同程度的提高。 相似文献