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油页岩没有有效孔隙,主要是通过裂缝网络生产油气,天然裂缝系统发育程度直接影响油页岩开采效益,因此油页岩裂缝的研究尤为重要。利用测井曲线可以较准确识别出油页岩段,但如何利用测井资料有效评价油页岩的裂缝发育程度仍然是一大难题。分析归纳了鄂尔多斯盆地长7段油页岩地层的测井响应特征之后,给出了能够较好地反映研究区内裂缝发育程度的5种测井指标,进而构建了鄂尔多斯盆地油页岩裂缝概率模型,同时利用层次分析法确定了模型中的权重。将此模型程序化,实现了油页岩裂缝的计算机自动定量识别。识别结果与成像测井对比表明,该方法能够较准确地对油页岩的裂缝进行识别,且精度较高、实用性强,能够满足油页岩地层裂缝测井识别精度的要求。
There is no effective pore in oil shale, which mainly produces oil and gas through the fracture network. The development degree of natural fracture system directly affects the benefit of oil shale mining. Therefore, the study of oil shale fracture is especially important. The logging curve can identify the oil shale section more accurately. However, how to use the well logging data to evaluate the fracture development of oil shale effectively remains a challenge. After analyzing the logging response characteristics of the oil shale formation in the Chang 7 Member of the Ordos Basin, five well logging indicators that can well reflect the degree of fracture development in the study area are given, and then the probability of oil shale fracture in the Ordos Basin is established Model, at the same time using the analytic hierarchy process to determine the weight of the model. This model is programmed to realize the computer automatic quantitative identification of oil shale cracks. The comparison between the recognition results and imaging logging shows that this method can identify the fracture of oil shale more accurately and has higher accuracy and practicability, which can meet the requirements of fracture logging identification accuracy of oil shale formation.