鄂尔多斯盆地长7段油页岩裂缝测井定量识别

Recognizing Oil Shale Fracture of Chang 7Member in Ordos Basin Using Logging Data

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 porosity in oil shale, and fracture network provides main flow path for oil product in this kind of reservoir,thus the development degree of natural fracture system directly affects the exploitation efficiency of oil shale reservoirs. Therefore,the study on oil shale＇s fracture is particularly im- portant. Logging curves can identify oil shale accurately,but it is still a challenge to evaluate the develop- ment degree of fracture in oil shale. In this work, five logging indexes which could reflect the degree of frac- ture development in Chang 7 Member in Ordos Basin were chosen after analyzing the different logging re- sponse of oil shale in this area, and the probability model of oil shale was established based on the five de- fined indexes and their weights which was determined using analytic hierarchy processes. The automatic- quantitative,, identification of oil shale fractures by computer is realized. Compared the recognition results with the image logging,it shows that this method can accurately recognize the fractures in oil shale, and it can satisfy the identification accuracy requirements of fracture in oil shale formation using logging data.