Comparison of NMR-Derived Hydraulic Conductivity with Various Hydraulic Testing Methods

核磁共振法测得的水力传导率与各种水力测试方法的比较

阅读:4

Abstract

Borehole nuclear magnetic resonance (NMR) can be used to estimate the hydraulic conductivity (K) of unconsolidated materials. Various petrophysical models have been developed to predict K based on NMR response, with considerable efforts on optimizing site-specific constants. In this study, we assessed the utility of NMR logs to estimate K within highly heterogeneous glaciofluvial deposits by comparing them with K measurements from three types of co-located hydraulic testing methods, including permeameter, multi-level slug, and direct-push hydraulic profiling tool (HPT) logging tests. Four NMR models, including Schlumberger-Doll Research (SDR), Seevers, Sum-of-Echoes (SOE), and Kozeny-Godefroy (KGM), were applied to construct K profiles at four locations with model constants optimized using permeameter-based K. Model constants suitable for glaciofluvial deposits were provided. Results showed that NMR logging can provide reliable K estimates for interbedded layers of sand/gravel, silt, and clay. Through cross-hole comparison of NMR-derived K profiles, the trends and magnitudes of K for aquifers/aquitards were readily mapped. Quantitatively, the NMR-derived K coincided with hydraulic-testing K, with optimal model fits within one order of magnitude. We noticed that (1) Seevers performed similarly but no better than SDR in predicting permeameter and slug testing measurements; (2) SOE yielded slightly better predictions than SDR; (3) the removal of porosity in SDR did not deteriorate its prediction, and the optimized SDR constant resembled the literature-based values for glacial deposits; and (4) KGM yielded the optimal fits with slug-based K, demonstrating its reliable performance. Lastly, we made recommendations on selecting suitable petrophysical models.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。