کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1754727 | 1522808 | 2015 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Estimation of shear wave velocity from wireline logs in gas-bearing shale
ترجمه فارسی عنوان
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
زمین شناسی اقتصادی
چکیده انگلیسی
Gas-bearing shale is one of the most important unconventional reservoirs. Shear wave velocities are essential for prestack AVO analysis, fracture identification, and fluid typing. Moreover, the recent studies of shear wave prediction mostly focused on conventional sandstones, wet shale, sandstone or carbonate rock may not be suitable for gas-bearing shale. Firstly, according to core analysis results of gas-bearing shale, petrophysics model is proposed. Then, shear wave prediction method based on Gasmann's theory, spatial averaging model, and elastic moduli of dry rock were studied in detail. Especially, point to organic shale with low porosity, Krief, Nur, and Pride models are selected to calculate the elastic moduli of dry rock, respectively, and the best critical porosity in Nur model and consolidation coefficient in Pride model are determined, which is virtual to gas-bearing shale. Pride model is finally optimized as the most suitable model through comparison of error analysis. Meanwhile, to implement the estimation of shear wave from well logs, a corresponding log interpretation method for gas-bearing shale is also studied. In case study, calculated volumetric concentrations of minerals are in good agreement with X-ray diffraction (XRD) analysis of cores. The final shear wave velocity also matches well with dipole sonic imaging (DSI) log. Therefore, the whole approach is verified correct and suitable for estimation of shear velocity or slowness in gas-bearing shale.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Petroleum Science and Engineering - Volume 133, September 2015, Pages 352-366
Journal: Journal of Petroleum Science and Engineering - Volume 133, September 2015, Pages 352-366
نویسندگان
Maojin Tan, Xiao Peng, Huilan Cao, Shixing Wang, Yijun Yuan,