A Quantitative Approach To Characterize Porosity Structure From Borehole Electrical Images and Its Application in a Carbonate Reservoir in the Tazhong Area, Tarim Basin
- Hai-cheng Fu (China University of Geosciences, Beijing) | Chang-chun Zou (Key Laboratory of Geo-detection (China University of Geosciences, Beijing)) | Ning Li (Research Institute of Petroleum Exploration & Development, PetroChina) | Cheng-wen Xiao (Research Institute of Exploration & Development, PetroChina Tarim Oilfield Company) | Cheng-sen Zhang (Research Institute of Exploration & Development, PetroChina Tarim Oilfield Company) | Xing-neng Wu (Research Institute of Exploration & Development, PetroChina Tarim Oilfield Company) | Rui-lin Liu (College of Geophysics and Petroleum Resource, Yangtze University, Wuhan)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- January 2016
- Document Type
- Journal Paper
- 18 - 23
- 2016.Society of Petroleum Engineers
- RMSRPS, porosity spectrum, borehole electrical images, LRPS, carbonate reservoir
- 0 in the last 30 days
- 381 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 10.00|
|SPE Non-Member Price:||USD 30.00|
For a carbonate reservoir that has low porosity, its validity cannot simply be measured by its total porosity. Therefore, one must find more-effective porosity parameters to indicate reservoir validity. Two parameters that reflect the porosity spectrum’s shape are proposed in this paper to characterize the porosity structure from borehole electrical images. One is the length of the right-porosity spectrum (LRPS), and the other is the root mean square (RMS) of the right-porosity spectrum (RMSRPS). Subsequently, the validity of a carbonate reservoir was considered by use of these two parameters. The logging evaluation, processing, and interpretation of multiple wells in a fractured/vuggy reservoir with low porosity in the Tarim Basin indicate that these two parameters reflect the variation of pore structures better than conventional methods, and they agree better with the well-test results.
|File Size||1 MB||Number of Pages||6|
Archie, G. E. 1942. Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics. Trans., AIME 146: 54–62. SPE-942054-G-PA. http://dx.doi.org/10.2118/942054-G-PA.
Fan-shun, Meng, Qing-fu, Feng, and Xiang-rui, Yang 2006. Using Electro-Imaging Logging Data To Analyze Secondary Porosity. Oil Geophysical Prospecting 41 (2): 221–225 (in Chinese).
Ghafoori, M. R., Roostaeian, M., and Sajjadian, V. A. 2008. Secondary Porosity: A Key Parameter Controlling the Hydrocarbon Production in Heterogeneous Carbonate Reservoirs (Case Study). Presented at the SPWLA 43th Annual Logging Symposium, Austin, Texas, 25–28 May. SPWLA-2008-TTTT.
Jinhu, Du, Xinyuan, Zhou, Qiming, Li et al. 2011. Characteristics and Controlling Factors of the Large Carbonate Petroleum Province in the Tarim Basin, NW China. Petroleum Exploration and Development 38 (6): 652–661(in Chinese). http://dx.doi.org/10.1016/S1876-3804(12)60002-0.
Newberry, B. M., Grace, L. M., and Stief, D. D. 1996. Analysis of Carbonate Dual Porosity Systems From Borehole Electrical Images. Presented at the Permian Basin Oil and Gas Recovery Conference, Midland, Texas, 27–29 March. SPE-35158-MS. http://dx.doi.org/10.2118/35158-MS.
Tyagi, Anil Kumar and Bhaduri, Amit 2002. Porosity Analysis Using Borehole Electrical Images in Carbonate Reservoirs. Presented at the SPWLA 43rd Annual Logging Symposium, Oiso, Japan, 2–5 June. SPWLA-2002-KK.
Xiao-hui, Li, Yan-qiu, Zhou, Yan-hong, Gou et al. 2012. Porosity Analysis of Micro-Electric Imaging Logging and Its Application in Carbonate Reservoir Production Capacity Forecast. Journal of Jilin University (Earth Science Edition) 42 (4): 928–934 (in Chinese).
Xiao-lu, Zhu, Hong-ju, He, Rui-lin, Liu et al. 2013. On the Response Features of Porosity Spectrum of Dolomite Reservoirs in DengYing Formation of Sinian System of Central Sichuan Area. Journal of Oil and Gas Technology (J.JPI) 35 (4): 83–88 (in Chinese).
Xing-neng, Wu, Ruilin, Liu, Jun Lei et al. 2008. Study on Converting Electrical Imaging Log Into Porosity Distribution Image. Well Logging Technology 32 (1): 53–56 (in Chinese).
Xinyuan, Zhou, Zhaoming, Wang, Haijun, Yang et al. 2006. Cases of Discovery and Exploration of Maine Fields in China (Part 5): Tazhong Ordovician Condensate Field in Tarim Basin. Marine Origin Petroleum Geology 11 (1): 45–51 (in Chinese).
Xinyuan, Zhou, Xiongqi, Pang, and Qiming, Li et al. 2010. Advances and Problems in Hydrocarbon Exploration in the Tazhong Area, Tarim Basin. Petroleum Science 7 (2): 164–178. http://dx.doi.org/10.1007/s12182-010-0020-1.