Permeability Prediction of the Tight Sandstone Reservoirs Using Hybrid Intelligent Algorithm and Nuclear Magnetic Resonance Logging Data

Author:

Zhu Lin-qi,Zhang Chong,Wei Yang,Zhang Chao-mo

Funder

the Natural Science Foundation of China

the Nature Science Foundation of Hubei Province

Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference40 articles.

1. Coates, G.R.; Marschall, D.; Mardon, D.: A new characterization of bulk-volume irreducible using magnetic resonance. In: SPWLA 38th Annual Logging Symposium on Society of Petrophysicists and Well Log Analysts (SPWLA 1997), QQ. TX (1997)

2. Shao, W.Z.; Jie, J.Y.; Chi, X.R.; Li, J.: On the relation of porosity and permeability in low porosity and low permeability rock. Well Logging Technol. 37(2), 149–153 (2013)

3. Trevizan, W.; Coutinho, B.; Netto, P.: Magnetic resonance (NMR) approach for permeability estimation in carbonate rocks. In: OTC Brasil on Offshore Technology Conference (OTC2015), MS. pp. 27–29. Rio (2015)

4. Kenyon,W.E.; Day, P.I.; Straley, C.: A three-part study of NMR logitudinal relaxation properties of water-saturated sandstones. In: SPE Fomation Evaluation on Society of Petroleum Engineers (SPE1988), PA, pp. 622–636. (1988)

5. Xiao, Z.X.; Xiao, L.: Method to calculate reservoir permeability using nuclear magnetic resonance logging and capillary pressure data. At. Energy Sci. Technol. 42(10), 868–871 (2008)

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