Automatic fracture density update using smart well data and artificial neural networks
Author:
Publisher
Elsevier BV
Subject
Computers in Earth Sciences,Information Systems
Reference19 articles.
1. Al-Anazi, A., Babadagli, T., 2007. Use of real-time dynamic data to generate fracture network models. Paper IPTC 11492. In: Proceedings of the International Petroleum Technology Conference, Dubai, UAE. pp. 10.
2. Athichanagorn, S., Horne, R., Kikani, J., 1999. Processing and interpretation of long-term data from permanent downhole pressure gauges. Paper SPE 56419. In: Proceedings of the Society of Petroleum Engineers Annual Technical Conference and Exhibition, Houston, TX, USA. pp. 16.
3. Aydinoglu, G. Bhat, M., Ertekin, T., 2002. Characterization of partially sealing faults from pressure transient data. Paper SPE 78715. In: Proceedings of the Society of Petroleum Engineers Eastern Regional Meeting, Lexington, Kentucky, USA. pp. 13.
4. Fractal analysis of 2D fracture networks of geothermal reservoir in south-western Turkey;Babadagli;Journal of Volcanology and Geothermal Research,2001
5. Boerner, S., Gray, D., Todorovic-Marinic, D., Zellou, M., Schnerk, G., 2003. Employing neural networks to integrate seismic and other data for the prediction of fracture intensity. Paper SPE 84453. In: Proceedings of the Society of Petroleum Engineers Annual Technical Conference and Exhibition, Denver, CO, USA. pp. 13.
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