About This Item
- Full TextFull Text(subscription required)
- Pay-Per-View PurchasePay-Per-View
Purchase Options Explain
Share This Item
The AAPG/Datapages Combined Publications Database
Indonesian Petroleum Association
Abstract
Fracture Network Characterization of Naturally Fractured Reservoir Using Artificial Neural Network and Fractal Methods
Abstract
The behaviour of a naturally fractured reservoir is very unpredictable, since, fractures greatly influence reservoir characteristic. Reservoir characteristic is often a critical parameter in accurately predicting reservoir performance. Fracture shape including parameters such as length, density, and orientation can be described as a non Euclidean object because of its complexity. Hence, it is believed that the fractal concept can be applied to fracture network characterization.
In this study we extend the method of fracture network mapping by introducing the fractal dimension as a constrain for mapping formula. Therefore, the result of reservoir description can be used with greater confidence.
The objective of this research is to develop a new approach in fracture network mapping for naturally fractured reservoirs that integrates geology, geomechanics, reservoir engineering, and the latest which are Neural Network and fractal concept. In this work, the fractal dimension of the reservoir is used to characterize the fracture network of actual reservoir. Fractal dimension is utilized as a limiting parameter in constructing the fracture intensity map of the reservoir.
Pay-Per-View Purchase Options
The article is available through a document delivery service. Explain these Purchase Options.
Watermarked PDF Document: $14 | |
Open PDF Document: $24 |