A NEW TECHNIQUE TO PREDICT THE FRACTURES DIP USING ARTIFICIAL NEURAL NETWORKS AND IMAGE LOGS DATA
作者： Mostafa Alizadeh , Zohreh Movahed , Radzuan Junin , Rahmat Mohsin , Mehdi Alizadeh
DOI: 10.11113/JT.V75.5330
关键词: Artificial neural network 、 Image (mathematics) 、 Learning rule 、 Fracture (geology) 、 Engineering 、 Tree (data structure) 、 Data mining 、 Field (computer science)
摘要: Fractures provide the place for oil and gas to be reserved they also can pathway them move into well, so having a proper knowledge of is essential every year companies try improve existed softwares in this technology. In work, new technique introduced added as application such Petrel geoframe softwares. The data used work are image logs other geological tree wells located Gachsaran field, number GS-A, GS-B GS-C. by using feed-forward artificial neural networks (ANN) with back-propagation learning rule predict fracture dip third well from 2 wells. result obtained showed that ANN model simulate relationship between fractures dips these 3 which multiple R training test sets 0.95099 0.912197, respectively.
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