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IMPLEMENTING ARTIFICIAL NEURAL NETWORK FOR PREDICTING CAPILLARY PRESSURE IN RESERVOIR ROCKS

Volume 4, Edição 4, 2013, pp. 315-325
DOI: 10.1615/SpecialTopicsRevPorousMedia.v4.i4.30
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RESUMO

Capillary pressure is one of the main parameters which is widely used to characterize and describe reservoir rock properties. Although some methods have been proposed to determine capillary pressure in reservoir rock, these methods may not be able to determine the capillary pressure accurately. In this study, an artificial neural network (ANN) algorithm was developed to estimate the capillary pressure in a hydrocarbon reservoir in the Middle East. A complete data set of several core samples includes porosity (Φ), normalized porosity (Φz), permeability (k), rock quality index (RQI),flow zone indicator (FZI); water saturation and drainage capillary pressure curves were applied to develop the ANN model. The ANN model which was designed in this study contains two separate parts. The first part categorized the reservoir rock into discrete groups with similar ranges of porosity and permeability, and the second part estimated the capillary pressure for each group. The results of this study revealed that ANN is an appropriate method to estimate the capillary pressure in reservoir rocks, particularly those which have heterogeneity in rock properties.

CITADO POR
  1. Jamshidian Majid, Mansouri Zadeh Mostafa, Hadian Mohsen, Moghadasi Ramin, Mohammadzadeh Omid, A novel estimation method for capillary pressure curves based on routine core analysis data using artificial neural networks optimized by Cuckoo algorithm – A case study, Fuel, 220, 2018. Crossref

  2. Busaleh Yasser R., Abdulraheem Abdulazeez , Okasha Taha , Prediction of Capillary Pressure for Oil Carbonate Reservoirs by Artificial Intelligence Technique, All Days, 2016. Crossref

  3. Zhang Zhenzihao, Ertekin Turgay, Proxy models for evaluation of permeability, three-phase relative permeability, and capillary pressure curves from rate-transient data, SIMULATION, 97, 2, 2021. Crossref

  4. Seyyedattar Masoud, Zendehboudi Sohrab, Butt Stephen, Technical and Non-technical Challenges of Development of Offshore Petroleum Reservoirs: Characterization and Production, Natural Resources Research, 29, 3, 2020. Crossref

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