Study on intelligent prediction method of rock drillability based on Bayesian lithology classification and optimized BP neural network-Reference-Cited by-同舟云学术

Study on intelligent prediction method of rock drillability based on Bayesian lithology classification and optimized BP neural network

Published:2022-02-13 Issue:17 Volume:40 Page:2141-2162
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Fang Xinxin¹²^ORCID,Feng Hong²,Wang Hao³

Affiliation:

1. China Coal Research Institute, Beijing, China

2. China Coal Technology & Engineering Group Xian Institute, Xi’an, China

3. Research Institute of Petroleum Exploration & Development, Beijing, China

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2022.2036759

Reference34 articles.

1. Application of artificial neural network in optimizing the drilling rate of penetration of western desert Egyptian wells

2. Prediction of asphaltene precipitation using artificial neural network optimized by imperialist competitive algorithm

3. Applying a sophisticated approach to predict CO2solubility in brines: application to CO2sequestration

4. Connectionist model predicts the porosity and permeability of petroleum reservoirs by means of petro-physical logs: Application of artificial intelligence

5. Evolving smart approach for determination dew point pressure through condensate gas reservoirs

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