Rate of Penetration Prediction Method for Ultra-Deep Wells Based on LSTM-FNN

Article Chemistry, Multidisciplinary

Intelligent Prediction of Stuck Pipe Using Combined Data-Driven and Knowledge-Driven Model

Shuo Zhu et al.

Summary: This study presents three methods for predicting stuck pipe, including detection of friction coefficient, prediction of stuck pipe probability using artificial neural network, and establishment of a comprehensive indicator using fuzzy mathematics. The results indicate that the last model is the best, with a high prediction accuracy.

APPLIED SCIENCES-BASEL (2022)

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Article Geosciences, Multidisciplinary

Prediction of rock penetration rate using a novel antlion optimized ANN and statistical modelling

Abiodun Ismail Lawal et al.

Summary: Predicting the penetration rate (PR) of granite rock is a complex task that relies on various variables. Different optimization tools, including antlion optimized ANN (ALO-ANN), have been used in studies to predict PR. The performance evaluation of these models shows that ALO-ANN provides a better predictive model, with rho and Is(50) having more influence on PR than mu. This study demonstrates the effectiveness of ALO-ANN in enhancing drilling and blasting designs.

JOURNAL OF AFRICAN EARTH SCIENCES (2021)

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Article Engineering, Geological

Hybrid ensemble soft computing approach for predicting penetration rate of tunnel boring machine in a rock environment

Abidhan Bardhan et al.

Summary: This study successfully predicts the rate of penetration of TBM using a hybrid ensemble machine learning method, demonstrating its feasibility in a rock environment. By constructing and validating multiple models, a hybrid ensemble model superior to others was developed.

JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING (2021)

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Article Energy & Fuels

Data-driven recurrent neural network model to predict the rate of penetration

Husam H. Alkinani et al.

Summary: The study successfully developed a recurrent neural network model to accurately predict the Rate of Penetration (ROP) in drilling operations. By optimizing the network architecture and training it with a large dataset, the model achieved a high level of prediction accuracy.

UPSTREAM OIL AND GAS TECHNOLOGY (2021)

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Article Energy & Fuels