APA (7th ed.) Citation

Neto, E. R. d. O., Fernandes, F. J. D., Fatah, T. Y. A., Dias, R. M., Piedade, Z. R. T. d., Freire, A. F. M., & Lupinacci, W. M. A data-driven approach to predict fracture intensity using machine learning for presalt carbonate reservoirs: A feasibility study in the Mero Field, Santos Basin, Brazil. KeAi Communications Co., Ltd.

Chicago Style (17th ed.) Citation

Neto, Eberton Rodrigues de Oliveira, Fábio Júnior Damasceno Fernandes, Tuany Younis Abdul Fatah, Raquel Macedo Dias, Zoraida Roxana Tejada da Piedade, Antonio Fernando Menezes Freire, and Wagner Moreira Lupinacci. A Data-driven Approach to Predict Fracture Intensity Using Machine Learning for Presalt Carbonate Reservoirs: A Feasibility Study in the Mero Field, Santos Basin, Brazil. KeAi Communications Co., Ltd.

MLA (9th ed.) Citation

Neto, Eberton Rodrigues de Oliveira, et al. A Data-driven Approach to Predict Fracture Intensity Using Machine Learning for Presalt Carbonate Reservoirs: A Feasibility Study in the Mero Field, Santos Basin, Brazil. KeAi Communications Co., Ltd.