| Data-driven deep-learning forecasting for oil production and pressure R de Oliveira Werneck, R Prates, R Moura, MM Gonçalves, M Castro, ... Journal of Petroleum Science and Engineering, 109937, 2021 | 33 | 2021 |
| A visual analytics approach to anomaly detection in hydrocarbon reservoir time series data A Soriano-Vargas, R Werneck, R Moura, PM Júnior, R Prates, M Castro, ... Journal of Petroleum Science and Engineering, 108988, 2021 | 12 | 2021 |
| Humidity effects on effective elastic properties of rock: An integrated experimental and numerical study MM Hossain, JY Arns, Z Liang, Z Chen, CH Arns Journal of Geophysical Research: Solid Earth 124, 1-21, 2019 | 12 | 2019 |
| Experimental and modelling approaches to determine the effect of moisture contents, grain contact and confining pressure on effective elastic properties of rock MM Hossain University of New South Wales, 2017 | 5 | 2017 |
| Detecting anomalies in production data using machine learning techniques https://doi.org/10.48072/2525-7579.rog.2022.298, 2022 | | 2022 |
| USE OF PRODUCTION DATA TO ASSESS CORRELATION & INTERWELL CONNECTIVITY DJSADG Maiara Moreira Gonçalves, M. Manzur Hossain, Aurea Rossy Soriano ... https://doi.org/10.48072/2525-7579.rog.2022.305, Proceedings of the Rio Oil …, 2022 | | 2022 |
| Image-based computation of effective elastic properties of porous rock incorporating the effect of surface energy change, grain contact zone MM Hossain, JY Arns, CH Arns inproceedings SEG/AGU Upper Crust Physics of Rocks Workshop, Hilo, Hawaii …, 2016 | | 2016 |
| The impact of interfacial tension on effective elastic properties of partially saturated rock MM Hossain, CH Arns inproceedings The 7th Annual Digital Core Research Consortium Meeting …, 2014 | | 2014 |
Jiyoun ArnsUniversity of New South WalesVerified email at unsw.edu.au
