From fluid flow to coupled processes in fractured rock: Recent advances and new frontiers

HS Viswanathan, J Ajo‐Franklin… - Reviews of …, 2022‏ - Wiley Online Library
Quantitative predictions of natural and induced phenomena in fractured rock is one of the
great challenges in the Earth and Energy Sciences with far‐reaching economic and …

Stacked ensemble machine learning for porosity and absolute permeability prediction of carbonate rock plugs

R Kalule, HA Abderrahmane, W Alameri, M Sassi - Scientific Reports, 2023‏ - nature.com
This study employs a stacked ensemble machine learning approach to predict carbonate
rocks' porosity and absolute permeability with various pore-throat distributions and …

A machine learning framework for rapid forecasting and history matching in unconventional reservoirs

S Srinivasan, D O'Malley, MK Mudunuru… - Scientific Reports, 2021‏ - nature.com
We present a novel workflow for forecasting production in unconventional reservoirs using
reduced-order models and machine-learning. Our physics-informed machine-learning …

Machine-learning predictions of the shale wells' performance

M Mehana, E Guiltinan, V Vesselinov… - Journal of Natural Gas …, 2021‏ - Elsevier
The ultra-low permeability nature of shale reservoirs leads to an extended linear flow and
necessitates horizontal wells with multi-stage engineered fractures to efficiently extract …

A multi-dimensional parametric study of variability in multi-phase flow dynamics during geologic CO2 sequestration accelerated with machine learning

H Wu, N Lubbers, HS Viswanathan, RM Pollyea - Applied Energy, 2021‏ - Elsevier
Successful geologic CO 2 storage projects depend on numerical simulations to predict
reservoir performance during site selection, injection verification, and post-injection …

Design and performance analysis of dry gas fishbone wells for lower carbon footprint

H Ouadi, A Laalam, A Hassan, A Chemmakh… - Fuels, 2023‏ - mdpi.com
Multilateral well drilling technology has recently assisted the drilling industry in improving
borehole contact area and reducing operation time, while maintaining a competitive cost …

Unsupervised time series clustering, class-based ensemble machine learning, and petrophysical modeling for predicting shear sonic wave slowness in …

S Bhattacharya - Geophysics, 2022‏ - pubs.geoscienceworld.org
Shear sonic logs are critical for formation evaluation, rock physics, quantitative reservoir
characterization, and geomechanical studies. Although empirical and conventional machine …

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

AG Sorokin, A Pachalieva, D O'Malley… - Advances in Water …, 2024‏ - Elsevier
Limiting the injection rate to restrict the pressure below a threshold at a critical location can
be an important goal of simulations that model the subsurface pressure between injection …

Deep learning to estimate permeability using geophysical data

MK Mudunuru, ELD Cromwell, H Wang… - Advances in Water …, 2022‏ - Elsevier
Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to
estimate three-dimensional (3D) permeability fields from electrical potential difference …

[HTML][HTML] Coupling Upscaled Discrete Fracture Matrix and Apparent Permeability Modelling in DFNWORKS for Shale Reservoir Simulation

C Zhong, JY Leung - Advances in Water Resources, 2024‏ - Elsevier
Modelling non-Darcy flow behaviour in shale rocks, composed of nanometer-sized pores
and multi-scale fracture networks, is crucial for various subsurface energy applications …