2026-10-06T07:28:32Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34046526 2026-10-01T15:30:16Z category_26839 category_29173 item_type_3 month_year_10_2026

Dataset for "Physics-Informed Super-Resolution for Two-Phase Multi-scale Reservoir Simulation" Haotian Li (25157103) Petroleum and reservoir engineering Machine learning not elsewhere classified super-resolution reservoir simulation physics-informed machine learning mass balance two-phase flow <p dir="ltr">This item contains the data sets for the paper "Physics-Informed Super-Resolution for Two-Phase Multi-scale Reservoir Simulation" (Li, Aslam, Ma, Wang, Yan).</p><p dir="ltr">The data are two-phase (oil-water) water-flooding simulations of a 10,000 x 10,000 x 10 ft channelized reservoir, generated with the CMG IMEX simulator on a coarse (20 x 20) and a fine (100 x 100) grid. Each case contains 11 timesteps (dt = 365 days) of pressure and water saturation, the permeability and porosity fields, well locations, and time-varying well controls (injection rates and producer bottom-hole pressures).</p><p dir="ltr">All files are in HDF5 format and can be read with h5py.</p><p><br></p> 2026-10-01T15:30:16Z Dataset Dataset 10.6084/m9.figshare.34046526.v1 https://figshare.com/articles/dataset/Dataset_for_Physics-Informed_Super-Resolution_for_Two-Phase_Multi-scale_Reservoir_Simulation_/34046526 CC BY 4.0