ENERXICO has organised a minisymposium at the SIAM Conference on Mathematical & Computational Issues in the Geosciences (GS21), which takes place virtually at 9:20-13:55 CEST on 21 June 2021.
Title: HPC numerical tools in Hydrocarbon Exploration and Development
The scope of this minisymposium encompasses HPC high accurate modeling codes to assist industrial-scale operations for hydrocarbon exploration and development. We will review numerical tools applied to the small-scale and complex dynamics of multiphase flows in naturally fractured reservoirs during production and pipeline transportation or to large-scale seismic wave propagation in realistic geological structures that highly support exploration and development. Speakers are invited to discuss code scalability and parallel optimizations, along with the physical consistency of the underlying computational methodology, both features crucial for practical field assessment and imaging of complex Earth models. This workshop would serve as a springboard for discussions about the next generation of Exascale modeling tools for upstream operations of the hydrocarbon industry.
|9:20-9:40||Applying Machine Learning in Geophysics Processing for Better Assessment of Subsurface Uncertainties||Taoufik Ait-Ettajer (REPSOL)|
|9:45-10:05||Full Waveform Inversion of Ocean-Bottom Seismic Data using a Fluid-Solid Coupled SEM Solver||Jian Cao (UGA)|
|10:10-10:30||Expansion-based time integrations for Pseudospectral modeling of acoustic wave propagation||Otilio Rojas (BSC)|
|10:35-10:55||Advanced Material Models for Seismic Simulations using ADER-DG||Sebastian Wolf (TUM)|
|11:00-11:20||Gas Injection Study for EOR Applications in a Mexican Gas/Condensate Reservoir Fluid||Humberto Hinojosa (ININ)|
|11:55-12:15||Reservoir characterization using geophysics electromagnetic and HPC||Octavio Castillo (BSC)|
|12:20-12:40||HPC for Seismic Processing and Stochastic Inversion in Brazil Asset||Cassiane Nunes (REPSOL-SINOPEC)|
|12-45-13:05||Passive Seismic, HPC and AI; a feasible cost effective future for subsurface monitoring||Carlos Santos Molina (REPSOL)|
|13:10-13:30||Machine Learning for Characterizing the Earth Subsurface||Ursula Iturraran Viveros (UNAM)|