Concepts, Data and Algorithms - Exploring Integrated Approaches in Reservoir Characterization

Tuesday, 17 October

0830 - 1130

Room 217 D

Technical Session

From Data-driven to deep learning, concepts, data and algorithms, this session which explore approaches in reservoir characterization.

0830-0855 215019
Seismic Reflectivity Inversion Using A Semi-supervised Learning Approach

A. Abd Rahman, PETRONAS; A.M. El Sheikh, Heriot-Watt University; M. Jaya, PETRONAS
0855-0920 215133
Causal Inference for the Characterization of Microseismic Events Induced by Hydraulic Fracturing

O. Rojas Conde, S. Misra, R. Liu, Texas A&M University
0920-0945 215072
Deep-learning-based Approach For Optimizing Infill Well Placement

P. Zhang, T. Gao, B. Fu, R. Li, Variables Intelligence Corporation
1015-1040 214792
Modeling Heterogeneity Of Glacial Reservoir Using Geostatistical Approach: A Case Study, Southwest Libya.

F.A. Bergigh, Akakus Oil Operations Libya; W.S. Meddaugh, Midwestern State University; T.M. Alkhemri, Akakus Oil Operations Libya
1040-1105 214789
Rock Physics Modeling Of Hydrogen-bearing Sandstone: Implications For Natural Hydrogen Exploration And Storage

M. Ahmad Fuad, H. Zhao, M. Jaya, E. Jones Jr, PETRONAS RESEARCH SDN BHD

2023 Technical Program