Deep Learning for Multiwell Automatic Log Correction
Distinguished Speaker: Vanessa Simoes (SLB)
Date: Tuesday, March 14, 2023
Time: Online (9:00 am – 10:00 am CDT)
Contact : Hyungjoo Lee (SPWLA PDDA SIG)
Corresponding: [email protected]
Speaker Bio:
Vanessa Simoes leads log quality control and improvement projects in the Digital Subsurface Intelligence team in SLB, Houston. She graduated in Computing and Applied Mathematics from the University of Sao Paulo (USP) in 2006. She received her MSc in mathematical modeling and her Ph.D. in mathematics from the Instituto de Matemática Pura e Aplicada (IMPA) in 2009 and 2013, respectively. She concluded two specialization programs in data analytics and deep learning at Pontifical Catholic University (PUC), Rio de Janeiro, in 2018. Vanessa joined SLB in 2013 and has worked as a research scientist and data scientist in Rio de Janeiro, Boston, and Houston. Her technical interests include renewable energies, acoustics, data analysis, statistics, and rock physics. In this presentation, she introduces MALC (Multiwell Automatic Log Correction), an innovative way to perform wellbore log correction. The method relies on statistics, deep learning, and multi-log multiwell analysis to improve log consistency. She describes the methodology, applies it in different scenarios, and introduces some evaluation strategies using information theory and domain knowledge.
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