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Salah El Din Mahmoud

Salah El Din Mahmoud

AI-Powered Seismic Data Labeling & Training Lead (ADNOC)

USA flagDallas / Tulsa, Usa
$75.00/hrExpertOther

Key Skills

Software

Other

Top Subject Matter

Seismic interpretation
fault and fracture analysis
carbon storage

Top Data Types

3D Sensor
TextText
DocumentDocument

Top Task Types

ClassificationClassification

Freelancer Overview

AI-Powered Seismic Data Labeling & Training Lead (ADNOC). Brings 37+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Geoteric and Other. Education includes Doctor of Philosophy, University of Texas (2004) and Master of Science, Cairo University (1995). AI-training focus includes data types such as Geospatial and Tiled Imagery and labeling workflows including Classification.

ExpertEnglishArabic

Labeling Experience

AI-Powered Seismic Data Labeling & Training Lead (ADNOC)

Classification
Oversaw the adoption of AI and deep learning techniques for fault interpretation in seismic geophysical data. Developed and applied a novel technique for ultra-high resolution fracture and fault characterization using artificial intelligence. Led training and mentoring on AI-driven seismic interpretation workflows for geoscientists. • Integrated microseismic data with fracture modeling for improved accuracy. • Used Geoteric AI for robust classification and labeling of faults and fractures. • Ensured high-quality validated data for seismic interpretation tasks. • Enhanced subsurface modeling with accurate labels facilitating carbon capture site characterization.

Oversaw the adoption of AI and deep learning techniques for fault interpretation in seismic geophysical data. Developed and applied a novel technique for ultra-high resolution fracture and fault characterization using artificial intelligence. Led training and mentoring on AI-driven seismic interpretation workflows for geoscientists. • Integrated microseismic data with fracture modeling for improved accuracy. • Used Geoteric AI for robust classification and labeling of faults and fractures. • Ensured high-quality validated data for seismic interpretation tasks. • Enhanced subsurface modeling with accurate labels facilitating carbon capture site characterization.

2019 - 2024

AI-Based Seismic Annotation & Classification Specialist (KUFPEC)

OtherClassification
Implemented AI’s neural networks to predict gas-layer thicknesses using seismic data. Developed a proprietary seismic conditioning technique to label features for reducing uncertainties in well placement. Led the Center of Excellence in mentoring young professionals in labeling and classification workflows using AI. • Applied novel AI-based techniques for static reservoir modeling. • Supervised annotation and classification of seismic datasets in multiple countries. • Utilized inversion analysis outcomes for prospect delineation and labeling. • Established best practices for seismic data conditioning labels and uncertainty reduction.

Implemented AI’s neural networks to predict gas-layer thicknesses using seismic data. Developed a proprietary seismic conditioning technique to label features for reducing uncertainties in well placement. Led the Center of Excellence in mentoring young professionals in labeling and classification workflows using AI. • Applied novel AI-based techniques for static reservoir modeling. • Supervised annotation and classification of seismic datasets in multiple countries. • Utilized inversion analysis outcomes for prospect delineation and labeling. • Established best practices for seismic data conditioning labels and uncertainty reduction.

2011 - 2017

Neural Network Data Labeling Lead (NALPETCO)

OtherClassification
Applied AI’s neural network classification for the identification of multi-target seismic prospects. Integrated multi-azimuth seismic volumes to label and classify sub-surface structures with challenging illumination. Supervised the geophysical studies department’s adoption of AI-based annotation workflows for prospect analysis. • Overcame poor illumination challenges using AI-driven classification efforts. • Established internal workflows for neural network-based data labeling. • Enabled faster identification and classification of prospects in complex basins. • Supported team development in AI labeling technique adoption.

Applied AI’s neural network classification for the identification of multi-target seismic prospects. Integrated multi-azimuth seismic volumes to label and classify sub-surface structures with challenging illumination. Supervised the geophysical studies department’s adoption of AI-based annotation workflows for prospect analysis. • Overcame poor illumination challenges using AI-driven classification efforts. • Established internal workflows for neural network-based data labeling. • Enabled faster identification and classification of prospects in complex basins. • Supported team development in AI labeling technique adoption.

2009 - 2010

Education

U

University of Texas

Doctor of Philosophy, Geosciences

Doctor of Philosophy
1997 - 2004
C

Cairo University

Master of Science, Geosciences

Master of Science
1995 - 1995

Work History

P

Pan-Tech

Principal Geophysicist

Dallas / Tulsa
2025 - Present
T

Total Energies

Senior Consultant Geophysicist

Basra
2024 - 2025