William Contreras

With over 30 years of experience in the oil industry, this Drilling Engineering Specialist brings a wealth of knowledge and expertise.

During last 10 years, focused on Digital Drilling Business, on capturing Data, implementation of ML solutions, and Engineering Solution on Real Time.

Throughout their career, they have successfully managed complex projects in challenging environments such as HPHT, H2S, CO2, and ERD. Their educational background includes a bachelor's degree in Mechanical Engineering from the University of Los Andes, Merida, Venezuela, as well as a Master of Science in Petroleum Engineering from the University of Tulsa. Alongside their academic achievements, they have also been granted multiple patents and have published numerous specialized papers and articles in their field. Their core competencies lie in effectively managing digital drilling projects, developing and testing innovative drilling technologies, analyzing and optimizing drilling data, providing support to operational and engineering departments, evaluating service company performance, and identifying best practices. Additionally, they have led and contributed to data management and analytics projects utilizing cutting-edge technologies such as data mining, machine learning, and artificial intelligence to enhance drilling efficiency. Passionate about driving innovation and excellence in drilling engineering, their ultimate goal is to deliver exceptional value and results.

• Place of Birth: Merida, Venezuela
• Date of Birth: 01/07/68
• Nationality: Venezuelan (American Green Card Holder)

• Method and system of drilling with geologically-driven rate of penetration, US 11339640, 05/24/22
• Automatic analysis of drill string dynamics, US 11506044, 11/2022
• Automatic slips detection system for the optimization of real-time drilling operations, US11519257, 12/06/22
• Analysis of Drilling Slurry Solids by Image Processing, US 11,719,089, 08/08/23
• Rig Power System efficiency optimization through image processing, US 11727555, 08/15/23
• Systems and methods to characterize well drilling activities, US11739626, 08/29/23
• System and Methods for the measurement of drilling mud flow in real-time, US 11,867,008, 01/09/24

• Saudi Aramco 2010 D&WO Recognition Award
• Saudi Aramco 2011 D&WO Recognition Award
• Saudi Aramco 2013 D&WO Recognition Award
• IoT evolution edge computing excellence award, IoT evolution, 07/2020, Award to the project camera-based edge analytics for drilling optimization.
• Innovative Technology, Energy institute, 08/2020, Award to the project camera-based edge analytics for drilling optimization.
• Global energy award, Global energy, 08/2020, Award to the project camera-based edge analytics for drilling optimization.
• ADIPEC. Digital transformation project of the year award, ADIPEC, 09/2020, Award to the project camera-based edge analytics for drilling optimization.
• IoT World award 2020, IOT world award, 11/2020, Award to the project camera-based edge analytics for drilling optimization.

• Diagnóstico de Fallas en Sistemas de Aire Acondicionado, Segundo Congreso Venezolano de Ingeniería Mecánica, Maracaibo, Venezuela, 1991
• Reducción del impacto ambiental a través del uso de Localizaciones Secas y sistemas cerrados de fluidos de Perforación, Décimo Congreso Latinoamericano de Perforación, Quito, Ecuador, 1996
• Reducción del impacto ambiental a través del uso de Localizaciones Secas y sistemas cerrados de fluidos de Perforación, Segundo Congreso de Protección Ambiental PDVSA, San Tome, 1997
• New Drilling Business Schemes, PDVSA-PETROBRAS Business Exchange Forum, Maturin, Venezuela, 2000
• The Effect of Inlet Gas Void Fraction on the Performance of Liquid-Liquid Cylindrical Cyclone (LLCC) Separator, University of Tulsa, Tulsa, OK, USA, 2002
• Knowledge Management (KM) to face the Challenges of the Oil Industry, Saudi Aramco DTD Focus, 2012
• Advanced Drilling Analysis Tool (DTA), Saudi Aramco DTD Focus, 2012
• ADAT, SPE ATS&E, Khobar, Saudi Arabia, 2013
• Advanced Drilling Analysis Tool, Journal of Technology, 2013
• Bottom-Hole Assembly Management System (BHAMS), SPE ATS&E, Khobar, Saudi Arabia, 2014
• Saudi Aramco Real-Time Drilling Operation Activity Recognition & Analysis Engine, SPE Abu Dhabi, 2015
• A Comprehensive Approach to Measure the Real-Time Data Quality Using Key Performance Indicator, SPE, 2016
• Management of the Change of Operation Classification Coding System for the Next Leap, SPE, 2018
• The future of Edge Computing in the Oil & Gas Industry, SPE Workshop: Delivering Value through Automation, 2019
• Intelligent Drilling Edge Analytics Environment: Challenges and Lessons Learned, SPE Workshop: Delivering Value through Automation, 2019
• Advanced Data Analytics and Procedures for the early detection of Stuck Pipe Incidents, SPE, 2019
• Tripping Performance Analysis and Quantifying Invisible Lost Time, IPTC, 2020
• Drilling in the Fourth Industrial Revolution. Vision and Challenges, IEEE Engineering Management Review, 2020
• Hybrid data-driven drilling rate of penetration optimization scheme guided by geological formation and historical data, ICWDT, 2020
• Camera-based edge analytics for drilling optimization, IEEE, 2020
• Drilling Real-time Data: Data Acquisition Time Synchronization Framework for Critical IR 4.0 Solutions, SPE, 2020
• Well control space out: a deep-learning approach for the optimization of drilling safety operations, IEEE, 2021
• Internet of Things IoT Edge computer vision systems on drilling rigs, SPE, 2021
• The Challenges with Drilling Real-Time Data and Proposed Data Management Framework, ADIPEC, 2022
• Real-time Bit Wear Prediction and Deployment Validation in Challenging Hard and Heterogeneous Sandstones using 3D Detailed and Simplified Physics-Based Progressive Wear Models, SPE, 2023
• Bit Performance Measurement Approach. An Innovative Way to Improve Bit Selection Process, SPE, 2023
• Drilling Optimization in Challenging Hard and Heterogeneous Sandstones using 3D Progressive Wear Simulation and Multiwell Data Learning, International Petroleum Technology Conference, 2023
• Real-time Bit Wear Prediction and Deployment Validation in Challenging Hard and Heterogeneous Sandstones Using 3D Detailed and Simplified Physics-Based Progressive Wear Models, The Aramco Journal of Technology, 2023