Daniel J. Salzman
Staff Program Analyst, Vice President
Daniel J. Salzman has more than 14 years of experience in the petroleum industry. He joined DeGolyer and MacNaughton in 2010 as an associate analyst, assisting in the evaluation of prospective resources in various geographic regions throughout the world. Since 2019, Salzman has led the firm’s Data Analytics group within the Information Technologies Division.
Salzman graduated with honors from the University of Notre Dame in 2010 with a bachelor’s degree in physics and a bachelor’s degree in classics. He is a member of the Society of Petroleum Engineers. He was named a Vice President of D&M in 2019.
Geographical Experience
- Australia
- Azerbaijan
- Brazil
- Cameroon
- China
- Colombia
- Egypt
- Grenada
- Guyana
- Indonesia
- Iraq
- Italy
- Kenya
- Liberia
- Libya
- Madagascar
- Malaysia
- Mexico
- Mozambique
- Mauritania
- Namibia
- Nigeria
- Norway
- Oman
- Peru
- The Philippines
- Ras al-Khaimah
- Republic of the Congo
- Russia
- Saudi Arabia
- Senegal
- Suriname
- Tanzania
- Thailand
- Trinidad and Tobago
- Uganda
- Ukraine
- United States
- United Kingdom
- Uruguay
- Vietnam
- Yemen
Topical Areas of Expertise
- Data visualization
- Cloud computing
- Monte Carlo simulation
- Reservoir performance forecasting
- Economic analysis
- Prospective resources evaluations
- Simulation modeling software
- Custom computer programming
- Cost analysis
- Mature waterflood analysis
Major Projects
Salzman has experience evaluating prospective resources and developing economic models for onshore and offshore oil and gas fields around the globe.
He has assisted with the development and maintenance of a proprietary, simulation-based software package used by D&M for reservoir performance forecasting and economic analysis in the evaluation of reserves and prospective resources.
He has overseen various projects related to increasing the efficiency of core business processes and employing advanced analytics and emerging technologies to improve and expand the firm’s offerings. These have included solutions for the identification of geologic analogs, probabilistic forecasting of production, and various data manipulation and visualization workflows.
