Scott E. Evans
Scott E. Evans has more than 17 years of experience in the petroleum industry. He joined DeGolyer and MacNaughton in 2007 as a specialist in computer programming and database design. Evans writes full-stack applications and numerous essential routines and performs database management services for geologic and engineering data.
Evans graduated with honors from Texas A&M University with a bachelor’s degree in physics in 2001 and a master’s degree in mathematics in 2008. He was named a Vice President of D&M in 2019.
Geographical Experience
- Algeria
- Brazil
- China
- Colombia
- Germany
- India
- Indonesia
- Iraq
- Mexico
- Kazakhstan
- Romania
- Russia
- Ukraine
- Saudi Arabia
- United States
- United Arab Emirates
- Venezuela
- Vietnam
Topical Areas of Expertise
- Reserves forecasting applications
- Economic evaluation applications
- Database design
- Database conversions
- Software applications and languages (C#, WPF, SQL Server, Azure, PHDWin, ARIES, Microsoft Access, Microsoft Excel, VB.Net, VBA)
Major Projects
Evans developed a comprehensive suite of applications to enhance technical forecasting, economic analysis, and data management. His production forecasting solution, designed to comply with SEC and PRMS guidelines, offers decline-curve analysis and charting tools and automatically integrates volumetric data to improve efficiency and accuracy. Originally developed to provide algorithms and custom visualizations to enable the efficient well-level evaluation of development, scheduling, and estimation scenarios for large Russian reserves assets, it has since expanded to handle the variable data environments that D&M encounters around the globe and interface directly with commercial software platforms such as PHDWin and D&M’s enterprise database.
Evans’ other projects include the design and development of economic models targeting the unique legal, operational, capital, tax, and market considerations of countries around the world. These models include analysis tools for real-time economic sensitivity evaluations and assessing the economic viability of scheduled developments. Additionally, he has written a diverse array of routines and solutions, including an application to automate the conversion of PHDWin databases to an ARIES-compatible format for North American assets, regression analysis algorithms to model well performance data, and interfaces and reports that facilitate user data analyses.
Evans’ ongoing work includes a comprehensive database solution providing management and integration of reserves and revenue projections with an emphasis on generating published reports. This versatile setup incorporates a suite of features such as report table designers, query designers, text markup language, Excel modeling and interoperability, PHDWin integration, economic limitations, reserves allocations, and category and forecast arithmetic with built-in functions and logic designers. These features simplify the process of creating customizable comparisons and reports, significantly reduce the effort involved, and serve as a consolidated dataset for big data analysis.