The SPE Student Paper Contest is a global competition that highlights students’ individual technical expertise through research presentations. Held at the undergraduate, master’s, and PhD levels, regional contests take place across 14 SPE regions, with top winners advancing to the International Student Paper Contest during SPE’s Annual Technical Conference and Exhibition. They also have the opportunity to publish their work in OnePetro.
Winners of the 2025 SPE Student Paper Contest include
Undergraduate
1st Place: Salman Alrasheed, King Fahd University of Petroleum and Minerals
Paper: Time-Dependent Effects of Fracturing Fluid Retention on the Geomechanical and Petrophysical Properties of Tight Sandstone
2nd Place: Alberto Christian Alvarez, Texas A&M University
Paper: Wavelet-Based Detection of Boundary-Dominated Flow Improves Forecasting in Unconventional Oil and Gas Reservoirs
3rd Place: Lindsey Elyse Kubsch, University of Oklahoma
Paper: Using Nuclear Magnetic Resonance (NMR) Spectroscopy to Determine Effective Hydrogen Gas Diffusivity in Shale
Master’s
1st Place: Azza Khalifa Abdullah Mundher Al Mandhri, Sultan Qaboos University
Paper: Effect of Potential Determining Ions Concentration and Temperature on Wettability Alteration of Dolomite
2nd Place: Sunghyun Ko, University of Texas at Austin
Paper: Aqueous Solution of 3-Pentanone for Enhanced Oil Recovery in Texas Shale Reservoirs
3rd Place: Malek Marwan Abdo Saleh, Technical University of Clausthal
Paper: Wettability of Shales at Geological Carbon Dioxide Storage Conditions: A Comparative Study of Results Obtained from Sessile and Captive Bubble Methods
PhD
1st Place: Issac Jayachandran, Texas A&M University at Qatar
Paper: From Classic Image Processing to State-of-the-art Deep Learning: Benchmarking Algorithms using SEM Petrography of Microtextures using Distortion Simulation
2nd Place: Leila Karabayanova, Texas A&M University
Paper: Wet In-Situ Combustion Substantially Increases Oil Recovery in Light Oil Shale Reservoirs
3rd Place: Zhen Qin, University of Southern California
Paper: Adaptive Multi-Resolution Inversion of Geologic CO2 Storage Using Deep Learning