Leo Ruiz

Research Interests

• Reservoir Engineering of conventional and unconventional oil and gas reservoirs.
• Rate-transient analysis (RTA)
• Decline-curve analysis (DCA).
• Geostatistics, classic and Bayesian statistics for uncertainty quantification of subsurface problems.
• Subsurface hydrogen and CO₂ storage.

Education

• Ph.D. (2022): Petroleum Engineering, The University of Texas at Austin
• MS. (2018): Petroleum Engineering, The University of Texas at Austin
• MS. (2016): Oil and Gas Engineering, University of Buenos Aires, Argentina
• Engineering Diploma (2010): Chemical Engineering, University of Buenos Aires, Argentina

Selected Publications

1. Ruiz Maraggi, L. M and Moscardelli, L. G. 2024. Hydrogen Storage Potential of Salt Domes in the Gulf Coast of the United States. Journal of Energy Storage 82, 110585 https://doi.org/10.1016/j.est.2024.110585 
2. Ruiz Maraggi, L. M., Walsh, M. P., and Lake, L. W. 2023. A New Approach to Apply Decline-Curve Analysis for Tight-Oil Reservoirs Producing Under Variable Pressure Conditions. SPE Journal, In Press. SPE-218016-PA. https://doi.org/10.2118/218016-PA 
3. Male, F., Marder, M. P., Ruiz Maraggi, L. M., Lake, L. W. 2023. Bluebonnet: Scaling solutions for production analysis from unconventional oil and gas wells. Journal of Open Source Software 8 (88): 5255. https://doi.org/10.21105/joss.05255 
4. Ruiz Maraggi, L. M and Moscardelli, L. G. 2023. Modeling hydrogen storage capacities, injection and withdrawal cycles in salt caverns: Introducing the GeoH₂ salt storage and cycling app. International Journal of Hydrogen Energy 48 (69): 26921-26936. https://doi.org/10.1016/j.ijhydene.2023.03.293
5. Ruiz Maraggi, L. M., Lake, L. W., and Walsh, M. P. 2023. Limitations of Rate Normalization and Material Balance Time in Rate-Transient Analysis of Unconventional Reservoirs. Geoenergy Science and Engineering 227 211844. https://doi.org/10.1016/j.geoen.2023.211844 
6. Ruiz Maraggi, L. M., Lake, L. W., and Walsh, M. P. 2022. Rate-Pseudopressure Deconvolution Enhances Rate-Time Models Production History Matches and Forecasts of Shale Gas Wells. SPE Res Eval & Eng 25 (04): 684–703. SPE-208967-PA. https://doi.org/10.2118/208967-PA
7. Ruiz Maraggi, L. M., Lake, L. W., and Walsh, M. P. 2022. Using Bayesian Leave-One-Out and Leave-Future-Out Cross-Validation to Evaluate the Performance of Rate-Time Models to Forecast Production of Tight-Oil Wells. SPE Res Eval & Eng 25 (04): 730–750. SPE- 209234-PA. https://doi.org/10.2118/209234-PA