Eugene Morgan's primary research focuses on developing Bayesian inversion strategies for extracting information from seismic survey data. In particular, Morgan investigates the use of seismic attenuation in these inversion strategies because intrinsic attenuation is theoretically linked more strongly to the hydraulic properties of a formation (i.e., porosity, permeability, saturation) than velocity. The non-linearity and multimodality of the rock physics equations that model attenuation warrant stochastic inversion techniques, and a Bayesian framework allows a convenient expression of prior geologic knowledge, as well as the predictions, in a probabilistic way. These methods can achieve a better characterization of reservoirs in the exploration phase.
Morgan is also interested in solving problems in the oil and gas industry using statistics, BIG data analytics, and machine learning. A large focus is on well-production data, where Morgan's group uses time series statistics, geostatistics, and pattern recognition techniques to improve forecasting and operational decision support.
- Participating Member, National Risk Assessment Partnership 2018–2022
- Member, Organizing Committee – IAMG Conference 2019
- Guest Editor, Mathematical Geosciences, IAMG 2019 Special Issue
- Scholarship Chair, SPE Pittsburgh Section 2014–2019
- Faculty Advisor, Penn State SPE Student Chapter 2014–2018
- Joon, S, Dawuda, I, Morgan, E, and Srinivasan, S (2022). Rock Physics-Based Data Assimilation of Integrated Continuous Active-Source Seismic and Pressure Monitoring Data during GCS. SPE Journal SPE-209585-PA (in press; posted 28 February 2022). doi:10.2118/209585-PA
- Udegbe, E, Morgan, EC, and Srinivasan, S (2019). Big Data Analytics for Seismic Fracture Identification, Using Amplitude-Based Statistics.Computational Geosciences: 11-15. doi:10.1007/s10596-019-09890-z
- Xi, Z, and Morgan, EC (2019). Combining Decline Curve Analysis and Geostatistics to Forecast Gas Production in the Marcellus Shale. SPE Reservoir Evaluation & Engineering -Formation Evaluation. doi:10.2118/197055-PA
- Udegbe, E, Morgan, EC, and Srinivasan, S (2019). Big Data Analytics for Production Data Classification using Feature Detection: Application to Restimulation Candidate Selection. SPE Reservoir Evaluation & Engineering -Formation Evaluation. doi:10.2118/187328-PA
- Morgan, EC, Vanneste, M, Lecomte, I, Baise, LG, Longva, O, and McAdoo, BG (2012). Estimation of free gas saturation from seismic reflection surveys by the genetic algorithm inversion of a P-wave attenuation model. Geophysics, 77(4): R175-R187. doi:10.1190/geo2011-0291.1
- Thompson, EM, Baise, LG, Kayen, RE, Morgan, EC, and Kaklamanos, J (2011). Integrated multiscale site response mapping. Bulletin of the Seismological Society of America, 101(3): 1081-1100. doi:10.1785/0120100211
- Morgan, EC, Lackner, M, Vogel, RM, and Baise, LG (2011). Probability distributions for offshore wind speeds. Energy Conversion and Management, 52(1): 15-26. doi:10.1016/j.enconman.2010.06.015
- Morgan, EC, McAdoo, BG, and Baise, LG (2008). Quantifying geomorphology associated with large subduction zone earthquakes. Basin Research, 20(4): 531-542. doi:10.1111/j.1365-2117.2008.00368.x
- Hoffmann, G, Silver, E, Day, S, Morgan, EC, Driscoll, NW, and Orange, D (2008). Sediment waves in the Bismarck volcanic arc, Papua New Guinea. Special Paper Geological Society of America, 436: 91-126. doi:10.1130/2008.2436(05)