Dr. Dario Grana

Selected Publications

• Grana D., Azevedo L., de Figueiredo L., Connolly P., and Mukerji T., Probabilistic inversion of seismic data for reservoir characterization, Geophysics, 1-47. 

• Grana D., Parsekian A., Flinchum B., Smeltz N., Callahan R., Li A., Hayes J., Carr B., Singha K., Riebe C., Holbrook S., 2022, Geostatistical rock physics inversion for predicting the spatial distribution of porosity and saturation in the critical zone, Mathematical Geosciences, 1-51.

• Callahan R., Riebe C., Sklar L., Pasquet S., Ferrier K., Hahm J., Taylor N., Grana D., Flinchum B., Hayes, J., and Holbrook S., 2022, Forest vulnerability to drought controlled by bedrock composition, Nature Geoscience, 1-25.

• Grana, D., de Figueiredo, L. and Mosegaard, K., 2022, Markov chain Monte Carlo for petrophysical inversion,Geophysics, 87(1), M13-M24.

• Grana D., 2022, Bayesian rock-physics inversion with Kumaraswamy prior models, Geophysics, 87(3), M87-M97. 

• Liu M., Grana D., and de Figueiredo L., 2022, Uncertainty quantification in stochastic inversion with model and data dimension reduction using variational autoencoder, Geophysics, 87 (2), M43-M58.

• Grana D., Mukerji T., and Doyen P. 2021, Seismic reservoir modeling: Theory, Examples, and Algorithms, Wiley.

• Grana D., 2021, Multivariate probabilistic rock physics model using Kumaraswamy distributions, Geophysics, 86 (5), 86(5), MR261-MR270.

• Grana D., and de Figueiredo L., 2021, SeReMpy: Seismic reservoir modeling python library, Geophysics, 86 (6), F61-F69.

• Grana D., Liu M., and Ayani M., 2021, Prediction of CO₂ saturation spatial distribution using geostatistical inversion of time-lapse geophysical data, IEEE Transactions on Geoscience and Remote Sensing, 59 (5), 3846-3856.

• de Figueiredo L., Schmitz T., Lunelli R., Roisenberg M., Freitas D., and Grana D., 2021, Direct Multivariate Simulation - A stepwise conditional transformation for multivariate geostatistical simulation, Computers & Geosciences, 147, 104659.

• Parsekian A., Grana D., Neves F., Pleasants M., Smeltz N., and Kelleners T., 2021, Hydro-geophysical comparison of hillslope critical zone architecture for different geologic substrates, Geophysics, 86 (3), WB29-WB49. 

• Talarico E., Leao W., and Grana D., 2020, Comparison of recursive neural network and Markov chain models in facies inversion, Mathematical Geosciences, 53 (3), 395-413.

• Callahan R., Riebe C., Pasquet S., Ferrier K., Grana D., Sklar L., Taylor N., Flinchum B., Hayes J., B. Carr B., Hartsough P., Green A., and Holbrook S., 2020, Subsurface weathering revealed in hillslope-integrated porosity distributions, Geophysical Research Letters, 47, 15.

• Ayani M., Liu M., and Grana D., 2020, Statistical rock physics inversion of elastic and electrical properties for CO2 sequestration studies, Geophysical Journal International, 223(1), 707–724.

• Ayani M., Liu M., and Grana D., 2020, Stochastic inversion method of time-lapse controlled source electromagnetic data for CO2 plume monitoring, International Journal of Greenhouse Gas Control, 100, 103098.

• Azevedo L., Grana D., and de Figueiredo L., 2020, Stochastic perturbation optimization for discrete-continuous inverse problems, Geophysics, 85(5).

• Liu M., and Grana D., 2020, Petrophysical characterization of deep saline aquifers for CO2 storage using ensemble smoother and deep convolutional autoencoder, Advances in Water Resources, 142, 103634.

• Grana D., 2020, Bayesian petroelastic inversion with multiple prior models, Geophysics, 85(5), M57-M71.  

• Talarico E., de Figueiredo L., and Grana D., 2020, Uncertainty quantification for seismic facies classification, Geophysics, 85(4), M43-M56. 

• Claes, N., Paige, G.B., Grana, D. and Parsekian, A.D., 2020, Parameterization of a hydrologic model with geophysical data to simulate observed subsurface return flow paths: Vadose Zone Journal, 19(1), 20024

• Grana D., and Azevedo L., 2019, Subsurface geostatistical modeling, Encyclopedia of Geology.

• de Figueiredo L., Grana D., and Le Ravalec M., 2019, Revisited formulation of FFT-moving average, Mathematical Geosciences, 1-16.

• Grana D., Azevedo L., and Liu M., 2019, A comparison of deep machine learning and Monte Carlo methods for facies classification from seismic data, Geophysics, 85(4), WA41-WA52.

• Liu M., and Grana D., 2019, Time-lapse seismic history matching with iterative ensemble smoother and deep convolutional autoencoder, Geophysics, 85(1), M15-M31.

• Grana D., de Figueiredo L., and Azevedo L., 2019, Uncertainty quantification in Bayesian inverse problems with model and data dimension reduction, Geophysics, 84(6), M15-M24.

• Liu M., and Grana D., 2019, Accelerating geostatistical seismic inversion using TensorFlow: A heterogeneous distributed deep learning framework, Computers and Geosciences, 124, 37-35.

• Lang X., and Grana D., 2019, Rock physics modeling and inversion for saturation and pressure changes in time-lapse studies, Geophysical Prospecting, 67 (7), 1912-1928.

• de Figueiredo, L.P., Grana, D., Roisenberg, M. and Rodrigues, B.B., 2019, Multimodal McMC method for non-linear petrophysical seismic inversion, Geophysics, 84 (5), M1-M13.

• de Figueiredo, L.P., Grana, D., Roisenberg, M. and Rodrigues, B.B., 2019., Gaussian Mixture McMC method for linear seismic inversion, Geophysics, 49 (4), 493-515.

• Azevedo L., Grana D., and Amaro C., 2019, Geostatistical rock physics AVA inversion, Geophysical Journal International, 216 (3), 1728–1739.

• Flinchum B., Holbrook S., Grana D., Parsekian A., Carr B., Hayes J., and Jiao J., 2018, Estimating the water holding capacity of the critical zone using near‐surface geophysics, Hydrological Processes, 32 (22), 3308-3326.

• Wang H., Alvarado V., McLaughlin F., Bagdonas D., Kaszuba J., Campbell E., and Grana D., 2018. Low‐field nuclear magnetic resonance characterization of carbonate and sandstone reservoirs from Rock Spring Uplift of Wyoming, Journal of Geophysical Research: Solid Earth, 123.

• de Figueiredo L., Grana D., Bordignon F., Santos M., Roisenberg M., and Rodrigues B., 2018, Joint Bayesian inversion based on rock-physics prior modeling for the estimation of spatially correlated reservoir properties, Geophysics, 83 (5), M49-M61.

• Grana D., 2018, Joint facies and reservoir properties inversion, Geophysics, 83 (3), M15-M24.

• Lang X., and Grana D., 2018, Bayesian linearized petrophysical AVO inversion, Geophysics, 83 (3), M1-M14.

• Liu M., and Grana D., 2018, Stochastic nonlinear inversion of seismic data for the estimation of petroelastic properties using the ensemble smoother and data re-parameterization, Geophysics, 83 (3), M25-M39.

• Fjeldstad T., and Grana D., 2018, Joint probabilistic petrophysics-seismic inversion based on Gaussian mixture and Markov chain prior models, Geophysics, 83 (1), R31-R42.

• Grana D., Fjeldstad T., and Omre H., 2017, Bayesian Gaussian mixture linear inversion for geophysical inverse problems, Mathematical Geosciences, 49 (4), 493-515.

• Grana D., Verma S., Pafeng J., Lang X., Sharma H., Wu W., McLaughlin F., Campbell E., Ng K., Alvarado V., Mallick S., and Kaszuba J., 2017 A rock physics and seismic reservoir characterization study of the Rock Spings Uplift, a CO2 sequestration site in Southwestern Wyoming, International Journal of Greenhouse Gas Control, 63, 296-309.

• de Figueiredo L., Grana D., Santos M., Figuereido W., Roisenberg M., and Neto G.S., 2017, Bayesian seismic inversion based on rock-physics prior modeling for the joint estimation of acoustic impedance, porosity and lithofacies, Journal of Computational Physics, 336, 128-142.

• Lang X., and Grana D., 2017, Geostatistical inversion of prestack seismic data for the joint estimation of facies and impedances using stochastic sampling from Gaussian mixture posterior distributions, Geophysics, 82 (4), M55-M65.

• Grana D., Lang X., Wu W., 2017, Statistical facies classification from multiple seismic attributes: comparison between Bayesian classification and Expectation-Maximization method and application in petrophysical inversion, Geophysical Prospecting, 65 (2), 544-562.

• Grana D., 2016, Bayesian linearized rock-physics inversion, Geophysics, 81 (6), D625-D641.

• Grana D., 2014, Probabilistic approach to rock physics modeling, Geophysics, 79 (4), D123-D143.

• Dvorkin J., Gutierrez M., and Grana D., 2014, Seismic reflection of rock properties, Cambridge University Press.

• Grana D., Mukerji T., Dvorkin J., and Mavko G., 2012, Stochastic inversion of facies from seismic data based on sequential simulations and probability perturbation method, Geophysics, 77 (4), M53-M72.

• Grana D., Pirrone M., and Mukerji T., 2012, Quantitative log interpretation and uncertainty propagation of petrophysical properties and facies classification from rock physics modeling and formation evaluation analysis, Geophysics, 77 (3), WA45–WA63.

• Grana D. and Della Rossa E., 2010, Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion, Geophysics 75 (3), O21-O37.

Research

I am a geophysicist with a background in mathematics and statistics. My research interests are: rock physics, seismic reservoir characterization, inverse problems, and geostatistics. These are the topics that are the current focus of my research:

Rock physics modeling in the critical zone,

Geophysical monitoring of CO2 sequestration,

Joint inversion of seismic and electromagnetic data,

Stochastic inversion methods for subsurface characterization.

Teaching

My teaching portfolio includes Quantitative Geoscience, Mathematical Methods for Geoscience, Exploration Geoscience, Diversity and Inclusion in Geoscience, and Rock Physics.

Student Opportunities

Students interested in working on one of the topics listed above are welcome to contact me at my email address.