M. Liu, J. Narciso, D. Grana, E. Van De Vijver, and L. Azevedo, 2023, Frequency-domain electromagnetic induction for the prediction of electrical conductivity and magnetic susceptibility using geostatistical inversion and randomized tensor decomposition, Geophysics, accepted for publication.
Q. Guo, C. Luo, and D. Grana, 2023, Bayesian linearized rock-physics AVO inversion for petrophysical and pore-geometry parameters in carbonate reservoirs, Geophysics, accepted for publication.
D. Grana, L. de Figueiredo, and K. Mosegaard, 2023, Markov chain Monte Carlo for seismic facies classification, Geophysics, 88(3), M131-M143.
M. Liu, D. Vashisth, D. Grana, and T. Mukerji, 2023, Joint inversion of geophysical data for geologic carbon sequestration monitoring: a differentiable physics-informed deep learning model, Journal of Geophysical Research: Solid Earth, 128(3), e2022JB025372.
Q. Hu, K. Innanen, and D. Grana, 2023, Feasibility of seismic time-lapse monitoring of CO2 with rock physics parameterized full waveform inversion, Geophysical International Journal, 233(1), 402-419.
R. Miele, L. Azevedo, D. Grana, L. Varella, and B. Barreto, 2023, Iterative geostatistical seismic inversion with rock physics constraints for permeability prediction, Geophysics, 88(2), M105-M117.
N. Ahmed, W. Weibull, and D. Grana, 2022, Frequency-dependent AVO inversion applied to physically based models for seismic attenuation, Geophysical International Journal, 233(1), 234-252.
D. Grana, B. Russell, and T. Mukerji, 2022, Petrophysical inversion based on f-s-r AVO linearization and canonical correlation analysis, Geophysics, 87 (6), 87: M247-M258.
D. Grana, L. Azevedo, L. de Figueiredo, P. Connolly, and T. Mukerji, 2022, Probabilistic inversion of seismic data for reservoir characterization: A review, Geophysics, 87 (5), M199-M216.
N. Ahmed, W. Weibull, and D. Grana, 2022, Constrained non-linear AVO Inversion based on the adjoint-state optimization, Computers & Geosciences, 168, 105214.
D. Grana, 2022, Bayesian rock physics inversion with Kumaraswamy prior models, Geophysics, 87 (3), M87-M97.
R. Feng, K. Mosegaard, D. Grana, and T. Mukerji, 2022, Application of Bayesian generative adversarial networks to geological facies modeling, Mathematical Geosciences, accepted for publication
M. Liu+, D. Grana, and T. Mukerji, 2022, Randomized tensor decomposition for large-scale data assimilation problems for carbon dioxide sequestration, Mathematical Geosciences, 1-25.
D. Grana, L. de Figueiredo, and K. Mosegaard, 2022, Markov chain Monte Carlo for petrophysical inversion, Geophysics, 87 (1), M13-M24.
M. Liu+, D. Grana, and L. de Figueiredo, 2022, Uncertainty quantification in stochastic inversion with model and data dimension reduction using variational autoencoder, Geophysics, 87 (2), M43-M58.
K. Li+, X. Ying, Z. Zong, and D. Grana, 2022, Estimation of porosity, fluid bulk modulus, and stiff-pore volume fraction using a multi-trace Bayesian AVO petrophysics inversion in multi-porosity reservoirs, Geophysics, 87 (1), M25-M41.
D. Grana, 2021, Multivariate probabilistic rock physics model using Kumaraswamy distributions, Geophysics, 86 (5), 86(5), MR261-MR270.
D. Grana, and L. de Figueiredo, 2021, SeReMpy: Seismic reservoir modeling python library, Geophysics, 86 (6), F61-F69.
F. Turco, L. Azevedo, D. Grana, A. Gorman, G. Crutchley, 2021, Characterization of gas hydrate systems of the Hikurangi margin (New Zealand) thought geostatistical seismic and petrophysical, Geophysics, 86 (6), R825-R838.
M. Conjard+, and D. Grana, 2021, Ensemble-based seismic and production data assimilation using selection Kalman model, Mathematical Geosciences, 53 (7), 1445-1468.
(Book) D. Grana, T. Mukerji, and P. Doyen, 2021, Seismic reservoir modeling, Wiley.
H. Wang, V. Alvarado, D. Bagdonas, F. McLaughlin, J. Kaszuba, D. Grana, E. Campbell, and K. Ng, 2021, Effect of CO2-brine-rock reactions on pore architecture and permeability in dolostone: Implications for CO2 storage and EOR: International Journal of Greenhouse Gas Control, 107, 103283.
R. Feng, N. Balling, and D. Grana, 2021, Imputation of missing well log data by random forest and uncertainty analysis, Computers & Geosciences, 152, 104763.
M. Loe+, D. Grana, and H. Tjelmeland, 2021, Geophysics-based fluid-facies predictions using ensemble updating of binary state, Mathematical Geosciences, 53 (3), 325-347.
D. Grana, M. Liu+, and M. Ayani+, 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.
L. de Figueiredo, T. Schmitz, R. Lunelli, M. Roisenberg, D. Freitas, and D. Grana, 2021, Direct Multivariate Simulation - A stepwise conditional transformation for multivariate geostatistical simulation, Computers & Geosciences, 147, 104659.
R. Feng, D. Grana, N. Balling, and T.M. Hansen, 2021, Bayesian convolutional neural networks for seismic facies classification, IEEE Transactions on Geoscience and Remote Sensing, accepted for publication.
R. Feng, D. Grana, and N. Balling, 2020, Variational inference in Bayesian neural network for well log prediction, Geophysics, 86 (3), M91-M99.
R. Feng, D. Grana, and N. Balling, 2020, Uncertainty quantification in fault detection using convolutional neural networks, Geophysics, 86 (3), M41-M48.
E. Talarico, W. Leao, and D. Grana, 2020, Comparison of recursive neural network and Markov chain models in facies inversion, Mathematical Geosciences, 53 (3), 395-413.
O. Forberg+, and D.Grana, 2020, Bayesian inversion of time-lapse seismic AVO data for multimodal reservoir properties, IEEE Transactions on Geoscience and Remote Sensing, accepted for publication.
G. Ghon+, D. Grana, E.C. Rankey, G.T. Baechle, F. Bleibinhaus, X. Lang, L. de Figueiredo, and M.C Poppelreiter, 2020, Bayesian facies inversion on a partially dolomitized isolated carbonate platform. A case study from Central Luconia province, Malaysia. Geophysics, 86 (2), 1MA-W19.
M. Ayani+, and D. Grana, 2020, Statistical rock physics inversion of elastic and electrical properties for CO2 sequestration studies, Geophysical Journal International, 223 (1), 707-724.
M. Ayani+, M. Liu+, and D. Grana, 2020, Stochastic inversion method of time-lapse controlled source electromagnetic data for CO2 plume monitoring, International Journal of Greenhouse Gas Control, 100, 103098.
L. Azevedo, D. Grana, and L. de Figueiredo+, 2020, Stochastic Perturbation Optimization for discrete-continuous inverse problems, Geophysics, 85 (5), M73-M83.
R. Feng, T. Hansen, D. Grana, and N. Balling, 2020, An unsupervised deep-learning method for porosity estimation based on post-stack seismic data, Geophysics, 85 (6), M97–M105.
M. Liu+, and D. Grana, 2020, Petrophysical characterization of deep saline aquifers for CO2 storage using ensemble smoother and deep convolutional autoencoder, Advances in Water Resources, 142, 103634.
D. Grana, 2020, Bayesian petroelastic inversion with multiple prior models, Geophysics, 85 (5), 57–M71.
E. Talarico, L. de Figueiredo, and D. Grana, 2020, Uncertainty quantification for seismic facies classification, Geophysics, 85 (4), M43–M56.
R. Feng, N. Balling, and D. Grana, 2020, Lithofacies classification of a geothermal reservoir in Denmark and its facies-dependent porosity estimation from seismic inversion, Geothermics, 87, 101854.
L. de Figueiredo, D. Grana, and M. Le Ravalec, 2019, Revisited formulation of FFT-moving average, Mathematical Geosciences, 52, 801–816.
D. Grana, L. Azevedo, and M. Liu+, 2019, A comparison of deep machine learning and Monte Carlo methods for facies classification from seismic data, Geophysics, 85 (4), WA41-WA52.
R. Lorenzen, T. Bhakta, D. Grana, X. Luo, R. Valestrand, and G. Nevdal, 2019, Simultaneous assimilation of production and seismic data: application to the Norne field, Computational Geosciences, 24, 907–920.
M. Liu+, and D. Grana, 2019, Time-lapse seismic history matching with iterative ensemble smoother and deep convolutional autoencoder, Geophysics, 85 (1), M15-M31.
D. Grana, L. de Figueiredo, and L. Azevedo, 2019, Uncertainty quantification in Bayesian inverse problems with model and data dimension reduction, Geophysics, 84 (6), M15-M24.
M. Liu+, and D. Grana, 2019, Accelerating geostatistical seismic inversion using TensorFlow: A heterogeneous distributed deep learning framework, Computers & Geosciences, 124, 37-35.
X. Lang+, and D. Grana, 2019, Rock physics modeling and inversion for saturation and pressure changes in time-lapse studies, Geophysical Prospecting, 67 (7), 1912-1928.
L. de Figueiredo+, D. Grana, M. Roisenberg, and B. Rodrigues, 2019, Multimodal McMC method for non-linear petrophysical seismic inversion, Geophysics, 84 (5), M1-M13.
L. de Figueiredo+, D. Grana, M. Roisenberg, and B. Rodrigues, 2019, Gaussian Mixture McMC method for linear seismic inversion, Geophysics, 49 (4), 493-515.
