Theses
Main content start
2023
- Kashefi, K. (2023). Deep learning algorithms for computational mechanics on irregular geometries [PhD]. https://searchworks.stanford.edu/view/14732781
- Wang, L. (2023). Integrating data and models for sustainable decision-making in hydrology [PhD]. https://searchworks.stanford.edu/view/14641244
2022
- Miltenberger, A. (2022). A measure-theoretic approach to Bayesian hypothesis testing and inversion with geophysical data [PhD]. https://searchworks.stanford.edu/view/14233991
2021
- Yang, L. (2021). Quantifying and visualizing uncertainty of 3D geological structures with implicit methods [PhD]. https://stacks.stanford.edu/file/druid:zy244dn1573/Liang_Yang_PhD_Dissertation_Uncertainty_Quantification-augmented.pdf
- Petrov, S. (2021). Seismic image segmentation with deep learning [MS]. https://acrobat.adobe.com/link/review?uri=urn:aaid:scds:US:2d891111-c043-366e-b0d3-80b4dd40334b
- Athens, N. (2021). Stochastic inversion of gravity data in fault-controlled geothermal systems [PhD]. https://stacks.stanford.edu/file/druid:wr109zn4354/Athens_Thesis-augmented.pdf
2020
- Pollack, A. (2020). Quantifying Geological Uncertainty and Optimizing Technoeconomic Decisions for Geothermal Reservoirs [PhD]. https://stacks.stanford.edu/file/druid:nm547ws8252/Dissertation_Ahinoam_Pollack-augmented.pdf
- Pradhan, A. (2020). Statistical learning and inference of subsurface properties under complex geological uncertainty with seismic data [PhD]. https://stacks.stanford.edu/file/druid:sg756xs1514/Dissertation_AnshumanPradhan-augmented.pdf
2019
- Nesvold, E. (2019). Building informative priors for the subsurface with generative adversarial networks and graphs [PhD]. https://searchworks.stanford.edu/view/13423377
- Muradov, R. (2019). Inference of Sub-Resolution Stacking Patterns from Seismic Data in Spatially Coupled Models [MS]. https://searchworks.stanford.edu/view/km001pf4033
- Al Ibrahim, M. (2019). Petroleum System Modeling of Heterogeneous Organic-Rich Mudrocks [PhD]. https://searchworks.stanford.edu/view/13250212
- Park, J. (2019). Uncertainty quantification and sensitivity analysis of geoscientific predictions with data-driven approaches [PhD]. https://searchworks.stanford.edu/view/13250154
2018
- Mendes, J. (2018). Morphdynamic Analysis and Statistical Synthesis of Geomorphic Data [PhD]. https://searchworks.stanford.edu/view/12746435
- Dutta, G. (2018). Value of Information Analysis for Time-Lapse Seismic Data in Reservoir Development [PhD]. https://searchworks.stanford.edu/view/12742067
2017
- Li, L. (2017). A Bayesian Approach to Causal and Evidential Analysis for Uncertainty Quantification throughout the Reservoir Forecasting Process [PhD]. https://searchworks.stanford.edu/view/12137330
- Aydin, O. (2017). A Bayesian Framework for Quantifying Fault Network Uncertainty Using a Marked Point Process Model [PhD]. https://searchworks.stanford.edu/view/11950552
- Grujić, O. (2017). A Subsurface Modeling with Functional Data [PhD]. https://searchworks.stanford.edu/view/12212152
- Yang, G. (2017). Holistic Strategies for Prediction Uncertainty Quantification of Contaminant Transport and Reservoir Production in Field Cases [PhD]. https://searchworks.stanford.edu/view/12123097
2016
- Tong, Y. (2016). Basin and Petroleum System Modeling with Uncertainty Quantification: a Case Study on the Piceance Basin, Colorado [PhD]. https://pangea.stanford.edu/ERE/db/pereports/record_detail.php?filename=Tong_Yao2016.pdf
- Luebbert, L. (2016). Quantitative Analysis of Dissimilarities Between Different Methods of Seismic Inversion to Facies Realizations [MS]. https://pangea.stanford.edu/ERE/db/pereports/record_detail.php?filename=Acquaviva2016.pdf
- Shin, Y. (2016). Reservoir Modeling with Multiple Geological Scenarios for Deformation of Reservoir Structure and Evolution of Reservoir Properties [PhD]. https://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2016_PhD_Yongduk_Shin_Thesis.pdf
- Xue, C. (2016). The Application of OPTSPACE Algorithm and Comparison with LMAFIT Algorithm in Three dimensional Seismic Data Reconstruction via Lowrank Matrix Completion [MS]. https://pangea.stanford.edu/ERE/db/pereports/record_detail.php?filename=Xue_Chen2016.pdf
2015
- Lee, J. (2015). Joint Integration of Time-Lapse Seismic, Electromagnetic, and Production Data for Reservoir Monitoring and Management [PhD]. https://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2015_PhD_Jaehoon%20Lee_Thesis.pdf
- Satija, A. (2015). Reservoir Forecasting Based on Statistical Functional Analysis of Data and Prediction Variables [PhD]. https://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2015_PhD_Addy_Satija_Thesis.pdf
- Wang, Y. (2015). Rule-Based Reservoir Modeling by Integration of Multiple Information Sources: Learning Time-Varying Geologic Processes [MS]. https://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2015_MS_Yinan_Wang_Thesis.pdf
2014
- Xu, S. (2014). Integration of geomorphic experiment data in surface-based modeling: from characterization to simulation [PhD]. https://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2014_PhD_Siyao_Xu_Thesis.pdf
- Jeong, C. (2014). Quantitative Reservoir Characterization Integrating Seismic Data and Geological Scenario Uncertainty [PhD]. https://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2014_PhD_Cheokyun_Jeong_Thesis.pdf
2013
- Suman, A. (2013). Joint inversion of production and time-lapse seismic data: application to Norne field [PhD]. https://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2013_PhD_Amit_Suman_Thesis.pdf
2012
2011
- Bertoncello, A. (2011). Conditioning surface-based models to well and thickness data [PhD]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2010_PhD_Trainor-Guitton.pdf
- Park, K. (2011). Modeling Uncertainty in Metric Space [PhD]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2011_PhD_KPark.pdf
- Honarkhah, M. (2011). Stochastic simulation of patterns using distance-based pattern modeling [PhD]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2011_PhD_Mehrdad_Honarkhah.pdf
2010
- Wang, J. (2010). A Metropolis sampling method to assess uncertainty of seismic impedance inverted from seismic amplitude data [MS]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2010_MS_JingWang.pdf
- Haugen, M. (2010). Exploring direct sampling and iterative spatial resampling in history matching [MS]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2010_MS_Haugen.pdf
- Jia, B. (2010). Linking geostatistics with basin and petroleum system modeling: Assessment of spatial uncertainties [MS]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2010_MS_BinJia.pdf
- Trainor-Guitton, W. (2010). On the value of information for spatial problems in the Earth sciences [PhD]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2010_PhD_Trainor-Guitton.pdf
- Kuralkhanov, D. (2010). Study of pattern correlation between time lapse seismic data and saturation changes [MS]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2010-2019/2010_MS_Kuralkhanov.pdf
2009
- Leiva, A. (2009). Construction of hybrid geostatistical models combining surface based methods with object-based simulation: use of flow direction and drainage area [MS]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2000-2009/2009_MS_Leiva.pdf
- Suman, A. (2009). Uncertainties in rock pore compressibility and effects on seismic history matching [MS]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2000-2009/2009_MS_Suman.pdf
2008
- Polyakova, E. (2008). A general theory for evaluating joint data interaction when combining diverse data sources [PhD]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2000-2009/2008_PhD_Polyakova.pdf
- Fadaei, S. (2008). Streamline assisted history matching of naturally fractured reservoirs using the probability perturbation method [MS]. http://pangea.stanford.edu/departments/ere/dropbox/scrf/documents/Theses/SCRF-Theses/2000-2009/2008_MS_Fadaei.pdf