HR job title
- Professor and Associate Department Head
- Contact Info
- 1 979 862 4578
Gildin, Eduardo Professor
Positions
- Professor, Petroleum Engineering, College of Engineering
- Faculty Affiliate, Energy Institute, Texas A&M Engineering Experiment Station (TEES)
I have research interests in reservoir modeling and optimization for the oil and gas industry using concepts from mathematical modeling using discretization of pde's (finite difference, finite element methods, and finite volumes), systems and control theory and model reduction of large scale dynamical systems. In particular, I am interested in closed-loop reservoir management.
- Overview
- Publications
- Research
- Teaching
- Works By Students
- Background
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Overview
Publications
selected publications
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academic article
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DallAqua, M. J., Coutinho, E., Gildin, E., Guo, Z., Zalavadia, H., & Sankaran, S.
(2023).
Guided Deep Learning Manifold Linearization of Porous Media Flow Equations. SPE JOURNAL.
1-24.
-
Jordanou, J. P., Antonelo, E. A., Camponogara, E., & Gildin, E.
(2023).
Investigation of Proper Orthogonal Decomposition for Echo State Networks. 548, 126395-126395.
-
Gurjao, K., Gildin, E., Gibson, R., & Everett, M.
(2022).
Investigation of Strain Fields Generated by Hydraulic Fracturing with Analytical and Numerical Modeling of Fiber Optic Response. 25(2), 367-379.
-
Khaled, M. S., Chen, M., Losoya, E. Z., Rodriguez, L. A., Gildin, E., & Skelton, R. E.
(2022).
Tensegrity laboratory drilling rig for earth and space drilling, mining, and exploration. International Journal of Solids and Structures.
252, 111785-111785.
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Khaled, M., Srinivasan, S., Toure, A., Chen, M., Kincaid, E., Lopaz, T., ... Moridis, G.
(2021).
DREAMS: Drilling and Extraction Automated System. abs/2106.05874.
-
Brankovic, M., Gildin, E., Gibson, R. L., & Everett, M. E.
(2021).
A Machine Learning-Based Seismic Data Compression and Interpretation Using a Novel Shifted-Matrix Decomposition Algorithm. Applied Sciences (Switzerland).
11(11), 4874-4874.
-
Coutinho, E., Dall'Aqua, M., & Gildin, E.
(2021).
Physics-Aware Deep-Learning-Based Proxy Reservoir Simulation Model Equipped With State and Well Output Prediction. Frontiers in Applied Mathematics and Statistics.
7, 651178.
-
Zalavadia, H., & Gildin, E.
(2021).
Two-Step Predict and Correct Non-Intrusive Parametric Model Order Reduction for Changing Well Locations Using a Machine Learning Framework. Energies.
14(6), 1765-1765.
-
Cheung, S. W., Chung, E. T., Efendiev, Y., Gildin, E., Wang, Y., & Zhang, J.
(2020).
Deep global model reduction learning in porous media flow simulation. 24(1), 261-274.
-
Zalavadia, H., & Gildin, E.
(2020).
Non-Intrusive Parametric Model Order Reduction with Error Correction Modeling for Changing Well Locations Using a Machine Learning Framework. abs%2F2001.05061.
-
de Holanda, R. W., Gildin, E., & Valko, P. P.
(2019).
Probabilistically Mapping Well Performance in Unconventional Reservoirs with a Physics-Based Decline-Curve Model. SPE Reservoir Evaluation and Engineering.
22(4), 1527-1550.
-
Tan, X., Gildin, E., Florez, H., Trehan, S., Yang, Y., & Hoda, N.
(2019).
Trajectory-based DEIM (TDEIM) model reduction applied to reservoir simulation. 23(1), 35-53.
-
Bao, A., Gildin, E., Narasingam, A., & Kwon, J. S.
(2019).
Data-Driven Model Reduction for Coupled Flow and Geomechanics Based on DMD Methods. Fluids.
4(3), 138-138.
-
de Holanda, R. W., Gildin, E., & Valk, P. P.
(2019).
Probabilistically Mapping Well Performance in Unconventional Reservoirs with a Physics-Based Decline-Curve Model. SPE Reservoir Evaluation and Engineering.
22(04), 1527-1550.
-
de Holanda, R. W., Gildin, E., & Valk, P. P.
(2018).
Combining Physics, Statistics, and Heuristics in the Decline-Curve Analysis of Large Data Sets In Unconventional Reservoirs. SPE Reservoir Evaluation and Engineering.
21(03), 683-702.
-
Cheung, S. W., Chung, E. T., Efendiev, Y., Gildin, E., & Wang, Y.
(2018).
Deep Global Model Reduction Learning
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Plaksina, T., & Gildin, E.
(2018).
Applied method for production design optimization under geologic and economic uncertainties in shale gas reservoirs. 38(2), 67-82.
-
de Holanda, R. W., Gildin, E., Jensen, J. L., Lake, L. W., & Kabir, C. S.
(2018).
A State-of-the-Art Literature Review on Capacitance Resistance Models for Reservoir Characterization and Performance Forecasting. Energies.
11(12), 3368-3368.
-
de Holanda, R. W., Gildin, E., & Jensen, J. L.
(2018).
A generalized framework for Capacitance Resistance Models and a comparison with streamline allocation factors. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING.
162, 260-282.
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De Holanda, R. W., Gildin, E., & Valk, P. P.
(2018).
Combining physics, statistics, and heuristics in the decline-curve analysis of large data sets in unconventional reservoirs. SPE Reservoir Evaluation and Engineering.
21(3), 683-702.
-
Beykal, B., Boukouvala, F., Floudas, C. A., Sorek, N., Zalavadia, H., & Gildin, E.
(2018).
Global optimization of grey-box computational systems using surrogate functions and application to highly constrained oil-field operations. Computers and Chemical Engineering.
114, 99-110.
-
Redick, B. S., & Gildin, E.
(2018).
Improved Surface-Subsurface Coupled Reservoir Simulation using Automatic PID Control. IFAC-PapersOnLine.
51(8), 82-87.
-
Losoya, E. Z., Gildin, E., & Noynaert, S. F.
(2018).
Real-time Rate of Penetration Optimization of an Autonomous Lab-Scale Rig using a Scheduled-Gain PID Controller and Mechanical Specific Energy. IFAC-PapersOnLine.
51(8), 56-61.
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Sorek, N., Gildin, E., Boukouvala, F., Beykal, B., & Floudas, C. A.
(2017).
Dimensionality reduction for production optimization using polynomial approximations. 21(2), 247-266.
-
Madiebo, K. I., Nasrabadi, H., & Gildin, E.
(2017).
LATTICE BOLTZMANN SIMULATION OF APPARENT PERMEABILITY FOR GAS FLOW IN NANOCHANNELS. 20(12), 1059-1070.
-
Plaksina, T., & Gildin, E.
(2017).
Rigorous Integrated Evolutionary Workflow for Optimal Exploitation of Unconventional Gas Assets. International Journal of Energy Optimization and Engineering.
6(1), 101-122.
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Yang, Y., Ghasemi, M., Gildin, E., Efendiev, Y., & Calo, V.
(2016).
Fast Multiscale Reservoir Simulations With POD-DEIM Model Reduction. SPE JOURNAL.
21(6), 2141-2154.
-
Benamram, Z., Tarakanov, A., Nasrabadi, H., & Gildin, E.
(2016).
Field-wide flow simulation in fractured porous media within lattice Boltzmann framework. Advances in Water Resources.
96, 170-179.
-
Ghasemi, M., & Gildin, E.
(2016).
Localized model order reduction in porous media flow simulation. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING.
145, 689-703.
-
Lozovskiy, A., Farthing, M., Kees, C., & Gildin, E.
(2016).
POD-based model reduction for stabilized finite element approximations of shallow water flows. Journal of Computational and Applied Mathematics.
302, 50-70.
-
Afra, S., & Gildin, E.
(2016).
Tensor based geology preserving reservoir parameterization with Higher Order Singular Value Decomposition (HOSVD). Computers and Geosciences.
94, 110-120.
-
Efendiev, Y., Gildin, E., & Yang, Y.
(2016).
Online Adaptive Local-Global Model Reduction for Flows in Heterogeneous Porous Media. Computation.
4(2), 22-22.
-
Vishnumolakala, N., Gildin, E., & Noynaert, S.
(2015).
A Simulation Environment for Automatic Managed Pressure Drilling Control. IFAC-PapersOnLine.
48(6), 128-133.
-
Ma, X., Gildin, E., & Plaksina, T.
(2015).
Efficient optimization framework for integrated placement of horizontal wells and hydraulic fracture stages in unconventional gas reservoirs. Journal of Unconventional Oil and Gas Resources.
9, 1-17.
-
Plaksina, T., & Gildin, E.
(2015).
Practical handling of multiple objectives using evolutionary strategy for optimal placement of hydraulic fracture stages in unconventional gas reservoirs. Journal of Natural Gas Science and Engineering.
27, 443-451.
-
Lerlertpakdee, P., Jafarpour, B., & Gildin, E.
(2014).
Efficient Production Optimization With Flow-Network Models. 19(6), 1083-1095.
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Fuentes-Cruz, G., Gildin, E., & Valko, P. P.
(2014).
On the analysis of production data: Practical approaches for hydraulically fractured wells in unconventional reservoirs. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING.
119, 54-68.
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Presho, M., Protasov, A., & Gildin, E.
(2014).
Local-global model reduction of parameter-dependent, single-phase flow models via balanced truncation. Journal of Computational and Applied Mathematics.
271, 163-179.
-
Efendiev, Y., Galvis, J., & Gildin, E.
(2012).
Local-global multiscale model reduction for flows in high-contrast heterogeneous media. Journal of Computational Physics.
231(24), 8100-8113.
-
Gildin, E., Antoulas, A. C., Sorensen, D., & Bishop, R. H.
(2009).
Model and controller reduction applied to structural control using passivity theory. 16(3), 319-334.
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Zhang, J., Zhang, R., Ataceri, I., Sarmah, A., Schechter, D., & Gildin, E.
Enhancing Oil Recovery in Eagle Ford Shale: A Multiscale Simulation Study of Surfactant Huff n Puff Methodology. SPE JOURNAL.
1-14.
-
Chen, J., Gildin, E., & Kompantsev, G.
Optimization of Pressure Management Strategies for Geological CO2 Sequestration Using Surrogate Model-based Reinforcement Learning. abs/2403.07360.
-
DallAqua, M. J., Coutinho, E., Gildin, E., Guo, Z., Zalavadia, H., & Sankaran, S.
(2023).
Guided Deep Learning Manifold Linearization of Porous Media Flow Equations. SPE JOURNAL.
1-24.
-
chapter
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Florez, H., Gildin, E., & Morkos, P.
(2022).
Model-Order Reduction for Coupled Flow and Linear Thermal-Poroplasticity with Applications to Unconventional Reservoirs. Realization and Model Reduction of Dynamical Systems.
(pp. 387-407).
Springer Nature.
-
Kheriji, W., Efendiev, Y., Calo, V. M., & Gildin, E.
(2017).
Model Reduction for Coupled Near-Well and Reservoir Models Using Multiple Space-Time Discretizations. MODEL REDUCTION OF PARAMETRIZED SYSTEMS.
(pp. 471-490).
Springer Nature.
-
Florez, H., Gildin, E., & Morkos, P.
(2022).
Model-Order Reduction for Coupled Flow and Linear Thermal-Poroplasticity with Applications to Unconventional Reservoirs. Realization and Model Reduction of Dynamical Systems.
(pp. 387-407).
Springer Nature.
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conference paper
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Rodriguez Castelblanco, A. X., Gildin, E., Cabrales, S. A., & Medaglia, A. L.
(2023).
A Novel Decision-Making Framework for Waterflooding Optimization using Long and Short-Term Memory Models and Metaheuristics
-
Dall'Aqua, M. J., Coutinho, E., Gildin, E., Guo, Z., Zalavadia, H., & Sankaran, S.
(2023).
Input-Output Invariant Fast Proxy Models for Production Optimization
-
Dall'Aqua, M. J., Coutinho, E., Gildin, E., Guo, Z., Zalavadia, H., & Sankaran, S.
(2023).
Guided Deep Learning Manifold Linearization of Porous Media Flow Equations
-
Ramos Gurjao, K. G., Gildin, E., Gibson, R., & Everett, M.
(2022).
Estimation of Far-Field Fiber Optics Distributed Acoustic Sensing DAS Response Using Spatio-Temporal Machine Learning Schemes and Improvement of Hydraulic Fracture Geometric Characterization
-
Shor, R. J., Kandala, S. S., Gildin, E., Noynaert, S. F., Losoya, E. Z., Kesireddy, V., ... Pastusek, P. E.
(2022).
Progress Toward an Open-Source Drilling Community: Contributing and Curating Models
-
de Holanda, R. W., & Gildin, E.
(2021).
The Windowing Algorithm: Dimensionality Reduction in Grey-Box System Identification of Reservoir Network Models. 1123-1128.
-
J. R. Coutinho, E., J. Dall'Aqua, M., & Gildin, E.
(2021).
Physics-Aware Deep-Learning-Based Proxy Reservoir Simulation Model Equipped with State and Well Output Prediction
-
Z. Losoya, E., Vishnumolakala, N., Noynaert, S. F., Medina-Cetina, Z., Bukkapatnam, S., & Gildin, E.
(2021).
Automatic Identification of Rock Formation Type While Drilling Using Machine Learning Based Data-Driven Models
-
Ramos Gurjao, K. G., Gildin, E., Gibson, R., & Everett, M.
(2021).
Mechanistic Modeling of Distributed Strain Sensing DSS and Distributed Acoustic Sensing DAS to Assist Machine Learning Schemes Interpreting Unconventional Reservoir Datasets
-
Vishnumolakala, N., Murphy, D. M., Nguyen, T., Losoya, E. Z., Kesireddy, V. R., & Gildin, E.
(2021).
Predicting Dysfunction Vibration Events while Drilling Using LSTM Recurrent Neural Networks
-
Pradhan, Y., Gildin, E., & Blasingame, T. A.
(2021).
Drawdown Management Strategies Midland Basin Case Studies
-
Gonzalez, K., Gildin, E., & Gibson Jr., R. L.
(2021).
Improving Microseismic Denoising Using 4D (Temporal) Tensors and High-Order Singular Value Decomposition
-
Gurjao, K., Gildin, E., Gibson, R., & Everett, M.
(2021).
Modeling of Distributed Strain Sensing (DSS) and Distributed Acoustic Sensing (DAS) Incorporating Hydraulic and Natural Fractures Interaction
-
Florez, H., & Gildin, E.
(2020).
Global/local model order reduction in coupled flow and linear thermal-poroelasticity. Computational Geosciences: modeling, simulation and data analysis.
709-735.
-
Lee, J. W., & Gildin, E.
(2020).
A New Framework for Compositional Simulation Using Reduced Order Modeling Based on POD-DEIM
-
Bao, A., Gildin, E., Huang, J., & Coutinho, E. J.
(2020).
Data-Driven End-To-End Production Prediction of Oil Reservoirs by EnKF-Enhanced Recurrent Neural Networks
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Souza, A., Castro, A., DallAqua, M., Tueros, J., Horowitz, B., & Gildin, E.
(2020).
Nonlinear State Constraints Handling in Waterflooding Optimization Through Reduced Order Models. 1-19.
-
Gurjao, K., Gildin, E., Hohendorff, J., & Schiozer, D. J.
(2020).
Oscillation mitigation in subsurface and surface couplings using PID controllers. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING.
106920-106920.
-
Morkos, P., & Gildin, E.
(2020).
Development of Agile Framework for Model-Order Reduction of Large-Scale Geomechanical Models: A Novel Workflow for Coupled Simulations
-
Zalavadia, H., Sankaran, S., Kara, M., Sun, W., & Gildin, E.
(2019).
A Hybrid Modeling Approach to Production Control Optimization Using Dynamic Mode Decomposition
-
Zhang, J., Cheung, S. W., Efendiev, Y., Gildin, E., & Chung, E. T.
(2019).
Deep Model Reduction-Model Learning for Reservoir Simulation
-
Florez, H., & Gildin, E.
(2019).
Model-Order Reduction of Coupled Flow and Geomechanics in Ultra-Low Permeability ULP Reservoirs
-
Kaul, S. P., Vaz, R. F., & Gildin, E.
(2019).
Single Block Productivity Approach - How it Identifies and Isolates Multiple Fracture Network Variants and Helps Improve History Matching and Prediction in Unconventional Reservoirs Using Reservoir Simulator
-
Yatsenko, M., Brankovic, M., Gildin, E., & Gibson, R. L.
(2019).
A Novel Approach to Discovery of Hidden Structures in Microseismic Data Using Machine Learning Techniques
-
Kaul, S. P., Vaz, R. F., & Gildin, E.
(2019).
Dimensionless Productivity Index and its Derivative GOR Variation of Two Phase Solution Gas Drive System in Liquids- Rich Shale Reservoirs
-
Florez, H., & Gildin, E.
(2018).
Model-Order Reduction Applied To Coupled Flow and Geomechanics. Conference proceedings.
-
de Holanda, R. W., Gildin, E., & Valko, P. P.
(2018).
Combining Physics, Statistics, and Heuristics in the Decline-Curve Analysis of Large Data Sets In Unconventional Reservoirs. SPE Reservoir Evaluation and Engineering.
683-702.
-
Bao, A., Gildin, E., & Zalavadia, H.
(2018).
Development Of Proxy Models For Reservoir Simulation By Sparsity Promoting Methods And Machine Learning Techniques. Conference proceedings.
-
Gurjao, K., Gildin, E., Schiozer, D., & Hohendorff, J. C.
(2018).
Oscillation Mitigation In Subsurface And Surface Couplings Using PID Controllers. Conference proceedings.
-
Redick, B., & Gildin, E.
(2018).
Improved Integrated Asset Simulation Surface-Reservoir Using PID Control in Adaptive Time Stepping
-
de Holanda, R. W., Gildin, E., & Valko, P. P.
(2018).
Mapping the Barnett Shale Gas With Probabilistic Physics-Based Decline Curve Models and the Development of a Localized Prior Distribution
-
Yang, Y., Gildin, E., Efendiev, Y., & Calo, V.
(2017).
Online Adaptive POD-DEIM Model Reduction for Fast Simulation of Flows in Heterogeneous Media. 1559-1570.
-
Bao, A., & Gildin, E.
(2017).
Data-Driven Model Reduction Based on Sparsity-Promoting Methods for Multiphase Flow in Porous Media
-
Kaul, S. P., Vaz, R. F., & Gildin, E.
(2017).
Dimensionless Productivity Index and Its Derivative - Insights into Connectivity and Conductivity Variations of Fractures During Flowback in Unconventional Reservoirs
-
Kaul, S. P., Vaz, R. F., & Gildin, E.
(2017).
Dimensionless Productivity Index and its Derivative - Insight into Connectivity and Conductivity Variations of Fractures During Flowback in Unconventional Reservoirs. Conference proceedings.
956-998.
-
Sorek, N., Zalavadia, H., & Gildin, E.
(2017).
Model Order Reduction and Control Polynomial Approximation for Well-Control Production Optimization. 1085-1109.
-
Tan, X., Gildin, E., Trehan, S., Yang, Y., & Hoda, N.
(2017).
Trajectory-Based DEIM TDEIM Model Reduction Applied to Reservoir Simulation. 194-212.
-
Akakpo, D., & Gildin, E.
(2017).
A Control Perspective to Adaptive Time-Stepping in Reservoir Simulation. 213-232.
-
Ghasemi, M., & Gildin, E.
(2016).
Model order reduction in porous media flow simulation using quadratic bilinear formulation. Computational Geosciences: modeling, simulation and data analysis.
723-735.
-
Ghommem, M., Gildin, E., & Ghasemi, M.
(2016).
Complexity Reduction of Multiphase Flows in Heterogeneous Porous Media. SPE JOURNAL.
144-151.
-
Madiebo, K. I., Nasrabadi, H., & Gildin, E.
(2016).
MESOSCOPIC SIMULATION OF SLIP MOTION FOR GAS FLOW IN NANOCHANNELS. v07bt09a024-v07bt09a024.
-
Tarakanov, A., Gildin, E., & Nasrabadi, H.
(2016).
Simulation of Flow in the Solid Matrix of Shale Reservoirs using Lattice-Boltzmann Method
-
Kaul, S. P., Vaz, R. F., & Gildin, E.
(2016).
Dimensionless Productivity Index and Its Derivative - A New Approach to Analyzing Unconventional Reservoirs
-
Vishnumolakala, N., Gildin, E., & Noynaert, S.
(2015).
A simulation environment for automatic managed pressure drilling control. IFAC-PapersOnLine.
128-133.
-
Ghasemi, M., & Gildin, E.
(2015).
Localized Model Reduction in Porous Media Flow1The authors would like to thanks the US DoD - Army Research Once and Foundation CMG for supporting this project. IFAC-PapersOnLine.
242-247.
-
Benamram, Z., Tarakanov, A., Nasrabadi, H., & Gildin, E.
(2015).
Efficient Fractured Reservoir Simulation Using Lattice Boltzmann Method
-
Holanda, R. W., Gildin, E., & Jensen, J. L.
(2015).
Improved Waterflood Analysis Using the Capacitance-Resistance Model Within a Control Systems Framework
-
Pinto, M. A., Gildin, E., & Schiozer, D. J.
(2015).
Short-Term and Long-Term Optimizations for Reservoir Management with Intelligent Wells
-
Plaksina, T., & Gildin, E.
(2015).
Theory of Petroleum Engineering Education: Big Bounce, Big Crunch, or Big Freeze?. 255-269.
-
Ghasemi, M., Yang, Y., Gildin, E., Efendiev, Y., & Calo, V.
(2015).
Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction. 1393-1410.
-
Pinto, M., Ghasemi, M., Sorek, N., Gildin, E., & Schiozer, D. J.
(2015).
Hybrid Optimization for Closed-Loop Reservoir Management. 1500-1510.
-
Tarrahi, M., Gildin, E., Moreno, J., & Gonzales, S.
(2014).
Dynamic Integration of DTS Data for Hydraulically Fractured Reservoir Characterization with the Ensemble Kalman Filter
-
Fuentes-Cruz, G., Gildin, E., & Valko, P. P.
(2014).
Analyzing Production Data From Hydraulically Fractured Wells: The Concept of Induced Permeability Field. SPE Reservoir Evaluation and Engineering.
220-232.
-
Gildin, E. G., & Ghasemi, M. G.
(2014).
A New Model Reduction Technique Applied to Reservoir Simulation. Conference proceedings.
-
Gildin, E., & Afra, S.
(2014).
Efficient Inference of Reservoir Parameter Distribution Utilizing Higher Order SVD Reparameterization. Conference proceedings.
-
Noynaert, S., & Gildin, E.
(2014).
Going Beyond the Tally book: A Novel Method for Analysis, Prediction and Control of Directionally Drilled Wellbores using Mechanical Specific Energy. 5264-5281.
-
Afra, S., Gildin, E., & Tarrahi, M.
(2014).
Heterogeneous Reservoir Characterization using Efficient Parameterization through Higher Order SVD (HOSVD). Proceedings of the ... American Control Conference. American Control Conference.
147-152.
-
Fuentes-Cruz, G., Gildin, E., & Valk, P. P.
(2014).
On the Analysis of Production Data: Practical Approaches for Hydraulically Fractured Wells in Unconventional Reservoirs. 415-433.
-
Tarrahi, M., Gonzales, S., & Gildin, E.
(2014).
Real-time Estimation of Hydraulic Fracture Characteristics from Production Data
-
Ghasemi, M., Ibrahim, A., & Gildin, E.
(2014).
Reduced Order Modeling In Reservoir Simulation Using the Bilinear Approximation Techniques. 1069-1078.
-
Tarrahi, M., Gildin, E., Moreno, J., & Gonzales, S.
(2014).
Dynamic Integration of DTS Data for Hydraulically Fractured Reservoir Characterization with the Ensemble Kalman Filter. 822-835.
-
Afra, S., & Gildin, E.
(2013).
Permeability Parametrization Using Higher Order Singular Value Decomposition (HOSVD). 188-193.
-
Ma, X., Plaksina, T., & Gildin, E.
(2013).
Integrated Horizontal Well Placement and Hydraulic Fracture Stages Design Optimization in Unconventional Gas Reservoirs. 1446-1457.
-
Wu, X. i., Hill, A. D., Oeth, C., Zhu, D., & Gildin, E.
(2013).
Integrated 3D Acid Fracturing Model for Carbonate Reservoir Stimulation. Annual Offshore Technology Conference.
780-790.
-
Fuentes-Cruz, G., Gildin, E., & Valk, P. P.
(2013).
Analyzing Production Data From Hydraulically Fractured Wells: the Concept of Induced Permeability Field. 329-338.
-
Ghommem, M., Calo, V. M., Efendiev, Y., & Gildin, E.
(2013).
Complexity Reduction of Multi-Phase Flows in Heterogeneous Porous Media. 253-263.
-
Gildin, E., Ghasemi, M., Romanovskay, A., & Efendiev, Y.
(2013).
Nonlinear Complexity Reduction for Fast Simulation of Flow in Heterogeneous Porous Media. 579-592.
-
Ma, X., Plaksina, T., & Gildin, E.
(2013).
Optimization of Placement of Hydraulic Fracture Stages in Horizontal Wells Drilled in Shale Gas Reservoirs. 1479-1489.
-
Gildin, E., & Lopez, T. J.
(2011).
Closed-Loop Reservoir Management: Do We Need Complex Models?. 509-519.
-
Gildin, E.
(2010).
Parametrized Model Order Reduction Applied to Reservoir Simulation. Conference proceedings.
-
Gildin, E., & Wheeler, M. F.
(2008).
Optimal Subsurface Flow Management Using Model Predictive Control Techniques. Conference proceedings.
-
Gildin, E., Bishop, R. H., Antoulas, A. C., & Sorensen, D.
(2007).
An Educational Perspective to Model and Controller Reduction of Dynamical Systems. IEEE Conference on Decision and Control.
2832-2837.
-
Gildin, E., Bishop, R. H., Antoulas, A. C., & Sorensen, D.
(2007).
An educational perspective to model and controller reduction of dynamical systems. Proceedings of the ... IEEE Conference on Decision & Control / IEEE Control Systems Society. IEEE Conference on Decision & Control.
5342-+.
-
Bishop, R. H., Lin, N., Gildin, E., & Falcon, J. S.
(2006).
UNIFYING CONTROL DESIGN AND IMPLEMENTATION IN AN UNDERGRADUATE CONTROL SYSTEMS LABORATORY. IFAC-PapersOnLine.
224-228.
-
Gildin, E., Klie, H., Rodriguez, A., Wheeler, M. F., & Bishop, R. H.
(2006).
Development of Low-Order Controllers for High-Order Reservoir Models and Smart Wells. 1326-1332.
-
Gildin, E., Klie, H., Rodriguez, A., F. Wheeler, M., & H. Bishop, R.
(2006).
Projection-Based Approximation Methods for the Optimal Control of Smart Oil Fields
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Gugercin, S., Antoulas, A. C., Beattie, C. A., & Gildin, E.
(2004).
Krylov-based controller reduction for large-scale systems. Proceedings of the ... IEEE Conference on Decision & Control / IEEE Control Systems Society. IEEE Conference on Decision & Control.
3074-3077.
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Losoya, E. Z., Gildin, E., Noynaert, S. F., Medina-Zetina, Z., Crain, T., Stewart, S., & Hicks, J.
An Open-Source Enabled Drilling Simulation Consortium for Academic and Commercial Applications
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Z. Losoya, E., Vishnumolakala, N., Gildin, E., Noynaert, S., Medina-Cetina, Z., Gabelmann, J., Glowka, D., & Houston, R.
Machine Learning Based Intelligent Downhole Drilling Optimization System Using An Electromagnetic Short Hop Bit Dynamic Measurements
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Zalavadia, H., & Gildin, E.
Parametric Model Order Reduction For Adaptive Basis Selection Using Machine Learning Techniques During Well Location Opt. Conference proceedings.
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Rodriguez Castelblanco, A. X., Gildin, E., Cabrales, S. A., & Medaglia, A. L.
(2023).
A Novel Decision-Making Framework for Waterflooding Optimization using Long and Short-Term Memory Models and Metaheuristics
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institutional repository document
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Chen, J., Gildin, E., & Killough, J. E.
(2023).
Physics-informed Convolutional Recurrent Surrogate Model for Reservoir Simulation with Well Controls
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Jordanou, J. P., Antonelo, E. A., Camponogara, E., & Gildin, E.
(2022).
Investigation of Proper Orthogonal Decomposition for Echo State Networks
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Coutinho, E., Dall'Aqua, M., McClenny, L., Zhong, M., Braga-Neto, U., & Gildin, E.
(2022).
Physics-Informed Neural Networks with Adaptive Localized Artificial Viscosity
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Khaled, M., Srinivasan, S., Toure, A., Chen, M., Kincaid, E., Lopaz, T., ... Moridis, G.
(2021).
DREAMS: Drilling and Extraction Automated System
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Zalavadia, H., & Gildin, E.
(2020).
Non-Intrusive Parametric Model Order Reduction With Error Correction Modeling for Changing Well Locations Using a Machine Learning Framework
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Cheung, S. W., Chung, E. T., Efendiev, Y., Gildin, E., & Wang, Y.
(2018).
Deep Global Model Reduction Learning
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Chen, J., Gildin, E., & Killough, J. E.
(2023).
Physics-informed Convolutional Recurrent Surrogate Model for Reservoir Simulation with Well Controls
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patent
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Zarate, L. E., Noynaert, S. F., El-sayed, I. S., Cunningham, T. A., & Gildin, E.
Methods For Real-time Optimization Of Drilling Operations
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Zarate, L. E., Noynaert, S. F., El-sayed, I. S., Cunningham, T. A., & Gildin, E.
Methods For Real-time Optimization Of Drilling Operations
Research
principal investigator on
- I-Corps: Self-guiding drilling tool for the oil, gas and geothermal industries awarded by Directorate for Engineering - (Arlington, Virginia, United States) 2021
- Control relevant complexity reduction for modeling of flow and transport in heterogeneous porous media awarded by Qatar National Research Fund - (Doha, Qatar) 2015 - 2018
- Local-Global Model Reduction for Large-Scale Models Integrating Systems-Theoretical Properties Research Area 3.3 Numerical Analysis awarded by United States Army - (Washington D.C., District of Columbia, United States) 2012 - 2016
Teaching
teaching activities
- ENGR684 Professional Internshp Instructor
- ICPE689 Sptp: Data Sci Intel Oil Fd Op Instructor
- ICPE689 Sptp: Oil Field Ops Digi Twins Instructor
- ICPE689 Sptp: Oil Field Ops Digital Tw Instructor
- ICPE689 Sptp:da Sci For Oil Fld Oper Instructor
- ITDE684 Professional Internship Instructor
- ITDE691 Research Instructor
- PETE219 Foundtns Pete Data Analytics Instructor
- PETE301 Pete Numerical Meth Instructor
- PETE301 Pete Numerical Meth:uk Instructor
- PETE401 Reservoir Simulation Instructor
- PETE404 Integ Reservoir Modeling Instructor
- PETE485 Directed Studies Instructor
- PETE485 Directed Studies:uk/germany Instructor
- PETE491 Hnr-research Instructor
- PETE491 Hnr-research Instructor
- PETE656 Adv Num Meth Res Sim Instructor
- PETE684 Professional Internship Instructor
- PETE685 Directed Studies Instructor
- PETE689 Sptp: Phys-basd & Data-driven Instructor
- PETE689 Sptp: Redu Order Mod In Res En Instructor
- PETE691 Research Instructor
- PETE692 Professional Study Instructor
Works By Students
chaired theses and dissertations
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Afra, Sardar (2015-05). Heterogeneous Reservoir Characterization Utilizing Efficient Geology Preserving Reservoir Parameterization through Higher Order Singular Value Decomposition (HOSVD).
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Agharzayeva, Zinyat (2018-08). Application of Machine Learning and Data Analytics Methods to Detect Interference Effects from Offset Wells.
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Akakpo, Dany Elom (2016-08). A Control Perspective to Adaptive Time Stepping in Reservoir Simulation.
-
Al Jawad, Murtada Saleh H (2018-05). Development of a Fully Integrated Acid Fracture Model.
-
Balogun, Oluwafemi Opeyemi (2017-12). New History Matching Methodology for Two Phase Reservoir Using Expectation-Maximization (EM) Algorithm.
-
Bhuripanyo, Chanapol (2014-08). Quantifying the Benefit of Ensemble Selection for Optimization Under Uncertainty.
-
Dall'Aqua, Marcelo Jacques (2016-12). Application of Simple Smart Logic for Waterflooding Reservoir Management.
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Fombad, Musaga Wasi (2016-05). A Technology Perspective and Optimized Workflow To Intelligent Well Applications.
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Fondren, Mark Edward (2013-08). Applying Calibration to Improve Uncertainty Assessment.
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Fuentes Cruz, Gorgonio (2014-12). Accounting for Nonuniform Induced Properties in Production Analysis of Unconventional Reservoirs.
-
Gao, Mengdi (2014-12). Reservoir and Surface Facilities Coupled Through Partially and Fully Implicit Approaches.
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Ghasemi, Mohammadreza (2015-05). Model Order Reduction in Porous Media Flow Simulation and Optimization.
-
Gonzales, Sergio Eduardo (2013-08). Application of the Ensemble Kalman Filter to Estimate Fracture Parameters in Unconventional Horizontal Wells by Downhole Temperature Measurements.
-
Iemcholvilert, Sevaphol (2013-08). A Research on Production Optimization of Coupled Surface and Subsurface Model.
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Leal Chapa, Jesus Jaime (2016-12). Proper Orthogonal Decomposition for Pressure Preconditioning for the GMRES Algorithm.
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Lerlertpakdee, Pongsathorn (2012-08). Efficient Production Optimization Using Flow Network Models.
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Lopez, Thomas Jai (2011-12). Subsurface Flow Management and Real-Time Production Optimization using Model Predictive Control.
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Ma, Xiaodan (2013-12). Integrated Hydraulic Fracture Placement and Design Optimization in Unconventional Gas Reservoirs.
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Moreno, Jose A (2014-08). Implementation of the Ensemble Kalman Filter in the Characterization of Hydraulic Fractures in Shale Gas Reservoirs by Integrating Downhole Temperature Sensing Technology.
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Nwosa, Obiajulu C (2013-05). Extending the Petrel Model Builder for Educational and Research Purposes.
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Plaksina, Tatyana (2015-05). Automated Optimization Strategies for Horizontal Wellbore and Hydraulic Fracture Stages Placement in Unconventional Gas Reseroirs.
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Plukmonton, Pattanapong (2017-04). Application of Ensemble-based Optimization on UNISIM-I.
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Redick, Brian Samuel (2017-08). PID Controlled Adaptive Time-Stepping in Coupled Surface-Subsurface Simulation: A Tool for Reducing Non-Physical Oscillation.
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Sorek, Nadav (2017-07). Reservoir Flooding Optimization by Control Polynomial Approximations.
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Suranetinai, Chaiyaporn (2017-07). Integrated Field Optimization on UNISIM-I-D Benchmark Case.
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Tarakanov, Alexander (2017-12). Impact of PVT Properties of the Fluid on the LBM Scheme Within the Scale Integration for Shale Reservoirs.
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Tarrahi, Mohammadali (2015-05). Geomechanical Reservoir Model Calibration and Uncertainty Assessment from Microseismic Data.
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Vishnumolakala, Narendra (2015-12). Automatic Control and Optimization of Drilling Operations.
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Wanderley De Holanda, Rafael (2015-08). Capacitance Resistance Model in a Control Systems Framework: A Tool for Describing and Controlling Waterflooding Reservoirs.
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Wu, Xi (2014-08). Integrated 3D Acid Fracturing Model for Carbonate Reservoir Stimulation.
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Zarate Losoya, Enrique (2016-12). Real-time Control and Vibrations Analysis of a Completely Automated Miniaturized Rig.
-
Zubarev, Maxim (2016-11). Simulation Approach Selection in Reservoir Management.
Background
education and training
- Ph.D. in Aerospace Engineering, The University of Texas at Austin - (Austin, Texas, United States) 2006
- M.S. in Mechanical Engineering, University of Sao Paulo - (São Paulo, Brazil) 1998
- B.S. in Mechanical Engineering, Centro Universitario da FEI - (São Bernardo do Campo, Brazil) 1995
awards and honors
Contact
first name
- Eduardo
has last name
- Gildin
mailing address
-
Texas A&M University
Petroleum Engineering
3116 TAMU
College Station, TX 77843-3116
USA
Other
In the News
- egildin@tamu.edu