Hector Klie

CEO @ DeepCast.ai | AI-driven Industrial Solutions, Technical Innovation

Research Interests

Artificial Intelligence
Machine Learning
Data Science
optimization
Computational Theory and Mathematics
Computers in Earth Sciences
Computational Mathematics
Computer Science Applications
Computer Graphics and Computer-Aided Design
Software
Mechanical Engineering
Mechanics of Materials
Computational Mechanics
Computer Networks and Communications
Theoretical Computer Science
Computer Vision and Pattern Recognition
Modeling and Simulation
Hardware and Architecture
Numerical Analysis
Applied Mathematics
Energy Engineering and Power Technology
Geotechnical Engineering and Engineering Geology
Management Science and Operations Research
Control and Optimization

About

**Results-driven AI leader with 20+ years of success spearheading model development and optimization initiatives in the energy industry and academia. Proven track record in leveraging computational data science, scientific machine learning, and AI to drive breakthrough physics-data solutions and deliver tangible business value. Adept at translating complex scientific concepts into robust AI models. Skilled in numerical simulation, scientific machine learning, and bilingual communication to optimize project outcomes.**

Publications

On optimization algorithms for the reservoir oil well placement problem

Computational Geosciences / Aug 17, 2006

Bangerth, W., Klie, H., Wheeler, M. F., Stoffa, P. L., & Sen, M. K. (2006). On optimization algorithms for the reservoir oil well placement problem. Computational Geosciences, 10(3), 303–319. https://doi.org/10.1007/s10596-006-9025-7

Algebraic Multigrid Methods (AMG) for the Efficient Solution of Fully Implicit Formulations in Reservoir Simulation

All Days / Feb 26, 2007

Stüben, K., Clees, T., Klie, H., Lu, B., & Wheeler, M. F. (2007, February 26). Algebraic Multigrid Methods (AMG) for the Efficient Solution of Fully Implicit Formulations in Reservoir Simulation. All Days. https://doi.org/10.2118/105832-ms

Stochastic collocation and mixed finite elements for flow in porous media

Computer Methods in Applied Mechanics and Engineering / Aug 01, 2008

Ganis, B., Klie, H., Wheeler, M. F., Wildey, T., Yotov, I., & Zhang, D. (2008). Stochastic collocation and mixed finite elements for flow in porous media. Computer Methods in Applied Mechanics and Engineering, 197(43–44), 3547–3559. https://doi.org/10.1016/j.cma.2008.03.025

A new acoustic wave equation for modeling in anisotropic media

SEG Technical Program Expanded Abstracts 2001 / Jan 01, 2001

Klíe, H., & Toro, W. (2001, January). A new acoustic wave equation for modeling in anisotropic media. SEG Technical Program Expanded Abstracts 2001. https://doi.org/10.1190/1.1816296

Exploiting Capabilities of Many Core Platforms in Reservoir Simulation

All Days / Feb 21, 2011

Klie, H., Sudan, H., Li, R., & Saad, Y. (2011, February 21). Exploiting Capabilities of Many Core Platforms in Reservoir Simulation. All Days. https://doi.org/10.2118/141265-ms

An Autonomic Reservoir Framework for the Stochastic Optimization of Well Placement

Cluster Computing / Oct 01, 2005

Bangerth, W., Klie, H., Matossian, V., Parashar, M., & Wheeler, M. F. (2005). An Autonomic Reservoir Framework for the Stochastic Optimization of Well Placement. Cluster Computing, 8(4), 255–269. https://doi.org/10.1007/s10586-005-4093-3

Studies of Robust Two Stage Preconditioners for the Solution of Fully Implicit Multiphase Flow Problems

All Days / Feb 02, 2009

Al-Shaalan, T. M., Klie, H., Dogru, A. H., & Wheeler, M. F. (2009, February 2). Studies of Robust Two Stage Preconditioners for the Solution of Fully Implicit Multiphase Flow Problems. All Days. https://doi.org/10.2118/118722-ms

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Lecture Notes in Computer Science / Jan 01, 2009

Wang, M., Klie, H., Parashar, M., & Sudan, H. (2009). Solving Sparse Linear Systems on NVIDIA Tesla GPUs. In Computational Science – ICCS 2009 (pp. 864–873). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-01970-8_87

Physics-Based and Data-Driven Surrogates for Production Forecasting

SPE Reservoir Simulation Symposium / Jan 01, 2015

Klie, H. (2015). Physics-Based and Data-Driven Surrogates for Production Forecasting. SPE Reservoir Simulation Symposium. https://doi.org/10.2118/173206-ms

A Timestepping Scheme for Coupled Reservoir Flow and Geomechanics on Nonmatching Grids

All Days / Oct 09, 2005

Gai, X., Sun, S., Wheeler, M. F., & Klie, H. (2005, October 9). A Timestepping Scheme for Coupled Reservoir Flow and Geomechanics on Nonmatching Grids. All Days. https://doi.org/10.2118/97054-ms

Tensor-Krylov methods for solving large-scale systems of nonlinear equations.

Aug 01, 2004

Bader, B. (2004). Tensor-Krylov methods for solving large-scale systems of nonlinear equations. Office of Scientific and Technical Information (OSTI). https://doi.org/10.2172/919158

Models, methods and middleware for grid-enabled multiphysics oil reservoir management

Engineering with Computers / Sep 16, 2006

Klie, H., Bangerth, W., Gai, X., Wheeler, M. F., Stoffa, P. L., Sen, M., Parashar, M., Catalyurek, U., Saltz, J., & Kurc, T. (2006). Models, methods and middleware for grid-enabled multiphysics oil reservoir management. Engineering with Computers, 22(3–4), 349–370. https://doi.org/10.1007/s00366-006-0035-9

Deflation AMG Solvers for Highly Ill-Conditioned Reservoir Simulation Problems

All Days / Feb 26, 2007

Klie, H., Wheeler, M. F., Clees, T., & Stüben, K. (2007, February 26). Deflation AMG Solvers for Highly Ill-Conditioned Reservoir Simulation Problems. All Days. https://doi.org/10.2118/105820-ms

A Black-Box Stencil Interpolation Method to Accelerate Reservoir Simulations

All Days / Feb 18, 2013

Chen, H., Klie, H., & Wang, Q. (2013, February 18). A Black-Box Stencil Interpolation Method to Accelerate Reservoir Simulations. All Days. https://doi.org/10.2118/163614-ms

Projection-Based Approximation Methods for the Optimal Control of Smart Oil Fields

ECMOR X - 10th European Conference on the Mathematics of Oil Recovery / Jan 01, 2006

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. ECMOR X - 10th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.201402503

Parallel Well Location Optimization Using Stochastic Algorithms on the Grid Computational Framework

ECMOR IX - 9th European Conference on the Mathematics of Oil Recovery / Jan 01, 2004

Klie, H., Bangerth, W., Wheeler, M. F., Parashar, M., & Matossian, V. (2004). Parallel Well Location Optimization Using Stochastic Algorithms on the Grid Computational Framework. ECMOR IX - 9th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609-pdb.9.b034

Data-Driven Prediction of Unconventional Shale-Reservoir Dynamics

SPE Journal / Aug 21, 2020

Klie, H., & Florez, H. (2020). Data-Driven Prediction of Unconventional Shale-Reservoir Dynamics. SPE Journal, 25(05), 2564–2581. https://doi.org/10.2118/193904-pa

Upscaling of Hydraulic Properties of Fractured Porous Media: Full Permeability Tensor and Continuum Scale Simulations

All Days / Apr 22, 2006

Rodriguez, A. A., Klie, H., Sun, S., Gai, X., Wheeler, M. F., & Florez, H. (2006, April 22). Upscaling of Hydraulic Properties of Fractured Porous Media: Full Permeability Tensor and Continuum Scale Simulations. All Days. https://doi.org/10.2118/100057-ms

Physics‐based preconditioners for solving PDEs on highly heterogeneous media

PAMM / Dec 01, 2007

Aksoylu, B., & Klie, H. (2007). Physics‐based preconditioners for solving PDEs on highly heterogeneous media. PAMM, 7(1), 1020703–1020704. Portico. https://doi.org/10.1002/pamm.200700324

A hybrid optimization approach for automated parameter estimation problems

PAMM / Dec 01, 2007

Argáez, M., Klie, H., Quintero, C., Velázquez, L., & Wheeler, M. (2007). A hybrid optimization approach for automated parameter estimation problems. PAMM, 7(1), 1062507–1062508. Portico. https://doi.org/10.1002/pamm.200700948

A Learning Computational Engine for History Matching

ECMOR X - 10th European Conference on the Mathematics of Oil Recovery / Jan 01, 2006

E. Banchs, R., Klie, H., Rodríguez, A., G. Thomas, S., & F. Wheeler, M. (2006). A Learning Computational Engine for History Matching. ECMOR X - 10th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.201402539

A Multiscale and Metamodel Simulation-Based Method for History Matching

ECMOR X - 10th European Conference on the Mathematics of Oil Recovery / Jan 01, 2006

A. Rodriguez, A., M. Klie, H., G. Thomas, S., & F. Wheeler, M. (2006). A Multiscale and Metamodel Simulation-Based Method for History Matching. ECMOR X - 10th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.201402495

Enabling Optimal Production Strategies under Uncertainties via Non-Intrusive Model Reduction Methods

ECMOR XIII - 13th European Conference on the Mathematics of Oil Recovery / Sep 10, 2012

Klie, H., Chen, H., Wang, Q., & Willcox, K. (2012, September 10). Enabling Optimal Production Strategies under Uncertainties via Non-Intrusive Model Reduction Methods. Proceedings. https://doi.org/10.3997/2214-4609.20143193

Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

Nov 01, 2006

Mani, S., van Bloemen Waanders, B., Cooper, S., Jakaboski, B., Normann, R., Jennings, J., Gilbert, B., Lake, L., Weiss, C., Lorenz, J., Elbring, G., Wheeler, M., Thomas, S., Rightley, M., Rodriguez, A., Klie, H., Banchs, R., Nunez, E., & Jablonowski, C. (2006). Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling. Office of Scientific and Technical Information (OSTI). https://doi.org/10.2172/966614

Ellipsoidal Approximation of Velocities in Orthorhombic Media

5th International Congress of the Brazilian Geophysical Society / Jan 01, 1997

Contreras, P., Klíe, H., Mora, C., & J. Michelena, reinaldo. (1997). Ellipsoidal Approximation of Velocities in Orthorhombic Media. 5th International Congress of the Brazilian Geophysical Society. https://doi.org/10.3997/2214-4609-pdb.299.87

5. Methods of Secant Type

Methods for Solving Systems of Nonlinear Equations / Jan 01, 1998

5. Methods of Secant Type. (1998). In Methods for Solving Systems of Nonlinear Equations (pp. 45–58). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611970012.ch5

Applications of the control volume function approximation method to reservoir simulations

Fluid Flow and Transport in Porous Media: Mathematical and Numerical Treatment / Jan 01, 2002

Huan, G., Chen, Z., & Li, B. (2002). Applications of the control volume function approximation method to reservoir simulations. Contemporary Mathematics; American Mathematical Society. https://doi.org/10.1090/conm/295/05020

Frequency-domain Modeling of Pseudo-acoustic Wave Propagation in 2D Tilted Transversely Isotropic Media

Proceedings / Jun 01, 2015

Du, Q. Z., Guo, C. F., Wang, G. C., & Yang, F. S. (2015, June 1). Frequency-domain Modeling of Pseudo-acoustic Wave Propagation in 2D Tilted Transversely Isotropic Media. 77th EAGE Conference and Exhibition 2015. https://doi.org/10.3997/2214-4609.201412699

Numerical Comparisons of Path-Following Strategies for a Primal-Dual Interior-Point Method for Nonlinear Programming

Journal of Optimization Theory and Applications / Aug 01, 2002

Argáez, M., Tapia, R., & Velázquez, L. (2002). Numerical Comparisons of Path-Following Strategies for a Primal-Dual Interior-Point Method for Nonlinear Programming. Journal of Optimization Theory and Applications, 114(2), 255–272. https://doi.org/10.1023/a:1016047200413

Dynamic Data-Driven Systems Approach for Simulation Based Optimizations

Computational Science – ICCS 2007 / Jan 01, 2007

Kurc, T., Zhang, X., Parashar, M., Klie, H., Wheeler, M. F., Catalyurek, U., & Saltz, J. (2007). Dynamic Data-Driven Systems Approach for Simulation Based Optimizations. In Lecture Notes in Computer Science (pp. 1213–1221). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-72584-8_158

Stochastic Subspace Projection Methods for Efficient Multiphase Flow Uncertainty Assessment

ECMOR X - 10th European Conference on the Mathematics of Oil Recovery / Jan 01, 2006

M. Klie, H., F. Wheeler, M., Liu, G., & Zhang, D. (2006). Stochastic Subspace Projection Methods for Efficient Multiphase Flow Uncertainty Assessment. ECMOR X - 10th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.201402510

Nonlinear Krylov-Secant Solvers

Jan 01, 2006

Klie, H., & Wheeler, M. F. (2006). Nonlinear Krylov-Secant Solvers. Defense Technical Information Center. https://doi.org/10.21236/ada446287

Optimal Learning of Field Operation and Well Placement in the Presence of Uncertainty

Day 2 Mon, December 07, 2015 / Dec 06, 2015

Klie, H., Agreda, A., & Likanapaisal, P. (2015, December 6). Optimal Learning of Field Operation and Well Placement in the Presence of Uncertainty. Day 2 Mon, December 07, 2015. https://doi.org/10.2523/iptc-18336-ms

Automated Lease Operating Statements for Cost Optimization and Reserve Evaluation Using Artificial Intelligence

Day 3 Wed, October 28, 2020 / Oct 19, 2020

Klie, A., Klie, H., Vuong, D., Chaban, F., & Chaban, N. (2020, October 19). Automated Lease Operating Statements for Cost Optimization and Reserve Evaluation Using Artificial Intelligence. Day 3 Wed, October 28, 2020. https://doi.org/10.2118/201710-ms

A multigrid solver for boundary value problems using programmable graphics hardware

ACM SIGGRAPH 2005 Courses on - SIGGRAPH '05 / Jan 01, 2005

Goodnight, N., Woolley, C., Lewin, G., Luebke, D., & Humphreys, G. (2005). A multigrid solver for boundary value problems using programmable graphics hardware. ACM SIGGRAPH 2005 Courses on - SIGGRAPH ’05. https://doi.org/10.1145/1198555.1198784

Mathematical Aspects of a Fast IMFES Formulation for Solving Three-Phase Black Oil Equations

ECMOR VIII - 8th European Conference on the Mathematics of Oil Recovery / Jan 01, 2002

Buitrago, S., & Klie, H. (2002). Mathematical Aspects of a Fast IMFES Formulation for Solving Three-Phase Black Oil Equations. ECMOR VIII - 8th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.201405952

An efficient and accurate conversion point formula for anisotropic CCP stacking

SEG Technical Program Expanded Abstracts 2000 / Jan 01, 2000

Klíe, H. (2000, January). An efficient and accurate conversion point formula for anisotropic CCP stacking. SEG Technical Program Expanded Abstracts 2000. https://doi.org/10.1190/1.1815588

Dynamic Data-Driven Application Systems for Reservoir Simulation-Based Optimization: Lessons Learned and Future Trends

Handbook of Dynamic Data Driven Applications Systems / Jan 01, 2023

Parashar, M., Kurc, T., Klie, H., Wheeler, M. F., Saltz, J. H., Jammoul, M., & Dong, R. (2023). Dynamic Data-Driven Application Systems for Reservoir Simulation-Based Optimization: Lessons Learned and Future Trends. In Handbook of Dynamic Data Driven Applications Systems (pp. 287–330). Springer International Publishing. https://doi.org/10.1007/978-3-031-27986-7_11

Shale Oil and Shale Gas Resources

May 23, 2020

Shale Oil and Shale Gas Resources. (2020). MDPI. https://doi.org/10.3390/books978-3-03928-876-2

Linear Stability Analysis of Time-Dependent Electrodeposition in Charged Porous Media

ECS Meeting Abstracts / May 01, 2019

Khoo, E., Zhao, H., & Bazant, M. Z. (2019). Linear Stability Analysis of Time-Dependent Electrodeposition in Charged Porous Media. ECS Meeting Abstracts, MA2019-01(22), 1140–1140. https://doi.org/10.1149/ma2019-01/22/1140

Video: Adjoint optimization of fluid mixing

71th Annual Meeting of the APS Division of Fluid Dynamics - Gallery of Fluid Motion / Nov 18, 2018

Eggl, M., & Schmid, P. (2018, November 18). Video: Adjoint optimization of fluid mixing. 71th Annual Meeting of the APS Division of Fluid Dynamics - Gallery of Fluid Motion. https://doi.org/10.1103/aps.dfd.2018.gfm.v0050

A multiscale method for parameter estimation in reservoir simulation

PAMM / Dec 01, 2007

Rodriguez, A., Klie, H., & Wheeler, M. (2007). A multiscale method for parameter estimation in reservoir simulation. PAMM, 7(1), 1151001–1151002. Portico. https://doi.org/10.1002/pamm.200700984

Stochastic Krylov subspace methods for flow in random porous media

PAMM / Dec 01, 2007

Klie, H., Rodriguez, A., & Wheeler, M. F. (2007). Stochastic Krylov subspace methods for flow in random porous media. PAMM, 7(1), 1140403–1140404. Portico. https://doi.org/10.1002/pamm.200701118

Multiscale deflation solvers for flow in porous media

PAMM / Dec 01, 2007

Klie, H., Rodriguez, A., & Wheeler, M. F. (2007). Multiscale deflation solvers for flow in porous media. PAMM, 7(1), 1020301–1020302. Portico. https://doi.org/10.1002/pamm.200700898

SPSA for oil‐parameter estimation and reservoir management

PAMM / Dec 01, 2007

Rodriguez, A., Klie, H., & Wheeler, M. (2007). SPSA for oil‐parameter estimation and reservoir management. PAMM, 7(1), 1062505–1062506. Portico. https://doi.org/10.1002/pamm.200700929

The Origin of the Earth Inner Core's Seismic Anisotropy

Chinese Journal of Geophysics / May 01, 2000

The Origin of the Earth Inner Core’s Seismic Anisotropy. (2000). Chinese Journal of Geophysics, 43(3), 338–347. Portico. https://doi.org/10.1002/cjg2.43

Data Connectivity Inference and Physics-AI Models For Field Optimization

Proceedings of the 2020 Latin America Unconventional Resources Technology Conference / Jan 01, 2020

Klie, H., Klie, A., & Yang, B. (2020). Data Connectivity Inference and Physics-AI Models For Field Optimization. Proceedings of the 2020 Latin America Unconventional Resources Technology Conference. https://doi.org/10.15530/urtec-2020-1098

Transfer Learning for Scalable Optimization of Unconventional Field Operations

Proceedings of the 8th Unconventional Resources Technology Conference / Jan 01, 2020

Klie, H., Yan, B., & Klie, A. (2020). Transfer Learning for Scalable Optimization of Unconventional Field Operations. Proceedings of the 8th Unconventional Resources Technology Conference. https://doi.org/10.15530/urtec-2020-2719

Leveraging US Unconventional Data Analytics Learnings in Vaca Muerta Shale Formation.

Day 3 Wed, June 05, 2019 / Jun 03, 2019

Primera, A., Klie, H., Klie, A., & Quesada, M. (2019, June 3). Leveraging US Unconventional Data Analytics Learnings in Vaca Muerta Shale Formation. Day 3 Wed, June 05, 2019. https://doi.org/10.2118/195511-ms

Data-Driven Discovery of Unconventional Shale Reservoir Dynamics

Day 1 Wed, April 10, 2019 / Mar 29, 2019

Klie, H., & Florez, H. (2019, March 29). Data-Driven Discovery of Unconventional Shale Reservoir Dynamics. Day 1 Wed, April 10, 2019. https://doi.org/10.2118/193904-ms

Improving Field Development Decisions in the Vaca Muerta Shale Formation by Efficient Integration of Data, AI, and Physics

Proceedings of the 7th Unconventional Resources Technology Conference / Jan 01, 2019

Klie, H., Klie, A., Rodriguez, A., Monteagudo, J., Primera, A., & Quesada, M. (2019). Improving Field Development Decisions in the Vaca Muerta Shale Formation by Efficient Integration of Data, AI, and Physics. Proceedings of the 7th Unconventional Resources Technology Conference. https://doi.org/10.15530/urtec-2019-938

Middle East Steamflood Field Optimization Demonstration Project

Day 3 Wed, November 13, 2019 / Nov 11, 2019

Behm, E., Al Asimi, M., Al Maskari, S., Juna, W., Klie, H., Le, D., Lutidze, G., Rastegar, R., Reynolds, A., Tathed, V., Younis, R., & Zhang, Y. (2019, November 11). Middle East Steamflood Field Optimization Demonstration Project. Day 3 Wed, November 13, 2019. https://doi.org/10.2118/197751-ms

Data-driven Model Inference and its Application to Optimal Control under Reservoir Uncertainty

Proceedings / Sep 08, 2014

Klie, H., Chen, H., & Wang, Q. (2014, September 8). Data-driven Model Inference and its Application to Optimal Control under Reservoir Uncertainty. ECMOR XIV - 14th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.20141865

Reduced-order modeling for thermal recovery processes

Computational Geosciences / Sep 01, 2013

Rousset, M. A. H., Huang, C. K., Klie, H., & Durlofsky, L. J. (2013). Reduced-order modeling for thermal recovery processes. Computational Geosciences, 18(3–4), 401–415. https://doi.org/10.1007/s10596-013-9369-8

Unlocking Fast Reservoir Predictions via Non-Intrusive Reduced Order Models

All Days / Feb 18, 2013

Klie, H. (2013, February 18). Unlocking Fast Reservoir Predictions via Non-Intrusive Reduced Order Models. All Days. https://doi.org/10.2118/163584-ms

Reduced-order Modeling for Thermal Recovery Processes

ECMOR XIII - 13th European Conference on the Mathematics of Oil Recovery / Sep 10, 2012

Rousset, M. A. H., Huang, C. K., Klie, H., & Durlofsky, L. J. (2012, September 10). Reduced-order Modeling for Thermal Recovery Processes. Proceedings. https://doi.org/10.3997/2214-4609.20143192

A Parallel Stochastic Framework for Reservoir Characterization and History Matching

Journal of Applied Mathematics / Jan 01, 2011

Thomas, S. G., Klie, H. M., Rodriguez, A. A., & Wheeler, M. F. (2011). A Parallel Stochastic Framework for Reservoir Characterization and History Matching. Journal of Applied Mathematics, 2011, 1–19. https://doi.org/10.1155/2011/535484

Dynamic Decision and Data-Driven Strategies for the Optimal Management of Subsurface Geo-Systems

Journal of Algorithms & Computational Technology / Dec 01, 2011

Parashar, M., Klie, H., Kurc, T., Catalyurek, U., Saltz, J., & Wheeler, M. F. (2011). Dynamic Decision and Data-Driven Strategies for the Optimal Management of Subsurface Geo-Systems. Journal of Algorithms & Computational Technology, 5(4), 645–665. https://doi.org/10.1260/1748-3018.5.4.645

High Performance Manycore Solvers for Reservoir Simulation

Proceedings / Sep 06, 2010

Sudan, H., Klie, H., Li, R., & Saad, Y. (2010, September 6). High Performance Manycore Solvers for Reservoir Simulation. 12th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.20144961

Parallel Sparsified Solvers for Reservoir Simulation

Proceedings / Sep 06, 2010

Klie, H. M. (2010, September 6). Parallel Sparsified Solvers for Reservoir Simulation. 12th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.20144960

A family of physics-based preconditioners for solving elliptic equations on highly heterogeneous media

Applied Numerical Mathematics / Jun 01, 2009

Aksoylu, B., & Klie, H. (2009). A family of physics-based preconditioners for solving elliptic equations on highly heterogeneous media. Applied Numerical Mathematics, 59(6), 1159–1186. https://doi.org/10.1016/j.apnum.2008.06.002

Towards a New Generation of Physics-Driven Solvers for Black-Oil and Compositional Flow Simulation

All Days / Feb 02, 2009

Klie, H., Monteagudo, J., Hoteit, H., & Rodriguez, A. (2009, February 2). Towards a New Generation of Physics-Driven Solvers for Black-Oil and Compositional Flow Simulation. All Days. https://doi.org/10.2118/118752-ms

A Novel Percolative Aggregation Approach for Solving Highly Ill-Conditioned Systems

Proceedings / Sep 08, 2008

Klie, H., & Wheeler, M. F. (2008, September 8). A Novel Percolative Aggregation Approach for Solving Highly Ill-Conditioned Systems. 11th European Conference on the Mathematics of Oil Recovery. https://doi.org/10.3997/2214-4609.20146369

Towards a rigorously justified algebraic preconditioner for high-contrast diffusion problems

Computing and Visualization in Science / Mar 27, 2008

Aksoylu, B., Graham, I. G., Klie, H., & Scheichl, R. (2008). Towards a rigorously justified algebraic preconditioner for high-contrast diffusion problems. Computing and Visualization in Science, 11(4–6), 319–331. https://doi.org/10.1007/s00791-008-0105-1

A neural stochastic multiscale optimization framework for sensor-based parameter estimation

Integrated Computer-Aided Engineering / May 13, 2007

Banchs, R. E., Klie, H., Rodriguez, A., Thomas, S. G., & Wheeler, M. F. (2007). A neural stochastic multiscale optimization framework for sensor-based parameter estimation. Integrated Computer-Aided Engineering, 14(3), 213–223. https://doi.org/10.3233/ica-2007-14302

Assessing Multiple Resolution Scales in History Matching With Metamodels

All Days / Feb 26, 2007

Rodriguez, A. A., Klie, H., Wheeler, M. F., & Banchs, R. (2007, February 26). Assessing Multiple Resolution Scales in History Matching With Metamodels. All Days. https://doi.org/10.2118/105824-ms

Integrated time‐lapse seismic inversion for reservoir petrophysics and fluid‐flow imaging

SEG Technical Program Expanded Abstracts 2007 / Jan 01, 2007

Hong, T., Sen, M. K., Stoffa, P. L., Klie, H., Thomas, S. G., Rodriguez, A., & Wheeler, M. F. (2007, January). Integrated time‐lapse seismic inversion for reservoir petrophysics and fluid‐flow imaging. SEG Technical Program Expanded Abstracts 2007. https://doi.org/10.1190/1.2792872

A Neural Stochastic Optimization Framework for Oil Parameter Estimation

Intelligent Data Engineering and Automated Learning – IDEAL 2006 / Jan 01, 2006

Banchs, R. E., Klie, H., Rodriguez, A., Thomas, S. G., & Wheeler, M. F. (2006). A Neural Stochastic Optimization Framework for Oil Parameter Estimation. In Lecture Notes in Computer Science (pp. 147–154). Springer Berlin Heidelberg. https://doi.org/10.1007/11875581_18

Assessing the value of sensor information in 4‐D seismic history matching

SEG Technical Program Expanded Abstracts 2006 / Jan 01, 2006

Klie, H., Rodriguez, A., Thomas, S. G., Wheeler, M. F., & Banchs, R. (2006, January). Assessing the value of sensor information in 4‐D seismic history matching. SEG Technical Program Expanded Abstracts 2006. https://doi.org/10.1190/1.2370204

Development of Low-Order Controllers for High-Order Reservoir Models and Smart Wells

All Days / Sep 24, 2006

Gildin, E., Klie, H., Rodriguez, A., Wheeler, M. F., & Bishop, R. H. (2006, September 24). Development of Low-Order Controllers for High-Order Reservoir Models and Smart Wells. All Days. https://doi.org/10.2118/102214-ms

Towards Dynamic Data-Driven Management of the Ruby Gulch Waste Repository

Computational Science – ICCS 2006 / Jan 01, 2006

Parashar, M., Matossian, V., Klie, H., Thomas, S. G., Wheeler, M. F., Kurc, T., Saltz, J., & Versteeg, R. (2006). Towards Dynamic Data-Driven Management of the Ruby Gulch Waste Repository. In Lecture Notes in Computer Science (pp. 384–392). Springer Berlin Heidelberg. https://doi.org/10.1007/11758532_52

An analysis of flow‐simulation scales and seismic response

SEG Technical Program Expanded Abstracts 2005 / Jan 01, 2005

Stoffa, P. L., Sen, M. K., Seifoullaev, R., Klie, H., Gai, X., Bangerth, W., Rungamornrat, J., & Wheeler, M. F. (2005, January). An analysis of flow‐simulation scales and seismic response. SEG Technical Program Expanded Abstracts 2005. https://doi.org/10.1190/1.2147965

Application of Grid-enabled technologies for solving optimization problems in data-driven reservoir studies

Future Generation Computer Systems / Jan 01, 2005

Parashar, M., Klie, H., Catalyurek, U., Kurc, T., Bangerth, W., Matossian, V., Saltz, J., & Wheeler, M. F. (2005). Application of Grid-enabled technologies for solving optimization problems in data-driven reservoir studies. Future Generation Computer Systems, 21(1), 19–26. https://doi.org/10.1016/j.future.2004.09.028

Fully integrated reservoir flow, geomechanics and seismic modeling: a tool for better reservoir characterization and geomechanical prediction using 4D seismic

SEG Technical Program Expanded Abstracts 2005 / Jan 01, 2005

Gai, X., Rungamornrat, J., Klie, H., Bangerth, W., Wheeler, M. F., Stoffa, P. L., Sen, M. K., & Seifoullaev, R. (2005, January). Fully integrated reservoir flow, geomechanics and seismic modeling: a tool for better reservoir characterization and geomechanical prediction using 4D seismic. SEG Technical Program Expanded Abstracts 2005. https://doi.org/10.1190/1.2147941

Krylov-Secant Methods for Accelerating the Solution of Fully Implicit Formulations

All Days / Jan 31, 2005

Klie, H., & Wheeler, M. F. (2005, January 31). Krylov-Secant Methods for Accelerating the Solution of Fully Implicit Formulations. All Days. https://doi.org/10.2118/92863-ms

Towards Dynamic Data-Driven Optimization of Oil Well Placement

Lecture Notes in Computer Science / Jan 01, 2005

Parashar, M., Matossian, V., Bangerth, W., Klie, H., Rutt, B., Kurc, T., Catalyurek, U., Saltz, J., & Wheeler, M. F. (2005). Towards Dynamic Data-Driven Optimization of Oil Well Placement. In Computational Science – ICCS 2005 (pp. 656–663). Springer Berlin Heidelberg. https://doi.org/10.1007/11428848_85

Application of Grid-Enabled Technologies for Solving Optimization Problems in Data-Driven Reservoir Studies

Computational Science - ICCS 2004 / Jan 01, 2004

Parashar, M., Klie, H., Catalyurek, U., Kurc, T., Matossian, V., Saltz, J., & Wheeler, M. F. (2004). Application of Grid-Enabled Technologies for Solving Optimization Problems in Data-Driven Reservoir Studies. In Lecture Notes in Computer Science (pp. 805–812). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-24688-6_104

Estimation of elastic constants from ellipsoidal velocities in orthorhombic media

SEG Technical Program Expanded Abstracts 1998 / Jan 01, 1998

Contreras, P., Klíe, H., & Michelena, R. J. (1998, January). Estimation of elastic constants from ellipsoidal velocities in orthorhombic media. SEG Technical Program Expanded Abstracts 1998. https://doi.org/10.1190/1.1820194

Education

Ph.D., Computational Science and Engineering / May, 1997

Houston, Texas, United States of America

Master of Arts, Computational and Applied Mathematics / May, 1995

Houston

Simón Bolívar University

Master of Science, Computer Science / May, 1991

Caracas

Simón Bolívar University

Bachelor, Computer Science / December, 1988

Caracas

Experience

DeepCast, LLC

CEO / May, 2017Present

ConocoPhillips Company

Staff Data Scientist / March, 2008April, 2016

Sanchez Oil and Gas

Director of Enterprise Data Solutions / March, 2016March, 2017

Design corporate data science platform, lead R&D in machine learning and AI to generate highly predictive models for field applications

Rice University

Adjunct Professor / January, 2016Present

Teach and mentor students and elevate industrial visibility and engagement of the Dept. of Applied Mathematics and Operation Research

The University of Texas at Austin

Associate Director and Sr. Research Associate / July, 2003February, 2008

Write research proposals for federal funding , lead research and promote industrial engagement at in the Center for Subsurface Modeling, Oden Institute for Computational Engineering and Science

Join Hector on NotedSource!
Join Now

At NotedSource, we believe that professors, post-docs, scientists and other researchers have deep, untapped knowledge and expertise that can be leveraged to drive innovation within companies. NotedSource is committed to bridging the gap between academia and industry by providing a platform for collaboration with industry and networking with other researchers.

For industry, NotedSource identifies the right academic experts in 24 hours to help organizations build and grow. With a platform of thousands of knowledgeable PhDs, scientists, and industry experts, NotedSource makes connecting and collaborating easy.

For academic researchers such as professors, post-docs, and Ph.D.s, NotedSource provides tools to discover and connect to your colleagues with messaging and news feeds, in addition to the opportunity to be paid for your collaboration with vetted partners.

Expert Institutions
NotedSource has experts from Stanford University
Expert institutions using NotedSource include Oxfort University
Experts from McGill have used NotedSource to share their expertise
University of Chicago experts have used NotedSource
MIT researchers have used NotedSource
Proudly trusted by
Microsoft uses NotedSource for academic partnerships
Johnson & Johnson academic research projects on NotedSource
ProQuest (Clarivate) uses NotedSource as their industry academia platform
Slamom consulting engages academics for research collaboration on NotedSource
Omnicom and OMG find academics on notedsource
Unilever research project have used NotedSource to engage academic experts