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Eduardo Gildin
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Proceedings Papers

Accelerated Calibration and CO2 Plume Tracking at the Illinois Basin Decatur Project: A Dynamic Mode Decomposition and Data Assimilation Approach

Omeke James, Kassem Alokla, Dimitrios Voulanas, Eduardo Gildin
Paper presented at the SPE Energy Transition Symposium, August 12–14, 2024
Paper Number: SPE-221411-MS
https://doi.org/10.2118/221411-MS
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View Paper titled, Accelerated Calibration and CO2 Plume Tracking at the Illinois Basin Decatur Project: A Dynamic Mode Decomposition and Data Assimilation Approach
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Proceedings Papers

Practical Challenges to Consider for Model-Based Engineering in Drilling Automation

Zackary W. Whitlow, Mohamed Mahjoub, Stephane Menand, Paul Pastusek, Greg Payette, Khac-Long Nguyen, Eduardo Gildin
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 5–7, 2024
Paper Number: SPE-217752-MS
https://doi.org/10.2118/217752-MS
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View Paper titled, Practical Challenges to Consider for Model-Based Engineering in Drilling Automation
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Journal Articles

Guided Deep Learning Manifold Linearization of Porous Media Flow Equations

Marcelo J. Dall’Aqua, Emilio J. R. Coutinho, Eduardo Gildin, Zhenyu Guo, Hardik Zalavadia, Sathish Sankaran
Journal: SPE Journal
Publisher: Society of Petroleum Engineers (SPE)
SPE J. 29 (02): 885–908.
Paper Number: SPE-212204-PA
https://doi.org/10.2118/212204-PA
Published: 14 February 2024
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View article titled, Guided Deep Learning Manifold Linearization of Porous Media Flow Equations
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Includes: Supplementary Content
Proceedings Papers

Optimizing Well Trajectory Navigation and Advanced Geo-Steering Using Deep-Reinforcement Learning

Narendra Vishnumolakala, Vivek Kesireddy, Sheelabhadra Dey, Eduardo Gildin, Enrique Z. Losoya
Paper presented at the SPE Annual Technical Conference and Exhibition, October 16–18, 2023
Paper Number: SPE-215011-MS
https://doi.org/10.2118/215011-MS
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View Paper titled, Optimizing Well Trajectory Navigation and Advanced Geo-Steering Using Deep-Reinforcement Learning
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Proceedings Papers

Modeling of Fiber-Optic Strain Response When Pumping Stops to Verify Potential Continuation of Fracture Extension

Kildare George Ramos Gurjao, Eduardo Gildin, Richard Gibson, Mark Everett
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3870194-MS
https://doi.org/10.15530/urtec-2023-3870194
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View Paper titled, Modeling of Fiber-Optic Strain Response When Pumping Stops to Verify Potential Continuation of Fracture Extension
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Proceedings Papers

From Laboratory to Field: Simulation of a Surfactant Huff-N-Puff Pilot in the Eagle Ford

Jingjing Zhang, Isaiah Ataceri, Eduardo Gildin, David Schechter, Hadi Nasrabadi
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3867529-MS
https://doi.org/10.15530/urtec-2023-3867529
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View Paper titled, From Laboratory to Field: Simulation of a Surfactant Huff-N-Puff Pilot in the Eagle Ford
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Proceedings Papers

Maximizing Efficiency of Deep-Reinforcement Learning Agents in Autonomous Directional Drilling with Hyperparameter Optimization

Vivek Kesireddy, Georgy Kompantsev, Sheelabhadra Dey, Eduardo Gildin, Enrique Z. Losoya, Narendra Vishnumolakala
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 13–15, 2023
Paper Number: URTEC-3865879-MS
https://doi.org/10.15530/urtec-2023-3865879
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View Paper titled, Maximizing Efficiency of Deep-Reinforcement Learning Agents in Autonomous Directional Drilling with Hyperparameter Optimization
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Proceedings Papers

Input-Output Invariant Fast Proxy Models for Production Optimization

Marcelo J. Dall'Aqua, Emilio J. R. Coutinho, Eduardo Gildin, Zhenyu Guo, Hardik Zalavadia, Sathish Sankaran
Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, June 14–15, 2023
Paper Number: SPE-213117-MS
https://doi.org/10.2118/213117-MS
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View Paper titled, Input-Output Invariant Fast Proxy Models for Production Optimization
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Proceedings Papers

Guided Deep Learning Manifold Linearization of Porous Media Flow Equations

Marcelo J. Dall'Aqua, Emilio J. R. Coutinho, Eduardo Gildin, Zhenyu Guo, Hardik Zalavadia, Sathish Sankaran
Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212204-MS
https://doi.org/10.2118/212204-MS
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View Paper titled, Guided Deep Learning Manifold Linearization of Porous Media Flow Equations
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Journal Articles

Investigation of Strain Fields Generated by Hydraulic Fracturing with Analytical and Numerical Modeling of Fiber Optic Response

Kildare George Ramos Gurjao, Eduardo Gildin, Richard Gibson, Mark Everett
Journal: SPE Reservoir Evaluation & Engineering
Publisher: Society of Petroleum Engineers (SPE)
SPE Res Eval & Eng 25 (02): 367–379.
Paper Number: SPE-206049-PA
https://doi.org/10.2118/206049-PA
Published: 11 May 2022
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View article titled, Investigation of Strain Fields Generated by Hydraulic Fracturing with Analytical and Numerical Modeling of Fiber Optic Response
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Proceedings Papers

Progress Toward an Open-Source Drilling Community: Contributing and Curating Models

Roman J. Shor, Shanti Swaroop Kandala, Eduardo Gildin, Sam F. Noynaert, Enrique Z. Losoya, Vivek Kesireddy, Narendra Vishnumolakala, Inho Kim, James Ng, Josh K. Wilson, Eric Cayeux, Rajat Dixit, Gregory S. Payette, Ty Cunningham, Paul E. Pastusek
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208794-MS
https://doi.org/10.2118/208794-MS
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View Paper titled, Progress Toward an Open-Source Drilling Community: Contributing and Curating Models
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Proceedings Papers

Estimation of Far-Field Fiber Optics Distributed Acoustic Sensing DAS Response Using Spatio-Temporal Machine Learning Schemes and Improvement of Hydraulic Fracture Geometric Characterization

Kildare George Ramos Gurjao, Eduardo Gildin, Richard Gibson, Mark Everett
Paper presented at the SPE Hydraulic Fracturing Technology Conference and Exhibition, February 1–3, 2022
Paper Number: SPE-209119-MS
https://doi.org/10.2118/209119-MS
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View Paper titled, Estimation of Far-Field Fiber Optics Distributed Acoustic Sensing DAS Response Using Spatio-Temporal Machine Learning Schemes and Improvement of Hydraulic Fracture Geometric Characterization
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Proceedings Papers

Physics-Aware Deep-Learning-Based Proxy Reservoir Simulation Model Equipped with State and Well Output Prediction

Emilio J. R. Coutinho, Marcelo J. Dall'Aqua, Eduardo Gildin
Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203994-MS
https://doi.org/10.2118/203994-MS
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View Paper titled, Physics-Aware Deep-Learning-Based Proxy Reservoir Simulation Model Equipped with State and Well Output Prediction
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Proceedings Papers

Predicting Dysfunction Vibration Events while Drilling Using LSTM Recurrent Neural Networks

Narendra Vishnumolakala, Dean Michael Murphy, Thu Nguyen, Enrique Zarate Losoya, Vivekvardhan Reddy Kesireddy, Eduardo Gildin
Paper presented at the SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, October 12–14, 2021
Paper Number: SPE-205571-MS
https://doi.org/10.2118/205571-MS
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View Paper titled, Predicting Dysfunction Vibration Events while Drilling Using LSTM Recurrent Neural Networks
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Proceedings Papers

Mechanistic Modeling of Distributed Strain Sensing DSS and Distributed Acoustic Sensing DAS to Assist Machine Learning Schemes Interpreting Unconventional Reservoir Datasets

Kildare George Ramos Gurjao, Eduardo Gildin, Richard Gibson, Mark Everett
Paper presented at the SPE Annual Technical Conference and Exhibition, September 21–23, 2021
Paper Number: SPE-206049-MS
https://doi.org/10.2118/206049-MS
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View Paper titled, Mechanistic Modeling of Distributed Strain Sensing DSS and Distributed Acoustic Sensing DAS to Assist Machine Learning Schemes Interpreting Unconventional Reservoir Datasets
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Proceedings Papers

Modeling of Distributed Strain Sensing (DSS) and Distributed Acoustic Sensing (DAS) Incorporating Hydraulic and Natural Fractures Interaction

Kildare George Ramos Gurjao, Eduardo Gildin, Richard Gibson, Mark Everett
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, July 26–28, 2021
Paper Number: URTEC-2021-5414-MS
https://doi.org/10.15530/urtec-2021-5414
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View Paper titled, Modeling of Distributed Strain Sensing (DSS) and Distributed Acoustic Sensing (DAS) Incorporating Hydraulic and Natural Fractures Interaction
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Proceedings Papers

Improving Microseismic Denoising Using 4D (Temporal) Tensors and High-Order Singular Value Decomposition

Keyla Gonzalez, Eduardo Gildin, Richard L. Gibson, Jr.
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, July 26–28, 2021
Paper Number: URTEC-2021-5662-MS
https://doi.org/10.15530/urtec-2021-5662
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View Paper titled, Improving Microseismic Denoising Using 4D (Temporal) Tensors and High-Order Singular Value Decomposition
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Proceedings Papers

Automatic Identification of Rock Formation Type While Drilling Using Machine Learning Based Data-Driven Models

Enrique Z. Losoya, Narendra Vishnumolakala, Samuel F. Noynaert, Zenon Medina-Cetina, Satish Bukkapatnam, Eduardo Gildin
Paper presented at the IADC/SPE Asia Pacific Drilling Technology Conference, June 8–9, 2021
Paper Number: SPE-201020-MS
https://doi.org/10.2118/201020-MS
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View Paper titled, Automatic Identification of Rock Formation Type While Drilling Using Machine Learning Based Data-Driven Models
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Proceedings Papers

Machine Learning Based Intelligent Downhole Drilling Optimization System Using An Electromagnetic Short Hop Bit Dynamic Measurements

Enrique Z. Losoya, Narendra Vishnumolakala, Eduardo Gildin, Samuel Noynaert, Zenon Medina-Cetina, Jeff Gabelmann, David Glowka, Robert Houston
Paper presented at the SPE Annual Technical Conference and Exhibition, October 26–29, 2020
Paper Number: SPE-201572-MS
https://doi.org/10.2118/201572-MS
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View Paper titled, Machine Learning Based Intelligent Downhole Drilling Optimization System Using An Electromagnetic Short Hop Bit Dynamic Measurements
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Proceedings Papers

Development of Agile Framework for Model-Order Reduction of Large-Scale Geomechanical Models: A Novel Workflow for Coupled Simulations

Patrick Morkos, Eduardo Gildin
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, July 20–22, 2020
Paper Number: URTEC-2020-3213-MS
https://doi.org/10.15530/urtec-2020-3213
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View Paper titled, Development of Agile Framework for Model-Order Reduction of Large-Scale Geomechanical Models: A Novel Workflow for Coupled Simulations
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