Ziming Xu

6-361 DICE, 9211 116th St, Edmonton, AB, CA • ziming4@ualberta.ca

Ph.D. Candidate in Petroleum Engineering

Hello, my name is Ziming Xu, and I am a fourth-year Ph.D. student at the University of Alberta. My research is dedicated to pioneering advancements in production forecasting and optimization through the application of advanced deep learning and numerical methods. I am deeply passionate about machine learning and its potential to solve critical subsurface problems. My work focuses on pushing the boundaries of knowledge in these areas, aiming to make a significant impact on both the academic and industrial fronts.

English/中文

Education

University of Alberta

Ph.D. in Petroleum Engineering • 2021 — Present

Edmonton, Alberta, CA

University of Alberta

M.Sc. in Petroleum Engineering • 2019 — 2021

Edmonton, Alberta, CA

University of Alberta

B.Sc. in Petroleum Engineering • 2015 — 2019

Edmonton, Alberta, CA

Experience

University of Alberta

Teaching Assistant (PETE375; PETE475) • Sep, 2022 — Present

Assisted in grading assignments and reports.
Facilitated engaging classroom discussions and responded to student inquiries.
Provided remote one-on-one guidance and addressed student concerns.

University of Alberta

Research Assistant • Sep, 2019 — Present

Conducted research and data analysis on unconventional reservoirs.
Collaborated with professors on publications.

BAFF International English

English Teacher • May, 2018 — August, 2018

Xian, Shannxi, China

Delivered Traveling English courses, enhancing practical communication skills for international travel.
Taught High School English, improving students' reading, writing, and critical thinking abilities.

Projects

Physics-Informed Deep Learning for Shale Gas Production Forecasting

• April 2023 — Present

Developed neural network solution for 3D Diffusivity equation.
Conducted field-scale experiments with a combined physics and data-driven model.

Graph Convolution for Capturing Well Interference in Production Forecasting

• Dec. 2022 — Present

Developed novel ST-GraphSAGE model for generalizing unseen nodes and computation of evolving graphs.
Incorporated a GRU encoder-decoder model to capture cross-time neighborhood information effectively.

Enhanced RNN-Based Production Forecasting for Shale Gas Reservoirs

• Sep. 2021 — April 2023

Developed novel MRA (Masked Recurrent Alignment) architecture, enabling inputs sequence with varied lengths.
Proposed novel RUF (Recursively Updated Forecasting) architecture, enabling real-time updates with production data.
Generated multi-stage hydraulic fracture synthetic dataset using DFNs and geomechanical simulation.

Impacts of Meshing and Discretization on DPDK Flow Simulation

• Jan. 2019 — Dec. 2021

Proposed quick analytical workflow for generating non-planar twisted fractures, improving fracture representation.
Developed novel workflow to restore connectivity between disconnected fractures after discretization.
Upscaled DFN into DPDK and conducted DPDK Flow simulation on fractured reservoir using a black oil simulator.

Activities

Reviewer for "Geoenergy Science and Engineering"

Journal reviewer • Jan. 2024 — Present

Advanced ML Model Reading Group

Organizer • Jan. 2024 — Present

Future Energy System (FES) Science Rendezvous

Activity Lead • May 2024

FES Energy Explorers

Activity Lead • Oct. 2023

Petroleum and Geoscience Reading Group

Organizer • April 2021 — Oct. 2022

ML-in-Physics Datathon-AI4Society

Data Specialist • Aug. 2022

UofA Open House

Volunteer • Oct. 2018

Technical Skills

Coding languages

Python, Matlab, R, Java

Industry Software

CMG, Fracman, MRST, COMSOL, AutoCAD, Petrel, FORGAS, PIPESIM

Database

RISM, Accumap

Server

Compute Canada

Awards

Scholarship of Pedagogy and Application of Research Knowledge - Engineering

• Dec. 2023

University of Alberta GSA Travel Award

• Aug. 2023

China Scholarship Council Award

• June 2021

University of Alberta Dean’s Research Award

• April 2019

University of Alberta Transfer Award

• Sep. 2015

Journal Publications

1. Ma, Z., Yuan, Q., Xu, Z., & Leung, J. Y. (2024). A Dynamic Solvent Chamber Propagation Estimation Framework using RNN for Warm Solvent Injection in Heterogeneous Reservoirs. Geoenergy Science and Engineering, 213405.

DOI: https://doi.org/10.1016/j.geoen.2024.213405

2. Xu, Z., & Leung, J. Y. (2024). Dynamic Real-Time Production Forecasting Model for Complex Subsurface Flow Systems with Variable-Length Input Sequences. SPE Journal. 2024;.

DOI: https://doi.org/10.2118/221482-PA

3. Xu, Z., & Leung, J. Y. (2024). Shale Gas Production Forecasting with Well Interference Based on Spatial-Temporal Graph Convolutional Network. SPE Journal. 2024;.

DOI: https://doi.org/10.2118/215056-PA

4. Xu, Z., & Leung, J. Y. (2024). A novel formulation of RNN-based neural network with real-time updating–An application for dynamic hydraulic fractured shale gas production forecasting. Geoenergy Science and Engineering, 233, 212491.

DOI: https://doi.org/10.1016/j.geoen.2023.212491

5. Xu, Z., & Leung, J. Y. (2023). An Improved Dual-Porosity Dual-Permeability Modeling Workflow for Representing Nonplanar Hydraulic Fractures. Gas Science and Engineering, 118, 205108.

DOI: https://doi.org/10.1016/j.jgsce.2023.205108

6. Chen, J., Xu, Z., & Leung, J. Y. (2022). Analysis of Fracture Interference–Coupling of Flow and Geomechanical Computations with Discrete Fracture Modeling Using MRST. Journal of Petroleum Science and Engineering, 219, 111134.

DOI: https://doi.org/10.1016/j.petrol.2022.111134

7. Xu, Z., & Leung, J. Y. (2022). Analyzing the Impacts of Meshing and Grid Alignment in Dual Porosity Dual-Permeability Upscaling. SPE Reservoir Evaluation & Engineering, 25(01), 61-80.

DOI: https://doi.org/10.2118/208573-PA

Conferences

1. Xu, Z., & Leung, J. Y. (2025, March). Deep Learning-based Production Forecasting For Liquid-rich Gas In The Duvernay Shale Play. SPE Canadian Energy Technology Conference and Exhibition (25CET-P-432-SPE), Calgary, Alberta, Canada.

2. Xu, Z., & Leung, J. Y. (2024, September). Graph-Level Feature Embedding with Spatial-Temporal GCN Method for Interconnected Well Production Forecasting. In SPE Annual Technical Conference and Exhibition (SPE-220790-MS), New Orleans, Louisiana, USA.

DOI: https://doi.org/10.2118/220790-MS

3. Xu, Z., & Leung, J. Y. (2023, October). Shale Gas Production Forecasting with Well Interference Based on Spatial-Temporal Graph Convolutional Network. In SPE Annual Technical Conference and Exhibition (p. D031S032R004), San Antonio, Texas, USA.

DOI: https://doi.org/10.2118/215056-MS

4. Ma, Z., Yuan, Q., Xu, Z., & Leung, J. Y. (2023, October). A Recurrent Neural Network-Based Solvent Chamber Estimation Framework During Warm Solvent Injection in Heterogeneous Reservoirs. In SPE Annual Technical Conference and Exhibition (p. D021S013R001), San Antonio, Texas, USA.

DOI: https://doi.org/10.2118/214984-MS

5. Xu, Z., & Leung, J. Y. (2023). A Recursively Enhanced GRU Model for Real-Time Production Forecasting in Central Montney Shale Gas Reservoirs. In the International Association for Mathematical Geosciences (IAMG) Conference, Trondheim, Norway.

Ph.D. in Petroleum Engineering • 2021 — Present

University of Alberta

M.Sc. in Petroleum Engineering • 2019 — 2021

University of Alberta

B.Sc. in Petroleum Engineering • 2015 — 2019

University of Alberta

Teaching Assistant (PETE375; PETE475) • Sep, 2022 — Present

University of Alberta

Research Assistant • Sep, 2019 — Present

BAFF International English

English Teacher • May, 2018 — August, 2018

Xian, Shannxi, China

Physics-Informed Deep Learning for Shale Gas Production Forecasting

• April 2023 — Present

• Dec. 2022 — Present

• Sep. 2021 — April 2023

Impacts of Meshing and Discretization on DPDK Flow Simulation

• Jan. 2019 — Dec. 2021

Advanced ML Model Reading Group

FES Energy Explorers

Petroleum and Geoscience Reading Group

Coding languages

Industry Software

Database

Server

Scholarship of Pedagogy and Application of Research Knowledge - Engineering

University of Alberta GSA Travel Award

China Scholarship Council Award

University of Alberta Dean’s Research Award

University of Alberta Transfer Award

1. Ma, Z., Yuan, Q., Xu, Z., & Leung, J. Y. (2024). A Dynamic Solvent Chamber Propagation Estimation Framework using RNN for Warm Solvent Injection in Heterogeneous Reservoirs. Geoenergy Science and Engineering, 213405.

2. Xu, Z., & Leung, J. Y. (2024). Dynamic Real-Time Production Forecasting Model for Complex Subsurface Flow Systems with Variable-Length Input Sequences. SPE Journal. 2024;.

3. Xu, Z., & Leung, J. Y. (2024). Shale Gas Production Forecasting with Well Interference Based on Spatial-Temporal Graph Convolutional Network. SPE Journal. 2024;.

4. Xu, Z., & Leung, J. Y. (2024). A novel formulation of RNN-based neural network with real-time updating–An application for dynamic hydraulic fractured shale gas production forecasting. Geoenergy Science and Engineering, 233, 212491.

5. Xu, Z., & Leung, J. Y. (2023). An Improved Dual-Porosity Dual-Permeability Modeling Workflow for Representing Nonplanar Hydraulic Fractures. Gas Science and Engineering, 118, 205108.

6. Chen, J., Xu, Z., & Leung, J. Y. (2022). Analysis of Fracture Interference–Coupling of Flow and Geomechanical Computations with Discrete Fracture Modeling Using MRST. Journal of Petroleum Science and Engineering, 219, 111134.

7. Xu, Z., & Leung, J. Y. (2022). Analyzing the Impacts of Meshing and Grid Alignment in Dual Porosity Dual-Permeability Upscaling. SPE Reservoir Evaluation & Engineering, 25(01), 61-80.

1. Xu, Z., & Leung, J. Y. (2025, March). Deep Learning-based Production Forecasting For Liquid-rich Gas In The Duvernay Shale Play. SPE Canadian Energy Technology Conference and Exhibition (25CET-P-432-SPE), Calgary, Alberta, Canada.

2. Xu, Z., & Leung, J. Y. (2024, September). Graph-Level Feature Embedding with Spatial-Temporal GCN Method for Interconnected Well Production Forecasting. In SPE Annual Technical Conference and Exhibition (SPE-220790-MS), New Orleans, Louisiana, USA.

3. Xu, Z., & Leung, J. Y. (2023, October). Shale Gas Production Forecasting with Well Interference Based on Spatial-Temporal Graph Convolutional Network. In SPE Annual Technical Conference and Exhibition (p. D031S032R004), San Antonio, Texas, USA.

4. Ma, Z., Yuan, Q., Xu, Z., & Leung, J. Y. (2023, October). A Recurrent Neural Network-Based Solvent Chamber Estimation Framework During Warm Solvent Injection in Heterogeneous Reservoirs. In SPE Annual Technical Conference and Exhibition (p. D021S013R001), San Antonio, Texas, USA.

5. Xu, Z., & Leung, J. Y. (2023). A Recursively Enhanced GRU Model for Real-Time Production Forecasting in Central Montney Shale Gas Reservoirs. In the International Association for Mathematical Geosciences (IAMG) Conference, Trondheim, Norway.

Member (5062345) • 2017 — Present

Fellow • 2019 — Present