Research

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Hyperlinked Table (Projects In Progress, i.e, no. 01, 03, 05, 06, 11);

01.

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Joint industry project (JIP), PHASE 2. A multi-disciplinary (i.e., Computer Science, Geoscience, and Petroleum Engineering) research and development of a Rapid Reservoir Modeling (RRM) software framework for prototyping complex conceptual reservoir models, using novel, sketch-based interface and modeling (SBIM) algorithms and methods, exploratory visualization & visual analytics, and numerical modeling and analysis of fundamental reservoir properties and behaviors.

Main deliverables from PHASE 1 (Completed).
The primary goal for PHASE 2 is to demonstrate RRM in several compelling application examples. These will examine how RRM adds value by supporting critical business decisions in asset environments and research & development (R&D) settings. The application examples are steering R&D in the RRM project to deliver the research results and technological advancements in the three main disciplines involved -- i.e., Computer Science, Geoscience, and Petroleum Engineering.

https://rapidreservoir.org/

Publications, RRM Phase 2 (alpha order, J = journal, C = conference):

  • Alshakri et al. '23 (J)
  • Baird et al. '23 (C)
  • Costa Sousa et al. '20 (C)
  • Hampson et al. '22 (C)
  • Jacquemyn et al. '22 (J) , '21a,(J), 21(b, c) (C)
  • Jackson et al. '22 (J)
  • Li et al. '22 (C)
  • Petrovskyy et al. '23 (J)

Three Principal Investigators (alpha. order):

1.

Dr. Mario Costa Sousa (Co-PI)

University of Calgary, Computer Science (CAN)

2.

Dr. Sebastian Geiger (Co-PI)

Delft University of Technology, Geoscience & Engineering (NLD)

3.

Dr. Matthew Jackson (Co-PI)

Imperial College London, Earth Science & Engineering (GBR)

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03.

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Ongoing R&D of illustrative visualization framework and toolset incorporates traditional Scientific-Technical-Medical (STM) illustration principles, practices, and methods with existing and forthcoming graphics and visualization systems and techniques.

Our program in PHASE 4 has two main objectives.

(1) To create informative, illustrative visualizations from modern STM data experiments, simulations and acquisitions, which are robust in their expressiveness and communication while providing room for visually exploring the data and gaining new insights into their uncertainties.

(2) To ensure the context is captured by the illustrative techniques used when information is presented during a visualization task, consisting of characteristics with varying degrees of available information (e.g., data modality, size, detail, and uncertainty), the interactive modeling, rendering and visualization communication goals, the users' expertise and experience, and the interaction techniques and technologies being utilized.

Also, refer to PHASES 1, 2, 3.

My role: PI

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05.


Science-informed strategies to manage induced-seismicity risks are hindered by critical knowledge gaps, including:

(1) Understanding which pre-existing faults are prone to induced seismicity;
(2) Characterizing the role of slow (aseismic) fault slip in generating earthquakes;
(3) Calibration of realistic numerical simulations using field observations; and
(4) Spatial and temporal variability in earthquake-induced ground motions.

This project's objectives include identifying and mapping critically stressed faults and understanding their impact on hydrocarbon production. Technological advancements within this program, including visual computing and machine learning, will contribute to the responsible development of natural resources, improved fundamental understanding of earthquake activation mechanisms, and unique opportunities to generate innovative methods and workflows.

https://www.microseismic-research.ca/

PI: Dr. David Eaton, Geoscience, University of Calgary
My role: Co-PI

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06.

 


The traditional methods of estimating permeability largely do not work well in heavy oil because of core disturbance or the fact that the core is filled with immobile bitumen. This project aims to use image-based data & visual analytics to estimate particle size distribution and then permeability from the drill core. Expected research outcomes would provide new data/visual analytics technology to help the user estimate permeability at reasonable cost at a high-vertical resolution in appraisal wells with core data. It would considerably improve the reservoir characterization, benefiting domains involved with subsurface modeling..

My role: PI

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11.


The research program's overall objective is to integrate technologies and methodologies from geomatics, electrical, mechanical and computer science (i.e., visual computing and software engineering) to develop systems to address a wide range of practical challenges. In the short-term, this will include identifying and developing inter-disciplinary synergies to address current research challenges with an emphasis on identifying new sensors and/or sensor combinations for data acquisition and, subsequently, novel algorithms for integrating the data. Low-cost prototype systems will be developed integrating all available sensor data to address practical applications involving navigation, mapping, and autonomous system control.

To accomplish these objectives, the program is divided into four themes: (1) Acquisition and Sensing Platforms; (2) Sensor Integration; (3) Human Interaction and Analytics; and (4) Applications.

PI, Dr. Naser El-Sheimy, Geomatics Engineering, University of Calgary
My role: Co-Applicant and Collaborator

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