Schedule

Short schedule

This short schedule is meant to have an overview over the talks

9:30- 9:40    Start and land acknowledgement
9:40- 10:20  Dr. Jithamala Caldera: Innovative Universal Severity Classification System for Natural Disasters
10:20-11:00 Ferdinand Hingerl: AI-powered Industrial Process Automation: A Solution to Balancing Economic Growth, Environmental Stewardship, and Worker Safety in the Energy Sector
11:00-11:10 Break
11:10-11:50 Brad Samis: BC Hydro Decarbonization through Low Carbon Electrification
12:00- 13:00  Lunchtime
13:00-13:25 Shima Bashti Monfared: Assessing the Sustainability of Direct Air Capture (DAC) of CO2 through Underground Energy Recovery for Achieving Net-Zero Emissions
13:25-13:40  Break
13:40-14:20 Dr. Esha Saha:  Can We Identify Active Tailings and Predict Methane Emissions from Incomplete Data?
14:20- 14:30 Break
14:30-15:10 Dr. Simon Michael Papalexiou: Capturing Nature’s Extremes: A Stochastic Approach to Modeling Hydroclimatic Events
15:10- 15:50 Greg Baden: Hydrogen Project in Alberta
15:50 - 16:00 Break
16:00-16:40   Bruce Fleming: Energy Transition, Climate Change, Complex Models?  Not Without Statistics.
16:40-17:20: Doug Leece: Cyber Security, Employment & Climate Concerns — Past, Present and Possible Future
17:30- open end: Industry mixer at the LDL

Detailed schedule

This detailed schedule contains more information about the talks

9:30- 9:40: start and land acknowledgement

9:40- 10:20:  Dr. Jithamala Caldera: Innovative Universal Severity Classification System for Natural Disasters
As climate change intensifies, the frequency and severity of natural disasters—such as floods, wildfires, hurricanes, and droughts—have surged, creating an urgent need for a standardized system to assess and communicate disaster impacts. This presentation introduces an Innovative Universal Severity Classification System for Natural Disasters, designed to address gaps in current disaster classification approaches by offering a consistent, multidimensional framework to measure and communicate disaster severity. This classification system integrates both quantitative and qualitative assessments, using a 0-10 scale and color-coded levels to encapsulate human and financial impacts, with factors such as fatalities, affected populations, and economic losses.

This system enables effective cross-border communication and coordination, essential as climate-related events increasingly transcend national boundaries. By providing precise severity indicators, it supports data-driven policy-making, allowing for targeted resource allocation and improved risk mitigation. Furthermore, the system fosters public understanding of climate risks, bridging linguistic and cultural gaps through universally understood terms and visuals, thereby enhancing community preparedness.

Beyond immediate response applications, the classification system offers a long-term perspective by enabling consistent tracking and comparison of climate-related disasters over time. This data contributes to understanding climate change’s impacts on disaster frequency and intensity, informing both local and global adaptation strategies.

10:20-11:00: Ferdinand Hingerl: AI-powered Industrial Process Automation: A Solution to Balancing Economic Growth, Environmental Stewardship, and Worker Safety in the Energy Sector

In the rapidly evolving energy sector, striking a balance between economic growth, environmental responsibility, and worker safety presents significant challenges. AI-powered industrial process automation emerges as a pivotal solution, offering transformative potential across these domains. This presentation will explore how such technologies not only optimize operations and maximize economic return, but also significantly mitigate environmental impacts and enhance worker safety standards.

Using the product suite of Ambyint, a Calgary based technology company, as a prime example, we will delve into the application of AI and machine learning in automating and optimizing upstream oil and gas production processes. Ambyint’s technology integrates seamlessly with existing SCADA systems to provide real-time data analytics and proactive set point management through advanced AI algorithms and physics-based models. This integration facilitates substantial reductions in methane emissions by minimizing the need for venting events and workovers, thereby contributing to substantial environmental benefits. Additionally, the reduction in the need for manual interventions and field visits enhances worker safety and operational reliability.

Furthermore, the presentation will cover the economic implications of these software solutions in the energy sector, highlighting how AI-powered process automation has successfully demonstrated cost savings and operational efficiencies for various clients. Expanding on these successes, we will also touch upon the broader impacts of AI in industrial automation, including potential scalability and adaptability challenges, risks, and how Ambyint addresses these issues.

By showcasing Ambyint's successes and ongoing innovations, this presentation aims to provide insights into how AI-powered industrial process automation can serve as a cornerstone for sustainable growth in the energy industry, offering a model that aligns economic objectives with environmental and safety commitments.

11:10-11:50: Brad Samis: BC Hydro Decarbonization through Low Carbon Electrification (virtual talked streamed)

Outline: 

• Program Overview -

• Funding / Process

• Eligibility

• Low Carbon Electrification Key Offerings

• Feasibility Studies

• Incentives

• Industrial Electrification Program

• Online eligibility

Bio: Brad Samis currently is the Sr. Program Manager for large  Low Carbon Electrification at BC Hydro.  Brad leads the Large Industrial and Transportation Custom LCE Program that supports a variety of customers in some of the largest sectors to transition away from the use of fossil fuels by using clean electricity. Brad is responsible for managing one of the most dynamic programs in the Electrification Plan and will be integral as we look forward to 2030 Clean-BC targets and our integration with other Demand-Side Management initiatives.

Brad started his journey with BC Hydro 16 years ago and has worked in Enterprise Strategy, Energy Planning, and Economic and Business Development. He joined Project Delivery in Portfolio and Resource Management in 2011, moved to a project management role in Capital Infrastructure Project Delivery, and then joined the PCM Capital Projects team in 2017. Brad has developed a unique enterprise skill set though numerous business solution-based initiatives experienced in multiple roles throughout the organization.

Prior to joining BC Hydro Brad spent time in the oil and gas (upstream and down stream), mining and forestry sectors in Alberta and BC.

12:00-13:00: Free lunch provided in the room

Let's enjoy some lunch while chatting about Mathematics, Statistics, Computer Science and climate change.

13:00-13:25: Shima Bashti Monfared: Assessing the Sustainability of Direct Air Capture (DAC) of CO2 through Underground Energy Recovery for Achieving Net-Zero Emissions

To effectively mitigate climate change, it is crucial to implement strategies that not only minimize greenhouse gas (GHG) emissions but also encompass approaches to reduce the existing concentration of CO2 in the atmosphere. These approaches, referred to as Negative Emission Technologies (NETs), are integral to achieving the targets outlined in the Paris Agreement. One such NET is Direct Air Capture (DAC), which directly removes CO2 from the atmosphere. However, DAC is faced with challenges such as its relatively high energy requirements and cost that diminishes its attractiveness compared to alternative mitigation options. To address this, integrating the CO2 capture system, along with its associated energy supply, with underground energy resources, such as oil, gas, and geothermal sources, presents a potential solution. In our research, we explore the feasibility of such a combination from an energy, carbon, and economic perspective to determine the potential for achieving net-zero or negative carbon emissions.

13:40-14:20: Dr. Esha Saha:  Can We Identify Active Tailings and Predict Methane Emissions from Incomplete Data? 

Climate change is one of the leading causes of the various environmental challenges we face every year. One such activity that has recently come into the spotlight for being a major contributor to methane emissions is the oil sand activity in Athabasca Oil Sand region in Alberta, Canada. Recent years have seen significant efforts in attempting to quantify methane emissions from various sources, especially activities pertaining to oil sands extraction. A classical approach in estimating methane emissions from oil sands activities is modeling the process of methanogenesis in oil sands tailing ponds (OSTPs) through differential equations based mechanistic models (MM). A more contemporary approach that has recently gained traction is the use of atmospheric data from weather monitoring stations to predict methane concentrations (or other variables of interest) through machine learning modeling. While both the traditional and contemporary modeling approaches have their own advantages, they are disconnected, leading to an understanding gap of how methane emissions from tailing ponds affect methane concentrations in the atmosphere. Our proposed framework aims to bridge this gap by using a hybrid machine learning approach to connect the MMs to real field data through atmospheric dispersion models (ADM). We formulate our problem as a constrained optimization problem that learns the methane concentrations in the atmosphere by enforcing a physical relationship between emissions and concentrations. Since our framework makes use of classical MMs to generate emission data, the proposed model serves as a validation framework for the MM by implicitly learning its solution in addition to jointly predicting concentrations in the atmosphere and learning the functions that govern the physics-based constraints. We compare our model to other unconstrained formulations with different model architectures and show that the proposed framework outperforms them, either in terms of prediction accuracy or model generalization, or both.

14:30-15:10: Dr. Simon Michael Papalexiou: Capturing Nature’s Extremes: A Stochastic Approach to Modeling Hydroclimatic Events

Understanding and predicting environmental risks requires tools that can capture the inherent randomness of nature. Physical models provide valuable insights, yet they often struggle to fully account for the complex variability seen in hydroclimatic processes. Stochastic methods present an efficient and adaptable alternative for replicating this complexity, offering a new perspective for environmental scientists and engineers. This presentation introduces CoSMoS (Complete Stochastic Modeling System), a flexible modeling framework designed to transition from simple to advanced scenarios, spanning multisite and space-time scales. CoSMoS excels at reproducing the likelihood and spatial-temporal relationships of weather events, from time series of individual variables to detailed simulations of storm events. By exploring current challenges and future advancements, this talk will demonstrate the potential of stochastic methods to enhance our ability to predict and prepare for extreme environmental events.

Bio: Simon Michael Papalexiou is an Associate Professor in the Department of Civil Engineering at the University of Calgary, Canada. His research centers on hydroclimatic variability and extremes, the development of advanced space-time stochastic models, downscaling methodologies, and climate change diagnostics. He has published 90 articles in leading journals and contributed to over 120 conference presentations. Simon serves as an Associate Editor for AGU’s Water Resources Research and Elsevier’s Journal of Hydrology. He has reviewed manuscripts for more than 50 journals, convened scientific sessions, and organized multiple workshops on time series modeling. Simon leads the development of CoSMoS, a widely-used software in stochastic modeling with a global user base. He is Vice-President of the International Commission on Statistical Hydrology and Team Lead for the Storms Module in the UNU Sustainability Nexus AID program. Recognized for his contributions, he received AGU’s 2024 Natural Hazard Early Career Award and several Best Paper awards. His work has been honored as Editor’s Choice in Science Magazine, Editor’s Highlight in Earth’s Future, and featured four times in AGU’s Eos Science News Magazine. Additionally, his research has been covered by over 100 news outlets, with highlights on radio and TV, among others.

15:10- 15:50: Greg Baden: Hydrogen Project in Alberta

Outline:

• What makes hydrogen an attractive energy source? 

• What are the challenges and costs of producing and using hydrogen in Alberta? 

•  How is hydrogen currently produced and what new production technologies are emerging?

• What is happening currently in the  Alberta hydrogen market and what will the market look like in the future?

16:00-16:40: Bruce Fleming: Energy Transition, Climate Change, Complex Models?  Not Without Statistics.

“Should We Be Worried?  Crude Oil vs Renewable Fuels in a Time of Disruptive Change”

North America’s largest Sustainable Aviation Fuel producer (2024), Montana Renewables, has repurposed part of a conventional petroleum refinery from fossil to renewable feedstocks.  Let’s see what we have learned and discuss how mathematics and statistics can better connect government energy policy to the real world.

North America’s three large energy distribution systems—the electrical grid; natural gas delivery; and petroleum products supply—have evolved over more than a century to be efficient and effective, delivering abundant low-cost energy to a growing population.  Now each system is showing warning signs of capacity constraints (spot reliability issues and price spikes) while society is asking energy producers to undertake the separate challenge of decarbonization.  

A classic private sector forecasting error.  Any large complex system is likely to be humbling to long-term forecasting, risk management, compliance, or capital allocation, to name a few.  Getting any of these wrong has tangible repercussions.  Consider the Darwinian nature of clean transportation fuels:  over 300 North American oil refineries were operating in 1980 but only about 115 are left standing today.  The rate of refinery closures accelerated during Covid, with another 9 gone.  These were not casualties of climate change, but of economics and forecasting.   Economically marginal refineries were exposed by the Covid demand drop, while then-conventional-wisdom forecasts called for declining fossil fuel consumption.  In other words, refinery owners faced an immediate Covid-related demand drop combined with a forecast for continuing demand decline, which pushed corporate decisions to shut down capacity.  Those decisions proved ill-timed, since demand rebounded post-Covid and the surviving refining capacity proved over-stretched (which in turn caused retail gasoline and diesel prices to skyrocket).  So the surviving refineries did well for a couple of years, but the closed refineries stayed closed.

A classic public policy forecasting error. What happens to closed refineries?  Some or many of these sites are suited for a new life processing renewable feedstocks instead of fossil.  Capital costs for re-purposing are significant, but less than the cost of greenfield construction of renewable refineries.  About a dozen refineries were converted to renewable diesel production.  The Catch-22 is that each conversion represents a net loss of around 70% of that refinery’s previous gasoline, jet and diesel production, meaning that converting one refinery causes the fossil fuel supply to shrink faster than the renewable fuel growth. If we shut down all the refineries out there, we lose 70% of the fuel.  This sets up a policy forecasting error.  When policy makers chart the recent growth in renewable capacity over time, they may be forgiven for thinking their policies are working when what really happened was a one-time step change which cannot be scaled across the entire fuels industry.  

A Non Governmental Organization forecasting error.  When the airline industry reaches capacity, say at holiday time, travelers know that one storm near a hub or one computer glitch at a regional control center can snarl the entire national system.  The evening news will show passengers sleeping on the floor.  Energy consumers don’t want the same thing happening when they reach for the light switch, or the gas heat, or the vehicle fuel pump.  The way to avoid the energy equivalent of sleeping on the floor is modify our energy distribution systems within two imperatives:  (1) decarbonization will take longer than advertised, simply because of the time it takes to design, permit and build the modifications needed to make a meaningful dent in the existing fossil infrastructure; and importantly (2) the Law of Unintended Consequences has not been repealed.  There will be setbacks when invasive surgery is performed on large complex systems.  The physician’s mantra “first do no harm” comes to mind.  

In conclusion:  Energy is always transitioning, from wood to peat to coal to oil to gas to nuclear…and historically these transitions are 50 years in the making.   There is a long runway ahead of us for the 21st century energy transition.  We will need a lot of smart people who are good at objective, quantitative, statistically sound mathematical models to guide the journey.

Bio: Bruce Fleming is CEO of Montana Renewables, the largest Sustainable Aviation Fuel producer in the western hemisphere. He has been Head of Corporate Development for Calumet Inc; Head of M&A for Tesoro Companies Inc; founder and Managing Director of Orient Refining Ltd (Hong Kong); VP China Business Development for Amoco Corporation; and chief scientist at Amoco Whiting, then the largest inland refinery in North America. Dr. Fleming is a member of the Board of M&A Standards and the CFO Business Panel of the Federal Reserve Bank (Atlanta). He has a PhD in Chemical Engineering from Princeton University, where his thesis addressed a fundamental issue in geothermal energy production, and a BS Chemical Engineering from University of Delaware. Dr. Fleming has over 40 years experience in building and operating commodities businesses, and has lived in five countries including Texas.

16:40-17:20: Doug Leece: Cyber Security, Employment & Climate Concerns — Past, Present and Possible Future

Calgary information systems security veteran Doug Leece will explore the intersection of digital technology and climate issues we are collectively facing. The convergence of potential environmental consequences and an ever-expanding digital attack surface presents a new challenge in the cyber security threat landscape.  The sophistication of modern cyber attacks demands more skilled defenders, but rather than another “the world needs more cyber security people” talk, this presentation will look at some potential gaps to be filled if we are to address eco driven cyber threats.

17:30 - open end: Math CS industry mixer at the LDL

After the talks, we will be holding a Math & CS industry mixer at the Last Defence Lounge, consisting of a panel discussion with industry representatives followed by an informal networking session over a light dinner. If you’re a mathematician, statistician, or computer scientist who’s interested in bringing your skills to industry, don’t pass up on this opportunity to build your network and connections!