Innovative Projects Realized

Estimating reservoir changes in a heavy oil reservoir through application of anelasticity and rock physics analysis to time-lapse seismic data

Oil-sands reservoirs offer huge resource potential with very low decline rates compared to other unconventional exploration targets. Unfortunately, this comes with the trade-off of requiring high initial investment as well as high operating costs. In order for such projects to be economic in the long-term, it is essential that we monitor changes in the reservoir to maximize production and by extension, return.
Time-lapse (4D) seismic monitoring is a common, cost-effective means of monitoring changes in reservoir due to production. Using amplitude vs. offset (AVO) inversion, we are able to estimate changes in elastic and petro-physical parameters in addition to the spatial mapping of reservoir changes. Unfortunately, the complex properties of viscous oil-sands outlines deficiencies in most commonly applied AVO inversion techniques. These algorithmic deficiencies cause errors in our elastic and petro-physical estimations. The purpose of this proposed project is to model the effect of viscous fluids on seismic data in order to either account for, or remove its effects to obtain a more accurate AVO inversion result. TO BE CONT’D

Deterministic Decision Making Using All Geological Realizations

Predicting the quantity of mineral (gold, coper, etc) or hydrocarbon (oil, gas) extracted from a given deposit is difficult. One concern is the uncertainty in the resources underground. A few initial wells or drill holes give us access to an estimate of the quantity of resource, but there is great uncertainty because sampling can be hundreds of meters or kilometers apart. There can only be one plan for extraction which necessitates that the plan be optimal from the beginning of the project; computer simulations can help greatly with this and improving the efficiency of these models through this research will ensure optimal extraction plans. Moreover, most existing strategies ignore uncertainty and this work aims to optimize extraction plans while accounting for uncertainty in the subsurface. This increases profitability, recovery and reduces environmental footprints.

Large Consumer-Generated Data Optimization and Prediction

The proposed research aims to target large-scale consumer-generated data to analyze, visualize, and make predictions out of. The data will be collected from the consumers to make assessments on their lifestyles, and will come in forms such as heart-rate variance, that is, being temporal data. Researchers with visual analytics background will apply new visualization techniques on the data in order to grasp the insights and improve the model to interpret the data. The research problem is to relate measures of stress, recovery and mindful activities to the data obtained. The purpose of the proposed research is to complement the data with subjective measures such as happiness, life stress, and mindfulness. Some of the main objectives are to find out whether increased awareness of stress/recovery is associated with a change in stress/recovery; or whether increased daily mindful activity is associated with a change in stress/recovery. Expected results involve finding out whether the new product will contribute to a change in stress/recovery, or to increased mindful activity.

Pando.js: a platform for scientific volunteer computing on the Web

Scientists need more and more computing resources to do research. At the same time, a huge amount of available computing resources is currently completely ignored in all the devices and computers we use to surf the Web. All that computing power could be used to make progress on research about cancer, climate change, epidemiology, etc. that affects all of humanity. The overall project goal is to make these computing resources available to scientists working on public research. The project consists in creating Pando.js, a volunteer computing platform in the form of a website the general public will visit to contribute computing power. The computing
tasks will run in a webpage, created automatically from a scientist’s program source code, and accessed through social media links. The outcome will be a more convenient platform both for scientists and the general public to exchange volunteer computing resources than existing alternatives.

Supporting Role and Request Conceptual Modeling with Ontology-Based Reasoning

This project involves creating a comprehensive method for developing and maintaining a Meta-model for the representation of Role and Request Modeling (R2M) constructs based on the notion of ontologies. R2M provides clear definitions and semantics for the constructs of conceptual models as well as a set of rules for guiding the modeling process.

The intern will provide an ontology-based Meta-model for modeling R2M constructs, and rules. She will provide a method for recognizing any update that is not consistent with the defined semantics for R2M and a method for ensuring that all rules are conformed by any given model. ModiViz, which is the owner of the intellectual property relating to R2M, will use the outcome of this project for having the ability to ensure consistency in the Meta-model, paving the way to the introduction of much more robust model validation and guidance in the tool, and educating modelers much quicker.

Support à la conception de robots souples

La complexité de conception de robots souples est due à leur nature pluridisciplinaire (intégration de systèmes mécaniques, électronique et logiciel) ainsi qu’aux contraintes introduites par la non-rigidité des membres, ce qui met donc à rude épreuve la créativité des ingénieurs. Cette complexité est liée principalement aux multiples dépendances existantes entre les différentes composantes du robot déformable. Les multiples dépendances d’un système résulte généralement (dans les systèmes rigides) en l’adoption par les ingénieurs d’une conception séquentielle alors que la communauté de design conseille l’utilisation d‘une méthodologie intégrée (conception concurrente des sous-systèmes) car elle permet de réduire le coût de développement tout en améliorant la performance du robot. Différentes méthodologies ont récemment été développées pour faciliter cette conception intégrée des systèmes rigides, par contre, ces méthodologies ne considèrent aucunement les caractéristiques liées aux systèmes robotiques souples. Afin d’y remédier, une nouvelle méthodologie basée sur l’utilisation d’agents intelligents artificiels (AIA) sera développée pour fin d’aide à la décision au stade de la conception de systèmes robotiques souples. Cette méthodologie sera conçue sur des bases similaires à ce qui est utilisé dans la conception logicielle. TO BE CONT’D

Learning Approaches to Graph Structure Discovery

The project would explore the use of modern techniques from the field of Machine Learning to identify networks from observational data. This is an important area of research in fields such as neuroscience and genetics, where it can shed light on the nature of various disease. Other applications include discovering influencers and communities in social networks. These problems are normally untenable in the general case and techniques rely on deriving mathematical approximations, which often make many assumptions, and require lengthy time to formulate by expert researchers. In this project we explore methods of automatically deriving approximations to these problems based simulated examples, which are much easier to formulate than mathematical approximations. We hope the outcome of the project can provide
useful tools for researchers studying neuroimaging, genomics, and social networks to solve problems in their field.

Design of a gene network implementing an associative memory circuit

The main goal of this research project is to implement an associative memory module in a gene network. The idea is to use the theoretical work already done at the Signals and Systems Laboratory (L2S) and to apply it in the area of genetics. The proposed approach is innovative, as it combines techniques from two disciplines: engineering and life sciences. The work done at L2S deals with a type of systems that includes networks, and in this particular case it would be applied to a network made up of genes. In case this approach is successful it would be possible to use synthetic biology in order to build a genetic network that could be programmed to provide for flexible responses of an organism in a variety of environmental conditions.

Compromis entre efficacité énergétique et protection aux pannes dans les « Software Defined Networks ».

Les réseaux de communications, notamment l’Internet, connaissent une importante croissance ses dernières années. Cette croissance s’accompagne d’une complexité grandissante ainsi que d’une consommation énergétique de plus en plus élevée. Les technologies actuellement déployées ne sont pas adaptées pour faciliter l’économie d’énergie sur des réseaux de grandes tailles. La technologie SDN nous offre un meilleur contrôle sur les équipements de réseaux et va nous permettre de développer des modèles pour l’économie d’énergie sur ces réseaux. Grâce à cette technologie, nous pouvons facilement décider des appareils à éteindre. Mais en réduisant le nombre de dispositifs actifs sur le réseau, nous abaissons sa tolérance à la panne.
Ce projet de recherche a pour but premièrement, d’étudier les différentes solutions actuelles de tolérance à la panne des réseaux et leurs comptabilités avec l’économie d’énergie et, ensuite, de proposer des solutions offrant un bon compromis entre les deux problèmes.

Controls on diagenetic evolution in Tithonian Jeanne d’Arc Formation, Terra Nova field: Implications for reservoir quality evolution

Hydrocarbons are hosted in porous sedimentary rocks which were deposited several million years prior to the ingress of hydrocarbons. Once these sedimentary rocks are deposited, other physical, chemical and biological, all termed diagenetic, processes act to modify their original properties. A major product of this diagenesis is cementation. The cement (minerals) occludes (plugs) the pore spaces in the sedimentary rock thus, in general, reducing its capacity to host hydrocarbons. This project, among others will seek to understand the types of cement and their origin in Terra Nova field. It will also attempt to predict their spatial distribution in the rock. The project is thought to be important because the cements sometimes ‘compartmentalize’ hydrocarbon volumes and pressure systems in the rock, which can have negative impact on hydrocarbon exploration and production. Such impact may or may not be significant depending on other factors.

Bobolink and eastern meadowlark occupancy in different agricultural land cover types

The bobolink (Dolichonyx oryzivorus) and eastern meadowlark (Sturnella magna) are listed as a species at risk in several Canadian provinces. Both songbird species are most abundant in Ontario and breed in hayfields, pastures, and other grassland-like environments. Ontario’s Endangered Species Act (ESA) seeks to protect these species by regulating activities that negatively affect their habitat. Improving our understanding of the breeding habitat used by these species will provide important science-based guidance in developing conservation solutions that minimize the economic impact on agricultural operations. This project aims to examine how frequently bobolink and eastern meadowlark occur in various land cover types (including hayfield, pasture, grassland, and grain crops) within regions predicted as having high and low abundance of these species (based on results of the second Ontario Breeding Bird Atlas). Results from this project will benefit both partner organizations, DG Taylor Inc. and Bird Ecology and Conservation Ontario (BECO), by providing new ecological information that can lead to better-informed conservation strategies and mitigation activities.

Development of a renewable and small scaled heat and power generation system for remote location using woody biomass as fuel

The key objective of this research is to develop a unit for combined heat and power production using biomass feedstock that can be used in remote areas where no grid power is available. Canada as the second largest country in the world, has a great potential for such units. Aboriginal communities or remote work facilities are only two possible applications for this technology. The existing heat and power generation system mostly rely on diesel and natural gas. Replacing the system with renewable biomass fueled units would have a positive impact on carbon dioxide emissions and promote the domestic market for pellets and renewable fuels. To develop the technology this research focuses on the properties of different feedstocks and technologies. A successful project would allow FPInnovations to either provide such a system or the necessary know how on the Canadian market.