The Stampede theme this year – Women in Western Culture

The theme for the Stampede this year is saluting women in western culture. On that note, it is appropriate to salute the women who were pioneers in geoscience.

One of the first female mineralogists was the Baroness de Beausoleil, Martine Bertereau. She was born in France in 1600 and married Jean de Chastelet, Baron de Beausoleil et d'Auffenbach, an expert in mining and at that time the Commissioner General of the mines of Hungary for the Holy Roman Empire. In 1626 Martine and her husband were commissioned by King Henry IV and later King Louis XIII to survey France for possible mine locations and revive the French mining industry (Wikipedia, 2019a). After asking to be paid for their work, Martine, Jean and their daughter were imprisoned for witchcraft and she and her daughter died in prison after 1642 (Wikipedia, 2019a).

A little closer to home, Diane Loranger was the first female geologist to work in the oil industry. She worked for Imperial Oil in Calgary in the 1940s as a geologist and paleobotanist. Her work was in the field and research lab as a micropaleontologist with an interest in the Cretaceous and Jurassic contact in Alberta. Her work helped establish where oil would be found depending on fossil profiles, and contributed to other methods for finding oil (Wikipedia, 2019b).

Another notable Canadian/American female geophysicist was Claudia Joan Alexander who was born in Vancouver, British Columbia on May 30, 1959. She specialized in geophysics and planetary science and worked for the United States Geological Survey and NASA's Jet Propulsion Laboratory. She was the last Project Manager of NASA's Galileo mission to Jupiter and, until the time of her death on July 11, 2015, served as Project Manager and Scientist of NASA's role in the European-led Rosetta mission to study Comet Churyumov–Gerasimenko (Wikipedia, 2019c).

While writing this column, I remembered someone I had gone to school with, probably one of the brightest students in math and the sciences I knew. However, at that time women were not encouraged to study the sciences and she did not go on to University, which was sad.

It is important that young women are encouraged to pursue jobs in the sciences. A former summer student once asked me if she should take a job offshore working on the rigs. I told her yes, because when I worked on a seismic vessel I worked alongside women and had a couple on my crew reporting directly to me. After working at it for a couple years she decided to go back to school and asked me to be a reference so she could get into an MBA program. I wrote 4 references for her and she was accepted into every program she applied to. She decided to attend the Haskayne School of Business at the University of Calgary. Each time I wrote a reference for her I began by explaining how she had accepted the position to work on the rig and how she had opened the door for other women to do it through her work ethic.

Our focus this edition

Continuing the road trip across Canada, we are focusing on Ontario. Ontario was where the first oil company in Canada was incorporated by Charles Nelson Tripp. In 1851 at Enniskillen Township, near Sarnia, Tripp started to develop the gum beds near Black Creek and in 1854, Parliament chartered the International Mining and Manufacturing Company. The charter empowered the company to explore for asphalt beds and oil and salt springs, and to manufacture oils, naphtha paints and burning fluids. Tripp built the first asphalt production plant but unfortunately this company was not a success. (Wikipedia, 2019d).

Tripp sold the company to James Miller Williams, with Tripp staying on as a landman in the new company, J.M. Williams & Company, formed in 1857. In 1858, Williams, looking to dig a water well on the properties he bought from Tripp, dug to a depth of 14 ft and struck oil. Somehow it is like the Beverly Hillbillies. It became the first commercial oil well in North America, remembered as the Williams No. 1 well at Oil Springs, Ontario (Wikipedia, 2019d).

This Oil Springs discovery occurred before American industrialists George R. Bissell and Jonathan Greenleaf Eveleth, founders of the Pennsylvania Rock Oil Company (later Seneca Oil Company), and American driller Colonel Edwin Drake, drilled their first successful oil well in Titusville, Pennsylvania on August 27, 1859. Titusville was the beginning of the American petroleum industry (Norman, 2019).

The early refineries were not like they are today. Each consisted of just a primitive firebox and a boiler, which were coupled with various condensation pipes and gauges that fed into storage vats, almost like distilling whiskey (King, 2006).

Pittsburgh, Pennsylvania and Cleveland, Ohio were where the refineries were built because that was where the railroad connections were located. In fact, the first refinery that was built in the United States was in 1854 in Pittsburgh, and along with that first discovery in Titusville, marked the start of the first US oil boom (King, 2006). With the boom, more refineries opened in Pittsburgh, Cleveland and in Ontario around the Enniskillen Township oil wells. The town of Petrolia was founded in 1866, and soon became the thriving centre of Canada’s oil industry.

Unfortunately, the oil in Ontario was sour. This caused odors in the products from the refineries, which made it tough to compete with the refineries in Pittsburgh and Cleveland (Bott, 2004).

In Ontario in 1860, Williams reincorporated as the Canadian Oil Company which produced oil, refined it and marketed the refined products, making it the world's first integrated oil company. (Wikipedia, 2019d).

Across the border, in 1870, Rockefeller formed Standard Oil of Ohio (Sohio), which bought up refineries. Rockefeller would keep the more efficient refineries running and simply shut down the less efficient operations. His goal was to bring a standard to the new oil industry, so that any kerosene sold by Standard Oil was a standard kerosene. Rockefeller promoted refined products and was one of the first businessmen to promote a “brand” (King, 2006).

Standard Oil purchased the oil at the wellhead, transported it by rail or pipeline to a storage facility, then on to a refinery, next to a packaging facility, and finally to wholesalers and retailers around the world. Standard Oil declined to enter the oil drilling business, because drilling wells was too risky (King, 2006).

In 1880, sixteen Ontario production and refining companies merged to form Imperial Oil Company, partly to fend off Standard Oil Trust. In 1898 Standard Oil of New Jersey (now Exxon Mobil Corporation) purchased a controlling interest in Imperial Oil and moved its refining operations from Petrolia to Sarnia, located on the south end of Lake Huron. This gave Imperial access to U.S. crude oil supplies to supplement Ontario’s declining production (Bott, 2004).

Today there are four refineries in Ontario (Wikipedia, 2019d): Refinery Production

Refinery Production
Nanticoke Refinery (Imperial Oil) 112,000 bbl/d 
Imperial Sarnia Refinery 115,000 bbl/d
Suncor Energy Sarnia Refinery 85,000 bbl/d
Shell Corunna Refinery 75,000 bbl/d
TOTAL PRODUCTION 387,000 bbl/d

Today Ontario has almost 2,400 producing oil and gas wells. Its manufacturing sector is an important supplier for Canada's oil and natural gas industry and in 2014 and 2015, the oil sands sector spent $3.9 billion on goods and services from 1,500 companies located in Ontario.

What is happening in Alberta? Where do we go from here?

Beginning in January 2015, thousands of oil and gas workers lost their jobs, which naturally included the geologists and geophysicists. Alberta’s unemployment rate reached its peak in November 2016 at 9.1%, which was like the unemployment rate in 1993. Unemployment rates do not really reflect all those who are out of a job since the numbers come from those collecting EI. Those that are unemployed but are not collecting EI are not counted. It is estimated that last year more than 865 unemployed oil and gas workers had given up searching for a job, 22.5% have been out of work for more than two years and 27.5% have been out of work for more than a year (Cattaneo, 2017).

Future for Geoscientists

Looking at the professional experiences and education of geophysicists and geologists, one sees they are highly skilled in mathematics, sciences, computer programming, computer hardware, geological software, and business acumen. These transferrable skills can be useful and viable to a career change in several other industries such as information technology/computer science, business management, education/teaching and entrepreneurship.

The United States Department of Labor Statistics has stated that employment of all computer and information research scientists is expected to rise 19% by the year 2026, which is deemed much faster than the average for all professions. In the oil and gas industry, companies are discussing the integration of numerous types of data, machine learning and deep learning. Because of this, companies are continuously searching for and employing data scientists.

For some of the younger geophysicists and geologists, returning to university became an imperative to staying competitive. Some are pursuing advanced degrees such as an MBA or PhD. Others, such as those very early in their careers as geoscientists or who could not find sustainable jobs in geoscience, are now pursuing another undergraduate degree in, for example, Computer Science or Information Technology.

However, senior geophysicists or geologists that have more than twenty years of experience in the oil and gas industry, and particularly individuals that have less than 5 years before retirement, are left to ponder if changing careers is still the best option. Due to recessions in the 1980s, early 1990s, and 2009, many professionals may not have enough salted away to retire. Many oil companies prefer to employ people under the age of 50 because they want to invest in someone’s long term future instead of people over 50, who are perceived as “short-timers” in the industry. They fail to acknowledge that the expertise of older professionals may add to their teams and companies.

Based on Statistics Canada (2019), a significant number of workers above the age of 50 are unemployed and having difficulty finding work due to their age, as shown in the graph below.

Data Science

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data (Wikipedia, 2019e). It involves data preparation such as applying standards, cleansing and normalization of the data, preparation and analysis.

Fig. 01
Figure 1. Alberta’s Employment gap by age taken from Canada Statistics (2019).

In order to do the higher end analyses such as machine learning, care needs to be taken that the data that are in the repository, such as geological tops and seismic horizons, are consistent across the area; rock properties from well data and seismic data are scaled properly which may involve machine learning such as neural nets, i.e. interval velocities, porosity, acoustic impedance; the best well log curves are chosen across the zone of interest out of the suite of well log curves; all the well log curves across an area are normalized properly; and the well log mnemonics are consistent i.e., the sonic logs should be referred to as sonic logs not DTC. The reason why data is becoming so important is that it drives big economic decisions such as the sanctioning of a new play.

Fig. 02
Figure 2. Venn diagram showing how Computer Science, Math & Statistics and knowledge of Geoscience (Domain Expert) overlap to form Data Science.

In most companies, terms like big data, machine and deep learning, and oil field digitization are being used at the executive level and in the boardrooms with the Directors of companies. In order to utilize the data to do things like oil field digitization, the seismic and well data need to be integrated through calibration which may involve scaling. This involves tying inversion products and seismic interval velocities to well data. The goal is to use the seismic to guide the interpolation between wells – using the seismic to bridge from the known (wells) to the unknown.

Other data, such as 3D Vertical Seismic Profiles (VSP) and Distributed Fibre Optic Sensing (DFOS) which are used to monitor what is occurring at the reservoir level during the completions / fracking or production, will have to be incorporated into the analysis, calibrated and possibly scaled to fit the already calibrated seismic and well data. How this data is being integrated is through machine and deep learning to try to understand trends that normally are not seen in the data. Engineering data such as completions data (i.e. pumping information, volumes of sand, etc.) are also incorporated. The key is to understand what is happening during the completions and with the production after the fracking. This enables a better understanding of the stimulated rock volume (SRV).

In order to do their jobs properly, data scientists need to interact with a team of domain experts. This is not a stand-alone job. It is combining programming, understanding of the data, statistics, intuition, experience, etc. The objectives of the study need to be clearly defined with regard to what is being investigated to determine whether the results make sense.

How to become a Data Scientist

The University of Calgary offers a Certificate in Fundamental Data Science and Analytics which will count towards a Diploma in Data Science and Analytics. The Diploma in Data Science and Analytics has three specialties: Data Science, Business Analytics and Health Data Science & Biostatistics.

Specialties breakdown:

  • Data Science is about the front end of data collection: cleaning and analysis.
  • Business Analytics is about using big data to extract information to help decision makers understand the past and current performances of a company.
  • Health Data Science & Biostatistics is used in the fields of animal and human health. An example of this is the testing of the effectiveness of medication in neuropsychology using functional magnetic resonance images or FMRIs of the brain. This moves from qualitative analysis of the testing of medicine towards quantified analysis. The hippocampus (controls emotions and memory) behaves differently for those who have depression compared to those who don’t, therefore it is a logical place in the brain to analyze when looking to see if a medicine will cure depression. If the hippocampus of a depressed individual begins to behave like a normal hippocampus then this strongly suggests the medicine is working. Psychology and psychiatry are moving towards neuropsychology and the use of tests to determine what is wrong with an individual rather than through counselling, observations and the patient telling us how they feel. This is moving from a qualitative analysis to a quantitative analysis and is giving us the ability to improve patient’s lives through the proper use of medication rather than hit-or-miss, trying to get the diagnosis right.

The University of Alberta, in conjunction with the Alberta Machine Intelligence Institute (AMii), has developed three new courses on artificial intelligence and machine learning: Applied Machine Learning, Demystifying Artificial Intelligence, and Intermediate Machine Learning.

Southern Alberta Institute of Technology (SAIT) has a diploma program in Geoscience Information Technology which gives the student a broad knowledge of the earth and its geology, along with the computer skills in database management, mapping applications and UNIX, and which prepares them for a career as a geological or geophysical technologist.

Any geoscientist entering Data Science should consider studying Geostatistics as part of their curriculum. Geostatistics is used to interpolate well properties in geomodels and in stochastic seismic inversions. The realizations from stochastic inversion are at the scale of the geomodel and can be integrated into the geomodel, to compute a seismic-driven facies model that accounts for uncertainties (Moyen, el al., 2012).

The University of Alberta has a Citation in Applied Geostatistics and the University of Calgary offers two courses in Geostatistics.



Bott, R. D., 2004, Evolution of Canada’s oil and gas industry. Canadian Centre for Energy Information, retrieved from:

Canada Statistics, 2019, Alberta Employment Gap by Gender. Retrieved from:

Cattaneo, C., 2017), 100,000 jobless energy workers struggle for a place in the new economy. Financial Post. Retrieve from:

King, B., 2006, John D. Rockefeller and the Age of Oil. Daily Reckoning, retrieved from:

Moyen, R., Porjesz, R., Bouziat, A., 2012, Integrating Stochastic Seismic Inversion into Reservoir Characterisation. European Association Geoscientists and Engineers (EAGE), Integrated Reservoir Modelling: Are we doing it right? 25-28 November 2012, Dubai, UAE DOI: 10.3997/2214-4609.20142846.

Norman, J., 2019, The First Successful Oil Well is Drilled in Titusville, Pennsylvania., retrieved from:

Wikipedia, 2019a, Martine Bertereau. Retrieved from:

Wikipedia, 2019b, Diane Loranger. Retrieved from:

Wikipedia, 2019c, Claudia Alexander. Retrieved from:

Wikipedia, 2019d, List of oil refineries. Retrieved from:

Wikipedia, 2019e, Data Analysis. Retrieved from:

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