Is the Future of Oil and Gas Looking Brighter Because of AI?
Is the Future of Oil and Gas Looking Brighter Because of AI?
By 2021 global spending on AI and other cognitive technologies is set to hit US$52.2 billion per year. Big data and AI technologies will have transformative effects on the oil and gas industry, ultimately allowing organizations to build smaller, more elite teams, that will deliver value more effectively and efficiently. Which in turn will positively position oil and gas companies for growth for decades to come.
Predictions are that the demand for crude oil and natural gas around the world will continue to rise until 2040. And by this time, developing nations like China and India will increase their energy consumption by 60%.
The method of energy mix supply will continue to evolve. It will include more renewable sources such as electricity, hydro, wind, solar and geothermal; however, these are not always appropriate replacements for all oil and gas uses and products. Oil and gas will continue to play an important role in Canada as well as around the world as global population grows and energy demand increases.
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That said, we are in the midst of a structural and technology transition and its effects are expected to be profound in the oil and gas industry. For decades, the energy industry has gone through important transitions and today is no different. Around the world, the emergence of increasingly sophisticated data, analytics, automation technologies, and artificial intelligence (AI) is transforming the way we work and live.
In Canada, the oil and gas industry continues to focus on innovation to drive performance, cost, efficiency, and speed. Technological advances are disrupting traditional development through data generation that use advanced analytics. Machine learning (AI) is growing and it will eventually harness opportunities for production, distribution, and refining. One global company boasts a long-term plan to roll out construction of 10 intelligent plants with a goal of a 20 percent reduction in operation costs.
“Oil and gas is one of the most exciting industries currently, since it involves massive volumes of data, and any easy solutions for optimizing production and business processes have long since been implemented. This combination, together with significant turnover and high level of technological development, creates good opportunities for securing a major effect from implementing solutions based on machine learning and artificial intelligence, and we look forward to a productive partnership, in the long term.”– Alexander Khaytin, COO, Yandex Data Factory
AI is growing exponentially due to its ability to solve problems, unlock value, and inspire new ways of doing business. Organizations have been digitizing data for decades, but the AI revolution is still in its infancy and as it grows, it’s expected to have an evolutionary effect on the traditional business models used by oil and gas companies today.
AI is expected to improve production, distribution, and refinement of oil and gas products through:
1. Monitoring & Sensing for Efficient Decision Making
AI can emulate human cognitive abilities, in some cases, AI can detect patterns in sensory data that reveal signals beyond the boundaries of normal human perception. For example, sensors embedded in a storage tank may be able to recognize concentrations of different chemical elements stored in the tank. This type of data can then be fed to a machine learning model to evaluate the impact of those elements on the health and durability of the tank.
Companies can also use sensing to determine where to drill. For example, geophones are ultrasensitive devices that send sound waves into the earth and record those that rebounce. Deep learning is then applied to this data to generate reservoir predictions and mitigate risks and potentially reduce drilling costs.
Other AI systems will be able to monitor drilling and pipelines to identify potential issues, automatically shutting down operations ahead of potentially catastrophic — and costly failures.
2. Development & Analysis
AI tools can not only analyze and process large data sets faster than traditional statistical approaches, but they can also identify patterns in the data that would escape human analysts. An intelligent system could automate the process of identifying and tracking the movement of personnel around worksites, helping to optimize safety, identify opportunities for training, and improve efficiency.
Oil and gas consistently underperforms on a return on asset (ROA) basis. Companies will be able to use the data generated by their own assets to improve efficiency. This increased efficiency will translate to greater predictability in exploration, accuracy in drilling, efficiency in production, and reliability in maintenance, throughout refining, and optimization in transportation and distribution.
AI and big data are also expected to have the ability to map and identify oil and natural gas deposits beneath the earth’s surface to drill for hydrocarbons using autonomous surface robots on oil and gas sites.
Another application for AI will be to automate mundane and repeatable processes that require limited cognitive attention. For example, an AI robot will have the ability to carry out inspections, during the day or night, which are currently performed by humans. Predictive-maintenance algorithms will then be linked to real-time deployment of maintenance teams so that there will be instant access to information for frontline decision makers.
An AI on-site chatbots could be used to receive unstructured input from operators in the field when performing maintenance work. The chatbots’ AI can then analyze the issues and offer effective solutions based on an archive of expertise and insight.
3. Enhanced Decision Making
The oil and gas industry requires a holistic view of the data to improve their operations from upstream to midstream to downstream. Organizations will use AI data to understand how opportunities and threats are evolving — to allow quick and appropriate responses.
AI can increasingly perform tasks that were previously done by humans, freeing them up for higher-value activities and better decision making. This leads to exponentially higher efficiency, which then allows employees to focus on high value optimization activities such as future predictive and creative decision making.
4. New Job Categories
Within ten years, oil and gas companies may be employing more data scientists than geologists, as there is a new demand for data scientists, statisticians, and machine-learning specialists. Entire new job categories, such as next generation programmers, data scientists and engineers, trainers and managers for robots, AI solution architects, and intelligent system monitors, will emerge.
The AI revolution is expected to reform all sectors of the oil and gas industry, from upstream to midstream to downstream. It is undeniable we are in the middle of a paradigm shift – and its effects will be transformational. The players of today may be the players of yesterday if they resist investing in what is seen as the bright future of oil and gas thanks in large part to big data and AI.