In the last decade, we have seen a record-breaking global interest in artificial intelligence (AI) by governments, corporations, and hobbyists. In 2018, Forbes published a piece that shed light on the urgency for corporations to adopt artificial intelligence and its significance for infrastructure leaders. While some organizations (mostly tech companies) are fully aware of the potential competitive advantage with the adoption of AI, many non-tech companies still trail in the automation race and are slowly losing competitiveness. Digital transformation and technical creativity have been the major causes for the steady increase in churn rate among S&P 500 companies. This churn rate is only set to receive a boost with the varied adoption rate of artificial intelligence.
Artificial intelligence is a field of study that deals with the theory and development of machines that mimic cognitive functions that humans associate with intelligence such as learning and problem solving. Artificial intelligence has received a lot of publicity in recent times due to breakthroughs in the sub fields – machine learning and deep learning. Deep learning, the area of machine learning concerned with autonomous and semi-autonomous learning of data representations as opposed to task-specific algorithms, has particularly generated a lot of interest by researchers, engineers, scientists, entrepreneurs, and investors mostly due to the role it has played in achieving above human performance is many cognitive tasks like computer vision, speech recognition, natural language processing, social network filtering, board games, robotics, autonomous vehicles, and many more.
The oil and gas industry has historically been a slow adopter of new technologies owing to the high risks involved with the exploration and production of crude oil and natural gas. Nonetheless, the oil and gas industry is a perfect fit for machine learning due to the quantity of data that it generates. The conscious brain can process only about 2000 bits per second (although the subconscious brain processes about 400 billion bits per second), while a single server-side GPU (graphic processing unit) processes over 5000 GB/s (5000 billion bits per second). These GPUs can also be stacked to perform computations in parallel leading to even greater performance. Hence with efficient algorithms, many tasks are just way better suited for machines.
Some of the major E&P companies have realized the competitive significance of leading the race in the implementation of artificial intelligence and have rightly adapted their business models and priorities. Not surprising that the AI market in oil and gas has been estimated to reach US $2.85 billion by 2022. Nonetheless, a lot of organizations still struggle with making and managing the appropriate changes due the scarcity of skilled resources with the relevant cross-disciplinary knowledge.
The potential applications of artificial intelligence in oil and gas is limitless and cuts across all oil and gas strategic business units including geo-sciences, engineering, accounting, legal, logistics, HR, and others. A few areas of application include:
1) Precision drilling and autonomous drilling
2) Data extraction
3) Data mining, analysis and interpretation
4) Inspection
5) Anomaly detection
6) Forecasts and predictions
7) Decision making
8) Systems modeling and development of twin systems
9) Design
10) Logistics planning
11) Daily operations
12) Power management
13) Optimization
Nth DS is one of the leading companies that specializes in the research, development, and implementation of artificial intelligence solutions within the oil and gas industry. We consult and develop AI solutions used by Fortune 500 companies. Our flagship product, Nspect, for geophysical data extraction and digitization, outperforms the previous industry preferred solutions in accuracy, efficiency (speed and resources), and usability.
If you’re interested in staying ahead of, or just keeping pace with the evolutionary curve, contact us and schedule a demo.