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Artificial Intelligence In The Oil And Gas Industry

December 11, 2019
A Pangea SI Expert

Introduction

Today, the oil and gas sector is facing an array of social, economic, environmental and political challenges. Novel technology, including Artificial Intelligence (AI), provides a means to address many of these challenges and help meet the demands of a transitional energy market. AI is set to become a major part of the energy sector, with its value in the petroleum industry alone predicted to be several billion dollars by 2022. In the longer-term, consulting firm McKinsey & Company estimates AI has the potential to create annual value of approximately $200 billion across the oil and gas sector, and $3.5-5.8 trillion of annual value in the global economy.

What is AI?

The term AI was first coined in 1956 by celebrated computer scientist John McCarthy and can be defined as a system capable of perceiving its environment and taking actions to maximise its chances of success. Machines with the capacity to learn in a way that can be compared to processes in the human brain. Thanks to developments in computational power, algorithms, data collection and digitalisation, AI that can mimic general human cognitive capabilities (rather than just make improvements within a single, narrow field) is now starting to become a reality. There is a current debate bridging ethics, philosophy and science around the possibility that mankind could soon create computers that are capable of learning independently at a speed that is infinitely faster than those who created them. For some, the possibilities of unheralded advancement are appealing. For others, the risks that a world totally beyond our control might emerge at an incomprehensible speed are a significant cause for concern.

Industry Challenges

Major issues facing the oil and gas sector include:

Additionally, the finite availability of hydrocarbons means that there are increasingly fewer unexploited accumulations left, whilst those remaining are often more technically challenging to produce or are in difficult locations, for example, the Arctic. “However, the biggest short-term challenge is cost reduction and AI will have a positive impact on it.” All in all, fossil fuels are set to play a major role over at least the next few decades as energy demand continues. To survive in this challenging climate, oil and gas companies must embrace new technology, including AI, to maximise efficiency and revenue.

“…the biggest short-term challenge is cost reduction and AI will have a positive impact on it.”
Speak to the economics and petrophysics who quoted this Expert Bio Expand

Expert Bio:
This Pangea SI Expert has spent the last 3 years in Data Analytics, Artificial Intelligence and Machine Learning techniques applied to economics and petrophysics.

With over 30 years’ experience in international Oil Majors and Oilfield Services Companies, including 21 years’ experience in Senior Petrophysicist roles in both the exploration and production of hydrocarbons.

Said Expert has been involved in:
– the discoveries ranging from multi-trillion Cubic Feet (Tcf) gas to Million Barrels (MMBls) oil in South America, to the development of rich Gulf of Mexico (GoM) and heavy oil reservoirs, both in clastics and carbonates.
– exploration projects in Peru, Brazil and Guyana – part of a team responsible for:
– the discovery of commercial accumulations in the Santos basin; increased production in Peru assets.
– supporting all aspects of reservoir management, monitoring, simulation and reserves certification.
– the interpretation of US Midcontinent logs for clients – part of teams that performed field studies from large (800+ wells) to small projects.

Their geographical expertise has spanned GoM, Louisiana, Oklahoma, Alaska and North/South America, as well as South America – specifically for real-time exploratory wells support.

Having implemented novel techniques for integrated Core-Log pay estimations, as well as implementing the first deviated borehole stability calculations, this Expert has been responsible for:
– the testing and implementation of new Nuclear Magnetic Resonance (NMR) techniques.
– integrating NMR with conventional logs, as well as implementing new acoustic interpretation methods, particularly Stoneley wave applications.

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The Solution

What are the applications of AI?

If you would like to speak to either of the Experts who contributed to this article, or other require other AI specific expertise, please reach out to Mr Callis on 020 7551 0782 or by email mike.callis@pangea-si.com.

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