As in science and engineering, the domain includes

   As Oil remains one of the most highly valued commodities in the
energy sector and as concerns over the environmental impact of energy
production and consumption persist, oil and gas companies are actively seeking
innovative approaches to achieving their business goals while reducing
environmental impact.

            
Another issue in oil and gas industries is Hydrocarbon exploration, the
ability to map and identify oil and natural gas deposits beneath the earth’s
surface, is a growing area of focus in the oil and gas industry. However, more
innovative and environmentally-friendly methods of achieving improved effectiveness
and efficiency are needed in the field. Environmental
conditions are increasingly challenging for workers conducting hydrocarbon
exploration thus technology capable of handling the task while retaining
optimal functionality is highly desirable.  

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           As a
result of that during
the last two decades, the petroleum industry across the world has experienced a sharp increase in the number of artificial
intelligence (AI) applications. This upsurge in the number of applications of
AI is due to the greater availability of human experts.

             Artificial Intelligence has been
defined as “the ability of the machine to
perform at the level of human expert”. Rooted in science and engineering, the
domain includes machine learning, natural language processing, pattern
recognition, search, inference, and
planning. It is devoted to designing ways to make computers perform tasks that
were previously thought to require human intelligence.

              AI studies are broadly classified
into two main categories;

1.      Studies that try to mimic the
operation of human brains known as Artificial Neural Network (ANN)

2.      Studies that understand and apply
thinking methodologies is known as classical Artificial Intelligence.

   

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