Oil and Gas

Transforming Oil and Gas with Enterprise AI

Building sophisticated AI solutions to optimize and strengthen oil and gas operations with data driven insights

The Oil and Gas industry, just like most other industries understands and appreciates the potential of AI and is investing majorly in data technologies to secure and maintain a competitive edge in a fast-changing environment.

Organizations involved in the oil and gas industry are turning towards modern technologies like AI to maximize and optimize their efficiency and revenues on the back of rising oil prices and depleting crude oil levels globally.

Leveraging AI to Explore and Utilize More Efficiently

Powering cutting-edge solutions for Oil & Gas companies by channelling big data

AI is proving to be a real enabler for oil & gas projects offering multiple applications that include reducing downtime for predictive maintenance of equipment, production optimization with computer vision to analyse seismic and subsurface data faster, reservoir understanding, and modelling for predicting oil corrosion risks to reduce maintenance costs.

To make the complex data used for oil & gas exploration and production more reachable, offshore businesses use AI in data science. This allows companies to discover new exploration prospects and enable better usage of existing infrastructures.

Oil and Gas in the Age of AI

Reshaping the oil and gas sector with intelligent analytics

Implementing intelligent algorithms for oil and gas companies that drive customer success

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Industry Problem:
Companies involved in the oil and gas industry leverage AI to drill and mine raw hydrocarbons and other products required to produce fuel. AI helps these companies by developing algorithms that provide accurate and precise intelligence to guide drills on water and land. Precision drilling helps in reducing the risk of accidents, oil spills, fires, and enhances the rate of penetration.

At MAG, we build solutions that can make accurate predictions by aggregating real-time data, providing an administrative dashboard to the organization in charge and enabling them to be more efficient in their drilling process.

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Industry Problem:
AI helps the oil and gas companies in optimizing their production by identifying the areas of inefficiency. AI systems can be trained on large volumes of raw production data that enable the automatic recognition of patterns and refining the data to generate analytics.  

At MAG, we leverage big data to help companies become more efficient with their production schedule by providing a holistic view of all the areas that can see increased efficiency basis the capability available on site.

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Reservoir Management

Industry Problem:
Oil reservoir management involves several technicalities like seismic interpretations, geology, management of reservoir, and production, for which the degree of optimization and maintenance is very high. AI systems can be trained on the data of these technicalities and help in field surveillance, reducing the reservoir maintenance costs, and reservoir engineering, among other things.

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Industry Problem:
Monitoring of oil fields, gas stations, plants, mines, and equipment will ensure the safety of employees and the environment. Accidents can be monitored from AI-powered cameras, robots, drones, among others to reduce the extent of potential damage.

Frequent inspection of equipment and risk assessment will help companies in taking predictive measures to avoid unforeseen circumstances. The implementation of AI-based solutions can lead to higher predictability and major cost savings.

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Industry Problem:
The oil and gas industry are a highly labour-intensive industry, and the employees work in highly uncertain conditions. Automation of tasks can help in saving time, labour, and costs. AI and ML help in automating almost all the routine tasks while identifying the best practices, thereby safeguarding the lives of employees, apart from reducing human errors and increasing efficiency.

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Other Solutions

Apart from Data Consultation, MAG provides solutions across two other business critical verticals

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