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Radometech

AI in "Oil & Gas"

Disruptive innovation in the energy sector is likely to be driven by digital tools bringing together artificial intelligence, machine learning, data analytics, supercomputing and automation.

Business Challenges

 

The gas and oil sector is going through a massive disruption. As the world continues to be dependent on the organic sources of energy, there are micro and macro challenges that are affecting the global industry. The oil and gas industry faces many challenges in its operational processes, ranging from unconnected environments to frequent downtime and maintenance issues for its various machines. Oil and gas companies operate in some of the most physically and operationally challenging environments. Add to that factors such as volatile market prices, fluctuating demand, complex compliance and regulatory regimes, projects that involve multiple third party suppliers.

 

 

 

How can AI help?

Artificial intelligence (AI) is proving to be a cost-saving investment for the oil and gas industry. It is increasingly being used to improve various upstream, midstream, and downstream processes in the industry, from boiler diagnostics to actual drilling. Applications such as quality control, prediction planning, and predictive maintenance for upstream, midstream, and downstream are majorly using AI. AI to extracts information and insights from data, using neural networks to link related pieces of data together and form more comprehensive pictures from existing information. Machine learning can be used to run simulations, using predictive data models to discover patterns based on a variety of inputs. 

 

 

 

Use cases

Automate and Optimize inspection & Maintenance results: During inspection and maintenance, we aim to detect any anomalies that may threaten the operational integrity of O&G assets, still errors and mistakes occur during inspection. Also, O&G companies need to perform optimization of inspection and maintenance plan because performing these activities are costly. Machine learning algorithms provide increased levels of automation in the knowledge engineering process, replacing much time-consuming human activity with automatic and optimized techniques that improve accuracy or efficiency by discovering and exploiting regularities in data. 

 

Defect Detection & Enhance Quality Assurance: One of the challenges in the oil and gas industry is identifying improper threading in pipelines or defects in error-prone mechanisms. Defects found at the end of the production line from upstream issues cost factory and budget resources. AI can verify the quality of production and provide deep insights of defects in analytics. AI powered Defect Detection solutions are cost-effective and is extremely economical in comparison to the prevailing processes.

 

 

Reduce Production & Maintenance Cost: Due to various temperatures and environmental conditions, oil and gas components often face material degradation and corrosion. AI can detect signs of corrosion by analyzing various parameters using knowledge graphs and predictive intelligence to approximate the corrosion occurrence probability and raise alerts to pipeline operators. This way, companies plan and adjust for downtime.

 

Arrive at Better Decisions with Analytics: Oil and gas businesses deal with lots of data coming from manufacturing processes but due to a lack of proper analytics tools, they’re unable to capitalize on the massive data resting in data silos. AI algorithms study various data streams from various sensors and machinery of different plants or entire Geoscience data and extract real-time analytics to generate intelligent suggestions based on business needs. 

 

Enchancing Supply Chain & Logistics Efficiency:  The supply chain for the oil and gas industry is a complex operation where there are several key decision nodes like crude purchase, price of the purchase, transportation to the refinery, refining operations, gantry operations, and retail sale of end products. Application of artificial intelligence and Machine Learning in the supply chain of oil and gas operations plays a vital role which includes Prediction of the market price of crude oil and finished products, proper planning and scheduling, enabling optimization of the crude basket, creating a smart warehouse, maintenance of inventories, handling shipping operations, Risk hedging, and improved delivery times and reduction in overall costs.

 

 

 

Why choose us?

Many oil and gas operators are still uncertain of AI, but these technologies are a perfect fit for the industry. And according to McKinsey’s research, advanced analytics could yield a 30 to 50 times return on investment within just a few months of implementation, because analytics is a perfect solution to oil and gas operators’ thorny multivariable problem.

 

We at RadomeTech believe AI is crucial for every business entity. Thus we have a developed a tool which lets the user have the power of Artificial Intelligence and Machine Learning !

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