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Analytics in Energy And Resources

Challenges faced by Companies in Energy & Resources sector

The decrease in oil costs and oil-delivering nations taking a cut in the pay and gain as the world is climbing into the time of these two elements. Stress can just mount further with offers of value improvement. Practically every one of the wellsprings of petroleum derivatives, sun oriented energy and Energy and Resource Analytics are quickly diminishing. Excessively exorbitant and requires new advancements are the providers for recognizing, getting to and creating other sources' fuel.

Every one of the Governments are influencing the cutting of fossil fuel byproducts thus that organizations are compelling their energy space to chop down the emanations. Before the finish of 2030, the organizations will widen their Data Science specialists by 1.1Billions residents. Greater power and more vehicles are adding oil to their industry issues. Raw petroleum is one of the huge jobs in transportation. The answer for these issues is mindfully created, which is the new standard of the day.

Case Study 1:How to improve temperature gradient in a Forced draft heat exchanger by increasing surface area of finned tubes
Business Problem Statement

In middle eastern countries where water is scares, the cooling water is recycled in the power plant. However, to recycle the cooling water the temperature of the same has to be considerably brought down, as this sometimes acquires temperature beyond boiling point. The hot water is passed through bank of finned tubes which is subject to a forced draft of air by fans from below.

Business Challenges

  • During extreme summer period, the heat recovery of the cooling water is greatlyreduced
  • Reduced effectiveness of total energy cycle and increased energy cost
  • Incidence of downtime due to excessive heating

Business Solutions

  • Various input parameters were measured that have an effect on the heat loss
  • Simulation techniques were used to study the cause-effect relationships by tweaking the various parameters in the heat cycle system
  • As part of the maintenance, the blocked tubes were routinely removed and fresh ones replaced; the finings on these tubes were increased based on the mathematical model prediction so as to compensate for the additional weight on the system and improved cooling efficiency

Business Impact

  • Improved heat reduction
  • Reduced cost for larger heat recovery
  • Improvement process was carried out during downtime maintenance to Heat Exchanger, thereby increasing the availability of machines by reducing separate downtime

Case Study 2: Want to know on how to identify the optimal route to transport crude oil to factory
Business Problem Statement

Communication/mobility is directly proportional to the growth of economy. Crude oil plays a major role in transportation. Refineries are losing a huge portion of their margins in the transportation of crude oil. They are also losing the time resource as well as human resource while dealing with the shipping of crude.

Business Challenges

  • Increase in cost of transporting crude oil to refineries
  • Unable to identify the ride mode of transporting crude oil
  • Unable to identify the delay in transportation

Business Solutions

  • Applied data optimization & network analysis to effectively identify the most appropriate route for transportation
  • Applied machine learning techniques to identify the most appropriate mode of transportation
  • Built prediction model & used survival analysis to predict the delay in transportation

Business Impact

  • Reduced the transportation cost
  • Reduced the time taken for transporting crude oil
  • Reduced the cycle time of up-stream to down-stream

Case Study 3:How to predict equipment failure to prevent losses
Business Problem Statement

One of the most challenging tasks of an oil company is to prevent oil spill/leakage. It not only effects the profit margins of the company, but also poses a threat to the eco-system in that drilling areas. Huge amount of resources is wasted out due to the leakage, and thus resulting in hampering of the entire drilling process.

Business Challenges

  • Losses due to equipment breakdown in oil drilling
  • Delay in the drilling of crude oil until the equipment is repaired or replaced
  • Under-utilization of labour due to halting of drilling process

Business Solutions

  • Predicted using machine learning algorithms on whether the equipment will breakdown or not
  • Used survival analysis to predict on when will the equipment breakdown
  • Sending proactive alerts on when maintenance of equipment should be scheduled

Business Impact

  • Reduction in repair costs of failed parts of equipment due to proactive maintenance based on failure prediction
  • Reduction in oil production downtime due to equipment failure

Case Study 4: Predict Electricity Production based on increase in Urbanization
Business Problem Statement

Most countries across the globe are facing challenges because of incorrect forecasting of electricity required to serve the people & industries to maintain a balanced growth of economy. Lack of forecasting the urbanization is leading to incorrect electricity needs thereby leading to incorrect forecasting of GDP & economic growth of nations.

Business Challenges

  • Low energy production leading to huge impact on industrial areas, thereby impacting the GDP of the nation
  • Excess energy production leading to unused power being sent back to grid leading to loss of energy and resources
  • Unable to sustain the economic growth because of inability to cater to the needs of growing urban population

Business Solutions

  • Predicting the population growth in urban regions
  • Given the population growth, predicting the amount of electricity required to meet the households demand
  • Predicting the number of new industries which might be required to setup to generate employment for the growing population in urban regions. Thereby predicting the electricity usage for these new industries setup

Business Impact

  • Appropriate electricity generation leading to reduced cost of operations
  • Ensuring that the households get the appropriate power leading to reduced inconvenience
  • Ensuring that industries get the appropriate power leading to higher productivity & thereby profits
  • Increased happiness index of the citizens

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