Six Ways Prescriptive Analytics Can Improve Energy Exploration and Production

Given all these data types, here are six practical ways Prescriptive Analytics with Hybrid Data can be used to make the Oil and Gas industry more efficient and more productive:

  1. Predict performing and non-performing wells by developing detailed analytical signatures – using data from production, subsurface, completion, and other sources – that lead to high-producing and low-producing wells.  Once an energy company has developed these fact-based signatures, it can avoid drilling wells that are predicted to underperform and focus its precious resources on wells that are predicted to outperform expectations.
  2. Improve performance of Electric Submersible Pumps (ESP) by predicting failures using data from pumps, production, completion, and subsurface characteristics, and prescribing actions to mitigate production loss from the predicted pump failures.  The software also predicts and prescribes the right pump for the right well, and helps identify fields with the greatest potential for production.
  3. Predict corrosion development in pipelines and prescribe preemptive/preventive actions.  Prescriptive Analytics with Hybrid Data can take into account all the data from Smart Pigs and soon-to-be-installed video cameras inside pipelines to predict development and progression of corrosion, cracks, and related issues – and then prescribe suitable preemptive actions to avoid downtime and environmental hazards.
  4. Improve fracture and production performance in unconventional wells by holistically taking into account different data sources and data types. Prescriptive Analytics can automatically interpret sounds from fiber optic sensors, images from well logs and seismic reports, videos from down-hole cameras, text from notes made by drillers and pumpers, and numbers from production and artificial lift data. Then it can combine these datasets to predict frac (and thus production) performance and prescribe how to improve this predicted frac and production performance.
  5. Provide automatic well log digitization and interpretation at a fraction of the cost and the time.  This “Sweet Spotting” capability can support multi-billion dollar investment and drilling decisions.  Software today can automatically and accurately digitize and interpret a well log in just a few minutes.
  6. Support horizontal drilling and hydraulic fracturing operations by automatically interpreting real-time sound (from fiber optic sensors) and video (from down-hole and other cameras) data.

Prescriptive Analytics is in the early stages of deployment as many companies begin to evaluate and apply the technology to their needs. For example, Apache Corp. is using Prescriptive Analytics to improve ESP performance. Shale oil producers in Texas are considering Prescriptive Analytics for several of these six applications. Interesting times for big data analytics in the oil patch!

By Atanu Basu, Ayata CEO

Atanu BasuSix Ways Prescriptive Analytics Can Improve Energy Exploration and Production

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