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Selection time for workover candidate reduced by 89% for PGN Saka

Using AI embedded in digital solutions from Schlumberger, PGN Saka automated its well workover and intervention programs to vastly accelerate the selection process. The automated system screens and ranks high-well-count assets in a fraction of the time to detect, diagnose and recommend the appropriate actions required to ensure that wells remain healthy, for an evergreen opportunity pipeline.

PGN Saka fast-tracked workover candidate selection. What will you change?

PGN Saka

“They performed full well optimization, workover and intervention across 196 completions weekly, compared to yearly on the previous manual review.”

– Excerpt from joint PGN Saka and Schlumberger technical paper published in World Oil, June 2020
AI Embedded

AI embedded digital solutions

PGN Saka used a hybrid physics- data-centric automated decision support system anchored in a knowledge-based framework to identify well performance signature and opportunities that we best aligned with the operator’s economic considerations. Machine learning (ML) models ensured the system keeps improving as decisions are made.

AI Working For You

AI working for you

The data science profile in the DELFI cognitive E&P environment enables customization of AI-powered well portfolio optimization systems by petrotechnical engineers.

 

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Read the full World Oil Article on PGN Saka’s AI system

In June 2020 World Oil published a detailed technical paper on PGN Saka’s use of AI to accelerate its workover selection program. You can read the full article by clicking the link below.

Read the article