Applying Data Science to Solve Frequent Exploratory Issues

We solved the downhole problems of lost circulations and lowered the unmanaged well cost

Discover the power of Data Science in resolving frequently occurring exploratory issues. At Bizmetric, we leverage cutting-edge data science models to tackle complex challenges head-on. Explore our case study to see how we harness the potential of Data Science to provide innovative solutions, driving efficiency and informed decision-making.

About the Industry

Adapting and positioning are the two factors that help energy companies sail through the volatile market condition. While many elements shape the industry’s future, infrastructure has always been an underserved entity. Along with improving the existing network, top energy players are now focusing on infrastructure modernization. An upgraded setup has helped the industry deliver results in a faster time frame. Walking through the trends, the inception of IoT has improved the quality of systems and hardware integration, resulting in better connectivity. The improved solution implementation will completely eradicate the downtime and machine replacements issues in the days to come.

About the Client

Our client is a multinational energy giant. Along with the business in hydrocarbon exploration and production, they have successfully engaged themselves in the transportation and marketing of finished carbon products. With a profitable business expansion in the competitive market of Southeast Asia, South Korea, and Australia, they have adopted the latest engineering mindset of operational diagnosis to achieve the complex business need.

The Business Challenges

Our client was struggling with the following operational challenges:

  • Unavailability of the historical wells and their associated data such as mud reports, drilling information, and average throughput values was an alarming concern before our client.
  • They failed to identify the root cause of the problems like lost circulation events, tripping issues, and rising downhole cases.
  • Lack of accuracy in the drilling proposals and service cost forecasts for the offset wells impacted the customer engagement scenario.

The Business Solution

  • We explicitly analyzed the data collected from the offset wells that were under operation. Our technical experts from the energy domain created more feasible and data-driven development plans and deployed various predictive methods in preparing an effective drilling proposal.
  • In the next stage, we analyzed different parameters of the wells under excavation. Factors such as the apparent viscosity, electrical stability, lubricity coefficient, % improvement, etc., helped gather large data sets. Our data management team applied predictive models on these data and succeeded in predetermining downhole problems before their actual occurrence.
  • An in-depth analysis of the upstream data ensured our client selects the most optimum drilling fluid chemicals and that too in the right amount.

Key Results

  • We marked an overall improvement in the drilling operation. Reduced cost, zero downtime, and easy-to-implement risk mitigation strategies were some radical improvements that our client witnessed.
  • An accurate pre-drilling proposal helped our client manage the future expenses and plan out the investment accordingly.
  • Our client noticed a remarkable improvement in customer engagement. They guaranteed victory in winning the trust of the service provider associates by meeting their complex business needs.

For Data Analytics

Contact Us

Looking for similar solutions

Talk to our Experts
Check Also

Related Case Studies