There’s no doubt the data produced in oil and gas is vast and valuable. Harnessing this data requires advanced techniques and tools, but by taking advantage of these, organisations can see significant improvements in their field planning and optimisation processes.
Where is big data used in oil and gas?
The amount of data collected by oil and gas organisations is extensive. It’s collected from many different sources in the upstream stage, including sensor data, seismic data and geolocation data. What’s more, these datasets span both public and private data sources.
What are the benefits of using big data?
If organisations can harness their massive and continuously evolving datasets, they can significantly improve decision-making. When applied to field planning and optimisation, this data could help them produce new solutions, enhance ROI and transform production.
However, it needs to be properly organised and aggregated before organisations can think about harvesting these possibilities.
This is where challenges are introduced.
Firstly, the huge volume of data makes analysis extremely slow. The memory and power constraints of traditional tools creates an unacceptable lag between data collection and data insight.
This puts organisations at a competitive disadvantage, as opportunities for field development, new well sites, acquisition opportunities, and so on, can’t be assessed reactively and may be acted upon too late.
Secondly, the disconnect between data sources is difficult to manage with traditional tools. These natural silos can’t be easily overcome, meaning organisations cannot analyse their full suite of available data in context, limiting their insights overall.
What are some use cases for big data?
The Brytlyt platform can help oil and gas organisations overcome these challenges and capitalise on their data for upstream use cases. Combining all data into one business intelligence tool, accelerated by the power of GPU, Brytlyt offers a highly valuable and responsive data experience.
Here are some applications for massive datasets in oil and gas:
Optimise well placement
Organisations can use data insights to pinpoint the most profitable locations for new developments. They can do this by considering both geospatial data as well as predictive data regarding value over a project lifecycle.
Maximise existing site value
Large datasets, through analytics and visualisation, can provide insight into how to optimise existing sites and streamline their operations. Users can analyse data to identify barriers to productivity and address these in real-time. By improving production efficiency, costs will also be reduced.
Improve production allocation
Using modelling and predictive analytics, organisations can optimise production allocation. Visualisation tools will allow them to view future trends and patterns and make informed decisions accordingly to optimise ROI.
Read more about how Brytlyt supports greater insights from massive datasets in our real-world use case example.
BI in Upstream Oil and Gas
Field planning and optimisation
