Thursday, December 1

How the oil and gas industry is using analytics to improve exploration



The economic shocks stemming from the complex landscape caused by the COVID-19 pandemic and exacerbated by the crisis in Ukraine have challenged leaders of all companies in the oil and gas sector to find more efficient ways to do more with resources. existing assets. The pandemic has brought great volatility to the market, with investors much more cautious. Escalating supply challenges are forcing companies in the oil and gas sector to look for new ways to extract resources and improve exploration in the fields.

The key to being able to maximize production in this industry is not just having access to the right data, but knowing how to get the insights it can generate. These insights range from discovering promising assets and fields, to prevailing trends to make more accurate predictions, to geologies most likely to be roadblocks. Similarly, it is essential to have a clear understanding of geophysics, engineering and logistics. Resistivity data, gamma rays and other analyzes of rock properties, for example, help identify minerals, fluids and structures deep down.

Leveraging this large volume of data in an optimal way can help the company in this area improve drilling technique and extract more oil, leading to more favorable fuel prices and consequently a healthier global economy. increasing investor confidence. Today, some analytics platforms can provide access to various innovative tools, such as:

Immersive visual analysis

Through a single-pane-of-glass experience, this solution offers point-and-click visual analytics, data discovery and insights, presenting clear pictures of real-time and historical data critical to drilling decision making.

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mods

Used to create innovative visualization and analysis applications, mods allow easy access to custom features and strong interactivity, as well as visualization libraries, APIs, and workflows.

Integrated interactive AI and data science

Identifying unique patterns and anomalies in the data stream through intelligent analytics allows proper precautions to be taken. Custom expressions and data functions make it possible for the company to manage and write scripts using R and Python languages ​​without having to deal with difficult coding. As a result, end users can take advantage of these features graphically and without coding.

Real-time streaming analytics

Data is never static. They constantly flow, making it difficult to get the information that can help the company to operate better. Bringing all the data together in a single tool to analyze and digest streaming and historical data can be critical to keeping your business on track in this ultra-competitive market.

Sen geoanalysis

Multi-layered map charts can provide deeper insights into exploration locations, while real-time data lets you recalculate models and update plans in real time.

data dispute smart

Data orchestration capabilities deliver all data through the fastest possible methods, pulling information from multiple sources. Data is automatically recorded, shareable and editable, simplifying future changes and audits. Basic tasks like AI-powered “smart joins” are automated to ensure data preparation is easy.

All of this is not just a theoretical concept, but real industry solutions that are already transforming operations in the oil and gas sector. One of the organizations that customize views for faster and smarter analysis is Petrobras. The company needed an easier way for business users to access and view well log data.

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Adopting a new analytics platform provided the insights needed for reliable, data-driven exploration, allowing the company to reduce costs, speed up field exploration and improve IT infrastructure. The significant decrease in geological hazards was supported by technologies such as 3D seismic, core data correlation, and geostatic simulation.

Now, Petrobras users can fully view well logs within the analysis platform, allowing them to make the right strategic investments and improve oilfield management. The company was able to reduce reservoir modeling steps by 80%. It’s an example of how a robust data analytics solution is critical to ensuring professionals and stakeholders have the data they need to make smart, actionable decisions.

By Jorge López, VP Sales Latam, TIBCO






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