GPU-Accelerated Analytics for the Energy and Oil & Gas Sector

With increasing demands to cut costs, optimize investments, and reduce risk, smart companies in the energy sector are turning to Kinetica for analytics on real-time data. Make sense from large volumes of streaming machine and sensor data for upstream, midstream and downstream use-cases. Kinetica's faster data processing and visualization tools make it possible to discover patterns, and uncover hidden insights in sub-second rather than minutes or hours.

Used By:

Streaming Analytics Database with Native Geospatial Pipeline

10x-100x faster query on 1/10 the hardware, compared to even the most advanced in-memory analytics systems

Lightning Fast Query

In tests, Kinetica returns results for advanced analytical queries on billions of rows of data in well under a second.
Fast Query on GPU »

Ideal for Streaming Data

Parallel ingest and reduced reliance on indexes means data on Kinetica is available for query the moment it arrives.

Augment BI

Business users can easily write queries with SQL, integrate Kinetica with retail BI tools or access via a comprehensive set of APIs.
Accelerate BI »

Geospatial Visualization

Visualize patterns on geospatial and temporal data. Kinetica harnsses the GPU for query and drawing geospatial display of vast volumes of data.
Location-Based Analytics »

Real-Time Analytics for the Energy Sector

Kinetica transforms energy and petroleum data into actionable insights and increased business value

Oil & Gas Exploration and Production (Upstream)

There are several areas where Kinetica can be deployed to drive greater efficiency in the energy industry. For example, oil and gas companies need to be able to leverage real-time pipeline, well, and spatial data to determine the most viable oil fields for exploration, to remotely monitor drilling and production performance, and to prevent safety and environmental issues. By using Kinetica’s visualization tools, these companies can perform a faster and richer analysis of seismic, drilling, and production data in order to improve geologic analysis, reduce exploration risk, increase drill and production performance, and improve oil market forecasting.

Energy Service Providers (Midstream)

The midstream component of the petroleum industry involves the transportation, storage and wholesale marketing of crude and refined oil and gas products. Kinetica’s native visualization and geospatial tools make it possible to provide these midstream companies, such as those that build the vast networks of oil pipelines, with the ability to analyze comprehensive data sets for pipeline oil pressure monitoring, supply/demand forecasting, and real-time visualization of pipeline operations. Other midstream players, such as energy traders, rely on real-time analysis of energy market data and asset sensor data to respond to rapidly changing market conditions.

Smart Meter Analytics (Downstream)

Discovering new value from high volumes of streaming IoT data is one of the biggest opportunities in energy today. Energy companies can utilize smart meters to measure how energy resources such as electricity, water, and natural gas are being used. Kinetica’s ability to process streaming data and multi-billion row datasets in real time makes it a perfect solution for analyzing smart meter data to optimize energy generation and uptime, predict and prevent power outages, chart energy trends, understand customer energy usage, and improve load forecasts.

A large electric utility uses Kinetica for geospatially visualizing smart grids, while ingesting real-time data streaming from smart meters. Kinetica’s GPU-accelerated OLAP database with built-in visualization can be used to plot billions of data points and monitor meters, power plants, distribution infrastructure, weather, service vehicles, outages and customer feedback—all in real time. By consolidating data silos and synthesizing the vast amount of location-aware data, utilities can optimize energy generation and uptime.

Equipment, Fleet, and Workforce Management

The analysis of streaming data plays a key role in monitoring and maintaining equipment in the energy and petroleum industries. Oil and gas companies can analyze sensor data from equipment and wells to avoid the downtime, costs, and safety issues that stem from equipment failures. Utilities can analyze electrical transmission, electrical distribution, gas distribution, gas transmission, and power pole data to predict, analyze, and minimize failures. In addition, “breadcrumb data” from maintenance personnel devices and service vehicles can be tracked to find the closest crew to a trouble call, identify the most efficient route, predict vehicle maintenance issues, and reduce emissions.