4 min read
This blog post introduces key concepts from the MapR Guide to Mining, Oil, and Gas. To read more, you can download it here.
Oil and gas companies have more choices than ever before as they try to better leverage information to compete and to survive. These choices are driven by trends, including: the proliferation of IoT devices, sensor miniaturization, and faster, cheaper storage and compute. Artificial intelligence (AI) and machine learning (ML) are also coming into the mainstream.
Here are 5 key aspects that I believe the oil and gas (O&G) industry cares about, which help to maximize production and improve operational excellence:
There should be ample opportunities to make each of these more efficient with time, given that relevant data from previous oil exploration activities is stored in historians, right? Somewhat right.
Historians have traditionally always had a few limitations. For example: (i) they are limited in storage capacity, leading to users sacrificing on data fidelity and limiting usage of data to simple visualization, (ii) they lack real-time processing capability to support predictive models, and (iii) they often don't support unstructured or semi-structured data.
The other limitation is the difficulty of bringing data that is constantly generated onboard the rigs, onshore and offshore, to a central cloud infrastructure. With sensors that are miniaturized and ruggedized enough for deployment aboard the rigs, the industry is now looking for robust and intelligent edge solutions – solutions that can accumulate data from these sensors, send just the "meaningful" data to the cloud, wisely split portions of machinelearning techniques between edge and cloud, and execute the decisions resulting from those techniques.
It suffices to say that most O&G companies are looking to build their "digital oil field" to handle large volumes of complex well, seismic, and machinery data with the intention to generate actionable insights, such as predicting pipeline leaks, identifying aging wells, and identifying new oil reserves at lower costs.
The O&G industry today is all about data-driven growth, not simply finding reserves and sinking new wells. Without the proper platforms for analyzing highly complex data sets in huge volumes, a predictable business in an environment of uncertainty in crude oil futures and price volatility is not possible.
Enter MapR for the oil and gas industry.
The following table provides the reader with a unique perspective on how MapR is helping our oil and gas customers achieve real results, using data-driven usecases:
Now, let's take a look at some pain points MapR has heard about from our O&G clients and how we solve for them..
Shown below is a high-level diagram of the MapR Data Platform, applied to the O&G industry vertical.
For more information on the MapR Data Platform and its applicability to the oil and gas industry, please read the MapR Industry Guide to Mining, Oil, and Gas.
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