Here is a guest post from Jake Goodman, freelance writer for online technology magazines.
With all the issues that have been surrounding global energy, a huge amount of pressure has been placed on the oil and gas industry to find new fields to explore as well as fully extract fossil fuels from wells. Regulations on production are constantly changing because of the rapid advances in the technology for extraction, and the demand for environmental protection is at an all-time high. In order for these companies to make well-informed decisions, high volumes of data need to be collected and analyzed, and from there they’ll be able to figure out what strategies to implement.
Data mining has become extremely important for oil and gas firms, with Drillinginfo’s director of data inventory John Fierstien even claiming that no one else has collected more data than the oil and gas industry, in terms of both volume and detail.
Recently, Norwegian company Ziebel announced that they gathered 1,708 terabytes of data over a period of eight months, a record breaking collection and transfer of data in global fossil fuel production. Using their unique Z System, the data compiled gave them insight on various business segments that were “applicable to well flow optimization, integrity risk control, reservoir modeling, and enhanced oil recovery, with interruption in production kept to a minimum.”
At the Offshore Technology Conference (OTC) in Houston that occurred early May, GE shared with fellow participants that had spent $1 billion over the last three years on a software center in California, where they learned how to optimize efficiency in equipment usage. They also explained to fellow participants the amount of potential that derives from big data, saying that big data analytics could foster the extraction of 80 billion barrels, which is equivalent to three years’ worth of global crude production.
Although more firms around the world are utilizing big data to give themselves a competitive edge, data mining isn’t commonly practiced in the Middle East. Three power plants are currently being built for South Oil Company in Iraq which could benefit from data mining as it would minimize obstacles in operations while preventing negative environmental impact. Adopting big data would also address future staff shortages and counteract the volatility of oil price, in turn increasing production by 8 percent, according to consulting firm Booze Allen Hamilton.
As the former business and technology editor of his university paper and a graduate of a prestigious computer science program, technology has always been his passion. He is currently freelancing with several online technology magazines while he waits for his internship to start in the fall.
Updated July 12th.
Our next Swiss Analytics Event, June 18th 6pm in Lausanne, is about text mining. Here is the program:
Tailor-made vs. off-the-shelf – A simple method for personalization in information retrieval (Melanie Imhof)
Abstract: The ever-increasing amount of unstructured data makes it not only difficult to find relevant information but also to formulate specific, non-ambiguous queries. Information retrieval systems generally apply the “one size fits all” paradigm, where… Continue reading... | 5 Comments
There are very few books available discussing general aspects of ensemble methods. One of them is Ensemble methods from Seni, Elder and Grossmann. It provides a high level overview of ensemble learning. However, the book contains a lot of equations which make it hard to read from beginning until the end. You will rather pick a few sections and read them independently.
Richard Boire recently published Data Mining for Managers – How to use data (big and small) to solve business challenges. The particularity of this book is to bring a new (non-US) view of the field. What I mean by “new” is that examples and case studies are from Canada and thus not appearing in other data mining books.
Data Mining Research (DMR): Could you introduce yourself to the readers of dataminingblog.com?
There are at least four kinds of books within data mining field. The first category focuses on theory and algorithms. The second one deals with specific tools and languages. The third class is for Management and C-level. The fourth group is concerned with practical applications and guidelines. Dean Abbott’s book, Applied Predictive Analytics – Principles and Techniques for the Professional… Continue reading... | 5 Comments
Let me welcome Amit Kumar for a guest post on Data Mining Research. Thanks Amit for your content.
Business analytics give arrangements which help to settle on key choice and business strategies by gathering expansive data and information. You would find that it does have not simple but complex data like profits, losses, transactions, marketing return, customer feedback and so forth. Normally business analytics programming is utilized to create… Continue reading... | 603 Comments