There's been a lot of buzz lately about "big data" - how it will revolutionize the world by helping businesses understand customers, make better products, and capture more opportunities.

In the oil and gas industry, though, big data is not a new concept. Just ask a landman who has sifted through decades of land lease deeds in a county courthouse. Or a geologist mapping plays using spreadsheets and surface maps.

The processes and procedures in the industry have long been based on the collection and analysis of data, starting in the 1920s with the use of the seismograph to create subsurface maps to today's digital oilfields where every single piece of equipment relays data back to headquarters. With nearly two million active wells in the US and 700,000 elsewhere in the world, the volume of data being collected is growing exponentially, and these data are critical to help the industry:

• Discover new reserves
• Save money on drilling and exploration
• Increase efficiency and productivity
• Match supply to demand
• Improve profit margins
• Leverage technology for greater efficiency

Yet taking full advantage of data isn't easy, as it is collected from various sources that don't "talk" to each other, rendering it difficult to manage and analyze. In fact, some data collected aren't digital. It can take weeks or months to standardize, audit and edit data so that it is actionable for you. A quick review of potential sources includes both digital and paper copies of government records, legacy files, service providers, technical papers, operator reports and regulatory agencies, company investor relations presentations--just to name a few. Each one represents valuable insights and aggregating them creates an even greater treasure trove of essential intelligence. However, traditional spreadsheets are quickly overwhelmed by so much input and not all digital applications can adequately organize and synthesize so much raw material into meaningful results.

Rather than getting to the business of drilling wells, companies are wasting time looking for data and managing the information, exacerbating a major loss factor for companies--non-productive time. Plus, they miss out on data-driven insights that might impact decisions. When workers in the field are delayed waiting for data, the costs can be astronomical - costing companies up to several million dollars per day. Unfortunately, many organizations using mismatched sources of data still rely on practices and tools that bog down workflows and create bottlenecks.

Choosing a Data Provider

If data is the foundation of decision making, then accuracy and reliability are as important as the ability to analyze and interpret the data. Choosing a data provider that has already aggregated data from various sources can alleviate the inefficiencies and inaccuracies of "do it yourself" data. However, not all databases are the same, and certainly the providers are not either. Look for the following qualities when choosing a data provider:

• Analytic and scientific rigor - There is plenty of data that are available at no cost. If you are paying a provider, be sure that they are earning their keep with data that are collected from a wide range of sources, have the appropriate historical data, and have been audited, edited, researched, and standardized. Rigorously compiled data dramatically reduce risk because your analysis is more likely to be quality-controlled-meaning more accurate, complete and timely.
• Data expertise - Not all data providers are equal because some are more focused on other oil field services with data as an add-on rather than a specialty. How long has the provider been in business? How many people are in the data research organization? What is the quality control and data maintenance process? When investing dollars in information, you want as much as you can get in as much detail as possible. For example, lease data without assignments does not provide a complete enough picture to move forward with a play. It's then necessary for a landman to visit a courthouse to search through documents to flesh out critical information. This slows down the process, adds cost and leaves opportunities open for the competition.
• Actionable data - Because data are collected from various sources, data also come in various formats. Look for a database that is standardized and can be manipulated for countless scenarios. For example, the data on static images of leases and documents can't be used to automatically create maps of current leasing positions or identify potential open or unleased acreage. The data would have to be entered manually, which takes time, adds cost and increases the chance of error.

The oil and gas industry is complicated. Clean, more complete, actionable data can help companies make better decisions regarding acquisition and drilling for more profitable outcomes.

Visit our website to learn more about the range of oil and gas data solutions offered by IHS Markit. Want more details on our land and lease data? See details.

Stephen Trammel is Director, North America Well and Production at IHS Markit.
Posted 22 February 2017

This article was published by S&P Global Commodity Insights and not by S&P Global Ratings, which is a separately managed division of S&P Global.