The Downside of “Free”
Maps and charts are the lifeblood of the oil and gas industry and most petroleum executives crave the ability to visualize exploration maps in a dashboard format. The advent of free applications such as Google Earth has made complex imagery available to everyone, and while this online tool has raised awareness of the “power of the image,” it have also created confusion. For example, one cannot judge the precision, vintage, spatial accuracy or resolution of a given image merely by inspection. “Where is that well we drilled last year?” you might reasonably ask. Having the answer to critical questions is essential before putting a map into the wild, lest you run the risk of losing a deal because of lack of due diligence. For the casual user of Google Earth, these are not concerns and therefore not talked about much. As professionals, though, we must ask these questions.

A picture is worth a thousand words
Virtually any source map can be scanned and tied to geographic coordinates to form an imagery data source. For imagery data to be useful in a Geographic Information System, however, it must be tied to coordinates and overlaid with other data such oil well or pipeline locations. Explorationists commonly use imagery in the form of an air photo, topographic map, or satellite image to add a sense of “ground truth” to their maps. Points, lines, and polygons in isolation simply do not convey the same sense of truth, even though they may be precisely placed. A picture is worth a thousand words. Given an air photo, an oil company executive can instantly see the location of wells and other infrastructure. The euphoria this creates is undeniable, but sometimes misplaced unless one has confidence in the underlying process that was used to acquire and process the data.

The potentially high cost of “free”
There are several “gotchas” associated with imagery and many points along the way where errors can be introduced. Free data sources do not provide sufficient information about an image, such as its production date and quality. Where does the recent imagery start and old imagery stop? If you zoom out in Google Earth, for example, you can see many strips of data of varying quality, color schemes, and vintage. Such information is critical for exploration companies. In addition, free map services tend to have updated data primarily in urban areas, because that’s what most people care about. Not so in the oil and gas industry where our infrastructure tends to be located in rural locations.

Data overload
Imagery data can quickly fill up local storage space, even on very large computers. As data resolution increases (and engineers always want the highest resolution data available) imagery fills up disk space exponentially faster. A consequence is that 30 centimeter resolution data requires nine times more storage space than the standard one meter resolution data of just a few years ago. This trend is unlikely to change.

Because different client applications require data in different formats, on today’s servers you’ll find multiple versions of the same data in different formats just burning up disk space. Imagery management quickly becomes a mess when dealing in terabytes and IT staff spends more and more time documenting inventory, allocating server space, and updating ever larger databases when they could be focusing on revenue enhancing activities.

Third party services have evolved to address these problems, taking on the tasks of maintaining the expanding imagery database so that it can be streamed directly to oil and gas applications. For now, this involves loading the various imagery data sets and establishing web services that client applications can consume. Clients can offload internal proprietary imagery to a third party vendor and have that data streamed back into the company. This web service reduces the burden on corporate IT, saving time and money.

The future of imagery
In the future, organizations will likely take advantage of evolving technologies such as Cloud Computing with its nearly infinite computing and storage capabilities. Challenges will include uploading and downloading vast amounts of data, including rapidly changing proprietary data sets. However, the computational power of the cloud environment will offer many benefits including speed of access and the ability to use Extract, Transform and Load technologies to reformat data “on the fly.”

Free maps have popularized geospatial imagery, but they simply don’t offer the quality, robustness, or versatility needed for modern scientific exploration. The vision of the future is to store and maintain dynamic, up-to-date, multi-terabyte imagery databases on the cloud and speedily stream that data back into the enterprise for near real time analysis and decision making. The good news is that this future isn’t all that far away.

We’ve been working with a number of companies who are working in or looking to work in the Marcellus Shale Formation.  Here’s a wiki link that has everything you’ve ever wanted to know about the Marcellus and then some:

http://en.wikipedia.org/wiki/Marcellus_Formation

WhiteStar has the data you need to put together base maps and presentations as your explore this formation.  Our Unlimited Base Map Access (UBA) and Unlimited Well Access (UWA) products can speed along the development of your maps to give you that competitive edge.  Scanned topos and 1 meter air photo imagery are also available.  Give us a call at 800-736-6277 if you would like to discuss our data product options.

-Mike

I was browsing the New Mexico State Lands web site the other day and came across these hard copy reports of oil and gas leases that the state wishes to lease in mid December. Here is the link to that web site: http://www.nmstatelands.org/default.aspx?PageID=36 in case you’re interested.

This site has legal descriptions for each lease as well as the total acres, primary rental fee, and the minimum acceptable bid. Using our legal2map web service, I keyed in the 49 legal descriptions as well as the other attributes I was interested in, then produced the polygons with the web service. Using ArcGIS and FME Workbench from Safe Software, I merged the Comma Separated Value (CSV) attribute file with the shape file. In ArcGIS I added our township and range data, well location data, and culture information (mainly roads and dry lake beds, but you wouldn’t want to drill a well in a dry lake bed if you could avoid it, would you?).  Here’s a link to the map I made:  http://www.whitestar.com/blog/?attachment_id=24

The entire excercise took about 2 hours and I greatly improve the quality of my decision making with all these additional sources of information and making my leases visual and mappable.  I also added the state oil and gas well data (using UWA) to show what leases already have production on them.  Sweet!

I went through this excercise to show you the power of putting together readily available pieces of information so that you can make the best decisions possible which is very important considering the high value of leasing programs these days.

Regards,

Robert