One of the topics today that was interesting was ‘Shades of Grey: Opportunities for Collaboration’ by Michael Gould of Esri. His talk covered Esri’s desire to work with Open Source collaboratively rather than having friction between the two camps. I can see the upside of this thinking. There are good tools on both sides of the fence.

Esri is even doing some out-of-the box thinking with EDN for the Open Source community.

More to come….
Mike

Secondly, we have processed all of the massive 1:24,000 scale contour lines for the state of Texas so that they can easily be extracted. This very important data layer helps you to establish missing well elevations and to plan drilling activities more precisely according to topography. This data is so voluminous in its raw format that it is almost impossible to use.

Finally we have digitized and compiled oil and gas field outlines for many states. These are all part of the value you receive when you obtain a subscription to the WhiteStar Culture product.

Blocks - 10
Surveys - 471
Abstract - 535

Overlapping Blocks - 17
Overlapping Surveys - 75
Overlapping Abstract - 86

Hemphill and Jefferson Counties realized the most changes.  In addition, portions of  Brazos, Denton, Duval, Hardin, Harris, Harrison, Robertson, Shelby, Terry, Wheeler and Wilbarger Counties show updates.  Keep an eye on the blog for additional data update announcements.

Thanks,
Mike

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.