matching of prior textures by image compression for geological mapping and novelty detection

We describe an image-comparison technique of Heidemann and Ritter (2008a, b), which uses image compression, and is capable of: (i) detecting novel textures in a series of images, as well as of: (ii) alerting the user to the similarity of a new image to a previously observed texture. This image-comparison technique has been implemented and tested using our Astrobiology Phone-cam system, which employs Bluetooth communication to send images to a local laptop server in the field for the image-compression analysis. We tested the system in a field site displaying a heterogeneous suite of sandstones, limestones, mudstones and coal beds. Some of the rocks are partly covered with lichen. The image-matching procedure of this system performed very well with data obtained through our field test, grouping all images of yellow lichens together and grouping all images of a coal bed together, and giving 91% accuracy for similarity detection. Such similarity detection could be employed to make maps of different geological units. The novelty-detection performance of our system was also rather good (64% accuracy). Such novelty detection may become valuable in searching for new geological units, which could be of astrobiological interest. The current system is not directly intended for mapping and novelty detection of a second field site based on image- compression analysis of an image database from a first field site, although our current system could be further developed towards this end. Furthermore, the image-comparison technique is an unsupervised technique that is not capable of directly classifying an image as containing a particular geological feature; labelling of such geological features is done post facto by human geologists associated with this study, for the purpose of analysing the system's performance. By providing more advanced capabilities for similarity detection and novelty detection, this image-compression technique could be useful in giving more scientific autonomy to robotic planetary rovers, and in assisting human astronauts in their geological exploration and assessment

Image Compression for Geological Mapping and Novelty Detection

We describe an image-comparison technique of Heidemann and Ritter [4,5] that uses image compression, and is capable of: (i) detecting novel textures in a series of images, as well as of: (ii) alerting the user to the similarity of a new image to a previously-observed texture. This image-comparison technique has been implemented and tested using our Astrobiology Phone-cam system, which employs Bluetooth communication to send images to a local laptop server in the field for the image-compression analysis. We tested the system in a field site displaying a heterogeneous suite of sandstones, limestones, mudstones and coalbeds. Some of the rocks are partly covered with lichen. The imagematching procedure of this system performed very well with data obtained through our field test, grouping all images of yellow lichens together and grouping all images of a coal bed together, and giving a 91% accuracy for similarity detection. Such similarity detection could be employed to make maps of different geological units. The novelty-detection performance of our system was also rather good (a 64% accuracy). Such novelty detection may become valuable in searching for new geological units, which could be of astrobiological interest. By providing more advanced capabilities for similarity detection and novelty detection, this image-compression technique could be useful in giving more scientific autonomy to robotic planetary rovers, and in assisting human astronauts in their geological exploration

Examples from the atlas of major Appalachian Gas Plays

The objectives of this contract are to produce a panted atlas of major Appalachian basin gas plays and to compile a machine-readable database of reservoir data. The Appalachian Oil and Natural Gas Research Consortium (AONGRC or the Consortium), a partnership of the state geological surveys in Kentucky, Ohio, Pennsylvania, and West Virginia, and the departments of Geology and Petroleum and Natural Gas Engineering at West Virginia University (WVU), agrees with the need to classify gas reservoirs by geologic plays. During meetings with industry representatives, the small independents in the basin emphasized that one of their prime needs was to place each producing reservoir within a stratigraphic framework subdivided by environment of deposition to enable them to develop exploration and development strategies. The text for eight of the 31 play descriptions has been completed, drafting of illustrations for these plays is underway (or complete for some plays), and the review process is ongoing

Atlas of major Appalachian basin gas plays

This regional study of gas reservoirs in the Appalachian basin has four main objectives: to organize all of the -as reservoirs in the Appalachian basin into unique plays based on common age, lithology, trap type and other geologic similarities; to write, illustrate and publish an atlas of major gas plays; to prepare and submit a digital data base of geologic, engineering and reservoir parameters for each gas field; and technology transfer to the oil and gas industry during the preparation of the atlas and data base