Carbonate reservoirs are often comprised of a heterogeneous pore system within a matrix of variably distributed minerals including anhydrite, dolomite, and calcite. When describing carbonate thin sections, it is routine to assign relative abundance levels to each of these components, which are qualitative to semiquantitative (e.g., point counting) and vary greatly depending on the petrographer. Over the past few decades image analysis has gained wide use among petrographers; however, thin-section characterization using this technique has been primarily limited to quantifying the pore space due to the difficulty associated with optical recognition beyond the blue-dyed epoxy associated with the pores. Here, we present a new method of computerized object-based image analysis (Quantitative Digital Petrography: QDP) that relies on a predefined rule set to enable rapid, automated thin-section quantification with limited interaction of a petrographer. We have developed a novel work flow that automatically isolates the sample on a high resolution (i.e., <1 μm/pixel) scanned thin section, segments the image, and assigns those segments to predefined categories; e.g., pores, cement, and grains. With this technique, statistically relevant numbers of thin sections can be rapidly batch processed and quality controlled, thereby allowing quantitative data from conventional core analysis, special core analysis, and reservoir surveillance to be integrated with the petrographic data for a more dynamic description of the carbonate rock. Our technique can also incorporate multiple layers, such as cross-polarization, backscatter electron imaging, and elemental maps, which allow additional information to be easily integrated with results from QDP. The QDP approach is a significant improvement over previous digital image analysis methods because it (1) does not require binarization, (2) eliminates the subjectivity in assessing abundance levels, (3) requires less interaction with a petrographer, and (4) provides a much fuller dataset that can be incorporated across an entire well or field to better address common challenges associated with carbonate reservoir characterization, such as understanding pore type and cement abundance, pore connectivity, grain distribution, and reservoir flow characteristics.

Abstract The US National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center (NGDC) and collocated World Data Center for Marine Geology and Geophysics, Boulder, CO, USA provides scientific data stewardship for many environmental datasets, including geological information derived from sea-floor samples. The essence of NGDC’s stewardship philosophy is that data management practices must evolve and incorporate new technologies in order to keep data interoperable with complementary data streams and maintain their usefulness in a changing research environment. The Index to Marine and Lacustrine Geological Samples database exemplifies NGDC’s evolutionary and collaborative approach to data management. The most recent version of the Index is a geospatially enabled relational database, providing data discovery and delivery via an interactive map on the Web. Geospatial databases and Internet mapping tools are an integral part of NGDC’s current centre-wide systems architecture.

Abstract Geomorphic systems are inherently complex and are the product of a unique integrative history of surface processes, making it difficult for engineers, scientists, and resource managers to regulate environmental change in order to attain a specific management goal. A powerful means for unpacking geomorphic complexity is hierarchical classification of the dominant process-response elements of a geomorphic system. We apply hierarchical analysis specifically to the evaluation of the probable environmental effects of erosion-abatement projects at drumlin bluffs along the southeastern shore of Lake Ontario, assessing their impact across a variety of spatial and temporal scales. Some of the conclusions about probable impacts of shore-stabilization structures on the Ontario lakeshore are not intuitive, but are logically derived from the systematic hierarchical analysis of the system’s geomorphic complexity.

A comprehensive suite of radiometric age determination clearly defines three periods of igneous activity in the Tooele 1° × 2° quadrangle, Utah. These periods and the associated igneous activity are (1) Jurassic calcalkaline plutonism, (2) late Eocene to early Miocene calc-alkaline plutonism and volcanism, and (3) middle and late Miocene bimodal basaltic and rhyolitic volcanism. These periods are recognized throughout the entire Great Basin. A characteristic metal or suite of metals is associated with each period. Tungsten skarns are commonly related to Jurassic plutonism; base-metal and precious-metal deposits are characteristic of the late Eocene to early Miocene igneous activity; and beryllium, fluorine, and uranium are elements associated with silicic rocks of the middle and late Miocene period of igneous activity.