Detection of reservoir fractures in imaging logs using directional filtering
Every rock, which has pores connected together, can be considered as a reservoir rock. Existing fractures in the reservoir rock are the most effective factors, which increase the production and harvesting of the well. Detection of reservoir rock fractures is a very complicated process, due to factors such as poor contrast, fracture variable thickness, noise, discontinuities in the curve of a fracture, and the existence of some phenomenon like fracture bedding. In the well-log images, some sinusoidal curves are fractures. The directions of fractures are shown as some special curves. According to this concept, in this paper, fractures are extracted based on an optimized algorithm using directional filters. The first order derivative of the imaging log is calculated for each pixel. Then, the direction filters are designed based on a different direction of each pixel, and applied to the original imaging log. Finally, using the Hough transform, some parameters of each fracture are obtained, and are displayed on a real imaging log.
Automatic extraction of natural fracture traces from borehole images
Natural fractures may greatly affect wellbore stability and fluid flow in oil reservoirs. The detection of fracture heterogeneities-also named fracture traces-on electrical image logs is not yet efficiently automated and consequently requires long and tedious work from geologists. In this article, we propose an efficient fracture trace extraction algorithm that produces fast, efficient and repeatable results. Morphology operations are first applied to detect high contrast traces while controlling their geometry. A priori information about the geometry of sedimentary surfaces is then used to compute the main fracture orientation. Finally, a clustering algorithm is performed for grouping the extracted traces and identifying those that correspond to natural fractures.
The role of coal petrography in understanding the properties of South African coal
Abstract The variations in physical and chemical properties of coal can only be explained in terms of its petrographical composition and its rank. By means of a TREND computer programme quantitative relationships (correlation coefficients > 0.97) were established between the contents of total carbon and hydrogen (daf) of South African humic coals and their volatile-matter and oxygen contents, their calorific value (all daf) and their mean maximum reflectance of vitrinite (Rmax). The inherent moisture content (ash-free), the vitrinite content (mineral-matter-free), and the Hardgrove and free-swelling indices yielded only semiquantitative relationships (correlation coefficients between 0.80 and 0.93 and high standard deviations) when expressed in terms of total carbon and hydrogen contents (daf). These interrelationships are shown graphically by means of a Seyler diagram modified for South African coal. The relatively poor correlation in the case of vitrinite content is due to the presence of fairly large amounts of reactive semifusinite in most South African coals, and for this reason it is necessary to distinguish between normal, perhydrous and subhydrous coals, depending on the relative difference between determined and inferred vitrinite contents. Due to the high content of low reflecting inertinite the modal reflectance of vitrinite is also regarded to a better rank parameter than the mean reflectance, as the former is not affected by sporadic low or high values. From the modified Seyler diagram it is also possible to devise a grade/type/rank classification for South African coals, where grade is given by the ash content (moisture-free basis). This classification complements Alpern's universal classification of solid fossil fuels. The Seyler diagram can also be used to delineate fields of the most useful application of South African coals, based on the relevant coal properties.