Simulation of Geological Contacts from Interpreted Geological Model Using Multiple-Point Statistics

Applications of multiple-point statistics (mps) algorithms to large non-repetitive geological objects such as those found in mining deposits are difficult because most mps algorithms rely on pattern repetition for simulation. In many cases, an interpreted geological model built from a computer-aided design system is readily available but suffers as a training image due to the lack of patterns repetitiveness. Porphyry copper deposits and iron ore formations are good examples of such mining deposits with non-repetitive patterns. This paper presents an algorithm called contactsim that focuses on reproducing the patterns of the contacts between geological types. The algorithm learns the shapes of the lithotype contacts as interpreted by the geologist, and simulates their patterns at a later stage. Defining a zone of uncertainty around the lithological contact is a critical step in contactsim, because it defines both the zones where the simulation is performed and where the algorithm should focus to learn the transitional patterns between lithotypes. A larger zone of uncertainty results in greater variation between realizations. The definition of the uncertainty zone must take into consideration the geological understanding of the deposit, and the reliability of the contact zones. The contactsim algorithm is demonstrated on an iron ore formation.     

Geostatistical facies simulation with geometric patterns of a petroleum reservoir

During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.     

Geological context,mineralization, and timing of the Juramento sediment-hosted stratiform copper–silver deposit,Salta district,northwestern Argentina

The Juramento deposit in northwestern Argentina exhibits several readily visible general characteristics of sediment-hosted stratiform copper (SSC) mineralization. It consists of fine-grained disseminated base-metal sulfides within marine to lacustrine graybeds (the basal whitish Late Cretaceous Lecho Sandstone and shallow-water carbonates of the overlying Maastrichtian Yacoraite Formation) that overlie a thick sequence of redbeds (the Pirgua Subgroup). The property has been examined and drilled in three successive exploration programs as a possible analog of world-class mineralization in the copperbelts of central Africa and the Kupferschiefer. The present report provides specific field and laboratory results that confirm the classification as SSC-type mineralization. The host graybeds are the basal sandstone and overlying oolitic and stromatolitic units of the Yacoraite Formation, which are shown from textural studies to be carbonaceous and to have initially contained very fine-grained, disseminated, syndiagenetic pyrite. These sediments would have been sufficiently porous and permeable in early diagenetic time to allow an infiltration of metalliferous fluids from the underlying redbeds, resulting in the observed progressive replacement of in situ pyrite by common base-metal sulfides (sphalerite, galena, argentiferous tetrahedrite, and copper-rich sulfides: first chalcopyrite, then bornite, and finally chalcocite). Sulfur isotope analyses indicate that a portion of the sulfur of ore-stage sulfides is isotopically heavier than that of pyrite, possibly due to a contribution from associated gypsum. Ore-stage sulfides are zoned vertically and obliquely through the mineralized zones, from cupriferous sulfides at low stratigraphic levels to lead- and zinc-rich mineralization above, with unreplaced pyrite remaining within upper Yacoraite strata. The zoned sulfides and their replacement textures, the peneconformable configuration of the mineralized zones, and the position of ore-stage mineralization adjacent to a stratigraphically defined redox transition from redbeds upward into graybeds indicate an overprint of copper (and accompanying ore-stage metals) on originally pyritic graybeds. The influx of ore-stage metals, presumably in an oxidized low-temperature brine, terminated with a silicification event that effectively sealed the host carbonates. These observations and the overall genetic interpretation are consistent with the general deposit-scale genetic model for early diagenetic SSC mineralization. The regional geologic context is also consistent with its classification as a SSC deposit: It is hosted by post-oxyatmoversion sediments and was formed in association with evaporites at a low paleolatitude in a major intracontinental rift system.     

Optical properties and light penetration in a deep,naturally acidic,iron rich lake: Lago Caviahue (Patagonia,Argentina)

The optical properties and light climate in the deep and extremely acid Lake Caviahue have been studied in order to better understand its characteristics and the possible influence upon the phytoplankton community. The absorption coefficients for the dissolved fraction were maximal in the ultraviolet (UV) region and the water absorption spectra showed a shoulder around 300 nm, which was attributed to the concentration of Fe(III). No radiation was detected in the water column below 360 nm. The depth of the 1% incident radiation was dependent of wavelength, showing its maximum of 13.3 m at 565 nm, compared to 1.7 m and 4.8 m at 400 nm and 700 nm, respectively. Phytoplankton biomass was low and showed an almost constant profile with depth despite the relative darkness of the water column. Optical climate of Lake Caviahue is not typical of high elevation lakes but is more similar to low elevation shallow lakes of the Andean region. The chemical composition of the water, mainly Fe oxidation state and concentration, is the responsible for the high attenuation of the UV radiation (UVR). Living organisms are protected of UVR because Lake Caviahue waters are a shield against UV-B.     

A model of diffuse degassing at three subduction-related volcanoes

2 and δ¹³C in soil gas were measured at three active subduction-related stratovolcanoes (Arenal and Poás, Costa Rica; Galeras, Colombia). In general, Rn, CO₂ and δ¹³C values are higher on the lower flanks of the volcanoes, except near fumaroles in the active craters. The upper flanks of these volcanoes have low Rn concentrations and light δ¹³C values. These observations suggest that diffuse degassing of magmatic gas on the upper flanks of these volcanoes is negligible and that more magmatic degassing occurs on the lower flanks where major faults and greater fracturing in the older lavas can channel magmatic gases to the surface. These results are in contrast to findings for Mount Etna where a broad halo of magmatic CO₂ has been postulated to exist over much of the edifice. Differences in radon levels among the three volcanoes studied here may result from differences in age, the degree of fracturing and faulting, regional structures or the level of hydrothermal activity. Volcanoes, such as those studied here, act as plugs in the continental crust, focusing magmatic degassing towards crater fumaroles, faults and the fractured lower flanks. Received: 16 December 1997 / Accepted: 27 January 2000     

Analysis of an illustrative interaction between structural features and earthworm populations in Brazilian ferralsols

Ferralsols are characterized by poorly-defined horizons, weak macrostructure and strong development of a fine granular structure comprising subangular micro-aggregates. In this study, the morphological and physical modifications caused by earthworm activity in a clayey ferralsol were analysed. After describing soil structures, undisturbed samples were taken for evaluating aggregates and determining clod bulk density and particle density. Soil water retention properties were measured and an inventory of soil invertebrate macrofauna was created. The structural and porous transformations were due to aggregates created by earthworm activity. Changes in bulk density can be associated with pore modifications caused by a change in the proportions of aggregate types, and a notable reduction of total porosity was measured, tending to increase soil volume with dense aggregates. Structural modifications affected the topsoil down to 0.5 m and water retention between −1 and −33 kPa, the principal water compartment of these soils.     

Predicting forest fire in the Brazilian Amazon using MODIS imagery and artificial neural networks

The presented work describes a methodology that employs artificial neural networks (ANN) and multi-temporal imagery from the MODIS/Terra-Aqua sensors to detect areas of high risk of forest fire in the Brazilian Amazon. The hypothesis of this work is that due to characteristic land use and land cover change dynamics in the Amazon forest, forest areas likely to be burned can be separated from other land targets. A study case was carried out in three municipalities located in northern Mato Grosso State, Brazilian Amazon. Feedforward ANNs, with different architectures, were trained with a backpropagation algorithm, taking as inputs the NDVI values calculated from MODIS imagery acquired during five different periods preceding the 2005 fire season. Selected samples were extracted from areas where forest fires were detected in 2005 and from other non-burned forest and agricultural areas. These samples were used to train, validate and test the ANN. The results achieved a mean squared error of 0.07. In addition, the model was simulated for an entire municipality and its results were compared with hotspots detected by the MODIS sensor during the year. A histogram analysis showed that the spatial distribution of the areas with fire risk were consistent with the fire events observed from June to December 2005. The ANN model allowed a fast and relatively precise method to predict forest fire events in the studied area. Hence, it offers an excellent alternative for supporting forest fire prevention policies, and in assisting the assessment of burned areas, reducing the uncertainty involved in currently used methods.