Geostatistical Simulation of Acoustic Log Data for Seismic Depth Conversion

Seismic reflection methods measure the time a seismic wave takes to travel through the ground, from the user defined source to a series of signal monitoring sensors known as geophones. The measured times need to be depth converted to allow for integration with other geological data. In order to convert from time to depth, an estimate of the rock volume velocity field must be made. The velocity field estimate can be made by assignment of velocity estimates to a geological model independent of the seismic processing. This article presents the results of using the acoustic geophysical log data extrapolated via sequential Gaussian simulation to derive the velocity field. The uncertainties associated with the velocity estimates were significant and provided the means to assess confidence limits for the actual depth determination. The technique is assessed by application to a major coal deposit, approximately 2.1 m thick and 210 m deep. Considering only the uncertainty associated with estimating the velocity field, half of the confidence interval values showed approximately 1 m of uncertainty in depth. The application of sequential Gaussian simulation to model the 3D distribution of acoustic velocity can be extended to other geophysical log parameters or derived estimates.     

A physically-based method for removing pits in digital elevation models

Spurious pits in digital elevation models (DEMs) are traditionally removed by filling depressions, often creating flat regions that lead to inaccurate estimation of landscape flow directions. In this study, a physical approach based on a simple landscape evolution model is proposed for DEM pit removal. This method, an alternative to traditional geometrical procedures, enforces more realistic slopes and flow directions on topography. The procedure is compared with the method most commonly used in the literature and distributed with commercial GIS software where, generally, elevations of a depression are increased up to the lowest value among neighbouring cells. Several tests are performed and parameters sensitivity is carried out in order to demonstrate the performance of the proposed model as compared to traditional methods.     

Neural network based daily precipitation generator (NNGEN-P)

Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation.     

The source of the 1722 Algarve earthquake: evidence from MCS and Tsunami data

The 27 December 1722 Algarve earthquake destroyed a large area in southern Portugal generating a local tsunami that inundated the shallow areas of Tavira. It is unclear whether its source was located onshore or offshore and, in any case, what was the tectonic source responsible for the event. We analyze available historical information concerning macroseismicity and the tsunami to discuss the most probable location of the source. We also review available seismotectonic knowledge of the offshore region close to the probable epicenter, selecting a set of four candidate sources. We simulate tsunamis produced by these candidate sources assuming that the sea bottom displacement is caused by a compressive dislocation over a rectangular fault, as given by the half-space homogeneous elastic approach, and we use numerical modeling to study wave propagation and run-up. We conclude that the 27 December 1722 Tavira earthquake and tsunami was probably generated offshore, close to 37°01′N, 7°49′W.     

Hydrothermal alteration and fluid inclusion study of the Lower Cretaceous porphyry Cu–Au deposit of Tiámaro, Michoacán, Mexico

The Tiámaro deposit in Michoacán state has been dated as Lower Cretaceous (Valanginian), though most of the porphyry deposits in central Mexico were dated or have an attributed Eocene–Oligocene age. The host rocks belong to a volcanoplutonic complex overlain by red conglomerates. These rocks were intruded by pre-Valanginian plutonic and hypabissal rocks. Propylitic, phyllic, and argillic alteration assemblages developed, and their superimposition draws the evolution of the deposit. Stage I is represented by propylitic assemblages, stage II contains the main ore forming stockworks and both phyllic and argillic assemblages, and stage III contains late carbonatization assemblages. The obtained temperatures and salinities from inclusion fluids are low for a porphyry-type deposit, but we interpret that the known part of the deposit represents the shallow portion of a bigger deposit. The evolution of mineralizing fluids draws a dilution trend of brines from “porphyry-like” to “epithermal-like” stages. The richest ore zone is roughly located between the 300 and 350 °C isotherms, though unnoticed resources may occur at depth.     

Deglaciation sequences in the Permo-Carboniferous Itararé Group, Paraná Basin, southern Brazil

The Late Carboniferous–Early Permian Itararé Group is a thick glacial unit of the Paraná Basin. Five unconformity-bounded sequences have been defined in the eastern outcrop belt and recognized in well logs along 400 km across the central portion of the basin. Deglaciation sequences are present in the whole succession and represent the bulk of the stratigraphic record. The fining-upward vertical facies succession is characteristic of a retrogradational stacking pattern and corresponds to the stratigraphic record of major ice-retreat phases. Laterally discontinuous subglacial tillites and boulder beds occur at the base of the sequences. When these subglacial facies are absent, deglaciation sequences lie directly on the basal disconformities. Commonly present in the lowermost portions of the deglaciation sequences, polymictic conglomerates and cross-bedded sandstones are generated in subaqueous proximal outwash fans in front of retreating glaciers. The overlying assemblage of diamictites, parallel-bedded and rippled sandstones, and Bouma-like facies sequences are interpreted as deposits of distal outwash fan lobes. The tops of the deglaciation sequences are positioned in clay-rich marine horizons that show little (fine-laminated facies with dropstones) or no evidence of glacial influence on the deposition and likely represent periods of maximum ice retreat.     

Hydrogeological investigation in Santiago Island (Cabo Verde) using magnetotellurics and VLF methods

A geoelectromagnetic research was carried out in the Santa Cruz region (Santiago Island, Cabo Verde) during June 2004. The survey comprised MT soundings and VLF profiles. The main purpose of the MT profile, carried out across three important valleys associated with freshwater aquifers, was to study the tectonic structures correlated to seawater infiltration. The VLF method was used inside of the valleys for investigating shallow structures related to the aquifer contamination by seawater.Numerical modelling shows that the ocean effect is not important for MT data collected at periods shorter than 1 s. The MT data were inverted using a two-dimensional approach, to obtain the sub-superficial electrical conductivity distribution. The VLF data were processed applying the Karous–Hjelt filters to obtain the equivalent current distribution and inverted using 2-D approach. The results obtained in one of the most important valleys show anomalous current concentration/low resistivity (<20 Ω m) areas at depths greater than 40 m that may correspond to an increase in seawater content.The MT data modelling show that the deep zones beneath the valley are strongly fractured representing good pathways for seawater circulation. The depth of the conductive zones increases from south to north, suggesting a northward decreasing of the seawater infiltration effect. This observation correlates very well with in situ geochemical observations.