Effects of a temperature dependent viscosity in surface nonlinear waves propagating in a shallow fluid heated from below

The effects of a temperature dependent viscosity in surface nonlinear waves propagating in a shallow fluid heated from below are investigated. It is shown that the (2+1)-dimensional Burgers equation may appear as the equation governing the upper free surface perturbations of a Bénard system, even when the viscosity is assumed to depend on temperature. The critical Rayleigh number for the appearance of waves governed by the Kadomtsev-Petviashvili equation, however, will be smaller than R=30, which is the critical number obtained for a constant viscosity. © 1992.

The Role of the Korteweg-de Vries Hierarchy in the N-Soliton Dynamics of the Shallow Water Wave Equation

We apply a multiple-time version of the reductive perturbation method to study long waves as governed by the shallow water wave model equation. As a consequence of the requirement of a secularity-free perturbation theory, we show that the well known N-soliton dynamics of the shallow water wave equation, in the particular case of α = 2β, can be reduced to the N-soliton solution that satisfies simultaneously all equations of the Korteweg-de Vries hierarchy.

Mapeamento do contorno estrutural do embasamento da bacia sedimentar de Curitiba - PR

The sedimentary Curitiba basin is located in the Central-Southern part of the first Parananense plateau, and comprises Curitiba (PR), and part of the neighbour Municipalities (fig.1). It is supposed to be of Plio-Pleistocene age. It has a shallow sedimentary fulfillment, represented by the Guabirotuba formation (BIGARELLA and SALAMUNI, 1962) which is dristributed over a large area of about 3.000km2. The internal geometry, not entirely known yet, is actually object of detailed research, that shows its geological evolution to Cenozoic tectonic movements. For the purpose of this study the definition of the structural contour of the basement and their depo-centers is fundamental. This paper presents the results of the integration of surface and subsurface data, processed by statistical methods, which allowed a more precise definition of the morphostructural framework of the basement. For the analysis of the geological spacial data, specific softwares were used for statistical processing for trend surfaces analysis. The data used in this study are of following types: a) drilling logs for ground water; b) description of surface points of geological maps (CRPM, 1977); c) description of points of geotechnical drillings and down geological survey. The data of 223 drilling logs for ground water were selected out of 770 wells. The description files of 700 outcrops, as well as planialtimetric field data, were used for the localization of the basement outcrop. Thus, a matrix with five columns was set up: utm E-W (x) and utm N-S (y); surface altitude (z); altimetric cote of the contact between sedimentary rocks and the basement (k); isopachs (l). For the study of the basement limits, the analysis of surface trends of 2(nd) and 3(rd) degree polinomial for the altimetric data (figs. 2 and 3) were used. For the residuals the method of the inverse of the square of the distance (fig.4) was used. The adjustments and the explanations of the surfaces were made with the aid of multiple linear regressions. The analysis of 3rd degree polinomial trend surface (fig.3) confirmed that the basement tends to be more exposed towards NNW-SSE explaining better the data trend through an ellipse, which striking NE-SW and dipping SW axis coincides with the trough of the basin observed in the trending surface of the basement. The performed analysis and the respective images offer a good degree of certainty of the geometric model of the Curitiba Basin and of the morphostructure of its basement. The surface trend allows to sketch with a greater degree of confidence the structural contour of the topgraphic surface (figs. 5 and 6) and of the basement (figs. 7 and 8), as well as the delimitation of intermediate structural heights, which were responsible for isolated and assymmetric depocenters. These details are shown in the map of figures 9 and 10. Thus, the Curitiba Basin is made up by a structural trough stretching NE-SW, with maximum preserved depths of about 80m, which are separated by heights and depocenters striking NW-SE (fig. 11). These structural features seems to have been controlled by tectonic reactivation during the Tertiary (HASUI, 1990) and which younger dissection was conditioned by neotectonic processes (SALAMUNI and EBERT, 1994).

Solid mass falling into the reservoirs shallow water equations validity from the engineering point of view

Water waves generated by a solid mass is a complex phenomenon discussed in this paper by numerical and experimental approaches. A model based on shallow water equations with shocks (Saint Venant) has developed. It can reproduce the amplitude and the energy of the wave quite well, but because it consistently generates a hydraulic jump, it is able to reproduce the profile, in the case of high relative thickness of slide, but in the case of small relative thickness it is unable to reproduce the amplitude of the wave. As the momentum conservation is not verified during the phase of wave creation, a second technique based on discharge transfer coefficient α, is introduced at the zone of impact. Numerical tests have been performed and validated this technique from the experimental results of the wave's height obtained in a flume.

Carriers escape mechanisms in shallow InGaAs/GaAs quantum wells grown on vicinal (001) GaAs substrates

We used photoluminescence spectroscopy in order to investigate the carriers escape mechanisms in In0.15Ga0.85As/GaAs quantum wells grown on top of nominal (001) and 2°-, 4°-and 6°-off (001) towards (111)A GaAs substrates. We described the escape processes using two models that fit the Arrhenius plot of the integrated PL intensity as a function of the inverse of the sample temperature. In the first model, we considered equal escape probability for electrons and holes. In the second one, we assumed that a single type of carrier can escape from the well. At high temperature, the first model fits the experimental data well, whereas, between 50 K and 100 K, the second model has to be taken into account to describe the data. We observed that the escape activation energy depends on the misorientation angle. An unusual behavior was noted when the full width at half maximum of the photoluminescence main emission was plotted as a function of the sample temperature. We showed that the escape process of the less-confined carriers drives this behavior. © 1999 Academic Press.

The use of shallow seismic reflection technique in near surface exploration of urban sites: An evaluation in the city of SãO Paulo, Brazil

In order to evaluate the use of shallow seismic technique to delineate geological and geotechnical features up to 40 meters depth in noisy urban areas covered with asphalt pavement, five survey lines were conducted in the metropolitan area of São Paulo City. The data were acquired using a 24-bit, 24-channel seismograph, 30 and 100 Hz geophones and a sledgehammer-plate system as seismic source. Seismic reflection data were recorded using a CMP (common mid point) acquisition method. The processing routine consisted of: prestack band-pass filtering (90-250 Hz); automatic gain control (AGC); muting (digital zeroin) of dead/noisy traces, ground roll, air-wave and refracted-wave; CMP sorting; velocity analyses; normal move-out corrections; residual static corrections; f-k filtering; CMP stacking. The near surface is geologically characterized by unconsolidated fill materials and Quaternary sediments with organic material overlying Tertiary sediments with the water table 2 to 5 m below the surface. The basement is composed of granite and gneiss. Reflections were observed from 40 milliseconds to 65 ms two-way traveltime and were related to the silt clay layer and fine sand layer contact of the Tertiary sediments and to the weathered basement. The CMP seismic-reflection technique has been shown to be useful for mapping the sedimentary layers and the bedrock of the São Paulo sedimentary basin for the purposes of shallow investigations related to engineering problems. In spite of the strong cultural noise observed in these urban areas and problems with planting geophones we verified that, with the proper equipment, field parameters and particularly great care in data collection and processing, we can overcome the adverse field conditions and to image reflections from layers as shallow as 20 meters.

Vertical migration during tidal transport of megalopae of Necora puber in coastal shallow waters during daytime

For meroplanktonic larvae that must settle in coastal areas, their successful return to the shore is determined largely by physical transport processes; however, many organisms perform vertical movements to aid successful recruitment. In this study, daytime tidal vertical migration of megalopae of the velvet swimming crab Necora puber was investigated across two different exposures in the shallow waters of Plymouth Sound. Crabs were collected using a plankton net at the surface and near the bottom during flood and ebb tides. Distribution of the pelagic postlarvae was patchy and the abundance varied spatially in tens and thousands of metres. In temporal scales, the annual pattern was dominated by low occurrence of megalopae, punctuated by episodic peaks of high abundance. Most megalopae were collected at the surface irrespective of the tidal phase. The effect of wave exposure on the vertical migration of megalopae was not clear, although there was a general higher abundance of megalopae on exposed shores. Daytime abundance in the water column appears to be regulated by the tidal cycle, as megalopae were more abundant during flood than ebb tides. Although the megalopae do not appear to make large vertical migrations, this behaviour should produce a net shoreward transport. © 2005 Elsevier Ltd. All rights reserved.

Application of ARX neural networks to model the rate of penetration of petroleum wells drilling

Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.

Applying a genetic neuro-model reference adaptive controller in drilling optimization

Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.

Optimal Boussinesq model for shallow-water waves interacting with a microstructure

In this paper, we consider the propagation of water waves in a long-wave asymptotic regime, when the bottom topography is periodic on a short length scale. We perform a multiscale asymptotic analysis of the full potential theory model and of a family of reduced Boussinesq systems parametrized by a free parameter that is the depth at which the velocity is evaluated. We obtain explicit expressions for the coefficients of the resulting effective Korteweg-de Vries (KdV) equations. We show that it is possible to choose the free parameter of the reduced model so as to match the KdV limits of the full and reduced models. Hence the reduced model is optimal regarding the embedded linear weakly dispersive and weakly nonlinear characteristics of the underlying physical problem, which has a microstructure. We also discuss the impact of the rough bottom on the effective wave propagation. In particular, nonlinearity is enhanced and we can distinguish two regimes depending on the period of the bottom where the dispersion is either enhanced or reduced compared to the flat bottom case. © 2007 The American Physical Society.

Classification of petroleum well drilling operations using Support Vector Machine (SVM)

During the petroleum well drilling operation many mechanical and hydraulic parameters are monitored by an instrumentation system installed in the rig called a mud-logging system. These sensors, distributed in the rig, monitor different operation parameters such as weight on the hook and drillstring rotation. These measurements are known as mud-logging records and allow the online following of all the drilling process with well monitoring purposes. However, in most of the cases, these data are stored without taking advantage of all their potential. On the other hand, to make use of the mud-logging data, an analysis and interpretationt is required. That is not an easy task because of the large volume of information involved. This paper presents a Support Vector Machine (SVM) used to automatically classify the drilling operation stages through the analysis of some mud-logging parameters. In order to validate the results of SVM technique, it was compared to a classification elaborated by a Petroleum Engineering expert. © 2006 IEEE.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm

This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Fast petroleum well drilling monitoring through optimum-path forest

Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the Optimum-Path Forest classifier. Given that the cutting's volume at the vibrating shale shaker can provide several information about drilling, we used computer vision techniques to extract texture informations from cutting images acquired by a digital camera. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and effciency. We used the Optimum-Path Forest (OPF), EOPF (Efficient OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP) Support Vector Machines (SVM), and a Bayesian Classifier (BC) to assess the robustness of our proposed schema for petroleum well drilling monitoring through cutting image analysis.