Characterization of micro-bubble size distribution and flow configuration in DAF contact zone by a non-intrusive image analysis system and tracer tests

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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.

Self-optimization of dense wireless sensor networks based on simulated annealing

Wireless sensor network (WSN) Is a technology that can be used to monitor and actuate on environments in a non-intrusive way. The main difference from WSN and traditional sensor networks is the low dependability of WSN nodes. In this way, WSN solutions are based on a huge number of cheap tiny nodes that can present faults in hardware, software and wireless communication. The deployment of hundreds of nodes can overcome the low dependability of individual nodes, however this strategy introduces a lot of challenges regarding network management, real-time requirements and self-optimization. In this paper we present a simulated annealing approach that self-optimize large scale WSN. Simulation results indicate that our approach can achieve self-optimization characteristics in a dynamic WSN. © 2012 IEEE.

Estudo de temperatura de plasma de álcool através de espectroscopia de emissão natural radical C2*

Non-intrusive methods of diagnosis, such as spectral analysis of the radiation emitted by the system, have been used as a viable alternative for determining the temperature of combustion systems. Among them, the determination of temperature by natural emission spectroscopy has the advantage of requiring relatively simple experimental devices. Once Chemiluminescent species are formed directly in the excited state, the collection and recording of radiation emission spectrum is enough to determine the temperature (CARINHANA, 2008). In this study we used the process of making direct comparisons between the experimental spectra obtained in the laboratory from the plasma of alcohol, and the theoretical spectra plotted from a computer program developed at the IEAv. The objective was to establish a fast and reliable method to measure the rotational temperature of the radical C2*. The results showed that the temperature of the plasma, which in turn can be taken as the rotational temperature of the system, is proportional to the pressure. The temperature values ranged from ca. 2300 ~ 2500 K at a pressure of 19 mmHg to 3100 ~ 3500 K for the pressure of 46 mmHg. The temperature values are somewhat smaller when we consider the theoretical spectrum as a Lorentzian curve. The overlap of the spectra was better when using the profile curve, but still were not exactly superimposed. The solution to improve the overlap of the theoretical with the experimental spectra is the use of a curve that has the convolution of two profiles analyzed: Lorentzian and Gaussian. This curve is called the Voigt profile, which will also be implemented by programmers and studied in a next work

Determinação de temperatura de chamas por espectroscopia de espécies quimioluminescentes

In a combustion process involving fossil fuels, there is the formation of species Chemiluminescent, especially CH*, C2* and OH*, whose spontaneous emission can be used as a diagnostic tool. In the present work, mapping and determination of the rotational temperature of the species CH* produced in flames on a burner fueled by Liquefied Petroleum Gas (LPG) was carried out. This study is part of a project involving the characterization of supersonic combustion in scramjets engines, whose study has been conducted in the hypersonic shock tunnel IEAv laboratories. The technique used was the natural emission spectroscopy, which has as main advantage of being non-intrusive. The rotational temperature determination was made using the Boltzmann method, whose principle is to relate the emission intensity of the species to the temperature by means of spectroscopic constants established.The temperature values were determined from the analysis of electronic bands AX and BX of the radical CH*. In order to confirm the results of flame temperatures obtained by the natural emission technique, was also used the technique of line reversal sodium. The results of both techniques showed that the temperature of the flames investigated is about 2500K a 2700K

Termometria em chamas utilizando a técnica de espalhamento Rayleigh

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)