981 resultados para petroleum wells
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We use the Ogg-McCombe Hamiltonian together with the Dresselhaus and Rashba spin-splitting terms to find the g factor of conduction electrons in GaAs-(Ga,Al)As semiconductor quantum wells (QWS) (either symmetric or asymmetric) under a magnetic field applied along the growth direction. The combined effects of non-parabolicity, anisotropy and spin-splitting terms are taken into account. Theoretical results are given as functions of the QW width and compared with available experimental data and previous theoretical works. © 2007 Elsevier B.V. All rights reserved.
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In this work the electronic structure of undoped AlGaAs/GaAs wide parabolic quantum wells (PQWs) with different well widths (1000 and 3000 ) were investigated by means of photoluminescence (PL) measurements. Due to the particular potential shape, the sample structure confines photocreated carriers with almost three-dimensional characteristics. Our data show that depending on the well width thickness it is possible to observe very narrow structures in the PL spectra, which were ascribed to emissions associated to the recombination of confined 1s-excitons of the parabolic potential wells. From our measurements, the exciton binding energies (of a few meV) were estimated. Besides the exciton emission, we have also observed PL emissions associated to electrons in the excited subbands of the PQWs. © 2010 IOP Publishing Ltd.
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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.
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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.
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The present study introduces a multi-agent architecture designed for doing automation process of data integration and intelligent data analysis. Different from other approaches the multi-agent architecture was designed using a multi-agent based methodology. Tropos, an agent based methodology was used for design. Based on the proposed architecture, we describe a Web based application where the agents are responsible to analyse petroleum well drilling data to identify possible abnormalities occurrence. The intelligent data analysis methods used was the Neural Network.
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This paper discusses the theoretical and experimental results obtained for the excitonic binding energy (Eb) in a set of single and coupled double quantum wells (SQWs and CDQWs) of GaAs/AlGaAs with different Al concentrations (Al%) and inter-well barrier thicknesses. To obtain the theoretical Eb the method proposed by Mathieu, Lefebvre and Christol (MLC) was used, which is based on the idea of fractional-dimension space, together with the approach proposed by Zhao et al., which extends the MLC method for application in CDQWs. Through magnetophotoluminescence (MPL) measurements performed at 4 K with magnetic fields ranging from 0 T to 12 T, the diamagnetic shift curves were plotted and adjusted using two expressions: one appropriate to fit the curve in the range of low intensity fields and another for the range of high intensity fields, providing the experimental Eb values. The effects of increasing the Al% and the inter-well barrier thickness on E b are discussed. The Eb reduction when going from the SQW to the CDQW with 5 Å inter-well barrier is clearly observed experimentally for 35% Al concentration and this trend can be noticed even for concentrations as low as 25% and 15%, although the Eb variations in these latter cases are within the error bars. As the Zhao's approach is unable to describe this effect, the wave functions and the probability densities for electrons and holes were calculated, allowing us to explain this effect as being due to a decrease in the spatial superposition of the wave functions caused by the thin inter-well barrier. © 2013 Elsevier B.V.
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Four crude oil samples from the Sergipe-Alagoas Basin, northeastern Brazil, were analyzed using full scan gas chromatography-quadrupole mass spectrometry (GC-qMS) for biomarkers, in order to correlate them using aromatic carotenoids thereby enhancing knowledge about the depositional environment of their source rocks. The geochemical parameters derived from saturated fractions of the oils show evidence of little or no biodegradation and similar thermal maturation (Ts/(Ts+Tm) for terpanes, C29 αββ/(αββ+ααα), C27, and C29 20S/(20S+20R) for steranes). Low pristane/phytane ratios and the abundance of gammacerane and β-carotane are indicative of an anoxic and saline depositional environment for the source rocks. Moreover, we identified a large range of diagenetic and catagenetic products of the aromatic carotenoid isorenieratene, including C40, C33, and C32 diaryl isoprenoids and aryl isoprenoid derivatives with short side chains and/or additional rings. These results indicate anoxia in the photic zone during the deposition of the source rocks. © 2013 The Authors.
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