43 resultados para Logging
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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.
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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.
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Among the several variables that influence timber harvesting is the slope, which influences the productivity of forest machines. In this experiment the harvester was evaluated technically and economically while cutting and processing eucalyptus activity on different slope classes. The technical analysis included a study of time and movements by the method of continuous time; productivity was determined by the volume in cubic meters of wood processing. The economic analysis included the parameters of operational cost, production cost and energy consumption. The analysis of the data showed that productivity decreased according to the increase of the percent slope inclination, resulting in an effective work hour productivity increase from 18.72 to 39.71 m 3sc, with a mean of operating cost of US$ 78.78 per work hour.
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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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The mineral exploration is a complex activity that should involve a combination of direct and indirect techniques of geological investigation. The growing demand for base metals in the national and international market provides the revaluation of mineral occurrences that can become deposits and mines. This paper presents the results of the electrical resistivity and induced polarization geophysical methods in azimuthal arrangement, applied in a mineral occurrence of disseminated copper sulfides, previously studied through trenches and core drilling, located in the Camaquã Sedimentary Basin, Rio Grande do Sul State, Brazil. The inversion models indicate the coincidence of high chargeability and low resistivity values. The integration of geophysical data permitted the elaboration of 3D attributes visualization models for the mineralization enclosed in volcanic tuffs. The integrated geophysical and geological analysis indicates the potential of a new mineralized area. © 2012 Sociedade Brasileira de Geofísica.
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The uplift capacity of helical piles depends on the shear resistance of the soil above the helical plates. During helical pile installation, the soil traversed by the plates are sheared and displaced laterally, and consequently the soil structure is disturbed. Considering this fact, the aim of this paper is presenting the effect of helical piles installation in the soil mass by means of CPT tests carried out close to the soil cylinder above the pile helices. The CPT tests were performed at the CRHEA site from the Sao Carlos School of Engineering, Sao Carlos city, inland of Sao Paulo State, Brazil. In addition, an interpretation of CPT tests data for stratigrafic logging are presented and compared to Standard Penetration Tests (SPT) carried out at this site. This study showed that the CPT sleeve friction fs data were affected by the installation of helical pile in this particular tropical soil site. © 2013 Taylor & Francis Group.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência Florestal - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA