Estudo e aplicação da transformada de Fourier na regularização de dados sísmicos na exploração de petróleo

In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.

Diagnóstico ecotoxicológico dos efluentes lançados no complexo estuarino do Jundiaí/Potengi, Natal/RN

Untreated effluents that reach surface water affect the aquatic life and humans. This study aimed to evaluate the wastewater s toxicity (municipal, industrial and shrimp pond effluents) released in the Estuarine Complex of Jundiaí- Potengi, Natal/RN, through chronic quantitative e qualitative toxicity tests using the test organism Mysidopsis Juniae, CRUSTACEA, MYSIDACEA (Silva, 1979). For this, a new methodology for viewing chronic effects on organisms of M. juniae was used (only renewal), based on another existing methodology to another testorganism very similar to M. Juniae, the M. Bahia (daily renewal).Toxicity tests 7 days duration were used for detecting effects on the survival and fecundity in M. juniae. Lethal Concentration 50% (LC50%) was determined by the Trimmed Spearman-Karber; Inhibition Concentration 50% (IC50%) in fecundity was determined by Linear Interpolation. ANOVA (One Way) tests (p = 0.05) were used to determinate the No Observed Effect Concentration (NOEC) and Low Observed Effect Concentration (LOEC). Effluents flows were measured and the toxic load of the effluents was estimated. Multivariate analysis - Principal Component Analysis (PCA) and Correspondence Analysis (CA) - identified the physic-chemical parameters better explain the patterns of toxicity found in survival and fecundity of M. juniae. We verified the feasibility of applying the only renewal system in chronic tests with M. Juniae. Most efluentes proved toxic on the survival and fecundity of M. Juniae, except for some shrimp pond effluents. The most toxic effluent was ETE Lagoa Aerada (LC50, 6.24%; IC50, 4.82%), ETE Quintas (LC50, 5.85%), Giselda Trigueiro Hospital (LC50, 2.05%), CLAN (LC50, 2.14%) and COTEMINAS (LC50, IC50 and 38.51%, 6.94%). The greatest toxic load was originated from ETE inefficient high flow effluents, textile effluents and CLAN. The organic load was related to the toxic effects of wastewater and hospital effluents in survival of M. Juniae, as well as heavy metals, total residual chlorine and phenols. In industrial effluents was found relationship between toxicity and organic load, phenols, oils and greases and benzene. The effects on fertility were related, in turn, with chlorine and heavy metals. Toxicity tests using other organisms of different trophic levels, as well as analysis of sediment toxicity are recommended to confirm the patterns found with M. Juniae. However, the results indicate the necessity for implementation and improvement of sewage treatment systems affluent to the Potengi s estuary

Predição não-linear de curvas de produção de petróleo via redes neurais recursivas

One of the main activities in the petroleum engineering is to estimate the oil production in the existing oil reserves. The calculation of these reserves is crucial to determine the economical feasibility of your explotation. Currently, the petroleum industry is facing problems to analyze production due to the exponentially increasing amount of data provided by the production facilities. Conventional reservoir modeling techniques like numerical reservoir simulation and visualization were well developed and are available. This work proposes intelligent methods, like artificial neural networks, to predict the oil production and compare the results with the ones obtained by the numerical simulation, method quite a lot used in the practice to realization of the oil production prediction behavior. The artificial neural networks will be used due your learning, adaptation and interpolation capabilities