Nuclear magnetic resonance and digital rock in oil industry: well logging applications

• Ano de defesa: 2017
• Autor(a) principal: Trevizan, Willian Andrighetto
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Avaliação de formações; Digital rock; Formation evaluation; Indústria de óleo e gás; Nuclear magnetic resonance; Oil/gas industry; Relaxatividade superficial; Ressonância magnética nuclear; Rocha digital; Surface relaxivity
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/76/76131/tde-10082017-113902/

This thesis discusses Nuclear Magnetic Resonance (NMR) techniques for formation evaluation in well log analysis for the oil/gas industry. We present the standard ingredients for NMR data processing and interpretation, and develop a methodology that extends the determination of surface relaxivity from the laboratory to the well site. The methodology consists of a processing algorithm for diffusion editing data, which enables surface relaxivity determination for conditions close to those found in well logging (regarding data availability and noise levels). At moderate noise levels, lower relaxivity values (below 10μm/s) can be determined solely from NMR diffusion data, while higher values (∼30μm/s) can be separated from intermediate ones. Application for actual logging data still requires some noise reduction techniques such as stationary measurements downhole or data stacking among different depths. However, it provides a way of converting T2 distributions into actual pore size distributions even for downhole acquisitions, before the samples get to the laboratory for routine analysis. Besides the logging analysis, we also developed a theoretical approximation to the diffusion equation with partial absorptive contour conditions, by calculating appropriate transition rates between cells in an arbitrary grid, allowing a simple methodology for obtaining the NMR data based on pore imaging. Calculated rates can in principle be used for modeling/understanding different diffusion phenomena, such as exchange between pores or relaxation sites.