INTEGRATED RESERVOIR CHARACTERIZATION IN DEEPWATER GULF OF MEXICO USING NUCLEAR MAGNETIC RESONANCE (NMR) FACTOR ANALYSIS AND FLUID SUBSTITUTION

摘要

A novel integrated workflow using Nuclear Magnetic Resonance (NMR) data is developed to evaluate sand reservoirs in deepwater Gulf of Mexico. Accurate characterization of the reservoir properties is the key to predict the formation producibility. Traditional interpretation methods based on Triple-Combo logs (density, neutron, resistivity and gamma ray) have been widely used to characterize clastic formations to provide cost-effective answers of lithology, porosity, saturation and permeability. Nevertheless, zones with fine grained rock texture or clay-rich thin beds represent low resistivity, causing net-to-gross estimation often pessimistic. Grain size variation and clay distribution also affect the vertical permeability and connectivity. Moreover, the traditional methods cannot provide other important quantities of interest such as reservoir properties, sand facies and reservoir quality indicators. The new approach incorporates modern techniques of NMR factor analysis and fluid substitution to fully characterize the formations by 1) identifying fluid types, evaluating clay distribution, quantifying porosity, saturation and permeability, 2) analyzing fluid facies from NMR factor analysis for rock typing to separate shale, clean sand and laminated sand intervals, 3) computing grain size distribution from a simulated 100% water-filled formation using NMR fluid substitution, 4) evaluating reservoir quality and producibility based on the reservoir properties estimated from 1) to 3). In this paper, we demonstrate the successful application of the proposed workflow to the wells in deepwater Gulf of Mexico. Interpretation from case studies are presented using wireline NMR data integrated with tri-axial resistivity, borehole image, formation testing and core analysis data. The results provide more accurate reservoir properties for better reservoir quality characterization.