Detecting Restricted Diffusion Effect when Identifying Hydrocarbons with NMR Logs
Authors: Bustos Ulises Daniel , Ortiz Alberto Cesar , Breda Eduardo W. , Costa Vagner L.F. 
Published: December 2007

Advanced nuclear magnetic resonance (NMR) methods for fluids identification and reservoir evaluation were developed recently. These techniques, focused on identifying and characterizing fluids in the reservoirs, were mostly applied in clastic and carbonate reservoirs. In such environments, fluid characterization with NMR logs is relatively simple when the fluid responds to standard models. However, exceptions to NMR models such as restricted diffusion produce variations in model behavior and cause erroneous answers. Experience shows that restricted diffusion occurs mostly in carbonates with water trapped in small pores and in short T2(ms) domains (bound water) in clastic formations. This effect reduces water diffusibility and produces NMR signals occurring in oil diffusion domains, with the consequent incorrect computation of liquid hydrocarbons.

The purpose of this study is the characterization of the restricted diffusion effect from rock samples measured in the laboratory with an NMR logging tool, as well as from field examples in diverse lithologies. It is expected that such analysis will help in reservoir petrophysical characterization and will avoid misinterpretations in fluid typing, when performing fluids identification based on NMR principles.

Since restricted diffusion phenomena have been observed in medium to long transverse relaxation times T2(ms), above T2 cutoff for free fluids (in moderate to high porosity environments), some possible explanations are proposed to understand such phenomena and the implications on reservoir evaluation both in exploratory and production wells.

Introduction

NMR logging tools provide valuable formation evaluation information that is difficult or impossible to obtain from other well logging measurements.

Previous methods of hydrocarbon identification such as shifted spectrum, time domain analysis, and differential spectrum relied on assumptions and oversimplified models, giving unreliable results when identifying fluids in the reservoirs. Moreover, recent NMR measurements based on diffusion are lacking both on proper minimum echo spacings to fully characterize short T1(ms) environments and in robustness in processing, because simple bidimensional inversion is applied. Both limitations give ambiguous responses in medium to heavy oils environments and in presence of exceptions to NMR models representing a big uncertainty when identifying water from hydrocarbons.1,2

Recent NMR methods for fluids identification3 allowed improvements of the fluids identification task by widening the range of viscosity recognized, separating overlapping water and hydrocarbon signals, and obtaining many valuable information related to the petrophysics of the reservoirs.

The technique applied in the present work is known as magnetic resonance fluid characterization diffusion-editing and has been described in detail by Hurliman3 and Freedman.4 The technique consists of a set of pulse sequences acquired in a stationary measurement with an NMR logging tool. The data obtained are then processed with tridimensional inversion algorithms, resulting in diffusion-T2 mappings (D-T2) on which the identification, characterization of fluids, and petrophysical evaluations are achieved. This was done on several samples of clastic and volcaniclastics rocks collected from outcrops and compared with some field examples.

The D-T2 maps interpretation are straightforward for fluids identification. However, in some cases it was observed variations between the predicted models and effective NMR signal responses, represented by the restricted diffusion phenomena.

Under certain conditions, diffusion of fluid filling the pore space in a reservoir is restricted. As a consequence, the fluid molecules diffuse less than expected by NMR models fitting the water signal into oil predicted response. The characterization of such phenomena adds a new challenge on the D-T2 maps interpretation to identify fluids when restricted diffusion is present and to avoid misinterpretations of hydrocarbons.