Accurate formation evaluation relies heavily on the quantification of rock matrix constituents. Rock mineralogy identification is commonly based on wireline spectroscopy measurements. Logging while drilling (LWD) techniques traditionally rely on density and neutron data to derive lithology. Historically, density and neutron tools that contain radioactive chemical sources were also the primary sensors used to determine porosity within the reservoir, which is a fundamental petrophysical attribute necessary to accurately quantify reserves. Although the potential irradiation and contamination risks associated with radioactive sources have always been known, the industry is now focusing toward reducing or eliminating their use, where possible.
The alternative source-less sensors for density and neutron tools, such as acoustic and nuclear magnetic resonance (NMR) measurements, were commonly used for porosity calculations. However, calculated porosities from acoustic measurements could contain significant errors arising from the uncertainty associated with the mineralogical composition. In addition, NMR porosity values can contain errors as a result of the effect of density and the hydrogen index of the hydrocarbons in place.
Advanced cutting analysis (ACA), either by X-ray fluorescence (XRF) and/or X-ray diffraction (XRD), provides an independent lithology from downhole tools. The lithology, matrix density, and slownesses computed from the minerals or directly measured by the XRD can, in turn, be used as input data for porosity calculations from sonic and/or NMR data. This helps to provide more accurate porosity measurements, as compared to the traditional calculated porosities, without using density and neutron tools. In addition, scanning electron microscopy (SEM) helps to enable the use of wellsite mineralogy, porosity, grain size distribution, and grain density from cuttings to calibrate the measurements from LWD acoustic and NMR tools.
This paper presents a comprehensive, cost effective method for multimineral formation evaluation using a combination of LWD and advanced mud logging, without the use of radioactive sources. A practical workflow with limitations is also presented.