Abstract
Abstract
A new openhole logging service, RockViewSM, has been developed which provides lithological and quantitative mineralogical information for accurate formation evaluation. The assessment begins with elemental formation weights and follows with an interpretation of lithology and mineralogy. Lithologies are divided into general categories including sand, shale, coal, carbonates, and evaporites. Potentially identifiable minerals are quartz, potassium-feldspar, albite, calcite, dolomite, siderite, anhydrite, illite/smectite, kaolinite, glauconite, chlorite, pyrite, and others.
The logging system utilizes an electronic pulsed source to send high energy neutrons into the surrounding formation1–8. These neutrons quickly lose energy as a result of scattering, after which they are absorbed by the various atoms within the ambient environment. The scattered as well as the absorbed neutrons cause the atoms of the various elements to emit gamma rays with characteristic energies. These are measured with a scintillation detector, resulting in both inelastic and capture gamma ray energy spectra. A matrix inversion spectral fit algorithm is used to analyze these spectra in order to separate the total response into its individual elemental components. The prominent measured elements associated with subsurface rock formations include calcium, silicon, magnesium, carbon, sulfur, aluminum, and iron. Potassium, thorium, and uranium are measured separately with a natural gamma ray spectroscopy instrument9–11. The tool response is characterized for each individual element by placing it into formations of known chemical composition.
Interpretation of the data begins with an assessment of the elemental formation weights, which then leads to a determination of lithology and mineralogy. Each step in the process is guided by the examination of ternary plots containing selected elements. Magnesium is an extremely important part of the interpretation process since it distinguishes dolomite from calcite and helps to identify various types of clay.
Data from field examples is presented in order to illustrate the effectiveness of this technology.
Introduction
Traditional formation evaluation using log data involved interpretation of measurements that included natural gamma ray, neutron porosity, density, and resistivity. Over the past decade, there has been an increase in the number of petrophysicists who desire additional information, including mineralogy-based logs. Such data helps resolve ambiguities in the traditional methods and opens up the possibility for new deductions to optimize hydrocarbon production. If one is concerned about calcite or anhydrite cement in a sand matrix, for example, such suspicions can be resolved through a measurement of the amounts of Ca and S. Knowledge of the formation matrix components can also be used to provide a more accurate porosity through an enhanced interpretation of the neutron and density data. In general, the interpretation of any measurement can be enhanced when the formation matrix is understood.
A deductive approach to mineralogy is described herein, which begins by identifying the general lithology associated with each tool measurement as follows:Elements ? General Lithology ? Specific Lithology ? Mineralogy
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