A New Pulsed Neutron Sonde for Derivation of Formation Lithology and Mineralogy

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

New Method for Determining Mineralogy and Matrix Properties From Elemental Chemistry Measured by Gamma Ray Spectroscopy Logging Tools

“…Applied mathematicians proved that RBF mapping functions provide more-accurate interpolations for multidimensional functions of many variables (Powell 2001) than do other interpolation methods. One of the attractive features of RBF interpolation is that neither densely populated nor large databases are required.…”

Influences of Al, Mg, and K on Calculating Concentrations of Other Formation Elements and Their Corrections in Geochemical Logging

“…The formation swas deemed to be one entity filled with different volumes of SiO 2 , CaCO 3 , FeCO 3 , CaSO 4 , and H 2 O; the major skeleton elements in the formation are Si, Ca, Fe, and S, as shown in Table 1 A constrained and weighted least-squares method is used to analyze simulated capture gamma-ray spectra of seven formations listed in Table 1 to get elemental relative yields because the method can ensure that physically feasible solutions are obtained for the individual contributions, or elemental yields. We obtained the relative yields of four elements, Si, Ca, Fe, and S; then, according to the detection sensitivity factors of these four elements and depth normalization factors of the seven formations (Ellis and Singer 2008, Pang 1991, Pemper et al 2006, Herron et al 2002, we calculated the dry weights of Si, Ca, Fe, and S. Dry weights of four elements obtained from spectral analysis were compared with real dry weights of various elements in the formation, as shown in Fig. 2, in which the diagonal dashed lines are the equivalent lines of calculated values and real values of the formation.…”