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When core data, such as mineralogy, porosity, total organic carbon, and elastic properties, are available from a large multiwell database, it is possible to extract meaningful statistical relationships between the data. These relationships can then be applied in other wells with limited or no core data. X-ray diffraction (XRD) mineralogical data is unique in that it can readily be transformed to synthetic wireline geochemical elemental data, such as the weight fractions, aluminum, silicon, and calcium. This transformation establishes a relationship between the mineralogical data and the synthetic wireline geochemical data, which can be applied to "real wireline" geochemical data to select an appropriate set of minerals for prediction from the wireline geochemical data. Statistical optimization based approaches are generally used to perform this prediction of mineralogy from wireline data. The most difficult aspect of predicting mineralogy from wireline geochemical data is the selection of the proper mineral model. The proposed approach assists the analyst in the selection of the proper model. In addition, this paper shows how core XRD mineralogical data can be used to establish constraints between the predicted mineralogy, such as percent clay fraction illite greater than 60%. An accurate prediction of mineralogy from wireline geochemical data can be transformed to an accurate prediction of grain density, enabling an accurate prediction of total porosity (corrected for kerogen effects). The workflow described in this paper provides an effective approach for establishing and predicting mineralogy, grain density, and porosity from wireline geochemical data. This paper presents results for a Haynesville shale example. Finally, the proposed approach helps to maximize the value of the core data for shale gas plays.

Compensated thermal neutron porosity devices provide reliable estimates of formation porosity in standard borehole conditions. Departure from these conditions perturb the measurement and it is necessary to apply corrections to determine the true porosity. One common perturbation is due to the salinity of the formation water.As the salinity of the formation water increases, its hydrogen density (or index) decreases. By itself, this would cause the apparent porosity reading to decrease, reflecting a lower hydrogen content. The additional chlorine, however, causes an increase in the thermal neutron capture cross section (E) that depresses the thermal neutron flux in the formation. This, in turn, tends to increase the apparent porosity. Empirical correction charts have been established for these two competing trends. They are sufficient for correcting porosity readings for salinity effects. However, the presence of additional thermal neutron absorbers associated with either the rock matrix or the pore fluid can result in a residual error on the porosity estimate even after salinity correction. This arises because the correlation between E and porosity, used to derive the salinity correction, is no longer valid.An analysis of the response of a compensated thermal neutron device has been made in terms of the slowing-down length, and diffusion length. It provides a simple method of describing salinity, absorption and lithological effects, and results in a predictive model of the tool response that separates neutron absorption effects from changes in hydrogen index. The model is shown to conform to established salinity corrections as well as to measurements made in laboratory formations with large values of E. It provides a means of correcting apparent neutron porosity values for variations in formation E not associated with salinity. 639

A new geochemical logging tool has been developed to provide measurements of elements important to the mineralogical analysis of rock formations and geochemical stratigraphy. The measurement system uses a chemical americium-beryllium neutron source to introduce moderate energy neutrons into the surrounding environment. These neutrons lose energy through scattering reactions and are eventually absorbed by materials in the borehole, the formation and the tool itself. The scattering and absorption reactions cause various elements among the atoms in the surrounding materials to emit gamma rays which have characteristic energies. Emitted gamma ray spectra are detected and recorded using a large bismuth germanate scintillation detector coupled to a high-efficiency photomultiplier and pulse-height analyzer.The recorded 256-channel spectra are analyzed to derive individual contributions, or elemental yields, arising from neutron capture reactions involving hydrogen, silicon, calcium, iron, sulfur, potassium, titanium, gadolinium, magnesium, aluminum and chlorine. The spectral analysis is performed with a constrained, weighted least-squares solver to ensure physically meaningful solutions are obtained for the elemental yields. Additional signals from inelastic neutron reactions with oxygen, carbon, silicon, calcium, and iron are treated separately in the spectral fitting process.The paper discusses several subjects including basic operation of the tool, derivation of characteristic elemental spectral responses, processing of the recorded spectra to obtain elemental yields and the conversion to elemental weight fractions for downstream formation mineralogy evaluations. Example logs from initial field tests are presented to demonstrate tool performance under various borehole conditions and lithologic environments including sandstone and carbonate reservoirs as well as organic shales.

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