Detailed stratigraphic interpretation of borehole electrical images includes the classification of different bedding types, such as sand (sandstone) bedding or shale bedding. Successful interpretation depends on accurately determining the sandstone - shale boundary. When using the total gamma ray log to separate sandstones and shales, this boundary (cutoff value) can frequently be set at about 60 to 80 API units in the case of common reservoirs. Using KCl in the drilling fluids leads to an overall radioactivity increase of the formations and an increase in the gamma ray cutoff value. If the sandstones contain potassium-rich micas and feldspars or heavy minerals rich in thorium or uranium, their radioactivity increases and the gamma ray cutoff increases accordingly. The increased radioactivity can make the sandstone reservoirs look like shaly formations, and the estimation of the clay volume fraction (Vclay) from the total gamma ray log may become inaccurate. In this case, Vclay can be estimated from neutron porosity - bulk density crossplots, but this method has its own limitations (bad hole or hydrocarbon-bearing intervals). If the Vclay can be properly estimated from single clay indicators or from a combination of indicators, the ternary Shepard (1954) diagram may then be used for lithological classification: sand (0 to 25﹪ Vclay), clayey sand (25 to 50﹪ Vclay), sandy clay (50 to 75﹪ Vclay), clay (75 to 100﹪ Vclay).
The accuracy of Vclay estimation and of the sandstone and shale intervals delineation can be checked by using gamma ray - bulk density, gamma ray - neutron porosity and gamma ray - apparent resistivity crossplots. Each of these methods responds differently to the presence of clay, and their joint response allows the identification of lithological trends and patterns in the data, as well as the separation of sandstone and shale intervals by means of suitable gamma ray cutoff values. The separation of these intervals can be further validated by comparison with the static image resulting from the processing of borehole electrical imaging data (sandstones - light tones and shales - dark tones). This paper presents case studies regarding the application of these methods in hydrocarbon exploration wells.