Integration of Advanced Logging Evaluation Techniques Proves Additional Reserves from Thin Bed, Low Resistivity Pay Formations

The biggest clastic reservoir based in Kuwait has been facing evaluation challenges over the thick intervals of highly laminated thin hydrocarbon layers. Conventional wireline tools have a limitation on resolution when it comes to addressing these thin beds. Therefore, the reserves are usually underestimated, and thin pays are often overlooked. This paper presents the integration of a variety of advanced Wireline tools in order to correctly evaluate and compute reserves from these thin pay zones. Acquisition of the triaxial induction tool enabled the study of resistivity anisotropy and the identification of thin pay zones through the distinct reading of the resistivity of the thin sand reservoir. The thin layers have also been further validated using high resolution advanced thin bed analysis from image logs. Advanced spectroscopy and NMR data were used to quantitively define the sand and shale fractions within the thin beds. These measurements were critical to input to improve the resistivity interpretation followed by a reliable estimate of the saturation. High resolution dielectric measurements provided resistivity-independent saturation information enhancing the NMR interpretation using water-filled porosity which was a key input into the identification of the heavy oil presence in Burgan. The newly identified thin pay zones have been further validated using the fluid sampling confirming presence of hydrocarbons with greater understanding of its properties and uniquely quantifying the mobile fluid fractions. The additional available reserves can only be properly determined by combining data from multiple sources to achieve a comprehensive evaluation. Resistivity anisotropy was observed based on the separation of vertical and horizontal resistivities and was therefore investigated to understand its root-cause over different zones. By integrating the results from the dielectric dispersion measurements, the diffusion-based NMR data, spectroscopy data, borehole image interpretation and high-resolution sand count delineation of different lithologic units at a finer scale, we were able to identify thin bedded sand-shale intervals in addition to pin-pointing the heavy oil intervals. Hydrocarbon saturations of individual sand layers showed improvement in hydrocarbon volumes, improvement in permeabilities across the studied zones and increased net pay estimations by 12%. Results from the fluid sampling performed across the newly identified thin pays have validated the advanced logging interpretation results and the presence of hydrocarbons. These intervals were overlooked by the standard basic evaluation and the reservoir potential has been revisited following the latest integrated advanced results. By combining the results of all these advanced wireline answer products, we were able to properly identify and quantify the additional available reserves and therefore change the classification of these reservoirs from poor to excellent with new development plan in place. The paper demonstrates the value solution of the high vertical resolutions taking advantage of the latest advanced technologies to enhance the characterization of laminated thin beds. The integrated advanced solution has enabled improved reservoir potential by the identification of new pay zones initially overlooked by the standard basic measurements.