Formation Evaluation of Low Resistivity Low Contrast Hydrocarbon Clean Sands Using Well Logs and Saturation Height Function

Abstract Identification and estimation of hydrocarbon volumes in Low Resistivity Low Contrast (LRLC) pay zones has always been a challenging exercise. It is more challenging to evaluate and estimate hydrocarbon volumes in a clean sand formation with low GR API above established hydrocarbon-water contact or free water level. Low resistivity low contrast pay sands are hydrocarbon bearing reservoirs that have low resistivity due to several factors such as mineralogy, shale content, microporosity, salinity, anisotropy, bed thickness to mention a few. These hydrocarbon bearing formations are easily assumed to be wet by mere looking at the typical log responses of GR-RES-DEN-NEU combination, resulting in wrong volume estimate, loss of value by not completing hydrocarbon bearing intervals based on log interpretation and difficulty in history matching production against estimated volumes when the intervals are completed and producing. It is also important to note that the presence of these low resistivity low contrast pay clean sands at the reservoir crest with no known shale barrier or baffles demarcating the low contrast pay sands from the hydrocarbon sands which gives the impression of water on top of hydrocarbons. These LRLC pay sands have been observed across several reservoirs in this field of study in the Niger Delta and further complicates volumetric reconciliation between static, deterministic, and dynamic models. In this paper we explore various techniques, technologies and evaluation procedures including logging and data acquisition required to properly identify and evaluate the hydrocarbon saturations in these low contrasts, low gamma ray zones. This paper will also show how saturation height function was used to estimate the ideal hydrocarbon response and volumes in reservoirs affected. The findings in this paper will show the importance of integrating all available multi-disciplinary data to properly identify and evaluate these elusive hydrocarbon zones for proper hydrocarbon reserves volumes estimation & reservoir development.