Modeling Oil Saturation Below a Present Day Free Water Level and Its Impact on Reserves Uncertainty: An Integrated Approach Using Logs, PGS Rock Typing, SCAL Modeling, and Saturation Depth Function

Hydrocarbon saturation below present-day free water levels (FWL) is observed in many fields and can be attributed to either past geologic events or more recent production-related pressure changes and fluid movement. However, modeling residual oil saturation (Sorw) below a present-day FWL is a topic of limited understanding within reservoir characterization, particularly in evaluating the impact on water injection efficiency and reserves uncertainty in dynamic reservoir modeling. The presence of significant volumes of residual oil below the FWL can have profound implications for reserves estimations and development scenarios in field development plans. This study, inspired by a recent oil discovery in clastic sediments on the Norwegian Continental Shelf, explores this phenomenon through an integrated approach that spans from core and log scale analyses to field-scale assessment. This paper will present a case-study showing the recognition of a significant paleo-oil column based on petrophysical logs and core data, and both the definition of a present-day FWL and prediction of a paleo FWL. This paper will further describe a versatile technique for modeling residual oil saturation below the current FWL by integrating geological and engineering data from routine (RCA) and special core analyses (SCAL), well logs, and 3D reservoir models. The methodology begins with a rigorous quality check of core analysis data and other relevant information to ensure accuracy and suitability of the data used. We then applied a novel rock typing technique based on similarities in pore geometry and structure (PGS), incorporating RCA and SCAL data. These were integrated into a newly developed Corey SCAL modeling method to establish static and dynamic saturation functions for each rock type, which were then used in 3D reservoir modeling and simulation. Subsequently, we estimated the SCAL uncertainty range for each rock type and integrated it into the reference 3D static and dynamic models. After assimilating all input data into the 3D reservoir models, production forecasts were generated, including sensitivity and uncertainty workflows. Additionally, we developed new water saturation model workflows for static modeling by implementing saturation depth functions (SDF) with established Pc-imbibition curves. Furthermore, a fishbone completion model for water injection wells was constructed, and production was forecasted under the selected scenario. A key result of this work is effectively modelling residual oil saturation below a current FWL by implementing PGS rock typing and a saturation depth function based on Pc- imbibition in both static and dynamic models. The presence of oil saturation below the current FWL matched the observation from core and logs and increased Initial Oil in Place (IOIP) by approximately 25% compared to the original case without residual oil modeling. Meanwhile, this also reduced the recoverable oil volume by approximately 11% compared to the reference case primarily due to decreased injectivity in water injection following relative permeability corrections based on SCAL modeling techniques. To mitigate this negative impact, we evaluated methods for improving injectivity using a fishbone completion model in water injector wells during reservoir simulation, which resulted in an incremental oil recovery of up to 9% compared to the base case scenario of this study. As a novelty, this study proposes a new solution for estimating oil saturation below the current FWL based on saturation depth functions that are consistent with rock typing and wettability physics derived from imbibition capillary pressure curves. Additionally, the value of SCAL modeling, particularly in capturing the uncertainty in reserves evaluation through relative permeability and PGS rock types, proves suitable for full-field reservoir simulations, uncertainty analyses, and field performance assessments. This workflow also facilitates permeability prediction as a function of porosity and irreducible water saturation while generating systematic saturation functions based on capillary pressure data.