Multidisciplinary Workflows Applied in Reservoir Characterization: A Heavy Oil Field Case Study During Early Stages of the Asset Life-Cycle

Abstract

Abstract New oil fields have been recently discovered in remote areas of the Peruvian Amazonian rainforest. Heavy oil was tested in Cretaceous age reservoirs of Marañon basin: Casablanca, Vivian and Chonta. Conceptual development options for these fields are being analyzed; that is why, a proper characterization of rock-fluid properties of reservoirs is particularly important in this early stage of the asset life-cycle to optimize the field development strategy. Several methodologies of reservoir characterization have been widely discussed in the literature; however not always interdisciplinary workflows are applied in data acquisition and processing for reservoir characterization. Study cases and lessons learned from studies carried out in a recently discovered heavy oil reservoir are discussed, as well as, the workflow applied to get representative SCAL data and integrated well test interpretation is described. On the one hand, the process to achieve representative SCAL data includes sample selection criteria, SCAL program, and data validation to come up with a high quality data set to refine reservoir models. Sample selection technique used for this study is based on Global Hydraulic Elements (Corbett et al. 2004)5, which is combined with sedimentological studies, electrofacies logs and statistics from geo-cellular 3D model. This is aimed to select representative core plug samples for a cost effective lab program execution. On the other hand, routine core analysis data was integrated into well test interpretation to understand flow units and select near wellbore flow models that are consistent with petrophysical data. Finally, after processing and validating information, a selected set of data was incorporated into reservoir models. The workflows discussed in this paper look forward to developing synergies in multy-disciplinary teams working on reservoir characterization, which could allow to improve the making decision process during early stage of the field.