Application of Tracer-Based Workflow for Calibrating Reservoir Heterogeneity

Abstract

Capturing the correct reservoir heterogeneity in a geological model is critical for designing and accurately forecasting expected production benefits from improved/enhanced oil recovery processes. In simple terms, reservoir heterogeneity is often considered as a measure of statistical variation of static properties, such as porosity and permeability. The Lorenz coefficient and Dykstra-Parsons coefficient are two such measures of reservoir heterogeneity that account for these static effects. These measures are considered simplistic because the spatial distribution and arrangement of these properties is more critical for reservoir characterization than its statistical variation. The dynamic Lorenz coefficient is one such measure that accounts for the spatial distribution and arrangement of porosity and permeability. The dynamic Lorenz coefficient cannot be directly measured in the field but can be implicitly inferred from tracer data. This inferred heterogeneity will be influenced by the spatial distribution of static properties and can also be significantly influenced by multiphase flow effects, such as viscous fingering and gravity over/underride, which often arise from the differences in the viscosities and densities of the different phases involved. The dynamic Lorenz coefficient interpreted from a tracer test response lumps both static and multiphase (dynamic) effects into one measure of heterogeneity. During geological model construction, the dynamic Lorenz coefficient is also used to rank the model in terms of heterogeneity to select the most representative model. However, the geological models are ranked using fast single-phase/streamline simulations and are devoid of complications caused by adverse mobility or density effects. This creates a disconnect between the heterogeneity measures used to characterize a geological model and those available to characterize a reservoir. Thus, calibrating a geological model to field data is a laborious task. In this paper, we present a workflow that bridges this gap by decoupling the effect of adverse mobility to obtain an approximate measure of heterogeneity that can be cross-checked against the geological realizations to select the most representative model. The workflow developed in this paper is for inverted, seven-spot patterns and is mainly focused on water-wet reservoirs.