Utilizing Advanced Logs for Flow Unit Classification in Vertical Interference Test Modeling

Abstract

Vertical Interference tests (VIT) are used to determine the hydraulic connectivity between the formation sand intervals. This paper showcases an innovative workflow of using the petrophysical log attributes to characterize a heterogeneous reservoir sand by making use of ANN (Artificial Neural Net) and SMLP (Stratigraphic Modified Lorentz) based rock typing techniques as well as image based advanced sand layer computation techniques. Vertical interference test is either performed using a wireline formation testing tool with multiple flow probes deployed in a vertical sequence at desired depth points on the borehole wall or using a drill stem test configuration. Based on the test design, flow rates are changed using downhole pumps, which induces pressure transients in the formation. The measured pressure response is then compared with a numerical model to derive the reservoir parameters such as vertical permeability, hydraulic connectivity etc. The conventional way of model generation is to consider a section of reservoir sand as homogenous, which generally leads to over estimation or underestimation of vertical permeabilities. The technique proposed in this paper utilizes advanced logs such as image logs; magnetic resonance logs, water saturation and other advanced lithology logs to obey heterogeneity in the reservoir model by utilizing ANN/SMLP based rock-typing techniques. These rock types would be helpful in making a multi layer formation model for the VIT modeling and regression approach. The vertical interference test model is then used to determine the vertical permeability values for each of the individual rock types. The paper displays the workflow to utilize the rock type based layered formation model in vertical interference test modeling for a channel sand scenario.