In many reservoir studies, anisotropic permeability is often ignored or considered to have only simple relationships. Often, permeability anisotropy is modeled only between the vertical and horizontal directions, while permeability values in a horizontal plane are considered equal. In reality, the depositional history of the reservoir results in more complex behavior. Knowledge of the permeability anisotropy has important implications in several types of devlopment scenarios, thus it is important to have accurate estimates of these directional permeability values. For example, a partially-penetrating well that allows for vertical flow at depths below the completed interval requires knowledge of the vertical to horizontal permeability anisotropy. As another example, improved estimates of horizontal permeability anisotropy would have significance for directional drilling design.
In this work, the utility of temperature data as a matching parameter was investigated to estimate these directional permeability values. The study utilized a full-physics, thermal reservoir simulator and a nonlinear, least-squares regression algorithm for parameter estimation. By modeling block temperatures near the well, the study attempted to replicate the temperature data gathered from Distributed Temperature Survey (DTS) tools which use fibers to measure temperature history at the well. Using this method, the permeability anisotropy in two scenarios (vertical-horizontal and horizontal-horizontal) was estimated successfully with a high degree of accuracy. Even with the addition of synthetic noise to the temperature signal, the regression was robust in estimating the values successfully in the majority of anisotropy scenarios that were tested.
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