Increasing Reliability of Stress Characterization through Optimum Design and Sensitivity Analysis of Fracture Injection Tests, Coupled with Enhanced Geomechanical Analysis

Abstract

Diagnostic fracture injection tests (DFIT) are conducted to estimate the magnitude of the minimum horizontal stress (tectonic) and characterize essential reservoir properties, such as reservoir permeability and actual reservoir pressure in conventional and unconventional reservoirs. When properly designed, and conducted, this type of transient test can help operators to reliably extract important reservoir data and reduce related operational costs and time. This paper provides a state of the art sensitivity analysis based on real pressure data that describes the impact of DFIT design on reservoir parameters acquisition. In this study, the engineering steps to optimize the design, conduct the test and interpret acquired data are examined through a sensitivity analysis to obtain reliable results. Furthermore, the interpretations of the performed tests can be combined with an enhanced image log analysis (if available) to constrain the in-situ stress conditions, including the magnitude and direction for all three principal stress components. Multiple operational parameters, such as injection rate, injection duration, rate reduction, leak-off mechanism and fall-off duration could significantly impact the fracture extent and mechanical response of the rock, thus affecting the fluid flow regime after shut-in. Therefore, all these variables should be evaluated in the proposed methodology to optimize the test, which is the key difference between conventional design and the presented reservoir driven design. To quantify the impact of operational parameters in reservoir response and validate the proposed approach, extensive sensitivities are performed with a complete well data set from a typical unconventional play by running in-house fracture models, considering multiple testing parameters (such as injection schedule, fluid type, leak-off, and net pressure analysis). Eventually, the optimal injection scenario can be determined, which could be applicable for regions with similar geological conditions. This study demonstrates how uncertainties can be narrowed down when estimating the stress condition from fracture injection tests. The proposed approach can identify critical parameters and suggest best practices for diagnostic fracture tests under certain reservoir conditions. It can also be coupled with an enhanced image log analysis to fully determine the in-situ stresses magnitude and direction, which will increase the reliability of related geomechanical and reservoir analyses.