The initial high cost of exploitation of the sustained, increasingly growing development of unconventional resources in Argentina has resulted in concentrating all efforts to increase well productivity while reducing construction and completion costs. The optimization of hydraulic fracture (HF) treatments is vitally important. It is the primary strategy used to achieve an optimal reservoir drainage area, consequently characterizing the fracture geometry, including the height, for the continuous improvement of HF treatment and planning.
Several types of technologies and methodologies are used to estimate fracture height during and after a hydraulic stimulation treatment. These technologies can provide information about the fracture geometry and extension in the near-wellbore (NWB) and far-field areas. The determination of a reliable correlation between those methodologies represents a challenge as a result of formation complexity, heterogeneity, and limitations of evaluation technologies. It is well-known that some areas in the Vaca Muerta formation contain layers that can act as fracture barriers and are responsible for fracture containment.
This paper presents a fast and simple methodology that uses conventional well logs [gamma ray (GR), sonic, and density] from pilot wells to identify potential fracture barriers. This approach establishes a means to evaluate the degree to which the rock will have the ability to control fracture height growth. This methodology was determined useful for planning perforation intervals or clusters placement, particularly in those formations with stress profile showing reduced stress contrast and, when complemented with geological information, this method also provides useful information for horizontal well trajectory. Case studies are provided to illustrate examples of the proposed fracture barrier index (FBI) being calibrated or compared to other fracture height assessment. Additionally, the benefits of adding this new approach to current methodologies and technologies to aid completion design optimization and decision making is discussed.