In recent years, several papers have been published on the subject of rock properties, stress and permeability models in the Vaca Muerta unconventional formation, with the intention of understanding fractured well performance. In most cases, however, these publications have failed on providing sufficient information to adequately describe the generated models, nor have studied in detail the benefits and limitations of applying different schools of thought and incorporating field measurements during the design and evaluation of hydraulic fractures. This work seeks to explain a systematic approach to characterize, constrain and validate such models through integration of prefrac diagnostic injections, core data, independently-determined fracture dimensions, and postfrac production data. The final objective is to build predictive models that can be used to improve completion strategies in this promising but still immature play.

As high-permeability reservoirs approach their last years of productivity, oil and gas production will likely come from lowpermeability formations, requiring hydraulic-fracture stimulation to be economically promising. This is the case in Argentina with the recent development of unconventional reservoirs targeting the Vaca Muerta shale play.The success of a hydraulic-fracture job depends on several factors, including the formation geology itself, the formation mechanical properties, field-stress regime (direction and magnitude), minimum horizontal stress contrast, and the transition from the simulation to the execution of the fracture job. Production companies need tools that help them determine how successfully the hydraulic fractures have optimized well production and field development. These tools should provide information about hydraulic-fracture conductivity, geometry, complexity, and orientation. This paper presents the application of time-lapse anisotropy analysis, using data from an acoustic scanning platform combined with a gyro, to obtain information such as the propped fracture height and the hydraulic-fracture orientation. This information is essential in planning horizontal wells when the well axis is to be transverse to the direction of the fractures. Application of the acoustic scanning platform technology as a fracture optimization tool in the Vaca Muerta shale play allows for a comprehensive evaluation of the hydraulic-fracture geometry, which can be combined with post-stimulation production results to provide direct impact in the well production and field development.

Diagnostic fracture injection tests contain critical information for reservoir characterization and hydraulic fracturing design, defining every input and output of the simulation modeling process. They help to assess the expected fracture geometry, proppant pack conductivity, formation flow capacity, and optimum hydraulic fracture design. At the same time, these data provide the necessary means to place a frac job adequately. However, interpretation challenges and inherent modeling nonuniqueness demonstrate the need for more constraints to reduce the solution space. Proprietary workflows have been applied using a 3D planar shear decoupled hydraulic fracture simulator to several vertical wells in the Vaca Muerta play in Argentina. The generated information makes it possible to build models consistent with multiple independent measurements from bottom-hole gauges, near wellbore, and far-field assessments of fracture geometry, which permit us to better understand production performance of the wells. The proposed workflow can be utilized to collapse the learning curve in a significant and meaningful way, playing a vital role in the optimization of horizontal wells and the field development strategy.

The Jurassic- and Cretaceous-age Vaca Muerta formation of the Neuquén Basin, Argentina, is a heterogeneous self-sourcing reservoir that is complicated by tectonic and volcanic influences. As an unconventional reservoir, its characterization requires the evaluation of key properties related to the production drivers: reservoir quality (RQ), drilling quality (DQ), and completion quality (CQ). A methodology is presented to maximize horizontal well success by identifying optimum horizontal well landing locations through integration of multidimensional petrophysical and geomechanical properties. This ongoing case study identifies of the key properties for RQ, DQ, and CQ through correlation analysis and production validation. The methodology uses a systematic and quantitative probability calculation to determine the lateral landing score (LLS) for all depths along a vertical pilot wellbore. Core-calibrated petrophysical evaluations of the interbedded siliciclastics, organic shales, ash beds, and tight limestones of the Vaca Muerta quantify uncertainty in estimates of reservoir properties (e.g., mineralogy, maturity, porosity, fluid saturations, and permeability) and RQ. Stress profiles, calibrated using core evaluation and stress tests, provide a predictive model of geomechanical properties (e.g., anisotropic elastic properties, in-situ stresses, wellbore stability, and rock fluid sensitivity). These parameters are critical for DQ and CQ predictions. Production results define appropriate normalization and weighting of properties for the LLS probability. Tectonic stresses in the Vaca Muerta may promote horizontal fractures that create restrictions to fracture growth and/or induce pinch points. Previous approaches to determine the target location in an unconventional resource play using geomechanical inputs alone may not apply to the Vaca Muerta because they overlook the effects of the fracture complexity induced by the stress regime of the prograding depositional environment. A high LLS occurs where positive RQ, DQ, and CQ values exist in sections thick enough to drill. The LLS brings together measurements from multiple domains to provide a qualitative, comparative, and repeatable ranking of ideal landing locations in tectonically active unconventional plays. Implementing the LLS as a decision-making tool for horizontal well placement generates both an optimized landing point and completion design. The workflow is iterated with available horizontal well production data to validate the relevant production drivers.