Consideration of Elastic Properties and Stresses Anisotropy in Fracturing Planning

Abstract

Development of complex-build oil and gas reservoirs is associated with advanced technologies such as horizontal wells drilling and multi-stage hydraulic fracturing. Geomechanical modeling for hydraulic fracturing purposes is a fundamental tool for assessing technological constraints and risks, as well as increasing efficiency of reservoir treatment. In proposed approach of horizontal stresses modeling and calibration to the actual hydraulic fracturing data additional features considered to compensate low contrast of Poisson's ratio calculated from broadband acoustics: elastic properties TIV-anisotropy, variation of Biot coefficient adjusted to mechanical facies, correlations between static elastic properties and petrophysical parameters based on core measurements. Lab measurements on oriented core samples revealed elastic properties anisotropy that caused difference of the static young's modulus parallel and perpendicular to the formation bedding up to 80 – 100%, and for the Poisson's ratio is up to 10 – 20%. Considering these results stress calculation leads to a difference between an isotropic and anisotropic profile up to 20%, this has significant impact on the hydraulic fracture geometry. The rock behavior under load is different and is determined by the properties of the rock grains and the contact between them. Thus, the section separation into mechanical facies plays an important role when estimating elastic parameters, including Biot coefficient (α), which is different for shales, sand and/or carbonate, for example. Correct estimation of α with respect to mechanical facies allows achieving good agreement between stress calculation and actual measurements obtained with a mini-frac job, thereby increasing fracture geometry prediction accuracy. Another tool to compensate lack of stress contrast calculated based on standard 1D geomechanical workflow is the use of petrophysical parameters such as porosity, clay content, neutron density and its correlation with static elastic properties to estimate minimum horizontal stress. This method may improve geomechanical model matching with field observations, but it has a limited scope of application. In this paper demonstrated that additional study of the rock properties with special logging and core measurements at initial phase of field development planning may significantly reduce geomechanical modeling uncertainties and improve understanding of hydraulic fracturing and fracture geometry, which is a basis for hydrocarbon production and economic evaluation of the project or the whole asset. The paper presents adapted geomechanical modeling workflow based on special lab core testing and elastic properties anisotropy and Biot coefficient evaluation to adjust the horizontal stresses profiles in complex-build reservoirs to the field measurements and observations as well as to fracturing data in existing wells.

Using AI and Machine Learning to Indicate Shale Anisotropy and Assist in Completions Design

“…Using VTI based parameters or an anisotropy values directly measured from a sonic logging tool could be potentially led to issues such as underestimating formation stresses and breakdown pressures [26]. This could to being as inaccurate as simply using an isotropic approach.…”