This framework enhances predictions of formation breakdown pressures in tight gas formations, suggesting improved hydraulic fracturing outcomes.
One of the most critical parameters affecting the solution of coupled flow and geomechanics problems is the Biot coefficient. This parameter theoretically ranges from zero to one, with zero corresponding to the case of nearly solid rocks without interconnected pores (i.e., impermeable rocks) and one corresponding to the case of highly porous (or highly permeable) rocks. From a purely numerical point of view, this parameter controls the degree of coupling between flow and effective rock stresses. In the standard Biot poroelastic model, when this parameter is zero, the flow problem does not experience any changes due to mechanical displacements, and vice versa - the mechanics problem does not experience any changes in pore pressures. On the other hand, when this coefficient is one, the two problems are tightly coupled. Despite its criticality, this parameter is often misunderstood and misrepresented in the underlying coupled models for computing formation breakdown pressures. For example, this parameter can vary both spatially and vertically across different formations and is often a function of other rock parameters (i.e., porosity and permeability). Therefore, assuming its value to be constant throughout the analysis, as is often the case in most existing breakdown pressure models in the literature, may lead to inaccuracies, potentially resulting in inefficient hydraulic fracturing operations, and increased operational risks. In this work, we propose a computational framework, developed by Almani et al. (2021), that can handle the underlying heterogeneities of the Biot coefficient when computing formation breakdown pressure. Our results demonstrate that this framework can lead to more accurate predictions compared to conventional techniques that ignore these heterogeneities, enabling optimized frac job, and reduced operational costs, ultimately enhancing the economic efficiency of hydrocarbon recovery operations.
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Al-Ameer et al. (2025) studied this question.
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