Traditionally, time-consuming, numerical simulations are used to calculate and interpret poroelastic pressure changes induced by hydraulic fractures. In this work, we develop and apply semi-analytical models to calculate the poroelastic pressure signature and estimate the geometry of the propagating fracture. The speed of the analytical forward model allows us to apply inverse models (which require the forward model to be run hundreds of times) to compute the fracture geometry in near-real-time.

A 3-D, semi-analytical model is developed to calculate reservoir deformation, stress shadow, and pressure changes around multiple hydraulic fractures. The model is extended and combined with an inversion algorithm to calculate the geometry of the propagating fracture for a measured poroelastic pressure signature recorded in a monitoring well. The model is then applied to a real field scenario with a treatment well and a fractured monitoring well where the pressure signature measured in the monitoring wells is used to estimate the dimensions of the propagating fractures in several fracturing stages.

The analytical model presented here is shown to be very accurate for predicting the stress shadow of multiple propagating fractures. This model is used to quantify the impact of various operational unknowns on the poroelastic pressure signature. We consider scenarios where the pressure change in the monitoring well is measured through isolated fractures in the monitoring well. We demonstrate the impact of the number of propagating fractures, their length, height, net pressure, and the monitoring well fracture geometry on the observed pressure change. Based on this understanding, an inversion algorithm is developed to convert the recorded poroelastic pressure into the dimensions of the propagating fractures and the dimensions of the monitoring fractures. Finally, the method is used to interpret poroelastic pressure measurements recorded in a pair of wells in the Delaware basin to estimate fracture dimensions.

In this work, we showcase the development and application of a novel semi-analytical model to interpret poroelastic pressure signatures observed in isolated monitoring well fractures. The application of the new method to estimate fracture dimensions is shown using a newly developed inversion algorithm. The efficient computations provide clear evidence that the developed workflow can be used for near-real-time fracture diagnostics.

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