Strain Type‐Curve Analysis During Recovery Using Evolutionary Polynomial Regression for Evaluating Confined Reservoir Properties

ABSTRACT Pressure changes in reservoirs lead to strain in the overlying confining unit, which can be measured near the ground surface using high‐precision strainmeters. We propose a methodology that adapts the classic Agarwal type curves used for analyzing recovery pressure data to interpret strain data. Poroelastic analyses indicate that plotting components of the strain tensor as a function of Agarwal time creates semi‐log straight lines. The average horizontal and vertical strains intersect the zero‐strain axis at times that are similar to the times determined using a similar analysis of the pressure. The intersection time gives a direct estimate of the hydraulic diffusivity. The relationship between the transformational strain and reservoir permeability, specific storage and porosity‐to‐fluid compressibility ratio was established using an Evolutionary Polynomial Regression (EPR) model. The model was trained and validated for different scenarios with the outlined reservoir parameters as inputs and simulated transformational strain as outputs. The result is an accurate model with good generalization power that will be used with strain data to estimate the bulk modulus of the solid and fluid and Poisson's ratio by assuming permeability is available from transient pressure well testing or other independent sources. The prediction and measurement uncertainties were also included in the solution process, leading to a distribution of the estimated parameters. The method was validated using (1) datasets from an idealized example created with a poroelastic simulator, and (2) field data measured at the North Avant Field during a recovery test conducted in a 530‐m reservoir.