Surface deformations generated as a result of oil production, waste or water reinjection can be applied to model reservoir deformations. This is referred to as inverse modeling. Inverse models presented in the literature are mostly based on the nucleus of strain approach, and apply one deformation data type (i.e., vertical displacements) as input. In this study, a new numerical model was developed based on the unidirectional deformation technique. In order to solve the inverse ill-posed problem, a regularization technique was developed. The main objective of this research was to study the effects of monitoring strategies on inverse simulation by applying combinations of surface deformation measurements as input. A detailed sensitivity analysis was therefore performed in order to optimize the data collection procedure. The sensitivity of the inverse simulation was examined based on the following parameters: observation area; geometry and number of benchmarks; and measurement error. The results indicated that adding benchmarks after a certain number did not significantly affect the simulation. The distribution pattern of benchmark points was also found to significantly affect the inverse simulation.


Ground surface deformations generated as a result of fluid/material injection or withdrawal, into or from the subsurface are easy to monitor and sensitive to subsurface pressure changes [1, 2, 3]. Induced surface deformation data can therefore be used to indirectly monitor subsurface deformations. This approach has considerable potential use in fast-paced projects, where continuous monitoring of reservoir deformation is vital: steam injection/steam-assisted gravity drainage, where the objective of screening is to monitor steam concentration zones in the subsurface; waste injection projects, in order to track and model induced deformations and fracture movements; general reservoir monitoring and optimization, where the objective is to monitor the behaviour of the reservoir with respect to production and reinjection processes. Applying surface deformation measurements in order to model subsurface deformation sources is referred to as solving for the inverse case. Direct and inverse models have been previously studied and reported on in the literature [4, 5, 6, 7, 8, 9, 10, 11, 12]. Previous studies on inverse modeling in the hydrocarbon industry are mostly based on the nucleus of strain approach [13], where subsurface deformation sources are simulated as point sources that expand or compact in all directions, representing expansion or compaction (e.g. [6, 10, 14, 15]). Most inverse simulations are developed based on one type of deformation data (i.e. vertical displacement measurements). Very few studies have focused on inverse simulation based on different combinations of surface displacement measurements (i.e., vertical displacements/tilt measurements) [16]. It has been revealed that tilt measurements are more appropriate for inverse modeling compared to vertical displacements [16]. The main focus of this paper was therefore, to numerically study the effect of the data collection procedure on reservoir inverse simulation, using combinations of surface tilt measurements.

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