Robust Non-Linear Inversion for Reservoir Deformation from Surface Displacement Data

Compacting and expanding reservoirs cause respectively subsidence and heave at the surface which at present can be measured using different geodetic methods. Knowing the source of compaction and expansion is of large value to our subsurface operations as it aids in assessment of reservoir conformance and possible containment issues. However, measured subsidence cannot be related one-on-one to actual reservoir compaction: An inversion process is required. Due to the spatial convolution and filtering nature of the subsurface on the actual reservoir compaction or expansion problem, inversion is a complicated process.

This paper describes an iterative inversion workflow, taking full advantage of the speed of semi-analytical forward models while adhering to the actual complexity of the subsurface captured in a detailed finite element model. The iterative scheme allows for handling of the ill-posed nature of the problem. The workflow presented here shows the utility of integrating geodetic data sources to estimate reservoir volume changes. This technique has proven to add value when it comes to monitoring areal and temporal changes in the reservoir. It is relatively easy to implement as it does not require large amounts of input data and can be applied to any field where surface deformation data is available.