Time‐lapse joint inversion of DC and seismic data

Abstract

The time-lapse joint inversion of geophysical data is required to image the evolution of oil reservoirs during production and enhanced oil recovery, CO2 sequestration, geothermal fields during production, active volcanoes, and the evolution of contaminant plumes. Joint inversion schemes reduce the uncertainty of the model in each monitoring stage, while time lapse inversion algorithms reduce time-related artifacts. There are several approaches that are possible to perform the time-lapse joint inverse problem. In this work, we select the structural joint inversion approach of Meju and Guallardo (the inversion looks for models with strcutural similarities) to perform the joint inversion of DC resistivity and seismic data. Timelapse inversion is performed with an actively timeconstrained (ATC) approach. In this approach, the subsurface is defined as a space-time model. All the snapshots are inverting together assuming a regularization over time of the sequence of snapshots. Still, this approach is flexible enough to allow for abrupt time-related changes in the areas where there are significant indications that these changes are effectively occurring. At the same time, the ATC approach removes inversion artefacts corresponding to spatial artefacts that are randomly distributed over time. We show the advantage of combining strcutural joint inversion and time-lapse inversion using a synthetic case corresponding to cross-hole seismic and DCresistivity data. We show that this approach reduces strongly artefact both with respect to individual inversion of the resistivity and seismic datasets and also with respect to the joint inversion of both data sets at each time step.