Reservoir property mapping and monitoring from joint inversion of time-lapse seismic, electromagnetic, and production data

Abstract

We have developed a deterministic multiphysics joint inversion approach integrating seismic, electromagnetic (EM), and production data to map relevant reservoir properties, such as permeability and porosity, and the time evolution of the flooding front movement, i.e., saturation changes with time. These measurements are complementary in terms of their sensitivity to individual reservoir properties and their coverage of reservoir volumes. As a consequence, integration reduces ambiguities in the interpretation. In the workflow, a reservoir model is first built based on prior information. The production data are simulated by evolving the model in time based on the known well-control strategy. Simultaneously, the temporal and spatial distribution of fluid properties, such as saturation, salt concentration, density, and pressure are also obtained from the forward modeling. These properties, together with in situ rock properties, are transformed to formation resistivity and elastic properties using prescribed petrophysical relationships, such as Archie’s law and effective medium rock-physics models. From the transformation results, synthetic EM and full-waveform seismic data can be subsequently simulated. A Gauss-Newton optimization scheme is used to iteratively update the reservoir permeability and porosity fields until the mismatch between the synthetic data and the observed data becomes less than a predefined threshold. This inverse problem is usually highly underdetermined; hence, it is necessary to bring in prior information to further constrain the inversion. Different regularization approaches are investigated to facilitate incorporation of prior information into the joint inversion algorithm.

Quantitative seismic characterization of CO2 at the Sleipner storage site, North Sea

“…However, using additional input data from either multiparameter quantitative seismic imaging (S-wave velocity or P-wave quality factor), or from controlled-source electromagnetic (CSEM) surveys can drastically help the estimation and reduce the uncertainties (Hoversten et al, 2006;Gao et al, 2012;Liang et al, 2016). For example, resistivity is highly sensitive to CO 2 saturation (Park et al, 2013;Eliasson et al, 2014).…”

Uncertainty reduction through geologically conditioned petrophysical constraints in joint inversion

“…Garofalo et al (2015) use a physical relationship and impose similar layer geometry during joint inversion. Another strategy has been introduced and used by Hoversten et al (2006), Gao et al (2012b), Giraud et al (2013), and Liang et al (2016) who use constitutive equations linking petrophysical properties to physical properties to retrieve petrophysical properties.…”

Using multiphase fluid-flow modeling and time-lapse electromagnetics to improve 4D monitoring of CO2 in an EOR reservoir

“…work has incorporated flow simulations and EM methods to improve inversion of borehole EM for reservoir simulation (Haber and Holtham 2013), and the two have been combined with seismic data to help obtain estimates of permeability and porosity within a reservoir (Liang et al 2016). However, most prior works have utilized only two-phase flow models which lump together oil and gas phases.…”