--> Abstract: Time-Lapse Joint Inversion of Seismic and Resistivity Data during Production of Oil in Carbonate Rocks, by A. Revil, M. Karaoulis, and J. Zhang; #120034 (2012)
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Previous HitTimeNext Hit-Lapse Joint Inversion of Seismic and Resistivity Data during Production of Oil in Carbonate Rocks

A. Revil, M. Karaoulis, and J. Zhang
Colorado School of Mines, Dept. of Geophysics, Golden, CO, USA

Previous HitTimeNext Hit-lapse joint inversion of geophysical data is required for a number of important problems in geosciences including the management of oil and gas reservoirs and the sequestration of CO2 (e.g., Kowalsky et al., 2006). In some cases, the inclusion of the physics of the monitored process directly in the inversion of the geophysical data can help to reduce the non-uniqueness of the geophysical inverse problem (e.g., Liang et al., 2011). If we consider joint inversion problem of geophysical data alone, there are essentially two types of strategies that can be used, one based on the use of petrophysical models to link geophysical methods (e.g., Hertrich and Yaramanci, 2002; Rabaute et al., 2003; Kowalsky et al., 2006; Woodruff et al., 2010) and one based on the use of structural similarities between the sought physical properties (e.g., Gallardo and Meju, 2003, Linde et al., 2008). Because different rock properties are usually sensitive to different aspects of the texture of porous materials (e.g., fracture versus matrix properties for dual porosity systems), the joint inversion based on petrophysical models may have some difficulties in a certain number of cases while the joint inversion based on the structural similarities (Gallardo and Meju, 2003) may have a better chance to work out the contributions from the different property groups, especially for Previous HittimeNext Hit-lapse tomography.

Several strategies are also possible for the Previous HittimeNext Hit-lapse inversion of geophysical datasets. While sequential Previous HittimeNext Hit-lapse inversion is generally successful (e.g. Karaoulis et al, 2011a), the result is sensitive to the inversion of the first snapshot of the physical process under study. Thus, the traditional approach of inverting separately different snapshots and comparing the results may not be the favoured strategy here. The actively Previous HittimeNext Hit-constrained (ATC) approach of Kim and Karaoulis (Kim et al., 2009; Karaoulis et al., 2011a, b) seems to be a very suitable approach to invert simultaneously a complete Previous HittimeNext Hit-lapse geophysical dataset using Previous HittimeNext Hit as a fourth dimension and using a Previous HittimeNext Hit-based regularization term into a generalized cost function.

In this presentation, we combine the structural joint inversion and the active Previous HittimeNext Hit-constrained Previous HittimeNext Hit-lapse inversion together to invert cross-hole data and we discuss the advantages in combining these two approaches together for the monitoring of partial saturation changes during the production of oil in carbonate reservoirs. This approach will be first illustrated below on a simple problem. A joint Previous HittimeNext Hit lapse inversion between ERT and GPR is shown by Doetch et al, 2010. In their approach Previous HittimeNext Hit lapse inversions were used by using the difference inversion (La Brecque and Yang, 2001). This approach minimizes the differences with respect a background model of each Previous HittimeNext Hit step separately. In our approach, Previous HittimeTop is introduced to the system and encompasses all space models during the entire monitoring period (global system). The minimized cost function includes a global misfit for all data during the entire monitoring period.

 

AAPG Search and Discovery Article #120034©2012 AAPG Hedberg Conference Fundamental Controls on Flow in Carbonates, Saint-Cyr Sur Mer, Provence, France, July 8-13, 2012