Reactive Transport Modeling and Geophysical Monitoring of Bioclogging at Reservoir Scale
Abstract
In Microbial-Enhanced-Hydrocarbon-Recovery (MEHR), preferential bioclogging targets the growth of the biofilms (def. immobilized biopolymers with active cells embodied in it) in highly permeable thief zones to enhance sweep efficiency in oil reservoirs. During MEHR, understanding and controlling bioclogging is hindered by the lack of advanced modeling and monitoring tools; these deficiencies contribute to suboptimal performance. Our focus in this study was on developing a systematic approach to understand and monitor bioclogging at the reservoir scale using a combination of reactive transport modeling and geophysical imaging tools (EM & seismic). In this study, we created a realistic reservoir model from a heterogeneous gas reservoir in the Southern Sacramento basin, California; the model well (Citizen Green #1) was characterized using sonic, electrical, nuclear, and NMR logs for hydrologic and geophysical properties. From the simplified 2D log data model, a strip of size 150m x75m with several high permeability streaks is identified for bioclogging simulation experiments. From the NMR log data it is observed that a good linear correlation exist between logarithmic permeability (0.55- 3.34 log (mD)) versus porosity (0.041-0.28). L. mesenteroides was chosen as the model bacteria. In the presence of sucrose, it enzymatically catalyzes the production of dextran, a useful bioclogging agent. Using microbial kinetics from our laboratory experiment and reservoir heterogeneity, a reactive transport model (RTM) is established for two kinds of bioclogging treatments based on whether microbes are present in situ or are supplied externally. In both cases, sucrose media (1.5 M) is injected at the rate of 1 liter/s for 20 days into the center of high permeable strip to stimulate microbes. Simulations show that the high dextran production was deep into the formation from the injection well. This phenomenon can be explained precisely with bacterial kinetics and injection rate. In the in situ treatment, dextran contributes to a maximum porosity reduction of 9.2%, while in the exogenous microbes treatment, the dextran contributes to a maximum of 10.9% porosity reduction. After RTM, the potential geophysical signature of the treatment was evaluated using previously developed experimental rock physics models and realistic forward modeling approaches. Seismic experiments during dextran production performed by Kwan & Ajo-Franklin (2011) were combined with full waveform viscoelastic modeling to yield a predicted attenuation response from the dextran distributions modeled using RTM. The response suggests that crosswell attenuation tomography may be a viable approach for in situ monitoring of the bioclogging process. Modeling the EM response involved the induced polarization (IP) method, where the simulated resistance amplitude and phase changes can be attributed to porosity reduction. Our studies suggest that the IP signals provide a valuable additional indicator. Both geophysical data methods in a joint imaging approach potentially increase the resolution of each geophysical attribute change. Likewise, reactive transport modeling and geophysical monitoring can provide a powerful tool for predicting different bioclogging scenarios in subsurface. The combination may enhance our capabilities of controlling and monitoring the MEHR bioclogging process at reservoir scale.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2012
- Bibcode:
- 2012AGUFM.B23B0444S
- Keywords:
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- 0412 BIOGEOSCIENCES / Biogeochemical kinetics and reaction modeling;
- 0416 BIOGEOSCIENCES / Biogeophysics;
- 0466 BIOGEOSCIENCES / Modeling;
- 0545 COMPUTATIONAL GEOPHYSICS / Modeling