Compositional Simulation of Cyclic Gas Injection in Liquid-Rich Shale Reservoirs Using Existing Simulators with a Framework for Incorporating Nanopores
- Ran Bi (Texas A & M University College Station) | Sheng Luo (Texas A & M University College Station) | Jodie Lutkenhaus (Texas A & M University College Station) | Hadi Nasrabadi (Texas A & M University College Station)
- Document ID
- Society of Petroleum Engineers
- SPE Improved Oil Recovery Conference, 31 August - 4 September, Tulsa, Oklahoma, USA
- Publication Date
- Document Type
- Conference Paper
- 2020. Society of Petroleum Engineers
- 5 Reservoir Desciption & Dynamics, 5.8 Unconventional and Complex Reservoirs, 5.1 Reservoir Characterisation, 5.5 Reservoir Simulation, 1.2.3 Rock properties, 5.4.2 Gas Injection Methods, 5.4 Improved and Enhanced Recovery, 5.1 Reservoir Characterisation, 5.7 Reserves Evaluation, 5.8.4 Shale Oil, 5.2.1 Phase Behavior and PVT Measurements, 5.2.2 Fluid Modeling, Equations of State
- Nanopores, Shale reservoirs, Gas injection, Compositional Simulation
- 64 in the last 30 days
- 69 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 28.00|
The current models for predicting the phase behavior of gas injection in shale can be highly unreliable because nanopores (with diameters less than 50 nm) form a significant pore volume in many shale formations. Conventional PVT models cannot describe the phase behavior in nanopores. Here, we present a practical framework to regenerate the PVT considering the shale nanopores effect for a more reliable compositional simulation of gas injection in shale reservoirs by using existing commercial simulators.
The pore-size distribution in shale reservoirs can be discretized into a bulk-region (fractures and macropores) and nanopores. We use a pore-size-dependent equation of state (PR-C EOS) to describe the phase behavior of the fluid for each pore. Bulk fluid characterization with laboratory PVT reports determines the bulk fluid parameters for the PR-C EOS. The confinement parameters for the PR-C EOS are from the reported database (Luo et al. 2018a). Further, multi-scale phase equilibria are calculated by minimizing the free energy. We model the multi-scale constant composition expansion and constant volume depletion with volume expansion per stage. The modeling generates multi-scale PVT (formation volume factor, saturation, etc.) for the shale reservoir, which is used to retrain the Peng–Robinson equation of state (PR EOS) by modifying the acentric factor, binary interactions, and critical temperature and pressure. The retrained PR EOS is then applied in a commercial compositional simulator to forecast gas injection improved oil recovery (IOR) in shale. We also use the updated gas saturations in the multi-scale PVT model to modify the relative permeability tables used in the compositional simulation.
We predict significantly higher gas production and lower oil production when the effect of shale nanopores on the phase behavior and updated relative permeability are considered in the compositional simulation of the primary depletion of shale reservoirs. In the gas injection improved oil recovery (IOR) stage, the cumulative oil production is enhanced with both the original and multi-scale PVT models. However, when the effect of nanopores is not considered in the compositional simulation, the increases in the cumulative oil production and cumulative gas production can be underestimated and overestimated, respectively. This can have significant consequences on the economic evaluation of the gas IOR projects in shale reservoirs.
The application of multi-scale phase equilibria in shale reservoirs is challenging in compositional simulators. Our proposed framework enables engineers to incorporate multi-scale phase equilibria from the PR-C EOS in their shale reservoir simulations. It does not require a change in the cubic equations of state in current developed commercial compositional simulators, thus preserving the efficiency of the compositional simulators.
|File Size||1 MB||Number of Pages||21|
Clark AJ. Determination of recovery factor in the Bakken formation, Mountrail County, ND. In SPE Annual Technical Conference and Exhibition 2009 Jan 1. Society of Petroleum Engineers. https://doi.org/10.2118/133719-STU
Dahaghi AK. Numerical simulation and modeling of enhanced gas recovery and CO2 sequestration in shale gas reservoirs: A feasibility study. In SPE international conference on CO2 capture, storage, and utilization 2010 Jan 1. Society of Petroleum Engineers. https://doi.org/10.2118/139701-MS
Du L, Chu L. Understanding anomalous phase behavior in unconventional oil reservoirs. In SPE Canadian Unconventional Resources Conference 2012 Jan 1. Society of Petroleum Engineers. https://doi.org/10.2118/161830-MS
Gamadi TD, Sheng JJ, Soliman MY, Menouar H, Watson MC, Emadibaladehi H. An experimental study of cyclic CO2 injection to improve shale oil recovery. In SPE improved oil recovery symposium 2014 Apr 12. Society of Petroleum Engineers. https://doi.org/10.2118/169142-MS
Hoffman BT. Huff-N-Puff gas injection pilot projects in the eagle ford. In SPE Canada Unconventional Resources Conference 2018 Mar 13. Society of Petroleum Engineers. https://doi.org/10.2118/189816-MS
Hoffman BT, Evans JG. Improved oil recovery IOR pilot projects in the Bakken formation. In SPE Low Perm Symposium 2016 May 5. Society of Petroleum Engineers. https://doi.org/10.2118/180270-MS
Jin B, Nasrabadi H. Phase behavior in shale organic/inorganic nanopores from molecular simulation. SPE Reservoir Evaluation & Engineering. 2018 Aug 1;21(03):626–37. https://doi.org/10.2118/187307-PA
Louk K, Ripepi N, Luxbacher K, Gilliland E, Tang X, Keles C, Schlosser C, Diminick E, Keim S, Amante J, Michael K. Monitoring CO2 storage and enhanced gas recovery in unconventional shale reservoirs: Results from the Morgan County, Tennessee injection test. Journal of Natural Gas Science and Engineering. 2017 Sep 1;45:11–25.
Luo S, Lutkenhaus JL, Nasrabadi H. Effect of Nano-Scale Pore Size Distribution on Fluid Phase Behavior of Gas IOR in Shale Reservoirs. In SPE Improved Oil Recovery Conference 2018 Apr 14. Society of Petroleum Engineers. https://doi.org/10.2118/190246-MS
Luo S, Lutkenhaus J, Nasrabadi H. A Framework for Incorporating Nanopores in Compositional Simulation to Model the Unusually High GOR Observed in Shale Reservoirs. In SPE Reservoir Simulation Conference 2019 Mar 29. Society of Petroleum Engineers. https://doi.org/10.2118/193884-MS
Pan* Y, Bi R, Zhou P, Deng L, Lee J. An Effective Physics-Based Deep Learning Model for Enhancing Production Surveillance and Analysis in Unconventional Reservoirs. In Unconventional Resources Technology Conference, Denver, Colorado, 22-24 July 2019 2019 Oct 16 (pp. 2579–2601). Unconventional Resources Technology Conference (URTeC); Society of Exploration Geophysicists. https://doi.org/10.15530/urtec-2019-145