Physics-Based Fluid-Flow Modeling of Liquids-Rich Shale Reservoirs Using a 3D Three-Phase Multiporosity Numerical-Simulation Model
- Bruno A. Lopez Jimenez (Schulich School of Engineering, University of Calgary) | Roberto Aguilera (Schulich School of Engineering, University of Calgary)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- November 2019
- Document Type
- Journal Paper
- 1,501 - 1,526
- 2019.Society of Petroleum Engineers
- stress-dependent properties, shale reservoirs, adsorption, diffusion from solid kerogen
- 3 in the last 30 days
- 110 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
Production from liquids-rich shale reservoirs in the US and Canada has increased significantly during the past few years. However, a rigorous understanding of shale rocks and fluid flow through them is still limited and remains a challenge. Thus, the objective of our research is developing a 3D physics-based model for simulating fluid flow through these types of multiporosity rocks. This is important given the recent spread of these types of reservoirs throughout the world.
Simulation of liquids-rich shale reservoirs is performed with the construction of an original fully implicit 3D multiphase modified black-oil finite-difference numerical formulation, which uses a multiporosity approach as well as diffusion from solid kerogen. The multiporosity system includes adsorbed porosity, organic porosity, inorganic porosity, natural-fracture porosity, and hydraulic-fracture porosity. A numerical model is developed with capabilities to handle dissolved gas in the solid part of the organic matter, adsorption/desorption from the organic pore walls, viscous- and non-Darcy-flow mechanisms (slip flow and Knudsen diffusion), and stress-dependent properties of natural and hydraulic fractures.
Examples of simulated results are presented as crossplots of pressure, production rates, and cumulative production vs. time. These plots are used to show the contributions of free gas, adsorbed gas, and dissolved gas to fluid production from liquids-rich shale reservoirs. Results indicate that both desorption and gas diffusion positively affect shale performance. Simulation results demonstrate that not taking into account desorption and diffusion from solid kerogen leads to underestimating production from liquids-rich shale reservoirs. Furthermore, the simulation study shows that long periods of time are required for the effects of these two mechanisms to be manifested. This helps to explain why shales have been produced over long periods of time (several decades), such as in the case of Devonian wells in the Appalachian Basin.
The type of 3D simulation model for multiporosity liquids-rich shale reservoirs developed in this paper is not currently available in the literature. The approach implemented in this paper provides a novel and important foundation for simulating complex shale reservoirs.
|File Size||2 MB||Number of Pages||26|
Aguilera, R. 2010. Flow Units: From Conventional to Tight Gas to Shale Gas Reservoirs. Presented at the Trinidad and Tobago Energy Resources Conference, Port of Spain, Trinidad, 27–30 June. SPE-132845-MS. https://doi.org/10.2118/132845-MS.
Aguilera, R. 2014. Flow Units: From Conventional to Tight-Gas to Shale-Gas to Tight-Oil to Shale-Oil Reservoirs. SPE Res Eval & Eng 17 (2): 190–208. SPE-165360-PA. https://doi.org/10.2118/165360-PA.
Alfi, M., Yan, B., Cao, Y. et al. 2014. How to Improve Our Understanding of Gas and Oil Production Mechanisms in Liquid-Rich Shale. Presented at the SPE Annual Technical Conference and Exhibition, Amsterdam, 27–29 October. SPE-170959-MS. https://doi.org/10.2118/170959-MS.
Alfi, M., Yan, B., Cao, Y. et al. 2015. Microscale Porosity Models as Powerful Tools to Analyze Hydrocarbon Production Mechanisms in Liquid Shale. J Nat Gas Sci Eng 26 (September): 1495–1505. https://doi.org/10.1016/j.jngse.2015.08.002.
Alharthy, N. S. 2015. Compositional Modeling of Multiphase Flow and Enhanced Oil Recovery Prospects in Liquid-Rich Unconventional Reservoirs. PhD dissertation, Colorado School of Mines, Golden, Colorado.
Alharthy, N., Teklu, T., Kazemi, H. et al. 2016. Compositional Rate Transient Analysis in Liquid Rich Shale Reservoirs. Presented at the SPE Annual Technical Conference and Exhibition, Dubai, 26–28 September. SPE-181699-MS. https://doi.org/10.2118/181699-MS.
Cao, Y., Yan, B., Alfi, M. et al. 2015. A Novel Compositional Model of Simulating Fluid Flow in Shale Reservoirs–Some Preliminary Tests and Results. Presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, Abu Dhabi, 14–16 September. SPE-175589-MS. https://doi.org/10.2118/175589-MS.
Cipolla, C. L., Lolon, E. P., Erdle, J. et al. 2009. Modeling Well Performance in Shale-Gas Reservoirs. Presented at the SPE/EAGE Reservoir Characterization and Simulation Conference, Abu Dhabi, 19–21 October. SPE-125532-MS. https://doi.org/10.2118/125532-MS.
Coats, K. H. 1985. Simulation of Gas Condensate Reservoir Performance. J Pet Technol 37 (10): 1870–1886. SPE-10512-PA. https://doi.org/10.2118/10512-PA.
Eveline, V. F., Akkutlu, I. Y., and Moridis, G. J. 2016. Impact of Hydraulic Fracturing Fluid Damage on Shale Gas Well Production Performance. Presented at the SPE Annual Technical Conference and Exhibition, Dubai, 26–28 September. SPE-181677-MS. https://doi.org/10.2118/181677-MS.
Fragoso, A., Lopez Jimenez, B. A., Aguilera, R. et al. 2019. Matching of Pilot Huff-and Puff-Gas Injection Project in the Eagle Ford Shale Using a 3D 3-Phase Multiporosity Numerical Simulation Model. Paper presented at the SPE Annual Technical Conference and Exhibition, Calgary, Alberta, Canada, 30 September–2 October. SPE-195822-MS. https://doi.org/10.2118/195822-MS.
Haghshenas, B., Soroush, M., Brohi, I. et al. 2014. Simulation of Liquid-Rich Shale Gas Reservoirs With Heavy Hydrocarbon Fraction Desorption. Presented at SPE Unconventional Resources Conference, The Woodlands, Texas, 1–3 April. SPE-168968-MS. https://doi.org/10.2118/168968-MS.
Javadpour, F. 2009. Nanopores and Apparent Permeability of Gas Flow in Mudrocks (Shales and Siltstone). J Can Pet Technol 48 (8): 16–21. PETSOC-09-08-16-DA. https://doi.org/10.2118/09-08-16-DA.
Javadpour, F., Fisher, D., and Unsworth, M. 2007. Nanoscale Gas Flow in Shale Gas Sediments. J Can Pet Technol 46 (10): 55–61. PETSOC-07-10-06. https://doi.org/10.2118/07-10-06.
Kazemi, H., Merrill, L. S. Jr., Porterfield, K. L. et al. 1976. Numerical Simulation of Water-Oil Flow in Naturally Fractured Reservoirs. SPE J. 16 (6): 317–326. SPE-5719-PA. https://doi.org/10.2118/5719-PA.
Li, N., Ran, Q., Li, J. et al. 2013. A Multiple-ContinuumModel for Simulation of Gas Production From Shale Gas Reservoirs. Presented at the SPE Reservoir Characterization and Simulation Conference and Exhibition, Abu Dhabi, 16–18 September. SPE-165991-MS. https://doi.org/10.2118/165991-MS.
Lopez, B. and Aguilera, R. 2013. Evaluation of Quintuple Porosity in Shale Petroleum Reservoirs. Presented at the SPE Eastern Regional Meeting, Pittsburgh, Pennsylvania, 20–22 August. SPE-165681-MS. https://doi.org/10.2118/165681-MS.
Lopez, B. and Aguilera, R. 2015a. Physics-Based Approach for Shale Gas Numerical Simulation: Quintuple Porosity and Gas Diffusion From Solid Kerogen. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 28–30 September. SPE-175115-MS. https://doi.org/10.2118/175115-MS.
Lopez, B. and Aguilera, R. 2015b. Sorption-Dependent Permeability of Shales. Presented at the SPE/CSUR Unconventional Resources Conference, Calgary, 20–22 October. SPE-175922-MS. https://doi.org/10.2118/175922-MS.
Lopez Jimenez, B. A. and Aguilera, R. 2018. Petrophysical Quantification of Multiple Porosities in Shale-Petroleum Reservoirs With the Use of Modified Pickett Plots. SPE Res Eval & Eng 21 (1): 187–201. SPE-171638-PA. https://doi.org/10.2118/171638-PA.
Loucks, R. G., Reed, R. M., Ruppel, S. C. et al. 2010. Preliminary Classification of Matrix Pores in Mudrocks. GCAGS Trans. 60: 435–441.
Piedrahita, J. A. and Aguilera, R. 2017. Models for Calculating Organic and Inorganic Porosities in Shale Oil Reservoirs. Presented at the SPE Latin America and Caribbean Petroleum Engineering Conference, Buenos Aires, 18–19 May. SPE-185591-MS. https://doi.org/10.2118/185591-MS.
Piedrahita, J., Lopez Jimenez, B., and Aguilera, R. 2019. Generalized Methodology for Estimating Stress-Dependent Properties in a Tight Gas Reservoir and Extension to Drill-Cuttings Data. SPE Res Eval & Eng 22 (1): 173–189. SPE-189972-PA. https://doi.org/10.2118/189972-PA.
Rubin, B. 2010. Accurate Simulation of Non-Darcy Flow in Stimulated Fractured Shale Reservoirs. Presented at the SPE Western Regional Meeting, Anaheim, California, 27–29 May. SPE-132093-MS. https://doi.org/10.2118/132093-MS.
Shabro, V., Torres-Verdin, C., and Sepehrnoori, K. 2012. Forecasting Gas Production in Organic Shale With the Combined Numerical Simulation of Gas Diffusion in Kerogen, Langmuir Desorption From Kerogen Surfaces, and Advection in Nanopores. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 8–10 October. SPE-159250-MS. https://doi.org/10.2118/159250-MS.
Sondergeld, C. H., Ambrose, R. J., Rai., C. S. et al. 2010. Micro-Structural Studies of Gas Shales. Presented at the SPE Unconventional Gas Conference, Pittsburgh, Pennsylvania, 23–25 February. SPE-131771-MS. https://doi.org/10.2118/131771-MS.
Song, H., Li, Z., Wang, Y. et al. 2015. A Novel Approach for Modeling Gas Flow Behaviors in Unconventional Reservoirs With Nanoporous Media. Presented at the International Petroleum Technology Conference, Doha, 6–9 December. IPTC-18316-MS. https://doi.org/10.2523/IPTC-18316-MS.
Spivak, A. and Dixon, T. N. 1973. Simulation of Gas-Condensate Reservoirs. Presented at the SPE Symposium on Numerical Simulation of Reservoir Performance, Houston, 11–12 January. SPE-4271-MS. https://doi.org/10.2118/4271-MS.
Swami, V. 2012. Shale Gas Reservoir Modeling: From Nanopores to Laboratory. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 8–10 October. SPE-1630365-STU. https://doi.org/10.2118/163065-STU.
Swami, V. 2013. Development of a “Quad Porosity” Numerical Flow Model for Shale Gas Reservoirs. Master’s thesis, University of Calgary, Calgary (January 2013).
Swami, V. and Settari, A. T. 2012. A Pore Scale Gas Flow Model for Shale Gas Reservoir. Presented at the SPE Americas Unconventional Resources Conference, Pittsburgh, Pennsylvania, 5–7 June. SPE-155756-MS. https://doi.org/10.2118/155756-MS.
Swami, V., Settari, A. T., and Javadpour, F. 2013. A Numerical Model for Multi-Mechanism Flow in Shale Gas Reservoirs With Application to Laboratory Scale Testing. Presented at the EAGE Annual Conference & Exhibition incorporating SPE Europec, London, 10–13 June. SPE-164840-MS. https://doi.org/10.2118/164840-MS.
Wu, P. and Aguilera, R. 2012. Investigation of Gas Shales at Nanoscale Using Scan Electron Microscopy, Transmission Electron Microscopy and Atomic Force Microscopy. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 8–10 October. SPE-159887-MS. https://doi.org/10.2118/159887-MS.
Wu, Y. S., Li, J., Ding, D. et al. 2013. A Generalized Framework Model for Simulation of Gas Production in Unconventional Gas Reservoirs. Presented at SPE Reservoir Simulation Symposium, The Woodlands, Texas, 18–20 February. SPE-163609-MS. https://doi.org/10.2118/163609-MS.
Yan, B., Alfi, M., Cao, Y. et al. 2015. Extended Abstract: Advanced Multiple Porosity Model for Fractured Reservoirs. Presented at the International Petroleum Technology Conference, Doha, 6–9 December. IPTC-18308-MS. https://doi.org/10.2523/IPTC-18308-MS.
Zhang, T., Ellis, G. S., Ruppel, S. C. et al. 2012. Effect of Organic-Matter Type and Thermal Maturity on Methane Adsorption in Shale-Gas Systems. Org. Geochem. 47 (June): 120–131. https://doi.org/10.1016/j.orggeochem.2012.03.012.