Estimation of Pore-Network Characteristics and Irreducible Saturations in Wolfcamp and Eagle Ford Shales Using Low-Pressure-Nitrogen-Adsorption/Desorption-Isotherm Measurements
- Shiv Prakash Ojha (University of Oklahoma) | Siddharth Misra (University of Oklahoma) | Ali Tinni (University of Oklahoma) | Carl H Sondergeld (University of Oklahoma) | Chandra Rai (University of Oklahoma)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- May 2018
- Document Type
- Journal Paper
- 373 - 391
- 2018.Society of Petroleum Engineers
- Pore size distribution, Residual Saturation, Pore connectivity, Percolation Theory, Adsorption Desorption
- 6 in the last 30 days
- 358 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 10.00|
|SPE Non-Member Price:||USD 30.00|
Pore-network characteristics, such as pore-size distribution (PSD), pore connectivity, and pore complexity, along with irreducible saturations in shales, are important petrophysical parameters for accurate estimation of absolute and relative permeability curves of various phases. We apply a method for estimation of these petrophysical parameters in shales by processing the low-pressure-nitrogen-adsorption/desorption (AD) measurements. The method uses effective-medium theory, percolation theory, and critical-path analysis (CPA) to quantify the transport properties of shales. The method has been applied to 35 samples of Eagle Ford and Wolfcamp Shales with different composition and from different maturity windows. Further, samples from the gas and oil windows of Eagle Ford Shale Formation were low-temperature plasma ashed to study the effect of the removal of organic matter on pore-network characteristics and irreducible saturations.
The estimated PSDs of condensate-window samples from Wolfcamp samples are significantly different from those of Eagle Ford samples. Our interpretation methodology indicates that the Eagle Ford samples exhibit better long-range pore connectivity and lower pore complexity compared with Wolfcamp samples. Consequently, Eagle Ford samples from oil and gas windows suggests better flow capacity compared with Wolfcamp samples from the condensate window. Moreover, the pore-network characteristics of kerogen from gas-window samples are significantly different from those of oil window samples. The estimated irreducible saturations for the samples collected from 100-ft interval in Eagle Ford gas window, 30-ft interval in Eagle Ford oil window, and the 60-ft interval in the Wolfcamp condensate window of shale formations exhibit minimal variation with depth. The samples exhibit large variations in organic content, pore connectivity, range of connected-pore network, and pore complexity that do not affect the irreducible-saturation estimates.
|File Size||1 MB||Number of Pages||19|
Al-Kharusi, A. S. and Blunt, M. J. 2007. Network Extraction from Sandstone and Carbonate Pore Space Images. J. Pet. Sci. Eng. 56 (4): 219–231. https://doi.org/10.1016/j.petrol.2006.09.003.
Arns, J. Y., Robins, V., Sheppard, A. P. et al. 2004. Effect of Network Topology on Relative Permeability. Transport Porous Med. 55 (1): 21–46. https://doi.org/10.1023/B:TIPM.0000007252.68488.43.
Avseth, P., Mukerji, T., and Mavko, G. 2010. Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk. Cambridge, UK: Cambridge University Press.
Bangia, V. K., Yau, F. F., and Hendricks, G. R. 1993. Reservoir Performance of a Gravity-Stable, Vertical CO2 Miscible Flood: Wolfcamp Reef Reservoir, Wellman Unit. SPE Res Eval & Eng 8 (4): 261–269. SPE-22898-PA. https://doi.org/10.2118/22898-PA.
Barrett, E. P., Joyner, L. G., and Halenda, P. P. 1951. The Determination of Pore Volume and Area Distributions in Porous Substances. I. Computations from Nitrogen Isotherms. I. Computations from Nitrogen Isotherms. J. Am. Chem. Soc. 73 (1): 373–380. https://doi.org/10.1021/ja01145a126.
Capline Pipeline. 2011. Capline Pipline Crude Assay Report, http://www.caplinepipeline.com/reports1.aspx (accessed 16 November 2016).
Chaudhary, A. S. 2011. Shale Oil Production Performance from a Stimulated Reservoir Volume. MS Thesis, Texas A&M University, College Station, Texas (August 2011).
Clarkson, C. R., Solano, N., Bustin, R. M. et al. 2013. Pore Structure Characterization of North American Shale Gas Reservoirs Using USANS/SANS, Gas Adsorption, and Mercury Intrusion. Fuel 103 (January): 606–616. https://doi.org/10.1016/j.fuel.2012.06.119.
Cluff, R. M. and Byrnes, A. P. 2010. Relative Permeability in Tight Gas Sandstone Reservoirs—The “Permeability Jail” Model. Presented at the SPWLA 51st Annual Logging Symposium, Perth, Australia, 19–23 June. SPWLA-2010-58470.
Cohan, L. H. 1938. Sorption Hysteresis and the Vapor Pressure of Concave Surfaces. J. Am. Chem. Soc. 60 (2): 433–435. https://doi.org/10.1021/ja01269a058.
Dacy, J. M. 2010. Core Tests for Relative Permeability of Unconventional Gas Reservoirs. Presented at SPE Annual Technical Conference and Exhibition, Florence, Italy, 19–22 September. SPE-135427-MS. https://doi.org/10.2118/135427-MS.
Dadmohammadi, Y., Misra, S., Sondergeld, C. H. et al. 2016a. Simultaneous Estimation of Intrinsic Permeability, Effective Porosity, PoreVolume Compressibility, and Klinkenberg-Slip Factor of Ultra-Tight Rock Samples Based on Laboratory Pressure-Step-Decay Method. Presented at SPE Low Perm Symposium, Denver, 5–6 May. SPE-180266-MS. https://doi.org/10.2118/180266-MS.
Dadmohammadi, Y., Misra, S., Sondergeld, C. H. et al. 2016b. Improved Petrophysical Interpretation of Laboratory Pressure-Step-Decay Measurements on Ultra-Tight Rock Samples. Presented at the Unconventional Resources Technology Conference, San Antonio, Texas, 1–3 August. URTEC-2441857-MS. https://doi.org/10.15530/URTEC-2016-2441857.
Dadmohammadi, Y., Misra, S., Sondergeld, C. H. et al. 2017. Petrophysical Interpretation of Laboratory Pressure-Step-Decay Measurements on Ultra-Tight Rock Samples. Part 1–In the Presence of Only Gas Slippage. J. Pet. Sci. Eng. 156 (July): 381–395. https://doi.org/10.1016/j.petrol.2017.06.013.
Daigle, H., Ezidiegwu, S., and Turner, R. 2015. Determining Relative Permeability in Shales by Including the Effects of Pore Structure on Unsaturated Diffusion and Advection. Presented at SPE Annual Technical Conference and Exhibition, Houston, 28–30 September. SPE-175019-MS. https://doi.org/10.2118/175019-MS.
Ghanbarian, B., Daigle, H., Hunt, A. G. et al. 2015. Gas and Solute Diffusion in Partially Saturated Porous Media: Percolation Theory and Effective Medium Approximation Compared with Lattice Boltzmann Simulations. J. Geophys. Res.-Sol. Ea. 120 (1): 182–190. https://doi.org/10.1002/2014JB011645.
Ghanbarian, B., Hunt, A. G., Ewing, R. P. et al. 2014. Universal Scaling of the Formation Factor in Porous Media Derived by Combining Percolation and Effective Medium Theories. Geophys. Res. Lett. 41 (11): 3884–3890. https://doi.org/10.1002/2014GL060180.
Ghanbarian, B., Sahimi, M., and Daigle, H. 2016. Modeling Relative Permeability of Water in Soil: Application of Effective-Medium Approximation and Percolation Theory. Water Resour. Res. 52 (7): 5025–5040. https://doi.org/10.1002/2015WR017903.
Ghanbarian-Alavijeh, B. and Hunt, A. G. 2012. Comparison of the Predictions of Universal Scaling of the Saturation Dependence of the Air Permeability with Experiment. Water Resour. Res. 48 (8): W08513. https://doi.org/10.1029/2011WR011758.
Gobin, O. C. 2006. SBA-16 Materials: Synthesis, Diffusion and Sorption Properties. Seminar thesis, Laval University, Quebec, Canada (January 2006).
Gregg, S. J. and Sing, K. S. 1983. Adsorption, Surface Area, and Porosity. Academic Press: New York.
Harkins, W. D. and Jura, G. 1944. Surfaces of Solids. XIII. A Vapor Adsorption Method for the Determination of the Area of a Solid without the Assumption of a Molecular Area, and the Areas Occupied by Nitrogen and Other Molecules on the Surface of a Solid. J. Am. Chem. Soc. 66 (8): 1366–1373. https://doi.org/10.1021/ja01236a048.
Hunt, A., Ewing, R., and Ghanbarian, B. 2014. Percolation Theory for Flow in Porous Media, third edition. New York City: Springer International Publishing.
Khoshghadam, M., Khanal, A., and Lee, W. J. 2015. Impact of Fluid, Rock and Hydraulic Fracture Properties on Reservoir Performance in Liquid-Rich Shale Oil Reservoirs. Presented at Unconventional Resources Technology Conference, San Antonio, Texas, 20–22 July. URTEC-2154207-MS. https://doi.org/10.15530/URTEC-2015-2154207.
Kruk, M., Antochshuk, V., Jaroniec, M. et al. 1999. New Approach to Evaluate Pore Size Distributions and Surface Areas for Hydrophobic Mesoporous Solids. J. Phys. Chem. B 103 (48): 10670–10678. https://doi.org/10.1021/jp992264h.
Kruk, M., Jaroniec, M., and Gadkaree, K. P. 1997a. Nitrogen Adsorption Studies of Novel Synthetic Active Carbons. J. Colloid Interf. Sci. 192 (1): 250–256. https://doi.org/10.1006/jcis.1997.5009.
Kruk, M., Jaroniec, M., and Sayari, A. 1997b. Application of Large Pore MCM-41 Molecular Sieves To Improve Pore Size Analysis Using Nitrogen Adsorption Measurements. Langmuir 13 (23): 6267–6273. https://doi.org/10.1021/la970776m.
Kuila, U. and Prasad, M. 2013a. Application of Nitrogen Gas-Adsorption Technique for Characterization of Pore Structure of Mudrocks. Leading Edge 32 (12): 1478–1485. https://doi.org/10.1190/tle32121478.1.
Kuila, U. and Prasad, M. 2013b. Specific Surface Area and Pore-Size Distribution in Clays and Shales. Geophys. Prospect. 62 (1): 341–362. https://doi.org/10.1111/1365-2478.12028.
Labani, M. M., Rezaee, R., Saeedi, A. et al. 2013. Evaluation of Pore Size Spectrum of Gas Shale Reservoirs Using Low Pressure Nitrogen Adsorption, Gas Expansion and Mercury Porosimetry: A Case Study from the Perth and Canning Basins, Western Australia. J. Pet. Sci. Eng. 112 (December): 7–16. https://doi.org/10.1016/j.petrol.2013.11.022.
Lee, C. -K. and Tsay, C. -S. 1998. Pore Connectivity of Alumina and Aluminium Borate From Nitrogen Isotherms. J. Chem. Soc. Faraday Trans. 94 (4): 573–577. https://doi.org/10.1039/A706581G.
Lin, B., Chen, M., Jin, Y. et al. 2015. Modeling Pore Size Distribution of Southern Sichuan Shale Gas Reservoirs. J. Nat. Gas. Sci. Eng. 26 (September): 883–894. https://doi.org/10.1016/j.jngse.2015.07.032.
Liu, H. and Seaton, N. A. 1994. Determination of the Connectivity of Porous Solids From Nitrogen Sorption Measurements—III. Solids Containing Large Mesopores. Chem. Eng. Sci. 49 (11): 1869–1878. https://doi.org/10.1016/0009-2509(94)80071-5.
Liu, H., Zhang, L., and Seaton, N. A. 1992. Determination of the Connectivity of Porous Solids from Nitrogen Sorption Measurements—II. Generalisation. Chem. Eng. Sci. 47 (17–18): 4393–4404. https://doi.org/10.1016/0009-2509(92)85117-T.
Liu, H., Zhang, L., and Seaton, N. A. 1994. Characterisation of Mesoporous Solids Using Sorption Hysteresis Measurements. Stud. Surf. Sci. Catal. 87: 129–139. https://doi.org/10.1016/S0167-2991(08)63072-4.
Liu, J. and Regenauer-Lieb, K. 2011. Application of Percolation Theory to Microtomography of Structured Media: Percolation Threshold, Critical Exponents, and Upscaling. Phys. Rev. E 83 (1): 016106.
Mahamud, M. M. and Novo, M. F. 2008. The Use of Fractal Analysis in the Textural Characterization of Coals. Fuel 87 (2): 222–231. https://doi.org/10.1016/j.fuel.2007.04.020.
Mavko, G. and Nur, A. 1997. The Effect of a Percolation Threshold in the Kozeny-Carman Relation. Geophysics 62 (5): 1480–1482. https://doi.org/10.1190/1.1444251.
Milovac, J. 2009. Rock Physics Modeling of an Unconsolidated Sand Reservoir. MS Thesis, University of Houston, Houston (December 2009).
Ojha, S. P., Misra, S., Tinni, A. O. et al. 2016. Estimation of Saturation-Dependent Relative Permeability in Shales based on Adsorption-Desorption Isotherm. Oral presentation given at the AAPG 2016 Eastern Section Meeting, 25–27 September.
Ojha, S. P., Misra, S., Sinha, A. et al. 2017a. Estimation of Pore Network Characteristics and Saturation-Dependent Relative Permeability in Organic-Rich Shale Samples Obtained From Bakken, Wolfcamp, and Woodford Shale Formations. Presented at the SPWLA 58th Annual Logging Symposium, Oklahoma City, Oklahoma, 17–21 June. SPWLA-2017-F.
Ojha, S. P., Misra, S., Tinni, A. et al. 2017b. Alterations in Pore Topology of Organic-Rich Shale Samples Due to the Removal of Dead Oil, Bitumen, and Kerogen. Presented at the SPWLA 58th Annual Logging Symposium, Oklahoma City, Oklahoma, 17–21 June. SPWLA-2017-WWW.
Ojha, S. P., Misra, S., Tinni, A. et al. 2017c. Relative Permeability Estimates for Wolfcamp and Eagle Ford Shale Samples from Oil, Gas and Condensate Windows Using Adsorption-Desorption Measurements. Fuel 208 (15 November): 52–64. https://doi.org/10.1016/j.fuel.2017.07.003.
Oren, P. E. and Bakke, S. 2002. Process Based Reconstruction of Sandstones and Prediction of Transport Properties. Transport Porous Med. 46 (2–3): 311–343. https://doi.org/10.1023/A:1015031122338.
Perfect, E. 2005. Modeling the Primary Drainage Curve of Prefractal Porous Media. Vadose Zone J. 4 (4): 959–966. https://doi.org/10.2136/vzj2005.0012.
Perrier, E., Bird, N., and Rieu, M. 1999. Generalizing the Fractal Model of Soil Structure: The Pore–Solid Fractal Approach. Geoderma 88 (3): 137–164. https://doi.org/10.1016/S0016-7061(98)00102-5.
Rigby, S. P. and Fletcher, R. S. 2004. Interfacing Mercury Porosimetry with Nitrogen Sorption. Part. Part. Syst. Char. 21 (2): 138–148. https://doi.org/10.1002/ppsc.200400925.
Ross, D. J. K. and Bustin, R. M. 2009. The Importance of Shale Composition and Pore Structure Upon Gas Storage Potential of Shale Gas Reservoirs. Mar. Petrol. Geol. 26 (6): 916–927. https://doi.org/10.1016/j.marpetgeo.2008.06.004.
Roth, M. 2011. North American Shale Gas Reservoirs: Similar, Yet So Different. Oral presentation given at the AAPG International Conference and Exhibition, Calgary, 12–15 September.
Sahimi, M. 1993a. Fractal and Superdiffusive Transport and Hydrodynamic Dispersion in Heterogeneous Porous Media. Transport Porous Med. 13 (1): 3–40. https://doi.org/10.1007/BF00613269.
Sahimi, M. 1993b. Flow Phenomena in Rocks: From Continuum Models to Fractals, Percolation, Cellular Automata, and Simulated Annealing. Rev. Mod. Phys. 65 (4): 1393–1534. https://doi.org/10.1103/RevModPhys.65.1393.
Seaton, N. A. 1991. Determination of the Connectivity of Porous Solids from Nitrogen Sorption Measurements. Chem. Eng. Sci. 46 (8): 1895–1909. https://doi.org/10.1016/0009-2509(91)80151-N.
Shanley, K. W., Cluff, R. M., and Robinson, J. W. 2004. Factors Controlling Prolific Gas Production from Low-Permeability Sandstone Reservoirs: Implications for Resource Assessment, Prospect Development, and Risk Analysis. AAPG Bull. 88 (8): 1083–1121.
Stauffer, D. and Aharony, A. 1994. Introduction to Percolation Theory. Boca Raton, Florida: CRC Press.
Vassilev, S. V. and Tascón, J. M. 2003. Methods for Characterization of Inorganic and Mineral Matter in Coal: A Critical Overview. Energy Fuels 17 (2): 271–281. https://doi.org/10.1021/ef020113z.
Yang, F., Ning, Z., and Liu, H. 2014. Fractal Characteristics of Shales from a Shale Gas Reservoir in the Sichuan Basin, China. Fuel 115 (January): 378–384. https://doi.org/10.1016/j.fuel.2013.07.040.
Yang, Y., Yao, J., Wang, C. et al. 2015. New Pore Space Characterization Method of Shale Matrix Formation by Considering Organic and Inorganic Pores. J. Nat. Gas Sci. Eng. 27 (November): 496–503. https://doi.org/10.1016/j.jngse.2015.08.017.
Yao, Y., Liu, D., Tang, D. et al. 2009. Fractal Characterization of Seepage-Pores of Coals from China: An Investigation on Permeability of Coals. Comput. Geosci. 35 (6): 1159–1166. https://doi.org/10.1016/j.cageo.2008.09.005.