Regional petrophysical properties of Mesaverde low-permeability sandstones

Transcription

1 Regional petrophysical properties of Mesaverde low-permeability sandstones Alan P. Byrnes, KGS John C. Webb, Discovery Robert M. Cluff, Discovery US DOE # DE-FC26-05NT42660

2 US DOE Project Summary Solicitation DE-PS26-04NT subtopic area : Understanding Tight Gas Resources Award Date: October, 2005 Completion Date: June 30, 2008 Contract # DE-FC26-05NT42660 Organization: University of Kansas, Kansas Geological Survey Principal Investigator: Alan P. Byrnes, KGS KGS-Discovery Group, Inc. co-participants DOE share $4,030 (80%) Industry share $2,804 (20%)

3 Objectives The project will provide petrophysical tools that address: ) minimum gas flow, critical and residual gas saturation, Sgc=f(lithofacies, Pc, architecture) 2) capillary pressure, Pc=f(P), Pc=f(lithofacies, k, φ, architecture) 3) electrical properties, m* & n* 4) facies and upscaling issues 5) wireline log interpretation algorithms 6) providing a web-accessible database of advanced rock properties.

4 Sampling Powder River 4-5 wells/5 basins Wind River 44 wells Wyoming Describe core Green River 2500 ft N 300 core samples Washakie advanced properties samples Utah Uinta Piceance Colorado

5 Digital Core Description Sampling designed to sample across all lithofacies 5 digit system basic type (Ss, Ls, coal) grain size/sorting/texture consolidation sedimentary structure cement mineralogy Property continuum not mnemonic Provides litholgy log traces and quantitative variables for multivariate analysis

6 Basic Properties Distributions Sampling QA Distribution is sampling dependent but interesting Distribution = f(basin, Lith, M/NM, GRI, etc.) Percent of Population (%) In situ Porosity (%) 6-8 All Green River Piceance Powder River Sand Wash Uintah Wind River Washakie mean median stdev φ All Green River Piceance Powder River Sand Wash Uintah Washakie Wind River Percent of Basin Population Percent of Population (%) E-7 - E All Green River Piceance Powder River Sand Wash Uintah Wind River Washakie E-6 - E E-5 - E Grain Density (g/cc) - Green River Piceance Powder River Uintah Wind River Washakie Sand Wash In situ Klinkenberg Permeability (md) 0-,

7 .5 Pore Volume Compressibility Pore Volume Change Intercept (/psi) y = 0.03x +.08 R 2 = 0.5 Fraction of Porosity at 200 psi Confining Pressure (psi) 3 Samples Log-linear pore volume change characteristic of fractures/sheet-pores Slope and intercept change with porosity β =^[( φ φ-.06)*logP +( φ φ φ+4.238)] Pore Volume Compressibility (^6/psi) 00 0 Routine Helium Porosity (%) Pore Volume Change Slope (-/psi) y = x R 2 = Routine Helium Porosity (%) φ = 24% φ = 2% φ = 8% φ = 5% φ = 2% φ = 8% φ = 6% φ = 4% φ = 2% Net Effective Stress (psi)

8 log In situ Klinkenberg Permeability (md) y = x x x R 2 = log Routine Air Permeability Ppore = 0 psi (md) 00 In situ Klinkenberg Permeability Generalized = f(p pore, Lith) k ik = ^[ (logk air ) (logk air ) logk air +0.46] k ik = ^[.34 (logk air ) - 0.6] (Byrnes, 997) Statistically similar except for k > md Gas Liquid k gas = k liq (+4c /r) = k liq (+b/p) b = 0.85 k ik (atm, Present Study) b = k liq (Jones & Owens) b = k liq (Heid) Klinkenberg b factor (atm) 0 0. E-08 E-07 E-06 E In situ Klinkenberg Permeability (md)

9 Permeability vs Porosity Generalized trend k ik = [0.333φi-5] with X error Different k-φ trends among basins due to lithologic variation Beyond common k with grain size, lithologic influence changes with porosity - nonlinear In situ Klinkenberg Permeability (md) Green River Piceance Powder River Uinta Wind River Washakie Calculated In situ Porosity (%)

10 in situ Klinkenberg Permeability (md) in situ Klinkenberg Permeability (md) Permeability vs Porosity 9XXX 8XXX 7XXX 6XXX 5XXX 4XXX 3XXX 2XXX XXX Calculated In situ Porosity (%) XX9X XX8X XX7X XX6X XX5X XX4X XX3X XX2X XXX XX0X Calculated in situ Porosity (%) logk ik = 0.282φ i + 0.8RC (+4.5X MLRA) logk ik = 0.034φ i φ i RC (+4.X MNLRA) Neural Network +3.3X Predicted in situ Klinkenberg Permeability (md) Measured in situ Klinkenberg Permeability (md) hidden layer: Hidden layer nodes: Mean> hidden layer- Std Dev> to-output Input-to-hidden layer weights weights Node Constant Phii RC2 RC4 Constant

11 Capillary Pressure under Pressure R ft k = 3 md φ = 24.5% Wetting Phase Saturation (%) PA ft k = mD φ = 2.7% Wetting Phase Saturation (%) R ft k = 7.96 md Wetting Phase Saturation (%) φ = 9.2% 3 md 8 md E ft k = md Wetting Phase Saturation (%) φ = 2.2% E ft k = mD Wetting Phase Saturation (%) φ = 9.5% LD43C ft k = 0.90 md Wetting Phase Saturation (%) φ = 2.9% 0.6 md 0.2 md B ft k = mD Wetting Phase Saturation (%) φ = 4.4% 0.04 md 0.02 md B ft k = md φ = 2.6% Wetting Phase Saturation (%) 0.00 md md Threshold Entry Pore Diameter (µm) A Air-Mercury Threshold Entry Pressure (psi) B Threshold Entry Gas Column Height (ft) C 0 0. y =.77x 0.50 R 2 = 0.77 y =.28x 0.50 R 2 = E Klinkenberg Permeability/Porosity (md/%) y = 8.9x R 2 = 0.77 y = 8.94x R 2 = 0.93 E Klinkenberg Permeability/Porosity (md/%) y = 6.48x R 2 = 0.77 y = 6.75x R 2 = 0.93 E-06 E Klinkenberg Permeability/Porosity (md/%)

12 Capillary Pressure Pore Size Distribution (PSD) PSD expressed by Pc slope Pc slope = f(k) Pc slope with P Leverett J Function md md 0.002md 0.007md 0.008md md md md md 0.02md 0.03md 0.032md 0.046md 0.085md 0.25md 0.4md 0.56md 0.84md 2.24md Wetting Phase Saturation (%) Brooks-Corey Capillary Pressure Slope unconfined Leverett J(Sw) = in situ Pc (k/φ) 0.5 /τcosθ Poor fit because Pc slope C = f(k) 0 E In situ Klinkenberg Permeability (md)

13 kik Primary Drainage First Imbibition Secondary Drainage Second Imbibition Tertiary Drainage Third Imbibition E ft φ = 7.4% Wetting Phase Saturation (%) = 28.9 md Primary Drainage Primary Imbibition Second Drainage Second Imbibition Third Drainage Third Imbibition E ft φ = 5.0% =.93 md Wetting Phase Saturation (%) Primary Drainage Primary Imbibition Second Drainage Second Imbibition Third Drainage Third Imbibition B ft (B) φ = 7.6% = md Wetting Phase Saturation (%) Primary Drainage Primary Imbibition Second Drainage Second Imbibition Third Drainage Third Imbibition E ft (A) φ = 9.5% = md Wetting Phase Saturation (%) Primary Drainage Primary Imbibition Second Drainage Second Imbibition Third Drainage Third Imbibition B ft (A) φ = 2.3% Wetting Phase Saturation (%) = 6.74 md Primary Drainage Primary Imbibition Second Drainage Second Imbibition Third Drainage Third Imbibition R ft (B) φ = 9.2% = md Wetting Phase Saturation (%) Primary Drainage Primary Imbibition Second Drainage Second Imbibition Third Drainage Third Imbibition S ft (B) φ = 8.6% = md Wetting Phase Saturation (%) Air-Hg Capillary Pressure (psia ) Primary Drainage Primary Imbibition Second Drainage Second Imbibition Third Drainage Third Imbibition KM ft (B) φ = 5.9% = md Wetting Phase Saturation (%) Residual Nonwetting Phase Saturation (Snwr) Residual Gas Saturation C = /Snwr-/Snwi Snwr = /[C + /Snwi] C = 0.55 (min ε).0 unconfined 0.9 confined Land C=0.66, Swi=0 0.8 Land C =0.54, Swi= Initial Nonwetting Phase Saturation (Snwi)

14 Critical Gas Saturation Experimental work indicates Sgc < % often < 5% but krg curves extrapolate to 35% < Sgc < 0% Issues little krg data at Sw > 65% Does p vary or Sgc vary or both? Gas Relative Permeability Relative Permeability (fraction) Water Saturation g- md w- md g- md w- md g-0. md w -0. md g-0.0 md w -0.0 md g-0.00 md w md Water Saturation (fraction) S gc?

15 Critical Nonwetting Voltmeter V Phase Saturation 36 SS end caps Electrical conductivity and Pc inflection indicate 0% < Sgc < 22% Higher Sgc in complex bedding lithofacies Core Rubber sleeve High pressure oil pump 0.22 Hg Critical Non-wetting Phase Saturation MICP-inflection Electrical Resistance Oil High Pressure Vessel Hg positive displacement pump Vacuum In situ Klinkenberg Permeability (md)

16 ) Percolation Network ( Np) - Macroscopically homogeneous, random distribution of bond sizes, e.g., Simple Cubic Network (z=6) Invasion direction 3) Series network ( N ) - preferential samplespanning orientation of pore sizes or beds of different Np networks perpendicular to the invasion direction. Sgc and Percolation Sgc (L) = A L D E (Wilkinson and Willemsen, 983) L is network dimension A is a numerical constant (for simple cubic network A = 0.65) D is the mass fractal dimension of the percolation cluster (D =.89 for 2-D, D = 2.52 for 3-D) E is the Euclidean dimension (E = 2 for 2-D and E = 3 for 3-D) As L Sgc 0 Sgc = 2.5% for L = Sgc = 2.4% for L = 00 Sgc = 0.8% for L = 000) 00 2) Parallel Network ( NII) preferential orientation of pore sizes or beds of different Np networks parallel to the invasion direction. 4) Discontinuous series network ( N d) - preferential non-sample-spanning orientation of pore sizes or beds of different Np networks perpendicular to the invasion direction. Represents continuum between N and N Experimental results can be explained using four pore network architecture models p. Gas-Water Capillary Pressure (kpa) md 0. md B A Water Saturation

17 Archie Cementation Exponent Empirical: m = φ φ 0.5 Dual porosity: m = log[(φ-φ 2 ) mm + φ 2 m2 ]/logφ 2.4 φ = bulk porosity φ 2 = fracture or touching vug porosity mm = matrix cementation exponent m 2 = fracture or touching vug cementation exponent Archie Cementation Exponent (m, A=) High: m m = 2., φ 2 = Int: m m = 2.0, φ 2 = 0.00 Low: m m =.8, φ 2 = m 2 = Porosity (fraction)

18 Conclusions Grain density for 2200 samples averages g/cc (+sd) with grain density distributions differing slightly among basins. Klinkenberg b(atm) = 0.85 kik-0.34 log k ik = φ i RC2-5.3 (+4.5X, sd) ANN analysis provides prediction within +3.3X Capillary pressure (Pc) exhibits an log-log linear threshold entry pressure (Pte) versus k ik and k ik /φ i trend and variable Brooks-Corey slopes. Snwr with Snwi consistent with the Land-type relation: /Snwr- /Snwi = Critical nonwetting-phase (e.g., gas) saturation is low (Sgc < 0.05) in massive and parallel bedded lithologies but may increase in rocks with more complex bedding Percolation theory provides a tool for predicting limits.. Archie cementation exponent (m) decreases with decreasing porosity (?) below approximately 6% and can be generally described by empirical or by a dual- porosity model These relationships are still being investigated. Mesaverde Project website is

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