Permian Wolfcamp Interesting Log Interpretation Problem* George B. Asquith 1 Search and Discovery Article #41896 (2016)** Posted September 26, 2016 *Adopted from oral presentation given at AAPG Southwest Section meeting in Abilene, Texas, April 9-12, 2016 **Datapages 2016 Serial rights given by author. For all other rights contact author directly. 1 Texas Tech University, Lubbock, Texas (asquith.george@att.net) Abstract In the log analysis of a Permian Wolfcamp well the Wolfcamp was subdivided into two zone labeled Wolfcamp 1 and Wolfcamp 2. Using GEOCHEM [ECS] data the total porosity [PHItotal] was calculated from the bulk density log using variable matrix analysis. Effective porosity [PHIe] was then determined [PHIe = PHItotal CBW]. The OOIPstb for both the Wolfcamp 1 and Wolfcamp 2 are listed below: Wolfcamp 1 OOIPstb 12.7mmbo Wolfcamp 2 OOIPstb 5.1mmbo The logging suite for this well also included a CMR Log therefore OOIPstb could be calculated at different T2 Relaxation Times. The results are listed below: Wolfcamp 1 [T2 3ms Pore Size 76.5nm] OOIPstb 8.8mmbo Wolfcamp 1 [T2 10ms Pore Size 250nm] OOIPstb 5.3mmbo Wolfcamp 2 [T2 3ms Pore Size 76.5nm] OOIPstb 5.5mmbo
Wolfcamp 2 [T2 10ms Pore Size 250nm] OOIPstb 2.0mmbo Note, in the above OOIPstb values Wolfcamp 1 has much greater OOIPstb values than Wolfcamp 2. An examination of the lithologies indicate that Wolfcamp 2 is more clay rich, and has a higher minimum closure stress [SHmin] and lower Brittleness Coefficient compared to Wolfcamp 1. Therefore the better reservoir with more hydrocarbons is Wolfcamp 1. However, because the well was logged with a High Resolution Array Laterolog [HRLA] the author examined the log for invasion profiles [HRLA5>HRLA2>Rxo], which indicate zones of moveable hydrocarbons due to invasion. The better invasion profiles were located in Wolfcamp 2, not Wolfcamp 1 as I would have expected. Next OOIPstb was calculated based on the degree of invasion (Tixier, 1956 and Asquith, 2015). Y = (Rmf/Rxo) 0.5 (Rw/Rt) 0.5 OOIPstb = (7758 Y h A)/BOI The results are listed below: Wolfcamp 1 [Y Method : Tixier, 1956] OOIPstb 1.5mmbo Wolfcamp 2 [Y Method : Tixier, 1956] OOIPstb 3.8mmbo Unlike the other OOIPstb values the OOIPstb determined from the Y Method are just the reverse, indicating the Wolfcamp 2 is the better reservoir [i.e. greater invasion]. The author has used the Y Method for years in many reservoirs including the Wolfcamp, and found it to be reliable [Asquith, 2015: WTGS Fall Symposium]. So the question is what is causing the Y Method to indicate that the better reservoir is Wolfcamp 2, when the other calculated OOIPstb values and Geomechanical properties indicated Wolfcamp 1 has the better reservoir potential? Selected References Asquith, G.B., 2015, VOOIP Utilizing GEOCHEM [ECS] Data, Triple Combo Data Only, and Pyrolysis S1 Data, Permian Wolfcamp "A" and "B" Shales, Midland Basin, Texas: Search and Discovery Article #110207 (2015). Website accessed September 2016.
Asquith, G.B., 2014, OOIP Utilizing GEOCHEM [ECS] Data, Triple Combo Data Only, and Pyrolysis S1 Data, Permian Wolfcamp A and B Shales : Search and Discovery Article #41406 (2014). Website September 2016. Brown, A.A., 2015, Are Gas Shales Suitable Analogs for Oil Shale Exploration?: Search and Discovery Article #41624 (2015). Website accessed September 2016. Millican, M.L., L.L. Raymer, and R.P. Alger, 1964, Wellsite Recording of Moveable Oil Plot: Society of Professional Well Log Analysts, 5th Annual Logging Symposium, Transactions, Paper F, p. F1-F11. Rafatian, N., and J. Capsan, 2015, Petrophysical Characterization of the Pore Space in Permian Wolfcamp Rocks: Petrophysics, v. 56/1, p. 45-55. Tixier, M.P., 1956, Fundamentals of Electric Logging: Petroleum Engineering Conference, University of Kansas, 171 p.
PERMIAN WOLFCAMP INTERESTING LOG INTERPRETATION PROBLEM G.B. Asquith, TEXAS TECH UNIVERSITY
KEY FACTORS for ECONOMIC SHALE [from: Rick Lewis (2013)] RESERVOIR QUALITY Hydrocarbons in Place Matrix Permeability Pore Pressure COMPLETION QUALITY Hydraulic Fracture Surface Area Hydraulic Fracture Conductivity Hydraulic Fracture Containment
200ft Gamma Ray [SGR & CGR] and Resistivity [HRLA] Permian Wolfcamp 0 50 100 150 200 250 300 0 100 200 300 1 10 100 1000 10500 10500 10,600 Upper Wolfcamp Wolfcamp 10700 1 10700 10800 10,800 10800 Rxo 10900 10900 11,00 HRLA2 HRLA5 11100 11100 11200 CGR SGR 11,200 11200 Middle Wolfcamp Wolfcamp 11300 2 11300 11400 11,400 11400 11500 11500 11600 11,600 11600
200ft Gamma Ray [SGR & CGR] and Neutron-Lithodensity Permian Wolfcamp 0 50 100 150 200 250 300 0 100 200 300-10 40 30 0 20 10 10 20 30 0-10 40 0 Pe 10 10500 10500 10,600 Upper Wolfcamp Wolfcamp 10700 1 10700 10800 10900 10,800 10800 10900 Nls Dls Pe 11,000 11100 11100 11200 CGR SGR 11,200 11200 Middle Wolfcamp Wolfcamp 11300 2 11300 11400 11,400 11400 11500 11500 11600 11,600 11600
200ft Lithology [ECS] & Saturations Permian Wolfcamp 00 0.2 0.2 0.4 0.6 0.8 1.0 1 1 200 399 598 797 996 1195 1394 1593 1792 1991 2190 Wolfcamp 1 OOIPstb/160ac. Total 12.7mmbo Wolfcamp 2 OOIPstb/160ac. Total 5.1mbo Vcl Vcal Vqtz Vpyr Vke om mm CBW Wtr
Permeability Cut Off Unconventional OIL Reservoirs Higher absolute permeability than in gas shales (~1 microdarcy minimum and preferably much higher). NanoDarcy-scale mudstone permeabilities are too low for economic oil production rates. (Brown, 2015: SW AAPG).
1mD 200ft OOIPstb [T2 3ms T210ms & KSDR Permeability] Permian Wolfcamp 0 10000 20000 30000 0 10000 20000 30000 0 0.1 10 1 10 100 1000 1 OOIPstb/160ac. 0.1 1.0 10 100 1000 KSDR Perm [md] T2 3ms 76.5nm T2 10ms 250nm 200 399 Wolfcamp 1 598 10800 T2 3ms 8.8mmbo 797 996 10800 T2 10ms 5.3mmbo 1195 1394 11200 1593 11200 Wolfcamp 2 1792 11400 T2 3ms 5.5mmbo 1991 11400 T2 10ms 2.0mmbo 2190 11600 ` 11600
1mD 200ft OOIPstb [T2 100ms] & KSDR Permeability [md] Permian Wolfcamp 0 5000 10000 150000 0.1 10 1 10 100 1000 1 1.0 0 5000 10000 15000 0.1 10 100 1000 OOIPstb/160ac. KSDR Perm [md] 200 399 Wolfcamp 1 598 10800 T2 100ms 2,500nm 797 10800 T2 100ms 0.8mmbo 996 1195 1394 11200 1593 11200 Wolfcamp 1 1792 11400 T2 100ms 0.3mmbo 1991 11400 2190 11600 11600
Pyrolysis S1 TOClab versus Pyrolysis S1 [mghc/g] Permian Wolfcamp Midland Basin 10.00 9.00 OOIP = S[21.89*S1*0.5 *160] 8.00 7.00 6.00 5.00 4.00 3.00 2.00 S1 = 1.2013*TOC R^2 = 0.83 N = 140 1.00 0.00 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 TOC(wt%)
1mD 200ft OOIP [Pyrolysis S1] & KSDR Permeability [md] Permian Wolfcamp 0.1 1 10 100 1000 0 10 0.1 1 0 5000 10000 15000 20000 1.0 10 100 1000 OOIP/160ac. KSDR Perm [md] 200 399 Wolfcamp 1 598 797 10800 996 S1 Pyrolysis 9.1mmbo 1195 1394 1593 11200 Wolfcamp 2 1792 S1 Pyrolysis 3.9mmbo 1991 11400 2190 11600
bitumen 0.07 0.06 0.05 0.04 0.03 Ro versus Non-Producible Bitumen [ bitumen] 6 bitumen = 0.0118*Ro^-2.4725 PERMIAN WOLFCAMP [Ro = 0.84 bitumen = 0.018] Wolfcamp 1 [ECS DATA] 5.4mmbo Wolfcamp 2 [ECS DATA] 1.1mmbo OOIPstb = S[7758*( oil- bitumen)*0.5 *160ac.]/BOI 0.02 Asquith, 2014 0.01 0 KSDR in md Data From: Lewis, 2013 & Rylander, 2014 AAPG BWLA School 10 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 Immature OIL Wet Gas + Oil %Ro Wet Gas + Condensate 6 Dry Gas
200ft 1mD OOIPstb [Bitumen Corrected] & KSDR Permeability Permian Wolfcamp 0 10000 20000 30000 40000 500000 0.1 10 1.0 1 10 100 1000 1000 1 OOIPstb/160ac. KSDR Perm [md] 200 399 Wolfcamp 1 598 10800 797 10800 996 5.4mmbo 1195 1394 11200 1593 11200 Wolfcamp 2 1792 11400 1.1mmbo 1991 11400 2190 11600 11600
200ft 1 200 Walls & others 2012 Pe<3 & RHOb<2.5 0 10 1 200 0 Lewis, 2010 Pe<4 & RHOb<2.53 10 1 10 100 1000 10000 1 10 100 1000 10000 KSDR/PHI3ms 399 399 598 598 Wolfcamp 1 797 797 10800 996 1195 996 1195 Avg. KSDR/PHI 357 1394 1394 1593 1593 11200 1792 1792 Wolfcamp 2 1991 1991 11400 Avg. KSDR/PHI 188 2190 2190 11600 KSDR in md
200ft 1 Walls & others 2012 Pe<3 & RHOb<2.5 0 10 1 0 Lewis, 2010 Pe<4 & RHOb<2.53 10 PERMIAN WOLFCAMP FLOW UNITS [KSDR/PHI3ms] 0 400 800 1200 1600 0 400 800 1200 1600 200 200 Average KSDR/PHI3ms 399 399 598 598 Wolfcamp 1 797 797 10800 996 996 1195 1195 1394 1394 1593 1593 11200 1792 1792 Wolfcamp 2 1991 1991 11400 2190 2190 11600 KSDR in md
200ft Lithology [ECS] & Geomechanics Permian Wolfcamp 0 0.2 0.2 0.4 0.6 0.8 1.0 1 2000 4000 6000 8000 10000 0 2,000 10 4,000 6,000 8,000 10,000 1 1 psi 200 200 10500 399 399 598 Wolfcamp 1 598 10700 797 996 1195 1394 T2 3ms 8.8mmbo T2 10ms 5.3mmbo 797 996 1195 1394 10800 10900 11100 Avg. Ksdr/PHI 357 Brittleness Coefficient 1593 1792 Wolfcamp 2 1593 1792 11200 11300 shmin Psi 1991 2190 T2 3ms 5.5mmbo T2 10ms 2.0mmbo 1991 2190 11400 11500 Avg. Ksdr/PHI 188 11600 4.0 6.0 8.0
CONCLUSION LATERAL LANDING POINT WOLFCAMP 1 HIGHER OOIPstb BETTER GEOMECHANICS HIGHER KSDR PERM
TO BE SURE LET S TRY ONE MORE METHOD of DETEMINING OOIPstb USING RESISTIVITY INVASION PROFILES
VERY IMPORTANT QUOTE Concerning Moveable Hydrocarbons effective log interpretation requires more than evaluating oil saturation, it requires identification of moveable oil. FROM: Millican,M.L.,L.L. Raymer, and R.P. Alger,1964, Wellsite Recording of Moveable Oil Plot: Soc. of Professional Well Log Analysts, 5 th Annual Logging Symposium, paper F.
MAXIMUM PRODUCIBLE OIL INDEX (Y) (Tixier, M.P.,1956, Fundamentals of Electric Logging: Petroleum Engineering Conference, University of Kansas, 171p.) Y = [(Rmf/Rxo)^0.5 (Rw/Rt)^0.5] Y = Maximum Producible Oil Index at Reservoir Conditions (i.e. the amount of oil per unit volume which is displaced by mud filtrate) Mobile OOIPstb = {7758* *[(1-Sw)-RHS]*h*A}/BOI Mobile OOIPstb = (7758*Y*h*A)/BOI Where: OOIPstb = original oil in place in stock tank barrels (stb) 7758 = barrels of oil in an acre-foot = porosity Sw = water saturation [Soil = 1-Sw] RHS = residual hydrocarbon saturation A = area h = thickness BOI = shrinkage factor (reservoir barrels to surface barrels of oil)
100ft. Gamma Ray [SGR & CGR] and Resistivity [HRLA] Permian Wolfcamp 0 50 100 150 200 1 10 100 1000 0 10 10100 0 50 100 150 200 1 10100 1.0 10 100 1000 GR (APIU) 10200 Wolfcamp #1 200 10200 10300 399 10300 598 10500 797 10500 996 Wolfcamp #2 Rxo 10700 1195 10700 HRLA2 10800 CGR SGR 1394 10800 HRLA5 10900 1593 10900 Asquith, 2015 WTGS Fall Symposium 1792
100ft. Gamma Ray [SGR & CGR] Neutron-Lithodensity Log Permain Wolfcamp 0 50 100 150 200 0 10 10100 10100 1 0 5 10 15 20 25 30 35 40 0 50 100 150 200 30 20 10 0-10 GR (APIU) 10200 Wolfcamp #1 200 10200 10300 399 10300 598 10500 797 10500 996 Wolfcamp #2 10700 10800 CGR SGR 1195 1394 10700 Pe 10800 Nls Dls 10900 1593 10900 Asquith, 2015 WTGS Fall Symposium 0 1792 Pe 10
100ft. Lithology [ECS], Porosity and Saturation Permian Wolfcamp 0.0 1 0 0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1.0 200 399 598 797 996 1195 1394 Wolfcamp #1 Total OOIPstb/160ac. 11.8mmbo Wolfcamp #2 ` Vcl Vcal Vqtz Vpyr Vke om mm CBW WTR 1593 Asquith, 2015 WTGS Fall Symposium
100ft. Gamma Ray [SGR & CGR] and Resistivity [HRLA] Permian Wolfcamp 0 50 100 150 200 0 10 10100 0 50 100 150 200 10100 1 1.0 GR (APIU) 1 10 100 1000 1.0 10 100 1000 10200 Wolfcamp #1 200 10200 10300 399 10300 ` 598 10500 797 10500 HRLA5 HRLA2 996 Rxo Wolfcamp #2 10700 10800 CGR SGR 1195 1394 10700 10800 NOTE: Resistivity Curves Only Plotted If: HRLA5 > 1.2*HRLA2 & HRLA2 > Rxo 10900 1593 10900 Asquith, 2015 WTGS Fall Symposium 1792
100ft. 10100 Mobile OOIP/160ac. from [MPOI] Permian Wolfcamp 0 50 100 150 200 10100 0 5000 10000 15000 20000 0 50 100 150 200 0 5000 10000 15000 2000 GR (APIU) OOIP/160ac. @ 0.5 Intervals 10200 Wolfcamp #1 10200 10300 10300 ` 10500 10500 Wolfcamp #2 10700 10700 MAXIMUM PRODUCIBLE OIL INDEX [Tixier,1956] 10800 CGR SGR 10800 Y = (Rmf/Rxo)^0.5 (Rw/Rt)^0.5 Mobile OOIPstb = [7758 * Y * 0.5 * 160]/1.4 10900 10900 Mobile OOIPstb = 2.2mmbo Asquith, 2015 WTGS Fall Symposium
Petrophysical Characterization of the Pore Space in Permian Wolfcamp Rocks [Rafatian and Capsan, 2015] PETROPHYSICS VOL. 56, No. 1, p. 45-55. the largest pore spaces and, by proxy, the largest continuous connected pore throats, have the largest impact on fluid flow and therefore the largest impact on the degree of invasion. [Asquith, 2015 WTGS FALL SYMPOSIUM]
200ft Gamma Ray [SGR & CGR] and Resistivity Invasion Profiles Permian Wolfcamp 0 50 100 150 200 250 300 0 100 200 300 1 10 10 100 1000 10500 10500 10,600 Upper Wolfcamp Wolfcamp 10700 1 10800 10900 10700 10,800 10800 10900 Rxo HRLA2 HRLA5 11,000 11100 11100 11200 11,200 11200 Middle Wolfcamp Wolfcamp 11300 2 11400 11500 11300 11,400 11400 11500 Only Plotted if: HRLA5>1.3*HRLA2 & HRLA2>1.2*Rxo 11600 11,600 11600
MAXIMUM PRODUCIBLE OIL INDEX (Y) (Tixier, 1956) Y = [(Rmf/Rxo)^0.5 (Rw/HRLT)^0.5] Y= Maximum Producible Oil Index at Reservoir Conditions (i.e. the amount of oil per unit volume which is displaced by mud filtrate) ------------------------------------------------------------------------------------------- Permian Wolfcamp Rmf = 0.021 Rw = 0.05 Area = 160ac. (assumed) BOI = 1.4 (assumed) Mobile OOIPstb = S[(7758 * Y * 0.5 * 160)/1.4] 5.3MMBO [Mobile OOIPstb]
1mD 200ft Mobile OOIPstb [Y] & KSDR Permeability [md] Permian Wolfcamp 0 5000 10000 15000 20000 0.1 1.0 10 100 1000 OOIPstb/160ac. 0 0.1 10 1 10 100 1000 1 KSDR Perm [md] 200 399 Wolfcamp 1 598 797 10800 [Y] Method 1.5mmbo 996 1195 1394 1593 11200 Wolfcamp 2 1792 [Y] Method 3.8mmbo 1991 2190 11400 11600
QUESTION? Why does the Wolfcamp 2 have such good invasion profiles indicating permeable reservoir with high OOIPstb values, and yet all other methods indicate lower OOIPstb values compared to Wolfcamp 1? In addition, why do the Brittleness Coefficient and SHmin indicate poorer GEOMECHANICAL values in Wolfcamp 2, compared to Wolfcamp 1, when the invasion profiles indicate Wolfcamp 2 is the better reservoir?.