Bob Cluff The Discovery Group, Denver, Colorado Mike Miller Cimarex, Tulsa, Oklahoma April 2010 DWLS luncheon

Transcription

1 Bob Cluff The Discovery Group, Denver, Colorado Mike Miller Cimarex, Tulsa, Oklahoma April 2010 DWLS luncheon

2 The early years shale evaluation from GR and density logs Trying to get quantitative deltalogr and other methods to estimate TOC from logs The porosity problem if TOC looks like porosity on density logs, how can you tell them apart? Geochemical logs finally find their market Modern multi-mineral solutions reverse engineering the Shale Gas logs Where are going next?

3 There was the gamma ray log, And it was good Recognition that black shales are radioactive is not rocket science, we saw it in the 40 s Early uses were just to separate hot shale from the background and map net thickness Black shale vs. Gray shale in Appalachian basin terms

4 Beers, 1945, AAPG Bull 29

5 Potter, Maynard & Pryor, 1980, fig 1.25

6 Mound Facility, 1980

7 Woodford Shale, Arkoma basin

8 Uranium in sea water drops out in reducing environments Uranium forms organometallic complexes with organic matter at or just below the sediment-water interface Requires very low oxygen in seawater (anoxia) Slow process, residence time dependent Anaerobic bacteria are involved in reduction of U(VI) to U(IV) Tetraethyl lead is a common example of an organometallic complex

9 Linear dependence of GR on TOC y = mx + b TOC = m GR + b m = slope of GR (API) vs TOC (wt %) b = GR intercept at 0% TOC (gray shale baseline) requires normalized GR logs relationship varies between basins no single set of coefficients work need local calibration to core data only approximate- the amount of uranium associated with TOC varies even within a formation Schmoker, 1981, AAPG

10 New Albany Shale, Illinois basin EGSP cores ( ), all Big Blue logs y = x R 2 = TOC % Gamma ray (API)

11 In the 1970 s, when bulk density logs first became common, it became apparent hot black shales also had low density Cross-plots of TOC vs. density quickly showed the story.. Kerogen is light, like coal, so it looks like porosity on a density log Very, very common to pick a density porosity cutoff as net pay in gas shale plays Schmoker, 1979, AAPG 63 (9)

12 New Albany Shale, Illinois Basin

13 New Albany Shale, Illinois basin EGSP cores ( ), all Blue logs ! slope varies if you plot TOC as v/v or as weight % total organic carbon (wt %) y = x R 2 = Bulk density (g/cm3)

14 Passey et al, 1990, AAPG Bull 74 (12) The deltalogr method was proposed as an improvement over simple GR and RhoB estimators for TOC Relied on two key observations: t (and also ρb) vary with kerogen content Resistivity increases with increasing maturity Logarithmic separation between t and Rdeep, appropriately scaled, can be related to TOC It s just an old-fashioned sonic F-overlay!!!

15 Passey et al, 1990, AAPG 74 (12)

16 Passey et al, 1990, AAPG 74 (12)

17 logr = log 10 (R/R baseline ) ( t- t baseline ) t - resisitivity separation means likely source interval logr separation is linearly related to TOC if maturity is known or can be estimated where: Rbaseline is the gray shale baseline resistivity tbaseline is the gray shale baseline t important: at any given logr, TOC decreases as LOM increases

18 TOC (wt %) = logr * 10^( *LOM) Passey et al, 1990, AAPG 74 (12)

19 Many people have noted, including Passey, that logr has trouble at high maturities TOC relationship was calibrated for LOM of 6-9 and low logr, everything else was extrapolated LOM scale is only loosely related to common lab values, including Tmax and Ro. Resistivity does not continually increase through the gas window, in fact it starts to fall back above Ro of ~1.1% We ve seen conductive shales at very, very high Ro s

20 Ro ~ Ro ~ > 4.5 Low RhoB, density-neutron converge, high Rt (100 s of ohmm) XRD mineralogy ~ equivalent between wells high RhoB, density-neutron separate, very very low Rt (< 1 ohmm) Mike Miller, BP, DWLS 2010 Spring Workshop

21 Data provided by Brian Cardott, Okla. Geol. Survey

22 5 th order polynomial fit LOM after Hood et al, 1975, AAPG 59 (6) 62 Vitrinite reflectance (%)

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24 If kerogen has a density of ~1.15 g/c3 and water is ~1.0, and both contain hydrogen, how the heck do you separate them? Two separate, related issues: Kerogen density is clearly low, but difficult to measure exactly Neutron porosity of kerogen is unknown So we just reverse the problem Solve for matrix values that work best to match both core measured TOC and core porosity

25 kerogen line Type II kerogen? Salt Water bad hole porosity line Dry shale point (50% qtz, 50% ill)

26 Sg Mike Miller, BP, DWLS 2010 Spring Workshop

27 Both GR and density correlations implicitly assume porosity is constant within the error of the measurements Slope-intercept of the regression compensates for the average porosity Scatter around the trend is presumably a measure of porosity that varies independently from TOC

28 18 16 Example: at any fixed TOC, RhoB Varies by +/- 0.1 g/c3 around the mean. At RhoMa = 2.72, this is +/- 6% porosity 14 total organic carbon (%) Bulk density (g/cc) RhoMa ~ 2.72

29 The old standard answer somebody will sell you another measurement. Pe doesn t cut it, not a matrix/lithology problem also heavy barite muds render it useless in several plays (e.g. Haynesville Sh) Spectral GR doesn t reduce uncertainty much, if any Nice to know the clay breakdown, but not essential Finally.geochemical spectroscopy logs find their purpose in life!

30 ECS tool uses AmBe chemical source, detects Si, Ca, Fe, S, Mg, and pseudo-al (+ Ti, Gd; not used) SpectroLith processing is a DETERMINISTIC set of equations, based on a large sample database, that solves for the common minerals: Fe, S pyrite excess Fe (after making pyrite) siderite Ca total carbonate (calcite + dolomite) Si, Ca, Mg, pseudo-al clay Left over quartz, feldspar + mica undifferentiated

31 Another regression equation is used to solve for grain density (RHGE) NOT a linear combination of mineral volumes and densities ECS does NOT see kerogen SpectroLith grain density is assumed to be a kerogen-free value: RHGE RHOM Vkerogen SpectroLith outputs ELAN combine with density, neutron, Pe, NGS, etc. STOCHASTICALLY solve for lithology, porosity, Sw, Vkerogen

32 R. Lewis, Schlumberger

33 Raw logs RhoMa ECS ELAN Porosity, Sw, TOC, & GIP

34 First issue is adsorbed gas content Complex function of TOC, pressure, temperature, maturity, and kerogen type Model calibrated to core isotherms Generally isotherms are run at reservoir temperature for the cored well, and T is ignored thereafter Isotherms set of Langmuir equations Langmuir volumes a linear function of TOC That plus pressures adsorbed gas content

35 GRI 91/ Gab = VL * P / (P + PL) TOC % Gas content (scf/ton) Pressure (psi)

36 Langmuir volume (scf/ton) y = x R² = Total organic carbon (%)

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38 Just like a tight sandstone or siltstone Need to determine porosity and saturation from a log model or core data GIP (scf) = ft 2 /ac * A h φ Sg / Bg where A is the area in acres h is the net thickness, in feet φ is porosity available for gas storage, v/v Sg is the gas saturation, v/v Bg is the gas formation volume factor, rcf/scf gas filled porosity

39 R. Lewis, Schlumberger

40 Multimineral, stochastic solutions seem to work better than deterministic 2, 3 or 4 mineral models Challenge is to incorporate ECS-type data directly in the models, bypassing the current regression based approaches Geomechanical modeling Vp-Vs data from cores suggest most properties can be predicted from DTC logs alone Better analysis of limited and older log suites Horizontal well evaluation with minimal data

41 Illinois Geological Survey for getting me started on black shales in the 70 s Chevron USA for supporting our work on Barnett Shale and others in the early 90 s BP North America Gas for recent log examples and ongoing support Todd Stephenson, BP Reserves & Renewal