TOC LECO or RockEval GR, density, resistivity. Mineralogy XRD, FTIR, XRF Density, neutron, Pe, ECS-type logs

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2 Property of interest Core data Log data Porosity Crushed dry rock He porosimetry Density (mostly) TOC LECO or RockEval GR, density, resistivity Water saturation As-received retort or Dean-Stark Resistivity + kerogen corrected porosity Mineralogy XRD, FTIR, XRF Density, neutron, Pe, ECS-type logs Permeability Pulse decay on crushed rock This is tough Geomechanics Static moduli DTC, DTS, RHOB, & synthetic substitutes Geochemistry Ro, S1-S2-S3, etc. Resistivity (sort of )

3 Global stochastic Global deterministic Local deterministic aka direct calibration to core Each has distinct advantages & disadvantages Each has its staunch defenders & proponents None is clearly the best for all shales Industry has not settled on one approach or best practices

4 Global/stochastic Figure out or guess what components are present in the shale (mineral, organic, fluid) Characterize end member properties of each Invert the logs for properties that best fit the observed log character Implementations include ELAN, Multimin, Statmin, etc.

5 Guess at mineral and fluid volumes Compute log responses from a forward model Compare computed log responses with actual log data Satisfactory match? No Yes DONE

6 Solutions are very Sensitive to the total error bars

7 Actual log curves vs. forward models convergence is the criteria for a satisfactory model.

8 How do you know, or guess at, the end member points? What are the kerogen endpoints (GR, RhoB, Nphi, etc.)? What is the inorganic grain density of the clay components? What are the error functions associated with those end points AND the log data (that is, the total error bar)?

9 Global/deterministic Characterize properties using broad collections of shale samples, either globally or basin/play specific Schmoker 1979, 1981 equations deltalogr (Passey, 1990) Schlumberger SpectroLith is a service company specific method

10 TOC (v/v) = (ρ gray sh ρ b ) / TOC (v/v) = (GR gray sh GR)/(1.378 * A) (1979 eqn) (1981 eqn) TOC (v/v) = W TOC * RHOma/RHO TOC

11 New Albany Shale, Illinois basin EGSP cores ( ), all blue logs total organic carbon (wt %) Published Schmoker relation Bulk density (g/cm3)

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13 Basically a sonic F overlay Two universal eqn s published by Passey et al. (1990, AAPG Bull) logr = log 10 (R/R bl ) ( T- T bl ) This defines deltalogr TOC = logr * 10^( LOM) This relates deltalogr to TOC (wt%) Most of us are concerned about the LOM parameter, but the second two constants were empirically determined

14 Passey et al, 2010, SPE

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

16 Deterministic suite of regression eqn s to compute mineral volumes and kerogen-free grain density RhoM ecs = a + b Si + c (Ca,Na) + d (Fe,Al )+ e S

17 Regional or global equation does not apply locally & you don t know that Variable selected does not really correlate very well with property of interest e.g. gamma ray, because V uranium is not a simple function of TOC Co-linearities e.g. using density to predict both porosity and TOC

18 Local/deterministic Calibrate our log models in restricted areas, down to individual wells or single cores Simple linear & non-linear regressions GR vs. TOC, RHOB vs. TOC Multiple linear regression methods Multiple non-linear regression A common implementation are neural networks

19 ρ = ρ φ(1 S ) + ρφs + ρ (1 φ V ) + ρ V b hc T wt w T wt m T TOC TOC TOC φ T = ρ ρ ( W * ρ / ρ W + 1) m b TOC m TOC TOC ρ ρ + W ρ (1 ρ / ρ ) m fl TOC fl m TOC SPE But, we don t directly measure the inorganic grain density, nor the kerogen density. Have to solve for these two properties by comparing model prediction to core measured TOC s and porosity

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21 New Albany Shale, Illinois basin EGSP cores ( ), all blue logs total organic carbon (wt %) Scatter results from variation in porosity & RhoMa from sample to sample 0% porosity, RhoKer = 1.00, RhoMa inorganic = 2.72 line Bulk density (g/cm3)

22 TOC from GR model

23 Colorado Niobrara example (too few core points!) Not so different than stochastic method, except it minimizes error in POROSITY only

24 logr = log 10 (R/R bl ) ( T- T bl ) TOC = logr * 10^( LOM), for LOM = 9

25 Merge in the core gamma scan Depth shift, honor the physical breaks Don t interpolate Convert core depths to log depth, then import Keep an audit trail! L = C + x

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27 Kill the outliers

28 Marcellus Sh., Vclay vs. XRD clay model

29 Everybody thinks they are right and have the best method.. Of course, we re all selling our services too! Each method has its advantages in certain settings or types of wells Rich suite of modern logs vs. old, public domain log coverage? Vertical vs. horizontal well bores? Do you have core data for calibration?

30 1. Transparency Some methods are basically black boxes & are difficult or impossible to reproduce Others are totally transparent, you can write out a set of equations and you may agree or not, but there they are And if you get more information, they are easy to tweak and re-apply to prior wells

31 2. Transportability Some solutions require proprietary software, or only one vendor can really run it. Others require a very specific logging measurement If you ran the wrong color logging company, or didn t run the right tool: you re done. If logging conditions prevent running a particular service: you re done. If it s not your well and you don t have access to that data: you re done.

32 3. Cheap and easy! This is self-explanatory, everyone likes cheap and easy. Some solutions are powerful and accurate, but may not be cheap (when you consider everything required to implement). Some solutions are difficult. They require a specialist and might be totally nonreproducible even by the same person! Try a double blind test sometime and see what you get back.

33 4. Fit for purpose accuracy Getting water saturation to 3 decimal places is probably not realistic so why do we do it? Sometimes close enough is good enough Log analysis on the hood of a Chevy vs. log inversions on a supercomputer What will impact your business decisions, and how different does an answer have to be to make you do something differently?

34 May your acreage map be yellow, your balance sheet black, And your 2012 outlook rosy! Happy holidays from all of us at The Discovery Group.