Making Best Use of Routine Core Analysis Data

Transcription

1 Making Best Use of Routine Core Analysis Data Craig Lindsay Senior SCAL Engineer Helix RDS Limited 28 th. March 2007

2 Making Best Use of Routine Core Analysis Data Aim to demonstrate how basic core data can be put to effective use Core material Routine core analysis (RCA) data types Example applications of RCA data - Quantifying Permeability Heterogeneity - Sampling for Special Core Analysis (SCAL) Studies Conclusions

3 Core Core Plug Core Slab Resinated Core Whole Core 3.8 cm 10 cm 10 cm

4 Routine Core Analysis Samples RCA Tests sidewall (< 2.54 cm.) core plugs ( cm.) Kv horizontal and vertical full diameter ( cm. (L), cm. (D) ) whole core (up to 60 cm. (L), cm.(d)) Kh Screen

5 Routine Core Analysis Data

6 Applying routine core analysis data Many possible applications of RCA data Examine two example applications of RCA data to obtain best VOI - Quantifying Permeability Heterogeneity - Sampling for Special Core Analysis (SCAL) Studies Issues of upscaling and application in reservoir models beyond the scope of the presentation

7 Measuring Core Permeability - Summary Plug permeameter P1 Confining Pressure P2 Pa In Regulator Plug Coreholder Regulator Qa Manometer Core Plug Gas in: Qi, Pi L Atmospheric Pressure, Pa Probe permeameter A P i P a Q a Tip Seal Rock Surface Gas flow lines k a 2000Qa a Pa 2 2 P Pi a L A k a 2000Qi i P i F 2 2 P. a P i

8 Permeability Data Presentation Tabular data Depth plots / x-plots most useful Air Permeability, md Helium Porosity, frac.

9 Permeability How well is it Quantified from core? Core plug measurements at 1 per ft may not fully characterise the level of permeability heterogeneity especially in laminated formations How do we know? Hurst and Rosvoll 1 proposed method to determine minimum number of measurements (No) to determine Arithmetic Mean Permeability +-20% Reducing the tolerances unrealistic number of measurements Calculate coefficient of variation, Cv = Standard Deviation / Arithmetic Average No = 100 Cv 2

10 Permeability How well was it Quantified Based upon Cv Corbett and Jensen 2 proposed heterogeneity classes: < 0.5 Homogeneous <1 Heterogeneous - >1 Very heterogeneous Three examples of applying these principles: Rotliegend reservoir SNS 150 plugs acquired (1 per ft.) Cv = 2.5, No = 625 Very heterogeneous Plug alone data did not quantify permeability heterogeneity probe permeability 5 measurements per ft = 729 points.

11 Permeability How well was it Quantified Forties Sandstone (marginal) - NNS 118 plugs acquired (1 per ft.) Cv = 1.6, No = 261 Heterogeneous Plug data did not quantify permeability heterogeneity probe permeability 5 measurements per ft = 590 points. Forties Sandstone (main channel) - NNS 75 plugs acquired (1 per ft.) Cv = 0.9, No = 81 Heterogeneous Plug data did effectively quantify permeability heterogeneity

12 Selecting samples for SCAL - Background Static SCAL capillary pressure (fluid contacts, Sw distribution), Sw model parameters - m, n, Qv, m*, n* (water saturation), porosity compaction, liquid permeability, PV compressibility (primary recovery) Dynamic SCAL wettability, relative permeability, imbibition capillary pressure (secondary recovery) Formation damage studies Geomechanical / specialist studies

13 Selecting samples for SCAL - Caveats Exact sampling protocols depend upon the specific objectives SCAL can be only be performed on a sub-set of samples due to cost and time constraints This example based upon assumption that RCA plugs can be employed where RCA sample preparation has been proven to be nondamaging and fresh state core is not required Correct use of RCA during sample selection essential

14 Selecting samples for SCAL from poro / perm Poro perm x-plot sufficient? No very crude Initially check reservoir zonation Zone X Zone Y Air Permeability, md Air Permeability, md Helium Porosity, frac Helium Porosity, frac.

15 Selecting samples for SCAL FZI and HFU Determine FZI (Amaefule et al 3 ) from RCA poro perm data FZI - a unique parameter that incorporates the geological attributes of texture and mineralogy in the discrimination of distinct reservoir hydraulic or flow units (HFU) RQI k e e z 1 e FZI RQI z HFU - a mappable portion of the total reservoir within which geological and petrophysical properties that affect the flow of fluids are consistent and predictably different from the properties of other reservoir rock volumes

16 Selecting samples for SCAL - HFU 1.0 HFU Frequency HU 1 HU 2 HU 3 HU 4 HU Log FZI HU 5 HU 4 HU 3 HU 2 HU 1 Air Permeability, md Air Permeability, md Helium Porosity, frac Helium Porosity, frac.

17 Selecting reservoir representative samples for SCAL HFU number and FZI range defined but.. Need to determine: - How representative is the cored interval of the reservoir unit (use log / analogue data to determine)? - Are entire / part zones represented? - What proportion of each interval does each HFU represent? Need to consider: - Static SCAL whole range of rock qualities represented - Dynamic (flow) SCAL bias sample selection towards best rock quality

18 Selecting samples for SCAL other issues Other considerations: - Economic how many tests can be performed for the available budget? - Minimum number of data points to define a property, e.g. 4 5 to define cementation exponent (m).? 100 Formation Factor at 3685 psig (-) 10 m= Porosity at 3685 psig (-)

19 Selecting samples for SCAL Loranz diagram Define Storage Hydraulic Units (SHU) and Flow Hydraulic Units (FHU) use of Lorenz diagram (Jensen et al. 4 )- a graphical presentation of the Lorenz coefficient (Lc) Lorenz Plot Fraction of total flow capacity (k*h), fi Transmissivity HU Storativity HU Air Permeability, md Transmissive HU Storage HU Fraction of total storage capacity (phi*h), ci Helium Porosity, fraction

20 Selecting samples for SCAL SHU and FHU Zonal distribution of SHU & FHU Porosity, frac Air Permeability, md THU SHU Depth, ft. TVDSS THU SHU Depth, ft. TVDSS

21 Selecting samples for SCAL - Example The example SCAL programme: - Confined to Static properties (m, n and drainage Pc), therefore all HU to be represented - The cored interval represented 1 entire reservoir zone, 2 part zones - The part represented zones were considered representative of the whole zone - Budgetary constraints on programme costs - Time constraints FF/RI pairs rather than same samples - Minimum number of sample for m, n etc. would be 4 per zone

22 Selecting samples for SCAL - Summary The SCAL programme: - 5 HU, 3 zones - 4 FF / RI pairs per zone - Zonal HU s represented appropriately HU- Met Zone Xbudgetary HU Actual and SCALtimeZone constraint Y HU Actual criteria SCAL Zone Z HU Actual SCAL HU % 25% 1 2% - HU % 75% 53 72% 75% 11 20% 25% HU3 5 23% 25% 5 7% % 25% HU4 1 5% % 25% HU % 25%

23 Conclusions Presented are some examples of how basic RCA data can be employed to derive considerable VOI Tools employed are straightforward documented procedures Important to benefit from use of published and current research Methodologies employed were fit for purpose other techniques available Issues of application and upscaling beyond the scope of this presentation Don t overlook the value of appropriately derived RCA data

24 References 1 Hurst, A. and Rosvoll, K Permeability variations in sandstones and their relationship to sedimentary structures, Reservoir Characterisation II, Academic Press, San Diego, p Corbett, P.W.M., and Jensen, J.L., Estimating the mean permeability: How many measurements do you need? First Break, 10, p Amaefule et al. Enhanced Reservoir Description: Using Core and Log Data to Identify Hydraulic (Flow) Units and Predict Permeability in Uncored Intervals / Wells, SPE 26436, Jensen, J.L., Lake, L.W., Corbett, P.W.M., and Goggin, D.J., 1997, Statistics for Petroleum Engineers and Geoscientists, Prentice-Hall, New Jersey

25 Acknowledgements AFES Thank You for your attention!