Improving Reservoir Characterization of Karst-Modified Reservoirs with 3-D Geometric Seismic Attributes

1. Improving Reservoir Characterization of Karst-Modified Reservoirs with 3-D Geometric Seismic Attributes Susan E. Nissen1, E. Charlotte Sullivan2, Kurt J. Marfurt3, and Timothy R. Carr4 1Consultant, McLouth, KS 2Pacific Northwest National Labs, Richland, WA 3College of Earth and Energy, University of Oklahoma, Norman, OK 4Department of Geology and Geography, West Virginia University, Morgantown, WV

2. Outline • Characteristics of karst-modified reservoirs • Multi-trace geometric seismic attributes • Seismic-based examples of • Collapse structures • Polygonal features • Oriented lineaments • Interpretation workflow for karst-modified reservoirs • Conclusions

3. Karst Modified Reservoirs • Carbonate reservoirs • Rocks modified by dissolution during subaerial exposure • May also have hydrothermal and tectonic overprints

4. Solution-enlarged fractures Residual paleo-highs • Fluid conduits (if open) or barriers (if filled) • May be hydro- carbon traps Loess-filled fractures, Missouri Cockpit karst, Jamaica www.cockpitcountry.com Examples of karst features that can affect reservoir performance Collapse features • Compartmentalize reservoir • Affect deposition of overlying strata Cave collapse facies in image log Ft. Worth Basin, Texas

5. Interpretation of Karst Features • Well data alone is insufficient for identifying the spatial extent and distribution of local karst features. • Karst features with substantial vertical relief can be readily identified using 3-D seismic. • Critical features relating to reservoir character are often subtleand not readily detected using standard 3-D seismic interpretation methods. • Multi-trace geometric seismic attributes can help!

6. Multi-Trace Geometric Seismic Attributes • Calculated using multiple input seismic traces and a small vertical analysis window • The analysis "box" moves throughout the entire data volume => attributes can be output as a 3-D volume • Provide quantitative information about lateral variations in the seismic data

7. Reference Trace Instantaneous dip = Dip with highest coherence Dips tested Multi-Trace Geometric Seismic Attributes • Coherence - A measure of the trace-to-trace similarity of the seismic waveform • Dip/azimuth - Numerical estimation of the instantaneous dip and azimuth of reflectors • Curvature– A measure of the bending of a surface (~2ndderivative of the surface)

8. Mid Continent examples - Collapse structures - Polygonal features - Oriented lineaments Central Kansas Uplift Ord. Arbuckle Mississippian Ft. Worth Basin Ord. Ellenburger

9. Collapse Features – Fort Worth Basin vertical seismic section Pennsylvanian Caddo • Collapse features are visible asdepressions on the3-D seismic profile • Collapse features extend from theEllenburger through Pennsylvanian strata ~2600 ft Collapse features Ordovician Ellenburger

10. Attribute time slices near the Ellenburger Amplitude Coherence fault N Dip/Azimuth Most Negative Curvature Collapse features W E S 3 mi

11. Collapse features line up at the intersections of negative curvature lineaments Coherence Most Negative Curvature Time = 1.2 s 1 mi

12. 1 mi 1 mi 1 mi 1.6 km 1.6 km 1.6 km Polygonal Features Ordovician ArbuckleKansas Ordovician EllenburgerFort Worth Basin Diameters ~700-900 ft Diameters ~1400-1600 ft Diameters ~1200 -3500 ft Vertical relief generally 2 ms (~15 ft) or less

13. Cockpit karst Cockpits (After Cansler and Carr, 2001) Arbuckle Polygonal Karst -- Cockpit Karst doline cone Arbuckle structure overlain with paleotopographic divides in Barton Co., KS (Cansler, 2000) Morphological map of karst area in New Guinea (Williams, 1972) Arbuckle time structure overlain by most positive curvature

14. Ellenburger polygonal karst - tectonic collapse structures Collapse feature at topographic high Faults Collapse Features Coincide with Deep Basement Faults N

15. Oriented lineaments -- Kansas Mississippian Lineament trend vs.oil/water production 0.5 mile

16. Workflow for Identification of Karst OverprintsUsing Multi-Trace Attributes Extract attributes along horizon or time slice Volumetric attributes Identify dominant karst geomorphology (e.g., polygonalkarst vs. groundwater-sapped plateaus) Predict general production performance based on type of karst overprint Horizonpicks Core and log data Separate subaerial karst from tectonic overprint Identify areas of enhanced or occluded porosity/permeability Production data Identify preferred orientations of fluid conduits vs. barriers Measure distance from oriented lineaments. Outline potential reservoir compartment boundaries(fluid barriers) Interpret features relating to structure, geomorphology, and reservoir architecture on attribute slices

17. Conclusions • Coherence, dip/azimuth, and curvature extractions are valuable for establishing seismic geomorphology • Different attributes reveal different details about karst features • A workflow utilizing multi-trace attributes, along with geologic and production information, can improve characterization of karst-modified carbonate reservoirs

18. Acknowledgements • Devon Energy • Grand Mesa Operating Company • John O. Farmer, Inc. • Murfin Drilling Company • IHS - geoPLUS Corporation • Seismic Micro-Technology, Inc. • U. S. Department of Energy • Petroleum Research Fund • State of Texas ATP • Kansas Geological Survey, University of Kansas • University of Houston