Oil and Gas Estimates for Arctic National Wildlife Refuge Area 1002,Alaska

Abstract

With minimal information from 5 seismic lines, and 7 projected pseudo-wells from the Arctic National Wildlife Refuge (ANWR) Area 1002 (undeformed area Brookian Sequence), Alaska, USA, state of the art basin modeling software was used to provide quantitative 1D and 2D patterns of the basin evolution in terms of burial history, hydrocarbon generation, migration and accumulation. With the available geological information a stratigraphic profile was constructed containing 10 layers representing different depths and formation ages. From the burial history analyses of the 7 pseudo-wells, forecasts were created at different spatial-temporal slices of cross-sections and contour maps for different variables, including TTI, kerogen fraction type II, fluid flow velocity, overpressure, and oil and gas available charges. This paper illustrates how a sensitivity analysis study provides information about which geological parameters involved in the system are causing the major contributions. Relative importance, relative contribution and relative sensitivity are examined to illustrate when individual parameters need to have their ranges of uncertainty narrowed in order to reduce the range of uncertainty of particular outputs. The Monte Carlo simulation procedures using Crystal Ball® as an interface for risk analysis are fast, taking on average 10 minutes on a laptop computer to perform 1000 iterations with 236 uncertain variables. Different groups of runs were performed individually, as well as combinations of different variables according to the module in use (geohistory, thermal history, geochemistry, fluid flow, and oil and gas generation, migration and accumulation) for uniform stochastic distributions in order to identify which groups of variables were causing the largest uncertainties to hydrocarbon charge estimates. Results indicate about 2.3 Bbbl as the maximum oil available charge. The ranges of uncertainty for different parameters were modified from their nominal values (for instance: the uncertainty in the oil fraction produced by Type II kerogen was modified from 50% to 25%; the geothermal gradient uncertainty at 23.8 MyBP was modified from 50% to 30%; migration loss uncertainty for formations deposited approximately 33 to 49 MyBP was reduced from 50% to 25%; and the uncertainty on the amount of kerogen type II for the same layers was lowered from 50% to 25%) emphasizing that the maximum contributions to the uncertainty for oil accumulation estimates were for kerogen type II (about 13% contribution) and the oil fraction produced from kerogen type II (12% contribution) for formations currently between 3.4 and 4.6 km depth and deposited approximately 33 to 49 MyBP. Just these two major contributors provide about 25% of the total uncertainty for available oil charge. For gas the maximum charge available reached was about 46 Bm³. Lowering the uncertainty of parameters (such as the oil fraction produced from type II kerogen from 50% to 25%, the geothermal gradient uncertainty at 33 MyBP from 50% to 30%, the geothermal gradient uncertainty at 28.5 MyBP from 50% to 30%, and the uncertainty on the kerogen type II amount at layer 10 from 50% to 20%) allowed one to determine that the major contributors to the uncertainty were from the uncertainty of the oil fraction produced by type II kerogen (about 12%) and from the uncertainty on the fraction of type II kerogen (11%), occurring in formations currently between 5 and 5.1 km depth and deposited between approximately 71 and 112 MyBP. The total uncertainty for gas charge available from these two major contributors sums to about 23%. The ranges in estimates of oil and gas charges available today are in contrast with previous assessments due to the inclusion of the influence of dynamic range uncertainties for the parameters.

References

Bagirov

, and Lerche

, 1997, Risk and Uncertainty Assessment of Basin Modeling Results Proceedings International Math. Geology Congress, Barcelona, 22–27 Sept. 1997, pp. 573–578, Part 2, 1997.

Beardsmore

G.R.

, and Cull

J.P.

, 2001, Crustal Heat Flow. A Guide to Measurement and Modelling, Cambridge University Press, Cambridge, 324 p.

Bird

K.J.

, 1999, Geographic and Geologic Setting, in The Oil and Gas Resource Potential of the 1002 Area, Arctic National Wildlife Refuge, Alaska, by ANWR Assessment Team, U. S. Geological Survey Open File Report 98–34.

Bird

K.J.

, and Molenaar

C.M.

, 1987, Stratigraphy of the northern part of the Arctic National Wildlife Refuge, northeastern Alaska. In: Bird

K.J.

Magoon

L.B.

, (Eds.), Petroleum geology of the northern part of the Arctic National Wildlife Refuge, northeastern Alaska. U.S. Geological Survey Bulletin 1778, pp. 37–59.

Cole

Bird

Mull

Wallace

Sassi

Murphy

, and Lee

, 1999, A Balanced Cross Section and Kinematics and Thermal Model Across the Northeastern Brooks Range Mountain Front, Arctic National Wildlife Refuge, Alaska, in The Oil and Gas Resource Potential of the 1002 Area, Arctic National Wildlife Refuge, Alaska, by ANWR Assessment Team, U. S. Geological Survey Open File Report 98–34.

Com

M. L.

Gelts

, and Baldwin

, 2001, The National Council for Science and the Environment. CRS Issue Brief for Congress – IB 10073: The Arctic National Wildlife Refuge: The Next Chapter. URL: http://www.cnie.org/nle/nrgen-23.html.

Frakes

L.A.

Francis

J.E.

, and Syktus

J.I.

, 1992, Climate Modes of the Phanerozoic, Cambridge University Press, Cambridge, 274 p.

Hayba

D. O.

Houseknecht

D.W.

, and Rowan

, 1999, Stratigraphic, Hydrogeologic, and Thermal Evolution of the Canning River Region, North Slope, Alaska. in The Oil and Gas Resource Potential of the 1002 Area, Arctic National Wildlife Refuge, Alaska, by ANWR Assessment Team, U. S. Geological Survey Open File Report 98–34.

Houseknecht

D. W.

, and Schenk

C. J.

, 1998, Chapter PI Topset Play, in The Oil and Gas Resource Potential of the 1002 Area, Arctic National Wildlife Refuge, Alaska, by ANWR Assessment Team, U. S. Geological Survey Open File Report 98–34.

10.

Jaeger

J.C.

, and Cook

N.G.W.

, 1976, Fundamentals of Rock Mechanics, Chapman & Hall, London, 372 p.

11.

Lerche

, 1990 Basin Analysis: Quantitative Methods, Vol. 1, Academic Press, Orlando, 562 p.

12.

Lerche

, and Rocha-Legorreta

, 2003, Risking Basin Analysis Results, Energy Explor. & Exploitation 21, 81–164.

13.

MacKenzie

J.J.

2001, Facing the United States oil supply problem: Would opening up the Arctic National Wildlife Refuge (ANWR) Costal Plain really make a difference? World Resources Institute URL: http://www.wri.org/climate/anwr.html.

14.

, 1990, Balanced Cross-Section, Bathtub Syncline to Beaufort Sea Through Niguanak Structural High, Arctic National Wildlife Refuge (ANWR), Northeastern Alaska in The Oil and Gas Resource Potential of the 1002 Area, Arctic National Wildlife Refuge, Alaska, by ANWR Assessment Team, U. S. Geological Survey Open File Report 98–34.

15.

Nelson

P.H.

, 1999, Petrophysical properties, in The Oil and Gas Resource Potential of the 1002 Area, Arctic National Wildlife Refuge, Alaska, by ANWR Assessment Team, U. S. Geological Survey Open File Report 98–34.

16.

Poag

, 1999, Chapter BI Biostratigraphic Framework, in The Oil and Gas Resource Potential of the 1002 Area, Arctic National Wildlife Refuge, Alaska, by ANWR Assessment Team, U. S. Geological Survey Open File Report 98–34.

17.

Powell

S.G.

, 1991, A Risk Analysis of Oil Development in the Arctic National Wildlife Refuge. The Energy Journal 72, 55–76.

18.

Thomsen

R.O.

, and Lerche

, 1997, Relative Contributions to Uncertainties in Reserve Estimates, Marine Petrol. Geol. 14, 65–74, 1997.

19.

USGS, 1998, The Oil and Gas Resource Potential of the Arctic National Wildlife Refuge 1002 Area, Alaska Open File Report 98–34.

20.

Waples

D.W.

, 1989, Maturity Modeling of Sedimentary Basins: Approaches, Limitations and Prediction of Future Developments, In: Quantitative Dynamic Stratigraphy (ed. Cross

T. A.

), Prentice Hall, Englewood Cliffs, pp. 181–193.

21.

Warren

J.E.

, 1978, The Evaluation of Oil and Gas Plays, SPE 17554.

22.

, 1992, Quantitative Basin Modeling: An Application in the Arctic National Wildlife Refuge of Alaska, and Salt Influences on Thermal Anomalies and Fracturing patterns of Sediments in Gulf of Mexico, Ph.D. dissertation, University of South Carolina, 161 p.