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

• Published in: Energy Exploration & Exploitation
• Main Authors: Rocha-Legorreta, Francisco, Lerche, Ian
• Format: Article in Journal/Newspaper
• Language: English
• Published: SAGE Publications 2004
• Subjects: Arctic; Alaska
• Online Access: http://dx.doi.org/10.1260/0144598042886308; https://journals.sagepub.com/doi/pdf/10.1260/0144598042886308

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 ...