2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 178-2
Presentation Time: 8:15 AM


CAMP, Erin R.1, JORDAN, Teresa E.1, HORNBACH, Matthew J.2, RICHARDS, Maria2, WHEALTON, Calvin3, SMITH, Jared3, FRONE, Zachary2, STEDINGER, Jery3, WELCKER, Kelydra4 and HE, Xiaoning4, (1)Earth and Atmospheric Sciences, Cornell University, Snee Hall, Ithaca, NY 14853-1504, (2)Roy M. Huffington Department of Earth Sciences, Southern Methodist University, PO Box 750395, Dallas, TX 75275-0395, (3)Civil and Environmental Engineering, Cornell University, Hollister Hall, Ithaca, NY 14853, (4)Chemical Engineering, West Virginia University, PO Box 6070, Morgantown, WV 26506-6070, erc85@cornell.edu

Geothermal resources are a promising source of clean and sustainable energy for heating and electricity. Currently geothermal is a small contributor to energy production in the USA, in part because of high capital costs and subsurface uncertainty. Identification and quantification of uncertainty during exploration reduces risk and enables efficient use of time and resources. The petroleum industry employs Play Fairway Analysis (PFA) as an exploration strategy to minimize geological risk. To assess the applicability of PFA in low-temperature (30-100ºC) geothermal resource exploration, we applied the technique to the Appalachian Basin of NY, PA and WV. Steps included characterizing and mapping the region’s thermal quality, natural reservoir potential, seismic risk, and proximity of demand for hot fluids, along with the associated uncertainty for each factor.

Assessing the three-dimensional distribution and quality of natural reservoirs for circulation of fluids and heat extraction was a major task. Methods were developed for basin-scale reservoir identification and favorability analysis using data generated by the oil and gas industry. Data integration required resolution of inconsistent data quality among different fields and formations, as well as across state boundaries. Reservoir favorability was calculated using a Monte Carlo Simulation (MCS) on a productivity metric incorporating reservoir permeability, thickness, depth, and area. Uncertainty for each reservoir was classified by the source and quality of the original data. Results indicate that the majority of known natural reservoirs exhibit low favorability due to low permeability. The most favorable formations include the Black River Limestone, Onondaga Limestone, Lockport Dolomite, and the Newburg Sandstone, distributed along the Southern Tier of NY, western PA, and southwestern WV. More locations may be suitable for heat extraction if stimulation options are considered. Because the data are biased toward intervals bearing hydrocarbons, future analyses and geological extrapolation may point to additional stratigraphic and naturally fractured reservoirs.

Authors also include Jefferson Tester (Cornell University), Brian Anderson (West Virginia University) and Cathy Chickering Pace (Southern Methodist University).

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