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Spatial Stochastic Modeling of Sedimentary Formations to Assess CO2 Storage Potential: A Case Study for the Pennsylvania Part of the Appalachian Basin

Popova, Olga H.; Small, Mitchell J.; Thomas, Andrew C.; McCoy, Sean; Karimi, Bobak; Rose, Stephen

CO2 capture and sequestration is an emerging technology for reducing greenhouse gas emissions to the atmosphere and reducing our impact to the climate system. The Appalachian Basin couples a high demand region with significant potential for storage capacity. Currently, there is a need to make more refined estimates of the distribution of storage resources and begin to identify viable storage capacity in the Appalachian basin.

Assessments of carbon sequestration resources that have been made for North America using existing methodologies likely underestimate uncertainty and variability in the reservoir parameters. The goals of this study are: 1) build a regional geomodel for the Low Devonian Oriskany formation of the Appalachian Basin 2) develop a spatial stochastic tool to construct a detailed geostatistical formation model, which accounts for spatial parameter distribution 3) use the geomodel and spatial stochastic approach to probabilistically quantify the storage resource for the Pennsylvania part of the Oriskany formation, and 4) reduce uncertainty in estimates.

The regional Oriskany geomodel is built using depth to top and thickness from 2162 development wells, neutron porosity logs from 148 wells, and temperature and pressure measurements from 3149 and 1486 wells respectively. The detailed Oriskany model is developed using Sequential Gaussian Simulation of the depth, thickness, porosity, temperature, and pressure interpolation, implemented in mGstat Matlab application.

The detailed Oriskany model integrates existing geologic and engineering data with spatial stochastic approach. This model helps to understand spatial variability of reservoir parameters, as well as relationship between these parameters critical to modeling sequestration resource. The results show the relative importance of the variability of input parameters on the carbon storage resource: the resource estimates can vary by factor of 4 in the presence of uncertainty and variability in formation parameters. Since a reduction in the uncertainty of the sequestration resource estimate is desired, our analysis suggests what future data collection (e.g. additional characterization wells) should be undertaken to achieve the greatest reduction, i.e. the value of information for further investigations is identified.


AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013